Publication Date:
2017-07-22
Description:
In the summer of 2016, severe storms caused serious casualties and destruction of facilities and properties over South China. Near-real-time (NRT) satellite precipitation products are attractive to rainstorm monitoring and flood warning guidance owing to its combination of timeliness, high spatiotemporal resolution, and broad coverage. We evaluate the performance of four NRT satellite products, i.e., Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, 3B42RT, Global Satellite Mapping of Precipitation (GSMaP) NRT, and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Late run using a high-quality merged product in the rainy June over South China. In addition, a method based on an empirical flash flood guidance and the Flash Flood Potential Index is proposed to examine the applicability of satellite products in guiding flood warning. The IMERG Late run and GSMaP NRT perform the closest-to-ground observations. 3B42RT detects the most flood warning events due to its notable overestimation of actual precipitation. We recommend that the IMERG Late run is the best NRT satellite product in capturing flood hazard events according to the Pareto Efficiency of jointly optimizing higher hit ratio and lower false alarms.
Print ISSN:
1545-598X
Electronic ISSN:
1558-0571
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
,
Geosciences
