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1

Scanning ARM Cloud Radar Handbook  

SciTech Connect (OSTI)

The scanning ARM cloud radar (SACR) is a polarimetric Doppler radar consisting of three different radar designs based on operating frequency. These are designated as follows: (1) X-band SACR (X-SACR); (2) Ka-band SACR (Ka-SACR); and (3) W-band SACR (W-SACR). There are two SACRs on a single pedestal at each site where SACRs are deployed. The selection of the operating frequencies at each deployed site is predominantly determined by atmospheric attenuation at the site. Because RF attenuation increases with atmospheric water vapor content, ARM's Tropical Western Pacific (TWP) sites use the X-/Ka-band frequency pair. The Southern Great Plains (SGP) and North Slope of Alaska (NSA) sites field the Ka-/W-band frequency pair. One ARM Mobile Facility (AMF1) has a Ka/W-SACR and the other (AMF2) has a X/Ka-SACR.

Widener, K; Bharadwaj, N; Johnson, K

2012-06-18T23:59:59.000Z

2

W-band ARM Cloud Radar (WACR) Handbook  

SciTech Connect (OSTI)

The W-band Atmospheric Radiation Measurement (ARM) Program Cloud Radar (WACR) systems are zenith pointing Doppler radars that probe the extent and composition of clouds at 95.04 GHz. The main purpose of this radar is to determine cloud boundaries (e.g., cloud bottoms and tops). This radar reports estimates for the first three spectra moments for each range gate up to 15 km. The 0th moment is reflectivity, the 1st moment is radial velocity, and the 2nd moment is spectral width. Also available are the raw spectra files. Unlike the millimeter wavelength cloud radar (MMCR), the WACR does not use pulse coding and operates in only copolarization and cross-polarization modes.

Widener, KB; Johnson, K

2005-01-05T23:59:59.000Z

3

Scanning ARM Cloud Radars Part I: Operational Sampling Strategies  

SciTech Connect (OSTI)

Probing clouds in three-dimensions has never been done with scanning millimeter-wavelength (cloud) radars in a continuous operating environment. The acquisition of scanning cloud radars by the Atmospheric Radiation Measurement (ARM) program and research institutions around the world generate the need for developing operational scan strategies for cloud radars. Here, the first generation of sampling strategies for the Scanning ARM Cloud Radars (SACRs) is discussed. These scan strategies are designed to address the scientific objectives of the ARM program, however, they introduce an initial framework for operational scanning cloud radars. While the weather community uses scan strategies that are based on a sequence of scans at constant elevations, the SACRs scan strategies are based on a sequence of scans at constant azimuth. This is attributed to the cloud properties that are vastly different for rain and snow shafts that are the primary target of precipitation radars. A “cloud surveillance” scan strategy is introduced (HS-RHI) based on a sequence of horizon-to-horizon Range Height Indicator (RHI) scans that sample the hemispherical sky (HS). The HS-RHI scan strategy is repeated every 30 min to provide a static view of the cloud conditions around the SACR location. Between HS-RHI scan strategies other scan strategies are introduced depending on the cloud conditions. The SACRs are pointing vertically in the case of measurable precipitation at the ground. The radar reflectivities are corrected for water vapor attenuation and non-meteorological detection are removed. A hydrometeor detection mask is introduced based on the difference of cloud and noise statistics is discussed.

Kollias, Pavlos; Bharadwaj, Nitin; Widener, Kevin B.; Jo, Ieng; Johnson, Karen

2014-03-01T23:59:59.000Z

4

ARM - Field Campaign - Cloud Radar IOP  

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5

ARRA-funded Cloud Radar Development for the Department of Energy's ARM Climate Research Facility  

E-Print Network [OSTI]

ARRA-funded Cloud Radar Development for the Department of Energy's ARM Climate Research Facility assembler jobs were saved because of this large order. ProSensing is also planning to engage a local defense for similar cloud radar contracts for customers in India, China and Korea. By developing these complex radar

6

ARM - Publications: Science Team Meeting Documents: W-Band ARM Cloud Radar  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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7

ARM: X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)  

SciTech Connect (OSTI)

X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

Widener, Kevin; Nelson, Dan; Bharadwaj, Nitin; Lindenmaier, Iosif [Andrei; Johnson, Karen

2011-09-14T23:59:59.000Z

8

ARM: W-Band Scanning ARM Cloud Radar (W-SACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

W-Band Scanning ARM Cloud Radar (W-SACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

Widener, Kevin; Nelson, Dan; Bharadwaj, Nitin; Lindenmaier, Iosif [Andrei; Johnson, Karen

9

ARM: Ka-Band Scanning ARM Cloud Radar (KASACR) Hemispherical Sky RHI Scan (6 horizon-to-horizon scans at 30-degree azimuth intervals)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Ka-Band Scanning ARM Cloud Radar (KASACR) Hemispherical Sky RHI Scan (6 horizon-to-horizon scans at 30-degree azimuth intervals)

Bharadwaj, Nitin; Widener, Kevin

10

ARM: X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

Widener, Kevin; Nelson, Dan; Bharadwaj, Nitin; Lindenmaier, Iosif [Andrei; Johnson, Karen

11

Cloud Effects on Radiative Heating Rate Profiles over Darwin using ARM and A-train Radar/Lidar Observations  

SciTech Connect (OSTI)

Observations of clouds from the ground-based U.S. Department of Energy Atmospheric Radiation Measurement program (ARM) and satellite-based A-train are used to compute cloud radiative forcing profiles over the ARM Darwin, Australia site. Cloud properties are obtained from both radar (the ARM Millimeter Cloud Radar (MMCR) and the CloudSat satellite in the A-train) and lidar (the ARM Micropulse lidar (MPL) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the A-train) observations. Cloud microphysical properties are taken from combined radar and lidar retrievals for ice clouds and radar only or lidar only retrievals for liquid clouds. Large, statistically significant differences of up to 1.43 K/day exist between the mean ARM and A-train net cloud radiative forcing profiles. The majority of the difference in cloud radiative forcing profiles is shown to be due to a large difference in the cloud fraction above 12 km. Above this altitude the A-train cloud fraction is significantly larger because more clouds are detected by CALIPSO than by the ground-based MPL. It is shown that the MPL is unable to observe as many high clouds as CALIPSO due to being more frequently attenuated and a poorer sensitivity even in otherwise clear-sky conditions. After accounting for cloud fraction differences and instrument sampling differences due to viewing platform we determined that differences in cloud radiative forcing due to the retrieved ice cloud properties is relatively small. This study demonstrates that A-train observations are better suited for the calculation cloud radiative forcing profiles. In addition, we find that it is necessary to supplement CloudSat with CALIPSO observations to obtain accurate cloud radiative forcing profiles since a large portion of clouds at Darwin are detected by CALIPSO only.

Thorsen, Tyler J.; Fu, Qiang; Comstock, Jennifer M.

2013-06-11T23:59:59.000Z

12

ARM - Field Campaign - DC-8 Cloud Radar Campaign  

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13

Scanning ARM Cloud Radars Part II: Data Quality Control and Processing  

SciTech Connect (OSTI)

The Scanning ARM Cloud Radars (SACR’s) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20-30 km radius from the ARM fixed and mobile sites. Here, the post-processing of the calibrated SACR measurements is discussed. First, a feature mask algorithm that objectively determines the presence of significant radar returns is described. The feature mask algorithm is based on the statistical properties of radar receiver noise. It accounts for atmospheric emission and is applicable even for SACR profiles with few or no signal-free range gates. Using the nearest-in-time atmospheric sounding, the SACR radar reflectivities are corrected for gaseous attenuation (water vapor and oxygen) using a line-by-line absorption model. Despite having a high pulse repetition frequency, the SACR has a narrow Nyquist velocity limit and thus Doppler velocity folding is commonly observed. An unfolding algorithm that makes use of a first guess for the true Doppler velocity using horizontal wind measurements from the nearest sounding is described. The retrieval of the horizontal wind profile from the Hemispherical Sky – Range Height Indicator SACR scan observations and/or nearest sounding is described. The retrieved horizontal wind profile can be used to adaptively configure SACR scan strategies that depend on wind direction. Several remaining challenges are discussed, including the removal of insect and second-trip echoes. The described algorithms significantly enhance SACR data quality and constitute an important step towards the utilization of SACR measurements for cloud research.

Kollias, Pavlos; Jo, Ieng; Borque, Paloma; Tatarevic, Aleksandra; Lamer, Katia; Bharadwaj, Nitin; Widener, Kevin B.; Johnson, Karen; Clothiaux, Eugene E.

2014-03-01T23:59:59.000Z

14

Observing Warm Clouds in 3D Using ARM Scanning Cloud  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Observing Warm Clouds in 3D Using ARM Scanning Cloud Radars and a Novel Ensemble Method For original submission and image(s), see ARM Research Highlights http:www.arm.gov...

15

Merging Cloud and Precipitation Radar Data Provides a Better  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Merging Cloud and Precipitation Radar Data Provides a Better View of Tropical Rain Clouds For original submission and image(s), see ARM Research Highlights http:www.arm.gov...

16

Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface Radar and Satellite Data in Support of ARM SCM Activities  

SciTech Connect (OSTI)

Single-column modeling (SCM) is one of the key elements of Atmospheric Radiation Measurement (ARM) research initiatives for the development and testing of various physical parameterizations to be used in general circulation models (GCMs). The data required for use with an SCM include observed vertical profiles of temperature, water vapor, and condensed water, as well as the large-scale vertical motion and tendencies of temperature, water vapor, and condensed water due to horizontal advection. Surface-based measurements operated at ARM sites and upper-air sounding networks supply most of the required variables for model inputs, but do not provide the horizontal advection term of condensed water. Since surface cloud radar and microwave radiometer observations at ARM sites are single-point measurements, they can provide the amount of condensed water at the location of observation sites, but not a horizontal distribution of condensed water contents. Consequently, observational data for the large-scale advection tendencies of condensed water have not been available to the ARM cloud modeling community based on surface observations alone. This lack of advection data of water condensate could cause large uncertainties in SCM simulations. Additionally, to evaluate GCMsâ�� cloud physical parameterization, we need to compare GCM results with observed cloud water amounts over a scale that is large enough to be comparable to what a GCM grid represents. To this end, the point-measurements at ARM surface sites are again not adequate. Therefore, cloud water observations over a large area are needed. The main goal of this project is to retrieve ice water contents over an area of 10 x 10 deg. surrounding the ARM sites by combining surface and satellite observations. Built on the progress made during previous ARM research, we have conducted the retrievals of 3-dimensional ice water content by combining surface radar/radiometer and satellite measurements, and have produced 3-D cloud ice water contents in support of cloud modeling activities. The approach of the study is to expand a (surface) point measurement to an (satellite) area measurement. That is, the study takes the advantage of the high quality cloud measurements (particularly cloud radar and microwave radiometer measurements) at the point of the ARM sites. We use the cloud ice water characteristics derived from the point measurement to guide/constrain a satellite retrieval algorithm, then use the satellite algorithm to derive the 3-D cloud ice water distributions within an 10�° (latitude) x 10�° (longitude) area. During the research period, we have developed, validated and improved our cloud ice water retrievals, and have produced and archived at ARM website as a PI-product of the 3-D cloud ice water contents using combined satellite high-frequency microwave and surface radar observations for SGP March 2000 IOP and TWP-ICE 2006 IOP over 10 deg. x 10 deg. area centered at ARM SGP central facility and Darwin sites. We have also worked on validation of the 3-D ice water product by CloudSat data, synergy with visible/infrared cloud ice water retrievals for better results at low ice water conditions, and created a long-term (several years) of ice water climatology in 10 x 10 deg. area of ARM SGP and TWP sites and then compared it with GCMs.

Liu, Guosheng

2013-03-15T23:59:59.000Z

17

Ka-Band ARM Zenith Radar (KAZR) Instrument Handbook  

SciTech Connect (OSTI)

The Ka-band ARM zenith radar (KAZR) is a zenith-pointing Doppler cloud radar operating at approximately 35 GHz. The KAZR is an evolutionary follow-on radar to ARM's widely successful millimeter-wavelength cloud radar (MMCR). The main purpose of the KAZR is to provide vertical profiles of clouds by measuring the first three Doppler moments: reflectivity, radial Doppler velocity, and spectra width. At the sites where the dual-polarization measurements are made, the Doppler moments for the cross-polarization channel are also available. In addition to the moments, velocity spectra are also continuously recorded for each range gate.

Widener, K; Bharadwaj, N; Johnson, K

2012-03-06T23:59:59.000Z

18

ARM Climate Research Facility Radar Operations Plan  

SciTech Connect (OSTI)

Roles, responsibilities, and processes associated with Atmospheric Radiation Measurement (ARM) Radar Operations.

Voyles, JW

2012-05-18T23:59:59.000Z

19

ARM: Millimeter Wave Cloud Radar (MMCR), replaces mmcrcal and mmcrmoments datastreams following C-40 processor upgrade of 2003.09.09  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Millimeter Wave Cloud Radar (MMCR), replaces mmcrcal and mmcrmoments datastreams following C-40 processor upgrade of 2003.09.09

Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen

20

Science Goals for the ARM Recovery Act Radars  

SciTech Connect (OSTI)

Science Goals for the ARM Recovery Act Radars. In October 2008, an ARM workshop brought together approximately 30 climate research scientists to discuss the Atmospheric Radiation Measurement (ARM) Climate Research Facility's role in solving outstanding climate science issues. Through this discussion it was noted that one of ARM's primary contributions is to provide detailed information about cloud profiles and their impact on radiative fluxes. This work supports cloud parameterization development and improved understanding of cloud processes necessary for that development. A critical part of this work is measuring microphysical properties (cloud ice and liquid water content, cloud particle sizes, shapes, and distribution). ARM measurements and research have long included an emphasis on obtaining the best possible microphysical parameters with the available instrumentation. At the time of the workshop, this research was reaching the point where additional reduction in uncertainties in these critical parameters required new instrumentation for applications such as specifying radiative heating profiles, measuring vertical velocities, and studying the convective triggering and evolution of three-dimensional (3D) cloud fields. ARM was already operating a subset of the necessary instrumentation to make some progress on these problems; each of the ARM sites included (and still includes) a cloud radar (operating at 35 or 94 GHz), a cloud lidar, and balloon-borne temperature and humidity sensors. However, these measurements were inadequate for determining detailed microphysical properties in most cases. Additional instrumentation needed to improve retrievals of microphysical processes includes radars at two additional frequencies for a total of three at a single site (35 GHz, 94 GHz, and a precipitation radar) and a Doppler lidar. Evolving to a multi-frequency scanning radar is a medium-term goal to bridge our understanding of two-dimensional (2D) retrievals to the 3D cloud field. These additional microphysical measurements would allow detailed cloud properties to be derived even in the presence of light precipitation. It is important to couple these detailed measurements of cloud microphysics to vertical motion on the cloud scale to couple microphysics with meteorological processes. Vertically pointing Doppler radars provide the vertical motion of cloud particles but, to separate particle motion from air motion, a wind profiler is required. The American Recovery and Reinvestment Act provided the means to address these needs and implement a multi-frequency suite of radars, including scanning radars, at each of the ARM sites. In addition, Doppler lidars have been deployed at several sites. With these new measurement capabilities, ARM has the measurement capabilities to tackle the problems of improving microphysical profile descriptions and evaluating the relationship between our current narrow-field-of view, zenith perspective on clouds to a description of the full 3D cloud field and its temporal evolution.

JH Mather

2012-05-29T23:59:59.000Z

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

ARM Scanning Radar  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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22

ARM - Measurement - Radar Doppler  

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23

ARM - Measurement - Radar polarization  

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24

ARM - Measurement - Radar reflectivity  

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25

Millimeter Wave Cloud Radar (MMCR) Handbook  

SciTech Connect (OSTI)

The millimeter cloud radar (MMCR) systems probe the extent and composition of clouds at millimeter wavelengths. The MMCR is a zenith-pointing radar that operates at a frequency of 35 GHz. The main purpose of this radar is to determine cloud boundaries (e.g., cloud bottoms and tops). This radar will also report radar reflectivity (dBZ) of the atmosphere up to 20 km. The radar possesses a doppler capability that will allow the measurement of cloud constituent vertical velocities.

KB Widener; K Johnson

2005-01-30T23:59:59.000Z

26

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, S-band Radar (williams-s_band)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher

27

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, S-band Radar (williams-s_band)  

SciTech Connect (OSTI)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher

2012-11-06T23:59:59.000Z

28

ARM - Measurement - Cloud size  

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29

ARM - Measurement - Cloud extinction  

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30

ARM - Measurement - Cloud fraction  

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31

ARM - Measurement - Cloud location  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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32

ARM - Measurement - Cloud phase  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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33

ARM - Measurement - Cloud type  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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34

ARM - Field Campaign - Cloud IOP  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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35

ARM - Cloud and Rain  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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36

NNSA Completes its Critical Radar Arming and Fuzing Test for...  

National Nuclear Security Administration (NNSA)

its Critical Radar Arming and Fuzing Test for the W88 ALT 370 | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission Managing the Stockpile...

37

ARM - Field Campaign - NSA Scanning Radar IOP  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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38

1498 JOURNAL OF ,\\TMOSPHERIC AND OCEANIC TECHNOLOGY VULIIME 25 A Techniqne for the Automatic Detection of Insect Clutter in Cloud Radar Returns  

E-Print Network [OSTI]

Radiation Measurement (ARM) Program operales 35- GHz millimclcr·w:lvclenglh cloud radars (MMCRs) in several levels in scan- ning weather radar applications (e.g., Vaughn 1985; Achtemeier 199]; Wilson el al. 1994 Detection of Insect Clutter in Cloud Radar Returns EDWARD P. LUKE, PAVLOS KOLLlAS, AND KAREN L. JOHNSON Aml

39

Cloud radar Doppler spectra in drizzling stratiform clouds: 2. Observations and microphysical modeling of drizzle evolution  

E-Print Network [OSTI]

Cloud radar Doppler spectra in drizzling stratiform clouds: 2. Observations and microphysical I, the influence of cloud microphysics and dynamics on the shape of cloud radar Doppler spectra in warm stratiform clouds was discussed. The traditional analysis of radar Doppler moments was extended

40

ARM Cloud Retrieval Ensemble Data Set (ACRED)  

SciTech Connect (OSTI)

This document describes a new Atmospheric Radiation Measurement (ARM) data set, the ARM Cloud Retrieval Ensemble Data Set (ACRED), which is created by assembling nine existing ground-based cloud retrievals of ARM measurements from different cloud retrieval algorithms. The current version of ACRED includes an hourly average of nine ground-based retrievals with vertical resolution of 45 m for 512 layers. The techniques used for the nine cloud retrievals are briefly described in this document. This document also outlines the ACRED data availability, variables, and the nine retrieval products. Technical details about the generation of ACRED, such as the methods used for time average and vertical re-grid, are also provided.

Zhao, C; Xie, S; Klein, SA; McCoy, R; Comstock, JM; Delanoë, J; Deng, M; Dunn, M; Hogan, RJ; Jensen, MP; Mace, GG; McFarlane, SA; O’Connor, EJ; Protat, A; Shupe, MD; Turner, D; Wang, Z

2011-09-12T23:59:59.000Z

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

ARM - Measurement - Cloud ice particle  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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42

ARM - Measurement - Cloud top height  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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43

X-band Scanning ARM Precipitation Radar (X-SAPR) Instrument Handbook  

SciTech Connect (OSTI)

The X-band scanning ARM cloud radar (X-SAPR) is a full-hemispherical scanning polarimetric Doppler radar transmitting simultaneously in both H and V polarizations. With a 200 kW magnetron transmitter, this puts 100 kW of transmitted power for each polarization. The receiver for the X-SAPR is a Vaisala Sigmet RVP-900 operating in a coherent-on-receive mode. Three X-SAPRs are deployed around the Southern Great Plains (SGP) Central Facility in a triangular array. A fourth X-SAPR is deployed near Barrow, Alaska on top of the Barrow Arctic Research Center.

Widener, K; Bharadwaj, N

2012-10-29T23:59:59.000Z

44

ARM - Evaluation Product - ARM Cloud Retrieval Ensemble Data  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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45

ARM - Measurement - Cloud droplet size  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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46

ARM - Measurement - Cloud effective radius  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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47

ARM - Measurement - Cloud optical depth  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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48

ARM - Measurement - Total cloud water  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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49

Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing applications  

E-Print Network [OSTI]

Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing broadening and drizzle growth in shallow liquid clouds remain not well understood. Detailed, cloudscale. Profiling, millimeterwavelength (cloud) radars can provide such observations. In particular, the first three

50

ARM Cloud Properties Working Group: Meeting Logistics  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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51

ARM - Lesson Plans: Making Clouds  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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52

MAGIC: Marine ARM GPCI Investigation of Clouds  

SciTech Connect (OSTI)

The second Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF2) will be deployed aboard the Horizon Lines cargo container ship merchant vessel (M/V) Spirit for MAGIC, the Marine ARM GPCI1 Investigation of Clouds. The Spirit will traverse the route between Los Angeles, California, and Honolulu, Hawaii, from October 2012 through September 2013 (except for a few months in the middle of this time period when the ship will be in dry dock). During this field campaign, AMF2 will observe and characterize the properties of clouds and precipitation, aerosols, and atmospheric radiation; standard meteorological and oceanographic variables; and atmospheric structure. There will also be two intensive observational periods (IOPs), one in January 2013 and one in July 2013, during which more detailed measurements of the atmospheric structure will be made.

Lewis, ER; Wiscombe, WJ; Albrecht, BA; Bland, GL; Flagg, CN; Klein, SA; Kollias, P; Mace, G; Reynolds, RM; Schwartz, SE; Siebesma, AP; Teixeira, J; Wood, R; Zhang, M

2012-10-03T23:59:59.000Z

53

ARM Installs Aircraft Detection Radar System  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust Documentation DataProductswsicloudwsicloudsummarygifAOS3 ARM93 ARM DataARM

54

ARM - Midlatitude Continental Convective Clouds  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

55

ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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56

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery Browse DataCloud

57

Comparison of POLDER Apparent and Corrected Oxygen Pressure to ARM/MMCR Cloud Boundary Pressures  

SciTech Connect (OSTI)

POLDER (POLarization and Directionality of the Earth’s Reflectances) cloud oxygen pressures are compared to cloud boundary pressures obtained from the combination of Lidar and Millimeter Wave Cloud Radar ground measurements located at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. Without ground reflection correction, the apparent pressures are found to be closer to the mean cloud pressure than to the cloud top pressure. Nevertheless, for almost a quarter of our comparison cases the apparent pressure level is found to be below the cloud base level. This problem practically disappears applying a simple correction for the surface reflection effect. The corrected oxygen pressures are then found to be very close (12 hPa on average) to the mean cloud pressure.

Vanbauce, Claudine; Cadet, Bertrand; Marchand, Roger T.

2003-03-06T23:59:59.000Z

58

Prospects of the WSR-88D Radar for Cloud Studies  

E-Print Network [OSTI]

Sounding of nonprecipitating clouds with the 10-cm wavelength Weather Surveillance Radar-1988 Doppler (WSR-88D) is discussed. Readily available enhancements to signal processing and volume coverage patterns of the WSR-88D allow observations of a...

Melnikov, Valery M.; Zrni?, Dusan S.; Doviak, Richard J.; Chilson, Phillip B.; Mechem, David B.; Kogan, Yefim L.

2011-04-01T23:59:59.000Z

59

A Climatology of Surface Cloud Radiative Effects at the ARM Tropical Western Pacific Sites  

SciTech Connect (OSTI)

Cloud radiative effects on surface downwelling fluxes are investigated using long-term datasets from the three Atmospheric Radiation Measurement (ARM) sites in the Tropical Western Pacific (TWP) region. The Nauru and Darwin sites show significant variability in sky cover, downwelling radiative fluxes, and surface cloud radiative effect (CRE) due to El Nińo and the Australian monsoon, respectively, while the Manus site shows little intra-seasonal or interannual variability. Cloud radar measurement of cloud base and top heights are used to define cloud types so that the effect of cloud type on the surface CRE can be examined. Clouds with low bases contribute 71-75% of the surface shortwave (SW) CRE and 66-74% of the surface longwave (LW) CRE at the three TWP sites, while clouds with mid-level bases contribute 8-9% of the SW CRE and 12-14% of the LW CRE, and clouds with high bases contribute 16-19% of the SW CRE and 15-21% of the LW CRE.

McFarlane, Sally A.; Long, Charles N.; Flaherty, Julia E.

2013-04-01T23:59:59.000Z

60

Climatology and Formation of Tropical Midlevel Clouds at the Darwin ARM Site  

SciTech Connect (OSTI)

A 4-yr climatology of midlevel clouds is presented from vertically pointing cloud lidar and radar measurements at the Atmospheric Radiation Measurement Program (ARM) site at Darwin, Australia. Few studies exist of tropical midlevel clouds using a dataset of this length. Seventy percent of clouds with top heights between 4 and 8 km are less than 2 km thick. These thin layer clouds have a peak in cloud-top temperature around the melting level (0°C) and also a second peak around -12.5°C. The diurnal frequency of thin clouds is highest during the night and reaches a minimum around noon, consistent with variation caused by solar heating. Using a 1.5-yr subset of the observations, the authors found that thin clouds have a high probability of containing supercooled liquid water at low temperatures: ~20% of clouds at -30°C, ~50% of clouds at -20°C, and ~65% of clouds at -10°C contain supercooled liquid water. The authors hypothesize that thin midlevel clouds formed at the melting level are formed differently during active and break monsoon periods and test this over three monsoon seasons. A greater frequency of thin midlevel clouds are likely formed by increased condensation following the latent cooling of melting during active monsoon periods when stratiform precipitation is most frequent. This is supported by the high percentage (65%) of midlevel clouds with preceding stratiform precipitation and the high frequency of stable layers slightly warmer than 0°C. In the break monsoon, a distinct peak in the frequency of stable layers at 0°C matches the peak in thin midlevel cloudiness, consistent with detrainment from convection.

Riihimaki, Laura D.; McFarlane, Sally A.; Comstock, Jennifer M.

2012-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Analysis of cloud layer structure in Shouxian, China using RS92 radiosonde aided by 95 GHz cloud radar  

E-Print Network [OSTI]

Analysis of cloud layer structure in Shouxian, China using RS92 radiosonde aided by 95 GHz cloud to analyze cloud vertical structure over this area by taking advantage of the first direct measurements of cloud vertical layers from the 95 GHz radar. Singlelayer, twolayer, and threelayer clouds account for 28

Li, Zhanqing

62

Ice Concentration Retrieval in Stratiform Mixed-phase Clouds Using Cloud Radar Reflectivity Measurements and 1D Ice Growth Model Simulations  

SciTech Connect (OSTI)

Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculated from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.

Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.; Fan, Jiwen; Luo, Tao

2014-10-01T23:59:59.000Z

63

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery Browse Data Related

64

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery Browse Data

65

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery Browse

66

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery BrowseMeasuring the

67

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery BrowseMeasuring

68

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery BrowseMeasuringSunshine

69

An annual cycle of Arctic cloud characteristics observed by radar and lidar at SHEBA  

E-Print Network [OSTI]

distribution of cloud boundary heights, and occurrence of liquid phase in clouds are determined from radar-observed clouds containing liquid was 73% for the year. The least amount of liquid water phase was observed during-detected clouds. Liquid was distributed in a combination of all-liquid and mixed phase clouds, and was detected

Shupe, Matthew

70

ARM - Field Campaign - Boundary Layer Cloud IOP  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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71

An Assessment of MultiAngle Imaging SpectroRadiometer (MISR) Stereo-Derived Cloud Top Heights and cloud top winds using ground-based radar, lidar, and microwave radiometers  

SciTech Connect (OSTI)

Clouds are of tremendous importance to climate because of their direct radiative effects and because of their role in atmospheric dynamics and the hydrological cycle. The value of satellite imagery in monitoring cloud properties on a global basis can hardly be understated. One cloud property that satellites are in an advantageous position to monitor is cloud top height. Cloud top height retrievals are especially important for MISR because the derived height field is used to co-register the measured radiances. In this presentation we show the results of an ongoing comparison between ground-based millimeter-wave cloud radar and lidar measurements of cloud top and MISR stereo-derived cloud top height. This comparison is based on data from three radar systems located in the U.S Southern Great Plains (Lamont, Oklahoma), the Tropical Western Pacific (Nauru Island) and the North Slope of Alaska (Barrow, Alaska). These radars are operated as part of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program. The MISR stereo height algorithm is performing largely as expected for most optically thick clouds. As with many satellite retrievals, the stereo-height retrieval has difficulty with optically thin clouds or ice clouds with little optical contrast near cloud top.

Marchand, Roger T.; Ackerman, Thomas P.; Moroney, C.

2007-03-17T23:59:59.000Z

72

ARM - Measurement - Cloud particle number concentration  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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73

ARM - Measurement - Cloud particle size distribution  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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74

Assessment of the Performance of the Chilbolton 3-GHz Advanced Meteorological Radar for Cloud-Top-Height Retrieval  

E-Print Network [OSTI]

. The potential for this radar to make useful measurements of low-altitude liquid water cloud structure is investigated. To assess the cloud-height assignment capabilities of the 3-GHz radar, low-level cloudAssessment of the Performance of the Chilbolton 3-GHz Advanced Meteorological Radar for Cloud

75

The Status of the ACRF Millimeter Wave Cloud Radars (MMCRs), the Path Forward for Future MMCR Upgrades, the Concept of 3D Volume Imaging Radar and the UAV Radar  

SciTech Connect (OSTI)

The United States (U.S.) Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) operates millimeter wavelength cloud radars (MMCRs) in several climatological regimes. The MMCRs, are the primary observing tool for quantifying the properties of nearly all radiatively important clouds over the ACRF sites. The first MMCR was installed at the ACRF Southern Great Plains (SGP) site nine years ago and its original design can be traced to the early 90s. Since then, several MMCRs have been deployed at the ACRF sites, while no significant hardware upgrades have been performed. Recently, a two-stage upgrade (first C-40 Digital Signal Processors [DSP]-based, and later the PC-Integrated Radar AcQuisition System [PIRAQ-III] digital receiver) of the MMCR signal-processing units was completed. Our future MMCR related goals are: 1) to have a cloud radar system that continues to have high reliability and uptime and 2) to suggest potential improvements that will address increased sensitivity needs, superior sampling and low cost maintenance of the MMCRs. The Traveling Wave Tube (TWT) technology, the frequency (35-GHz), the radio frequency (RF) layout, antenna, the calibration and radar control procedure and the environmental enclosure of the MMCR remain assets for our ability to detect the profile of hydrometeors at all heights in the troposphere at the ACRF sites.

P Kollias; MA Miller; KB Widener; RT Marchand; TP Ackerman

2005-12-30T23:59:59.000Z

76

ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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77

ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3,Cloud OD Sensor TWST Cloud OD Sensor TWST ARM DataExtended

78

ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3,Cloud OD Sensor TWST Cloud OD Sensor TWST ARM

79

ARM - Field Campaign - FIRE-Arctic Cloud Experiment/SHEBA  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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80

ARM - Evaluation Product - Cloud Classification VAP  

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Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

ARM - Field Campaign - Fall 1997 Cloud IOP  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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82

Evaluating cloud retrieval algorithms with the ARM BBHRP framework  

SciTech Connect (OSTI)

Climate and weather prediction models require accurate calculations of vertical profiles of radiative heating. Although heating rate calculations cannot be directly validated due to the lack of corresponding observations, surface and top-of-atmosphere measurements can indirectly establish the quality of computed heating rates through validation of the calculated irradiances at the atmospheric boundaries. The ARM Broadband Heating Rate Profile (BBHRP) project, a collaboration of all the working groups in the program, was designed with these heating rate validations as a key objective. Given the large dependence of radiative heating rates on cloud properties, a critical component of BBHRP radiative closure analyses has been the evaluation of cloud microphysical retrieval algorithms. This evaluation is an important step in establishing the necessary confidence in the continuous profiles of computed radiative heating rates produced by BBHRP at the ARM Climate Research Facility (ACRF) sites that are needed for modeling studies. This poster details the continued effort to evaluate cloud property retrieval algorithms within the BBHRP framework, a key focus of the project this year. A requirement for the computation of accurate heating rate profiles is a robust cloud microphysical product that captures the occurrence, height, and phase of clouds above each ACRF site. Various approaches to retrieve the microphysical properties of liquid, ice, and mixed-phase clouds have been processed in BBHRP for the ACRF Southern Great Plains (SGP) and the North Slope of Alaska (NSA) sites. These retrieval methods span a range of assumptions concerning the parameterization of cloud location, particle density, size, shape, and involve different measurement sources. We will present the radiative closure results from several different retrieval approaches for the SGP site, including those from Microbase, the current 'reference' retrieval approach in BBHRP. At the NSA, mixed-phase clouds and cloud with a low optical depth are prevalent; the radiative closure studies using Microbase demonstrated significant residuals. As an alternative to Microbase at NSA, the Shupe-Turner cloud property retrieval algorithm, aimed at improving the partitioning of cloud phase and incorporating more constrained, conditional microphysics retrievals, also has been evaluated using the BBHRP data set.

Mlawer,E.; Dunn,M.; Mlawer, E.; Shippert, T.; Troyan, D.; Johnson, K. L.; Miller, M. A.; Delamere, J.; Turner, D. D.; Jensen, M. P.; Flynn, C.; Shupe, M.; Comstock, J.; Long, C. N.; Clough, S. T.; Sivaraman, C.; Khaiyer, M.; Xie, S.; Rutan, D.; Minnis, P.

2008-03-10T23:59:59.000Z

83

STUDY OF CLOUD LIFETIME EFFECTS USING THE SGP HETEROGENEOUS DISTRIBUTED RADAR NETWORK: PRELIMINARY CONSIDERATIONS  

E-Print Network [OSTI]

STUDY OF CLOUD LIFETIME EFFECTS USING THE SGP HETEROGENEOUS DISTRIBUTED RADAR NETWORK: PRELIMINARY-dimensional morphology and life cycle of clouds. Detailing key cloud processes as they transit from the formation stage to precipitation onset and cloud dissipation is critical towards establishing uncertainties in climate models

84

Polarimetric Radar Observation Operator for a Cloud Model with Spectral Microphysics  

E-Print Network [OSTI]

-proven advantages such as hydro- meteor classification and improvement in radar data quality and rainfall modeling via improvement of micro- physical parameterization and direct assimilation of polarimetric radar the output of numerical cloud models was pioneered using the models with bulk parameterization of cloud micro

Mark, Pinsky

85

A Comparison of Simulated Cloud Radar Output from the Multiscale Modeling Framework Global Climate Model with CloudSat Cloud Radar Observations  

SciTech Connect (OSTI)

Over the last few years a new type of global climate model (GCM) has emerged in which a cloud-resolving model is embedded into each grid cell of a GCM. This new approach is frequently called a multiscale modeling framework (MMF) or superparameterization. In this article we present a comparison of MMF output with radar observations from the NASA CloudSat mission, which uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. We account for radar detection limits by simulating the 94 GHz radar reflectivity that CloudSat would observe from the high-resolution cloud-resolving model output produced by the MMF. Overall, the MMF does a good job of reproducing the broad pattern of tropical convergence zones, subtropical belts, and midlatitude storm tracks, as well as their changes in position with the annual solar cycle. Nonetheless, the comparison also reveals a number of model shortfalls including (1) excessive hydrometeor coverage at all altitudes over many convectively active regions, (2) a lack of low-level hydrometeors over all subtropical oceanic basins, (3) excessive low-level hydrometeor coverage (principally precipitating hydrometeors) in the midlatitude storm tracks of both hemispheres during the summer season (in each hemisphere), and (4) a thin band of low-level hydrometeors in the Southern Hemisphere of the central (and at times eastern and western) Pacific in the MMF, which is not observed by CloudSat. This band resembles a second much weaker ITCZ but is restricted to low levels.

Marchand, Roger T.; Haynes, J. M.; Mace, Gerald G.; Ackerman, Thomas P.; Stephens, Graeme L.

2009-01-13T23:59:59.000Z

86

Comparison between active sensor and radiosonde cloud boundaries over the ARM Southern Great Plains site  

E-Print Network [OSTI]

of radar, lidar, and ceilometer data collected at the Atmospheric Radiation Measurements Southern Great [1995] and Chernykh and Eskridge [1996]. The lidar and ceilometer data yield lowest-level cloud base. These quantities are used to assess the accuracy of coincident cloud base heights obtained from radar and the two

87

Radiation Parameterization for Three-Dimensional Inhomogeneous Cirrus Clouds Applied to ARM Data and Climate Models  

SciTech Connect (OSTI)

OAK-B135 (a) We developed a 3D radiative transfer model to simulate the transfer of solar and thermal infrared radiation in inhomogeneous cirrus clouds. The model utilized a diffusion approximation approach (four-term expansion in the intensity) employing Cartesian coordinates. The required single-scattering parameters, including the extinction coefficient, single-scattering albedo, and asymmetry factor, for input to the model, were parameterized in terms of the ice water content and mean effective ice crystal size. The incorporation of gaseous absorption in multiple scattering atmospheres was accomplished by means of the correlated k-distribution approach. In addition, the strong forward diffraction nature in the phase function was accounted for in each predivided spatial grid based on a delta-function adjustment. The radiation parameterization developed herein is applied to potential cloud configurations generated from GCMs to investigate broken clouds and cloud-overlapping effects on the domain-averaged heating rate. Cloud inhomogeneity plays an important role in the determination of flux and heating rate distributions. Clouds with maximum overlap tend to produce less heating than those with random overlap. Broken clouds show more solar heating as well as more IR cooling as compared to a continuous cloud field (Gu and Liou, 2001). (b) We incorporated a contemporary radiation parameterization scheme in the UCLA atmospheric GCM in collaboration with the UCLA GCM group. In conjunction with the cloud/radiation process studies, we developed a physically-based cloud cover formation scheme in association with radiation calculations. The model clouds were first vertically grouped in terms of low, middle, and high types. Maximum overlap was then used for each cloud type, followed by random overlap among the three cloud types. Fu and Liou's 1D radiation code with modification was subsequently employed for pixel-by-pixel radiation calculations in the UCLA GCM. We showed that the simulated cloud cover and OLR fields without special tuning are comparable to those of ISCCP dataset and the results derived from radiation budget experiments. Use of the new radiation and cloud schemes enhances the radiative warming in the middle to upper tropical troposphere and alleviates the cold bias in the UCLA atmospheric GCM. We also illustrated that ice crystal size and cloud inhomogeneous are significant factors affecting the radiation budgets at the top of the atmosphere and the surface (Gu et al. 2003). (c) An innovative approach has been developed to construct a 3D field of inhomogeneous clouds in general and cirrus in particular in terms of liquid/ice water content and particle size on the basis of a unification of satellite and ground-based cloud radar data. Satellite remote sensing employing the current narrow-band spectro-radiometers has limitation and only the vertically integrated cloud parameters (optical depth and mean particle size) can be determined. However, by combining the horizontal cloud mapping inferred from satellites with the vertical structure derived from the profiling Doppler cloud radar, a 3D cloud field can be constructed. This represents a new conceptual approach to 3D remote sensing and imaging and offers a new perspective in observing the cloud structure. We applied this novel technique to AVHRR/NOAA satellite and mm-wave cloud radar data obtained from the ARM achieve and assessed the 3D cirrus cloud field with the ice crystal size distributions independently derived from optical probe measurements aboard the University of North Dakota Citation. The retrieved 3D ice water content and mean effective ice crystal size involving an impressive cirrus cloud occurring on April 18, 1997, are shown to be comparable to those derived from the analysis of collocated and coincident in situ aircraft measurements (Liou et al. 2002). (d) Detection of thin cirrus with optical depths less than 0.5, particularly those occurring i n the tropics remains a fundamental problem in remote sensing. We developed a new detection scheme for the

Kuo-Nan Liou

2003-12-29T23:59:59.000Z

88

ARM KAZR-ARSCL Value Added Product  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Ka-band ARM Zenith Radars (KAZRs) have replaced the long-serving Millimeter Cloud Radars, or MMCRs. Accordingly, the primary MMCR Value Added Product (VAP), the Active Remote Sensing of CLouds (ARSCL) product, is being replaced by a KAZR-based version, the KAZR-ARSCL VAP. KAZR-ARSCL provides cloud boundaries and best-estimate time-height fields of radar moments.

Jensen, Michael

89

ARM - Field Campaign - IR Cloud Camera Feasibility Study  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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90

GFDL ARM Project Technical Report: Using ARM Observations to Evaluate Cloud and Convection Parameterizations & Cloud-Convection-Radiation Interactions in the GFDL Atmospheric General Circulation Model  

SciTech Connect (OSTI)

This report briefly summarizes the progress made by ARM postdoctoral fellow, Yanluan Lin, at GFDL during the period from October 2008 to present. Several ARM datasets have been used for GFDL model evaluation, understanding, and improvement. This includes a new ice fall speed parameterization with riming impact and its test in GFDL AM3, evaluation of model cloud and radiation diurnal and seasonal variation using ARM CMBE data, model ice water content evaluation using ARM cirrus data, and coordination of the TWPICE global model intercomparison. The work illustrates the potential and importance of ARM data for GCM evaluation, understanding, and ultimately, improvement of GCM cloud and radiation parameterizations. Future work includes evaluation and improvement of the new dynamicsPDF cloud scheme and aerosol activation in the GFDL model.

V. Ramaswamy; L. J. Donner; J-C. Golaz; S. A. Klein

2010-06-17T23:59:59.000Z

91

CHAPTER 2: Analysis of cloud radar data 21 1000 1030 1100 1130 1200 1230 1300 1330  

E-Print Network [OSTI]

, and the corresponding noise­ equivalent reflectivity at 1 km measured by the 94 GHz radar (using the cloud­free gates the sensitivity of the radar is to subtract an estimate of the noise â?? N from the measured average power â?˘ P of magnitude below the noise level. Of­ ten rain radars simply reject the data that fall below a particular

Hogan, Robin

92

Use of the ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes & Aerosol-Cloud Interaction  

SciTech Connect (OSTI)

This project focuses on cloud-radiation processes in a general three-dimensional cloud situation, with particular emphasis on cloud optical depth and effective particle size. The proposal has two main parts. Part one exploits the large number of new wavelengths offered by the Atmospheric Radiation Measurement (ARM) zenith-pointing ShortWave Spectrometer (SWS), to develop better retrievals not only of cloud optical depth but also of cloud particle size. We also take advantage of the SWS’ high sampling resolution to study the “twilight zone” around clouds where strong aerosol-cloud interactions are taking place. Part two involves continuing our cloud optical depth and cloud fraction retrieval research with ARM’s 2-channel narrow vield-of-view radiometer and sunphotometer instrument by, first, analyzing its data from the ARM Mobile Facility deployments, and second, making our algorithms part of ARM’s operational data processing.

Chiu, Jui-Yuan Christine [University of Reading] [University of Reading

2014-04-10T23:59:59.000Z

93

Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties  

SciTech Connect (OSTI)

The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processes is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model simulations. The ultimate goal is to improve our cloud classification algorithm into a VAP.

Wang, Zhien

2010-06-29T23:59:59.000Z

94

W-Band ARM Cloud Radar - Specifications and Design  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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95

W-band ARM Cloud Radar (WACR) Update and Status  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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96

ARM - Evaluation Product - Precipitation Radar Moments Mapped to a  

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97

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II: Cloud Fraction and Surface Radiative Forcing  

E-Print Network [OSTI]

at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility and for single-layered low (0­3 km), middle (3­6 km), and high clouds ( 6 km) using ARM SCF ground-based paired-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties

Dong, Xiquan

98

Ice iron/sodium film as cause for high noctilucent cloud radar reflectivity  

E-Print Network [OSTI]

Ice iron/sodium film as cause for high noctilucent cloud radar reflectivity P. M. Bellan1 Received] Noctilucent clouds, tiny cold electrically charged ice grains located at about 85 km altitude, exhibit by assuming the ice grains are coated by a thin metal film; substantial evidence exists indicating

Bellan, Paul M.

99

Long-term Observations of the Convective Boundary Layer Using Insect Radar Returns at the SGP ARM Climate Research Facility  

SciTech Connect (OSTI)

A long-term study of the turbulent structure of the convective boundary layer (CBL) at the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Climate Research Facility is presented. Doppler velocity measurements from insects occupying the lowest 2 km of the boundary layer during summer months are used to map the vertical velocity component in the CBL. The observations cover four summer periods (2004-08) and are classified into cloudy and clear boundary layer conditions. Profiles of vertical velocity variance, skewness, and mass flux are estimated to study the daytime evolution of the convective boundary layer during these conditions. A conditional sampling method is applied to the original Doppler velocity dataset to extract coherent vertical velocity structures and to examine plume dimension and contribution to the turbulent transport. Overall, the derived turbulent statistics are consistent with previous aircraft and lidar observations. The observations provide unique insight into the daytime evolution of the convective boundary layer and the role of increased cloudiness in the turbulent budget of the subcloud layer. Coherent structures (plumes-thermals) are found to be responsible for more than 80% of the total turbulent transport resolved by the cloud radar system. The extended dataset is suitable for evaluating boundary layer parameterizations and testing large-eddy simulations (LESs) for a variety of surface and cloud conditions.

Chandra, A S; Kollias, P; Giangrande, S E; Klein, S A

2009-08-20T23:59:59.000Z

100

A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.  

SciTech Connect (OSTI)

The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phase cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.

Luke,E.; Kollias, P.

2007-08-06T23:59:59.000Z

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

ARM - Midlatitude Continental Convective Clouds (jensen-sonde)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment.

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

102

ARM - Midlatitude Continental Convective Clouds (jensen-sonde)  

SciTech Connect (OSTI)

A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment.

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19T23:59:59.000Z

103

Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations  

SciTech Connect (OSTI)

The works supported by this ASR project lay the solid foundation for improving the parameterization of convection and clouds in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and ARM observations to produce thermodynamically and dynamically consistent multi-year cloud and radiative properties; improve the GCM simulations of convection, clouds and radiative heating rate and fluxes using the ARM observations and CRM simulations; and understand the seasonal and annual variation of cloud systems and their impacts on climate mean state and variability. We conducted multi-year simulations over the ARM SGP site using the CRM with multi-year ARM forcing data. The statistics of cloud and radiative properties from the long-term CRM simulations were compared and validated with the ARM measurements and value added products (VAP). We evaluated the multi-year climate simulations produced by the GCM with the modified convection scheme. We used multi-year ARM observations and CRM simulations to validate and further improve the trigger condition and revised closure assumption in NCAR GCM simulations that demonstrate the improvement of climate mean state and variability. We combined the improved convection scheme with the mosaic treatment of subgrid cloud distributions in the radiation scheme of the GCM. The mosaic treatment of cloud distributions has been implemented in the GCM with the original convection scheme and enables the use of more realistic cloud amounts as well as cloud water contents in producing net radiative fluxes closer to observations. A physics-based latent heat (LH) retrieval algorithm was developed by parameterizing the physical linkages of observed hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water.

Wu, Xiaoqing

2014-02-25T23:59:59.000Z

104

DOE/SC-ARM-13-008 First ARM/ASR Radar Workshop: Workshop  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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105

Constructing a Merged Cloud-Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll  

SciTech Connect (OSTI)

To improve understanding of the convective processes key to the Madden-Julian-Oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and Atmospheric Radiation Measurement MJO Investigation Experiment (AMIE) collected four months of observations from three radars, the S-band Polarization Radar (S-Pol), the C-band Shared Mobile Atmospheric Research & Teaching Radar (SMART-R), and Ka-band Zenith Radar (KAZR) on Addu Atoll in the tropical Indian Ocean. This study compares the measurements from the S-Pol and SMART-R to those from the more sensitive KAZR in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars. Frequency comparisons for precipitating convective clouds and non-precipitating high clouds agree much better than non-precipitating low clouds for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high cloud tops by 0.3 to 1.1 km, while S-Pol underestimates cloud tops by less than 0.4 km for these cloud types. S-Pol shows excellent dynamic range in detecting various types of clouds and therefore its data are well suited for characterizing the evolution of the 3D cloud structures, complementing the profiling KAZR measurements. For detecting non-precipitating low clouds and thin cirrus clouds, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates cloud top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR cloud top heights is described, and a merged radar dataset is produced to provide improved cloud boundary estimates, microphysics and radiative heating retrievals.

Feng, Zhe; McFarlane, Sally A.; Schumacher, Courtney; Ellis, Scott; Comstock, Jennifer M.; Bharadwaj, Nitin

2014-05-16T23:59:59.000Z

106

Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data  

E-Print Network [OSTI]

Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data ERWIN L. A. WOLTERS, ROBERT A. ROEBELING, AND ARNOUT J. FEIJT Royal Netherlands 2007) ABSTRACT Three cloud-phase determination algorithms from passive satellite imagers are explored

Stoffelen, Ad

107

An Intercomparison of Radar-Based Liquid Cloud Microphysics Retrievals and Implication for Model Evaluation Studies  

E-Print Network [OSTI]

Research Facility of the US Department of Energy provides long-term continuous cloud and radiation datasets Forks, ND 58202, U.S.A. 4 University of Utah, Salt Lake City, UT 84112, U.S.A. Corresponding Author Dong of single-frequency radar approaches. It is therefore suggested that data users should use the retrievals

Dong, Xiquan

108

Toward Understanding of Differences in Current Cloud Retrievals of ARM Ground-based Measurements  

SciTech Connect (OSTI)

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasize on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice effective radius. It is shown that most of these large differences have their roots in the retrieval algorithms used by these cloud products, including the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Zhao, Chuanfeng; Xie, Shaocheng; Klein, Stephen A.; Protat, Alain; Shupe, Matthew D.; McFarlane, Sally A.; Comstock, Jennifer M.; Delanoe, Julien; Deng, Min; Dunn, Maureen; Hogan, Robin; Huang, Dong; Jensen, Michael; Mace, Gerald G.; McCoy, Renata; O'Conner, Ewan J.; Turner, Dave; Wang, Zhien

2012-05-30T23:59:59.000Z

109

Toward understanding of differences in current cloud retrievals of ARM ground-based measurements  

SciTech Connect (OSTI)

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Zhao C.; Dunn M.; Xie, S.; Klein, S. A.; Protat, A.; Shupe, M. D.; McFarlane, S. A.; Comstock, J. M.; Delanoë, J.; Deng, M.; Hogan, R. J.; Huang, D.; Jensen, M. P.; Mace, G. G.; McCoy, R.; O’Connor, E. J.; Turner, D. D.; Wang, Z.

2012-05-30T23:59:59.000Z

110

arm remote clouds: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

with the Milky Way galaxy. Using the Parkes Galactic All-Sky Survey (GASS) of atomic hydrogen we explore the role of drag on the evolution of the so-called Leading Arm (LA). We...

111

Use of the ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes & Aerosol-Cloud Interaction  

SciTech Connect (OSTI)

We proposed a variety of tasks centered on the following question: what can we learn about 3D cloud-radiation processes and aerosol-cloud interaction from rapid-sampling ARM measurements of spectral zenith radiance? These ARM measurements offer spectacular new and largely unexploited capabilities in both the temporal and spectral domains. Unlike most other ARM instruments, which average over many seconds or take samples many seconds apart, the new spectral zenith radiance measurements are fast enough to resolve natural time scales of cloud change and cloud boundaries as well as the transition zone between cloudy and clear areas. In the case of the shortwave spectrometer, the measurements offer high time resolution and high spectral resolution, allowing new discovery-oriented science which we intend to pursue vigorously. Research objectives are, for convenience, grouped under three themes: â?˘ Understand radiative signature of the transition zone between cloud-free and cloudy areas using data from ARM shortwave radiometers, which has major climatic consequences in both aerosol direct and indirect effect studies. â?˘ Provide cloud property retrievals from the ARM sites and the ARM Mobile Facility for studies of aerosol-cloud interactions. â?˘ Assess impact of 3D cloud structures on aerosol properties using passive and active remote sensing techniques from both ARM and satellite measurements.

Alexander Marshak; Warren Wiscombe; Yuri Knyazikhin; Christine Chiu

2011-05-24T23:59:59.000Z

112

A Comparison of ARM Cloud Radar Profiles with MMF Simulated Radar Profiles  

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113

Evaluation of A New Mixed-Phase Cloud Microphysics Parameterization with the NCAR Climate Atmospheric Model (CAM3) and ARM Observations Fourth Quarter 2007 ARM Metric Report  

SciTech Connect (OSTI)

Mixed-phase clouds are composed of a mixture of cloud droplets and ice crystals. The cloud microphysics in mixed-phase clouds can significantly impact cloud optical depth, cloud radiative forcing, and cloud coverage. However, the treatment of mixed-phase clouds in most current climate models is crude and the partitioning of condensed water into liquid droplets and ice crystals is prescribed as temperature dependent functions. In our previous 2007 ARM metric reports a new mixed-phase cloud microphysics parameterization (for ice nucleation and water vapor deposition) was documented and implemented in the NCAR Community Atmospheric Model Version 3 (CAM3). The new scheme was tested against the Atmospheric Radiation Measurement (ARM) Mixed-phase Arctic Cloud Experiment (M-PACE) observations using the single column modeling and short-range weather forecast approaches. In this report this new parameterization is further tested with CAM3 in its climate simulations. It is shown that the predicted ice water content from CAM3 with the new parameterization is in better agreement with the ARM measurements at the Southern Great Plain (SGP) site for the mixed-phase clouds.

X Liu; SJ Ghan; S Xie; J Boyle; SA Klein

2007-09-30T23:59:59.000Z

114

ARM - Publications: Science Team Meeting Documents: A Climatology of Clouds  

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115

ARM Value-Added Cloud Products: Description and Status  

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116

Application of Stochastic Radiative Transfer Theory to the ARM Cloud-Radiative Parameterization Problem  

SciTech Connect (OSTI)

This project had two primary goals: (1) development of stochastic radiative transfer as a parameterization that could be employed in an AGCM environment, and (2) exploration of the stochastic approach as a means for representing shortwave radiative transfer through mixed-phase layer clouds. To achieve these goals, climatology of cloud properties was developed at the ARM CART sites, an analysis of the performance of the stochastic approach was performed, a simple stochastic cloud-radiation parameterization for an AGCM was developed and tested, a statistical description of Arctic mixed phase clouds was developed and the appropriateness of stochastic approach for representing radiative transfer through mixed-phase clouds was assessed. Significant progress has been made in all of these areas and is detailed in the final report.

Dana E. Veron

2012-04-09T23:59:59.000Z

117

ARM - Publications: Science Team Meeting Documents: Interpretation of cloud  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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118

ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:  

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119

ARM - Field Campaign - Cloud LAnd Surface Interaction Campaign (CLASIC)  

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120

ARM - Field Campaign - Complex Layered Cloud Experiment (CLEX)  

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Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Continuous Profiles of Cloud Microphysical Properties for the Fixed Atmospheric Radiation Measurement Sites  

SciTech Connect (OSTI)

The Atmospheric Radiation Measurement (ARM) Program defined a specific metric for the third quarter of Fiscal Year 2006 to produce and refine a one-year continuous time series of cloud microphysical properties based on cloud radar measurements for each of the fixed ARM sites. To accomplish this metric, we used a combination of recently developed algorithms that interpret radar reflectivity profiles, lidar backscatter profiles, and microwave brightness temperatures into the context of the underlying cloud microphysical structure.

Jensen, M; Jensen, K

2006-06-01T23:59:59.000Z

122

ARM - PI Product - Cloud Property Retrieval Products for Graciosa Island,  

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123

ARM - PI Product - Tropical Cloud Properties and Radiative Heating Profiles  

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124

Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part II: Multi-layered cloud  

SciTech Connect (OSTI)

Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a deep, multi-layered, mixed-phase cloud system observed during the ARM Mixed-Phase Arctic Cloud Experiment. This cloud system was associated with strong surface turbulent sensible and latent heat fluxes as cold air flowed over the open Arctic Ocean, combined with a low pressure system that supplied moisture at mid-level. The simulations, performed by 13 single-column and 4 cloud-resolving models, generally overestimate the liquid water path and strongly underestimate the ice water path, although there is a large spread among the models. This finding is in contrast with results for the single-layer, low-level mixed-phase stratocumulus case in Part I of this study, as well as previous studies of shallow mixed-phase Arctic clouds, that showed an underprediction of liquid water path. The overestimate of liquid water path and underestimate of ice water path occur primarily when deeper mixed-phase clouds extending into the mid-troposphere were observed. These results suggest important differences in the ability of models to simulate Arctic mixed-phase clouds that are deep and multi-layered versus shallow and single-layered. In general, models with a more sophisticated, two-moment treatment of the cloud microphysics produce a somewhat smaller liquid water path that is closer to observations. The cloud-resolving models tend to produce a larger cloud fraction than the single-column models. The liquid water path and especially the cloud fraction have a large impact on the cloud radiative forcing at the surface, which is dominated by the longwave flux for this case.

Morrison, H; McCoy, R B; Klein, S A; Xie, S; Luo, Y; Avramov, A; Chen, M; Cole, J; Falk, M; Foster, M; Genio, A D; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; McFarquhar, G; Poellot, M; Shipway, B; Shupe, M; Sud, Y; Turner, D; Veron, D; Walker, G; Wang, Z; Wolf, A; Xu, K; Yang, F; Zhang, G

2008-02-27T23:59:59.000Z

125

Cloud Occurrence Frequency at the Barrow, Alaska, ARM Climate Research Facility for 2008 Third Quarter 2009 ARM and Climate Change Prediction Program Metric Report  

SciTech Connect (OSTI)

Clouds represent a critical component of the Earth’s atmospheric energy balance as a result of their interactions with solar and terrestrial radiation and a redistribution of heat through convective processes and latent heating. Despite their importance, clouds and the processes that control their development, evolution and lifecycle remain poorly understood. Consequently, the simulation of clouds and their associated feedbacks is a primary source of inter-model differences in equilibrium climate sensitivity. An important step in improving the representation of cloud process simulations is an improved high-resolution observational data set of the cloud systems including their time evolution. The first order quantity needed to understand the important role of clouds is the height of cloud occurrence and how it changes as a function of time. To this end, the Atmospheric Radiation Measurement (ARM) Climate Research Facilities (ACRF) suite of instrumentation has been developed to make the observations required to improve the representation of cloud systems in atmospheric models.

M Jensen; K Johnson; JH Mather

2009-07-14T23:59:59.000Z

126

ARM - Field Campaign - Colorado: The Storm Peak Lab Cloud Property  

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127

ARM - Field Campaign - Midlatitude Continental Convective Clouds Experiment  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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128

ARM - Field Campaign - Midlatitude Continental Convective Clouds Experiment  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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129

ARM - Field Campaign - Mixed-Phase Arctic Cloud Experiment  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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130

Comparison of POLDER Cloud Phase Retrievals to Active Remote Sensors Measurements at the ARM SGP Site  

SciTech Connect (OSTI)

In our present study, cloud boundaries derived from a combination of active remote sensors at the ARM SGP site are compared to POLDER cloud top phase index which is derived from polarimetric measurements using an innovative method. This approach shows the viability of the POLDER phase retrieval algorithm, and also leads to interesting results. In particular, the analysis demonstrates the sensitivity of polarization measurements to ice crystal shape and indicates that occurrence of polycrystalline ice clouds has to be taken into account in order to improve the POLDER phase retrieval algorithm accuracy. Secondly, the results show that a temperature threshold of 240 K could serve for cloud top particle phase classification. Considering the limitations of the analysis, the temperature threshold could be biased high, but not by more than about 5 degrees.

Riedi, J.; Goloub, P.; Marchand, Roger T.

2001-06-01T23:59:59.000Z

131

ARM - Evaluation Product - Active Remote Sensing of Clouds from Ka-band ARM  

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132

ARM - Publications: Science Team Meeting Documents: Increasing Cloud  

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133

ARM - Evaluation Product - Cloud Optical Properties from MFRSR Using Min  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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134

ARM - Field Campaign - Cirrus Clouds and Aerosol Properties Campaign  

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135

ARM - Field Campaign - Deep Convective Clouds and Chemistry  

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136

ARM - Midlatitude Continental Convective Clouds (comstock-hvps)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

137

DOE/SC-ARM-TR-099 ARM Cloud Retrieval Ensemble Data Set  

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138

DOE/SC-ARM-14-030 ARM Cloud Aerosol Precipitation Experiment  

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139

ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC): RH  

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140

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Surface Meteorology (williams-surfmet)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Vertical Air Motion (williams-vertair)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

142

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Parcivel Disdrometer (williams-disdro)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

143

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, 449 MHz Profiler(williams-449_prof)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

144

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, 449 MHz Profiler(williams-449_prof)  

SciTech Connect (OSTI)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

145

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Parcivel Disdrometer (williams-disdro)  

SciTech Connect (OSTI)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

146

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Vertical Air Motion (williams-vertair)  

SciTech Connect (OSTI)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

147

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Surface Meteorology (williams-surfmet)  

SciTech Connect (OSTI)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

148

DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING OF CLOUDS AND RADIATION USING ARM DATA, FINAL REPORT  

SciTech Connect (OSTI)

During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products and raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.

Minnis, Patrick [NASA Langley Research Center, Hampton, VA

2013-06-28T23:59:59.000Z

149

Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave radiometer data are systematically compared to models to quantify and  

E-Print Network [OSTI]

Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave a systematic evaluation of clouds in forecast models. Clouds and their associated microphysical processes for end users of weather forecasts, who may be interested not only in cloud cover, but in other variables

Hogan, Robin

150

Atmospheric Radiation Measurement (ARM) Data from Steamboat Springs, Colorado, for the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

In October 2010, the initial deployment of the second ARM Mobile Facility (AMF2) took place at Steamboat Springs, Colorado, for the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX). The objective of this field campaign was to obtain data about liquid and mixed-phase clouds using AMF2 instruments in conjunction with Storm Peak Laboratory (located at an elevation of 3220 meters on Mt. Werner), a cloud and aerosol research facility operated by the Desert Research Institute. STORMVEX datasets are freely available for viewing and download. Users are asked to register with the ARM Archive; the user's email address is used from that time forward as the login name.

151

Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud  

SciTech Connect (OSTI)

Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics indicate that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is some evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics. This case study, which has been well observed from both aircraft and ground-based remote sensors, could be a benchmark for model simulations of mixed-phase clouds.

Klein, S A; McCoy, R B; Morrison, H; Ackerman, A; Avramov, A; deBoer, G; Chen, M; Cole, J; DelGenio, A; Golaz, J; Hashino, T; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; Luo, Y; McFarquhar, G; Menon, S; Neggers, R; Park, S; Poellot, M; von Salzen, K; Schmidt, J; Sednev, I; Shipway, B; Shupe, M; Spangenberg, D; Sud, Y; Turner, D; Veron, D; Falk, M; Foster, M; Fridlind, A; Walker, G; Wang, Z; Wolf, A; Xie, S; Xu, K; Yang, F; Zhang, G

2008-02-27T23:59:59.000Z

152

OAK 270 - The use of Lidar/radiometer (LIRAD) in the ARM program to obtain optical properties and microphysics of high and midlevel clouds  

SciTech Connect (OSTI)

OAK 270 - The use of Lidar/Radiometer (LIRAD) in the ARM program to obtain optical properties and microphysics of high and midlevel clouds

C.M.R. Platt; R.T. Austin; S.A. Young; and G.L. Stephens

2002-12-13T23:59:59.000Z

153

Use of the ARM Measurement of Spectral Zenith Radiance For Better Understanding Of 3D Cloud-Radiation Processes and Aerosol-Cloud Interaction  

SciTech Connect (OSTI)

Our proposal focuses on cloud-radiation processes in a general 3D cloud situation, with particular emphasis on cloud optical depth and effective particle size. We also focus on zenith radiance measurements, both active and passive. The proposal has three main parts. Part One exploits the �¢����solar-background�¢��� mode of ARM lidars to allow them to retrieve cloud optical depth not just for thin clouds but for all clouds. This also enables the study of aerosol cloud interactions with a single instrument. Part Two exploits the large number of new wavelengths offered by ARM�¢����s zenith-pointing ShortWave Spectrometer (SWS), especially during CLASIC, to develop better retrievals not only of cloud optical depth but also of cloud particle size. We also propose to take advantage of the SWS�¢���� 1 Hz sampling to study the �¢����twilight zone�¢��� around clouds where strong aerosol-cloud interactions are taking place. Part Three involves continuing our cloud optical depth and cloud fraction retrieval research with ARM�¢����s 2NFOV instrument by, first, analyzing its data from the AMF-COPS/CLOWD deployment, and second, making our algorithms part of ARM�¢����s operational data processing.

D. Jui-Yuan Chiu

2010-10-19T23:59:59.000Z

154

Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud  

SciTech Connect (OSTI)

Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed average liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the average mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics suggest that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics.

Klein, Stephen A.; McCoy, Renata B.; Morrison, Hugh; Ackerman, Andrew S.; Avramov, Alexander; de Boer, Gijs; Chen, Mingxuan; Cole, Jason N.S.; Del Genio, Anthony D.; Falk, Michael; Foster, Michael J.; Fridlind, Ann; Golaz, Jean-Christophe; Hashino, Tempei; Harrington, Jerry Y.; Hoose, Corinna; Khairoutdinov, Marat F.; Larson, Vincent E.; Liu, Xiaohong; Luo, Yali; McFarquhar, Greg M.; Menon, Surabi; Neggers, Roel A. J.; Park, Sungsu; Poellot, Michael R.; Schmidt, Jerome M.; Sednev, Igor; Shipway, Ben J.; Shupe, Matthew D.; Spangenberg, Douglas A.; Sud, Yogesh C.; Turner, David D.; Veron, Dana E.; von Salzen, Knut; Walker, Gregory K.; Wang, Zhien; Wolf, Audrey B.; Xie, Shaocheng; Xu, Kuan-Man; Yang, Fanglin; Zhang, Gong

2009-02-02T23:59:59.000Z

155

ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scm_forcing)  

SciTech Connect (OSTI)

The constrained variational objective analysis approach described in Zhang and Lin [1997] and Zhang et al. [2001]was used to derive the large-scale single-column/cloud resolving model forcing and evaluation data set from the observational data collected during Midlatitude Continental Convective Clouds Experiment (MC3E), which was conducted during April to June 2011 near the ARM Southern Great Plains (SGP) site. The analysis data cover the period from 00Z 22 April - 21Z 6 June 2011. The forcing data represent an average over the 3 different analysis domains centered at central facility with a diameter of 300 km (standard SGP forcing domain size), 150 km and 75 km, as shown in Figure 1. This is to support modeling studies on various-scale convective systems.

Xie, Shaocheng; McCoy, Renata; Zhang, Yunyan

2012-10-25T23:59:59.000Z

156

ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scm_forcing)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The constrained variational objective analysis approach described in Zhang and Lin [1997] and Zhang et al. [2001]was used to derive the large-scale single-column/cloud resolving model forcing and evaluation data set from the observational data collected during Midlatitude Continental Convective Clouds Experiment (MC3E), which was conducted during April to June 2011 near the ARM Southern Great Plains (SGP) site. The analysis data cover the period from 00Z 22 April - 21Z 6 June 2011. The forcing data represent an average over the 3 different analysis domains centered at central facility with a diameter of 300 km (standard SGP forcing domain size), 150 km and 75 km, as shown in Figure 1. This is to support modeling studies on various-scale convective systems.

Xie, Shaocheng; McCoy, Renata; Zhang, Yunyan

157

Testing AGCM-Predicted Cloud and Radiation Properties with ARM Data: The Super-Parameterization Approach  

SciTech Connect (OSTI)

The goal of our study is to directly evaluate treatment of clouds and radiation in an atmospheric global climate model (AGCM) using long-term observations from the Atmospheric Radiation Measurement (ARM) program. In this presentation, we will present a comparison of observations from two ARM sites, one in north central Oklahoma and one at Nauru island in the Tropical Western Pacific region, with the model output from corresponding grid points. Traditional parametric approach of diagnosing cloud and radiation properties from large-scale model fields is not well suited for comparison with observed time series at selected locations. A recently emerging approach called super parameterization has shown promise to bridge the gap. Super parameterization consists of a two-dimensional cloud system resolving model (CSRM) embedded into each grid of the NCAR Community Climate System Model thereby computing cloud properties at a scale that is more consistent with observations. Because the approach is computationally expensive only limited simulations have been carried out. Two sets of one year long simulations are considered: one using climatological sea surface temperatures (SST) and another using 1999 SST. Each set includes a run with super-parameterization (SP) as well as an AGCM run with traditional or standard (STD) cloud and radiation treatment. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are statistically analyzed. Nearly all parameters of frequency distributions of these variables from SP run are shown to be more consistent with observation than those from STD model run. Different temporal and spatial averaging in the simulations and observations imposes limitations on the comparisons and these scale effects will be discussed. Output from the STD run represents statistics for the AGCM grid, which, in our case, is roughly 300 km x 300 km. In contrast, the CSRM domain is 4 km x 256 km and consists of a row of 64 columns, 4 km x 4 km each. One of the benefits of the SP approach is that statistics can be collected for domain-averaged as well as column cloud and radiation properties. The column statistics are representative of scales that are closer to the scales of observations and therefore allow for more direct comparisons.

Ovchinnikov, Mikhail; Ackerman, Thomas P.; Marchand, Roger T.; Khairoutdinov, Marat

2004-01-31T23:59:59.000Z

158

Stratus cloud structure from MM-radar transects and satellite images: scaling properties and artifact detection with semi-discrete wavelet analysis  

SciTech Connect (OSTI)

Spatial and/or temporal variabilities of clouds is of paramount importance for at least two in tensely researched sub-problems in global and regional climate modeling: (1) cloud-radiation interaction where correlations can trigger 3D radiative transfer effects; and (2) dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets as a simple yet powerful way of quantifying cloud variability. More precisely, we use 'semi-discrete' wavelet transforms which, at least in the present statistical applications, have advantages over both its continuous and discrete counterparts found in the bulk of the wavelet literature. With the particular choice of normalization we adopt, the scale-dependence of the variance of the wavelet coefficients (i.e,, the wavelet energy spectrum) is always a better discriminator of transition from 'stationary' to 'nonstationary' behavior than conventional methods based on auto-correlation analysis, second-order structure function (a.k.a. the semi-variogram), or Fourier analysis. Indeed, the classic statistics go at best from monotonically scale- or wavenumber-dependent to flat at such a transition; by contrast, the wavelet spectrum changes the sign of its derivative with respect to scale. We apply 1D and 2D semi-discrete wavelet transforms to remote sensing data on cloud structure from two sources: (1) an upward-looking milli-meter cloud radar (MMCR) at DOE's climate observation site in Oklahoma deployed as part of the Atmospheric Radiation Measurement (ARM) Progrm; and (2) DOE's Multispectral Thermal Imager (MTI), a high-resolution space-borne instrument in sunsynchronous orbit that is described in sufficient detail for our present purposes by Weber et al. (1999). For each type of data, we have at least one theoretical prediction - with empirical validation already in existence - for a power-law relation for wavelet statistics with respect to scale. This is what is expected in physical (i.e., finite scaling range) fractal phenomena. In particular, we find long-range correlations in cloud structure coming from the important nonstationary regime. More surprisingly, we also uncover artifacts the data that are traceable either to instrumental noise (in the satellite data) or to smoothing assumptions (in the MMCR data processing). Finally, we discuss the potentially damaging ramifications the smoothing artifact can have on both cloud-radiation and cloud-modeling studies using MMCR data.

Davis, A. B. (Anthony B.); Petrov, N. P. (Nikola P.); Clothiaux, E. E. (Eugene E.); Marshak, A. (Alexander)

2002-01-01T23:59:59.000Z

159

ARM CLASIC ER2 CRS/EDOP  

SciTech Connect (OSTI)

Data was taken with the NASA ER-2 aircraft with the Cloud Radar System and other instruments in conjunction with the DOE ARM CLASIC field campaign. The flights were near the SGP site in north Central Oklahoma and targeted small developing convection. The CRS is a 94 GHz nadir pointing Doppler radar. Also on board the ER-2 was the Cloud Physics Lidar (CPL). Seven science flights were conducted but the weather conditions did not cooperate in that there was neither developing convection, or there was heavy rain.

Gerald Heymsfield

2010-12-20T23:59:59.000Z

160

COLLABORATIVE RESEARCH:USING ARM OBSERVATIONS & ADVANCED STATISTICAL TECHNIQUES TO EVALUATE CAM3 CLOUDS FOR DEVELOPMENT OF STOCHASTIC CLOUD-RADIATION  

SciTech Connect (OSTI)

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key step in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been a collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen).

Somerville, Richard

2013-08-22T23:59:59.000Z

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161

Comparison of the CALIPSO satellite and ground-based observations of cirrus clouds at the ARM TWP sites  

SciTech Connect (OSTI)

Statistics of ice cloud macrophysical and optical properties from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite are compared with those from ground-based lidar observations over a 31 month period. Ground-based lidar observations are taken from the micropulse lidars (MPL) at the three Department of Energy Atmospheric Radiation Measurement (ARM) tropical western pacific (TWP) sites: Manus, Nauru and Darwin. CALIPSO observations show a larger cloud fraction at high altitudes while the ground-based MPLs show a larger cloud fraction at low altitudes. The difference in mean ice cloud top and base heights at the Manus and Nauru sites are all within 0.51 km, although differences are statistically significant. Mean ice cloud geometrical thickness agree to within 0.05 km at the Manus and Nauru sites. Larger differences exist at Darwin due to excessive degradation of the MPL output power during our sampling period. Both sets of observations show thicker clouds during the nighttime which may be real but could also be partially an artifact of the decreased signal-to-noise ratio during the daytime. The number of ice cloud layers per profile are also shown to be consistent after accounting for the difference in spatial resolution. For cloud optical depths, four different retrieval methods are compared, two for each set of observations. All products show that the majority of ice cloud optical depths ({approx}60%) fall below an optical depth of 0.2. For most comparisons all four retrievals agree to within the uncertainty intervals. We find that both CALIPSO retrievals agree best to ground-based optical depths when the lidar ratio in the latter is retrieved instead of set to a fixed value. Also thoroughly compared is the cloud properties for the subset of ice clouds which reside in the tropical tropopause layer (TTL).

Thorsen, Tyler J.; Fu, Q.; Comstock, Jennifer M.

2011-11-10T23:59:59.000Z

162

Atmospheric Radiation Measurement (ARM) Data from Los Angeles, California, to Honolulu, Hawaii for the Marine ARM GPCI Investigation of Clouds (MAGIC) Field Campaign (an AMF2 Deployment)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

From October 2012 through September 2013, the second ARM Mobile Facility (AMF2) was deployed on the container ship Spirit, operated by Horizon Lines, for the Marine ARM GPCI* Investigation of Clouds (MAGIC) field campaign. During approximately 20 round trips between Los Angeles, California, and Honolulu, Hawaii, AMF2 obtained continuous on-board measurements of cloud and precipitation, aerosols, and atmospheric radiation; surface meteorological and oceanographic variables; and atmospheric profiles from weather balloons launched every six hours. During two two-week intensive observational periods in January and July 2013, additional instruments were deployed and balloon soundings were be increased to every three hours. These additional data provided a more detailed characterization of the state of the atmosphere and its daily cycle during two distinctly different seasons. The primary objective of MAGIC was to improve the representation of the stratocumulus-to-cumulus transition in climate models. AMF2 data documented the small-scale physical processes associated with turbulence, convection, and radiation in a variety of marine cloud types.

163

ARM - Site Instruments  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band ARM Cloud RadarPearl

164

Evaluation of Mixed-Phase Cloud Microphysics Parameterizations with the NCAR Single Column Climate Model (SCAM) and ARM Observations  

SciTech Connect (OSTI)

Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate models have generally proven unsuccessful at simulating the partitioning of condensed water into liquid droplets and ice crystals in these Arctic clouds, which affect modeled cloud phase, cloud lifetime and radiative properties. An ice nucleation parameterization and a vapor deposition scheme were developed that together provide a physically-consistent treatment of mixed-phase clouds in global climate models. These schemes have been implemented in the National Center for Atmospheric Research (NCAR) Community Atmospheric Model Version 3 (CAM3). This report documents the performance of these schemes against ARM Mixed-phase Arctic Cloud Experiment (M-PACE) observations using the CAM single column model version (SCAM). SCAM with our new schemes has a more realistic simulation of the cloud phase structure and the partitioning of condensed water into liquid droplets against observations during the M-PACE than the standard CAM simulations.

Liu, X; Ghan, SJ; Xie, S

2007-04-01T23:59:59.000Z

165

Thunderstorm characteristics of cloud-to-ground lightning at the Kennedy Space Center, Florida: a study of lightning initiation signatures as indicated by Doppler radar  

E-Print Network [OSTI]

Studies . a. Ground Flash Density b. First Stroke Peak Current . . c. Diurnal Cycle 2. Thunderstorm Characteristics a. Thunderstorm Electrification . . . . . . . b. Thunderstorm Activity . 3. Radar Studies . a. Radar Analysis b. Vertical Profiles... Mexico. Taylor (1978) also found the center of activity to be associated with the supercooled cloud layer between the regions of ? 5'C and ? 20'C. One theory of thunderstorm electrification supports the idea of an ice-related precipitation...

Gremillion, Michael Shane

1998-01-01T23:59:59.000Z

166

ARM: Microwave Radiometer data (MWR Profiles - QME), water vapor, temp, cloud liquid water, precip water retrievals  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Microwave Radiometer data (MWR Profiles - QME), water vapor, temp, cloud liquid water, precip water retrievals

Cadeddu, Maria

167

ARM - Midlatitude Continental Convective Clouds - Ultra High Sensitivity Aerosol Spectrometer(tomlinson-uhsas)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Ultra High Sensitivity Aerosol Spectrometer (UHSASA) A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

Tomlinson, Jason; Jensen, Mike

168

ARM - Midlatitude Continental Convective Clouds Microwave Radiometer Profiler (jensen-mwr)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

Jensen, Mike

169

ARM - Midlatitude Continental Convective Clouds Microwave Radiometer Profiler (jensen-mwr)  

SciTech Connect (OSTI)

A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

Jensen, Mike

2012-02-01T23:59:59.000Z

170

ARM - Midlatitude Continental Convective Clouds - Ultra High Sensitivity Aerosol Spectrometer(tomlinson-uhsas)  

SciTech Connect (OSTI)

Ultra High Sensitivity Aerosol Spectrometer (UHSASA) A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

Tomlinson, Jason; Jensen, Mike

2012-02-28T23:59:59.000Z

171

Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations  

SciTech Connect (OSTI)

Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulations in the IPCC AR4 GCMs against ARM ground measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity, for both inter-model deviation and model-measurement discrepancy. Our intercomparisons of three CF or sky-cover related dataset reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The results also show that the model-observation and the inter-model deviations have a similar magnitude for the total CF (TCF) and the normalized cloud effect, and they are twice as large as the surface downward solar radiation and cloud transmissivity. This implies that the other cloud properties, such as cloud optical depth and height, have a similar magnitude of disparity to TCF among the GCMs, and suggests that a better agreement among the GCMs in solar radiative fluxes could be the result of compensating errors in either cloud vertical structure, cloud optical depth or cloud fraction. Similar deviation pattern between inter-model and model-measurement suggests that the climate models tend to generate larger bias against observations for those variables with larger inter-model deviation. The simulated TCF from IPCC AR4 GCMs are very scattered through all seasons over three ARM sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). The GCMs perform better at SGP than at Manus and NSA in simulating the seasonal variation and probability distribution of TCF; however, the TCF in these models is remarkably underpredicted and cloud transmissivity is less susceptible to the change of TCF than the observed at SGP. Much larger inter-model deviation and model bias are found over NSA than the other sites in estimating the TCF, cloud transmissivity and cloud-radiation interaction, suggesting that the Arctic region continues to challenge cloud simulations in climate models. Most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels in the tropics. The high altitude CF is much larger in the GCMs than the observation and the inter-model variability of CF also reaches maximum at high levels in the tropics. Most of the GCMs tend to underpredict CF by 50-150% relative to the measurement average at low and middle levels over SGP. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near surface over the Arctic. The internal variability of CF simulated in ensemble runs with the same model is very minimal.

Qian, Yun; Long, Charles N.; Wang, Hailong; Comstock, Jennifer M.; McFarlane, Sally A.; Xie, Shaocheng

2012-02-17T23:59:59.000Z

172

CLOUD CHARACTERISTICS FROM DUAL WAVELENGTH MILLIMETREWAVE RADAR Robin J. Hogan , Anthony J. Illingworth and Henri Sauvageot +  

E-Print Network [OSTI]

­ veloping radar algorithms for measuring LWC is the ubiq­ uitous presence of occasional drizzle drops, which is clearly measurable even for vertically­pointing radars. The differential attenuation due to atmospheric and mean­sea­level pressure it has a (two­way) value of 1.0 dBkm 1 if the air is saturated. Measurements

Reading, University of

173

Environmental assessment for the Atmospheric Radiation Measurement (ARM) Program: Southern Great Plains Cloud and Radiation Testbed (CART) site  

SciTech Connect (OSTI)

The Atmospheric Radiation Measurement (ARM) Program is aimed at supplying improved predictive capability of climate change, particularly the prediction of cloud-climate feedback. The objective will be achieved by measuring the atmospheric radiation and physical and meteorological quantities that control solar radiation in the earth`s atmosphere and using this information to test global climate and related models. The proposed action is to construct and operate a Cloud and Radiation Testbed (CART) research site in the southern Great Plains as part of the Department of Energy`s Atmospheric Radiation Measurement Program whose objective is to develop an improved predictive capability of global climate change. The purpose of this CART research site in southern Kansas and northern Oklahoma would be to collect meteorological and other scientific information to better characterize the processes controlling radiation transfer on a global scale. Impacts which could result from this facility are described.

Policastro, A.J.; Pfingston, J.M.; Maloney, D.M.; Wasmer, F.; Pentecost, E.D.

1992-03-01T23:59:59.000Z

174

Radar-Derived Forecasts of Cloud-to-Ground Lightning Over Houston, Texas  

E-Print Network [OSTI]

,399 unique cells, and 1,028,510 to find the best lightning forecast criteria. Results show that using 30 dBZ at the -20 ?C isotherm on cells within 75 km of the radar that have been tracked for at least 2 consecutive scan produces the best forecasts... with a critical success index (CSI) of 0.71. The best VII predictor was 0.734 kg m-2 on cells within 75 km of the radar that have been tracked for at least 2 consecutive scans iv producing a CSI of 0.68. Results of this study further suggest...

Mosier, Richard Matthew

2011-02-22T23:59:59.000Z

175

Detection of supercooled liquid in mixedphase clouds using radar Doppler spectra  

E-Print Network [OSTI]

in the temperature range from 0 to -40°C, where both liquid and ice hydrometeor phases are sustainable of their hydrometeors (i.e., liquid or ice). Current cloud parameterizations that parti- tion water into liquid and ice 2010; published 1 October 2010. [1] Cloud phase identification from active remote sensors

Shupe, Matthew

176

Using Radar, Lidar and Radiometer Data from NSA and SHEBA to Quantify Cloud Property Effects on the Surface Heat Budget in the Arctic  

SciTech Connect (OSTI)

Cloud and radiation data from two distinctly different Arctic areas are analyzed to study the differences between coastal Alaskan and open Arctic Ocean region clouds and their respective influence on the surface radiation budget. The cloud and radiation datasets were obtained from (1) the DOE North Slope of Alaska (NSA) facility in the coastal town of Barrow, Alaska, and (2) the SHEBA field program, which was conducted from an icebreaker frozen in, and drifting with, the sea-ice for one year in the Western Arctic Ocean. Radar, lidar, radiometer, and sounding measurements from both locations were used to produce annual cycles of cloud occurrence and height, atmospheric temperature and humidity, surface longwave and shortwave broadband fluxes, surface albedo, and cloud radiative forcing. In general, both regions revealed a similar annual trend of cloud occurrence fraction with minimum values in winter (60-75%) and maximum values during spring, summer and fall (80-90%). However, the annual average cloud occurrence fraction for SHEBA (76%) was lower than the 6-year average cloud occurrence at NSA (92%). Both Arctic areas also showed similar annual cycle trends of cloud forcing with clouds warming the surface through most of the year and a period of surface cooling during the summer, when cloud shading effects overwhelm cloud greenhouse effects. The greatest difference between the two regions was observed in the magnitude of the cloud cooling effect (i.e., shortwave cloud forcing), which was significantly stronger at NSA and lasted for a longer period of time than at SHEBA. This is predominantly due to the longer and stronger melt season at NSA (i.e., albedo values that are much lower coupled with Sun angles that are somewhat higher) than the melt season observed over the ice pack at SHEBA. Longwave cloud forcing values were comparable between the two sites indicating a general similarity in cloudiness and atmospheric temperature and humidity structure between the two regions.

Janet Intrieri; Mathhew Shupe

2005-01-01T23:59:59.000Z

177

Toward a Diurnal Climatology of Cold-Season Turbulence Statistics in Continental Stratocumulus as Observed by the Atmospheric Radiation Millimeter- Wavelength Cloud Radars  

SciTech Connect (OSTI)

Numerous observational studies of marine stratocumulus have demonstrated a pronounced diurnal cycle. At night, longwave flux divergence at the top of the cloud drives negatively buoyant eddies that tend to keep the boundary layer well mixed. During the day, solar absorption by the cloud tends to reduce the turbulent intensity and often decouples the planetary boundary layer (PBL) into cloud- and sub-cloud circulations. The delicate balance between turbulent intensity, entrainment, and fluxes dictates cloud geometry and persistence, which can significantly impact the shortwave radiation budget. Millimeter-wavelength cloud radars (MMCRs) have been used to study the turbulent structure of boundary layer stratocumulus (e.g. Frisch et al. 1995; Kollias and Albrecht 2000). Analysis is confined to nondrizzling or lightly drizzling cloud systems for which precipitation contamination is negligible. Under such assumptions the Doppler velocity field becomes a proxy for vertical velocity. Prior research has mainly consisted of a few case studies of specific cloud systems using radar scan strategies optimized for this particular cloud type. The MMCR operating at the Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility is broadly configured to be able to detect many different cloud types over a broad range of reflectivities and altitudes, so it is not specifically optimized for PBL clouds. Being in more-or-less continuous operation since the end of 1996, it does, however, have the advantage of long data coverage, which suggests that statistically significant measures of the diurnal cycle of turbulence should be attainable. This abstract summarizes the first few steps toward this goal, using 7 months of cold season MMCR data.

Mechem, D.B.; Kogan, Y.L.; Childers, M.E.; Donner, K.M.

2005-03-18T23:59:59.000Z

178

Validation of Surface Retrieved Cloud Optical Properties with in situ Measurements at the Atmospheric Radiation Measurement Program (ARM) South Great Plains Site  

SciTech Connect (OSTI)

The surface inferred cloud optical properties from a multifilter rotating shadowband radiometer have been validated against the in situ measurements during the second ARM Enhanced Shortwave Experiment (ARESE II) field campaign at the ARM South Great Plains (SGP) site. On the basis of eight effective radius profiles measured by the in situ Forward Spectra Scattering Probe (FSSP), our retrieved cloud effective radii for single-layer warm water clouds agree well with in situ measurements, within 5.5%. The sensitivity study also illustrates that for this case a 13% uncertainty in observed liquid water path (LWP, 20 g/m2) results in 1.5% difference in retrieved cloud optical depth and 12.7% difference in referred cloud effective radius, on average. The uncertainty of the LWP measured by the microwave radiometer (MWR) is the major contributor to the uncertainty of retrieved cloud effective radius. Further, we conclude that the uncertainty of our inferred cloud optical properties is better than 5% for warm water clouds based on a surface closure study, in which cloud optical properties inferred from narrowband irradiances are applied to a shortwave model and the modeled broadband fluxes are compared to a surface pyranometer.

Min, Qilong; Duan, M.; Marchand, Roger T.

2003-09-11T23:59:59.000Z

179

ARM - Radar Backgrounder  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC :ProductsSCM Forcing Data DerivedInstruments Related Links

180

Cloud Computing as a Tool to Secure and Manage Information Flow in Swedish Armed Forces Networks.  

E-Print Network [OSTI]

??In the last few years cloud computing has created much hype in the IT world. It has provided new strategies to cut down costs and… (more)

Ali, Muhammad

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

ARM - SPARTICUS Planning - Data Plots  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band ARM Cloud Radar

182

Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia  

SciTech Connect (OSTI)

Ground-based radar and lidar observations obtained at the Department of Energy’s Atmospheric Radiation Measurement Program’s Tropical Western Pacific site located in Darwin, Australia are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar-lidar and two radar only algorithms) are compared by examining mean profiles and probability density functions of effective radius (Re), ice water content (IWC), extinction, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on the cloud radiative effect and radiative heating rates are presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which is attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes-large differences in cloud radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m-2 on average. These differences, which we believe are primarily driven by the uncertainty in Re, can cause up to 2 K/day difference in the radiative heating rates between algorithms.

Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.; Delanoe, Julien; Deng, Min

2013-05-22T23:59:59.000Z

183

On Deriving Vertical Air Motions from Cloud Radar Doppler Spectra MATTHEW D. SHUPE  

E-Print Network [OSTI]

on a statistical comparison of four cases comprising nearly 6 h of data. Turbulent dissipation rate comparisons multiple ground-based remote sensors. Corrections for Doppler spectrum broadening due to turbulence, wind the Department of Energy (DOE) Atmospheric Radiation Measurement Program's (ARM) site in Barrow, Alaska, during

184

Collaborative Research: ARM observations for the development and evaluation of models and parameterizations of cloudy boundary layers  

SciTech Connect (OSTI)

This is a collaborative project with Dr. Ping Zhu at Florida International University. It was designed to address key issues regarding the treatment of boundary layer cloud processes in climate models with UM’s research focusing on the analyses of ARM cloud radar observations from MMCR and WACR and FIU’s research focusing on numerical simulations of boundary layer clouds. This project capitalized on recent advancements in the ARM Millimeter Cloud Radar (MMCR) processing and the development of the WACR (at the SGP) to provide high temporal and spatial resolution Doppler cloud radar measurements for characterizing in-cloud turbulence, large-eddy circulations, and high resolution cloud structures of direct relevance to high resolution numerical modeling studies. The principal focus of the observational component of this collaborative study during this funding period was on stratocumulus clouds over the SGP site and fair-weather cumuli over the Nauru site. The statistical descriptions of the vertical velocity structures in continental stratocumulus clouds and in the Nauru shallow cumuli that are part of this study represents the most comprehensive observations of the vertical velocities in boundary layer clouds to date and were done in collaboration with Drs. Virendra Ghate and Pavlos Kollias.

Albrecht, Bruce,

2013-07-12T23:59:59.000Z

185

Application of Stochastic Radiative Transfer Theory to the ARM Cloud-Radiative Parameterization Problem  

SciTech Connect (OSTI)

This project had two primary goals: 1) development of stochastic radiative transfer as a parameterization that could be employed in an AGCM environment, and 2) exploration of the stochastic approach as a means for representing shortwave radiative transfer through mixed-phase layer clouds. To achieve these goals, an analysis of the performance of the stochastic approach was performed, a simple stochastic cloud-radiation parameterization for an AGCM was developed and tested, a statistical description of Arctic mixed phase clouds was developed and the appropriateness of stochastic approach for representing radiative transfer through mixed-phase clouds was assessed. Significant progress has been made in all of these areas and is detailed below.

Veron, Dana E

2009-03-12T23:59:59.000Z

186

Final Report - Satellite Calibration and Verification of Remotely Sensed Cloud and Radiation Properties Using ARM UAV Data (February 28, 1995 - February 28, 1998)  

SciTech Connect (OSTI)

The work proposed under this agreement was designed to validate and improve remote sensing of cloud and radiation properties in the atmosphere for climate studies with special emphasis on the use of satellites for monitoring these parameters to further the goals of the Atmospheric Radiation Measurement (ARM) Program.

Minnis, Patrick

1998-02-28T23:59:59.000Z

187

Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud  

E-Print Network [OSTI]

radiation calculations performed with an ice-free ocean orradiation calculations performed with an ice-free ocean orradiation. STREAMER calculations with the observed cloud, either over an ocean

Klein, Stephen A.

2009-01-01T23:59:59.000Z

188

Cloud Properties from Doppler Radar Spectra - a Growing Suite of Information Extraction Algorithms  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation Proposed New SubstationClean Communities of WesternVailCloisteredPresence offrom Doppler Radar

189

SGP and TWP (Manus) Ice Cloud Vertical Velocities  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Daily netcdf-files of ice-cloud dynamics observed at the ARM sites at SGP (Jan1997-Dec2010) and Manus (Jul1999-Dec2010). The files include variables at different time resolution (10s, 20min, 1hr). Profiles of radar reflectivity factor (dbz), Doppler velocity (vel) as well as retrieved vertical air motion (V_air) and reflectivity-weighted particle terminal fall velocity (V_ter) are given at 10s, 20min and 1hr resolution. Retrieved V_air and V_ter follow radar notation, so positive values indicate downward motion. Lower level clouds are removed, however a multi-layer flag is included.

Kalesse, Heike

190

SGP and TWP (Manus) Ice Cloud Vertical Velocities  

SciTech Connect (OSTI)

Daily netcdf-files of ice-cloud dynamics observed at the ARM sites at SGP (Jan1997-Dec2010) and Manus (Jul1999-Dec2010). The files include variables at different time resolution (10s, 20min, 1hr). Profiles of radar reflectivity factor (dbz), Doppler velocity (vel) as well as retrieved vertical air motion (V_air) and reflectivity-weighted particle terminal fall velocity (V_ter) are given at 10s, 20min and 1hr resolution. Retrieved V_air and V_ter follow radar notation, so positive values indicate downward motion. Lower level clouds are removed, however a multi-layer flag is included.

Kalesse, Heike

2013-06-27T23:59:59.000Z

191

ARM - PI Product - Cloud Properties and Radiative Heating Rates for TWP  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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192

Retrieval of optical and microphysical properties of ice clouds using Atmospheric Radiation Measurement (ARM) data  

E-Print Network [OSTI]

is based on a method proposed by Yang et al. (2005). The research examines single-layer ice clouds in the midlatitude and polar regions. The retrieved information in the midlatitudes is then verified using retrievals from the Moderate-resolution Imaging...

Kinney, Jacqueline Anne

2005-11-01T23:59:59.000Z

193

A Bootstrap Technique for Testing the Relationship Between Local-Scale Radar Observations of Cloud Occurrence and Large-Scale Atmospheric Fields  

SciTech Connect (OSTI)

In this paper an atmospheric classification scheme based on fields that are resolved by global climate models (and numerical weather prediction models) is investigated as a mechanism to map the large-scale (synoptic-scale) atmospheric state to distributions of local-scale cloud properties. Using a bootstrap resampling technique, the temporal stability and distinctness of vertical profiles of cloud occurrence (obtained from a vertically pointing millimeter wavelength cloud-radar) are analyzed as a function of the atmospheric state. A stable class-based map from the large-scale to local-scale cloud properties could be of great utility in the analysis of GCM-predicted cloud properties, by providing a physical context from which to understand any differences between the model output and observations, as well as to separate differences (in total distribution) that are caused by having different weather regimes (or synoptic scale activity) rather than problems in the representation of clouds for a particular regime. Furthermore, if sufficiently robust mappings can be established, it could form the basis of a statistical GCM cloud parameterization.

Marchand, Roger T.; Beagley, Nathaniel; Thompson, Sandra E.; Ackerman, Thomas P.; Schultz, David M.

2006-11-01T23:59:59.000Z

194

The Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured Fluxes and Lidar/Radar Profiles at SIRTA Atmospheric Observatory  

SciTech Connect (OSTI)

Ice clouds play a major role in the radiative energy budget of the Earth-atmosphere system (Liou 1986). Their radiative effect is governed primarily by the equilibrium between their albedo and greenhouse effects. Both macrophysical and microphysical properties of ice clouds regulate this equilibrium. For quantifying the effect of these clouds onto climate and weather systems, they must be properly characterized in atmospheric models. In this paper we use remote-sensing measurements from the SIRTA ground based atmospheric observatory (Site Instrumental de Recherche par Teledetection Atmospherique, http://sirta.lmd.polytechnique.fr). Lidar and radar observations taken over 18 months are used, in order to gain statistical confidence in the model evaluation. Along this period of time, 62 days are selected for study because they contain parts of ice clouds. We use the ''model to observations'' approach by simulating lidar and radar signals from MM5 outputs. Other more classical variables such as shortwave and longwave radiative fluxes are also used. Four microphysical schemes, among which that proposed by Reisner et al. (1998) with original or modified parameterizations of particle terminal fall velocities (Zurovac-Jevtic and Zhang 2003, Heymsfield and Donner 1990), and the simplified Dudhia (1989) scheme are evaluated in this study.

Chiriaco, M.; Vautard, R.; Chepfer, H.; Haeffelin, M.; Wanherdrick, Y.; Morille, Y.; Protat, A.; Dudhia, J.

2005-03-18T23:59:59.000Z

195

Atmospheric Radiation Measurement (ARM) Data from the Eastern North Atlantic Site (ENA), Graciosa Island, Azores  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

From May 2009 through December 2010, the ARM Mobile Facility obtained data from a location near the airport on Graciosa Island to support the Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) field campaign. The campaign was led by principal investigator Robert Wood. Results from this campaign confirmed that the Azores have the ideal mix of conditions to study how clouds, aerosols, and precipitation interact. This new observation site will have significant enhancements to instruments previously deployed to the Azores, including a Ka-/W-band scanning cloud radar, precipitation radar, and Doppler lidar. It has the full support of the Azorean government and collaborators at the University of the Azores. Los Alamos National Laboratory will operate the site for the ARM Facility.

Wood, Robert

196

ARM - PI Product - Cloud-Scale Vertical Velocity and Turbulent Dissipation  

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197

ARM - PI Product - SGP and TWP (Manus) Ice Cloud Vertical Velocities  

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198

Marine ARM GPCI Investigation of Clouds (MAGIC) Science Objectives and Significance  

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199

Validation of Cloud Properties Derived from GOES-9 Over the ARM TWP Region  

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200

ARM - Evaluation Product - MicroPulse LIDAR Cloud Optical Depth (MPLCOD)  

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We encourage you to perform a real-time search of NLEBeta
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201

ARM - Field Campaign - Ground-based Cloud Tomography Experiment at SGP  

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202

ARM - Field Campaign - MASRAD: Pt. Reyes Stratus Cloud and Drizzle Study  

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203

ARM - PI Product - MWR Retrievals of Cloud Liquid Water and Water Vapor  

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204

Cloud Properties and Radiative Heating Rates for TWP  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

Comstock, Jennifer

205

Cloud Properties and Radiative Heating Rates for TWP  

SciTech Connect (OSTI)

A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

Comstock, Jennifer

2013-11-07T23:59:59.000Z

206

Comparing Clouds Using Cloud Radar  

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207

FINAL REPORT FOR THE DOE/ARM PROJECT TITLED Representation of the Microphysical and Radiative Properties of Ice Clouds in SCMs and GCMs  

SciTech Connect (OSTI)

The broad goal of this research is to improve climate prediction through better representation of cirrus cloud microphysical and radiative properties in global climate models (GCMs). Clouds still represent the greatest source of uncertainty in climate prediction, and the representation of ice clouds is considerably more challenging than liquid water clouds. While about 40% of cloud condensate may be in the form of ice by some estimates, there have been no credible means of representing the ice particle size distribution and mass removal rates from ice clouds in GCMs. Both factors introduce large uncertainties regarding the global net flux, the latter factor alone producing a change of 10 W/m2 in the global net flux due to plausible changes in effective ice particle fallspeed. In addition, the radiative properties of ice crystals themselves are in question. This research provides GCMs with a credible means of representing the full (bimodal) ice particle size distribution (PSD) in ice clouds, including estimates of the small crystal (D < 65 microns) mode of the PSD. It also provides realistic estimates of mass sedimentation rates from ice clouds, which have a strong impact on their ice contents and radiative properties. This can be done through proper analysis of ice cloud microphysical data from ARM and other field campaigns. In addition, this research tests the ice cloud radiation treatment developed under two previous ARM projects by comparing it against laboratory measurements of ice cloud extinction efficiency and by comparing it with explicit theoretical calculations of ice crystal optical properties. The outcome of this project includes two PSD schemes for ice clouds; one appropriate for mid-latitude cirrus clouds and another for tropical anvil cirrus. Cloud temperature and ice water content (IWC) are the inputs for these PSD schemes, which are based on numerous PSD observations. The temperature dependence of the small crystal mode of the PSD for tropical anvils is opposite to that of mid-latitude cirrus, and this results in very different radiative properties for these two types of cirrus at temperatures less than about 50 C for a given ice water path. In addition, the representative PSD fall velocity is strongly influenced by the small crystal mode, and for temperatures less than 52 C, this fall velocity for mid-latitude cirrus is 2-8 times greater than for tropical anvil cirrus. Finally, the treatment of ice cloud optical properties was found to agree with laboratory measurements and exact theory within 15% for any given wavelength, PSD and ice particle shape. This treatment is analytical, formulated in terms of the PSD and ice particle shape properties. It thus provides the means for explicitly coupling the ice cloud microphysical and radiative properties, and can treat any combination of ice particle shape. It is very inexpensive regarding computer time. When these three deliverables were incorporated into the GCM at the National Center for Atmospheric Research (NCAR) under another project, it was found that the sunlight reflected and the amount of upwelling heat absorbed by cirrus clouds depended strongly on the PSD scheme used (i.e. mid-latitude or tropical anvil). This was largely due to the fall velocities associated with the two PSD schemes, although the PSD shape was also important.

Mitchell, David L.

2005-08-08T23:59:59.000Z

208

ARM: ARSCL: cloud boundaries from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

ARSCL: cloud boundaries from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

209

ARM: 10-minute Raman Lidar: aerosol depolarization profiles and single layer cloud optical depths from first Turner algorithm  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

10-minute Raman Lidar: aerosol depolarization profiles and single layer cloud optical depths from first Turner algorithm

Newsom, Rob; Goldsmith, John

210

ARM: ARSCL: cloud base height from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

ARSCL: cloud base height from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

211

ARM: Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.

Gaustad, Krista; Gaustad, Krista; McFarlane, Sally; McFarlane, Sally

212

Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models  

SciTech Connect (OSTI)

We examined cloud radar data in monsoon climates, using cloud radars at Darwin in the Australian monsoon, on a ship in the Bay of Bengal in the South Asian monsoon, and at Niamey in the West African monsoon. We followed on with a more in-depth study of the continental MCSs over West Africa. We investigated whether the West African anvil clouds connected with squall line MCSs passing over the Niamey ARM site could be simulated in a numerical model by comparing the observed anvil clouds to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model at high resolution using six different ice-phase microphysical schemes. We carried out further simulations with a cloud-resolving model forced by sounding network budgets over the Niamey region and over the northern Australian region. We have devoted some of the effort of this project to examining how well satellite data can determine the global breadth of the anvil cloud measurements obtained at the ARM ground sites. We next considered whether satellite data could be objectively analyzed to so that their large global measurement sets can be systematically related to the ARM measurements. Further differences were detailed between the land and ocean MCS anvil clouds by examining the interior structure of the anvils with the satellite-detected the CloudSat Cloud Profiling Radar (CPR). The satellite survey of anvil clouds in the Indo-Pacific region was continued to determine the role of MCSs in producing the cloud pattern associated with the MJO.

Houze, Jr., Robert A. [University of Washington Dept. of Atmospheric Sciences

2013-11-13T23:59:59.000Z

213

ARM - Cloud Memory  

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214

ARM - Cloud Twist  

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215

ARM - Cloud Word Seek  

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216

Fine-scale Horizontal Structure of Arctic Mixed-Phase Clouds.  

SciTech Connect (OSTI)

Recent in situ observations in stratiform clouds suggest that mixed phase regimes, here defined as limited cloud volumes containing both liquid and solid water, are constrained to narrow layers (order 100 m) separating all-liquid and fully glaciated volumes (Hallett and Viddaurre, 2005). The Department of Energy Atmospheric Radiation Measurement Program's (DOE-ARM, Ackerman and Stokes, 2003) North Slope of Alaska (NSA) ARM Climate Research Facility (ACRF) recently started collecting routine measurement of radar Doppler velocity power spectra from the Millimeter Cloud Radar (MMCR). Shupe et al. (2004) showed that Doppler spectra has potential to separate the contributions to the total reflectivity of the liquid and solid water in the radar volume, and thus to investigate further Hallett and Viddaurre's findings. The Mixed-Phase Arctic Cloud Experiment (MPACE) was conducted along the NSA to investigate the properties of Arctic mixed phase clouds (Verlinde et al., 2006). We present surface based remote sensing data from MPACE to discuss the fine-scale structure of the mixed-phase clouds observed during this experiment.

Rambukkange,M.; Verlinde, J.; Elorante, E.; Luke, E.; Kollias, P.; Shupe, M.

2006-07-10T23:59:59.000Z

217

Failure and Redemption of Multifilter Rotating Shadowband Radiometer (MFRSR)/Normal Incidence Multifilter Radiometer (NIMFR) Cloud Screening: Contrasting Algorithm Performance at Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) and Southern Great Plains (SGP) Sites  

SciTech Connect (OSTI)

Well-known cloud-screening algorithms, which are designed to remove cloud-contaminated aerosol optical depths (AOD) from AOD measurements, have shown great performance at many middle-to-low latitude sites around the world. However, they may occasionally fail under challenging observational conditions, such as when the sun is low (near the horizon) or when optically thin clouds with small spatial inhomogeneity occur. Such conditions have been observed quite frequently at the high-latitude Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) sites. A slightly modified cloud-screening version of the standard algorithm is proposed here with a focus on the ARM-supported Multifilter Rotating Shadowband Radiometer (MFRSR) and Normal Incidence Multifilter Radiometer (NIMFR) data. The modified version uses approximately the same techniques as the standard algorithm, but it additionally examines the magnitude of the slant-path line of sight transmittance and eliminates points when the observed magnitude is below a specified threshold. Substantial improvement of the multi-year (1999-2012) aerosol product (AOD and its Angstrom exponent) is shown for the NSA sites when the modified version is applied. Moreover, this version reproduces the AOD product at the ARM Southern Great Plains (SGP) site, which was originally generated by the standard cloud-screening algorithms. The proposed minor modification is easy to implement and its application to existing and future cloud-screening algorithms can be particularly beneficial for challenging observational conditions.

Kassianov, Evgueni I.; Flynn, Connor J.; Koontz, Annette S.; Sivaraman, Chitra; Barnard, James C.

2013-09-11T23:59:59.000Z

218

SGP Cloud and Land Surface Interaction Campaign (CLASIC): Measurement Platforms  

SciTech Connect (OSTI)

The Cloud and Land Surface Interaction Campaign (CLASIC) will be conducted from June 8 to June 30, 2007, at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. Data will be collected using eight aircraft equipped with a variety of specialized sensors, four specially instrumented surface sites, and two prototype surface radar systems. The architecture of CLASIC includes a high-altitude surveillance aircraft and enhanced vertical thermodynamic and wind profile measurements that will characterize the synoptic scale structure of the clouds and the land surface within the ACRF SGP site. Mesoscale and microscale structures will be sampled with a variety of aircraft, surface, and radar observations. An overview of the measurement platforms that will be used during the CLASIC are described in this report. The coordination of measurements, especially as it relates to aircraft flight plans, will be discussed in the CLASIC Implementation Plan.

MA Miller; R Avissar; LK Berg; SA Edgerton; ML Fischer; TJ Jackson; B. Kustas; PJ Lamb; G McFarquhar; Q Min; B Schmid; MS Torn; DD Tuner

2007-06-01T23:59:59.000Z

219

EnKF assimilation of high-resolution, mobile Doppler radar data of the 4 May 20071 Greensburg, Kansas supercell into a numerical cloud model2  

E-Print Network [OSTI]

, and low-level vortex strength and20 longevity.21 22 #12;2 1. Introduction1 Radar is one of few atmospheric routinely collected9 across most of the contiguous United States. The two measured radar variables mostEnKF assimilation of high-resolution, mobile Doppler radar data of the 4 May 20071 Greensburg

Xue, Ming

220

Validation of MODIS-Retrieved Cloud Fractions Using Whole Sky Imager Measurements at the Three ARM Sites  

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Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Parameterization and analysis of 3-D radiative transfer in clouds  

SciTech Connect (OSTI)

This report provides a summary of major accomplishments from the project. The project examines the impact of radiative interactions between neighboring atmospheric columns, for example clouds scattering extra sunlight toward nearby clear areas. While most current cloud models don�t consider these interactions and instead treat sunlight in each atmospheric column separately, the resulting uncertainties have remained unknown. This project has provided the first estimates on the way average solar heating is affected by interactions between nearby columns. These estimates have been obtained by combining several years of cloud observations at three DOE Atmospheric Radiation Measurement (ARM) Climate Research Facility sites (in Alaska, Oklahoma, and Papua New Guinea) with simulations of solar radiation around the observed clouds. The importance of radiative interactions between atmospheric columns was evaluated by contrasting simulations that included the interactions with those that did not. This study provides lower-bound estimates for radiative interactions: It cannot consider interactions in cross-wind direction, because it uses two-dimensional vertical cross-sections through clouds that were observed by instruments looking straight up as clouds drifted aloft. Data from new DOE scanning radars will allow future radiative studies to consider the full three-dimensional nature of radiative processes. The results reveal that two-dimensional radiative interactions increase overall day-and-night average solar heating by about 0.3, 1.2, and 4.1 Watts per meter square at the three sites, respectively. This increase grows further if one considers that most large-domain cloud simulations have resolutions that cannot specify small-scale cloud variability. For example, the increases in solar heating mentioned above roughly double for a fairly typical model resolution of 1 km. The study also examined the factors that shape radiative interactions between atmospheric columns and found that local effects were often much larger than the overall values mentioned above, and were especially large for high sun and near convective clouds such as cumulus. The study also found that statistical methods such as neural networks appear promising for enabling cloud models to consider radiative interactions between nearby atmospheric columns. Finally, through collaboration with German scientists, the project found that new methods (especially one called �stepwise kriging�) show great promise in filling gaps between cloud radar scans. If applied to data from the new DOE scanning cloud radars, these methods can yield large, continuous three-dimensional cloud structures for future radiative simulations.

Varnai, Tamas

2012-03-16T23:59:59.000Z

222

The ARM Climate Research Facility: A Review of Structure and Capabilities  

SciTech Connect (OSTI)

The Atmospheric Radiation Measurement (ARM) program (www.arm.gov) is a Department of Energy, Office of Science, climate research user facility that provides atmospheric observations from diverse climatic regimes around the world. Use of ARM data is free and available to anyone through the ARM data archive. ARM is approaching 20 years of operations. In recent years, the facility has grown to add two mobile facilities and an aerial facility to its network of fixed-location sites. Over the past year, ARM has enhanced its observational capabilities with a broad array of new instruments at its fixed and mobile sites and the aerial facility. Instruments include scanning millimeter- and centimeter-wavelength radars; water vapor, cloud/aerosol extinction, and Doppler lidars; a suite of aerosol instruments for measuring optical, physical, and chemical properties; instruments including eddy correlation systems to expand measurements of the surface and boundary layer; and aircraft probes for measuring cloud and aerosol properties. Taking full advantage of these instruments will involve the development of complex data products. This work is underway but will benefit from engagement with the broader scientific community. In this article we will describe the current status of the ARM program with an emphasis on developments over the past eight years since ARM was designated a DOE scientific user facility. We will also describe the new measurement capabilities and provide thoughts for how these new measurements can be used to serve the climate research community with an invitation to the community to engage in the development and use of these data products.

Mather, James H.; Voyles, Jimmy W.

2013-03-01T23:59:59.000Z

223

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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224

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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225

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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226

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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227

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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228

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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229

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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230

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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231

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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232

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar032875

233

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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234

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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235

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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236

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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237

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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238

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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239

The Microbase Value-Added Product: A Baseline Retrieval of Cloud Microphysical Properties  

SciTech Connect (OSTI)

This report describes the Atmospheric Radiation Measurement (ARM) Climate Research Facility baseline cloud microphysical properties (MICROBASE) value-added product (VAP). MICROBASE uses a combination of millimeter-wavelength cloud radar, microwave radiometer, and radiosonde observations to estimate the vertical profiles of the primary microphysical parameters of clouds including the liquid/ice water content and liquid/ice cloud particle effective radius. MICROBASE is a baseline algorithm designed to apply to most conditions and locations using a single set of parameterizations and a simple determination of water phase based on temperature. This document provides the user of this product with guidelines to assist in determining the accuracy of the product under certain conditions. Quality control flags are designed to identify outliers and indicate instances where the retrieval assumptions may not be met. The overall methodology is described in this report through a detailed description of the input variables, algorithms, and output products.

Dunn, M; Johnson, K; Jensen, M

2011-05-31T23:59:59.000Z

240

The Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured Fluxes and Lidar/Radar Profiles at the  

E-Print Network [OSTI]

to produce too much solid water (ice and snow) and not enough liquid water. 1. Introduction Ice clouds playThe Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured­NCAR Mesoscale Model (MM5) to simulate midlatitude ice clouds is evaluated. Model outputs are compared to long

Protat, Alain

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

ARM - About ARM  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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242

Using Surface Remote Sensors to Derive Radiative Characteristics of Mixed-Phase Clouds: An Example from M-PACE  

SciTech Connect (OSTI)

Measurements from ground-based cloud radar, high spectral resolution lidar and microwave radiometer are used in conjunction with a column version of the Rapid Radiative Transfer Model (RRTMG) and radiosonde measurements to derive the surface radiative properties under mixed-phase cloud conditions. These clouds were observed during the United States Department of Energy (US DOE) Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Clouds Experiment (M-PACE) between September and November of 2004. In total, sixteen half hour time periods are reviewed due to their coincidence with radiosonde launches. Cloud liquid (ice) water paths are found to range between 11.0-366.4 (0.5-114.1) gm-2, and cloud physical thicknesses fall between 286-2075 m. Combined with temperature and hydrometeor size estimates, this information is used to calculate surface radiative flux densities using RRTMG, which are demonstrated to generally agree with measured flux densities from surface-based radiometric instrumentation. Errors in longwave flux density estimates are found to be largest for thin clouds, while shortwave flux density errors are generally largest for thicker clouds. A sensitivity study is performed to understand the impact of retrieval assumptions and uncertainties on derived surface radiation estimates. Cloud radiative forcing is calculated for all profiles, illustrating longwave dominance during this time of year, with net cloud forcing generally between 50 and 90 Wm-2.

de Boer, Gijs; Collins, William D.; Menon, Surabi; Long, Charles N.

2011-12-02T23:59:59.000Z

243

ARM - Measurement - Cloud base height  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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244

ARM - Measurement - Cloud condensation nuclei  

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245

ARM - Measurement - Images of Clouds  

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246

ARM TR-047  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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247

Cloud Services Cloud Services  

E-Print Network [OSTI]

Cloud Services Cloud Services In 2012 UCD IT Services launched an exciting new set of cloud solutions called CloudEdu, which includes cloud servers, cloud storage, cloud hosting and cloud network. The CloudEdu package includes a consultancy service in design, deployment, management and utilisation

248

ARM: Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.

Gaustad, Krista; Gaustad, Krista; McFarlane, Sally; McFarlane, Sally

249

Parameterizing Size Distribution in Ice Clouds  

SciTech Connect (OSTI)

PARAMETERIZING SIZE DISTRIBUTIONS IN ICE CLOUDS David L. Mitchell and Daniel H. DeSlover ABSTRACT An outstanding problem that contributes considerable uncertainty to Global Climate Model (GCM) predictions of future climate is the characterization of ice particle sizes in cirrus clouds. Recent parameterizations of ice cloud effective diameter differ by a factor of three, which, for overcast conditions, often translate to changes in outgoing longwave radiation (OLR) of 55 W m-2 or more. Much of this uncertainty in cirrus particle sizes is related to the problem of ice particle shattering during in situ sampling of the ice particle size distribution (PSD). Ice particles often shatter into many smaller ice fragments upon collision with the rim of the probe inlet tube. These small ice artifacts are counted as real ice crystals, resulting in anomalously high concentrations of small ice crystals (D < 100 µm) and underestimates of the mean and effective size of the PSD. Half of the cirrus cloud optical depth calculated from these in situ measurements can be due to this shattering phenomenon. Another challenge is the determination of ice and liquid water amounts in mixed phase clouds. Mixed phase clouds in the Arctic contain mostly liquid water, and the presence of ice is important for determining their lifecycle. Colder high clouds between -20 and -36 oC may also be mixed phase but in this case their condensate is mostly ice with low levels of liquid water. Rather than affecting their lifecycle, the presence of liquid dramatically affects the cloud optical properties, which affects cloud-climate feedback processes in GCMs. This project has made advancements in solving both of these problems. Regarding the first problem, PSD in ice clouds are uncertain due to the inability to reliably measure the concentrations of the smallest crystals (D < 100 µm), known as the “small mode”. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of ice cloud optical properties formulated in terms of PSD parameters in combination with remote measurements of thermal radiances to characterize the small mode. This is possible since the absorption efficiency (Qabs) of small mode crystals is larger at 12 µm wavelength relative to 11 µm wavelength due to the process of wave resonance or photon tunneling more active at 12 µm. This makes the 12/11 µm absorption optical depth ratio (or equivalently the 12/11 µm Qabs ratio) a means for detecting the relative concentration of small ice particles in cirrus. Using this principle, this project tested and developed PSD schemes that can help characterize cirrus clouds at each of the three ARM sites: SGP, NSA and TWP. This was the main effort of this project. These PSD schemes and ice sedimentation velocities predicted from them have been used to test the new cirrus microphysics parameterization in the GCM known as the Community Climate Systems Model (CCSM) as part of an ongoing collaboration with NCAR. Regarding the second problem, we developed and did preliminary testing on a passive thermal method for retrieving the total water path (TWP) of Arctic mixed phase clouds where TWPs are often in the range of 20 to 130 g m-2 (difficult for microwave radiometers to accurately measure). We also developed a new radar method for retrieving the cloud ice water content (IWC), which can be vertically integrated to yield the ice water path (IWP). These techniques were combined to determine the IWP and liquid water path (LWP) in Arctic clouds, and hence the fraction of ice and liquid water. We have tested this approach using a case study from the ARM field campaign called M-PACE (Mixed-Phase Arctic Cloud Experiment). This research led to a new satellite remote sensing method that appears promising for detecting low levels of liquid water in high clouds typically between -20 and -36 oC. We hope to develop this method in future research.

DeSlover, Daniel; Mitchell, David L.

2009-09-25T23:59:59.000Z

250

ARM - ARM Logos  

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251

Ice Formation in Arctic Mixed-Phase Clouds: Insights from a 3-D Cloud-Resolving Model with Size-Resolved Aerosol and Cloud Microphysics  

SciTech Connect (OSTI)

The single-layer mixed-phase clouds observed during the Atmospheric Radiation Measurement (ARM) program’s Mixed-Phase Arctic Cloud Experiment (MPACE) are simulated with a 3-dimensional cloud-resolving model the System for Atmospheric Modeling (SAM) coupled with an explicit bin microphysics scheme and a radar-lidar simulator. Two possible ice enhancement mechanisms – activation of droplet evaporation residues by condensation-followed-by-freezing and droplet freezing by contact freezing inside-out, are scrutinized by extensive comparisons with aircraft and radar and lidar measurements. The locations of ice initiation associated with each mechanism and the role of ice nuclei (IN) in the evolution of mixed-phase clouds are mainly addressed. Simulations with either mechanism agree well with the in-situ and remote sensing measurements on ice microphysical properties but liquid water content is slightly underpredicted. These two mechanisms give very similar cloud microphysical, macrophysical, dynamical, and radiative properties, although the ice nucleation properties (rate, frequency and location) are completely different. Ice nucleation from activation of evaporation nuclei is most efficient near cloud top areas concentrated on the edges of updrafts, while ice initiation from the drop freezing process has no significant location preference (occurs anywhere that droplet evaporation is significant). Both enhanced nucleation mechanisms contribute dramatically to ice formation with ice particle concentration of 10-15 times higher relative to the simulation without either of them. The contribution of ice nuclei (IN) recycling from ice particle evaporation to IN and ice particle concentration is found to be very significant in this case. Cloud can be very sensitive to IN initially and form a nonquilibrium transition condition, but become much less sensitive as cloud evolves to a steady mixed-phase condition. The parameterization of Meyers et al. [1992] with the observed MPACE IN concentration is able to predict the observed mixed-phase clouds reasonably well. This validation may facilitate the application of this parameterization in the cloud and climate models to simulate Arctic clouds.

Fan, Jiwen; Ovtchinnikov, Mikhail; Comstock, Jennifer M.; McFarlane, Sally A.; Khain, Alexander

2009-02-27T23:59:59.000Z

252

The Mid-Latitude Continental Convective Clouds Experiment (MC3E)  

SciTech Connect (OSTI)

The Midlatitude Continental Convective Cloud Experiment (MC3E) will take place in central Oklahoma during the April-May 2011 period. The experiment is a collaborative effort between the U.S. Department of Energy Atmospheric Radition Measurement Program and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation program. The Intensive Observation Period leverages the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding. The overarching goal is to provide the most complete characterization of convective cloud systems, precipitation and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall observations over land that have never before been available. Several different components of convective processes tangible to the convective parameterization problem are targeted such as, pre-convective environment and convective initiation, updraft / downdraft dynamics, condensate transport and detrainment, precipitation and cloud microphysics, influence on the environment and radiation and a detailed description of the large-scale forcing. MC3E will use a new multi-scale observing strategy with the participation of a network of distributed sensors (both passive and active). The approach is to document in 3-D not only the full spectrum of precipitation rates, but also clouds, winds and moisture in an attempt to provide a holistic view of convective clouds and their feedback with the environment. A goal is to measure cloud and precipitation transitions and environmental quantities that are important for satellite retrieval algorithms, convective parameterization in large-scale models and cloud-resolving model simulations. This will be accomplished through the deployment of several different elements that complement the existing (and soon to become available) ARM facilities: a network of radiosonde stations, NASA scanning multi-frequency/parameter radar systems at three different frequencies (Ka/Ku/S), high-altitude remote sensing and in situ aircraft, wind profilers and a network of surface disdrometers. In addition to these special MC3E instruments, there will be important new instrumentation deployed by DOE at the ARM site including: 3 networked scanning X-band radar systems, a C-band scanning radar, a dual wavelength (Ka/W) scanning cloud radar, a Doppler lidar and upgraded vertically pointing millimeter cloud radar (MMCR) and micropulse lidar (MPL).To fully describe the properties of precipitating cloud systems, both in situ and remote sensing airborne observations are necessary. The NASA GPM-funded University of North Dakota (UND) Citation will provide in situ observations of precipitation-sized particles, ice freezing nuclei and aerosol concentrations. As a complement to the UND Citation's in situ observations, the NASA ER-2 will provide a high altitude satellite simulator platform that carrying a Ka/Ku band radar and passive microwave radiometers (10-183 GHZ).

Petersen,W.; Jensen,M.; Genio, A. D.; Giangrande, S.; Heymsfield, A.; Heymsfield, G.; Hou, A.; Kollias, P.; Orr, B.; Rutledge, S.; Schwaller, M.; Zipser, E.

2010-03-15T23:59:59.000Z

253

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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254

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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255

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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256

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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257

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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258

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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259

ARM - About ARM  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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260

ARM - ARM Data Integrator  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

ARM - ARM Safety Policy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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262

ARM - ARM Science Board  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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263

Final Report on the Development of an Improved Cloud Microphysical Product for Model and Remote Sensing Evaluation using RACORO Observations  

SciTech Connect (OSTI)

We proposed to analyze data collected during the Routine Aerial Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) in order to develop an integrated product of cloud microphysical properties (number concentration of drops in different size bins, total liquid drop concentration integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds bw, effective radius of water drops re, and radar reflectivity factor) that could be used to evaluate large-eddy simulations (LES), general circulation models (GCMs) and ground-based remote sensing retrievals, and to develop cloud parameterizations with the end goal of improving the modeling of cloud processes and properties and their impact on atmospheric radiation. We have completed the development of this microphysical database and have submitted it to ARM for consideration of its inclusion on the ARM database as a PI product. This report describes the development of this database, and also describes research that has been conducted on cloud-aerosol interactions using the data obtained during RACORO. A list of conference proceedings and publications is also included.

McFarquhar, Greg

2012-09-19T23:59:59.000Z

264

E-Print Network 3.0 - advanced precipitation radar Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

clutter Summary: of precipitation for every pixel in a Meteosat-8 scene. Via pixel-level image fusion of the radar data... and the Precipitating Clouds product, supervised...

265

EnKF Assimilation of High-Resolution, Mobile Doppler Radar Data of the 4 May 2007 Greensburg, Kansas, Supercell into a Numerical Cloud Model  

E-Print Network [OSTI]

Kalman filter (EnKF) technique into a non- hydrostatic, compressible numerical weather prediction model weather prediction (NWP) models to improve under- standing of convective storm dynamics is now a fairly, Kansas, Supercell into a Numerical Cloud Model ROBIN L. TANAMACHI,*,1,# LOUIS J. WICKER,@ DAVID C. DOWELL

Xue, Ming

266

Clouds, Aerosol, and Precipitation in the Marine Boundary Layer: Analysis of Results from the ARM Mobile Facility Deployment to the Azores (2009/2010)  

SciTech Connect (OSTI)

The project focuses upon dataset analysis and synthesis of datasets from the AMF deployment entitled “Clouds, Aerosols, and Precipitation in the Marine Boundary Layer (CAP?MBL)” at Graciosa Island in the Azores. Wood is serving a PI for this AMF deployment.

Wood, Robert [University of Washington, Dept of Atmos Sci

2013-05-31T23:59:59.000Z

267

Relationship between cloud radiative forcing, cloud fraction and cloud albedo, and new surface-based approach for determining cloud albedo  

SciTech Connect (OSTI)

This paper focuses on three interconnected topics: (1) quantitative relationship between surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo; (2) surface-based approach for measuring cloud albedo; (3) multiscale (diurnal, annual and inter-annual) variations and covariations of surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo. An analytical expression is first derived to quantify the relationship between cloud radiative forcing, cloud fraction, and cloud albedo. The analytical expression is then used to deduce a new approach for inferring cloud albedo from concurrent surface-based measurements of downwelling surface shortwave radiation and cloud fraction. High-resolution decade-long data on cloud albedos are obtained by use of this surface-based approach over the US Department of Energy's Atmospheric Radiaton Measurement (ARM) Program at the Great Southern Plains (SGP) site. The surface-based cloud albedos are further compared against those derived from the coincident GOES satellite measurements. The three long-term (1997-2009) sets of hourly data on shortwave cloud radiative forcing, cloud fraction and cloud albedo collected over the SGP site are analyzed to explore the multiscale (diurnal, annual and inter-annual) variations and covariations. The analytical formulation is useful for diagnosing deficiencies of cloud-radiation parameterizations in climate models.

Liu, Y.; Wu, W.; Jensen, M. P.; Toto, T.

2011-07-21T23:59:59.000Z

268

Use of ARM/NSA Data to Validate and Improve the Remote Sensing Retrieval of Cloud and Surface Properties in the Arctic from AVHRR Data  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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269

Kinematical relations among radar-observed water concentrations, vertical motions, and liquid-water drop-size spectra in convective clouds  

E-Print Network [OSTI]

of return settling are often cloudless or consist of cumulus clouds which have had their growth impeded. If conditions in the atmosphere are favorable, convection cells form and the updraft areas associated with these cells develop into cumulonimbus... and time, M & M(x, y, z, t). The x- and y-directions are horizontal and z-direction is positive toward the zenith. If the quantity M is conservative, the local rate of change at a fixed locality (the local change) can be represented by the following...

Runnels, Robert Clayton

1962-01-01T23:59:59.000Z

270

ARM - Site Instruments  

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271

ARM - Events Article  

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272

A Model Evaluation Data Set for the Tropical ARM Sites  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

This data set has been derived from various ARM and external data sources with the main aim of providing modelers easy access to quality controlled data for model evaluation. The data set contains highly aggregated (in time) data from a number of sources at the tropical ARM sites at Manus and Nauru. It spans the years of 1999 and 2000. The data set contains information on downward surface radiation; surface meteorology, including precipitation; atmospheric water vapor and cloud liquid water content; hydrometeor cover as a function of height; and cloud cover, cloud optical thickness and cloud top pressure information provided by the International Satellite Cloud Climatology Project (ISCCP).

Jakob, Christian

273

ARM Instrumentation  

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274

Atmospheric Rivers Coming to a Cloud Near You  

ScienceCinema (OSTI)

Learn about the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) field campaign in this short video. Ruby Leung, PNNL's lead scientist on this campaign's observational strategy to monitor precipitation.

Leung, Ruby

2014-06-12T23:59:59.000Z

275

Atmospheric Rivers Coming to a Cloud Near You  

SciTech Connect (OSTI)

Learn about the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) field campaign in this short video. Ruby Leung, PNNL's lead scientist on this campaign's observational strategy to monitor precipitation.

Leung, Ruby

2014-03-29T23:59:59.000Z

276

ARM Participation  

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277

ARM - ARM at AGU 2011  

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278

Comparison of Airborne and Spaceborne 95-GHz Radar Reflectivities and Evaluation of Multiple Scattering Effects in Spaceborne Measurements  

E-Print Network [OSTI]

of coincident measurements collected by an airborne 95-GHz radar during the African Monsoon Multidisci- plinary radar calibration is assessed. Collocated measurements of the spaceborne and airborne radars within the CloudSat measurements have to be corrected for this effect, if one wants to derive accurate level 2

Protat, Alain

279

Atmospheric Radiation Measurement (ARM) Data from the ARM Aerial Facility  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Atmospheric Radiation Measurement (ARM) Program is the largest global change research program supported by the U.S. Department of Energy. The primary goal of the ARM Program is to improve the treatment of cloud and radiation physics in global climate models in order to improve the climate simulation capabilities of these models. ARM data is collected both through permanent monitoring stations and field campaigns around the world. Airborne measurements required to answer science questions from researchers or to validate ground data are also collected. To find data from all categories of aerial operations, follow the links from the AAF information page at http://www.arm.gov/sites/aaf. Tables of information will provide start dates, duration, lead scientist, and the research site for each of the named campaigns. The title of a campaign leads, in turn, to a project description, contact information, and links to the data. Users will be requested to create a password, but the data files are free for viewing and downloading. The ARM Archive physically resides at the Oak Ridge National Laboratory.

280

ARM Climate Research Facility Annual Report 2005  

SciTech Connect (OSTI)

Through the ARM Program, the DOE funded the development of several highly instrumented ground stations for studying cloud formation processes and their influence on radiative transfer, and for measuring other parameters that determine the radiative properties of the atmosphere. This scientific infrastructure, and resultant data archive, is a valuable national and international asset for advancing scientific knowledge of Earth systems. In fiscal year (FY) 2003, the DOE designated ARM sites as a national scientific user facility: the ARM Climate Research (ACRF). The ACRF has enormous potential to contribute to a wide range interdisciplinary science in areas such as meteorology, atmospheric aerosols, hydrology, biogeochemical cycling, and satellite validation, to name only a few.

J. Voyles

2005-12-31T23:59:59.000Z

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

ARM - Acronyms  

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282

ARM - Article  

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283

Radiative Heating of the ISCCP Upper Level Cloud Regimes and its Impact on the Large-scale Tropical Circulation  

SciTech Connect (OSTI)

Radiative heating profiles of the International Satellite Cloud Climatology Project (ISCCP) cloud regimes (or weather states) were estimated by matching ISCCP observations with radiative properties derived from cloud radar and lidar measurements from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) sites at Manus, Papua New Guinea, and Darwin, Australia. Focus was placed on the ISCCP cloud regimes containing the majority of upper level clouds in the tropics, i.e., mesoscale convective systems (MCSs), deep cumulonimbus with cirrus, mixed shallow and deep convection, and thin cirrus. At upper levels, these regimes have average maximum cloud occurrences ranging from 30% to 55% near 12 km with variations depending on the location and cloud regime. The resulting radiative heating profiles have maxima of approximately 1 K/day near 12 km, with equal heating contributions from the longwave and shortwave components. Upper level minima occur near 15 km, with the MCS regime showing the strongest cooling of 0.2 K/day and the thin cirrus showing no cooling. The gradient of upper level heating ranges from 0.2 to 0.4 K/(day?km), with the most convectively active regimes (i.e., MCSs and deep cumulonimbus with cirrus) having the largest gradient. When the above heating profiles were applied to the 25-year ISCCP data set, the tropics-wide average profile has a radiative heating maximum of 0.45Kday-1 near 250 hPa. Column-integrated radiative heating of upper level cloud accounts for about 20% of the latent heating estimated by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The ISCCP radiative heating of tropical upper level cloud only slightly modifies the response of an idealized primitive equation model forced with the tropics-wide TRMM PR latent heating, which suggests that the impact of upper level cloud is more important to large-scale tropical circulation variations because of convective feedbacks rather than direct forcing by the cloud radiative heating profiles. However, the height of the radiative heating maxima and gradient of the heating profiles are important to determine the sign and patterns of the horizontal circulation anomaly driven by radiative heating at upper levels.

Li, Wei; Schumacher, Courtney; McFarlane, Sally A.

2013-01-31T23:59:59.000Z

284

Shipboard measurements of the cloud-capped marine boundary layer during FIRE/ASTEX  

SciTech Connect (OSTI)

Results are reported on measurements of the cloud-capped marine boundary layer during FIRE/ASTEX. A method was developed from the ASTEX dataset for measuring profiles of liquid water content, droplet size and concentration from cloud radar/microwave radiometer data in marine boundary layer clouds. Profiles were also determined from the first three moments of the Doppler spectrum measured in drizzle with the ETL cloud radar during ASTEX.

NONE

1997-09-01T23:59:59.000Z

285

ARM - Evaluation Product - ISCCP Cloud Data Around the ARM Sites  

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286

ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX):  

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287

ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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288

ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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289

ARM - Field Campaign - Marine ARM GPCI Investigation of Clouds (MAGIC)  

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290

ARM - Field Campaign - Marine ARM GPCI Investigation of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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291

ARM - Field Campaign - Marine ARM GPCI Investigation of Clouds (MAGIC):  

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292

ARM - Field Campaign - Marine ARM GPCI Investigation of Clouds (MAGIC):  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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293

ARM - Collaborations  

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294

ARM - Instrument -  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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295

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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296

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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297

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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298

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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299

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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300

ARM - Archive  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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302

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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303

ARM - Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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304

ARM - Blog  

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305

ARM - Brochures  

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306

ARM MJO Investigation Experiment on Gan Island (AMIE-Gan) Science Plan  

SciTech Connect (OSTI)

The overarching campaign, which includes the ARM Mobile Facility 2 (AMF2) deployment in conjunction with the Dynamics of the Madden-Julian Oscillation (DYNAMO) and the Cooperative Indian Ocean experiment on intraseasonal variability in the Year 2011 (CINDY2011) campaigns, is designed to test several current hypotheses regarding the mechanisms responsible for Madden-Julian Oscillation (MJO) initiation and propagation in the Indian Ocean area. The synergy between the proposed AMF2 deployment with DYNAMO/CINDY2011, and the corresponding funded experiment on Manus, combine for an overarching ARM MJO Investigation Experiment (AMIE) with two components: AMF2 on Gan Island in the Indian Ocean (AMIE-Gan), where the MJO initiates and starts its eastward propagation; and the ARM Manus site (AMIE-Manus), which is in the general area where the MJO usually starts to weaken in climate models. AMIE-Gan will provide measurements of particular interest to Atmospheric System Research (ASR) researchers relevant to improving the representation of MJO initiation in climate models. The framework of DYNAMO/CINDY2011 includes two proposed island-based sites and two ship-based locations forming a square pattern with sonde profiles and scanning precipitation and cloud radars at both island and ship sites. These data will be used to produce a Variational Analysis data set coinciding with the one produced for AMIE-Manus. The synergy between AMIE-Manus and AMIE-Gan will allow studies of the initiation, propagation, and evolution of the convective cloud population within the framework of the MJO. As with AMIE-Manus, AMIE-Gan/DYNAMO also includes a significant modeling component geared toward improving the representation of MJO initiation and propagation in climate and forecast models. This campaign involves the deployment of the second, marine-capable, AMF; all of the included measurement systems; and especially the scanning and vertically pointing radars. The campaign will include sonde launches at a rate of eight per day for the duration of the deployment. The increased sonde launches for the entire period matches that of the AMIE-Manus campaign and makes possible a far more robust Variational Analysis forcing data set product for the entire campaign, and thus better capabilities for modeling studies and synergistic research using the data from both AMIE sites.

Long, CL; Del Genio, A; Deng, M; Fu, X; Gustafson, W; Houze, R; Jakob, C; Jensen, M; Johnson, R; Liu, X; Luke, E; May, P; McFarlane, S; Minnis, P; Schumacher, C; Vogelmann, A; Wang, Y; Webster, P; Xie, S; Zhang, C

2011-04-11T23:59:59.000Z

307

ARM - ARM Operations Quarterly Reports  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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308

Evaluation of ground-based remotely sensed liquid water cloud properties using shortwave radiation measurements  

E-Print Network [OSTI]

properties of low level water clouds. A number of remote sensing retrieval techniques provide either radar-only retrie- vals or combine millimeter-wave radar with microwave radiometer measurements (Frisch et al., 1995 radiation measurements from the ground. The remote sensing observations of radar reflectivity, microwave

Haak, Hein

309

ARM - Collaborations  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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310

ARM - Collaborations  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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311

ARM - Collaborations  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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312

A census of precipitation features in the tropics using TRMM: radar, ice scattering, and lightning observations  

E-Print Network [OSTI]

and two ocean regions during August, September and October 1998, this study used radar retrievals and 85 GHz Polarization Corrected Temperatures (PCTs, which passively measure relative concentrations of precipitation-sized ice particles within a cloud...

Nesbitt, Stephen William

1999-01-01T23:59:59.000Z

313

ARM - Blog Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

, 2014 ARM Mobile Facility 2, BAECC, Blog, Field Notes AMF2 Arrives in Finland Bookmark and Share Editor's note: Mike Ritsche, technical operations manager for the ARM Mobile...

314

Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models  

SciTech Connect (OSTI)

This three-year project, in cooperation with Professor Bob Houze at University of Washington, has been successfully finished as planned. Both ARM (the Atmospheric Radiation Measurement Program) data and cloud-resolving model (CRM) simulations were used to identify the water budgets of clouds observed in two international field campaigns. The research results achieved shed light on several key processes of clouds in climate change (or general circulation models), which are summarized below. 1. Revealed the effect of mineral dust on mesoscale convective systems (MCSs) Two international field campaigns near a desert and a tropical coast provided unique data to drive and evaluate CRM simulations, which are TWP-ICE (the Tropical Warm Pool International Cloud Experiment) and AMMA (the African Monsoon Multidisciplinary Analysis). Studies of the two campaign data were contrasted, revealing that much mineral dust can bring about large MCSs via ice nucleation and clouds. This result was reported as a PI presentation in the 3rd ASR Science Team meeting held in Arlington, Virginia in March 2012. A paper on the studies was published in the Journal of the Atmospheric Sciences (Zeng et al. 2013). 2. Identified the effect of convective downdrafts on ice crystal concentration Using the large-scale forcing data from TWP-ICE, ARM-SGP (the Southern Great Plains) and other field campaigns, Goddard CRM simulations were carried out in comparison with radar and satellite observations. The comparison between model and observations revealed that convective downdrafts could increase ice crystal concentration by up to three or four orders, which is a key to quantitatively represent the indirect effects of ice nuclei, a kind of aerosol, on clouds and radiation in the Tropics. This result was published in the Journal of the Atmospheric Sciences (Zeng et al. 2011) and summarized in the DOE/ASR Research Highlights Summaries (see http://www.arm.gov/science/highlights/RMjY5/view). 3. Used radar observations to evaluate model simulations In cooperation with Profs. Bob Houze at University of Washington and Steven Rutledge at Colorado State University, numerical model results were evaluated with observations from W- and C-band radars and CloudSat/TRMM satellites. These studies exhibited some shortcomings of current numerical models, such as too little of thin anvil clouds, directing the future improvement of cloud microphysics parameterization in CRMs. Two papers of Powell et al (2012) and Zeng et al. (2013), summarizing these studies, were published in the Journal of the Atmospheric Sciences. 4. Analyzed the water budgets of MCSs Using ARM data from TWP-ICE, ARM-SGP and other field campaigns, the Goddard CRM simulations were carried out to analyze the water budgets of clouds from TWP-ICE and AMMA. The simulations generated a set of datasets on clouds and radiation, which are available http://cloud.gsfc.nasa.gov/. The cloud datasets were available for modelers and other researchers aiming to improve the representation of cloud processes in multi-scale modeling frameworks, GCMs and climate models. Special datasets, such as 3D cloud distributions every six minutes for TWP-ICE, were requested and generated for ARM/ASR investigators. Data server records show that 86,206 datasets were downloaded by 120 users between April of 2010 and January of 2012. 5. MMF simulations The Goddard MMF (multi-scale modeling framework) has been improved by coupling with the Goddard Land Information System (LIS) and the Goddard Earth Observing System Model, Version 5 (GOES5). It has also been optimized on NASA HEC supercomputers and can be run over 4000 CPUs. The improved MMF with high horizontal resolution (1 x 1 degree) is currently being applied to cases covering 2005 and 2006. The results show that the spatial distribution pattern of precipitation rate is well simulated by the MMF through comparisons with satellite retrievals from the CMOPRH and GPCP data sets. In addition, the MMF results were compared with three reanalyses (MERRA, ERA-Interim and CFSR). Although the MMF tends

Tao, Wei-Kuo; Houze, Robert, A., Jr.; Zeng, Xiping

2013-03-14T23:59:59.000Z

315

ARM - Field Campaign - ISDAC - NASA ARCTAS Coordination with ARM  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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316

Development and Comparison of Ground and Satellite-based Retrievals of Cirrus Cloud Physical Properties  

SciTech Connect (OSTI)

This report is the final update on ARM research conducted at DRI through May of 2006. A relatively minor amount of work was done after May, and last month (November), two journal papers partially funded by this project were published. The other investigator on this project, Dr. Bob d'Entremont, will be submitting his report in February 2007 when his no-cost extension expires. The main developments for this period, which concludes most of the DRI research on this project, are as follows: (1) Further development of a retrieval method for cirrus cloud ice particle effective diameter (De) and ice water path (IWP) using terrestrial radiances measured from satellites; (2) Revision and publication of the journal article 'Testing and Comparing the Modified Anomalous Diffraction Approximation'; and (3) Revision and publication of our radar retrieval method for IWC and snowfall rate.

Mitchell, David L

2009-10-14T23:59:59.000Z

317

ARM - Field Campaign - Spring Cloud IOP  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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318

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms  

SciTech Connect (OSTI)

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9th-10th October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and undersaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

Sednev, Igor; Sednev, I.; Menon, S.; McFarquhar, G.

2008-02-18T23:59:59.000Z

319

Simulating mixed-phase Arctic stratus clouds: Sensitivity to ice initiationmechanisms  

SciTech Connect (OSTI)

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during October 9th-10th, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-hour simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and subsaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

Sednev, I.; Menon, S.; McFarquhar, G.

2009-04-10T23:59:59.000Z

320

VALIDATION OF RAIN RATE RETRIEVALS FROM SEVIRI USING WEATHER RADAR OBSERVATIONS  

E-Print Network [OSTI]

and for improving parameterization cloud processes in numerical weather prediction (NWP) models or assimilation in these models. Although operational networks of Weather Radars are expanding over Europe and the United StatesVALIDATION OF RAIN RATE RETRIEVALS FROM SEVIRI USING WEATHER RADAR OBSERVATIONS R. A. Roebeling

Stoffelen, Ad

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321

Micropulse Lidar Cloud Mask Value-Added Product Technical Report  

SciTech Connect (OSTI)

Lidar backscattered signal is a useful tool for identifying vertical cloud structure in the atmosphere in optically thin clouds. Cloud boundaries derived from lidar signals are a necessary input for popular ARM data products, such as the Active Remote Sensing of Clouds (ARSCL) product. An operational cloud boundary algorithm (Wang and Sassen 2001) has been implemented for use with the ARM Micropulse Lidar (MPL) systems. In addition to retrieving cloud boundaries above 500 m, the value-added product (VAP) named Micropulse Lidar Cloud Mask (MPLCMASK) applies lidar-specific corrections (i.e., range-square, background, deadtime, and overlap) as described in Campbell et al. (2002) to the measured backscattered lidar. Depolarization ratio is computed using the methodology developed by Flynn et al. (2007) for polarization-capable MPL systems. The cloud boundaries output from MPLCMASK will be the primary lidar cloud mask for input to the ARSCL product and will be applied to all MPL systems, including historical data sets.

Sivaraman, C; Comstock, J

2011-07-25T23:59:59.000Z

322

Cloud Property Retrieval Products for Graciosa Island, Azores  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.

Dong, Xiquan

323

Cloud Property Retrieval Products for Graciosa Island, Azores  

SciTech Connect (OSTI)

The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.

Dong, Xiquan

2014-05-05T23:59:59.000Z

324

Cloud Processes: Insights over a Decade into the Links between  

E-Print Network [OSTI]

Cloud Resolving Models Satellite and radar data Field Campaigns Radar Simulators (image: C. McGee) Grid Diffuse Sensible heat flux Latent heat flux Latent heat flux Aerosol direct effects Incoming solar radiation Direct Diffuse Sensible heat flux SiB RAMS CO2 Fluxes: Photosynthesis Respiration CO2 Radiative

Collett Jr., Jeffrey L.

325

MMCR Calibration Report  

SciTech Connect (OSTI)

Calibration report for the Millimeter Wavelength Cloud Radar performed for the ARM Climate Research Facility by ProSensing Inc.

Mead, D

2010-03-23T23:59:59.000Z

326

The ARM unpiloted aerospace vehicle (UAV) program  

SciTech Connect (OSTI)

Unmanned aerospace vehicles (UAVs) are an important complement to the DOE`s Atmospheric Radiation Measurement (ARM) Program. ARM is primarily a ground-based program designed to extensively quantify the radiometric and meteorological properties of an atmospheric column. There is a need for airborne measurements of radiative profiles, especially flux at the tropopause, cloud properties, and upper troposphere water vapor. There is also a need for multi-day measurements at the tropopause; for example, in the tropics, at 20 km for over 24 hours. UAVs offer the greatest potential for long endurance at high altitudes and may be less expensive than piloted flights. 2 figs.

Sowle, D. [Mission Research Corporation, Santa Barbara, CA (United States)

1995-09-01T23:59:59.000Z

327

Performance limits for Synthetic Aperture Radar.  

SciTech Connect (OSTI)

The performance of a Synthetic Aperture Radar (SAR) system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to ''get your arms around'' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics, no matter how bright the engineer tasked to generate a system design. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall SAR system. For example, there are definite optimum frequency bands that depend on weather conditions and range, and minimum radar PRF for a fixed real antenna aperture dimension is independent of frequency. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the ''seek time''.

Doerry, Armin Walter

2006-02-01T23:59:59.000Z

328

ARM - Publications: Science Team Meeting Documents  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAn Assessment ofCloud StructureCloud Radiativean ImprovedARM

329

ARM - Publications: Science Team Meeting Documents  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAn Assessment ofCloud StructureCloudModeling Aerosols andARM

330

ARM - Publications: Science Team Meeting Documents  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAn Assessment ofCloudInteractions Between Clouds andUsing ARM

331

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1 Microphysical Characterization of Microwave Radar  

E-Print Network [OSTI]

.g., Meteosat sensors) are usually exploited for long-range trajectory tracking and for measuring low level measurements may be blocked by water and ice clouds at higher levels and their overall utility is reduced Radar Reflectivity Due to Volcanic Ash Clouds Frank Silvio Marzano, Senior Member, IEEE, Gianfranco

Rose, William I.

332

WACR Calibration Report  

SciTech Connect (OSTI)

Calibration report for the W-Band (95 GHz) ARM Cloud Radar performed for the ARM Climate Research Facility by ProSensing Inc.

Mead, D

2010-03-23T23:59:59.000Z

333

The DOE ARM Aerial Facility  

SciTech Connect (OSTI)

The Department of Energy Atmospheric Radiation Measurement (ARM) Program is a climate research user facility operating stationary ground sites that provide long-term measurements of climate relevant properties, mobile ground- and ship-based facilities to conduct shorter field campaigns (6-12 months), and the ARM Aerial Facility (AAF). The airborne observations acquired by the AAF enhance the surface-based ARM measurements by providing high-resolution in-situ measurements for process understanding, retrieval-algorithm development, and model evaluation that are not possible using ground- or satellite-based techniques. Several ARM aerial efforts were consolidated into the AAF in 2006. With the exception of a small aircraft used for routine measurements of aerosols and carbon cycle gases, AAF at the time had no dedicated aircraft and only a small number of instruments at its disposal. In this "virtual hangar" mode, AAF successfully carried out several missions contracting with organizations and investigators who provided their research aircraft and instrumentation. In 2009, AAF started managing operations of the Battelle-owned Gulfstream I (G-1) large twin-turboprop research aircraft. Furthermore, the American Recovery and Reinvestment Act of 2009 provided funding for the procurement of over twenty new instruments to be used aboard the G-1 and other AAF virtual-hangar aircraft. AAF now executes missions in the virtual- and real-hangar mode producing freely available datasets for studying aerosol, cloud, and radiative processes in the atmosphere. AAF is also engaged in the maturation and testing of newly developed airborne sensors to help foster the next generation of airborne instruments.

Schmid, Beat; Tomlinson, Jason M.; Hubbe, John M.; Comstock, Jennifer M.; Mei, Fan; Chand, Duli; Pekour, Mikhail S.; Kluzek, Celine D.; Andrews, Elisabeth; Biraud, S.; McFarquhar, Greg

2014-05-01T23:59:59.000Z

334

ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The ARM CMBE-CLDRAD [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected cloud and radiation relevant quantities from ACRF observations

McCoy, Renata; Xie, Shaocheng

335

Evaluation of convection-permitting model simulations of cloud populations associated with the Madden-Julian Oscillation using data collected during the AMIE/DYNAMO field campaign  

SciTech Connect (OSTI)

Regional cloud permitting model simulations of cloud populations observed during the 2011 ARM Madden Julian Oscillation Investigation Experiment/ Dynamics of Madden-Julian Experiment (AMIE/DYNAMO) field campaign are evaluated against radar and ship-based measurements. Sensitivity of model simulated surface rain rate statistics to parameters and parameterization of hydrometeor sizes in five commonly used WRF microphysics schemes are examined. It is shown that at 2 km grid spacing, the model generally overestimates rain rate from large and deep convective cores. Sensitivity runs involving variation of parameters that affect rain drop or ice particle size distribution (more aggressive break-up process etc) generally reduce the bias in rain-rate and boundary layer temperature statistics as the smaller particles become more vulnerable to evaporation. Furthermore significant improvement in the convective rain-rate statistics is observed when the horizontal grid-spacing is reduced to 1 km and 0.5 km, while it is worsened when run at 4 km grid spacing as increased turbulence enhances evaporation. The results suggest modulation of evaporation processes, through parameterization of turbulent mixing and break-up of hydrometeors may provide a potential avenue for correcting cloud statistics and associated boundary layer temperature biases in regional and global cloud permitting model simulations.

Hagos, Samson M.; Feng, Zhe; Burleyson, Casey D.; Lim, Kyo-Sun; Long, Charles N.; Wu, Di; Thompson, Gregory

2014-11-12T23:59:59.000Z

336

ARM Climate Research Facility Annual Report 2004  

SciTech Connect (OSTI)

Like a rock that slowly wears away beneath the pressure of a waterfall, planet earth?s climate is almost imperceptibly changing. Glaciers are getting smaller, droughts are lasting longer, and extreme weather events like fires, floods, and tornadoes are occurring with greater frequency. Why? Part of the answer is clouds and the amount of solar radiation they reflect or absorb. These two factors clouds and radiative transfer represent the greatest source of error and uncertainty in the current generation of general circulation models used for climate research and simulation. The U.S. Global Change Research Act of 1990 established an interagency program within the Executive Office of the President to coordinate U.S. agency-sponsored scientific research designed to monitor, understand, and predict changes in the global environment. To address the need for new research on clouds and radiation, the U.S. Department of Energy (DOE) established the Atmospheric Radiation Measurement (ARM) Program. As part of the DOE?s overall Climate Change Science Program, a primary objective of the ARM Program is improved scientific understanding of the fundamental physics related to interactions between clouds and radiative feedback processes in the atmosphere.

Voyles, J.

2004-12-31T23:59:59.000Z

337

PROGRESS REPORT OF FY 2004 ACTIVITIES: IMPROVED WATER VAPOR AND CLOUD RETRIEVALS AT THE NSA/AAO  

SciTech Connect (OSTI)

The basic goals of the research are to develop and test algorithms and deploy instruments that improve measurements of water vapor, cloud liquid, and cloud coverage, with a focus on the Arctic conditions of cold temperatures and low concentrations of water vapor. The importance of accurate measurements of column amounts of water vapor and cloud liquid has been well documented by scientists within the Atmospheric Radiation Measurement Program. Although several technologies have been investigated to measure these column amounts, microwave radiometers (MWR) have been used operationally by the ARM program for passive retrievals of these quantities: precipitable water vapor (PWV) and integrated water liquid (IWL). The technology of PWV and IWL retrievals has advanced steadily since the basic 2-channel MWR was first deployed at ARM CART sites Important advances are the development and refinement of the tipcal calibration method [1,2], and improvement of forward model radiative transfer algorithms [3,4]. However, the concern still remains that current instruments deployed by ARM may be inadequate to measure low amounts of PWV and IWL. In the case of water vapor, this is especially important because of the possibility of scaling and/or quality control of radiosondes by the water amount. Extremely dry conditions, with PWV less than 3 mm, commonly occur in Polar Regions during the winter months. Accurate measurements of the PWV during such dry conditions are needed to improve our understanding of the regional radiation energy budgets. The results of a 1999 experiment conducted at the ARM North Slope of Alaska/Adjacent Arctic Ocean (NSA/AAO) site during March of 1999 [5] have shown that the strength associated with the 183 GHz water vapor absorption line makes radiometry in this frequency regime suitable for measuring low amounts of PWV. As a portion of our research, we conducted another millimeter wave radiometric experiment at the NSA/AAO in March-April 2004. This experiment relied heavily on our experiences of the 1999 experiment. Particular attention was paid to issues of radiometric calibration and radiosonde intercomparisons. Our theoretical and experimental work also supplements efforts by industry (F. Solheim, Private Communication) to develop sub-millimeter radiometers for ARM deployment. In addition to quantitative improvement of water vapor measurements at cold temperature, the impact of adding millimeter-wave window channels to improve the sensitivity to arctic clouds was studied. We also deployed an Infrared Cloud Imager (ICI) during this experiment, both for measuring continuous day-night statistics of the study of cloud coverage and identifying conditions suitable for tipcal analysis. This system provided the first capability of determining spatial cloud statistics continuously in both day and night at the NSA site and has been used to demonstrate that biases exist in inferring cloud statistics from either zenith-pointing active sensors (lidars or radars) or sky imagers that rely on scattered sunlight in daytime and star maps at night [6].

E. R. Westwater; V. V. Leuskiy; M. Klein; A. J. Gasiewski; and J. A. Shaw

2004-11-01T23:59:59.000Z

338

Sandia National Laboratories: Radar Friendly Blades  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

MitigationRadar Friendly Blades Radar Friendly Blades Some wind farms have the potential to cause interference with the normal operation of radar systems used for security, weather...

339

TROPICAL CLOUD LIFE CYCLE AND OVERLAP STRUCTURE A. M. Vogelmann, M. P. Jensen, P. Kollias, and E. Luke  

E-Print Network [OSTI]

TROPICAL CLOUD LIFE CYCLE AND OVERLAP STRUCTURE A. M. Vogelmann, M. P. Jensen, P. Kollias, and E.bnl.gov ABSTRACT The profile of cloud microphysical properties and how the clouds are overlapped within a vertical simulations. We will present how cloud microphysical properties and overlap structure retrieved at the ARM

340

Tornado identification from analyses of digital radar data  

E-Print Network [OSTI]

of Yukon, 40 km north- west of NSSL. Later, a cell to the northwest of Oklahoma City developed to str'ong intensity and a funnel cloud was reported over Tinker AFB at 1930 CST. Hist~or of the Yukon Storm During the afternoon, the squall line moved... signature 1n analyses of digital radar data from ceni;ra 1 Oklahoma during the Spring. The data were collected by the l0-cm WSR-57 radar at the National Severe S torms Laboratory at Ilorman, Oklahoma. Three types of numerical analyses were used in th1s...

Pittman, Donald Wayne

2012-06-07T23:59:59.000Z

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they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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341

Atmospheric Radiation Measurement (ARM) Data from Specific Instruments Used in the ARM Program  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

ARM is known for its comprehensive set of world-class, and in some cases, unique, instruments available for use by the global scientific community. In addition to the ARM instruments, the ARM Climate Research Facility identifies and acquires a wide variety of data including model, satellite, and surface data, from "external instruments," to augment the data being generated within the program. External instruments belong to organizations that are outside of the ARM Program. Field campaign instruments are another source of data used to augment routine observations. The huge archive of ARM data can be organized by instrument categories into twelve "collections:" Aerosols, Airborne Observations, Atmospheric Carbon, Atmospheric Profiling, Cloud Properties, Derived Quantities and Models, Ocean Observations, Radiometric, Satellite Observations, Surface Meteorology, Surface/Subsurface Properties, and Other. Clicking on one of the instrument categories leads to a page that breaks that category down into sub-categories. For example, "Atmospheric Profiling" is broken down into ARM instruments (with 11 subsets), External Instruments (with 6 subsets), and Field Campaign Instruments (with 42 subsets). Each of the subset links, in turn, leads to detailed information pages and links to specific data streams. Users will be requested to create a password, but the data files are free for viewing and downloading.

342

Atmospheric Radiation Measurement Program Science Plan Current Status and Future Directions of the ARM Science Program  

SciTech Connect (OSTI)

The Atmospheric Radiation Measurement (ARM) Program has matured into one of the key programs in the U.S. Climate Change Science Program. The ARM Program has achieved considerable scientific success in a broad range of activities, including site and instrument development, atmospheric radiative transfer, aerosol science, determination of cloud properties, cloud modeling, and cloud parameterization testing and development. The focus of ARM science has naturally shifted during the last few years to an increasing emphasis on modeling and parameterization studies to take advantage of the long time series of data now available. During the next 5 years, the principal focus of the ARM science program will be to: • Maintain the data record at the fixed ARM sites for at least the next five years. • Improve significantly our understanding of and ability to parameterize the 3-D cloud-radiation problem at scales from the local atmospheric column to the global climate model (GCM) grid square. • Continue developing techniques to retrieve the properties of all clouds, with a special focus on ice clouds and mixed-phase clouds. • Develop a focused research effort on the indirect aerosol problem that spans observations, physical models, and climate model parameterizations. • Implement and evaluate an operational methodology to calculate broad-band heating rates in the atmospheric columns at the ARM sites. • Develop and implement methodologies to use ARM data more effectively to test atmospheric models, both at the cloud-resolving model scale and the GCM scale. • Use these methodologies to diagnose cloud parameterization performance and then refine these parameterizations to improve the accuracy of climate model simulations. In addition, the ARM Program is actively developing a new ARM Mobile Facility (AMF) that will be available for short deployments (several months to a year or more) in climatically important regions. The AMF will have much of the same instrumentation as the remote facilities at ARM’s Tropical Western Pacific and the North Slope of Alaska sites. Over time, this new facility will extend ARM science to a much broader range of conditions for model testing.

TP Ackerman; AD Del Genio; RG Ellingson; RA Ferrare; SA Klein; GM McFarquhar; PJ Lamb; CN Long; J Verlinde

2004-10-30T23:59:59.000Z

343

ARM - Evaluation Product - Corrected Precipitation Radar Moments in Antenna  

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344

ARM - Field Campaign - 2001 Multi-Frequency Radar IOP  

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345

Properties of tropical convection observed by ARM millimeter-radars  

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346

Downhole pulse radar  

DOE Patents [OSTI]

A borehole logging tool generates a fast rise-time, short duration, high peak-power radar pulse having broad energy distribution between 30 MHz and 300 MHz through a directional transmitting and receiving antennas having barium titanate in the electromagnetically active region to reduce the wavelength to within an order of magnitude of the diameter of the antenna. Radar returns from geological discontinuities are sampled for transmission uphole. 7 figs.

Chang, Hsi-Tien

1987-09-28T23:59:59.000Z

347

Planning Single-arm Manipulations with N-Arm Robots  

E-Print Network [OSTI]

Planning Single-arm Manipulations with N-Arm Robots Benjamin Cohen bcohen@seas.upenn.edu University@cs.cmu.edu Carnegie Mellon University Abstract--Many robotic systems are comprised of two or more arms. Such systems robotic arms. While the use of multiple arms increases the pro- ductivity of the system and extends

Guestrin, Carlos

348

Cloud Computing  

SciTech Connect (OSTI)

Chicago Matters: Beyond Burnham (WTTW). Chicago has become a world center of "cloud computing." Argonne experts Pete Beckman and Ian Foster explain what "cloud computing" is and how you probably already use it on a daily basis.

Pete Beckman and Ian Foster

2009-12-04T23:59:59.000Z

349

ARM - Evaluation Product - ARM Navigation Best Estimate 10 Hz (NAVBE) and  

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350

Atmospheric State, Cloud Microphysics and Radiative Flux  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates for the ARM Southern Great Plains (SGP) site. The data represent a characterization of the physical state of the atmospheric column compiled on a five-minute temporal and 90m vertical grid. Sources for this information include raw measurements, cloud property and radiative retrievals, retrievals and derived variables from other third-party sources, and radiative calculations using the derived quantities.

Mace, Gerald

351

Armed With A Heart.  

E-Print Network [OSTI]

?? This paper thoroughly examines the production of the thesis short film, Armed With A Heart, from conception to completion. Each area of the film's… (more)

Horton, Willie Charles, Jr.

2009-01-01T23:59:59.000Z

352

ARM Mobile Facilities  

ScienceCinema (OSTI)

This video provides an overview of the ARM Mobile Facilities, two portable climate laboratories that can deploy anywhere in the world for campaigns of at least six months.

Orr, Brad; Coulter, Rich

2014-09-15T23:59:59.000Z

353

Combined CloudSatCALIPSOMODIS retrievals of the properties of ice clouds  

E-Print Network [OSTI]

March 2010; published 21 July 2010. [1] In this paper, data from spaceborne radar, lidar and infrared radiometers on the "ATrain" of satellites are combined in a variational algorithm to retrieve ice cloud the impact of the microphysical assumptions on the algorithm when radiances are not assimilated by evaluating

Hogan, Robin

354

Determination of cloud liquid water distribution using 3D cloud tomography  

E-Print Network [OSTI]

, but they provide a less direct measurement of cloud water content (since radar reflectivity depends strongly, the number of scanning angles, the radiometer characteristics (e.g., noise level, beam width), the physical accuracy. For a setup consisting of four microwave radiometers of typical noise level 0.3 K, the tomography

355

Retrievals of Cloud Fraction and Cloud Albedo from Surface-based Shortwave Radiation Measurements: A Comparison of 16 Year Measurements  

SciTech Connect (OSTI)

Ground-based radiation measurements have been widely conducted to gain information on clouds and the surface radiation budget; here several different techniques for retrieving cloud fraction (Long2006, Min2008 and XL2013) and cloud albedo (Min2008, Liu2011 and XL2013) from ground-based shortwave broadband and spectral radiation measurements are examined, and sixteen years of retrievals collected at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are compared. The comparison shows overall good agreement between the retrievals of both cloud fraction and cloud albedo, with noted differences however. The Long2006 and Min2008 cloud fractions are greater on average than the XL2013 values. Compared to Min2008 and Liu2011, the XL2013 retrieval of cloud albedo tends to be greater for thin clouds but smaller for thick clouds, with the differences decreasing with increasing cloud fraction. Further analysis reveals that the approaches that retrieve cloud fraction and cloud albedo separately may suffer from mutual contamination of errors in retrieved cloud fraction and cloud albedo. Potential influences of cloud absorption, land-surface albedo, cloud structure, and measurement instruments are explored.

Xie, Yu; Liu, Yangang; Long, Charles N.; Min, Qilong

2014-07-27T23:59:59.000Z

356

ARM - ARM Mobile Facility 1 Article  

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357

ARM - ARM Recovery Act Project FAQs  

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358

Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals  

SciTech Connect (OSTI)

Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files are available for manually-selected, stratiform, mixed-phase cloud cases observed at the North Slope of Alaska (NSA) site during periods covering the Mixed-Phase Arctic Cloud Experiment (MPACE, late September through early November 2004) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC, April-early May 2008). These time periods will be expanded in a future submission.

Shupe, Matthew

2013-05-22T23:59:59.000Z

359

Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files are available for manually-selected, stratiform, mixed-phase cloud cases observed at the North Slope of Alaska (NSA) site during periods covering the Mixed-Phase Arctic Cloud Experiment (MPACE, late September through early November 2004) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC, April-early May 2008). These time periods will be expanded in a future submission.

Shupe, Matthew

360

Tropical Cloud Properties and Radiative Heating Profiles  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

We have generated a suite of products that includes merged soundings, cloud microphysics, and radiative fluxes and heating profiles. The cloud microphysics is strongly based on the ARM Microbase value added product (Miller et al., 2003). We have made a few changes to the microbase parameterizations to address issues we observed in our initial analysis of the tropical data. The merged sounding product is not directly related to the product developed by ARM but is similar in that it uses the microwave radiometer to scale the radiosonde column water vapor. The radiative fluxes also differ from the ARM BBHRP (Broadband Heating Rate Profile) product in terms of the radiative transfer model and the sampling interval.

Mather, James

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Torras: Robot Arm Control 1 Robot Arm Control  

E-Print Network [OSTI]

Torras: Robot Arm Control 1 Robot Arm Control Carme Torras Institut de Rob#18;otica i Inform#18;atica Industrial (CSIC-UPC) Llorens i Artigas 4-6, 08028-Barcelona. RUNNING HEAD: Robot Arm Control: 34-93-401.57.50 e-mail: ctorras@iri.upc.es #12; Torras: Robot Arm Control 2 INTRODUCTION A robot

Torras, Carme

362

Cloud Computing.  

E-Print Network [OSTI]

?? Cloud computing has been given a great deal of attention during recent years. Almost all the technology market leaders and leading hosting service providers… (more)

Siddiqui, Muhammad Anas

2013-01-01T23:59:59.000Z

363

ARM - Publications: Science Team Meeting Documents  

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364

ARM - Publications: Science Team Meeting Documents  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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365

ARM - Field Campaign - Fall 1997 Shortwave IOP  

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366

ARM - Field Campaign - Fall 1997 UAV IOP  

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367

ARM - Field Campaign - Fall 2002 SCM IOP  

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368

ARM - Field Campaign - ISDAC - Hemispheric Flux Spectroradiometer  

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369

ARM Climate Research Facility  

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370

ARM Climate Research Facility  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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371

ARM Climate Research Facility  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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372

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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373

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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374

ARM Water Vapor IOP  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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375

ARM XDC Datastreams  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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376

ARM XDC Datastreams  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62ARM Water

377

ARM XDC Datastreams  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62ARM

378

Contribution to the development of DOE ARM Climate Modeling Best Estimate Data (CMBE) products: Satellite data over the ARM permanent and AMF sites: Final Report  

SciTech Connect (OSTI)

To support the LLNL ARM infrastructure team Climate Modeling Best Estimate (CMBE) data development, the University of North Dakota (UND)'s group will provide the LLNL team the NASA CERES and ISCCP satellite retrieved cloud and radiative properties for the periods when they are available over the ARM permanent research sites. The current available datasets, to date, are as follows: the CERES/TERRA during 200003-200812; the CERES/AQUA during 200207-200712; and the ISCCP during 199601-200806. The detailed parameters list below: (1) CERES Shortwave radiative fluxes (net and downwelling); (2) CERES Longwave radiative fluxes (upwelling) - (items 1 & 2 include both all-sky and clear-sky fluxes); (3) CERES Layered clouds (total, high, middle, and low); (4) CERES Cloud thickness; (5) CERES Effective cloud height; (6) CERES cloud microphysical/optical properties; (7) ISCCP optical depth cloud top pressure matrix; (8) ISCCP derived cloud types (r.g., cirrus, stratus, etc.); and (9) ISCCP infrared derived cloud top pressures. (10) The UND group shall apply necessary quality checks to the original CERES and ISCCP data to remove suspicious data points. The temporal resolution for CERES data should be all available satellite overpasses over the ARM sites; for ISCCP data, it should be 3-hourly. The spatial resolution is the closest satellite field of view observations to the ARM surface sites. All the provided satellite data should be in a format that is consistent with the current ARM CMBE dataset so that the satellite data can be easily merged into the CMBE dataset.

Xie, B; Dong, X; Xie, S

2012-05-18T23:59:59.000Z

379

DOE/SC-ARM-12-006 ARM Climate Research Facility Radar Operations Plan  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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380

DOE/SC-ARM-12-009 ARM Radar Organization JW Voyles  

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Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

DOE/SC-ARM-12-010 Science Goals for the ARM Recovery Act Radars  

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382

Science Plan for the Atmospheric Radiation Measurement Program (ARM)  

SciTech Connect (OSTI)

The purpose of this Atmospheric Radiation Measurement (ARM) Science Plan is to articulate the scientific issues driving the ARM Program, and to relate them to DOE`s programmatic objectives for ARM, based on the experience and scientific progress gained over the past five years. ARM programmatic objectives are to: (1) Relate observed radiative fluxes and radiances in the atmosphere, spectrally resolved and as a function of position and time, to the temperature and composition of the atmosphere, specifically including water vapor and clouds, and to surface properties, and sample sufficient variety of situations so as to span a wide range of climatologically relevant possibilities; (2) develop and test parameterizations that can be used to accurately predict the radiative properties and to model the radiative interactions involving water vapor and clouds within the atmosphere, with the objective of incorporating these parameterizations into general circulation models. The primary observational methods remote sending and other observations at the surface, particularly remote sensing of clouds, water vapor and aerosols.

NONE

1996-02-01T23:59:59.000Z

383

Testbed model and data assimilation for ARM  

SciTech Connect (OSTI)

The objectives of this contract are to further develop and test the ALFA (AER Local Forecast and Assimilation) model originally designed at AER for local weather prediction and apply it to three distinct but related purposes in connection with the Atmospheric Radiation Measurement (ARM) program: (a) to provide a testbed that simulates a global climate model in order to facilitate the development and testing of new cloud parametrizations and radiation models; (b) to assimilate the ARM data continuously at the scale of a climate model, using the adjoint method, thus providing the initial conditions and verification data for testing parameumtions; (c) to study the sensitivity of a radiation scheme to cloud parameters, again using the adjoint method, thus demonstrating the usefulness of the testbed model. The data assimilation will use a variational technique that minimizes the difference between the model results and the observation during the analysis period. The adjoint model is used to compute the gradient of a measure of the model errors with respect to nudging terms that are added to the equations to force the model output closer to the data. The radiation scheme that will be included in the basic ALFA model makes use of a gen two-stream approximation, and is designed for vertically inhonogeneous, multiple-scattering atmospheres. The sensitivity of this model to the definition of cloud parameters will be studied. The adjoint technique will also be used to compute the sensitivities. This project is designed to provide the Science Team members with the appropriate tools and modeling environment for proper testing and tuning of new radiation models and cloud parametrization schemes.

Louis, J.F.

1992-09-22T23:59:59.000Z

384

ROBOTICS -INTRODUCTION t Manipulator Arms  

E-Print Network [OSTI]

ROBOTICS - INTRODUCTION t Manipulator Arms The common industrial manipulator is often referred to as a robot arm, with links and joints described in similar terms. Manipulators which emulate. The motion of articulated robot arms differs from the motion of the human arm. While robot joints have fewer

Petriu, Emil M.

385

Atmospheric Radiation Measurement (ARM) Data from the North Slope Alaska (NSA) Site  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Atmospheric Radiation Measurement (ARM) Program is the largest global change research program supported by the U.S. Department of Energy. The primary goal of the ARM Program is to improve the treatment of cloud and radiation physics in global climate models in order to improve the climate simulation capabilities of these models. To achieve this goal, ARM scientists and researchers around the world use continuous data obtained through the ARM Climate Research Facility. ARM maintains four major, permanent sites for data collection and deploys the ARM Mobile Facility to other sites as determined. The North Slope of Alaska (NSA) site is a permanent site providing data about cloud and radiative processes at high latitudes. These data are being used to refine models and parameterizations as they relate to the Arctic. Centered at Barrow and extending to the south (to the vicinity of Atqasuk), west (to the vicinity of Wainwright), and east (towards Oliktok), the NSA site has become a focal point for atmospheric and ecological research activity on the North Slope. Approximately 300,000 NSA data sets from 1993 to the present reside in the ARM Archive at http://www.archive.arm.gov/. Users will need to register for a password, but all files are then free for viewing or downloading. The ARM Archive physically resides at the Oak Ridge National Laboratory.

386

FINAL REPORT (DE-FG02-97ER62338): Single-column modeling, GCM parameterizations, and ARM data  

SciTech Connect (OSTI)

Our overall goal is the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have compared SCM (single-column model) output with ARM observations at the SGP, NSA and TWP sites. We focus on the predicted cloud amounts and on a suite of radiative quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art three-dimensional atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable.

Richard C. J. Somerville

2009-02-27T23:59:59.000Z

387

ARM Climate Research Facility  

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388

ARM Climate Research Facility  

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389

ARM Climate Research Facility  

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390

ARM Climate Research Facility  

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391

ARM TR-008  

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392

ARM - Instrument - sodar  

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393

ARM - Instrument - sp2  

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394

ARM - Instrument - spn  

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395

ARM - Instrument - stable  

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396

ARM - Measurement - Nitrogen  

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397

ARM - Measurement - Surface albedo  

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398

ARM - Measurement - Surface condition  

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399

ARM - Measurement - Total carbon  

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400

Atmospheric Radiation Measurement (ARM) Data from the ARM Specific Measurement Categories  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The ARM Program gathers a wide variety of measurements from many different sources. Each day, the Data Archive stores and distributes large quantities of data collected from these sources. Scientists then use these data to research atmospheric radiation balance and cloud feedback processes, which are critical elements of global climate change. The huge archive of ARM data can be organized by measurement categories into six "collections:" Aerosols, Atmospheric Carbon, Atmospheric State, Cloud Properties, Radiometric, and Surface Properties. Clicking on one of the measurement categories leads to a page that breaks that category down into sub-categories. For example, "Aerosols" is broken down into Microphysical and Chemical Properties (with 9 subsets) and Optical and Radiative Properties (with 7 subsets). Each of the subset links, in turn, leads to detailed information pages and links to specific data streams. Users will be requested to create a password, but the data files are free for viewing and downloading. The ARM Archive physically resides at the Oak Ridge National Laboratory.

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

METR 3223: Physical Meteorology II: Cloud Physics, Atmospheric Electricity and Optics  

E-Print Network [OSTI]

METR 3223: Physical Meteorology II: Cloud Physics, Atmospheric Electricity and Optics CLASS: Monday of the physical states and processes of clouds and precipitation as well as atmospheric electricity and optics and results Radar observation and estimation Atmospheric electricity: Electrostatics Electromagnetic wave

Droegemeier, Kelvin K.

402

Anvil characteristics as seen by C-POL during the Tropical Warm Pool International Cloud Experiment (TWP-ICE)  

E-Print Network [OSTI]

The Tropical Pacific Warm Pool International Cloud Experiment (TWP-ICE) took place in Darwin, Australia in early 2006. C-band radar data from this experiment were used to characterize tropical anvil areal coverage, height, and thickness during...

Frederick, Kaycee Loretta

2007-04-25T23:59:59.000Z

403

Retrieval of Cloud Phase Using the Moderate Resolution Imaging Spectroradiometer Data during the Mixed-Phase Arctic Cloud Experiment  

SciTech Connect (OSTI)

Improving climate model predictions over Earth's polar regions requires a comprehensive knowledge of polar cloud microphysics. Over the Arctic, there is minimal contrast between the clouds and background snow surface, making it difficult to detect clouds and retrieve their phase from space. Snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds make it even more difficult to determine cloud phase. Also, since determining cloud phase is the first step toward analyzing cloud optical depth, particle size, and water content, it is vital that the phase be correct in order to obtain accurate microphysical and bulk properties. Changes in these cloud properties will, in turn, affect the Arctic climate since clouds are expected to play a critical role in the sea ice albedo feedback. In this paper, the IR trispectral technique (IRTST) is used as a starting point for a WV and 11-{micro}m brightness temperature (T11) parameterization (WVT11P) of cloud phase using MODIS data. In addition to its ability to detect mixed-phase clouds, the WVT11P also has the capability to identify thin cirrus clouds overlying mixed or liquid phase clouds (multiphase ice). Results from the Atmospheric Radiation Measurement (ARM) MODIS phase model (AMPHM) are compared to the surface-based cloud phase retrievals over the ARM North Slope of Alaska (NSA) Barrow site and to in-situ data taken from University of North Dakota Citation (CIT) aircraft which flew during the Mixed-Phase Arctic Cloud Experiment (MPACE). It will be shown that the IRTST and WVT11P combined to form the AMPHM can achieve a relative high accuracy of phase discrimination compared to the surface-based retrievals. Since it only uses MODIS WV and IR channels, the AMPHM is robust in the sense that it can be applied to daytime, twilight, and nighttime scenes with no discontinuities in the output phase.

Spangenberg, D.; Minnis, P.; Shupe, M.; Uttal, T.; Poellot, M.

2005-03-18T23:59:59.000Z

404

FINAL REPORT: An Investigation of the Microphysical, Radiative, and Dynamical Properties of Mixed-Phase Clouds  

SciTech Connect (OSTI)

This final report summarizes the major accomplishments and products resulting from a three-year grant funded by the DOE, Office of Science, Atmospheric Radiation Measurement Program titled: An Investigation of the Microphysical, Radiative, and Dynamical Properties of Mixed-Phase Clouds. Accomplishments are listed under the following subcategories: Mixed-phase cloud retrieval method development; Mixed-phase cloud characterization; ARM mixed-phase cloud retrieval review; and New ARM MICROBASE product. In addition, lists are provided of service to the Atmospheric Radiation Measurement Program, data products provided to the broader research community, and publications resulting from this grant.

Shupe, Matthew D

2007-10-01T23:59:59.000Z

405

Imaging synthetic aperture radar  

DOE Patents [OSTI]

A linear-FM SAR imaging radar method and apparatus to produce a real-time image by first arranging the returned signals into a plurality of subaperture arrays, the columns of each subaperture array having samples of dechirped baseband pulses, and further including a processing of each subaperture array to obtain coarse-resolution in azimuth, then fine-resolution in range, and lastly, to combine the processed subapertures to obtain the final fine-resolution in azimuth. Greater efficiency is achieved because both the transmitted signal and a local oscillator signal mixed with the returned signal can be varied on a pulse-to-pulse basis as a function of radar motion. Moreover, a novel circuit can adjust the sampling location and the A/D sample rate of the combined dechirped baseband signal which greatly reduces processing time and hardware. The processing steps include implementing a window function, stabilizing either a central reference point and/or all other points of a subaperture with respect to doppler frequency and/or range as a function of radar motion, sorting and compressing the signals using a standard fourier transforms. The stabilization of each processing part is accomplished with vector multiplication using waveforms generated as a function of radar motion wherein these waveforms may be synthesized in integrated circuits. Stabilization of range migration as a function of doppler frequency by simple vector multiplication is a particularly useful feature of the invention; as is stabilization of azimuth migration by correcting for spatially varying phase errors prior to the application of an autofocus process.

Burns, Bryan L. (Tijeras, NM); Cordaro, J. Thomas (Albuquerque, NM)

1997-01-01T23:59:59.000Z

406

ARM - ARM Summer Training and Science Applications  

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407

ARM - Field Campaign - ARM LBNL Carbon Project  

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408

ARM - 1998 ARM Science Team Meeting  

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409

ARM - 1999 ARM Science Team Meeting  

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410

ARM - 2000 ARM Science Team Meeting  

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411

ARM - 2001 ARM Science Team Meeting  

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412

ARM - 2002 ARM Science Team Meeting  

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413

ARM - ARM Engineering and Operations Contacts  

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414

ARM - ARM Facility at EGU 2012  

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415

ARM - ARM Facility at EGU 2014  

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416

ARM - ARM MJO Investigation Experiment (AMIE)  

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417

CIMEL SUN PHOTOMETERS: UPDATES ON NEW DEPLOYMENTS AND CLOUD MODE ZENITH RADIANCE DATA  

E-Print Network [OSTI]

CIMEL SUN PHOTOMETERS: UPDATES ON NEW DEPLOYMENTS AND CLOUD MODE ZENITH RADIANCE DATA Richard of Science ABSTRACT Since March 1998, ARM has deployed Cimel Sun PHOTometers (CSPHOT) at several but not all

418

The Tropical Warm Pool International Cloud Experiment  

SciTech Connect (OSTI)

One of the most complete data sets describing tropical convection ever collected will result from the upcoming Tropical Warm Pool International Cloud Experiment (TWP-ICE) in the area around Darwin, Northern Australia in January and February 2006. The aims of the experiment, which will be operated in conjunction with the DOE Atmospheric Radiation Measurement (ARM) site in Darwin, will be to examine convective cloud systems from their initial stages through to the decay of the cirrus generated and to measure their impact on the environment. The experiment will include an unprecedented network of ground-based observations (soundings, active and passive remote sensors) combined with low, mid and high altitude aircraft for in-situ and remote sensing measurements. A crucial outcome of the experiment will be a data set suitable to provide the forcing and evaluation data required by cloud resolving and single column models as well as global climate models (GCMs) with the aim to contribute to parameterization development. This data set will provide the necessary link between the observed cloud properties and the models that are attempting to simulate them. The experiment is a large multi-agency experiment including substantial contributions from the United States DOE ARM program, ARM-UAV program, NASA, the Australian Bureau of Meteorology, CSIRO, EU programs and many universities.

May, Peter T.; Mather, James H.; Vaughan, Geraint; Jakob, Christian; McFarquhar, Greg; Bower, Keith; Mace, Gerald G.

2008-05-01T23:59:59.000Z

419

Retrieval of cloud properties using SCIAMACHY on ENVISAT  

E-Print Network [OSTI]

;2 AGENDA 1. Rationale 2. SCIAMACHY and its calibration 3. Algorithms 4. SCIMACHY cloud retrievals 5 Synthetic Aperture Radar (ASAR), operating at C-band, ASAR ensures continuity with the image mode (SAR;13 VICARIOUS CALIBRATION USING MERIS #12;14 MERIS on ENVISAT spacecraft /1.03.2002-present/ · Instrument bands

Kuligowski, Bob

420

Dynamic Cloud Infrastructure.  

E-Print Network [OSTI]

??This thesis will explore and investigate the possibility of implementing nested clouds to increase flexibility. A nested cloud is a private cloud running inside another… (more)

Gundersen, Espen

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Securing Cloud Storage Service.  

E-Print Network [OSTI]

?? Cloud computing brought flexibility, scalability, and capital cost savings to the IT industry. As more companies turn to cloud solutions, securing cloud based services… (more)

Zapolskas, Vytautas

2012-01-01T23:59:59.000Z

422

ARM Climate Research Facility  

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423

ARM Climate Research Facility  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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424

ARM People Search  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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425

ARM Poster 2007.ai  

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426

ARM Science Meeting  

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427

ARM TR-006  

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428

ARM TR-008  

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429

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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430

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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431

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP Program20Site756

432

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP Program20Site7567

433

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP Program20Site75677

434

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP Program20Site756778

435

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP

436

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric

437

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric1 ACRF

438

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric1

439

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric13

440

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric134

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10

442

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric

443

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric4 ACRF

444

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric4

445

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric46

446

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric461

447

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric46107

448

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10 Atmospheric461079

449

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10

450

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric

451

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric5

452

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric59

453

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric599

454

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric5990

455

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101

456

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144

457

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision Gas

458

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision Gas

459

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision

460

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision51

Note: This page contains sample records for the topic "arm cloud radar" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision5125

462

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449

463

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave

464

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave7 Total Sky

465

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave7 Total

466

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave7

467

ARM TR-008  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave73 Whole-Sky

468

ARM TR-009  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave73

469

ARM XDC Datastreams  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62ARMStreamsC-Band

470

ARM XDC Datastreams  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62ARMStreamsC-BandModel

471

ARM - Facility News Article  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3, 2010September 30,June 24,ARM Science LiaisonBestNovemberARM

472

ARM - About RSS Feeds  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM Engineering and RelatedCenterARM

473

Performance limits for exo-clutter Ground Moving Target Indicator (GMTI) radar.  

SciTech Connect (OSTI)

The performance of a Ground Moving Target Indicator (GMTI) radar system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to 'get your arms around' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall GMTI radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'.

Doerry, Armin Walter

2010-09-01T23:59:59.000Z

474

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Imager Data over the Atmospheric Radiation Measurement Sites  

SciTech Connect (OSTI)

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 {micro}m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-{micro}m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60{sup o}N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).

Trepte, Q.Z.; Minnis, P.; Heck, P.W.; Palikonda, R.

2005-03-18T23:59:59.000Z

475

Triggered star formation in the Magellanic Clouds  

E-Print Network [OSTI]

Abstract. We discuss how tidal interaction between the Large Magellanic Cloud (LMC), the Small Magellanic Cloud (SMC), and the Galaxy triggers galaxy-wide star formation in the Clouds for the last ? 0.2 Gyr based on our chemodynamical simulations on the Clouds. Our simulations demonstrate that the tidal interaction induces the formation of asymmetric spiral arms with high gas densities and consequently triggers star formation within the arms in the LMC. Star formation rate in the present LMC is significantly enhanced just above the eastern edge of the LMC’s stellar bar owing to the tidal interaction. The location of the enhanced star formation is very similar to the observed location of 30 Doradus, which suggests that the formation of 30 Doradus is closely associated with the last Magellanic collision about 0.2 Gyr ago. The tidal interaction can dramatically compress gas initially within the outer part of the SMC so that new stars can be formed from the gas to become intergalactic young stars in the inter-Cloud region (e.g., the Magellanic Bridge). The metallicity distribution function of the newly formed stars in the Magellanic Bridge has a peak of [Fe/H] ? ?0.8, which is significantly lower than the stellar metallicity of the SMC.

B. G. Elmegreen; J. Palous; Kenji Bekki

2006-01-01T23:59:59.000Z

476

Cloud Computing Adam Barker  

E-Print Network [OSTI]

Cloud Computing 1 Adam Barker #12;Overview · Introduction to Cloud computing · Enabling technologies · Di erent types of cloud: IaaS, PaaS and SaaS · Cloud terminology · Interacting with a cloud: management consoles · Launching an instance · Connecting to an instance · Running your application · Clouds

St Andrews, University of

477

Experiment to Characterize Tropical Cloud Systems  

SciTech Connect (OSTI)

A major experiment to study tropical convective cloud systems and their impacts will take place around Darwin, Northern Australia in early 2006. The Tropical Warm Pool International Cloud Experiment (TWP-ICE) is a collaboration including the DOE ARM (Atmospheric Radiation Measurement) and ARM-UAV programs, NASA centers, the Australian Bureau of Meteorology, CSIRO, and universities in the USA, Australia, Japan, the UK, and Canada. TWP-ICE will be preceded in November/December 2004 by a collaborating European aircraft campaign involving the EU SCOUT-O3 and UK NERC ACTIVE projects. Detailed atmospheric measurements will be made in the Darwin area through the whole Austral summer, giving unprecedented coverage through the pre-monsoon and monsoon periods.

May, Peter T.; Mather, Jim H.; Jakob, Christian

2005-08-02T23:59:59.000Z

478

Data Quality Assessment and Control for the ARM Climate Research Facility  

SciTech Connect (OSTI)

The mission of the Atmospheric Radiation Measurement (ARM) Climate Research Facility is to provide observations of the earth climate system to the climate research community for the purpose of improving the understanding and representation, in climate and earth system models, of clouds and aerosols as well as their coupling with the Earth's surface. In order for ARM measurements to be useful toward this goal, it is important that the measurements are of a known and reasonable quality. The ARM data quality program includes several components designed to identify quality issues in near-real-time, track problems to solutions, assess more subtle long-term issues, and communicate problems to the user community.

Peppler, R

2012-06-26T23:59:59.000Z

479

Overview of Radar Data Compression Valliappa Lakshmanan  

E-Print Network [OSTI]

of radar data is 1km in range and approximately 1 degree in azimuth. 1.1 Size The raw radar data ("Level I are distributed as "moment" data, called Level II. The Level II data comprises a value of radar reflectivity, velocity toward/away from the radar and spectrum width (a measure of the spread of velocity values

Lakshmanan, Valliappa

480

ARM User Survey Report  

SciTech Connect (OSTI)

The objective of this survey was to obtain user feedback to, among other things, determine how to organize the exponentially growing data within the Atmospheric Radiation Measurement (ARM) Climate Research Facility, and identify users’ preferred data analysis system. The survey findings appear to have met this objective, having received approximately 300 responses that give insight into the type of work users perform, usage of the data, percentage of data analysis users might perform on an ARM-hosted computing resource, downloading volume level where users begin having reservations, opinion about usage if given more powerful computing resources (including ability to manipulate data), types of tools that would be most beneficial to them, preferred programming language and data analysis system, level of importance for certain types of capabilities, and finally, level of interest in participating in a code-sharing community.

Roeder, LR

2010-06-22T23:59:59.000Z

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481

Robot arm apparatus  

DOE Patents [OSTI]

A robot arm apparatus is provided for inspecting and/or maintaining an interior of a steam generator which has an outside wall and a port for accessing the interior of the steam generator. The robot arm apparatus includes a flexible movable conduit for conveying inspection and/or maintenance apparatus from outside the steam generator to the interior of the steam generator. The flexible conduit has a terminal working end which is translated into and around the interior of the steam generator. Three motors located outside the steam generator are employed for moving the terminal working end inside the steam generator in "x", "y", and "z" directions, respectively. Commonly conducted inspection and maintenance operations include visual inspection for damaged areas, water jet lancing for cleaning sludge deposits, core boring for obtaining sludge deposits, and scrubbing of internal parts.