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Sample records for vaisala ceilometer vceil

  1. ARM - PI Product - Vaisala CL51 ceilometer

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

    ProductsVaisala CL51 ceilometer Citation DOI: 10.5439/1177195 [ What is this? ] 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 : Vaisala CL51 ceilometer [ research data - External funding ] Vaisala CL51 ceilometer providing attenuated backscatter coefficients and cloud base heights. Purpose Understand vertical profiles of aerosol and cloud. Data Details Developed by Ewan OConnor | Reijo Roinonen Contact

  2. ARM: ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

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

    Karen Johnson; Michael Jensen

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

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

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

    Karen Johnson; Michael Jensen

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

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

    SciTech Connect (OSTI)

    Karen Johnson; Michael Jensen

    1996-11-08

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

  5. ARM: ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

    SciTech Connect (OSTI)

    Karen Johnson; Michael Jensen

    1996-11-08

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

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

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

    Karen Johnson; Michael Jensen

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

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

    SciTech Connect (OSTI)

    Karen Johnson; Michael Jensen

    1996-11-08

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

  8. ARM: Vaisala Ceilometer (VCEIL): cloud base heights, 25,000 feet...

    Office of Scientific and Technical Information (OSTI)

    OSTI Identifier: 1025313 DOE Contract Number: DE-AC05-00OR22725 Resource Type: Dataset Data Type: Numeric Data Research Org: Atmospheric Radiation Measurement (ARM) Archive, Oak ...

  9. ARM - Instrument - vceil

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

    govInstrumentsvceil Documentation VCEIL : Handbook Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Error occurred. Instrument...

  10. Laser Ceilometer CL51 Demonstration Field Campaign Report

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

    ... and G Pappalardo (eds), Proceedings of SPIE vol. 8534, id. 853409, doi:10.111712.9743. Morris, VR, C Flynn, and H Winston. 2009. "A demonstration of Vaisala's new ceilometer." ...

  11. Vaisala CL51 ceilometer (Dataset) | Data Explorer

    Office of Scientific and Technical Information (OSTI)

    Authors: Ewan OConnor Publication Date: 2015-04-01 OSTI Identifier: 1177195 DOE Contract Number: DE-AC05-00OR22725 Resource Type: Dataset Data Type: Numeric Data Research ...

  12. Ceilometer Instrument Handbook

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

    20 Ceilometer Instrument Handbook VR Morris April 2016 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.

  13. DISCLAIMER

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

    DOE/SC-ARM-TR-020 Vaisala Ceilometer (VCEIL) Handbook VR Morris March 2012 Work supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research VR Morris, March 2012, DOE/SC-ARM-TR-020 ii Contents 1.0 General Overview ................................................................................................................................. 1 2.0 Contacts

  14. Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern...

    Office of Scientific and Technical Information (OSTI)

    Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern Great Plains Site Title: Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern Great Plains Site ...

  15. In Situ Validation of a Correction for Time-Lag and Bias Errors in Vaisala RS80-H Radiosonde Humidity Measurements

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

    In Situ Validation of a Correction for Time-Lag and Bias Errors in Vaisala RS80-H Radiosonde Humidity Measurements L. M. Miloshevich National Center for Atmospheric Research Boulder, Colorado H. Vömel and S. J. Oltmans National Oceanic and Atmospheric Administration Boulder, Colorado A. Paukkunen Vaisala Oy Helsinki, Finland Introduction Radiosonde relative humidity (RH) measurements are fundamentally important to Atmospheric Radiation Measurement (ARM) Program goals because they are used in a

  16. Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern Great Plains Site

    SciTech Connect (OSTI)

    Jensen, M. P.; Holdridge, D.; Survo, P.; Lehtinen, R.; Baxter, S.; Toto, T.; Johnson, K. L.

    2015-11-02

    In the fall of 2013, the Vaisala RS41-SG (4th generation) radiosonde was introduced as a replacement for the RS92-SGP radiosonde with improvements in measurement accuracy of profiles of atmospheric temperature, humidity and pressure. Thus, in order to help characterize these improvements, an intercomparison campaign was undertaken at the US Department of Energy's Atmospheric Radiation Measurement (ARM) Facility site in north Central Oklahoma USA. During 3–8 June 2014, a total of 20 twin-radiosonde flights were performed in a variety of atmospheric conditions representing typical midlatitude continental summertime conditions. The results suggest that the RS92 and RS41 measurements generally agree within manufacturer specified tolerances with notable exceptions when exiting liquid cloud layers where the "wet bulbing" effect is mitigated in the RS41 observations. The RS41 measurements also appear to show a smaller impact from solar heating. These results suggest that the RS41 does provide important improvements, particularly in cloudy conditions, but under most observational conditions the RS41 and RS92 measurements agree within the manufacturer specified limits and so a switch to RS41 radiosondes will have little impact on long-term observational records.

  17. Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern Great Plains Site

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

    Jensen, M. P.; Holdridge, D.; Survo, P.; Lehtinen, R.; Baxter, S.; Toto, T.; Johnson, K. L.

    2015-11-02

    In the fall of 2013, the Vaisala RS41-SG (4th generation) radiosonde was introduced as a replacement for the RS92-SGP radiosonde with improvements in measurement accuracy of profiles of atmospheric temperature, humidity and pressure. Thus, in order to help characterize these improvements, an intercomparison campaign was undertaken at the US Department of Energy's Atmospheric Radiation Measurement (ARM) Facility site in north Central Oklahoma USA. During 3–8 June 2014, a total of 20 twin-radiosonde flights were performed in a variety of atmospheric conditions representing typical midlatitude continental summertime conditions. The results suggest that the RS92 and RS41 measurements generally agree within manufacturermore » specified tolerances with notable exceptions when exiting liquid cloud layers where the "wet bulbing" effect is mitigated in the RS41 observations. The RS41 measurements also appear to show a smaller impact from solar heating. These results suggest that the RS41 does provide important improvements, particularly in cloudy conditions, but under most observational conditions the RS41 and RS92 measurements agree within the manufacturer specified limits and so a switch to RS41 radiosondes will have little impact on long-term observational records.« less

  18. Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

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

    Dzambo, Andrew M.; Turner, David D.; Mlawer, Eli J.

    2016-04-12

    Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwellingmore » radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes

  19. Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

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

    Dzambo, A. M.; Turner, D. D.; Mlawer, E. J.

    2015-10-20

    Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV),moredownwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km MSL), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, mid-latitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities done for clear-sky scenes use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RH are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this

  20. Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

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

    Dzambo, Andrew M.; Turner, David D.; Mlawer, Eli J.

    2016-04-12

    Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV),more » downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. Lastly, the

  1. ARM: Ceilometer (Dataset) | Data Explorer

    Office of Scientific and Technical Information (OSTI)

    Sponsoring Org: USDOE Office of Science (SC), Biological and Environmental Research (BER) Country of Publication: United States Availability: ORNL Language: English Subject: 54 ...

  2. ARM - Data Announcements Article

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

    5, 2014 [Data Announcements] Ceilometer Derived Planetary Boundary Layer Height Datastream Available Bookmark and Share At the 2012 ASR Science Team Meeting, this comparison received positive feedback from researchers. At the 2012 ASR Science Team Meeting, this comparison received positive feedback from researchers. Planetary Boundary Layer (PBL) height data are now being collected at ARM sites and mobile facilities using an enhanced gradient method algorithm from the Vaisala Ceilometers

  3. Impact of Vaisala Radiosonde Humidity Corrections on ARM IOP Data

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

    Energy Impact of Teaming Arrangements on Small Business Status Impact of Teaming Arrangements on Small Business Status Impact of Teaming Arrangements on Small Business Status The Department of Energy is planning to set aside for small businesses a number of acquisitions of a very complex nature, requiring a myriad of capabilities on the part of offerors, which might result in teaming arrangements or joint ventures being formed. Given this, the Department believes that potential offerors

  4. ARM: Vaisala Automatic Weather Station (Dataset) | Data Explorer

    Office of Scientific and Technical Information (OSTI)

    Authors: Donna Holdridge ; Cristina Marinovici ; Jenni Kyrouac Publication Date: 2014-09-08 OSTI Identifier: 1182027 DOE Contract Number: DE-AC05-00OR22725 Resource Type: Dataset ...

  5. ARM: Belfort Laser Ceilometer (BLC): profiles (Dataset) | Data...

    Office of Scientific and Technical Information (OSTI)

    Sponsoring Org: USDOE Office of Science (SC), Biological and Environmental Research (BER) Country of Publication: United States Availability: ORNL Language: English Subject: 54 ...

  6. Laser Ceilometer CL51 Demonstration Field Campaign Report

    Office of Scientific and Technical Information (OSTI)

    ...stmpostersview?id1171. 7.0 References Schafer, K, P Wagner, S Emeis, C Jahn, C Munkel, and P Suppan. 2012. "Mixing layer height and air pollution levels in urban area." ...

  7. Laser Ceilometer CL51 Demonstration Field Campaign Report (Technical...

    Office of Scientific and Technical Information (OSTI)

    ... Close Cite: Bibtex Format Close 0 pages in this document matching the terms "" Search For Terms: Enter terms in the toolbar above to search the full text of this document for ...

  8. ARM - Evaluation Product - Ceilometer Corrected for Ship Motion...

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

    product for the MAGIC and ACAPEX campaigns. Data Details Developed by Michael Jensen Contact Tami Toto ttoto@bnl.gov (631) 344-7021 Upton, NY 11973 Resource(s) Data...

  9. Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern...

    Office of Scientific and Technical Information (OSTI)

    OSTI Identifier: 1228850 Report Number(s): BNL--108582-2015-JA Journal ID: ISSN 1867-8610; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000 GrantContract Number: SC00112704 Type: ...

  10. MHK ISDB/Instruments/Vaisala WINDCAP Ultrasonic Wind Sensor WMT700...

    Open Energy Info (EERE)

    Velocity Planar Measurement (Current), 3D Velocity Volumetric Measurement (Current), Density (Ice), Direction (Ice), Speed (Ice), Thickness (Ice), Pressure (Tidal), Sea Surface...

  11. ARM - Publications: Science Team Meeting Documents

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

    Two-Year Comparison of Cloud-Base Height Measured by MPL, MMCR, and VCEIL at the ARMNSA Barrow Facility Petracca, B., Shaw, J.A., and Zak, B.D., Montana State University and ...

  12. ARM - Measurement - Cloud base height

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

    ARM Instruments BLC : Belfort Laser Ceilometer CEIL : Ceilometer IRSI : Infra-Red Sky ... External Instruments NOAASURF : NOAA Surface Meteorology Data, collected by NWS and ...

  13. ARM - AMF2 Architecture

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

    Barometer (Vaisala) CR-3000 logger (Campbell Sci) GNDRAD 1-PSP (Eppley) 1-PIR ... Barometer (Vaisala) CR-3000 logger (Campbell Sci) Bulk Aerodynamic Flux (BAF) GMP343 ...

  14. SCM Working Group

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

    Clouds and Cloud Microphysical Properties Millimeter-wavelength cloud radar Micropulse Lidars Laser Ceilometers Aircraft Microwave Radiometers Surface Radiation Radiometric ...

  15. ARM - Facility News Article

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

    August 15, 2008 [Facility News] New Ceilometer Evaluated at Southern Great Plains Site Bookmark and Share Dan Nelson, SGP facilities manager, inspects the new ceilometer during its evaluation period on the platform of the SGP Guest Instrument Facility between June and July 2008. Dan Nelson, SGP facilities manager, inspects the new ceilometer during its evaluation period on the platform of the SGP Guest Instrument Facility between June and July 2008. To analyze cloud properties, ARM scientists

  16. 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...

  17. Microsoft Word - Group4CloudtoPrecip(RS).docx

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

    Ceilometer first cloud base, radar reflectivity, and various Doppler moments (Doppler velocity power spectrum, spectrum width, and spectrum skewness) were smoothed to 2-, 5-, and ...

  18. Section 75

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

    temperature profiles from the radio acoustic sounding system (RASS); and the cloud ... Currently, only the lack of ceilometers prevent the running of this VAP on data from the ...

  19. PowerPoint Presentation

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

    Cloud and Radiation Measurements Millimeter-wavelength cloud radar Micropulse Lidars Laser Ceilometers Aircrafts Surface Microwave Radiometers Surface Radiometric Instrument System ...

  20. ARM Value-Added Cloud Products: Description and Status

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

    This VAP combines the data from the millimeter cloud radar (MMCR), micropulse lidar (MPL), laser ceilometer, microwave radiometer (MWR), and surface measurements. It produces a ...

  1. FACT SHEET U.S. Department of Energy ARM Mobile Facility

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

    Alaska (2013-2018) * 95-GHz W-Band ARM Cloud Radar * Balloon-Borne Sounding System * Doppler Lidar, Micropulse Lidar, and Laser Ceilometer * Microwave Radiometer * Microwave...

  2. ARM - Data Announcements Article

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

    6, 2015 Data Announcements New and Improved Ceilometer Datastream Available Bookmark and Share First cloud base height data are shown above at the various heights at which cloud ...

  3. 1

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

    Preliminary Correction of Vaisala Radiosonde Humidity Measurements for Slow Sensor Time-Response at Cold Temperatures L. M. Miloshevich and A. J. Heymsfield National Center for Atmospheric Research Boulder, Colorado A. Paukkunen Vaisala Oy Helsinki, Finland Introduction The goal of this study is to improve the accuracy of relative humidity (RH) measurements from Vaisala radiosondes, especially in the upper troposphere (UT), by correcting measurement error that results from slow time-response of

  4. ARM TR-008

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

    ...Relative Humidity (TRH) Probe Campbell Scientific Inc. 815 W. 1800 N. Logan UT ... TRH sensor: Thermistor and Vaisala RH, Campbell Scientific Model HMP35C Temperature and ...

  5. Revised for pdf of instruments 8.5x11 (2)

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

    RWP KA/WSACR KAZR MPL MWRHF SASHE AERI SWS CSPHOT VCEIL MWR3C MWR TSI RSS PWD 10IRT 10MFR SWATS EBBR ORG DISDROMETER VDIS WBRG SUOMINET BRS-BSRN NIMFR MFRN1 SIRS MFR USDA ARRAY SIRS TEST BED RAIN MET 10 METER TB TOWER 10 METER TOWER DL N W E S A R M S G P 60 METER TOWER (TWR) PGS RAMAN LIDAR AOS ACSM,APS,CCN,CLAP, CPC,NEPHELOMETER, PASS3,PSAP,TDMA. ECOR OPTICAL CLUSTER CCB OCO GIF OPTICAL TRAILER RCF ERL CULTIVATED GROUND SONDE CO2FLX,IRT, MFR,UIR. THWAPS IRT WACR CENTRAL CLUSTER SCALE

  6. Section 74

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

    The Belfort Laser Ceilometer (BLC) is also an eye-safe instrument. It is a laser-based system, where the signal is averaged to produce a sample every 30 seconds. The vertical...

  7. ARM - Campaign Instrument - ceil-umiami

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

    would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Campaign Instrument : Ceilometer(University of Miami) (CEIL-UMIAMI) Instrument Categories...

  8. ARM - Publications: Science Team Meeting Documents

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

    For the surface data, the cloud-base height is derived laser ceilometer and cloud top height is derived cloud radar, and cloud temperatures are measured from ARM radiosonde ...

  9. Property:CommProtocol | Open Energy Information

    Open Energy Info (EERE)

    Doppler Volume Sampler + RS-232 + MHK ISDBInstrumentsVaisala WINDCAP Ultrasonic Wind Sensor WMT700 + RS-232 + MHK ISDBInstrumentsVector V102 GPS Compass + RS-232 + MHK ISDB...

  10. ARM - Facility News Article

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

    be difficult, even dangerous, in the arctic climates of the North Slope of Alaska (NSA). ... manufactured by Vaisala, is scheduled to be installed at the NSA site later this summer. ...

  11. Applicant/Institution: The University of Georgia Research Foundation...

    Office of Scientific and Technical Information (OSTI)

    ... Wind profiles from 20 to 905 m height were recorded every 30 ... probe (GMP343, Vaisala, Finland) with an atmospheric ... is important due to the energy and momentum they ...

  12. A New Microwave Temperature Profiler … First Measurements in...

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

    Institute of Atmospheric Physics CNR, Italy Introduction Temperature inversions are a ... the Figure 4. MTP-5P have been tested in Italy by Rome IFA-CNR and compared with Vaisala ...

  13. 1

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

    Vaisala RS-80H Radiosonde Dry-Bias Correction Redux B. M. Lesht Environmental Research Division Argonne National Laboratory Argonne, Illinois S. J. Richardson Department of Meteorology Pennsylvania State University University Park, Pennsylvania Introduction In previous studies (e.g., Lesht 1997, 1998, 1999; Lesht and Richardson 2001; Richardson et al. 2000) we examined the effects of dry bias in Vaisala RS-80H radiosonde humidity measurements on Atmospheric Radiation Measurement (ARM) data. Some

  14. ARM - Facility News Article

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

    Improved Radiosonde Sensor Ready for Launch Bookmark and Share At the end of a string tied to the weather balloon, a small sensor package, called a radiosonde, contains the "brains" for measuring atmospheric temperature, pressure and humidity. As part of the Balloon Borne Sounding System, radiosondes launched at the the ARM Climate Research Facility sites are supplied by Vaisala, one of the market leaders of this technology. Vaisala began phasing out production of the RS90 radiosondes

  15. miller-er-99.PDF

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

    Correction for Dry Bias in Vaisala Radiosonde RH Data E. R. Miller, J. Wang, and H. L. Cole National Center for Atmospheric Research Atmospheric Technology Division Boulder, Colorado Abstract Extensive data analysis of sounding data from the Tropical Ocean Global Atmosphere-Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) and other research projects coupled with supporting evidence from other sources have lead to the conclusion that there is a dry bias in Vaisala radiosonde relative

  16. Radiosondes Corrected for Inaccuracy in RH Measurements

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

    Miloshevich, Larry

    2008-01-15

    Corrections for inaccuracy in Vaisala radiosonde RH measurements have been applied to ARM SGP radiosonde soundings. The magnitude of the corrections can vary considerably between soundings. The radiosonde measurement accuracy, and therefore the correction magnitude, is a function of atmospheric conditions, mainly T, RH, and dRH/dt (humidity gradient). The corrections are also very sensitive to the RH sensor type, and there are 3 Vaisala sensor types represented in this dataset (RS80-H, RS90, and RS92). Depending on the sensor type and the radiosonde production date, one or more of the following three corrections were applied to the RH data: Temperature-Dependence correction (TD), Contamination-Dry Bias correction (C), Time Lag correction (TL). The estimated absolute accuracy of NIGHTTIME corrected and uncorrected Vaisala RH measurements, as determined by comparison to simultaneous reference-quality measurements from Holger Voemel's (CU/CIRES) cryogenic frostpoint hygrometer (CFH), is given by Miloshevich et al. (2006).

  17. Testing the Wind in the Columbia River Gorge | Department of Energy

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

    Testing the Wind in the Columbia River Gorge Testing the Wind in the Columbia River Gorge April 11, 2016 - 9:59am Addthis Project team members from WFIP 2 meet at the Biglow Canyon Wind Farm, a data-collection site in Sherman County, Oregon. Photo courtesy: Justin Sharp/Vaisala Project team members from WFIP 2 meet at the Biglow Canyon Wind Farm, a data-collection site in Sherman County, Oregon. Photo courtesy: Justin Sharp/Vaisala Joel Cline Meteorologist, Wind Program Fast Facts About WFIP2:

  18. Southern Great Plains Newsletter

    SciTech Connect (OSTI)

    J. Prell L. R. Roeder

    2010-09-01

    This months issue contains the following articles: (1) Scientists convene at SGP site for complex convective cloud experiment; (2) VORTEX2 spins down; (3) Sunphotometer supports SPARTICUS (a Sun and Aureole Measurement imaging sunphotometer) campaign and satellite validation studies; and (4) Ceilometer represents first deployment of new ground-based instruments from Recovery Act.

  19. Section 18

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

    Analysis of the Temperature Dependence of Low Cloud Optical Thickness Using ARM Data and the GISS GCM A. D. Del Genio NASA/Goddard Institute for Space Studies New York, New York A. B. Wolf Science Systems and Applications, Inc. New York, New York G. Tselioudis Columbia University New York, New York One of the larger uncertainties in global climate model C The Belfort Laser Ceilometer (BLC) measures cloud base estimates of sensitivity to external perturbations is the height projected climate

  20. ARM - Facility News Article

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

    10, 2010 [Facility News] Supporting Science at Summit Station, Greenland Bookmark and Share This month, an ARM micropulse lidar and ceilometer began collecting data from Summit Station in Greenland as part of the ICECAPS field campaign that runs through October 2014. Scientist Matthew Shupe joined colleagues on location to install the ICECAPS mobile laboratory, documenting their progress through his field blog. Great job, Matt! Visit the campaign website for more information

  1. ARM - Publications: Science Team Meeting Documents

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

    Comparisons of Measurements of Cloud Lower Boundaries by the MPL, BLC, MMCR, BBSS and AERI Han, D., and Ellingson, R.G., University of Maryland Eighth Atmospheric Radiation Measurement (ARM) Science Team Meeting The cloud lower boundary is an important factor in radiative transfer under various cloud conditions. Several ground-based instruments at the ARM CART Central Facility, including the micro pulse lidar (MPL), the Belfort laser ceilometer (BLC), and the MilliMeter Cloud profiling Radar

  2. ARM - Publications: Science Team Meeting Documents

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

    An Integrated Algorithm for Retrieving Non-precipitating Stratus Cloud Microphysical Properties Using Millimeter Radar and Microwave Radiometer Data Dong, X. and Mace, G.G., University of Utah Eleventh Atmospheric Radiation Measurement (ARM) Science Team Meeting A new algorithm has been developed to retrieve the vertical profiles of cloud microphysical properties using the ground- based measurements of cloud radar, laser ceilometer, and microwave and solar radiometers. A relationship between

  3. ARM - Data Announcements Article

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

    June 30, 2008 [Data Announcements] Black Forest, Germany, WACR-ARSCL Evaluation Products Now Available Bookmark and Share FKB WACR-ARSCL Reflectivity Best Estimate data plot example. Observations from the 95 GHz W-band ARM Cloud Radar (WACR), Micropulse Lidar, and ceilometer have been combined using the new WACR-Active Remote Sensing of Clouds (WACR-ARSCL) value-added process (VAP) (Kollias and Miller, 2007) to produce cloud boundaries and time-height profiles of cloud location, radar moments,

  4. 1

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

    Validation of Satellite Retrieved Cloud Amounts Over the Continental United States with Automatic Sciences Research Center Ceilometer Data D.R. Doelling, D.N. Phan, and D.A. Spangenberg Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis National Aeronautics and Space Administration - Langley Research Center Hampton, Virginia Introduction The National Aeronautics and Space Administration (NASA) Langley cloud and radiation retrieval products are produced near real time over the

  5. marchand-99.PDF

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

    Two-Year Cloud Climatology for the Southern Great Plains Site R. T. Marchand, T. P. Ackerman, and E. E. Clothiaux Pennsylvania State University University Park, Pennsylvania Introduction The addition of the millimeter cloud radar to the suite of instruments at the Southern Great Plains (SGP) site has provided the necessary observations to produce a cloud climatology. Using algorithms developed by our research group, data from the radar are combined with data from the Belfort ceilometer and

  6. Posters Climate Zones for Maritime Clouds A. B. White and D. Ruffieux

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

    1 Posters Climate Zones for Maritime Clouds A. B. White and D. Ruffieux Cooperative Institute for Research in Environmental Sciences University of Colorado at Boulder/National Oceanic and Atmospheric Administration Boulder, Colorado C. W. Fairall National Oceanic and Atmospheric Administration Environmental Research Laboratories Environmental Technology Laboratory Boulder, Colorado Introduction In this paper we use a commercially available lidar ceilometer to investigate how the basic structure

  7. ARM - PI Product - Radiosondes Corrected for Inaccuracy in RH Measurements

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

    ProductsRadiosondes Corrected for Inaccuracy in RH Measurements 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 : Radiosondes Corrected for Inaccuracy in RH Measurements Corrections for inaccuracy in Vaisala radiosonde RH measurements have been applied to ARM SGP radiosonde soundings. The magnitude of the corrections can vary considerably between soundings. The radiosonde measurement accuracy, and

  8. 1

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

    Improved Water Vapor Measurements from ARM Radiosondes L. Miloshevich and A. J. Heymsfield National Center for Atmospheric Research Boulder, Colorado A. Paukkunen Vaisala Oy Helsinki, Finland Introduction Accurate radiosonde measurements of water vapor in the mid and upper troposphere are important for such applications as evaluating remote-sensor water vapor retrievals, initializing numerical models, and improving parameterizations of radiative and cloud processes. Measurements of relative

  9. Thunderhead Radiation Measurements and Radiative Flux Analysis in Support of STORMVEX

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

    Thunderhead Radiation Measurements and Radiative Flux Analysis in Support of STORMVEX Chuck Long Jay Mace Intent * Provide downwelling broadband radiation measurements at Thunderhead * Physically small footprint portable system * Designed to provide inputs necessary for Radiative Flux Analysis Basic RFA System COPS Hornisgrinde Deployment 1200m elevation System Components * Eppley ventilated PSP * Eppley ventilated PIR * Delta-T SPN-1 * Vaisala HMP-50 T/RH probe * Campbell CR23X datalogger SPN-1

  10. Research Highlight

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

    Field Testing the Next-Generation of Radiosondes PI Contact: Jensen, M., Brookhaven National Laboratory Holdridge, D., Argonne National Laboratory Area of Research: Atmospheric Thermodynamics and Vertical Structures Working Group(s): Cloud Life Cycle Journal Reference: Jensen MP, DJ Holdridge, P Survo, R Lehtinen, S Baxter, T Toto, and KL Johnson. 2016. "Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern Great Plains site." Atmospheric Measurement Techniques, 9,

  11. ARM - VAP Process - wacrarscl

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

    Productswacrarscl Documentation & Plots 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 : W-band Cloud Radar Active Remote Sensing of Cloud (WACRARSCL) Instrument Categories Cloud Properties Observations from the 95 GHz W-band ARM Cloud Radar (WACR), Micropulse Lidar, and ceilometer have been combined using the new WACR Active Remote Sensing of Clouds (WACR-ARSCL)

  12. 1

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

    a Science ACROSS 3 Meteorology is the name for the scientific study of ____. 5 The ____ point of water is 100°C and 212°F. 7 A ceilometer is a tool used to measure cloud ____. 8 Scientists gather information, also called ___, to study and make predictions or get ideas. 10 ____ are formed when water vapor condenses in the air. 11 The ____ point of water is 0°C and 32°F. 13 Humidity is the amount of moisture present in the air in the form of invisible ____ vapor. 14 Temperature is typically

  13. July08.pdf

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

    8 ANL/EVS/NL-08-07 Technical Contact: Brad W. Orr Phone: 630-252-8665 Email: brad.orr@anl.gov Editor: Donna J. Holdridge Contributor: Lynne Roeder Website: http://www.arm.gov ACRF Southern Great Plains Newsletter is published by Argonne National Laboratory, managed by UChicago Argonne, LLC, for the U.S. Department of Energy under contract number DE-AC02-06CH11357. New Ceilometer Evaluated at Southern Great Plains Site To analyze cloud properties, ARM scientists use data from an instrument called

  14. ARM - Field Campaign - Supplemental Sondes

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

    govCampaignsSupplemental Sondes 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 : Supplemental Sondes 1999.05.01 - 1999.10.31 Lead Scientist : Barry Lesht Data Availability Data Quality Report Vaisala has confirmed ARM findings of an apparent dry bias in the relative humidity measured by RS-80H radiosondes. The cause of the dry bias is thought to be contamination of the humidity sensor by volatile organic

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

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N

    2012-10-29

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

  16. SOAR Data: Data from Shipboard Oceanographic and Atmospheric Radiation (SOAR)1999 through 2001

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

    Click on the DATA menu button and then click on a specific ship to find instructions on accessing data from that particular cruise. Instructions will lead you to an FTP site from which data can be downloaded. SOAR data for 1999 through 2001 is reported. SOAR is a global network of research and volunteer ships that carry global change instrumentation. The primary emphasis for SOAR is solar and IR radiation but some ships cary ceilometers, meteorological instruments, and related equipment. All data are collected in a central data collection computer and the flexible data collection software can be adapted to any other user instrumentation. Currently SOAR is installed pas permanent instrumentation on four ships operating in the western Pacific, eastern tropical Pacific, West Indies, and an oceanographic ship that operates around the world. In addition, six other system are used on cruises of opportunity. [Taken from SOAR homepage at http://www.gim.bnl.gov/soar/index.html

  17. A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer

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

    Ahn, M. H.; Han, D.; Won, H. Y.; Morris, Victor R.

    2015-02-03

    For better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two-step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear-sky Tb obtained by an empirical formula as a function of surface air temperaturemore » and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of clear-sky conditions. It is designated as cloud-free data only when both the spectral and temporal tests confirm cloud-free data. Overall, most of the thick and uniform clouds are successfully detected by the spectral test, while the broken and fast-varying clouds are detected by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for six months, from January to June 2013. The overall proportion of correctness is about 88.3% and the probability of detection is 90.8%, which are comparable with or better than those of previous similar approaches. Two thirds of discrepancies occur when the new algorithm detects clouds while the ceilometer does not, resulting in different values of the probability of detection with different cloud-base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.« less

  18. A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer

    SciTech Connect (OSTI)

    Ahn, M. H.; Han, D.; Won, H. Y.; Morris, Victor R.

    2015-02-03

    For better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two-step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear-sky Tb obtained by an empirical formula as a function of surface air temperature and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of clear-sky conditions. It is designated as cloud-free data only when both the spectral and temporal tests confirm cloud-free data. Overall, most of the thick and uniform clouds are successfully detected by the spectral test, while the broken and fast-varying clouds are detected by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for six months, from January to June 2013. The overall proportion of correctness is about 88.3% and the probability of detection is 90.8%, which are comparable with or better than those of previous similar approaches. Two thirds of discrepancies occur when the new algorithm detects clouds while the ceilometer does not, resulting in different values of the probability of detection with different cloud-base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.

  19. Sonde Adjust Value-Added Product Technical Report

    SciTech Connect (OSTI)

    Troyan, D

    2012-01-09

    The Sonde Adjust (SONDEADJUST) value-added product (VAP) creates a file that includes all fields from original Atmospheric Radiation Measurement Climate Research Facility (ARM Facility) radiosonde files and contains several value-added fields that provide adjustments related to well-known humidity issues. SONDEADJUST produces data that correct documented biases in radiosonde humidity measurements. Previous efforts towards applying some of these corrections are available via the discontinued PI product sgpsondecorr1miloC1. Unique fields contained within this datastream include smoothed original relative humidity, dry bias corrected relative humidity, and final corrected relative humidity. The smoothed RH field refines the relative humidity from integers-the resolution of the instrument-to fractions of a percent. This profile is then used to calculate the dry bias corrected field. The final correction fixes the time-lag problem and uses the dry-bias field as input into the algorithm. In addition to dry bias, solar heating is another correction that is encompassed in the final corrected RH field. Output from SONDEADJUST differs from the previous RH-corrected datastreams in important ways. First, all three types of ARM radiosondes-Vaisala RS-80, RS-90, and RS-92-are corrected using dedicated procedures and/or parameters. Second, the output variables include all of those found in the original radiosonde file: dry bulb temperature, dewpoint temperature, wind speed, wind direction, eastward wind component, northward wind component, wind status (a Vaisala-produced field used in conjunction with the Loran system), ascent rate, and original relative humidity. Additional humidity fields are smoothed relative humidity, dry biased corrected relative humidity, final ambient relative humidity, and scaled adjusted relative humidity. Third, quality control (QC) flags of the fields from the original radiosonde datastream are brought into the SONDEADJUST output file. Additional QC

  20. Atmospheric sensing for the H.E.S.S. array

    SciTech Connect (OSTI)

    Aye, K.-M.; Brown, A.M.; Chadwick, P.M.; Hadjichristidis, C.; Latham, I.J.; Le Gallou, R.; McComb, T.J.L.; Nolan, S.J.; Noutsos, A.; Orford, K.J.; Osborne, J.L.; Rayner, S.M.

    2005-02-21

    Several atmospheric monitoring instruments have been installed at the H.E.S.S. gamma-ray observatory in Namibia. Firstly, Heitronics KT19 infrared radiometers, aligned paraxially with the H.E.S.S. telescopes, measure the infrared radiation of the water molecules. These allow us to detect clouds crossing the telescopes' field of view and to estimate the humidity present in the atmosphere. For a general estimate of the atmosphere's transmittance, i.e. the detection of any light-attenuating aerosols, a ceilometer, which is a LIDAR with built-in atmospheric data reduction code, is being used. It will be complemented soon by an instrument which will measure the transmissivity of the atmosphere at different wavelengths up to 500m above the ground. The overall status of the weather is monitored by a fully automated weatherstation. This paper describes the setup, the data analysis and how this will be used in order to improve the knowledge of the telescopes' effective collection area.

  1. Spatial Variability of Surface Irradiance Measurements at the Manus ARM Site

    SciTech Connect (OSTI)

    Riihimaki, Laura D.; Long, Charles N.

    2014-05-16

    The location of the Atmospheric Radiation Measurement (ARM) site on Manus island in Papua New Guinea was chosen because it is very close the coast, in a geographically at, near-sea level area of the island, minimizing the impact of local island effects on the meteorology of the measurements [Ackerman et al., 1999]. In this study, we confirm that the Manus site is in deed less impacted by the island meteorology than slightly inland by comparing over a year of broadband surface irradiance and ceilometer measurements and derived quantities at the standard Manus site and a second location 7 km away as part of the AMIE-Manus campaign. The two sites show statistically similar distributions of irradiance and other derived quantities for all wind directions except easterly winds, when the inland site is down wind from the standard Manus site. Under easterly wind conditions, which occur 17% of the time, there is a higher occurrence of cloudiness at the down wind site likely do to land heating and orographic effects. This increased cloudiness is caused by shallow, broken clouds often with bases around 700 m in altitude. While the central Manus site consistently measures a frequency of occurrence of low clouds (cloud base height less than 1200 m) about 25+4% regardless of wind direction, the AMIE site has higher frequencies of low clouds (38%) when winds are from the east. This increase in low, locally produced clouds causes an additional -20 W/m2 shortwave surface cloud radiative effect at the AMIE site in easterly conditions than in other meteorological conditions that exhibit better agreement between the two sites.

  2. Microwave signatures of ice hydrometeors from ground-based observations above Summit, Greenland

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

    Pettersen, Claire; Bennartz, Ralf; Kulie, Mark S.; Merrelli, Aronne J.; Shupe, Matthew D.; Turner, David D.

    2016-04-15

    Multi-instrument, ground-based measurements provide unique and comprehensive data sets of the atmosphere for a specific location over long periods of time and resulting data compliment past and existing global satellite observations. This paper explores the effect of ice hydrometeors on ground-based, high-frequency passive microwave measurements and attempts to isolate an ice signature for summer seasons at Summit, Greenland, from 2010 to 2013. Data from a combination of passive microwave, cloud radar, radiosonde, and ceilometer were examined to isolate the ice signature at microwave wavelengths. By limiting the study to a cloud liquid water path of 40 gm–2 or less, themore » cloud radar can identify cases where the precipitation was dominated by ice. These cases were examined using liquid water and gas microwave absorption models, and brightness temperatures were calculated for the high-frequency microwave channels: 90, 150, and 225 GHz. By comparing the measured brightness temperatures from the microwave radiometers and the calculated brightness temperature using only gas and liquid contributions, any residual brightness temperature difference is due to emission and scattering of microwave radiation from the ice hydrometeors in the column. The ice signature in the 90, 150, and 225 GHz channels for the Summit Station summer months was isolated. As a result, this measured ice signature was then compared to an equivalent brightness temperature difference calculated with a radiative transfer model including microwave single-scattering properties for several ice habits. Initial model results compare well against the 4 years of summer season isolated ice signature in the high-frequency microwave channels.« less

  3. AMIE (ARM MJO Investigation Experiment): Observations of the Madden-Julian Oscillation for Modeling Studies Science Plan

    SciTech Connect (OSTI)

    Long, C; Del Genio, A; Gustafson, W; Houze, R; Jakob, C; Jensen, M; Klein, S; Leung, L Ruby; Liu, X; Luke, E; May, P; McFarlane, S; Minnis, P; Schumacher, C; Vogelmann, A; Wang, Y; Wu, X; Xie, S

    2010-03-22

    season (typically March), affording the documentation of conditions before, during, and after the peak MJO season. The increased frequency of sonde launches throughout the experimental period will provide better diurnal understanding of the thermodynamic profiles, and thus a better representation within the variational analysis data set. Finally, a small surface radiation and ceilometer system will be deployed at the PNG Lombrum Naval Base about 6 km away from the ARM Manus site in order to provide some documentation of scale variability with respect to the representativeness of the ARM measurements.