Event‐Based Evaluation of the GPM Multisatellite Merged Precipitation Product From 2014 to 2018 Over China: Methods and Results

Abstract

While gauge observations serve as a traditional way to measure precipitation, remote sensing technology has grown rapidly in recent decades and become another effective method for estimating precipitation (Kucera et al., 2013; Yang et al., 2013). By detecting the properties of precipitating clouds, satellites estimate snapshots of the precipitation rate from infrared (IR) sensors, relatively direct passive microwave (PMW) sensors, or Precipitation Radar (PR) (Kummerow et al., 2015; Sun et al., 2018; Yang et al., 2013). By further combining these multiple satellite sources, quasi-global gridded products have been developed (e.g., Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), Climate Prediction Center (CPC) Morphing (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Integrated MultisatellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG)), which have been used in a wide range of applications (

Mapping the representativeness of precipitation measurements in Mainland China

“…With the surroundings of the Tibetan Plateau and the Pacific Ocean, China has a particularly complex topography and underlying surface (Yu et al 2014). The complex topographic conditions cause the distribution of weather stations in China to be very uneven, with more densely distributed stations over the eastern plains and a scarcity of stations over the western mountainous areas (Li et al 2021). In the past, many scientists have investigated the spatial representativeness of surface meteorological stations by merely using gauge observations, such as the correlation between neighboring gauge observations in a certain area (Nappo et al 1982, Jacobs 1989, Wang et al 2011, Li and Li 2017.…”

“…Precipitation, a vital component of the water and energy cycle, is one of the most common weather events that occurs in our daily lives (Trenberth et al 2003, Kidd and Huffman 2011, Hou et al 2014. Unlike other meteorological fields, precipitation is a discontinuous variable and presents in the form of events (Li et al 2021). Due to various formation mechanisms, precipitation may also vary greatly with distance (Li et al 2011).…”

Evaluation of Three Gridded Precipitation Products to Quantify Water Inputs over Complex Mountainous Terrain of Western China

“…IMERG provides rainfall and snowfall information at 0.1 • spatial and half-hour temporal resolutions. The recent version of IMERG V6 uses retrospective processing back through the TRMM era and integrates the advantages of many previous algorithms [83], such as the PERSIANN Cloud Classification System [84], TMPA satellite-gauge combination procedure [43], and CMORPH Kalman filter Lagrangian time interpolation algorithm [35] and covers the period beginning in June 2000 [85,86]. IMERG precipitation estimates from 2000 to 2018 indicated that IMERG is robust in the transition period around 2014 [35].…”

How is spatial homogeneity in precipitation extremes changing globally?

“…Even though the satellite products are known to underestimate rainfall rates for deep convective systems (Adhikari et al, 2019;Dinku et al, 2010;Duan et al, 2015;Kucera & Klepp, 2022;R. Li et al, 2021), their high spatio-temporal resolution and global coverage make them useful in assessing change in the spatial extent of precipitation.…”