Research and application of bias correction method for heavy rainfall forecast of ECMWF model

Using the daily precipitation data at 81 stations in Anhui province, NCEP 500 hPa height reanalysis data, EC precipitation and 500 hPa height forecast, on the basis of the objective judgment of rainstorm center and weather type, the forecast bias of precipitation center of 23 heavy precipitation eve...

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Main Authors: Jiao ZHANG, Dongyong WANG, Linlin ZHENG, Chen YAO, Yueqi HU, Hongfang ZHU, Yi XU
Format: Article
Language:zho
Published: Editorial Office of Torrential Rain and Disasters 2021-08-01
Series:暴雨灾害
Subjects:
Online Access:http://www.byzh.org.cn/cn/article/doi/10.3969/j.issn.1004-9045.2021.04.011
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author Jiao ZHANG
Dongyong WANG
Linlin ZHENG
Chen YAO
Yueqi HU
Hongfang ZHU
Yi XU
author_facet Jiao ZHANG
Dongyong WANG
Linlin ZHENG
Chen YAO
Yueqi HU
Hongfang ZHU
Yi XU
author_sort Jiao ZHANG
collection DOAJ
description Using the daily precipitation data at 81 stations in Anhui province, NCEP 500 hPa height reanalysis data, EC precipitation and 500 hPa height forecast, on the basis of the objective judgment of rainstorm center and weather type, the forecast bias of precipitation center of 23 heavy precipitation events from 2012 to 2018 is classified and counted. The results show that when the EC forecast precipitation center is located in the north of the 584 dagpm line from 115°E to 120°E, the forecast of precipitation center tends to be biased north. According to the latitude difference between the two and the forecast bias of precipitation center, a correction method of main rain belt position based on weather classification is established. meanwhile, according to the daily averaged biases of the precipitation forecast in the maximum precipitation area of 23 heavy precipitation events, a method for correcting the intensity of rainstorm is established. The bias correction method is applied during the plum flood season in Anhui province in 2020, and the results show that the TS score of rainstorm forecast can be significantly improved regardless of the location or intensity correction. After the correction of both location and intensity, the improvement of TS score is more obvious, especially for the two strongest precipitation events in 2020.
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spelling doaj.art-035bdac9dbd54508a322014cd3d0a9282023-07-06T04:31:04ZzhoEditorial Office of Torrential Rain and Disasters暴雨灾害2097-21642021-08-0140443043610.3969/j.issn.1004-9045.2021.04.0112763Research and application of bias correction method for heavy rainfall forecast of ECMWF modelJiao ZHANG0Dongyong WANG1Linlin ZHENG2Chen YAO3Yueqi HU4Hongfang ZHU5Yi XU6Anhui Meteorological Observatory, Hefei 230031Anhui Meteorological Observatory, Hefei 230031Anhui Meteorological Observatory, Hefei 230031Anhui Meteorological Observatory, Hefei 230031Huangshan Meteorological Bureau of Anhui Province, Huangshan 245000Anhui Meteorological Observatory, Hefei 230031Anhui Meteorological Observatory, Hefei 230031Using the daily precipitation data at 81 stations in Anhui province, NCEP 500 hPa height reanalysis data, EC precipitation and 500 hPa height forecast, on the basis of the objective judgment of rainstorm center and weather type, the forecast bias of precipitation center of 23 heavy precipitation events from 2012 to 2018 is classified and counted. The results show that when the EC forecast precipitation center is located in the north of the 584 dagpm line from 115°E to 120°E, the forecast of precipitation center tends to be biased north. According to the latitude difference between the two and the forecast bias of precipitation center, a correction method of main rain belt position based on weather classification is established. meanwhile, according to the daily averaged biases of the precipitation forecast in the maximum precipitation area of 23 heavy precipitation events, a method for correcting the intensity of rainstorm is established. The bias correction method is applied during the plum flood season in Anhui province in 2020, and the results show that the TS score of rainstorm forecast can be significantly improved regardless of the location or intensity correction. After the correction of both location and intensity, the improvement of TS score is more obvious, especially for the two strongest precipitation events in 2020.http://www.byzh.org.cn/cn/article/doi/10.3969/j.issn.1004-9045.2021.04.011ec rainstorm forecastweather classificationprecipitation centerposition biascorrection method
spellingShingle Jiao ZHANG
Dongyong WANG
Linlin ZHENG
Chen YAO
Yueqi HU
Hongfang ZHU
Yi XU
Research and application of bias correction method for heavy rainfall forecast of ECMWF model
暴雨灾害
ec rainstorm forecast
weather classification
precipitation center
position bias
correction method
title Research and application of bias correction method for heavy rainfall forecast of ECMWF model
title_full Research and application of bias correction method for heavy rainfall forecast of ECMWF model
title_fullStr Research and application of bias correction method for heavy rainfall forecast of ECMWF model
title_full_unstemmed Research and application of bias correction method for heavy rainfall forecast of ECMWF model
title_short Research and application of bias correction method for heavy rainfall forecast of ECMWF model
title_sort research and application of bias correction method for heavy rainfall forecast of ecmwf model
topic ec rainstorm forecast
weather classification
precipitation center
position bias
correction method
url http://www.byzh.org.cn/cn/article/doi/10.3969/j.issn.1004-9045.2021.04.011
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