Probabilistic Quantitative Precipitation Estimates with Ground-based Radar Networks

The uncertainty structure of radar quantitative precipitation estimation (QPE) is largely unknown at fine spatiotemporal scales near the radar measurement scale (1-km/5-min). By using the WSR-88D radar network and rain gauge datasets across the conterminous US, an investigation of this subject has been carried out within the framework of the NOAA/NSSL ground radar-based Multi-Radar/Multi- Sensor System (MRMS). Probability distributions of precipitation rates are computed using a model quantifying the relation between radar reflectivity and the corresponding “true” precipitation. It considers the influence of physical factors as well as the impacts of correction algorithms on the radar signal in radar QPE. This approach preserves the fine space/time sampling properties of the radar and conditions probabilistic quantitative precipitation estimates (PQPE) on the rain rate and precipitation type. This PQPE model provides the basis for precipitation probability maps and the generation of radar precipitation ensembles. Maps of the precipitation exceedance probability for specific thresholds (e.g. precipitation extremes) are demonstrated for risk analysis. Precipitation probability maps are accumulated to the hourly time scale and compare positively to the MRMS deterministic QPE. This approach to PQPE can readily apply to other systems including space-based passive and active sensor algorithms.