Cross Validation of Spaceborne Radar and Ground Polarimetric Radar Aided by Polarimetric Echo Classification of Hydrometeor Types

Yixin Wen Department of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

Search for other papers by Yixin Wen in
Current site
Google Scholar
PubMed
Close
,
Yang Hong Department of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

Search for other papers by Yang Hong in
Current site
Google Scholar
PubMed
Close
,
Guifu Zhang Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma
School of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Guifu Zhang in
Current site
Google Scholar
PubMed
Close
,
Terry J. Schuur NOAA/National Severe Storms Laboratory, Norman, Oklahoma
Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

Search for other papers by Terry J. Schuur in
Current site
Google Scholar
PubMed
Close
,
Jonathan J. Gourley NOAA/National Severe Storms Laboratory, Norman, Oklahoma

Search for other papers by Jonathan J. Gourley in
Current site
Google Scholar
PubMed
Close
,
Zac Flamig NOAA/National Severe Storms Laboratory, Norman, Oklahoma
Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

Search for other papers by Zac Flamig in
Current site
Google Scholar
PubMed
Close
,
K. Robert Morris Science Applications International Corporation, and NASA Goddard Space Flight Center, Greenbelt, Maryland

Search for other papers by K. Robert Morris in
Current site
Google Scholar
PubMed
Close
, and
Qing Cao Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

Search for other papers by Qing Cao in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Ground-based polarimetric weather radar is arguably the most powerful validation tool that provides physical insight into the development and interpretation of spaceborne weather radar algorithms and observations. This study aims to compare and resolve discrepancies in hydrometeor retrievals and reflectivity observations between the NOAA/National Severe Storm Laboratory “proof of concept” KOUN polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) and the spaceborne precipitation radar (PR) on board NASA’s Tropical Rainfall Measuring Mission (TRMM) platform. An intercomparison of PR and KOUN melting-layer heights retrieved from 2 to 5 km MSL shows a high correlation coefficient of 0.88 with relative bias of 5.9%. A resolution volume–matching technique is used to compare simultaneous TRMM PR and KOUN reflectivity observations. The comparisons reveal an overall bias of <0.2% between PR and KOUN. The bias is hypothesized to be from non-Rayleigh scattering effects and/or errors in attenuation correction procedures applied to Ku-band PR measurements. By comparing reflectivity with respect to different hydrometeor types (as determined by KOUN’s hydrometeor classification algorithm), it is found that the bias is from echoes that are classified as rain–hail mixture, wet snow, graupel, and heavy rain. These results agree with expectations from backscattering calculations at Ku and S bands, but with the notable exception of dry snow. Comparison of vertical reflectivity profiles shows that PR suffers significant attenuation at lower altitudes, especially in convective rain and in the melting layer. The attenuation correction performs very well for both stratiform and convective rain, however. In light of the imminent upgrade of the U.S. national weather radar network to include polarimetric capabilities, the findings in this study will potentially serve as the basis for nationwide validation of space-based precipitation products and also invite synergistic development of coordinated space–ground multisensor precipitation products.

Corresponding author address: Dr. Yang Hong, Dept. of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73019. E-mail: yanghong@ou.edu

Abstract

Ground-based polarimetric weather radar is arguably the most powerful validation tool that provides physical insight into the development and interpretation of spaceborne weather radar algorithms and observations. This study aims to compare and resolve discrepancies in hydrometeor retrievals and reflectivity observations between the NOAA/National Severe Storm Laboratory “proof of concept” KOUN polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) and the spaceborne precipitation radar (PR) on board NASA’s Tropical Rainfall Measuring Mission (TRMM) platform. An intercomparison of PR and KOUN melting-layer heights retrieved from 2 to 5 km MSL shows a high correlation coefficient of 0.88 with relative bias of 5.9%. A resolution volume–matching technique is used to compare simultaneous TRMM PR and KOUN reflectivity observations. The comparisons reveal an overall bias of <0.2% between PR and KOUN. The bias is hypothesized to be from non-Rayleigh scattering effects and/or errors in attenuation correction procedures applied to Ku-band PR measurements. By comparing reflectivity with respect to different hydrometeor types (as determined by KOUN’s hydrometeor classification algorithm), it is found that the bias is from echoes that are classified as rain–hail mixture, wet snow, graupel, and heavy rain. These results agree with expectations from backscattering calculations at Ku and S bands, but with the notable exception of dry snow. Comparison of vertical reflectivity profiles shows that PR suffers significant attenuation at lower altitudes, especially in convective rain and in the melting layer. The attenuation correction performs very well for both stratiform and convective rain, however. In light of the imminent upgrade of the U.S. national weather radar network to include polarimetric capabilities, the findings in this study will potentially serve as the basis for nationwide validation of space-based precipitation products and also invite synergistic development of coordinated space–ground multisensor precipitation products.

Corresponding author address: Dr. Yang Hong, Dept. of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73019. E-mail: yanghong@ou.edu
Save
  • Amitai, E., X. Llort, and D. Sempere-Torres, 2009: Comparison of TRMM radar rainfall estimates with NOAA next-generation QPE. J. Meteor. Soc. Japan, 87A, 109118.

    • Search Google Scholar
    • Export Citation
  • Anagnostou, E., C. Morales, and T. Dinku, 2001: The use of TRMM precipitation radar observations in determining ground radar calibration biases. J. Atmos. Oceanic Technol., 18, 616628.

    • Search Google Scholar
    • Export Citation
  • Barnes, S. L., 1973: Mesoscale objective map analysis using weighted time series observations. NOAA Tech. Memo. ERL NSSL-62, 60 pp.

  • Bolen, S., and V. Chandrasekar, 2000: Quantitative cross validation of space-based and ground-based radar observations. J. Appl. Meteor., 39, 20712079.

    • Search Google Scholar
    • Export Citation
  • Bolen, S., and V. Chandrasekar, 2003: Methodology for aligning and comparing spaceborne radar and ground-based radar observations. J. Atmos. Oceanic Technol., 20, 647659.

    • Search Google Scholar
    • Export Citation
  • Cao, Q., G. Zhang, E. Brandes, T. J. Schuur, A. V. Ryzhkov, and K. Ikeda, 2008: Analysis of video disdrometer and polarimetric radar data to characterize rain microphysics in Oklahoma. J. Appl. Meteor. Climatol., 47, 22382255.

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., A. Hou, E. Smith, V. N. Bringi, S. A. Rutledge, E. Gorgucci, W. A. Petersen, and G. S. Jackson, 2008: Potential role of dual-polarization radar in the validation of satellite precipitation measurements: Rationale and opportunities. Bull. Amer. Meteor. Soc., 89, 11271145.

    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., and D. S. Zrnic, 1993: Doppler Radar and Weather Observations. 2nd ed. Dover, 562 pp.

  • Giangrande, S. E., and A. V. Ryzhkov, 2005: Calibration of dual-polarization radar in the presence of partial beam blockage. J. Atmos. Oceanic Technol., 22, 11561166.

    • Search Google Scholar
    • Export Citation
  • Giangrande, S. E., and A. V. Ryzhkov, 2008: Estimation of rainfall based on the results of polarimetric echo classification. J. Appl. Meteor. Climatol., 47, 24452462.

    • Search Google Scholar
    • Export Citation
  • Giangrande, S. E., J. M. Krause, and A. V. Ryzhkov, 2008: Automatic designation of the melting layer with a polarimetric prototype of the WSR-88D radar. J. Appl. Meteor. Climatol., 47, 13541364.

    • Search Google Scholar
    • Export Citation
  • Gunn, K. L. S., and J. S. Marshall, 1958: The distribution with size of aggregate snowflakes. J. Meteor., 15, 452461.

  • Harris, G. N., Jr., K. P. Bowman, and D. B. Shin, 2000: Comparison of freezing-level altitudes from the NCEP reanalysis with TRMM precipitation radar brightband data. J. Climate, 13, 41374148.

    • Search Google Scholar
    • Export Citation
  • Iguchi, T., R. Meneghini, J. Awaka, T. Kozu, and K. Okamoto, 2000: Rain profiling algorithm for TRMM precipitation radar. J. Appl. Meteor., 39, 20382052.

    • Search Google Scholar
    • Export Citation
  • Kozu, T., and Coauthors, 2001: Development of precipitation radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite. IEEE Trans. Geosci. Remote Sens., 39, 102116.

    • Search Google Scholar
    • Export Citation
  • Liao, L., and R. Meneghini, 2009: Validation of TRMM precipitation radar through comparison of its multiyear measurements with ground-based radar. J. Appl. Meteor. Climatol., 48, 804817.

    • Search Google Scholar
    • Export Citation
  • Morris, K. R., and M. R. Schwaller, 2009: An enhanced global precipitation measurement (GPM) validation network prototype. Preprints, 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., P7.3. [Available online at http://ams.confex.com/ams/pdfpapers/155254.pdf.]

    • Search Google Scholar
    • Export Citation
  • NASDA, 1999: TRMM PR algorithm instruction manual V1.0. Communications Research Laboratory, 52 pp. [Available from Communications Research Laboratory, 4-2-1 Nukui-kitamachi, Koganei-chi, Tokyo 184, Japan.]

    • Search Google Scholar
    • Export Citation
  • Park, H., A. V. Ryzhkov, D. S. Zrnic, and K. E. Kim, 2009: The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS. Wea. Forecasting, 24, 730748.

    • Search Google Scholar
    • Export Citation
  • Petersen, W. A., and M. R. Schwaller, 2008: Global Precipitation Mission (GPM) ground validation science implementation plan (draft). NASA Doc., 37 pp. [Available online at http://gpm.gsfc.nasa.gov/documents/GPM_GVS_imp_plan_Jul08.pdf.]

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., S. E. Giangrande, V. M. Melnikov, and T. J. Schuur, 2005: Calibration issues of dual-polarization radar measurements. J. Atmos. Oceanic Technol., 22, 11381155.

    • Search Google Scholar
    • Export Citation
  • Schumacher, C., and R. A. Houze, 2000: Comparison of radar data from the TRMM satellite and Kwajalein oceanic validation site. J. Appl. Meteor., 39, 21512164.

    • Search Google Scholar
    • Export Citation
  • Shin, D.-B., G. R. North, and K. P. Bowman, 2000: A summary of reflectivity profiles from the first year of TRMM radar data. J. Climate, 13, 40724086.

    • Search Google Scholar
    • Export Citation
  • Simpson, J., C. Kummerow, W.-K. Tao, and R. F. Adler, 1996: On the Tropical Rainfall Measuring Mission (TRMM). Meteor. Atmos. Phys., 60, 1936.

    • Search Google Scholar
    • Export Citation
  • Vivekanandan, J., W. M. Adams, and V. N. Bringi, 1991: Rigorous approach to polarimetric radar modeling of hydrometeor orientation distributions. J. Appl. Meteor., 30, 10531063.

    • Search Google Scholar
    • Export Citation
  • Wang, J., and D. Wolff, 2009: Comparisons of reflectivities from the TRMM precipitation radar and ground-based radars. J. Atmos. Oceanic Technol., 26, 857875.

    • Search Google Scholar
    • Export Citation
  • Waterman, P. C., 1971: Symmetry, unitarity, and geometry in electromagnetic scattering. Phys. Rev. D, 3, 825839.

  • Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. Academic Press, 467 pp.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 645 231 23
PDF Downloads 316 138 22