Optimizing Rainfall Estimates with the Aid of Radar

Abstract

Estimates of precipitation are improved when raingage observations are used to calibrate quantitative radar data as well as to estimate precipitation in areas without radar data. Estimated areal precipitation depth errors for nine rainfalls over a 3000 km2 watershed averaged 13 and 14% (1.5 and 1.8 mm) when the radar was calibrated by networks of raingages having densities of one gage per 900 and 1600 km2. Areal precipitation estimates derived from rainfalls observed at the gages alone produced errors of 21 and 24% (2.5 and 3.0 mm). Adjusting the radar data by a single calibration factor (the simple average ratio of gage-observed and radar-inferred rainfall at all input gages without regard to the spatial variation among ratios) resulted in error reduction to 18% (2.1 mm). Radar data added to gage observations also increased the explained variance in point rainfall estimates above that from gages alone, from 53 to 77% and 46 to 72% for the above gage densities. Abstract Estimates of precipitation are improved when raingage observations are used to calibrate quantitative radar data as well as to estimate precipitation in areas without radar data. Estimated areal precipitation depth errors for nine rainfalls over a 3000 km2 watershed averaged 13 and 14% (1.5 and 1.8 mm) when the radar was calibrated by networks of raingages having densities of one gage per 900 and 1600 km2. Areal precipitation estimates derived from rainfalls observed at the gages alone produced errors of 21 and 24% (2.5 and 3.0 mm). Adjusting the radar data by a single calibration factor (the simple average ratio of gage-observed and radar-inferred rainfall at all input gages without regard to the spatial variation among ratios) resulted in error reduction to 18% (2.1 mm). Radar data added to gage observations also increased the explained variance in point rainfall estimates above that from gages alone, from 53 to 77% and 46 to 72% for the above gage densities.