TY - JOUR
T1 - Performance assessment of GPM-based near-real-time satellite products in depicting diurnal precipitation variation over Taiwan
AU - Hsu, Jie
AU - Huang, Wan Ru
AU - Liu, Pin Yi
N1 - Funding Information:
We greatly appreciate the IMERG, GSMaP, and CWB precipitation data provided by NASA (available at https://gpm.nasa.gov/data/imerg ), JAXA (available at https://sharaku.eorc.jaxa.jp/GSMaP/ ), and CWB (available at https://dbar.pccu.edu.tw/ ), respectively. In addition, we are particularly grateful to Dr. Takuji Kubota and Dr. George J. Huffman for providing comments to help explain the possible factors of bias in the GSMaP data and IMERG data, respectively. This study was supported by the Ministry of Science and Technology of Taiwan under MOST 106-2628-M-003-001-MY4 , MOST 110-2111-M-003-003 , and MOST 110-2625-M-003-004 .
Funding Information:
We greatly appreciate the IMERG, GSMaP, and CWB precipitation data provided by NASA (available at https://gpm.nasa.gov/data/imerg), JAXA (available at https://sharaku.eorc.jaxa.jp/GSMaP/), and CWB (available at https://dbar.pccu.edu.tw/), respectively. In addition, we are particularly grateful to Dr. Takuji Kubota and Dr. George J. Huffman for providing comments to help explain the possible factors of bias in the GSMaP data and IMERG data, respectively. This study was supported by the Ministry of Science and Technology of Taiwan under MOST 106-2628-M-003-001-MY4, MOST 110-2111-M-003-003, and MOST 110-2625-M-003-004.
Publisher Copyright:
© 2021 The Authors
PY - 2021/12
Y1 - 2021/12
N2 - Study Region: Taiwan. Study Focus: The precipitation in Taiwan demonstrates clear diurnal variations. This study evaluated the performance of four near-real-time (NRT) multiple-satellite precipitation products (MSPPs) from the Global Precipitation Measurement (GPM) mission in depicting the variation in diurnal precipitation from 2017 to 2020, in May to September (MJJAS). The four MSPPs include the V06 of Integrated Multi-satellitE Retrievals for the GPM Early Run (IMERG-E) and Late Run (IMERG-L), and the V07 of Global Satellite Mapping of Precipitation NRT (GSMaP-N) and Gauge-NRT (GSMaP-GN). Two sub-components of diurnal precipitation variation were evaluated, daily mean (Pm) and anomalies (ΔP); ΔP was further separated into diurnal (S1) and semidiurnal (S2) harmonic modes. New hydrological insights for the region: Compared with surface observations, results show that all NRT MSPPs underestimate Pm and ΔP, but the IMERG products are better than GSMaP products in most of the examined spatial characteristics. Temporally, only IMERG-E depicts the phase evolution of both S1 and S2, similar to surface observations. These findings indicate that IMERG-E is the best NRT product for studying the diurnal precipitation characteristics across MJJAS in Taiwan. The general bias in the NRT MSPPs considered in the study in depicting the features examined was attributed to the limitation of passive microwave sensors in illustrating the developing and dissipating stage of diurnal precipitation formation, and to the weakness of infrared precipitation algorithms in detecting warm orographic clouds.
AB - Study Region: Taiwan. Study Focus: The precipitation in Taiwan demonstrates clear diurnal variations. This study evaluated the performance of four near-real-time (NRT) multiple-satellite precipitation products (MSPPs) from the Global Precipitation Measurement (GPM) mission in depicting the variation in diurnal precipitation from 2017 to 2020, in May to September (MJJAS). The four MSPPs include the V06 of Integrated Multi-satellitE Retrievals for the GPM Early Run (IMERG-E) and Late Run (IMERG-L), and the V07 of Global Satellite Mapping of Precipitation NRT (GSMaP-N) and Gauge-NRT (GSMaP-GN). Two sub-components of diurnal precipitation variation were evaluated, daily mean (Pm) and anomalies (ΔP); ΔP was further separated into diurnal (S1) and semidiurnal (S2) harmonic modes. New hydrological insights for the region: Compared with surface observations, results show that all NRT MSPPs underestimate Pm and ΔP, but the IMERG products are better than GSMaP products in most of the examined spatial characteristics. Temporally, only IMERG-E depicts the phase evolution of both S1 and S2, similar to surface observations. These findings indicate that IMERG-E is the best NRT product for studying the diurnal precipitation characteristics across MJJAS in Taiwan. The general bias in the NRT MSPPs considered in the study in depicting the features examined was attributed to the limitation of passive microwave sensors in illustrating the developing and dissipating stage of diurnal precipitation formation, and to the weakness of infrared precipitation algorithms in detecting warm orographic clouds.
KW - Complex terrain
KW - Diurnal precipitation
KW - East Asia
KW - Satellite Precipitation
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U2 - 10.1016/j.ejrh.2021.100957
DO - 10.1016/j.ejrh.2021.100957
M3 - Article
AN - SCOPUS:85118500382
SN - 2214-5818
VL - 38
JO - Journal of Hydrology: Regional Studies
JF - Journal of Hydrology: Regional Studies
M1 - 100957
ER -