Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China

This study evaluated and intercompared seven near-real-time (NRT) versions of satellite-based precipitation products (SPPs) with latencies of less than one day, including GSMaP-NRT, GSMaP-Gauge-NRT, GSMaP-NOW, IMERG-Early, IMERG-Late, TMPA 3B42RT, and PERSIANN-CCS for wet seasons from 2008 to 2019 i...

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Autores principales:	Yanhong Dou, Lei Ye, Jiayan Zhang, Chi Zhang, Huicheng Zhou
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	near real-time satellite-based precipitation flood sub-seasons streamflow simulations Nierji Basin Science Q
Acceso en línea:	https://doaj.org/article/3c1d6cbe26cf40b1a19826f0d89476eb
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spelling	oai:doaj.org-article:3c1d6cbe26cf40b1a19826f0d89476eb2021-11-25T18:54:10ZEvaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China10.3390/rs132245522072-4292https://doaj.org/article/3c1d6cbe26cf40b1a19826f0d89476eb2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4552https://doaj.org/toc/2072-4292This study evaluated and intercompared seven near-real-time (NRT) versions of satellite-based precipitation products (SPPs) with latencies of less than one day, including GSMaP-NRT, GSMaP-Gauge-NRT, GSMaP-NOW, IMERG-Early, IMERG-Late, TMPA 3B42RT, and PERSIANN-CCS for wet seasons from 2008 to 2019 in a typical middle–high latitude temperate monsoon climate basin, namely, the Nierji Basin in China, in four aspects: flood sub-seasons, rainfall intensities, precipitation events, and hydrological utility. Our evaluation shows that the cell-scale and area-scale intercomparison ranks of NRT SPPs are similar in these four aspects. The performances of SPPs at the areal scale, at the event scale, and with light magnitude are better than those at the cell scale, at the daily scale, and with heavy magnitude, respectively. Most SPPs are similar in terms of their Pearson Correlation Coefficient (CC). The main difference between SPPs is in terms of their root-mean-square error (RMSE). The worse performances of TMPA 3B42RT are mainly caused by the poor performances during main flood seasons. The worst performances of PERSIANN-CCS are primarily reflected by the lowest CC and the underestimation of precipitation. Though GSMaP-NOW has the highest RMSE and overestimates precipitation, it can reflect the precipitation variation, as indicated by the relatively high CC. The differences among SPPs are more significant in pre-flood seasons and less significant in post-flood seasons. These results can provide valuable guidelines for the selection, correction, and application of NRT SPPs and contribute to improved insight into NRT-SPP retrieval algorithms.Yanhong DouLei YeJiayan ZhangChi ZhangHuicheng ZhouMDPI AGarticlenear real-timesatellite-based precipitationflood sub-seasonsstreamflow simulationsNierji BasinScienceQENRemote Sensing, Vol 13, Iss 4552, p 4552 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	near real-time satellite-based precipitation flood sub-seasons streamflow simulations Nierji Basin Science Q
spellingShingle	near real-time satellite-based precipitation flood sub-seasons streamflow simulations Nierji Basin Science Q Yanhong Dou Lei Ye Jiayan Zhang Chi Zhang Huicheng Zhou Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China
description	This study evaluated and intercompared seven near-real-time (NRT) versions of satellite-based precipitation products (SPPs) with latencies of less than one day, including GSMaP-NRT, GSMaP-Gauge-NRT, GSMaP-NOW, IMERG-Early, IMERG-Late, TMPA 3B42RT, and PERSIANN-CCS for wet seasons from 2008 to 2019 in a typical middle–high latitude temperate monsoon climate basin, namely, the Nierji Basin in China, in four aspects: flood sub-seasons, rainfall intensities, precipitation events, and hydrological utility. Our evaluation shows that the cell-scale and area-scale intercomparison ranks of NRT SPPs are similar in these four aspects. The performances of SPPs at the areal scale, at the event scale, and with light magnitude are better than those at the cell scale, at the daily scale, and with heavy magnitude, respectively. Most SPPs are similar in terms of their Pearson Correlation Coefficient (CC). The main difference between SPPs is in terms of their root-mean-square error (RMSE). The worse performances of TMPA 3B42RT are mainly caused by the poor performances during main flood seasons. The worst performances of PERSIANN-CCS are primarily reflected by the lowest CC and the underestimation of precipitation. Though GSMaP-NOW has the highest RMSE and overestimates precipitation, it can reflect the precipitation variation, as indicated by the relatively high CC. The differences among SPPs are more significant in pre-flood seasons and less significant in post-flood seasons. These results can provide valuable guidelines for the selection, correction, and application of NRT SPPs and contribute to improved insight into NRT-SPP retrieval algorithms.
format	article
author	Yanhong Dou Lei Ye Jiayan Zhang Chi Zhang Huicheng Zhou
author_facet	Yanhong Dou Lei Ye Jiayan Zhang Chi Zhang Huicheng Zhou
author_sort	Yanhong Dou
title	Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China
title_short	Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China
title_full	Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China
title_fullStr	Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China
title_full_unstemmed	Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China
title_sort	evaluation of seven near-real-time satellite-based precipitation products for wet seasons in the nierji basin, china
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3c1d6cbe26cf40b1a19826f0d89476eb
work_keys_str_mv	AT yanhongdou evaluationofsevennearrealtimesatellitebasedprecipitationproductsforwetseasonsinthenierjibasinchina AT leiye evaluationofsevennearrealtimesatellitebasedprecipitationproductsforwetseasonsinthenierjibasinchina AT jiayanzhang evaluationofsevennearrealtimesatellitebasedprecipitationproductsforwetseasonsinthenierjibasinchina AT chizhang evaluationofsevennearrealtimesatellitebasedprecipitationproductsforwetseasonsinthenierjibasinchina AT huichengzhou evaluationofsevennearrealtimesatellitebasedprecipitationproductsforwetseasonsinthenierjibasinchina
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Evaluation of Seven Near-Real-Time Satellite-Based Precipitation Products for Wet Seasons in the Nierji Basin, China

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