Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting

Abstract Next-Generation Weather Radar (NEXRAD) multisensor precipitation estimates will be used for a host of applications that include operational streamflow forecasting at the National Weather Service River Forecast Centers (RFCs) and nonoperational purposes such as studies of weather, climate, and hydrology. Given these expanding applications, it is important to understand the quality and error characteristics of NEXRAD multisensor products. In this paper, the issues involved in evaluating these products are examined through an assessment of a 5.5-yr record of multisensor estimates from the Arkansas–Red Basin RFC. The objectives were to examine how known radar biases manifest themselves in the multisensor product and to quantify precipitation estimation errors. Analyses included comparisons of multisensor estimates based on different processing algorithms, comparisons with gauge observations from the Oklahoma Mesonet and the Agricultural Research Service Micronet, and the application of a validation f...

[1]  Emmanouil N. Anagnostou,et al.  Calibration of the WSR-88D Precipitation Processing Subsystem , 1998 .

[2]  Witold F. Krajewski,et al.  Sampling Errors of Tipping-Bucket Rain Gauge Measurements , 2001 .

[3]  David A. Imy,et al.  A Description of the Initial Set of Analysis Products Available from the NEXRAD WSR-88D System , 1993 .

[4]  Witold F. Krajewski,et al.  Estimation of the mean field bias of radar rainfall estimates , 1991 .

[5]  Matthias Steiner,et al.  Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation , 1999 .

[6]  I. Rodríguez‐Iturbe,et al.  Evaluation of mean square error involved in approximating the areal average of a rainfall event by a discrete summation , 1976 .

[7]  Michael D. Hudlow,et al.  Technological developments in real-time operational hydrologic forecasting in the United States , 1988 .

[8]  D. Maidment,et al.  Coordinate Transformations for Using NEXRAD Data in GIS-Based Hydrologic Modeling , 1999 .

[9]  Dong-Jun Seo,et al.  An Intercomparison Study of NEXRAD Precipitation Estimates , 1996 .

[10]  Donald W. Burgess,et al.  Recording, Archiving, and Using WSR-88D Data , 1993 .

[11]  Dong-Jun Seo,et al.  The WSR-88D rainfall algorithm , 1998 .

[12]  Michael D. Eilts,et al.  The Oklahoma Mesonet: A Technical Overview , 1995 .

[13]  Anton Kruger,et al.  An evaluation of NEXRAD precipitation estimates in complex terrain , 1999 .

[14]  Witold F. Krajewski,et al.  Cokriging radar‐rainfall and rain gage data , 1987 .

[15]  Victor Koren,et al.  Comparing Mean Areal Precipitation Estimates from NEXRAD and Rain Gauge Networks , 1999 .

[16]  W. Krajewski,et al.  On the estimation of radar rainfall error variance , 1999 .

[17]  Witold F. Krajewski,et al.  Numerical simulation studies of rain gage data correction due to wind effect , 1999 .

[18]  Dong-Jun Seo,et al.  Real-time estimation of rainfall fields using radar rainfall and rain gage data , 1998 .

[19]  Witold F. Krajewski,et al.  Efficient storage of weather radar data , 1997 .

[20]  Witold F. Krajewski,et al.  Experimental and numerical studies of small-scale rainfall measurements and variability , 1998 .

[21]  Jay P. Breidenbach,et al.  The WSR-88 D Rainfall Algorithm , 1998 .