Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis
Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean st...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Li, Chunxiang [verfasserIn] Zhao, Tianbao [verfasserIn] Shi, Chunxiang [verfasserIn] Liu, Zhiquan [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
China Meteorological Administration (CMA) |
|---|
| Übergeordnetes Werk: |
Enthalten in: Acta Meteorologica Sinica - The Chinese Meteorological Society, 2011, 34(2020), 1 vom: Feb., Seite 117-136 |
|---|---|
| Übergeordnetes Werk: |
volume:34 ; year:2020 ; number:1 ; month:02 ; pages:117-136 |
| Links: |
|---|
| DOI / URN: |
10.1007/s13351-020-8196-9 |
|---|
| Katalog-ID: |
SPR039027457 |
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| 520 | |a Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. | ||
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10.1007/s13351-020-8196-9 doi (DE-627)SPR039027457 (SPR)s13351-020-8196-9-e DE-627 ger DE-627 rakwb eng Li, Chunxiang verfasserin aut Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. China Meteorological Administration (CMA) (dpeaa)DE-He213 the CMA Global Atmospheric Interim Reanalysis (CRAI) (dpeaa)DE-He213 precipitation (dpeaa)DE-He213 daily (dpeaa)DE-He213 Zhao, Tianbao verfasserin aut Shi, Chunxiang verfasserin aut Liu, Zhiquan verfasserin aut Enthalten in Acta Meteorologica Sinica The Chinese Meteorological Society, 2011 34(2020), 1 vom: Feb., Seite 117-136 (DE-627)SPR031424376 nnns volume:34 year:2020 number:1 month:02 pages:117-136 https://dx.doi.org/10.1007/s13351-020-8196-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 34 2020 1 02 117-136 |
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10.1007/s13351-020-8196-9 doi (DE-627)SPR039027457 (SPR)s13351-020-8196-9-e DE-627 ger DE-627 rakwb eng Li, Chunxiang verfasserin aut Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. China Meteorological Administration (CMA) (dpeaa)DE-He213 the CMA Global Atmospheric Interim Reanalysis (CRAI) (dpeaa)DE-He213 precipitation (dpeaa)DE-He213 daily (dpeaa)DE-He213 Zhao, Tianbao verfasserin aut Shi, Chunxiang verfasserin aut Liu, Zhiquan verfasserin aut Enthalten in Acta Meteorologica Sinica The Chinese Meteorological Society, 2011 34(2020), 1 vom: Feb., Seite 117-136 (DE-627)SPR031424376 nnns volume:34 year:2020 number:1 month:02 pages:117-136 https://dx.doi.org/10.1007/s13351-020-8196-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 34 2020 1 02 117-136 |
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10.1007/s13351-020-8196-9 doi (DE-627)SPR039027457 (SPR)s13351-020-8196-9-e DE-627 ger DE-627 rakwb eng Li, Chunxiang verfasserin aut Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. China Meteorological Administration (CMA) (dpeaa)DE-He213 the CMA Global Atmospheric Interim Reanalysis (CRAI) (dpeaa)DE-He213 precipitation (dpeaa)DE-He213 daily (dpeaa)DE-He213 Zhao, Tianbao verfasserin aut Shi, Chunxiang verfasserin aut Liu, Zhiquan verfasserin aut Enthalten in Acta Meteorologica Sinica The Chinese Meteorological Society, 2011 34(2020), 1 vom: Feb., Seite 117-136 (DE-627)SPR031424376 nnns volume:34 year:2020 number:1 month:02 pages:117-136 https://dx.doi.org/10.1007/s13351-020-8196-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 34 2020 1 02 117-136 |
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10.1007/s13351-020-8196-9 doi (DE-627)SPR039027457 (SPR)s13351-020-8196-9-e DE-627 ger DE-627 rakwb eng Li, Chunxiang verfasserin aut Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. China Meteorological Administration (CMA) (dpeaa)DE-He213 the CMA Global Atmospheric Interim Reanalysis (CRAI) (dpeaa)DE-He213 precipitation (dpeaa)DE-He213 daily (dpeaa)DE-He213 Zhao, Tianbao verfasserin aut Shi, Chunxiang verfasserin aut Liu, Zhiquan verfasserin aut Enthalten in Acta Meteorologica Sinica The Chinese Meteorological Society, 2011 34(2020), 1 vom: Feb., Seite 117-136 (DE-627)SPR031424376 nnns volume:34 year:2020 number:1 month:02 pages:117-136 https://dx.doi.org/10.1007/s13351-020-8196-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 34 2020 1 02 117-136 |
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10.1007/s13351-020-8196-9 doi (DE-627)SPR039027457 (SPR)s13351-020-8196-9-e DE-627 ger DE-627 rakwb eng Li, Chunxiang verfasserin aut Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. China Meteorological Administration (CMA) (dpeaa)DE-He213 the CMA Global Atmospheric Interim Reanalysis (CRAI) (dpeaa)DE-He213 precipitation (dpeaa)DE-He213 daily (dpeaa)DE-He213 Zhao, Tianbao verfasserin aut Shi, Chunxiang verfasserin aut Liu, Zhiquan verfasserin aut Enthalten in Acta Meteorologica Sinica The Chinese Meteorological Society, 2011 34(2020), 1 vom: Feb., Seite 117-136 (DE-627)SPR031424376 nnns volume:34 year:2020 number:1 month:02 pages:117-136 https://dx.doi.org/10.1007/s13351-020-8196-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 34 2020 1 02 117-136 |
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A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. 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Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis |
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Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis |
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Li, Chunxiang |
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Acta Meteorologica Sinica |
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2020 |
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Li, Chunxiang Zhao, Tianbao Shi, Chunxiang Liu, Zhiquan |
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34 |
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Elektronische Aufsätze |
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Li, Chunxiang |
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10.1007/s13351-020-8196-9 |
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evaluation of daily precipitation product in china from the cma global atmospheric interim reanalysis |
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Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis |
| abstract |
Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. |
| abstractGer |
Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. |
| abstract_unstemmed |
Abstract The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs. |
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Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis |
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Zhao, Tianbao Shi, Chunxiang Liu, Zhiquan |
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