Effects of Spatial and Temporal Data Aggregation on the Performance of the Multi‐Radar Multi‐Sensor System

The objectives of this study were to (1) evaluate the performance of the Multi-Radar Multi-Sensor (MRMS) system in capturing precipitation compared to gauge data, and (2) assess the effects of spatial (1-50 km) and temporal (15-120 min) data aggregation scales on the performance of the MRMS system. Point-to-grid comparisons were conducted between 215 rain gauges and the MRMS system. The MRMS system at 1 km spatial and 15 min temporal resolutions captured precipitation reasonably well with average R-2, root mean square error (RMSE), and percent bias (PBIAS) values of 0.65, 0.5 mm, and 11.9 mm; whereas Threat Score, probability of detection, and false alarm ratio were 0.57, 0.92, and 0.40, respectively. Decreasing temporal resolution from 15 min to two hours resulted in an increase in R-2 and a decrease in RMSE, whereas PBIAS was not affected. Reducing spatial resolution from 1 to 50 km resulted in increases in R-2 and PBIAS, whereas RMSE was decreased. Increasing spatial aggregation scale from 1 to 50 km resulted in an R-2 increase of only 0.08. Similarly, improvement in R-2 was only modest (0.17) compared to an eightfold reduction in temporal resolution (from 15 min to two hours). While aggregating data at coarser temporal resolutions resolved some of the under/overestimation issues of the MRMS system, it was apparent even at coarser spatial and temporal resolutions the MRMS system inherently overestimated smaller precipitation events while underestimated bigger events.