National Library of Energy BETA

Sample records for method lbtm cloud

  1. ARM - VAP Process - lbtm-minnis

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

    : Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Darwin lbtm3minnisman : Layered Bispectral Threshold Method (LBTM) cloud products derived...

  2. ARM - VAP Product - lbtm3minnisdar

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

    below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNISDAR Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Darwin Active Dates 2002.04.01...

  3. ARM - VAP Product - lbtm3minnisman

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

    minnisman Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNISMAN Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Manus

  4. ARM - VAP Product - lbtm3minnisnau

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

    minnisnau Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNISNAU Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Nauru

  5. ARM - VAP Product - lbtm3minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNIS Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5 Active Dates 1998.01.03 - 2003.05.21 Originating VAP Process Minnis Cloud Products Using LBTM Algorithm : LBTM-MINNIS Measurements The measurements below provided by this

  6. ARM - Campaign Instrument - lbtm-minnis

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

    govInstrumentslbtm-minnis Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign Instrument : Minnis Cloud Products Using LBTM Algorithm (LBTM-MINNIS) Instrument Categories Cloud Properties, Satellite Observations Campaigns ARESE II IOP [ Download Data ] Southern Great Plains, 2000.02.01 - 2000.04.05 Nauru99 Campaign [ Download Data ] Tropical Western Pacific, 1999.06.16 - 1999.07.15 Primary Measurements Taken The following measurements are

  7. ARM - Measurement - Cloud optical depth

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

    TWST : Three Waveband Spectrally-agile Technique Sensor WRF-CHEM : Weather Research and Forecasting (WRF) Model Output Value-Added Products LBTM-MINNIS : Minnis Cloud Products...

  8. Testing a Cloud Condensation Nuclei Remote Sensing Method

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

    a Cloud Condensation Nuclei Remote Sensing Method S. J. Ghan Climate Physics Pacific Northwest National Laboratory Richland, Washington D. R. Collin Department of Atmospheric...

  9. ARM - Publications: Science Team Meeting Documents

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

    GOES-8 cloud and radiative properties data set. The ARM GOES-8 data set is derived using the Layered Bispectral Threshold Method (LBTM, see Khaiyer et al., 2001 this conference). ...

  10. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-19

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köhler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

  11. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-19

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Kohler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. Furthermore, the model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

  12. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2015-09-01

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. The model combines Khler theory with semi-empirical group contribution methods to estimate molar volumes, activity coefficients and liquid-liquid phase boundaries tomorepredict the effective hygroscopicity parameter, kappa. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of two. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging testbeds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger scale models.less

  13. Variational optimization method for calculation of cloud drop growth in an Eulerian drop-size framework

    SciTech Connect (OSTI)

    Liu, Qingfu; Kogan, Y.L.; Lilly, D.K.; Khairoutdinov, M.P.

    1997-10-15

    A variational optimization (VO) method that requires specification of only one variable in each bin size for condensation and evaporation calculations in an Eulerian drop-size framework is proposed. The method is tested against the exact solution given by the Lagrangian method using more than 15000 spectra selected from experiments with a three-dimensional large eddy simulation model with explicit microphysics. The results show that the VO method not only conserves the integral parameters of the spectrum, such as drop number, mean radius, liquid water content, and the effective radius, but also provides an accurate calculation of the spectrum itself.

  14. Precipitating clouds

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

    A suggestion for a new focus on cloud microphysical process study in the ARM program 1. Retrieving precipitating mixed- phase cloud properties Zhien Wang University of Wyoming zwang@uwyo.edu Retrieving Precipitating Mixed-phase Cloud Properties Global distribution of supercooled water topped stratiform clouds (top > 1 km and length> 14km) Most of them are mixed-phase with precipitation or virga An multiple sensor based approach to provide water phase as well as ice phase properties

  15. ARM - Measurement - Cloud size

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

    measurements as cloud thickness, cloud area, and cloud aspect ratio. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  16. ARM - VAP Product - goes12minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES12MINNIS GOES-12: 0.5 degree cloud products Active Dates 2003.04.01 - 2003.08.31 Originating VAP Process Minnis Cloud Products Using LBTM Algorithm : LBTM-MINNIS Measurements The measurements below provided by this product are those considered

  17. ARM - Measurement - Cloud type

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

    Measurement : Cloud type Cloud type such as cirrus, stratus, cumulus etc Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  18. Dispelling Clouds of Uncertainty

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Lewis, Ernie; Teixeira, João

    2015-06-15

    How do you build a climate model that accounts for cloud physics and the transitions between cloud regimes? Use MAGIC.

  19. Opaque cloud detection

    DOE Patents [OSTI]

    Roskovensky, John K.

    2009-01-20

    A method of detecting clouds in a digital image comprising, for an area of the digital image, determining a reflectance value in at least three discrete electromagnetic spectrum bands, computing a first ratio of one reflectance value minus another reflectance value and the same two values added together, computing a second ratio of one reflectance value and another reflectance value, choosing one of the reflectance values, and concluding that an opaque cloud exists in the area if the results of each of the two computing steps and the choosing step fall within three corresponding predetermined ranges.

  20. THE ATOMIC-TO-MOLECULAR TRANSITION IN GALAXIES. III. A NEW METHOD FOR DETERMINING THE MOLECULAR CONTENT OF PRIMORDIAL AND DUSTY CLOUDS

    SciTech Connect (OSTI)

    McKee, Christopher F.; Krumholz, Mark R. E-mail: krumholz@ucolick.ed

    2010-01-20

    Understanding the molecular content of galaxies is a critical problem in star formation and galactic evolution. Here we present a new method, based on a Stroemgren-type analysis, to calculate the amount of H{sub I} that surrounds a molecular cloud irradiated by an isotropic radiation field. We consider both planar and spherical clouds, and H{sub 2} formation either in the gas phase or catalyzed by dust grains. Under the assumption that the transition from atomic to molecular gas is sharp, our method gives the solution without any reference to the photodissociation cross section. We test our results for the planar case against those of a photodissociation region code and find typical accuracies of about 10%. Our results are also consistent with the scaling relations found in Paper I of this series, but they apply to a wider range of physical conditions. We present simple, accurate analytic fits to our results that are suitable for comparison to observations and to implementation in numerical and semi-analytic models.

  1. Comparisons of cloud ice mass content retrieved from the radar-infrared radiometer method with aircraft data during the second international satellite cloud climatology project regional experiment (FIRE-II)

    SciTech Connect (OSTI)

    Matrosov, S.Y. |; Heymsfield, A.J.; Kropfli, R.A.; Snider, J.B.

    1996-04-01

    Comparisons of remotely sensed meteorological parameters with in situ direct measurements always present a challenge. Matching sampling volumes is one of the main problems for such comparisons. Aircraft usually collect data when flying along a horizontal leg at a speed of about 100 m/sec (or even greater). The usual sampling time of 5 seconds provides an average horizontal resolution of the order of 500 m. Estimations of vertical profiles of cloud microphysical parameters from aircraft measurements are hampered by sampling a cloud at various altitudes at different times. This paper describes the accuracy of aircraft horizontal and vertical coordinates relative to the location of the ground-based instruments.

  2. Dispelling Clouds of Uncertainty

    SciTech Connect (OSTI)

    Lewis, Ernie; Teixeira, João

    2015-06-15

    How do you build a climate model that accounts for cloud physics and the transitions between cloud regimes? Use MAGIC.

  3. ARM - Measurement - Cloud location

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

    point in space and time, typically expressed as a binary cloud mask. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  4. The Role of Shallow Cloud Moistening in MJO and Non-MJO Convective...

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

    to quantify bulk shallow cloud moistening through evaporation of condensed water using a simple method based on observations of liquid water path, cloud depth and temporal...

  5. Science Cloud 2011

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

    Science Cloud 2011 Science Cloud 2011 June 17, 2011 The Magellan teams at NERSC and Argonne recently presented a joint paper detailing their progress and conclusions. At Science Cloud 2011: The Second Workshop on Scientific Cloud Computing, in a paper titled "Magellan: Experiences from a Science Cloud" (PDF, 320KB), lead author Lavanya Ramakrishnan outlined the groups' most recent achievements and conclusions, including a successful run of real-time data analysis for the STAR

  6. Cloud Properties Working Group Low Clouds Update

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

    Cloud Properties Working Group Low Clouds Update Low Clouds Update Jennifer Comstock Jennifer Comstock Dave Turner Dave Turner Andy Andy Vogelmann Vogelmann Instruments Instruments 90/150 GHz microwave radiometer 90/150 GHz microwave radiometer Deployed during COPS AMF Deployed during COPS AMF Exploring calibration w/ DPR ( Exploring calibration w/ DPR ( Crewell Crewell & & L L ö ö hnert hnert ) ) See COPS Breakout, Wednesday evening See COPS Breakout, Wednesday evening 183 GHz (GVR)

  7. A boundary-layer cloud study using Southern Great Plains Cloud and radiation testbed (CART) data

    SciTech Connect (OSTI)

    Albrecht, B.; Mace, G.; Dong, X.; Syrett, W.

    1996-04-01

    Boundary layer clouds-stratus and fairweather cumulus - are closely coupled involves the radiative impact of the clouds on the surface energy budget and the strong dependence of cloud formation and maintenance on the turbulent fluxes of heat and moisture in the boundary layer. The continuous data collection at the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site provides a unique opportunity to study components of the coupling processes associated with boundary layer clouds and to provide descriptions of cloud and boundary layer structure that can be used to test parameterizations used in climate models. But before the CART data can be used for process studies and parameterization testing, it is necessary to evaluate and validate data and to develop techniques for effectively combining the data to provide meaningful descriptions of cloud and boundary layer characteristics. In this study we use measurements made during an intensive observing period we consider a case where low-level stratus were observed at the site for about 18 hours. This case is being used to examine the temporal evolution of cloud base, cloud top, cloud liquid water content, surface radiative fluxes, and boundary layer structure. A method for inferring cloud microphysics from these parameters is currently being evaluated.

  8. Cloud classification using whole-sky imager data

    SciTech Connect (OSTI)

    Buch, K.A. Jr.; Sun, C.H.; Thorne, L.R.

    1996-04-01

    Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes based on measured data from real cloud scenes. These renderings will provide the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here uses binary decision trees to distinguish the different cloud types based on cloud features vectors.

  9. ARM - Measurement - Cloud extinction

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

    Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud extinction The removal of radiant energy from an incident beam by the process of cloud absorption andor ...

  10. Scientific Cloud Computing Misconceptions

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

    Scientific Cloud Computing Misconceptions Scientific Cloud Computing Misconceptions July 1, 2011 Part of the Magellan project was to understand both the possibilities and the limitations of cloud computing in the pursuit of science. At a recent conference, Magellan investigator Shane Canon outlined some persistent misconceptions about doing science in the cloud - and what Magellan has taught us about them. » Read the ISGTW story. » Download the slides (PDF, 4.1MB

  11. Surface based remote sensing of aerosol-cloud interactions

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

    Surface based remote sensing of aerosol-cloud interactions Feingold, Graham NOAA/Environmental Technology Laboratory Frisch, Shelby NOAA/Environmental Technology Laboratory Min, Qilong State University of New York at Albany Category: Cloud Properties We will present an analysis of the effect of aerosol on clouds at the Southern Great Plains ARM site. New methods for retrieving cloud droplet effective radius with radar (MMCR), multifilter rotating shadowband radiometer (MFRSR), and microwave

  12. Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Prather, M. J.

    2015-08-14

    A new approach for modeling photolysis rates (J values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations by four quadrature atmospheres produces mean J values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 % errorsmore » using simpler approximations. Cloud-J is practical for chemistry–climate models, requiring only an average of 2.8 Fast-J calls per atmosphere vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections, is also incorporated into Cloud-J.« less

  13. Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Prather, M. J.

    2015-05-27

    A new approach for modeling photolysis rates (J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations. Cloud-Jmore » is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.« less

  14. Cloud Property Retrieval Products for Graciosa Island, Azores

    SciTech Connect (OSTI)

    Dong, Xiquan

    2014-05-05

    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.

  15. Cloud Property Retrieval Products for Graciosa Island, Azores

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

    Dong, Xiquan

    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.

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

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

    Azores ProductsCloud Property Retrieval Products for Graciosa Island, Azores ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Cloud Property Retrieval Products for Graciosa Island, Azores [ research data - ASR funded ] 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

  17. Evolution in Cloud Population Statistics of the MJO: From AMIE...

    Office of Scientific and Technical Information (OSTI)

    to Global-Cloud Permitting Models Final Report Version 1 Methods of convectivestratiform precipitation classification and surface rain rate estimation based on the ...

  18. Evolution in Cloud Population Statistics of the MJO. From AMIE...

    Office of Scientific and Technical Information (OSTI)

    to Global-Cloud Permitting Models final report Version 1 Methods of convectivestratiform precipitation classification and surface rain rate estimation based on the ...

  19. ARM - Measurement - Cloud fraction

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

    Flux Analysis SWFLUXANAL : Shortwave Flux Analysis TSI : Total Sky Imager UAV-EGRETT : UAV-Egrett WSI : Whole Sky Imager WSICLOUD : Whole Sky Imager Cloud Products ...

  20. ARM - Measurement - Cloud phase

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

    that involves property descriptors such as stratus, cumulus, and cirrus. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  1. Finance Idol Word Cloud

    Broader source: Energy.gov [DOE]

    This word cloud represents the topics discussed during the Big and Small Ideas: How to Lower Solar Financing Costs breakout session at the SunShot Grand Challenge.

  2. Boundary Layer Cloud Turbulence Characteristics

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

    Boundary Layer Cloud Turbulence Characteristics Virendra Ghate Bruce Albrecht Parameter Observational Readiness (/10) Modeling Need (/10) Cloud Boundaries 9 9 Cloud Fraction Variance Skewness Up/Downdraft coverage Dominant Freq. signal Dissipation rate ??? Observation-Modeling Interface

  3. Parameterizing Size Distribution in Ice Clouds

    SciTech Connect (OSTI)

    DeSlover, Daniel; Mitchell, David L.

    2009-09-25

    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 m wavelength relative to 11 m wavelength due to the process of wave resonance or photon tunneling more active at 12 m. This makes the 12/11 m absorption optical depth ratio (or equivalently the 12/11 m 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.

  4. Evolution in Cloud Population Statistics of the MJO. From AMIE Field

    Office of Scientific and Technical Information (OSTI)

    Observations to Global-Cloud Permitting Models final report Version 1 (Technical Report) | SciTech Connect Evolution in Cloud Population Statistics of the MJO. From AMIE Field Observations to Global-Cloud Permitting Models final report Version 1 Citation Details In-Document Search Title: Evolution in Cloud Population Statistics of the MJO. From AMIE Field Observations to Global-Cloud Permitting Models final report Version 1 Methods of convective/stratiform precipitation classification and

  5. Cloud computing security.

    SciTech Connect (OSTI)

    Shin, Dongwan; Claycomb, William R.; Urias, Vincent E.

    2010-10-01

    Cloud computing is a paradigm rapidly being embraced by government and industry as a solution for cost-savings, scalability, and collaboration. While a multitude of applications and services are available commercially for cloud-based solutions, research in this area has yet to fully embrace the full spectrum of potential challenges facing cloud computing. This tutorial aims to provide researchers with a fundamental understanding of cloud computing, with the goals of identifying a broad range of potential research topics, and inspiring a new surge in research to address current issues. We will also discuss real implementations of research-oriented cloud computing systems for both academia and government, including configuration options, hardware issues, challenges, and solutions.

  6. Temperature, Water Vapor, and Clouds"

    Office of Scientific and Technical Information (OSTI)

    Radiometric Studies of Temperature, Water Vapor, and Clouds" Project ID: 0011106 ... measurements of column amounts of water vapor and cloud liquid has been well ...

  7. ARM - Measurement - Cloud effective radius

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

    the number size distribution of cloud particles, whether liquid or ice. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  8. TC_CLOUD_REGIME.cdr

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

    intensity (e.g. May and Ballinger, 2007) Resulting Cloud Properties Examine rain DSD using polarimetric radar Examine ice cloud properties using MMCR and MPL Expect...

  9. Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-02-16

    Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m−2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m−2.« less

  10. Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-07-02

    Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m-2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m-2.« less

  11. Magellan: A Cloud Computing Testbed

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

    Magellan News & Announcements Archive Petascale Initiative Exascale Computing APEX Home » R & D » Archive » Magellan: A Cloud Computing Testbed Magellan: A Cloud Computing Testbed Cloud computing is gaining a foothold in the business world, but can clouds meet the specialized needs of scientists? That was one of the questions NERSC's Magellan cloud computing testbed explored between 2009 and 2011. The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Oce

  12. First observations of tracking clouds using scanning ARM cloud radars

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.

  13. First observations of tracking clouds using scanning ARM cloud radars

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (first echo). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.

  14. Science on the Hill: Methane cloud hunting

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

    Methane cloud hunting Science on the Hill: Methane cloud hunting Los Alamos researchers go ... Science on the Hill: Methane cloud hunting When our team from Los Alamos National ...

  15. Cloud Property Retrieval Products for Graciosa Island, Azores...

    Office of Scientific and Technical Information (OSTI)

    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. ...

  16. Evaluation of tropical cloud and precipitation statistics of CAM3 using CloudSat and CALIPSO data

    SciTech Connect (OSTI)

    Zhang, Y; Klein, S; Boyle, J; Mace, G G

    2008-11-20

    The combined CloudSat and CALIPSO satellite observations provide the first simultaneous measurements of cloud and precipitation vertical structure, and are used to examine the representation of tropical clouds and precipitation in the Community Atmosphere Model Version 3 (CAM3). A simulator package utilizing a model-to-satellite approach facilitates comparison of model simulations to observations, and a revised clustering method is used to sort the subgrid-scale patterns of clouds and precipitation into principal cloud regimes. Results from weather forecasts performed with CAM3 suggest that the model underestimates the horizontal extent of low and mid-level clouds in subsidence regions, but overestimates that of high clouds in ascending regions. CAM3 strongly overestimates the frequency of occurrence of the deep convection with heavy precipitation regime, but underestimates the horizontal extent of clouds and precipitation at low and middle levels when this regime occurs. This suggests that the model overestimates convective precipitation and underestimates stratiform precipitation consistent with a previous study that used only precipitation observations. Tropical cloud regimes are also evaluated in a different version of the model, CAM3.5, which uses a highly entraining plume in the parameterization of deep convection. While the frequency of occurrence of the deep convection with heavy precipitation regime from CAM3.5 forecasts decreases, the incidence of the low clouds with precipitation and congestus regimes increases. As a result, the parameterization change does not reduce the frequency of precipitating convection that is far too high relative to observations. For both versions of CAM, clouds and precipitation are overly reflective at the frequency of the CloudSat radar and thin clouds that could be detected by the lidar only are underestimated.

  17. Automated detection of cloud and cloud-shadow in single-date Landsat imagery using neural networks and spatial post-processing

    SciTech Connect (OSTI)

    Hughes, Michael J. [University of Tennessee, Knoxville (UTK)] [University of Tennessee, Knoxville (UTK); Hayes, Daniel J [ORNL] [ORNL

    2014-01-01

    Use of Landsat data to answer ecological questions is contingent on the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of Cloud and Shadow. The method uses neural networks to determine cloud, cloud-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality cloud and cloud-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for clouds (0.8% and 0.9%, respectively), substantially lower omission error for cloud-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the cloud and cloud-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.

  18. Evaluation of high‐level clouds in cloud resolving model...

    Office of Scientific and Technical Information (OSTI)

    Evaluation of high-level clouds in cloud resolving model 10.10022015MS000478 simulations with ARM and KWAJEX observations Key Points: * Two-moment microphysics improves simulated ...

  19. Bringing Clouds into Focus

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

    Bringing Clouds into Focus Bringing Clouds into Focus A New Global Climate Model May Reduce the Uncertainty of Climate Forecasting May 11, 2010 Contact: John Hules, JAHules@lbl.gov , +1 510 486 6008 Randall-fig4.png The large data sets generated by the GCRM require new analysis and visualization capabilities. This 3D plot of vorticity isosurfaces was developed using VisIt, a 3D visualization tool with a parallel distributed architecture, which is being extended to support the geodesic grid used

  20. Cloud Based Applications and Platforms (Presentation)

    SciTech Connect (OSTI)

    Brodt-Giles, D.

    2014-05-15

    Presentation to the Cloud Computing East 2014 Conference, where we are highlighting our cloud computing strategy, describing the platforms on the cloud (including Smartgrid.gov), and defining our process for implementing cloud based applications.

  1. TWP Island Cloud Trail Studies

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

    These island cloud trails have been observed from both the islands of Nauru and Manus, Papua New Guinea. Figure 2 shows an island cloud at Manus observed from MTI and from the ...

  2. ARM - Measurement - Images of Clouds

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

    govMeasurementsImages of Clouds ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Images of Clouds Digital images of cloud scenes (various formats) from satellite, aircraft, and ground-based platforms. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a

  3. ARM - Measurement - Total cloud water

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

    cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a

  4. First observations of tracking clouds using scanning ARM cloud radars

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud fieldmore » and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.« less

  5. Enhanced toxic cloud knockdown spray system for decontamination applications

    DOE Patents [OSTI]

    Betty, Rita G.; Tucker, Mark D.; Brockmann, John E.; Lucero, Daniel A.; Levin, Bruce L.; Leonard, Jonathan

    2011-09-06

    Methods and systems for knockdown and neutralization of toxic clouds of aerosolized chemical or biological warfare (CBW) agents and toxic industrial chemicals using a non-toxic, non-corrosive aqueous decontamination formulation.

  6. A Simple Empirical Equation to Calculate Cloud Optical Thickness...

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

    and high values of this quantity. With the above evidence in mind, we conclude that the empirical method described here is a useful tool for estimating cloud optical thickness at...

  7. Evaluation of high-level clouds in cloud resolving model simulations...

    Office of Scientific and Technical Information (OSTI)

    Title: Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations: HIGH CLOUD IN CRM Authors: Liu, Zheng 1 ; Muhlbauer, Andreas 2 ; ...

  8. ARM - VAP Product - goes7minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES7MINNIS GOES-7: 0.5 degree cloud products

  9. ARM - VAP Product - goes7minnis-acf

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

    minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES7MINNIS-ACF GOES-7: 0.3 degree cloud products, ARM Central Facility

  10. ARM - VAP Product - goes8minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES8MINNIS GOES-8: 0.5 degree cloud products

  11. ARM - VAP Product - goes8minnis-acf

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

    minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES8MINNIS-ACF GOES-8: 0.3 degree cloud products, ARM Central Facility

  12. Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer

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

    Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer I. Genkova and C. N. Long Pacific Northwest National Laboratory Richland, Washington T. Besnard ATMOS SARL Le Mans, France D. Gillotay Institute d'Aeronomie Spatiale de Belgique Brussels, Belgium Introduction In the effort to resolve uncertainties about global climate change, the Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) is improving the treatment of cloud radiative forcing and feedbacks in general

  13. First observations of tracking clouds using scanning ARM cloud...

    Office of Scientific and Technical Information (OSTI)

    These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator ...

  14. TURBULENCE DECAY AND CLOUD CORE RELAXATION IN MOLECULAR CLOUDS

    SciTech Connect (OSTI)

    Gao, Yang; Law, Chung K.; Xu, Haitao

    2015-02-01

    The turbulent motion within molecular clouds is a key factor controlling star formation. Turbulence supports molecular cloud cores from evolving to gravitational collapse and hence sets a lower bound on the size of molecular cloud cores in which star formation can occur. On the other hand, without a continuous external energy source maintaining the turbulence, such as in molecular clouds, the turbulence decays with an energy dissipation time comparable to the dynamic timescale of clouds, which could change the size limits obtained from Jean's criterion by assuming constant turbulence intensities. Here we adopt scaling relations of physical variables in decaying turbulence to analyze its specific effects on the formation of stars. We find that the decay of turbulence provides an additional approach for Jeans' criterion to be achieved, after which gravitational infall governs the motion of the cloud core. This epoch of turbulence decay is defined as cloud core relaxation. The existence of cloud core relaxation provides a more complete understanding of the effect of the competition between turbulence and gravity on the dynamics of molecular cloud cores and star formation.

  15. Parameterization and analysis of 3-D radiative transfer in clouds

    SciTech Connect (OSTI)

    Varnai, Tamas

    2012-03-16

    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.

  16. Holistic Interactions of Shallow Clouds,

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

    Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems Research Instrumentation HI-SCALE will utilize the ARM Aerial Facility's Gulfstream-159 (G-1), as well as ground instrumentation located at the SGP megasite. 7e G-1 will complete transects over the site at multiple altitudes within the boundary layer, within clouds, and above clouds. 7e payload on the G-1 includes: * high frequency meteorological and radiation (both up and downwelling) measurements that also permit computing

  17. Cumulus Clouds and Reflected Sunlight

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

    Cumulus Clouds and Reflected Sunlight from Landsat ETM+ G. Wen and L. Oreopoulos National Aeronautics and Space Administration Goddard Space Flight Center University of Maryland Baltimore County Joint Center of Earth System Technology Greenbelt, Maryland R. F. Cahalan and S. C. Tsay National Aeronautics and Space Administration Goddard Space Flight Center Greenbelt, Maryland Introduction Cumulus clouds attenuate solar radiation casting shows on the ground. Cumulus clouds can also enhance solar

  18. Identifying clouds over the Pierre Auger Observatory using infrared satellite data

    SciTech Connect (OSTI)

    Abreu, Pedro; et al.,

    2013-12-01

    We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

  19. ARM - Measurement - Cloud top height

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

    RUC : Rapid Update Cycle Model Data Field Campaign Instruments CO2LIDAR : Carbon Dioxide Doppler Lidar MPLCMASK : Cloud mask from Micropulse Lidar VARANAL : Constrained...

  20. ARM - Measurement - Cloud condensation nuclei

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

    AOS : Aerosol Observing System CCN : Cloud Condensation Nuclei Particle Counter TDMA : Tandem Differential Mobility Analyzer Field Campaign Instruments AMT : Aerosol Modeling...

  1. ARM - Measurement - Cloud ice particle

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

    : Lear Jet PARTIMG : Particle imager UAV-PROTEUS-MICRO : Proteus Cloud Microphysics ... particle imager MET : Surface Meteorological Instrumentation UAV-PROTEUS : UAV Proteus

  2. ARM - Measurement - Cloud droplet size

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

    Impactor MIRAI : JAMSTEC Research Vessel Mirai PDI : Phase Doppler Interferometer UAV-PROTEUS-MICRO : Proteus Cloud Microphysics Instruments SPEC-CPI : Stratton Park ...

  3. Widget:LogoCloud | Open Energy Information

    Open Energy Info (EERE)

    LogoCloud Jump to: navigation, search This widget adds css selectors and javascript for the Template:LogoCloud. For example: Widget:LogoCloud Retrieved from "http:...

  4. Zenith Radiance Retrieval of Cloud Properties

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

    retrievals of cloud properties from the AMF/COPS campaign Preliminary retrievals of cloud properties from the AMF/COPS campaign Christine Chiu, UMBC/JCET Alexander Marshak, GSFC Yuri Knyazikhin, Boston University Warren Wiscombe, GSFC Christine Chiu, UMBC/JCET Alexander Marshak, GSFC Yuri Knyazikhin, Boston University Warren Wiscombe, GSFC The cloud optical properties of interest are: The cloud optical properties of interest are: * Cloud optical depth τ - the great unknown * Radiative cloud

  5. [Multifractal cloud properties data assessment

    SciTech Connect (OSTI)

    Gautier, C.; Ricchiazzi, P.; Peterson, P.; Lavallee, D. ); Frouin, R.; Lubin, D. ); Lovejoy, S. ); Schertzer, D. )

    1992-05-06

    Our group has been very active over the last year, analyzing a number of data sets to characterize multifractal cloud properties and assess the effects of clouds on surface radiation properties (spectral and broadband). The data sets analyzed include: AVHRR observations of clouds over the ocean, SPOT observations of clouds over the ocean, SSM/I observations of clouds over the ocean, pyranometer data with all-sky photographs, pyrgeometer data all-sky photographs, and spectral surface irradiance all-sky photographs. A number of radiative transfer computations have been performed to help in the interpretation of these observations or provide theoretical guidance for their analysis. Finally 4 number of radiative transfer models have been acquired and tested to prepare for the interpretation of ARM/CART data.

  6. Satellite determination of stratus cloud microphysical properties...

    Office of Scientific and Technical Information (OSTI)

    of liquid water path from SSMI, broadband albedo from ERBE, and cloud characteristics from ISCCP are used to study stratus regions. An average cloud liquid water path of ...

  7. Clouds Environmental Ltd | Open Energy Information

    Open Energy Info (EERE)

    Clouds Environmental Ltd Jump to: navigation, search Name: Clouds Environmental Ltd Place: Portsmouth, United Kingdom Zip: PO3 5EG Product: Independent consultancy specialising in...

  8. Radiative Effects of Cloud Inhomogeneity and

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

    Ackerman et al. 1999), to develop cloud statistics and improve the treatment of subgrid ... and Curry 1989; Liang and Wang 1997). Statistics of Subgrid Cloud Variability We have ...

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

    SciTech Connect (OSTI)

    Kollias, P.; Luke, E.; Szyrmer, W.; Rmillard, J.

    2011-07-02

    In part 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 to include skewness and kurtosis as additional descriptors of the Doppler spectrum. Here, a short climatology of observed Doppler spectra moments as a function of the radar reflectivity at continental and maritime ARM sites is presented. The evolution of the Doppler spectra moments is consistent with the onset and growth of drizzle particles and can be used to assist modeling studies of drizzle onset and growth. Time-height radar observations are used to exhibit the coherency of the Doppler spectra shape parameters and demonstrate their potential to improve the interpretation and use of radar observations. In addition, a simplified microphysical approach to modeling the vertical evolution of the drizzle particle size distribution in warm stratiform clouds is described and used to analyze the observations. The formation rate of embryonic drizzle droplets due to the autoconversion process is not calculated explicitly; however, accretion and evaporation processes are explicitly modeled. The microphysical model is used as input to a radar Doppler spectrum forward model, and synthetic radar Doppler spectra moments are generated. Three areas of interest are studied in detail: early drizzle growth near the cloud top, growth by accretion of the well-developed drizzle, and drizzle depletion below the cloud base due to evaporation. The modeling results are in good agreement with the continental and maritime observations. This demonstrates that steady state one-dimensional explicit microphysical models coupled with a forward model and comprehensive radar Doppler spectra observations offer a powerful method to explore the vertical evolution of the drizzle particle size distribution.

  10. Cloud/Aerosol Parameterizations: Application and Improvement of General Circulation Models

    SciTech Connect (OSTI)

    Penner, Joyce

    2012-06-30

    One of the biggest uncertainties associated with climate models and climate forcing is the treatment of aerosols and their effects on clouds. The effect of aerosols on clouds can be divided into two components: The first indirect effect is the forcing associated with increases in droplet concentrations; the second indirect effect is the forcing associated with changes in liquid water path, cloud morphology, and cloud lifetime. Both are highly uncertain. This project applied a cloud-resolving model to understand the response of clouds under a variety of conditions to changes in aerosols. These responses are categorized according to the large-scale meteorological conditions that lead to the response. Meteorological conditions were sampled from various fields, which, together with a global aerosol model determination of the change in aerosols from present day to pre-industrial conditions, was used to determine a first order estimate of the response of global cloud fields to changes in aerosols. The response of the clouds in the NCAR CAM3 GCM coupled to our global aerosol model were tested by examining whether the response is similar to that of the cloud resolving model and methods for improving the representation of clouds and cloud/aerosol interactions were examined.

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

    SciTech Connect (OSTI)

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

    2014-05-16

    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.

  12. Electron Cloud at Low Emittance in CesrTA

    SciTech Connect (OSTI)

    Palmer, Mark; Alexander, James; Billing, Michael; Calvey, Joseph; Conolly, Christopher; Crittenden, James; Dobbins, John; Dugan, Gerald; Eggert, Nicholas; Fontes, Ernest; Forster, Michael; Gallagher, Richard; Gray, Steven; Greenwald, Shlomo; Hartill, Donald; Hopkins, Walter; Kreinick, David; Kreis, Benjamin; Leong, Zhidong; Li, Yulin; Liu, Xianghong; /more authors..

    2012-07-06

    The Cornell Electron Storage Ring (CESR) has been reconfigured as a test accelerator (CesrTA) for a program of electron cloud (EC) research at ultra low emittance. The instrumentation in the ring has been upgraded with local diagnostics for measurement of cloud density and with improved beam diagnostics for the characterization of both the low emittance performance and the beam dynamics of high intensity bunch trains interacting with the cloud. A range of EC mitigation methods have been deployed and tested and their effectiveness is discussed. Measurements of the electron cloud's effect on the beam under a range of conditions are discussed along with the simulations being used to quantitatively understand these results.

  13. Biogenic Aerosols - Effects on Climate and Clouds. Cloud Optical...

    Office of Scientific and Technical Information (OSTI)

    A good range of cloud conditions were observed from clear sky to heavy rainfall. Authors: Niple, E. R. 1 ; Scott, H. E. 1 + Show Author Affiliations Aerodyne Research, Inc., ...

  14. cloud | OpenEI Community

    Open Energy Info (EERE)

    - 13:42 How cleantech-as-a-service will drive renewable energy adoption 2015 adoption Big Data clean tech clean-tech cleantech cleantech forum cleantech-as-a-service cloud...

  15. Millimeter Wave Cloud Radar (MMCR) Handbook

    SciTech Connect (OSTI)

    KB Widener; K Johnson

    2005-01-30

    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.

  16. Aircrew ionizing doses from radioactive dust cloud generated by nuclear burst. Master's thesis

    SciTech Connect (OSTI)

    Hickman, B.E.

    1982-03-01

    This report will evaluate the threat of radioactive fallout to which aircrew members will be exposed when flying through a descending fallout cloud. A computer program is developed for calculating the ionizing dose rate of a radioactive dust cloud as a function of time, and also the dose that an aircrew receives when flying through the respective cloud. A cloud model that is patterned after the AFIT fallout smearing code was developed. A comparison is made between the activities at various altitudes from 305 meters to 9150 meters to provide information for possible re-direction of flight. The external ionizing dose to the aircrew is computed by the new code considering the cloud size, the aircraft's transit time through the cloud, and the ingestion rate of radioactive particles into the aircraft's cabin. Information is also provided to indicate the method by which doses can be computed from a cloud of multiple bursts. The results demonstrate that total dose to each aircrew member is approximately 8 rems after flying through a fallout cloud one hour after cloud stabilization of a 1 Mt burst, with the mission continuing for eight hours subsequent to the cloud transit.

  17. Evaluating cloud retrieval algorithms with the ARM BBHRP framework

    SciTech Connect (OSTI)

    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.

    2008-03-10

    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

  18. Evaluation of high-level clouds in cloud resolving model simulations...

    Office of Scientific and Technical Information (OSTI)

    Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations Citation Details In-Document Search Title: Evaluation of high-level clouds in ...

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

    SciTech Connect (OSTI)

    Shupe, Matthew D

    2007-10-01

    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.

  20. Evaluation of Mixed-Phase Cloud Microphysics Parameterizations...

    Office of Scientific and Technical Information (OSTI)

    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. ...

  1. Preliminary Studies on the Variational Assimilation of Cloud...

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

    Studies on the Variational Assimilation of Cloud-Radiation Observations Using ARM ... A linearized cloud scheme and a radiation scheme including cloud effects have been ...

  2. MAGIC Cloud Properties from Zenith Radiance Data Final Campaign...

    Office of Scientific and Technical Information (OSTI)

    Title: MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary Cloud droplet size and optical depth are the most fundamental properties for understanding cloud ...

  3. A novel approach for introducing cloud spatial structure into...

    Office of Scientific and Technical Information (OSTI)

    A novel approach for introducing cloud spatial structure into cloud radiative transfer ... Sponsoring Org: USDOE Country of Publication: United Kingdom Language: English Word Cloud ...

  4. ARM Cloud Properties Working Group: Meeting Logistics

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

    to 1630: J. Comstock - Clouds with Low Optical Water Depth (CLOWD) 1630 to 1645: B. Albrecht - Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CLAP-MBL) 1645 to ...

  5. ARM - Field Campaign - Fall 1997 Cloud IOP

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

    The primary objective of the Cloud IOP was to generate a multi-platform data set that can ... Given the diversity of cloud types sampled during the IOP, the analysis of this data set ...

  6. Researching Impact of Clouds on Solar Plants

    Office of Energy Efficiency and Renewable Energy (EERE)

    Sandia National Laboratories (SNL) researchers developed a new system to monitor how clouds affect large-scale solar photovoltaic (PV) power plants. By observing cloud shape, size and movement, the...

  7. ARM - Measurement - Cloud particle size distribution

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

    from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle size distribution The number of cloud particles present in any given volume of air...

  8. ARM - Measurement - Cloud particle number concentration

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

    from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle number concentration The total number of cloud particles present in any given volume...

  9. Evaluating the MMF Using CloudSat

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

    its cloud Evaluate the MMF and improve its cloud simulations simulations Borrowed from Dave Randall, CSU The big picture The big picture ... ... . . Data ARM A-Train, MISR etc. ...

  10. What Makes Clouds Form, Grow and Die?

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

    Makes Clouds Form, Grow and Die? What Makes Clouds Form, Grow and Die? Simulations Show Raindrops Physics May Affect Climate Model Accuracy February 19, 2015 thunderstorm Brazil shuttle NASA 1984 540 PNNL scientists used real-world observations to simulate how small clouds are likely to stay shallow, while larger clouds grow deeper because they mix with less dry air. Pictured are small and large thunderstorms growing over southern Brazil, taken from the space shuttle. Image: NASA Johnson Space

  11. Unlocking the Secrets of Clouds

    Broader source: Energy.gov [DOE]

    Clouds may look soft, fluffy and harmless to the untrained eye, but to an expert climate model scientist they represent great challenges. Fortunately the Atmospheric Radiation Measurement (ARM) Climate and Research Facility is kicking off a five-month study which should significantly clear the air.

  12. ARM Data for Cloud Parameterization

    SciTech Connect (OSTI)

    Xu, Kuan-Man

    2006-10-02

    The PI's ARM investigation (DE-IA02-02ER633 18) developed a physically-based subgrid-scale saturation representation that fully considers the direct interactions of the parameterized subgrid-scale motions with subgrid-scale cloud microphysical and radiative processes. Major accomplishments under the support of that interagency agreement are summarized in this paper.

  13. Quantifying Diurnal Cloud Radiative Effects by Cloud Type in the Tropical Western Pacific

    SciTech Connect (OSTI)

    Burleyson, Casey D.; Long, Charles N.; Comstock, Jennifer M.

    2015-06-01

    Cloud radiative effects are examined using long-term datasets collected at the three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facilities in the tropical western Pacific. We quantify the surface radiation budget, cloud populations, and cloud radiative effects by partitioning the data by cloud type, time of day, and as a function of large scale modes of variability such as El Niño Southern Oscillation (ENSO) phase and wet/dry seasons at Darwin. The novel facet of our analysis is that we break aggregate cloud radiative effects down by cloud type across the diurnal cycle. The Nauru cloud populations and subsequently the surface radiation budget are strongly impacted by ENSO variability whereas the cloud populations over Manus only shift slightly in response to changes in ENSO phase. The Darwin site exhibits large seasonal monsoon related variations. We show that while deeper convective clouds have a strong conditional influence on the radiation reaching the surface, their limited frequency reduces their aggregate radiative impact. The largest source of shortwave cloud radiative effects at all three sites comes from low clouds. We use the observations to demonstrate that potential model biases in the amplitude of the diurnal cycle and mean cloud frequency would lead to larger errors in the surface energy budget compared to biases in the timing of the diurnal cycle of cloud frequency. Our results provide solid benchmarks to evaluate model simulations of cloud radiative effects in the tropics.

  14. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the systems ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  15. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  16. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  17. Clouds, Aerosols and Precipitation in

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

    the Marine Boundary Layer (CAP-MBL) Graciosa Island, Azores, NE Atlantic Ocean Graciosa Island, Azores, NE Atlantic Ocean May 2009-December 2010 May 2009-December 2010 Rob Wood, University of Washington Rob Wood, University of Washington AMF Deployment Team Thanks to Mark Miller: AMF Site Scientist Mark Miller: AMF Site Scientist Kim Nitschke: AMF Site Manager CAP-MBL Proposal Team Importance of Low-Clouds for Climate Imperative that we understand the processes controlling the formation,

  18. Dispersion of Hydrogen Clouds

    SciTech Connect (OSTI)

    Michael R. Swain; Eric S. Grilliot; Matthew N. Swain

    2000-06-30

    The following is the presentation of a simplification of the Hydrogen Risk Assessment Method previously developed at the University of Miami. It has been found that for simple enclosures, hydrogen leaks can be simulated with helium leaks to predict the concentrations of hydrogen gas produced. The highest concentrations of hydrogen occur near the ceiling after the initial transients disappear. For the geometries tested, hydrogen concentrations equal helium concentrations for the conditions of greatest concern (near the ceiling after transients disappear). The data supporting this conclusion is presented along with a comparison of hydrogen, LPG, and gasoline leakage from a vehicle parked in a single car garage. A short video was made from the vehicle fuel leakage data.

  19. Vertical microphysical profiles of convective clouds as a tool for

    Office of Scientific and Technical Information (OSTI)

    obtaining aerosol cloud-mediated climate forcings (Technical Report) | SciTech Connect Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings Citation Details In-Document Search Title: Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud

  20. Evaluation of Cloud Type Occurrences and Radiative Forcings Simulated by a Cloud Resolving Model Using Observations from Sa...

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

    Cloud Type Occurrences and Radiative Forcings Simulated by a Cloud Resolving Model Using Observations from Satellite and Cloud Radar Y. Luo and S. K. Krueger University of Utah Salt Lake City, Utah Introduction Because of both the various effects clouds exert on the earth-atmospheric system and the cloud feedback, correct representations of clouds in numerical models are critical for accurate climate modeling and weather forecast. Unfortunately, determination of clouds and their radiative

  1. Storm Peak Lab Cloud Property Validation

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

    Peak Lab Cloud Property Validation Experiment (STORMVEX) Operated by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for the U.S. Department of Energy, the second ARM Mobile Facility (AMF2) begins its inaugural deployment November 2010 in Steamboat Springs, Colorado, for the Storm Peak Lab Cloud Property Validation Experiment, or STORMVEX. For six months, the comprehensive suite of AMF2 instruments will obtain measurements of cloud and aerosol properties at various sites

  2. Testing a New Cirrus Cloud Parameterizaton

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

    Testing a New Cirrus Cloud Parameterization in NCAR CCM3 D. Zurovac-Jevtic, G. J. Zhang, and V. Ramanathan Center for Atmospheric Sciences Scripps Institute of Oceanography La Jolla, California Introduction Cirrus cloud cover and ice water content (IWC) are the two most important properties of cirrus clouds. However, in general circulation models (GCMs), their treatment is very crude. For example, in the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3), IWC is

  3. Midlatitude Continental Convective Clouds Experiment Science Objective

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

    Midlatitude Continental Convective Clouds Experiment Science Objective Despite improvements in computing power, current weather and climate models are unable to accurately reproduce the formation, growth, and decay of clouds and precipitation associated with storm systems. Not only is this due to a lack of data about precipitation, but also about the 3-dimensional environment of the surrounding clouds, winds, and moisture, and how that affects the transfer of energy between the sun and Earth. To

  4. Development and Testing of a Life Cycle Model and a Parameterization of Thin Mid-level Stratiform Clouds

    SciTech Connect (OSTI)

    Krueger, Steven K.

    2008-03-03

    We used a cloud-resolving model (a detailed computer model of cloud systems) to evaluate and improve the representation of clouds in global atmospheric models used for numerical weather prediction and climate modeling. We also used observations of the atmospheric state, including clouds, made at DOE's Atmospheric Radiation Measurement (ARM) Program's Climate Research Facility located in the Southern Great Plains (Kansas and Oklahoma) during Intensive Observation Periods to evaluate our detailed computer model as well as a single-column version of a global atmospheric model used for numerical weather prediction (the Global Forecast System of the NOAA National Centers for Environmental Prediction). This so-called Single-Column Modeling approach has proved to be a very effective method for testing the representation of clouds in global atmospheric models. The method relies on detailed observations of the atmospheric state, including clouds, in an atmospheric column comparable in size to a grid column used in a global atmospheric model. The required observations are made by a combination of in situ and remote sensing instruments. One of the greatest problems facing mankind at the present is climate change. Part of the problem is our limited ability to predict the regional patterns of climate change. In order to increase this ability, uncertainties in climate models must be reduced. One of the greatest of these uncertainties is the representation of clouds and cloud processes. This project, and ARM taken as a whole, has helped to improve the representation of clouds in global atmospheric models.

  5. Dynamics of Molecular Clouds: Observations, Simulations, and...

    Office of Scientific and Technical Information (OSTI)

    Simulations, and NIF Experiments Citation Details In-Document Search Title: Dynamics of Molecular Clouds: Observations, Simulations, and NIF Experiments You are ...

  6. What Makes Clouds Form, Grow and Die?

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

    were born and grew. Those formulas did not always reflect reality. With more advanced computers came the ability to explicitly simulate large-cloud systems instead of approximating...

  7. The LANL Cloud-Aerosol Model

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

    that incorporates two unique aspects in its formulation. First, the model employs a nonlinear solver that requires cloud-aerosol parameterizations be smooth or contain reasonable...

  8. Fragmentation in rotating isothermal protostellar clouds

    SciTech Connect (OSTI)

    Bodenheimer, P.; Tohline, J.E.; Black, D.C.

    1980-01-01

    Results of an extensive set of 3-D hydrodynamic calculations that have been performed to investigate the susceptibility of rotating clouds to gravitational fragmentation are presented. (GHT)

  9. Characterizing Arctic Mixed-phase Cloud Structure

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

    have two distinguished cloud base heights (CBHs) that can be defined by both ceilometer (black dots) and micropulse lidar (MPL; pink dots) measurements (Figure 1). For a...

  10. ARM - Field Campaign - Spring Cloud IOP

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

    govCampaignsSpring Cloud IOP ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Spring Cloud IOP 2000.03.01 - 2000.03.26 Lead Scientist : Gerald Mace For data sets, see below. Summary The Atmospheric Radiation Measurement (ARM) Program conducted a Cloud Intensive Operational Period (IOP) in March 2000 that was the first-ever effort to document the 3-dimensional cloud field from observational data. Prior

  11. ARM - Field Campaign - Cloud Radar IOP

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

    of aerosol properties during clear-sky conditions. The ETL Radar Meteorology and Oceanography Division will field their NOAAK scanning cloud radar near the new ARM millimeter...

  12. CHARACTERIZATION OF CLOUDS IN TITAN'S TROPICAL ATMOSPHERE

    SciTech Connect (OSTI)

    Griffith, Caitlin A.; Penteado, Paulo; Rodriguez, Sebastien; Baines, Kevin H.; Buratti, Bonnie; Sotin, Christophe; Clark, Roger; Nicholson, Phil; Jaumann, Ralf

    2009-09-10

    Images of Titan's clouds, possible over the past 10 years, indicate primarily discrete convective methane clouds near the south and north poles and an immense stratiform cloud, likely composed of ethane, around the north pole. Here we present spectral images from Cassini's Visual Mapping Infrared Spectrometer that reveal the increasing presence of clouds in Titan's tropical atmosphere. Radiative transfer analyses indicate similarities between summer polar and tropical methane clouds. Like their southern counterparts, tropical clouds consist of particles exceeding 5 {mu}m. They display discrete structures suggestive of convective cumuli. They prevail at a specific latitude band between 8 deg. - 20 deg. S, indicative of a circulation origin and the beginning of a circulation turnover. Yet, unlike the high latitude clouds that often reach 45 km altitude, these discrete tropical clouds, so far, remain capped to altitudes below 26 km. Such low convective clouds are consistent with the highly stable atmospheric conditions measured at the Huygens landing site. Their characteristics suggest that Titan's tropical atmosphere has a dry climate unlike the south polar atmosphere, and despite the numerous washes that carve the tropical landscape.

  13. Tropical Cloud Life Cycle and Overlap Structure

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

    Tropical Cloud Life Cycle and Overlap Structure Vogelmann, Andrew Brookhaven National Laboratory Jensen, Michael Brookhaven National Laboratory Kollias, Pavlos Brookhaven National ...

  14. ARM - Evaluation Product - Cloud Classification VAP

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

    properties includes cloud boundaries, thickness, phase, type, and precipitation information, and hence provides a useful tool for evaluation of model simulations and...

  15. ARM - Midlatitude Continental Convective Clouds - Single Column...

    Office of Scientific and Technical Information (OSTI)

    - Single Column Model Forcing (xie-scmforcing) Title: ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scmforcing) The constrained variational ...

  16. Ground-based Microwave Cloud Tomography

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

    Courtesy of Bernhard Mayer Cloud structure important to radiation - Cumulus (Benner & Evans 2001, Pincus et al. 2005), deep convection (DiGiuseppe & Tompkins 2003) - Horizontal...

  17. Mountain-induced Dynamics Influence Cloud Phase

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

    2010-2011 via coordinated projects targeting clouds, precipitation, and dynamics in the Park Range of Colorado. The National Science Foundation sponsored aircraft measurements as...

  18. DOE Research and Development Accomplishments Tag Cloud

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

    Database Tag Cloud This tag cloud is a specific type of weighted list that provides a quick look at the content of the DOE R&D Accomplishments database. It can be easily browsed because terms are in alphabetical order. With this tag cloud, there is a direct correlation between font size and quantity. The more times a term appears in the bibliographic citations, the larger the font size. This tag cloud is also interactive. Clicking on a term will activate a search for that term. Search

  19. ARM - PI Product - AERIoe Thermodynamic Profile and Cloud Retrieval for SGP

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

    CF during LABLE-2012 2 ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : AERIoe Thermodynamic Profile and Cloud Retrieval for SGP CF during LABLE-2012 [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The method is a

  20. ARM - PI Product - AERIoe Thermodynamic Profile and Cloud Retrieval for SGP

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

    CF during LABLE-2013 3 ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : AERIoe Thermodynamic Profile and Cloud Retrieval for SGP CF during LABLE-2013 [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The method is a

  1. ARM - VAP Product - goes12minnis-acf

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

    minnisgoes12minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES12MINNIS-ACF GOES-12: 0.3 degree cloud products, ARM Central Facility Active Dates 2003.04.01 - 2003.08.31

  2. ARM - VAP Product - goes7minnis-scm

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

    scm Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES7MINNIS-SCM GOES-7: 0.5 degree cloud products, Single Column Model Active Dates 1994.07.01 - 1994.07.31

  3. Electron Cloud Effects in Accelerators

    SciTech Connect (OSTI)

    Furman, M.A.

    2012-11-30

    Abstract We present a brief summary of various aspects of the electron-cloud effect (ECE) in accelerators. For further details, the reader is encouraged to refer to the proceedings of many prior workshops, either dedicated to EC or with significant EC contents, including the entire ?ECLOUD? series [1?22]. In addition, the proceedings of the various flavors of Particle Accelerator Conferences [23] contain a large number of EC-related publications. The ICFA Beam Dynamics Newsletter series [24] contains one dedicated issue, and several occasional articles, on EC. An extensive reference database is the LHC website on EC [25].

  4. VOCALS: The VAMOS Ocean-Cloud-Atmosphere-Land Study () | Data...

    Office of Scientific and Technical Information (OSTI)

    VOCALS: The VAMOS Ocean-Cloud-Atmosphere-Land Study Title: VOCALS: The VAMOS Ocean-Cloud-Atmosphere-Land Study VOCALS (VAMOS* Ocean-Cloud-Atmosphere-Land Study) is an international ...

  5. ARM - Field Campaign - Measuring Clouds at SGP with Stereo Photogramme...

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

    the form of the Point Cloud of Cloud Points Product (PCCPP). The PCCPP will: provide context on life-cycle stage and cloud position for vertically pointing radars, lidars, and...

  6. Intercomparison of model simulations of mixed-phase clouds observed...

    Office of Scientific and Technical Information (OSTI)

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

  7. Cloud Optical Properties from the Multifilter Shadowband Radiometer (MFRSRCLDOD). An ARM Value-Added Product

    SciTech Connect (OSTI)

    Turner, D. D.; McFarlane, S. A.; Riihimaki, L.; Shi, Y.; Lo, C.; Min, Q.

    2014-02-01

    The microphysical properties of clouds play an important role in studies of global climate change. Observations from satellites and surface-based systems have been used to infer cloud optical depth and effective radius. Min and Harrison (1996) developed an inversion method to infer the optical depth of liquid water clouds from narrow band spectral Multifilter Rotating Shadowband Radiometer (MFRSR) measurements (Harrison et al. 1994). Their retrieval also uses the total liquid water path (LWP) measured by a microwave radiometer (MWR) to obtain the effective radius of the warm cloud droplets. Their results were compared with Geostationary Operational Environmental Satellite (GOES) retrieved values at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site (Min and Harrison 1996). Min et al. (2003) also validated the retrieved cloud optical properties against in situ observations, showing that the retrieved cloud effective radius agreed well with the in situ forward scattering spectrometer probe observations. The retrieved cloud optical properties from Min et al. (2003) were used also as inputs to an atmospheric shortwave model, and the computed fluxes were compared with surface pyranometer observations.

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

    SciTech Connect (OSTI)

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

    2014-10-01

    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.

  9. Towards a Characterization of Arctic Mixed-Phase Clouds

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

    manual classification of cloud phase. Using collocated cloud radar and depolarization lidar observations, it is shown that mixed-phase conditions have a high correlation with a...

  10. Tropical Cloud Properties and Radiative Heating Profiles (Dataset...

    Office of Scientific and Technical Information (OSTI)

    Tropical Cloud Properties and Radiative Heating Profiles Title: Tropical Cloud Properties ... in that it uses the microwave radiometer to scale the radiosonde column water vapor. ...

  11. USING CLOUD CLASSIFICATION TO MODEL SOLAR VARIABILITY Matthew...

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

    Hourly cloud classified satellite images are compared to multiple years of ground measured ... type of cloud or weather pattern, as classified by NOAA. Instinctively, the type of ...

  12. City of Red Cloud, Nebraska (Utility Company) | Open Energy Informatio...

    Open Energy Info (EERE)

    Red Cloud, Nebraska (Utility Company) Jump to: navigation, search Name: Red Cloud Municipal Power Place: Nebraska Phone Number: 402-746-2215 Website: www.redcloudnebraska.comgover...

  13. Determination of Large-Scale Cloud Ice Water Concentration by...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Determination of Large-Scale Cloud Ice Water Concentration by Combining ... Title: Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface ...

  14. ARM: Aerosol Observing System (AOS): cloud condensation nuclei...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: Aerosol Observing System (AOS): cloud condensation nuclei data Aerosol Observing System (AOS): cloud condensation nuclei data Authors: Scott Smith ; Cynthia Salwen ; ...

  15. Humidity trends imply increased sensitivity to clouds in a warming...

    Office of Scientific and Technical Information (OSTI)

    is modulated by cloud properties; however, CRE also depends on humidity because clouds emit at wavelengths that are semi-transparent to greenhouse gases, most notably water vapour. ...

  16. ARM - Publications: Science Team Meeting Documents: Cloud Radiative...

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

    Research Facility: Part 2. The Vertical Redistribution of Radiant Energy by Clouds. ... Documentation with data of the effects of clouds on the radiant energy balance of the ...

  17. Effective Radius of Cloud Droplets Derived from Ground-based...

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

    which could eventually facilitate aerosol-cloud interactions. (Kim, Klein, Norris, JGR, 2005) SD z (m) SD LWP (g m -2 ) Efficacy of Aerosol-Cloud Interactions - ...

  18. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

  19. ARM: AOS: Cloud Condensation Nuclei Counter (Dataset) | Data...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: AOS: Cloud Condensation Nuclei Counter AOS: Cloud Condensation Nuclei Counter Authors: Scott Smith ; Cynthia Salwen ; Janek Uin ; Gunnar Senum ; Stephen Springston ; ...

  20. ARM - Evaluation Product - CMWG Data - SCM-Forcing Data, Cloud...

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

    data. Cloud microphysical properties derived from Mace's data of atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates are regridded to a...

  1. Direct Numerical Simulations and Robust Predictions of Cloud...

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

    cloud. Credit: Computational Science and Engineering Laboratory, ETH Zurich, Switzerland Direct Numerical Simulations and Robust Predictions of Cloud Cavitation Collapse PI Name:...

  2. The Sensitivity of Radiative Fluxes to Parameterized Cloud Microphysic...

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

    these fields include cloud altitude, cloud amount, liquid and ice content, particle size spectra, and radiative fluxes at the surface and the TOA. Comparisons with Atmospheric...

  3. ARM: Millimeter Wavelength Cloud Radar (MMCR): transmitted RF...

    Office of Scientific and Technical Information (OSTI)

    transmitted RF power Title: ARM: Millimeter Wavelength Cloud Radar (MMCR): transmitted RF power Millimeter Wavelength Cloud Radar (MMCR): transmitted RF power Authors: Karen ...

  4. ARM: Microwave Radiometer Retrievals (MWRRET) of Cloud Liquid...

    Office of Scientific and Technical Information (OSTI)

    Microwave Radiometer Retrievals (MWRRET) of Cloud Liquid Water and Precipitable Water Vapor Title: ARM: Microwave Radiometer Retrievals (MWRRET) of Cloud Liquid Water and ...

  5. Final Report on the Development of an Improved Cloud Microphysical...

    Office of Scientific and Technical Information (OSTI)

    Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative ... integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds ...

  6. Thin Liquid Water Clouds: Their Importance and Our Challenge...

    Office of Scientific and Technical Information (OSTI)

    Thin Liquid Water Clouds: Their Importance and Our Challenge Citation Details In-Document Search Title: Thin Liquid Water Clouds: Their Importance and Our Challenge Many of the ...

  7. Positive low cloud and dust feedbacks amplify tropical North...

    Office of Scientific and Technical Information (OSTI)

    amplify tropical North Atlantic Multidecadal Oscillation: CLOUD AND DUST FEEDBACK AND AMO Title: Positive low cloud and dust feedbacks amplify tropical North Atlantic ...

  8. Cloud microphysical relationships and their implication on entrainment...

    Office of Scientific and Technical Information (OSTI)

    Cloud microphysical relationships and their implication on entrainment and mixing mechanism for the stratocumulus clouds measured during the VOCALS project Citation Details ...

  9. Summary of workshop session F on electron-cloud instabilities...

    Office of Scientific and Technical Information (OSTI)

    Conference: Summary of workshop session F on electron-cloud instabilities Citation Details In-Document Search Title: Summary of workshop session F on electron-cloud instabilities ...

  10. Understanding and Improving CRM and GCM Simulations of Cloud...

    Office of Scientific and Technical Information (OSTI)

    of convection, clouds and radiative heating rate and fluxes using the ARM ... as well as cloud water contents in producing net radiative fluxes closer to observations. ...

  11. Monitoring of Precipitable Water Vapor and Cloud Liquid Path...

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

    Monitoring of Precipitable Water Vapor and Cloud Liquid Path from Scanning Microwave ... used to measure atmospheric precipitable water vapor (PWV) and cloud liquid path (CLP). ...

  12. Determining Cloud Ice Water Path from High-Frequency Microwave...

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

    Determining Cloud Ice Water Path from High-Frequency Microwave Measurements G. Liu ... A better understanding of cloud water content and its large-scale distribution ...

  13. Spectral observations of Ellerman bombs and fitting with a two-cloud model

    SciTech Connect (OSTI)

    Hong, Jie; Ding, M. D.; Li, Ying; Fang, Cheng; Cao, Wenda

    2014-09-01

    We study the Hα and Ca II 8542 Å line spectra of four typical Ellerman bombs (EBs) in the active region NOAA 11765 on 2013 June 6, observed with the Fast Imaging Solar Spectrograph installed at the 1.6 m New Solar Telescope at Big Bear Solar Observatory. Considering that EBs may occur in a restricted region in the lower atmosphere, and that their spectral lines show particular features, we propose a two-cloud model to fit the observed line profiles. The lower cloud can account for the wing emission, and the upper cloud is mainly responsible for the absorption at line center. After choosing carefully the free parameters, we get satisfactory fitting results. As expected, the lower cloud shows an increase of the source function, corresponding to a temperature increase of 400-1000 K in EBs relative to the quiet Sun. This is consistent with previous results deduced from semi-empirical models and confirms that local heating occurs in the lower atmosphere during the appearance of EBs. We also find that the optical depths can increase to some extent in both the lower and upper clouds, which may result from either direct heating in the lower cloud, or illumination by an enhanced radiation on the upper cloud. The velocities derived from this method, however, are different from those obtained using the traditional bisector method, implying that one should be cautious when interpreting this parameter. The two-cloud model can thus be used as an efficient method to deduce the basic physical parameters of EBs.

  14. HOT HYDROGEN IN DIFFUSE CLOUDS

    SciTech Connect (OSTI)

    Cecchi-Pestellini, Cesare; Duley, Walt W.; Williams, David A. E-mail: wwduley@uwaterloo.ca

    2012-08-20

    Laboratory evidence suggests that recombination of adsorbed radicals may cause an abrupt temperature excursion of a dust grain to about 1000 K. One consequence of this is the rapid desorption of adsorbed H{sub 2} molecules with excitation temperatures of this magnitude. We compute the consequences of injection of hot H{sub 2} into cold diffuse interstellar gas at a rate of 1% of the canonical H{sub 2} formation rate. We find that the level populations of H{sub 2} in J = 3, 4, and 5 are close to observed values, and that the abundances of CH{sup +} and OH formed in reactions with hot hydrogen are close to the values obtained from observations of diffuse clouds.

  15. Modeling Incoherent Electron Cloud Effects

    SciTech Connect (OSTI)

    Vay, Jean-Luc; Benedetto, E.; Fischer, W.; Franchetti, G.; Ohmi, K.; Schulte, D.; Sonnad, K.; Tomas, R.; Vay, J.-L.; Zimmermann, F.; Rumolo, G.; Pivi, M.; Raubenheimer, T.

    2007-06-18

    Incoherent electron effects could seriously limit the beam lifetime in proton or ion storage rings, such as LHC, SPS, or RHIC, or blow up the vertical emittance of positron beams, e.g., at the B factories or in linear-collider damping rings. Different approaches to modeling these effects each have their own merits and drawbacks. We describe several simulation codes which simplify the descriptions of the beam-electron interaction and of the accelerator structure in various different ways, and present results for a toy model of the SPS. In addition, we present evidence that for positron beams the interplay of incoherent electron-cloud effects and synchrotron radiation can lead to a significant increase in vertical equilibrium emittance. The magnitude of a few incoherent e+e- scattering processes is also estimated. Options for future code development are reviewed.

  16. ARM - Midlatitude Continental Convective Clouds

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

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

    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.

  17. Radiative properties of ice clouds

    SciTech Connect (OSTI)

    Mitchell, D.L.; Koracin, D.; Carter, E.

    1996-04-01

    A new treatment of cirrus cloud radiative properties has been developed, based on anomalous diffraction theory (ADT), which does not parameterize size distributions in terms of an effective radius. Rather, is uses the size distribution parameters directly, and explicitly considers the ice particle shapes. There are three fundamental features which characterize this treatment: (1) the ice path radiation experiences as it travels through an ice crystal is parameterized, (2) only determines the amount of radiation scattered and absorbed, and (3) as in other treatments, the projected area of the size distribution is conserved. The first two features are unique to this treatment, since it does not convert the ice particles into equivalent volume or area spheres in order to apply Mie theory.

  18. Scanning ARM Cloud Radar Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N; Johnson, K

    2012-06-18

    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.

  19. ARM - Midlatitude Continental Convective Clouds

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

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

    2012-01-19

    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.

  20. Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas

    2015-11-05

    In this paper, we evaluate high-level clouds in a cloud resolving model during two convective cases, ARM9707 and KWAJEX. The simulated joint histograms of cloud occurrence and radar reflectivity compare well with cloud radar and satellite observations when using a two-moment microphysics scheme. However, simulations performed with a single moment microphysical scheme exhibit low biases of approximately 20 dB. During convective events, two-moment microphysical overestimate the amount of high-level cloud and one-moment microphysics precipitate too readily and underestimate the amount and height of high-level cloud. For ARM9707, persistent large positive biases in high-level cloud are found, which are not sensitivemore » to changes in ice particle fall velocity and ice nuclei number concentration in the two-moment microphysics. These biases are caused by biases in large-scale forcing and maintained by the periodic lateral boundary conditions. The combined effects include significant biases in high-level cloud amount, radiation, and high sensitivity of cloud amount to nudging time scale in both convective cases. The high sensitivity of high-level cloud amount to the thermodynamic nudging time scale suggests that thermodynamic nudging can be a powerful ‘‘tuning’’ parameter for the simulated cloud and radiation but should be applied with caution. The role of the periodic lateral boundary conditions in reinforcing the biases in cloud and radiation suggests that reducing the uncertainty in the large-scale forcing in high levels is important for similar convective cases and has far reaching implications for simulating high-level clouds in super-parameterized global climate models such as the multiscale modeling framework.« less

  1. Absorption of solar radiation in broken clouds

    SciTech Connect (OSTI)

    Zuev, V.E.; Titov, G.A.; Zhuravleva, T.B.

    1996-04-01

    It is recognized now that the plane-parallel model unsatisfactorily describes the transfer of radiation through broken clouds and that, consequently, the radiation codes of general circulation models (GCMs) must be refined. However, before any refinement in a GCM code is made, it is necessary to investigate the dependence of radiative characteristics on the effects caused by the random geometry of cloud fields. Such studies for mean fluxes of downwelling and upwelling solar radiation in the visible and near-infrared (IR) spectral range were performed by Zuev et al. In this work, we investigate the mean spectral and integrated absorption of solar radiation by broken clouds (in what follows, the term {open_quotes}mean{close_quotes} will be implied but not used, for convenience). To evaluate the potential effect of stochastic geometry, we will compare the absorption by cumulus (0.5 {le} {gamma} {le} 2) to that by equivalent stratus ({gamma} <<1) clouds; here {gamma} = H/D, H is the cloud layer thickness and D the characteristic horizontal cloud size. The equivalent stratus clouds differ from cumulus only in the aspect ratio {gamma}, all the other parameters coinciding.

  2. ARM - Field Campaign - Arctic Cloud Infrared Imaging

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

    govCampaignsArctic Cloud Infrared Imaging Campaign Links Field Campaign Report ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Arctic Cloud Infrared Imaging 2012.07.16 - 2014.07.31 Lead Scientist : Joseph Shaw For data sets, see below. Abstract The 3rd-generation Infrared Cloud Imager (ICI) instrument was deployed close to the Great White facility at the North Slope of Alaska site and operated as

  3. Albedo and transmittance of inhomogeneous stratus clouds

    SciTech Connect (OSTI)

    Zuev, V.E.; Kasyanov, E.I.; Titov, G.A.

    1996-04-01

    A highly important topic is the study of the relationship between the statistical parameters of optical and radiative charactertistics of inhomogeneous stratus clouds. This is important because the radiation codes of general circulation models need improvement, and it is important for geophysical information. A cascade model has been developed at the Goddard Space Flight Center to treat stratocumulus clouds with the simplest geometry and horizontal fluctuations of the liquid water path (optical thickness). The model evaluates the strength with which the stochastic geometry of clouds influences the statistical characteristics of albedo and the trnasmittance of solar radiation.

  4. Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Sarna, Karolina; Russchenberg, Herman W. J.

    2016-03-14

    A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example case studies were chosen from the Atmospheric Radiation Measurementmore » (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius (re) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m–2 wide. For every LWP bin we present the correlation coefficient between ln re and ln ATB, as well as ACIr (defined as ACIr = –d ln re/d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACIr are in the range 0.01–0.1. Lastly, we show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.« less

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

    SciTech Connect (OSTI)

    Kollias, P.; Luke, E.; Rmillard, J.; Szyrmer, W.

    2011-07-02

    Several aspects of spectral broadening and drizzle growth in shallow liquid clouds remain not well understood. Detailed, cloud-scale observations of microphysics and dynamics are essential to guide and evaluate corresponding modeling efforts. Profiling, millimeter-wavelength (cloud) radars can provide such observations. In particular, the first three moments of the recorded cloud radar Doppler spectra, the radar reflectivity, mean Doppler velocity, and spectrum width, are often used to retrieve cloud microphysical and dynamical properties. Such retrievals are subject to errors introduced by the assumptions made in the inversion process. Here, we introduce two additional morphological parameters of the radar Doppler spectrum, the skewness and kurtosis, in an effort to reduce the retrieval uncertainties. A forward model that emulates observed radar Doppler spectra is constructed and used to investigate these relationships. General, analytical relationships that relate the five radar observables to cloud and drizzle microphysical parameters and cloud turbulence are presented. The relationships are valid for cloud-only, cloud mixed with drizzle, and drizzle-only particles in the radar sampling volume and provide a seamless link between observations and cloud microphysics and dynamics. The sensitivity of the five observed parameters to the radar operational parameters such as signal-to-noise ratio and Doppler spectra velocity resolution are presented. The predicted values of the five observed radar parameters agree well with the output of the forward model. The novel use of the skewness of the radar Doppler spectrum as an early qualitative predictor of drizzle onset in clouds is introduced. It is found that skewness is a parameter very sensitive to early drizzle generation. In addition, the significance of the five parameters of the cloud radar Doppler spectrum for constraining drizzle microphysical retrievals is discussed.

  6. Cloud-Resolving Model Simulation and Mosaic Treatment of Subgrid Cloud-Radiation Interaction

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

    of Energy Cloud-Based Transportation Management System Delivers Savings Cloud-Based Transportation Management System Delivers Savings October 21, 2014 - 1:53pm Addthis DOE's cloud based transportation management system (ATLAS) offers dramatically enhanced capabilities and modernization. ATLAS provides a powerful user-friendly system built to allow access to information to meet transportation needs. Its processes promote regulatory compliance, while providing access to qualified carriers and

  7. X.509 Authentication/Authorization in FermiCloud

    SciTech Connect (OSTI)

    Kim, Hyunwoo; Timm, Steven

    2014-11-11

    We present a summary of how X.509 authentication and authorization are used with OpenNebula in FermiCloud. We also describe a history of why the X.509 authentication was needed in FermiCloud, and review X.509 authorization options, both internal and external to OpenNebula. We show how these options can be and have been used to successfully run scientific workflows on federated clouds, which include OpenNebula on FermiCloud and Amazon Web Services as well as other community clouds. We also outline federation options being used by other commercial and open-source clouds and cloud research projects.

  8. QER- Comment of Cloud Peak Energy Inc

    Office of Energy Efficiency and Renewable Energy (EERE)

    Dear Ms Pickett Please find attached comments from Cloud Peak Energy as input to the Department of Energy’s Quadrennial Energy Review. If possible I would appreciate a confirmation that this email has been received Thank you.

  9. Developing and Evaluating Ice Cloud Parameterizations by

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

    by remote sensing is that the transfer functions which relate the observables (e. g., radar Doppler spectrum) to cloud properties (e. g., ice water content, or IWC) are not...

  10. Parameterizations of Cloud Microphysics and Indirect Aerosol...

    Office of Scientific and Technical Information (OSTI)

    A recent report published by the National Academy of Science states "The greatest ... 1977 and the "semi-direct" effect on cloud coverage e.g., Ackerman et al., 2000. ...

  11. HPC CLOUD APPLIED TO LATTICE OPTIMIZATION

    SciTech Connect (OSTI)

    Sun, Changchun; Nishimura, Hiroshi; James, Susan; Song, Kai; Muriki, Krishna; Qin, Yong

    2011-03-18

    As Cloud services gain in popularity for enterprise use, vendors are now turning their focus towards providing cloud services suitable for scientific computing. Recently, Amazon Elastic Compute Cloud (EC2) introduced the new Cluster Compute Instances (CCI), a new instance type specifically designed for High Performance Computing (HPC) applications. At Berkeley Lab, the physicists at the Advanced Light Source (ALS) have been running Lattice Optimization on a local cluster, but the queue wait time and the flexibility to request compute resources when needed are not ideal for rapid development work. To explore alternatives, for the first time we investigate running the Lattice Optimization application on Amazon's new CCI to demonstrate the feasibility and trade-offs of using public cloud services for science.

  12. Posters Sensitivity of Cirrus Cloud Radiative

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

    ... Takahashi, T., and K. Kuhara. 1993. Precipitation mechanisms of cumulonimbus clouds at Pohnpei, Micronesia. Meteor. Soc. Japan 71:21-31. Takano, Y., and K. N. Liou. 1989. Radiative ...

  13. Building a private cloud with Open Nebula

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

    Short Ryan Glenn Ross Nordeen Mentors: Andree Jacobson ISTI-OFF David Kennel DCS-1 LA-UR 10-05197 Why use Virtualized Cloud Computing for HPC? * Support Legacy Software Stacks *...

  14. Electron-Cloud Build-Up: Summary

    SciTech Connect (OSTI)

    Furman, M.A.

    2007-06-18

    I present a summary of topics relevant to the electron-cloud build-up and dissipation that were presented at the International Workshop on Electron-Cloud Effects 'ECLOUD 07' (Daegu, S. Korea, April 9-12, 2007). This summary is not meant to be a comprehensive review of the talks. Rather, I focus on those developments that I found, in my personal opinion, especially interesting. The contributions, all excellent, are posted in http://chep.knu.ac.kr/ecloud07/.

  15. Science on the Hill: Methane cloud hunting

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

    Methane cloud hunting Methane cloud hunting Los Alamos researchers go hunting for methane gas over the Four Corners area of northwest New Mexico and find a strange daily pattern. July 12, 2015 methane map Methane, the primary component of natural gas, is also a potent greenhouse gas, trapping energy in the atmosphere. Last year NASA released satellite images showing a hot spot in the area where New Mexico, Colorado, Utah and Arizona meet, prompting scientists to go in search of the sources.

  16. Ignition of Aluminum Particles and Clouds

    SciTech Connect (OSTI)

    Kuhl, A L; Boiko, V M

    2010-04-07

    Here we review experimental data and models of the ignition of aluminum (Al) particles and clouds in explosion fields. The review considers: (i) ignition temperatures measured for single Al particles in torch experiments; (ii) thermal explosion models of the ignition of single Al particles; and (iii) the unsteady ignition Al particles clouds in reflected shock environments. These are used to develop an empirical ignition model appropriate for numerical simulations of Al particle combustion in shock dispersed fuel explosions.

  17. Atmospheric State, Cloud Microphysics and Radiative Flux

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

    Mace, Gerald

    2008-01-15

    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.

  18. Atmospheric State, Cloud Microphysics and Radiative Flux

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

    Mace, Gerald

    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.

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

    SciTech Connect (OSTI)

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

    2014-07-27

    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.

  20. ARM - Publications: Science Team Meeting Documents: Day and Night cloud

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

    fraction - Cloud Inter-Compariosn IOP results Day and Night cloud fraction - Cloud Inter-Compariosn IOP results Genkova, Iliana University of Illinois-Champaign Long, Chuck Pacific Northwest National Laboratory Turner, David Pacific Northwest National Laboratory We present results from the CIC IOP from March-may, 2003. Day time and night time cloud fraction retrieval algorithms have been presented and intercompared. Amount of low, middle and high cloud have been estimated and compared to

  1. ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate

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

    Climate Campaign Links Final Campaign Summary BAECC Website ARM Data Discovery Browse Data Related Campaigns Biogenic Aerosols - Effects on Clouds and Climate: Cloud OD Sensor TWST 2014.06.15, Scott, AMF Biogenic Aerosols - Effects on Clouds and Climate: Extended Radiosonde IOP 2014.05.01, Nicoll, AMF Biogenic Aerosols - Effects on Clouds and Climate: FIGAERO-ToF-CIMS Instrument in Hyytiala with AMF-2 2014.04.01, Thornton, AMF Biogenic Aerosols - Effects on Clouds and Climate: Snowfall

  2. Longwave scattering effects on fluxes in broken cloud fields

    SciTech Connect (OSTI)

    Takara, E.E.; Ellingson, R.G.

    1996-04-01

    The optical properties of clouds in the radiative energy balance are important. Most works on the effects of scattering have been in the shortwave; but longwave effects can be significant. In this work, the fluxes above and below a single cloud layer are presented, along with the errors in assuming flat black plate clouds or black clouds. The predicted fluxes are the averaged results of analysis of several fields with the same cloud amount.

  3. Magellan Explores Cloud Computing for DOE's Scientific Mission

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

    Explores Cloud Computing for DOE's Scientific Mission Magellan Explores Cloud Computing for DOE's Scientific Mission March 30, 2011 Cloud Control -This is a picture of the Magellan management and network control racks at NERSC. To test cloud computing for scientific capability, NERSC and the Argonne Leadership Computing Facility (ALCF) installed purpose-built testbeds for running scientific applications on the IBM iDataPlex cluster. (Photo Credit: Roy Kaltschmidt) Cloud computing is gaining

  4. Estimation of the cloud transmittance from radiometric measurements at the ground level

    SciTech Connect (OSTI)

    Costa, Dario; Mares, Oana

    2014-11-24

    The extinction of solar radiation due to the clouds is more significant than due to any other atmospheric constituent, but it is always difficult to be modeled because of the random distribution of clouds on the sky. Moreover, the transmittance of a layer of clouds is in a very complex relation with their type and depth. A method for estimating cloud transmittance was proposed in Paulescu et al. (Energ. Convers. Manage, 75 690–697, 2014). The approach is based on the hypothesis that the structure of the cloud covering the sun at a time moment does not change significantly in a short time interval (several minutes). Thus, the cloud transmittance can be calculated as the estimated coefficient of a simple linear regression for the computed versus measured solar irradiance in a time interval Δt. The aim of this paper is to optimize the length of the time interval Δt. Radiometric data measured on the Solar Platform of the West University of Timisoara during 2010 at a frequency of 1/15 seconds are used in this study.

  5. Star formation relations in nearby molecular clouds

    SciTech Connect (OSTI)

    Evans, Neal J. II; Heiderman, Amanda; Vutisalchavakul, Nalin

    2014-02-20

    We test some ideas for star formation relations against data on local molecular clouds. On a cloud by cloud basis, the relation between the surface density of star formation rate and surface density of gas divided by a free-fall time, calculated from the mean cloud density, shows no significant correlation. If a crossing time is substituted for the free-fall time, there is even less correlation. Within a cloud, the star formation rate volume and surface densities increase rapidly with the corresponding gas densities, faster than predicted by models using the free-fall time defined from the local density. A model in which the star formation rate depends linearly on the mass of gas above a visual extinction of 8 mag describes the data on these clouds, with very low dispersion. The data on regions of very massive star formation, with improved star formation rates based on free-free emission from ionized gas, also agree with this linear relation.

  6. A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; Holmes, Aimee; Luke, Edward

    2016-06-10

    Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty informationmore » on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. This is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.« less

  7. A study of Monte Carlo radiative transfer through fractal clouds

    SciTech Connect (OSTI)

    Gautier, C.; Lavallec, D.; O`Hirok, W.; Ricchiazzi, P.

    1996-04-01

    An understanding of radiation transport (RT) through clouds is fundamental to studies of the earth`s radiation budget and climate dynamics. The transmission through horizontally homogeneous clouds has been studied thoroughly using accurate, discreet ordinates radiative transfer models. However, the applicability of these results to general problems of global radiation budget is limited by the plane parallel assumption and the fact that real clouds fields show variability, both vertically and horizontally, on all size scales. To understand how radiation interacts with realistic clouds, we have used a Monte Carlo radiative transfer model to compute the details of the photon-cloud interaction on synthetic cloud fields. Synthetic cloud fields, generated by a cascade model, reproduce the scaling behavior, as well as the cloud variability observed and estimated from cloud satellite data.

  8. A comparison of cloud properties at a coastal and inland site...

    Office of Scientific and Technical Information (OSTI)

    have examined differences in cloud liquid water paths (LWPs) at a coastal (Barrow) and an ... KEYWORDS: arctic clouds, cloud liquid water, microwave radiometer, ECMWF model, ...

  9. Probability Density Function Method for Langevin Equations with...

    Office of Scientific and Technical Information (OSTI)

    Language: English Subject: PDF method, uncertainty quantification, Langevin equation, Fokker-Planck equation, colored-noise, Large-Eddy-Diffusivity approximation Word Cloud More ...

  10. Incorporating the min-max mesh optimization method within the...

    Office of Scientific and Technical Information (OSTI)

    Incorporating the min-max mesh optimization method within the Target-Matrix Paradigm. ... Country of Publication: United States Language: English Word Cloud More Like This Full ...

  11. Incorporating the min-max mesh optimization method within the...

    Office of Scientific and Technical Information (OSTI)

    Title: Incorporating the min-max mesh optimization method within the Target-Matrix ... Country of Publication: United States Language: English Word Cloud More Like This Full ...

  12. Development and application of new methods to retrieve vertical...

    Office of Scientific and Technical Information (OSTI)

    information, so developments of remote sensing methods for retrievals of parameters in precipitating cloud condition was essential. Providing modelers with retrieval results ...

  13. Development and application of new methods to retrieve vertical...

    Office of Scientific and Technical Information (OSTI)

    methods for retrievals of parameters in precipitating cloud condition was essential. Providing modelers with retrieval results was also one of the key objectives of this research ...

  14. Modification and Application of a New Method for Retrieving Water...

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

    of a New Method for Retrieving Water-Cloud Microphysics Vertical Profile F.-L Chang and Z. Li Earth System Science Interdisciplinary Center University of Maryland College...

  15. The diverse use of clouds by CMS

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Andronis, Anastasios; Bauer, Daniela; Chaze, Olivier; Colling, David; Dobson, Marc; Fayer, Simon; Girone, Maria; Grandi, Claudio; Huffman, Adam; Hufnagel, Dirk; et al

    2015-01-01

    The resources CMS is using are increasingly being offered as clouds. In Run 2 of the LHC the majority of CMS CERN resources, both in Meyrin and at the Wigner Computing Centre, will be presented as cloud resources on which CMS will have to build its own infrastructure. This infrastructure will need to run all of the CMS workflows including: Tier 0, production and user analysis. In addition, the CMS High Level Trigger will provide a compute resource comparable in scale to the total offered by the CMS Tier 1 sites, when it is not running as part of themore » trigger system. During these periods a cloud infrastructure will be overlaid on this resource, making it accessible for general CMS use. Finally, CMS is starting to utilise cloud resources being offered by individual institutes and is gaining experience to facilitate the use of opportunistically available cloud resources. Lastly, we present a snap shot of this infrastructure and its operation at the time of the CHEP2015 conference.« less

  16. Magellan: experiences from a Science Cloud

    SciTech Connect (OSTI)

    Ramakrishnan, Lavanya; Zbiegel, Piotr; Campbell, Scott; Bradshaw, Rick; Canon, Richard; Coghlan, Susan; Sakrejda, Iwona; Desai, Narayan; Declerck, Tina; Liu, Anping

    2011-02-02

    Cloud resources promise to be an avenue to address new categories of scientific applications including data-intensive science applications, on-demand/surge computing, and applications that require customized software environments. However, there is a limited understanding on how to operate and use clouds for scientific applications. Magellan, a project funded through the Department of Energy?s (DOE) Advanced Scientific Computing Research (ASCR) program, is investigating the use of cloud computing for science at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing Facility (NERSC). In this paper, we detail the experiences to date at both sites and identify the gaps and open challenges from both a resource provider as well as application perspective.

  17. Parameterizations of Cloud Microphysics and Indirect Aerosol Effects

    SciTech Connect (OSTI)

    Tao, Wei-Kuo

    2014-05-19

    , 2005]. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated. 2. MODEL DESCRIPTION AND CASE STUDIES 2.1 GCE MODEL The model used in this study is the 2D version of the GCE model. Modeled flow is anelastic. Second- or higher-order advection schemes can produce negative values in the solution. Thus, a Multi-dimensional Positive Definite Advection Transport Algorithm (MPDATA) has been implemented into the model. All scalar variables (potential temperature, water vapor, turbulent coefficient and all five hydrometeor classes) use forward time differencing and the MPDATA for advection. Dynamic variables, u, v and w, use a second-order accurate advection scheme and a leapfrog time integration (kinetic energy semi-conserving method). Short-wave (solar) and long-wave radiation as well as a subgrid-scale TKE turbulence scheme are also included in the model. Details of the model can be found in Tao and Simpson (1993) and Tao et al. (2003). 2.2 Microphysics (Bin Model) The formulation of the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (cloud droplets and raindrops), and six types of ice particles: pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops

  18. Testing a Cloud Condensation Nuclei Remote Sensing Method

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

    is calculated from the Kohler theory using the hygroscopic properties of ammonium sulfate. Figure 1 shows the CCN concentration at supersaturations S of 0.01%, 0.1%, and 1%...

  19. ARM - Field Campaign - Boundary Layer Cloud IOP

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

    govCampaignsBoundary Layer Cloud IOP Campaign Links Campaign Images ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Boundary Layer Cloud IOP 2005.07.11 - 2005.08.07 Lead Scientist : William Shaw For data sets, see below. Abstract Investigators from Pacific Northwest National Laboratory, in collaboration with scientists from a number of other institutions, carried out a month of intensive measurements at

  20. Cloud-based Architecture Capabilities Summary Report

    SciTech Connect (OSTI)

    Vang, Leng; Prescott, Steven R; Smith, Curtis

    2014-09-01

    In collaborating scientific research arena it is important to have an environment where analysts have access to a shared of information documents, software tools and be able to accurately maintain and track historical changes in models. A new cloud-based environment would be accessible remotely from anywhere regardless of computing platforms given that the platform has available of Internet access and proper browser capabilities. Information stored at this environment would be restricted based on user assigned credentials. This report reviews development of a Cloud-based Architecture Capabilities (CAC) as a web portal for PRA tools.

  1. ARM - Evaluation Product - ARM Cloud Retrieval Ensemble Data

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

    cloud microphysical property ensemble data set created by assembling existing ARM cloud ... One purpose of developing such an ensemble data set is to provide a rough estimate of the ...

  2. Biogenic Aerosols„Effects on Clouds and Climate (BAECC)

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

    Biogenic Aerosols-Effects on Clouds and Climate (BAECC) Final Campaign Summary T Petj ... DOESC-ARM-15-051 Biogenic Aerosols-Effects on Clouds and Climate (BAECC) Final Campaign ...

  3. Simulation of E-Cloud Driven Instability And Its Attenuation...

    Office of Scientific and Technical Information (OSTI)

    Simulation of E-Cloud Driven Instability And Its Attenuation Using a Feedback System in the CERN SPS Citation Details In-Document Search Title: Simulation of E-Cloud Driven ...

  4. Layered Atlantic Smoke Interactions with Clouds (LASIC) Science...

    Office of Scientific and Technical Information (OSTI)

    Many uncertainties contribute to the highly variable model radiation fields: the aging of ... layer, and how the low clouds adjust to smoke-radiation and smoke-cloud interactions. ...

  5. Analysis of In situ Observations of Cloud Microphysics from M...

    Office of Scientific and Technical Information (OSTI)

    Cloud Microphysics from M-PACE Final Report, DOE Grant Agreement No. DE-FG02-06ER64168 Citation Details In-Document Search Title: Analysis of In situ Observations of Cloud ...

  6. W-Band ARM Cloud Radar - Specifications and Design

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

    W-Band ARM Cloud Radar - Specifications and Design K. B. Widener Pacific Northwest ... to develop and deploy the W-band ARM Cloud Radar (WACR) at the SGP central facility. ...

  7. Testing Cloud Microphysics Parameterizations in NCAR CAM5 with...

    Office of Scientific and Technical Information (OSTI)

    Title: Testing Cloud Microphysics Parameterizations in NCAR CAM5 with ISDAC and M-PACE Observations Arctic clouds simulated by the NCAR Community Atmospheric Model version 5 (CAM5) ...

  8. Joint retrievals of cloud and drizzle in marine boundary layer...

    Office of Scientific and Technical Information (OSTI)

    Specifically, the vertical structure of droplet size and water content of both cloud and ... cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g ...

  9. E-Cloud Build-up in Grooved Chambers

    SciTech Connect (OSTI)

    Venturini, Marco

    2007-05-01

    We simulate electron cloud build-up in a grooved vacuumchamber including the effect of space charge from the electrons. Weidentify conditions for e-cloud suppression and make contact withprevious estimates of an effective secondary electron yield for groovedsurfaces.

  10. Treatments of Inhomogeneous Clouds in a GCM Column Radiation...

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

    of fractal stratocumulus clouds. J. Atmos. Sci., 51, 2434 -2455. Chou, M.-D., M. J. Suarez, C.-H. Ho, M. M.-H. Yan, and K.-T. Lee, 1998: Parameterizations for cloud...

  11. Observations of the Madden Julian Oscillation for Cloud Modeling...

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

    Dyn.) Manus MJO signal in downwelling SW cloud radiative forcing GRL paper submitted Y. Wang, C. Long, and J. Mather Manus MJO signal in retrieved cloud amount GRL paper...

  12. ARM - Field Campaign - Thin Cloud Rotating Shadowband Radiometer

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

    Thin Cloud Rotating Shadowband Radiometer 2008.01.08 - 2008.07.18 Lead Scientist : Mary Jane Bartholomew For data sets, see below. Abstract The Thin-Cloud Rotating Shadowband...

  13. Nighttime Cloud Detection Over the Arctic Using AVHRR Data

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

    ... Table 3. SHEBA domain cloud statistics from the polar cloud mask for January-March 1998. ... Earth Radiation Budget Experiment (ERBE) and NOAA-9 AVHRR data from 1986 were matched to ...

  14. Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate...

    Office of Scientific and Technical Information (OSTI)

    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 ...

  15. The relationship between interannual and long-term cloud feedbacks

    SciTech Connect (OSTI)

    Zhou, Chen; Zelinka, Mark D.; Dessler, Andrew E.; Klein, Stephen A.

    2015-12-11

    The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual and long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.

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

    SciTech Connect (OSTI)

    Wang, Zhien

    2010-06-29

    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

  17. To the Cloud! Apidae Helps Modelers Turn Information into Knowledge |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy To the Cloud! Apidae Helps Modelers Turn Information into Knowledge To the Cloud! Apidae Helps Modelers Turn Information into Knowledge October 26, 2015 - 2:41pm Addthis Apidae is a collection of cloud-based simulation and data analysis tools that help modelers better understand their models. Image credit: BUILDlab. Apidae is a collection of cloud-based simulation and data analysis tools that help modelers better understand their models. Image credit: BUILDlab. Apidae

  18. Direct Numerical Simulations and Robust Predictions of Cloud Cavitation

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

    Collapse | Argonne Leadership Computing Facility Initiation of cloud cavitation collapse for 50,000 bubbles Initiation of cloud cavitation collapse for 50,000 bubbles. Jonas Sukys, ETH Zurich Direct Numerical Simulations and Robust Predictions of Cloud Cavitation Collapse PI Name: Petros Koumoutsakos PI Email: petros@ethz.ch Institution: ETH Zurich Allocation Program: INCITE Allocation Hours at ALCF: 72 Million Year: 2016 Research Domain: Engineering Cloud cavitation collapse-the evolution

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

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

    govCampaignsMarine ARM GPCI Investigation of Clouds (MAGIC) Campaign Links MAGIC Website ARM Data Discovery Browse Data Related Campaigns Marine ARM GPCI Investigations of Clouds (MAGIC): Measuring the Composition of Aerosol Particles 2013.07.01, Lewis, AMF Marine ARM GPCI Investigation of Clouds (MAGIC): Shortwave Hyperspectral Observations 2013.07.01, McBride, AMF Marine ARM GPCI Investigation of Clouds (MAGIC): Marine Ice Nuclei Collections 2013.06.01, DeMott, AMF Marine ARM GPCI

  20. Model of E-Cloud Instability in the Fermilab Recycler

    SciTech Connect (OSTI)

    Balbekov, V.

    2015-06-24

    Simple model of electron cloud is developed in the paper to explain e-cloud instability of bunched proton beam in the Fermilab Recycler. The cloud is presented as an immobile snake in strong vertical magnetic field. The instability is treated as an amplification of the bunch injection errors from the batch head to its tail. Nonlinearity of the e-cloud field is taken into account. Results of calculations are compared with experimental data demonstrating good correlation.

  1. Treatment of cloud radiative effects in general circulation models

    SciTech Connect (OSTI)

    Wang, W.C.; Dudek, M.P.; Liang, X.Z.; Ding, M.

    1996-04-01

    We participate in the Atmospheric Radiation Measurement (ARM) program with two objectives: (1) to improve the general circulation model (GCM) cloud/radiation treatment with a focus on cloud verticle overlapping and layer cloud optical properties, and (2) to study the effects of cloud/radiation-climate interaction on GCM climate simulations. This report summarizes the project progress since the Fourth ARM Science Team meeting February 28-March 4, 1994, in Charleston, South Carolina.

  2. Prediction of cloud droplet number in a general circulation model

    SciTech Connect (OSTI)

    Ghan, S.J.; Leung, L.R.

    1996-04-01

    We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.

  3. LES Modeling of High Resolution Satellite Cloud Spatial and Thermal

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

    Structure at ARM-SGP site: How well can we Simulate Clouds from Space? LES Modeling of High Resolution Satellite Cloud Spatial and Thermal Structure at ARM-SGP site: How well can we Simulate Clouds from Space? Dubey, Manvendra DOE/Los Alamos National Laboratory Chylek, Petr DOE/Los Alamos National Laboratory Reisner, Jon Los Alamos National Laboratory Porch, William Los Alamos National Laboratory Category: Cloud Properties We report high fidelity observations of the spatial and thermal

  4. Limiting Factors for Convective Cloud Top Height in the Tropics

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

    Limiting Factors for Convective Cloud Top Height in the Tropics M. P. Jensen and A. D. Del Genio National Aeronautics and Space Administration Goddard Institute for Space Studies Columbia University New York, New York Introduction Populations of tropical convective clouds are mainly comprised of three types: shallow trade cumulus, mid-level cumulus congestus and deep convective clouds (Johnson et al. 1999). Each of these cloud types has different impacts on the local radiation and water budgets.

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

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

    ProductsTropical Cloud Properties and Radiative Heating Profiles ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Tropical Cloud Properties and Radiative Heating Profiles 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.,

  6. The dependence of cloud particle size and precipitation probability...

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

    effect Hongfei Shao and Guosheng Liu Meteorology Department, Florida State University INTRODUCTION INTRODUCTION Anthropogenic aerosols enhance cloud reflectance of solar...

  7. Determining Best Estimates and Uncertainties in Cloud Microphysical

    Office of Scientific and Technical Information (OSTI)

    Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions (Technical Report) | SciTech Connect Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions Citation Details In-Document Search Title: Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for

  8. Mean-state acceleration of cloud-resolving models and large eddy simulations

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Jones, C. R.; Bretherton, C. S.; Pritchard, M. S.

    2015-10-29

    In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate themore » evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.« less

  9. Mean-state acceleration of cloud-resolving models and large eddy simulations

    SciTech Connect (OSTI)

    Jones, C. R.; Bretherton, C. S.; Pritchard, M. S.

    2015-10-29

    In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate the evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.

  10. Retrievals of Cloud Fraction and Cloud Albedo from Surface-based...

    Office of Scientific and Technical Information (OSTI)

    Ground-based radiation measurements have been widely conducted to gain information on ... Compared to Min2008 and Liu2011, the XL2013 retrieval of cloud albedo tends to be greater ...