Comparison of Single- and Dual-Polarization–Based Rainfall Estimates Using NEXRAD Data for the NASA Iowa Flood Studies Project

Bong-Chul Seo IIHR–Hydroscience and Engineering, The University of Iowa, Iowa City, Iowa

Search for other papers by Bong-Chul Seo in
Current site
Google Scholar
PubMed
Close
,
Brenda Dolan Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Search for other papers by Brenda Dolan in
Current site
Google Scholar
PubMed
Close
,
Witold F. Krajewski IIHR–Hydroscience and Engineering, The University of Iowa, Iowa City, Iowa

Search for other papers by Witold F. Krajewski in
Current site
Google Scholar
PubMed
Close
,
Steven A. Rutledge Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Search for other papers by Steven A. Rutledge in
Current site
Google Scholar
PubMed
Close
, and
Walter Petersen Wallops Flight Facility, NASA GSFC, Wallops, Virginia

Search for other papers by Walter Petersen in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

This study compares and evaluates single-polarization (SP)- and dual-polarization (DP)-based radar-rainfall (RR) estimates using NEXRAD data acquired during Iowa Flood Studies (IFloodS), a NASA GPM ground validation field campaign carried out in May–June 2013. The objective of this study is to understand the potential benefit of the DP quantitative precipitation estimation, which selects different rain-rate estimators according to radar-identified precipitation types, and to evaluate RR estimates generated by the recent research SP and DP algorithms. The Iowa Flood Center SP (IFC-SP) and Colorado State University DP (CSU-DP) products are analyzed and assessed using two high-density, high-quality rain gauge networks as ground reference. The CSU-DP algorithm shows superior performance to the IFC-SP algorithm, especially for heavy convective rains. We verify that dynamic changes in the proportion of heavy rain during the convective period are associated with the improved performance of CSU-DP rainfall estimates. For a lighter rain case, the IFC-SP and CSU-DP products are not significantly different in statistical metrics and visual agreement with the rain gauge data. This is because both algorithms use the identical NEXRAD reflectivity–rain rate (ZR) relation that might lead to substantial underestimation for the presented case.

Corresponding author address: Bong-Chul Seo, IIHR–Hydroscience and Engineering, The University of Iowa, 100 C. Maxwell Stanley Hydraulics Laboratory, Iowa City, IA 52242. E-mail: bongchul-seo@uiowa.edu

This article is included in the IFloodS 2013: A Field Campaign to Support the NASA-JAXA Global Precipitation Measurement Mission Special Collection.

Abstract

This study compares and evaluates single-polarization (SP)- and dual-polarization (DP)-based radar-rainfall (RR) estimates using NEXRAD data acquired during Iowa Flood Studies (IFloodS), a NASA GPM ground validation field campaign carried out in May–June 2013. The objective of this study is to understand the potential benefit of the DP quantitative precipitation estimation, which selects different rain-rate estimators according to radar-identified precipitation types, and to evaluate RR estimates generated by the recent research SP and DP algorithms. The Iowa Flood Center SP (IFC-SP) and Colorado State University DP (CSU-DP) products are analyzed and assessed using two high-density, high-quality rain gauge networks as ground reference. The CSU-DP algorithm shows superior performance to the IFC-SP algorithm, especially for heavy convective rains. We verify that dynamic changes in the proportion of heavy rain during the convective period are associated with the improved performance of CSU-DP rainfall estimates. For a lighter rain case, the IFC-SP and CSU-DP products are not significantly different in statistical metrics and visual agreement with the rain gauge data. This is because both algorithms use the identical NEXRAD reflectivity–rain rate (ZR) relation that might lead to substantial underestimation for the presented case.

Corresponding author address: Bong-Chul Seo, IIHR–Hydroscience and Engineering, The University of Iowa, 100 C. Maxwell Stanley Hydraulics Laboratory, Iowa City, IA 52242. E-mail: bongchul-seo@uiowa.edu

This article is included in the IFloodS 2013: A Field Campaign to Support the NASA-JAXA Global Precipitation Measurement Mission Special Collection.

Save
  • Bellon, A., Lee G. W. , Kilambi A. , and Zawadzki I. , 2007: Real-time comparisons of VPR-corrected daily rainfall estimates with a gauge Mesonet. J. Appl. Meteor. Climatol., 46, 726741, doi:10.1175/JAM2502.1.

    • Search Google Scholar
    • Export Citation
  • Brandes, E. A., Zhang G. , and Vivekanandan J. , 2002: Experiments in rainfall estimation with a polarimetric radar in a subtropical environment. J. Appl. Meteor., 41, 674685, doi:10.1175/1520-0450(2002)041<0674:EIREWA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., Bringi V. N. , Rutledge S. A. , Hou A. , Smith E. , Jackson G. S. , Gorgucci E. , and Petersen W. A. , 2008: Potential role of dual-polarization radar in the validation of satellite precipitation measurements: Rationale and opportunities. Bull. Amer. Meteor. Soc., 89, 11271145, doi:10.1175/2008BAMS2177.1.

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., Keranen R. , Lim S. , and Moisseev D. , 2013: Recent advances in classification of observations from dual polarization weather radars. Atmos. Res., 119, 97111, doi:10.1016/j.atmosres.2011.08.014.

    • Search Google Scholar
    • Export Citation
  • Ciach, G. J., 2003: Local random errors in tipping-bucket rain gauge measurements. J. Atmos. Oceanic Technol., 20, 752759, doi:10.1175/1520-0426(2003)20<752:LREITB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ciach, G. J., and Krajewski W. F. , 2006: Analysis and modeling of spatial correlation structure in small-scale rainfall in central Oklahoma. Adv. Water Resour., 29, 14501463, doi:10.1016/j.advwatres.2005.11.003.

    • Search Google Scholar
    • Export Citation
  • Cifelli, R., Chandrasekar V. , Lim S. , Kennedy P. C. , Wang Y. , and Rutledge S. A. , 2011: A new dual-polarization radar rainfall algorithm: Application in Colorado precipitation events. J. Atmos. Oceanic Technol., 28, 352364, doi:10.1175/2010JTECHA1488.1.

    • Search Google Scholar
    • Export Citation
  • Cunha, L. K., Smith J. A. , Baeck M. L. , and Krajewski W. F. , 2013: An early performance evaluation of the NEXRAD dual-polarization radar rainfall estimates for urban flood applications. Wea. Forecasting, 28, 14781497, doi:10.1175/WAF-D-13-00046.1.

    • Search Google Scholar
    • Export Citation
  • Cunha, L. K., Smith J. A. , Krajewski W. F. , Baeck M. L. , and Seo B.-C. , 2015: NEXRAD NWS polarimetric precipitation product evaluation for IFloodS. J. Hydrometeor., doi:10.1175/JHM-D-14-0148.1, in press.

  • Fulker, D., Bates S. , and Jacobs C. , 1997: Unidata: A virtual community sharing resources via technological infrastructure. Bull. Amer. Meteor. Soc., 78, 457468, doi:10.1175/1520-0477(1997)078<0457:UAVCSR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fulton, R. A., Breidenbach J. P. , Seo D.-J. , Miller D. A. , and O’Bannon T. , 1998: The WSR-88D rainfall algorithm. Wea. Forecasting, 13, 377395, doi:10.1175/1520-0434(1998)013<0377:TWRA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Giangrande, S. E., and Ryzhkov A. V. , 2008: Estimation of rainfall based on the results of polarimetric echo classification. J. Appl. Meteor., 47, 24452460, doi:10.1175/2008JAMC1753.1.

    • Search Google Scholar
    • Export Citation
  • Hou, A. Y., and Coauthors, 2014: Global Precipitation Measurement (GPM) Mission. Bull. Amer. Meteor. Soc., 95, 701722, doi:10.1175/BAMS-D-13-00164.1.

    • Search Google Scholar
    • Export Citation
  • Istok, M., and Coauthors, 2009: WSR-88D dual-polarization initial operational capabilities. 25th Conf. on Int. Interactive Information and Processing Systems (IIPS) in Meteorology, Oceanography, and Hydrology, Phoenix, AZ, Amer. Meteor. Soc., 15.5. [Available online at http://ams.confex.com/ams/pdfpapers/148927.pdf.]

  • Kelleher, K. E., and Coauthors, 2007: A real-time delivery system for NEXRAD Level II data via the internet. Bull. Amer. Meteor. Soc., 88, 10451057, doi:10.1175/BAMS-88-7-1045.

    • Search Google Scholar
    • Export Citation
  • Klazura, G. E., and Kelly D. S. , 1995: A comparison of high resolution rainfall accumulation estimates from the WSR-88D precipitation algorithm with rain gage data. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 3134.

  • Krajewski, W. F., Ciach G. J. , and Habib E. , 2003: An analysis of small-scale rainfall variability in different climatic regimes. Hydrol. Sci. J., 48, 151162, doi:10.1623/hysj.48.2.151.44694.

    • Search Google Scholar
    • Export Citation
  • Krajewski, W. F., Vignal B. , Seo B.-C. , and Villarini G. , 2011: Statistical model of the range-dependent error in radar-rainfall estimates due to the vertical profile of reflectivity. J. Hydrol., 402, 306316, doi:10.1016/j.jhydrol.2011.03.024.

    • Search Google Scholar
    • Export Citation
  • Krajewski, W. F., Kruger A. , Singh S. , Seo B.-C. , and Smith J. A. , 2013: Hydro-NEXRAD-2: Real time access to customized radar-rainfall for hydrologic applications. J. Hydroinf., 15, 580590, doi:10.2166/hydro.2012.227.

    • Search Google Scholar
    • Export Citation
  • Lerach, D. G., Rutledge S. A. , Williams C. R. , and Cifelli R. , 2010: Vertical structure of convective systems during NAME 2004. Mon. Wea. Rev., 138, 16951714, doi:10.1175/2009MWR3053.1.

    • Search Google Scholar
    • Export Citation
  • Lim, S., Chandrasekar V. , and Bringi V. N. , 2005: Hydrometeor classification system using dual-polarization radar measurements: Model improvements and in situ verification. IEEE Trans. Geosci. Remote Sens., 43, 792801, doi:10.1109/TGRS.2004.843077.

    • Search Google Scholar
    • Export Citation
  • Marshall, J. S., and Palmer W. McK. , 1948: The distribution of raindrops with size. J. Meteor., 5, 165166, doi:10.1175/1520-0469(1948)005<0165:TDORWS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Park, H., Ryzhkov A. V. , Zrnic D. S. , and Kim K.-E. , 2009: The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS. Wea. Forecasting, 24, 730748, doi:10.1175/2008WAF2222205.1.

    • Search Google Scholar
    • Export Citation
  • Petersen, W. A., and Krajewski W. , 2013: Status update on the GPM Ground Validation Iowa Flood Studies (IFloodS) field experiment. Geophysical Research Abstracts, Vol. 15, Abstract EGU2013-13345. [Available online at http://meetingorganizer.copernicus.org/EGU2013/EGU2013-13345.pdf.]

  • Ryzhkov, A. V., Giangrande S. E. , and Schuur T. J. , 2005a: Rainfall estimation with a polarimetric prototype of WSR-88D. J. Appl. Meteor., 44, 502515, doi:10.1175/JAM2213.1.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., Schuur T. J. , Burgess D. W. , Heinselman P. L. , Giangrande S. E. , and Zrnic D. S. , 2005b: The joint polarization experiment: Polarimetric rainfall measurements and hydrometeor classification. Bull. Amer. Meteor. Soc., 86, 809824, doi:10.1175/BAMS-86-6-809.

    • Search Google Scholar
    • Export Citation
  • Sachidananda, M., and Zrnic D. S. , 1987: Rain rate estimates from differential polarization measurements. J. Atmos. Oceanic Technol., 4, 588598, doi:10.1175/1520-0426(1987)004<0588:RREFDP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schumacher, C., and Houze R. A. Jr., 2000: Comparison of radar data from the TRMM satellite and Kwajalein oceanic validation site. J. Appl. Meteor., 39, 21512164, doi:10.1175/1520-0450(2001)040<2151:CORDFT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Seliga, T. A., and Bringi V. N. , 1976: Potential use of radar differential reflectivity measurements at orthogonal polarizations for measuring precipitation. J. Appl. Meteor., 15, 6976, doi:10.1175/1520-0450(1976)015<0069:PUORDR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Seo, B.-C., Krajewski W. F. , Kruger A. , Domaszczynski P. , Smith J. A. , and Steiner M. , 2011: Radar-rainfall estimation algorithms of Hydro-NEXRAD. J. Hydroinf., 13, 277291, doi:10.2166/hydro.2010.003.

    • Search Google Scholar
    • Export Citation
  • Seo, B.-C., Cunha L. K. , and Krajewski W. F. , 2013: Uncertainty in radar-rainfall composite and its impact on hydrologic prediction for the eastern Iowa flood of 2008. Water Resour. Res., 49, 27472764, doi:10.1002/wrcr.20244.

    • Search Google Scholar
    • Export Citation
  • Seo, B.-C., Krajewski W. F. , Cunha L. K. , Dolan B. , Smith J. A. , Rutledge S. , and Petersen W. , 2014: Comprehensive evaluation of the IFloodS precipitation datasets for hydrologic applications. Extended Abstracts, Ninth Int. Symp. on Weather Radar and Hydrology, Washington, D.C., Environmental and Water Resources Institute, 1-49.

  • Sherretz, L. A., and Fulker D. W. , 1988: Unidata: Enabling universities to acquire and analyze scientific data. Bull. Amer. Meteor. Soc., 69, 373376, doi:10.1175/1520-0477(1988)069<0373:UEUTAA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Skofronick-Jackson, G., Petersen W. A. , Hou A. Y. , Stocher E. F. , Kaye J. , and Kakar R. , 2013: Global Precipitation Measurement (GPM) science implementation plan. NASA GSFC Doc., 162 pp. [Available online at http://pmm.nasa.gov/resources/documents/home.]

  • Steiner, M., and Smith J. A. , 2002: Use of three-dimensional reflectivity structure for automated detection and removal of nonprecipitating echoes in radar data. J. Atmos. Oceanic Technol., 19, 673686, doi:10.1175/1520-0426(2002)019<0673:UOTDRS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Steiner, M., Smith J. A. , Burges S. J. , Alonso C. V. , and Darden R. W. , 1999: Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation. Water Resour. Res., 35, 24872503, doi:10.1029/1999WR900142.

    • Search Google Scholar
    • Export Citation
  • Vignal, B., and Krajewski W. F. , 2001: Large-sample evaluation of two methods to correct range-dependent error for WSR-88D rainfall estimates. J. Hydrometeor., 2, 490504, doi:10.1175/1525-7541(2001)002<0490:LSEOTM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Villarini, G., Krajewski W. F. , and Smith J. A. , 2009: New paradigm for statistical validation of satellite precipitation estimates: Application to a large sample of the TMPA 0.25° 3-hourly estimates over Oklahoma. J. Geophys. Res., 114, D12106, doi:10.1029/2008JD011475.

    • Search Google Scholar
    • Export Citation
  • Villarini, G., Seo B.-C. , Serinaldi F. , and Krajewski W. F. , 2014: Spatial and temporal modeling of radar rainfall uncertainties. Atmos. Res., 135-136, 91101, doi:10.1016/j.atmosres.2013.09.007.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., and Chandrasekar V. , 2009: Algorithm for estimation of the specific differential phase. J. Atmos. Oceanic Technol., 26, 25652578, doi:10.1175/2009JTECHA1358.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 872 232 15
PDF Downloads 489 93 3