Precipitation measurements provide crucial information for hydrometeorological applications. In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources. This study examines the performance of NASA's Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG, GPM) satellite precipitation dataset in capturing the spatio-temporal variability of weather events compared to the German weather radar dataset RADOLAN RW. Besides quantity, also timing of rainfall is of very high importance when modeling or monitoring the hydrologic cycle. Therefore, detection metrics are evaluated along with standard statistical measures to test both datasets. Using indices like probability of detection allows a binary evaluation showing the basic categorical accordance of the radar and satellite data. Furthermore, a pixel-by-pixel comparison is performed to assess the ability to represent the spatial variability of rainfall and precipitation quantity. All calculations are additionally carried out for seasonal subsets of the data to assess potentially different behavior due to differences in precipitation schemes. The results indicate significant differences between the datasets. Overall, GPM IMERG overestimates the quantity of precipitation compared to RADOLAN, especially in the winter season. Moreover, shortcomings in detection performance arise in this season with significant erroneously-detected, yet also missed precipitation events compared to the weather radar data. Additionally, along secondary mountain ranges and the Alps, topographically-induced precipitation is not represented in GPM data, which generally shows a lack of spatial variability in rainfall and snowfall estimates due to lower resolution.
机构:
Hohai Univ, Coll Water Conservancy & Hydroelect Power, Nanjing, Peoples R China
Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing, Peoples R China
Nanjing Hydraul Res Inst, Ctr Ecoenvironm Res, Nanjing, Peoples R ChinaHohai Univ, Coll Water Conservancy & Hydroelect Power, Nanjing, Peoples R China
Chen, Cheng
Chen, Qiuwen
论文数: 0引用数: 0
h-index: 0
机构:
Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing, Peoples R China
Nanjing Hydraul Res Inst, Ctr Ecoenvironm Res, Nanjing, Peoples R ChinaHohai Univ, Coll Water Conservancy & Hydroelect Power, Nanjing, Peoples R China
Chen, Qiuwen
Qin, Binni
论文数: 0引用数: 0
h-index: 0
机构:
Hohai Univ, Coll Hydrol & Water Resources, Nanjing, Peoples R ChinaHohai Univ, Coll Water Conservancy & Hydroelect Power, Nanjing, Peoples R China
Qin, Binni
Zhao, Shuhe
论文数: 0引用数: 0
h-index: 0
机构:
Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Peoples R China
Jiangsu Ctr Collaborat Innovat Geog Informat Res, Nanjing, Peoples R ChinaHohai Univ, Coll Water Conservancy & Hydroelect Power, Nanjing, Peoples R China
Zhao, Shuhe
Duan, Zheng
论文数: 0引用数: 0
h-index: 0
机构:
Lund Univ, Dept Phys Geog & Ecosyst Sci, Lund, SwedenHohai Univ, Coll Water Conservancy & Hydroelect Power, Nanjing, Peoples R China