Creation of Multisensor Precipitation Products from WSI NOWrad Reflectivity Data

Abstract

Radar and multisensor quantitative precipitation estimates (QPEs) have played a critical role in real-time hydrologic and weather predictions. The utility of this data set for hydrologic model calibration, however, is hampered by the limited data archive and the presence of data gaps. In the research reported in this paper, the use of a composite reflectivity data set is investigated, namely the Weather Services International (WSI) National Operational Weather radar (NOWrad) data set, to create an hourly QPE that would complement the National Weather Service (NWS) Stage III archive by filling in the latter’s gaps and potentially improving the latter’s accuracy. The paper starts from an inventory analysis of Stage III and NOWrad products, and through which it is found that as much as 17% of the Stage III data were missing for some of the regions, and some of these gaps can be filled using the NOWrad data. Then, the paper presents two experimental products, as follows: (1) NOWrad–Raw, based on variable