Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale
The precipitation phase (i.e., rain and snow) is important for the global hydrologic cycle and climate system. The objective of this study is to evaluate the precipitation-phase partitioning capabilities of remote sensing and reanalysis modeling methods on the global scale. Specifically, observation...
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2022
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ftdoajarticles:oai:doaj.org/article:3f163eb5d0a547298160e7dcfc4e20d9 2023-05-15T14:06:28+02:00 Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale Wentao Xiong Guoqiang Tang Tsechun Wang Ziqiang Ma Wei Wan 2022-03-01T00:00:00Z https://doi.org/10.3390/w14071122 https://doaj.org/article/3f163eb5d0a547298160e7dcfc4e20d9 EN eng MDPI AG https://www.mdpi.com/2073-4441/14/7/1122 https://doaj.org/toc/2073-4441 doi:10.3390/w14071122 2073-4441 https://doaj.org/article/3f163eb5d0a547298160e7dcfc4e20d9 Water, Vol 14, Iss 1122, p 1122 (2022) snowfall precipitation phase temperature NCEP ADP statistical evaluation Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 article 2022 ftdoajarticles https://doi.org/10.3390/w14071122 2022-12-31T12:11:48Z The precipitation phase (i.e., rain and snow) is important for the global hydrologic cycle and climate system. The objective of this study is to evaluate the precipitation-phase partitioning capabilities of remote sensing and reanalysis modeling methods on the global scale. Specifically, observation data from the National Centers for Environmental Prediction (NCEP) Automated Data Processing (ADP), from 2000 to 2007, are used to evaluate the rain–snow discrimination accuracy of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5). The results show that: (1) the ERA5 performs better than the IMERG at distinguishing rainfall and snowfall events, overall. (2) The ERA5 has high accuracy in all continents except for South America, while the IMERG performs well only in Antarctica and North America. (3) Compared with the IMERG, the ERA5 can more effectively capture snowfall events at high latitudes but shows worse performance at mid-low latitude regions. Both the IMERG and ERA5 have lower accuracy for rain–snow partitioning under heavy precipitation. Overall, the results of this study provide references for the application and improvement of global rain–snow partitioning products. Article in Journal/Newspaper Antarc* Antarctica Directory of Open Access Journals: DOAJ Articles Water 14 7 1122 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
snowfall precipitation phase temperature NCEP ADP statistical evaluation Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 |
spellingShingle |
snowfall precipitation phase temperature NCEP ADP statistical evaluation Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Wentao Xiong Guoqiang Tang Tsechun Wang Ziqiang Ma Wei Wan Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale |
topic_facet |
snowfall precipitation phase temperature NCEP ADP statistical evaluation Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 |
description |
The precipitation phase (i.e., rain and snow) is important for the global hydrologic cycle and climate system. The objective of this study is to evaluate the precipitation-phase partitioning capabilities of remote sensing and reanalysis modeling methods on the global scale. Specifically, observation data from the National Centers for Environmental Prediction (NCEP) Automated Data Processing (ADP), from 2000 to 2007, are used to evaluate the rain–snow discrimination accuracy of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5). The results show that: (1) the ERA5 performs better than the IMERG at distinguishing rainfall and snowfall events, overall. (2) The ERA5 has high accuracy in all continents except for South America, while the IMERG performs well only in Antarctica and North America. (3) Compared with the IMERG, the ERA5 can more effectively capture snowfall events at high latitudes but shows worse performance at mid-low latitude regions. Both the IMERG and ERA5 have lower accuracy for rain–snow partitioning under heavy precipitation. Overall, the results of this study provide references for the application and improvement of global rain–snow partitioning products. |
format |
Article in Journal/Newspaper |
author |
Wentao Xiong Guoqiang Tang Tsechun Wang Ziqiang Ma Wei Wan |
author_facet |
Wentao Xiong Guoqiang Tang Tsechun Wang Ziqiang Ma Wei Wan |
author_sort |
Wentao Xiong |
title |
Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale |
title_short |
Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale |
title_full |
Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale |
title_fullStr |
Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale |
title_full_unstemmed |
Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale |
title_sort |
evaluation of imerg and era5 precipitation-phase partitioning on the global scale |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/w14071122 https://doaj.org/article/3f163eb5d0a547298160e7dcfc4e20d9 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_source |
Water, Vol 14, Iss 1122, p 1122 (2022) |
op_relation |
https://www.mdpi.com/2073-4441/14/7/1122 https://doaj.org/toc/2073-4441 doi:10.3390/w14071122 2073-4441 https://doaj.org/article/3f163eb5d0a547298160e7dcfc4e20d9 |
op_doi |
https://doi.org/10.3390/w14071122 |
container_title |
Water |
container_volume |
14 |
container_issue |
7 |
container_start_page |
1122 |
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1766278179793666048 |