Abstract
Satellite remote sensing is a practical technique to estimate global precipitation with adequate spatiotemporal resolution in ungauged regions. However, the performance of satellite-based precipitation products is variable and uncertain for the Tibetan Plateau (TP) because of its complex terrain and climate conditions. In this study, we evaluated the abilities of nine widely used satellite-based precipitation products over the Eastern Tibetan Plateau (ETP) and quantified precipitation dynamics over the entire TP. The evaluation was carried out from three aspects, i.e., magnitude agreement, occurrence consistency, and elevation dependency, from grid-cell to regional scales. The results show that the nine satellite-based products exhibited different agreement with gauge-based reference data with median correlation coefficients ranging from 0.15 to 0.95. Three products (climate hazards group infrared precipitation with stations (CHIRPS), multi-source weighted-ensemble precipitation (MSWEP), and tropical rainfall measuring mission multi-satellite precipitation analysis (TMPA)) generally presented the best performance with the reference data, even in complex terrain regions, given their root mean square errors (RMSE) of less than 25 mm/mon. The climate prediction center merged analysis of precipitation (CMAP) product has relatively coarse spatial resolution, but it also exhibited good performance with a bias of less than 20% in watershed scale. Two other products (precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system (PER-CCS) and climate prediction center morphing technique-raw (CMORPH-RAW)) overestimated precipitation with median RMSEs of 87 mm/mon and 45 mm/mon, respectively. All the precipitation products generally exhibited better agreement with the reference data for rainy season and lower-elevation regions. All of the products captured precipitation occurrence well, with hit event over 60%, and similar percentages of missed and false event. According to the evaluation, the four products (CHIRPS, MSWEP, TMPA, and CMAP) revealed that the annual precipitation over the TP fluctuated between 333 mm/yr and 488 mm/yr during the period 2003 to 2015. The study indicates the importance of integration of multiple data sources and post-processing (e.g., gauge data fusion and elevation correction) for satellite-based products and have implications for selection of suitable precipitation products for hydrological modeling and water resources assessment for the TP.
Highlights
Precipitation is a critical variable dominating land surface hydrological processes, e.g., runoff generation and soil moisture dynamics, and regulating energy balances associated with latent and sensible heat fluxes [1,2]
Accurate estimation of precipitation is necessary for water resource management, climate change detection, and hydrological modeling, and it is important for the Tibetan Plateau (TP), which is regarded as the Asian water tower for sources of major Asian river basins [3]
It is worth noting that center merged analysis of precipitation (CMAP) product given a large bias but favorable performance according to the other two measures
Summary
Precipitation is a critical variable dominating land surface hydrological processes, e.g., runoff generation and soil moisture dynamics, and regulating energy balances associated with latent and sensible heat fluxes [1,2]. Accurate estimation of precipitation is necessary for water resource management, climate change detection, and hydrological modeling, and it is important for the Tibetan Plateau (TP), which is regarded as the Asian water tower for sources of major Asian river basins [3]. Precipitation can be generally estimated using in situ gauge networks, global climate models (GCMs), reanalysis systems, and remote sensing retrievals. In situ measurement with gauge networks is a traditional approach to obtaining point-scale precipitation information [1,4]. A large portion of TP, in the western TP, does not have in situ gauge networks for precipitation measurement because of the severe weather, high elevation, and complex terrain [5]
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