Effects of Spatial and Temporal Data Aggregation on the Performance of the Multi‐Radar Multi‐Sensor System
Abstract
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 R2, 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 R2 and a decrease in RMSE, whereas PBIAS was not affected. Reducing spatial resolution from 1 to 50 km resulted in increases in R2 and PBIAS, whereas RMSE was decreased. Increasing spatial aggregation scale from 1 to 50 km resulted in an R2 increase of only 0.08. Similarly, improvement in R2 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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 18, 2019
- Source ID
- 10.1111/1752-1688.12799
Entities
People
- Ali Fares
- Dawit Ghebreyesus
- Haimanote K. Bayabil
- Hatim O. Sharif
- Hernan A. Moreno
Organizations
- Army Research Office
- National Institute of Food and Agriculture
- Texas AgriLife Research
- University of Florida
- University of Oklahoma
- University of Texas at San Antonio