Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecasting
Based on the ensemble precipitation prediction data of the European Centre for medium range weather forecast from 2018 to 2021, ensemble statistics area rainfall prediction products such as mode,mean,optimal percentile,percentile and probability have been developed. Threat score,bias score,relative...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Torrential Rain and Disasters
2022-10-01
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| Series: | 暴雨灾害 |
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| Online Access: | http://www.byzh.org.cn/cn/article/doi/10.12406/byzh.2022-029 |
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| author | Yin YANG jian LIN Hongjun BAO |
| author_facet | Yin YANG jian LIN Hongjun BAO |
| author_sort | Yin YANG |
| collection | DOAJ |
| description | Based on the ensemble precipitation prediction data of the European Centre for medium range weather forecast from 2018 to 2021, ensemble statistics area rainfall prediction products such as mode,mean,optimal percentile,percentile and probability have been developed. Threat score,bias score,relative operating characteristic (ROC) curve method,comprehensive performance diagram and brier skill score are used for verification to ensemble statistics area rainfall prediction products above heavy rain in the Yangtze River basin. Result shows that ensemble statistics area rainfall prediction products were superior to area rainfall forecasting calculated from deterministic precipitation prediction,and the score of plain area basin is higher than that of mountain basin for the area rainfall above heavy rain. There are differences in the types and ranking of the optimal areal rainfall quantitative prediction products in different sub basins of Yangtze River. The overall performance is that the median,mean and optimal percentile was the best,second and third in score among ensemble statistics area rainfall prediction products. The top three ideal ensemble statistics area rainfall prediction product were recommended according to the comprehensive verification result in each sub-basin of Yangtze River. The optimal probability forecast value corresponding to the best threat score of the probability forecast product gradually decreases with the increase of the area rainfall magnitude,and the optimal probability of area rainfall prediction above 15mm (40 mm) magnitude is 50%(30%). Taking the optimal TS score as the benchmark,the reference interval of areal rainfall probability forecast is obtained by floating down 10%. When the ensemble statistics areal rainfall probability forecast is located in the reference interval,the forecast reference value is higher. Taking the No. 5 flood process of the Yangtze River in 2020 as an example,the application analysis of the ensemble statistics area rainfall prediction product combining probability prediction and quantitative prediction recommendation products is carried out,which further shows that the error of the ensemble statistics area rainfall prediction product is significantly less than the deterministic forecast. |
| first_indexed | 2024-03-13T01:17:04Z |
| format | Article |
| id | doaj.art-f919520bbfe04e998c938d092e115c78 |
| institution | Directory Open Access Journal |
| issn | 2097-2164 |
| language | zho |
| last_indexed | 2024-03-13T01:17:04Z |
| publishDate | 2022-10-01 |
| publisher | Editorial Office of Torrential Rain and Disasters |
| record_format | Article |
| series | 暴雨灾害 |
| spelling | doaj.art-f919520bbfe04e998c938d092e115c782023-07-05T10:06:56ZzhoEditorial Office of Torrential Rain and Disasters暴雨灾害2097-21642022-10-0141557157910.12406/byzh.2022-0292862Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecastingYin YANG0jian LIN1Hongjun BAO2National meteorological Center, Beijing 100081National meteorological Center, Beijing 100081National meteorological Center, Beijing 100081Based on the ensemble precipitation prediction data of the European Centre for medium range weather forecast from 2018 to 2021, ensemble statistics area rainfall prediction products such as mode,mean,optimal percentile,percentile and probability have been developed. Threat score,bias score,relative operating characteristic (ROC) curve method,comprehensive performance diagram and brier skill score are used for verification to ensemble statistics area rainfall prediction products above heavy rain in the Yangtze River basin. Result shows that ensemble statistics area rainfall prediction products were superior to area rainfall forecasting calculated from deterministic precipitation prediction,and the score of plain area basin is higher than that of mountain basin for the area rainfall above heavy rain. There are differences in the types and ranking of the optimal areal rainfall quantitative prediction products in different sub basins of Yangtze River. The overall performance is that the median,mean and optimal percentile was the best,second and third in score among ensemble statistics area rainfall prediction products. The top three ideal ensemble statistics area rainfall prediction product were recommended according to the comprehensive verification result in each sub-basin of Yangtze River. The optimal probability forecast value corresponding to the best threat score of the probability forecast product gradually decreases with the increase of the area rainfall magnitude,and the optimal probability of area rainfall prediction above 15mm (40 mm) magnitude is 50%(30%). Taking the optimal TS score as the benchmark,the reference interval of areal rainfall probability forecast is obtained by floating down 10%. When the ensemble statistics areal rainfall probability forecast is located in the reference interval,the forecast reference value is higher. Taking the No. 5 flood process of the Yangtze River in 2020 as an example,the application analysis of the ensemble statistics area rainfall prediction product combining probability prediction and quantitative prediction recommendation products is carried out,which further shows that the error of the ensemble statistics area rainfall prediction product is significantly less than the deterministic forecast.http://www.byzh.org.cn/cn/article/doi/10.12406/byzh.2022-029ensemble statistics area rainfallyangtze river basinverification |
| spellingShingle | Yin YANG jian LIN Hongjun BAO Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecasting 暴雨灾害 ensemble statistics area rainfall yangtze river basin verification |
| title | Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecasting |
| title_full | Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecasting |
| title_fullStr | Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecasting |
| title_full_unstemmed | Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecasting |
| title_short | Prediction and application of area rainfall in the Yangtze River basin based on ensemble precipitation forecasting |
| title_sort | prediction and application of area rainfall in the yangtze river basin based on ensemble precipitation forecasting |
| topic | ensemble statistics area rainfall yangtze river basin verification |
| url | http://www.byzh.org.cn/cn/article/doi/10.12406/byzh.2022-029 |
| work_keys_str_mv | AT yinyang predictionandapplicationofarearainfallintheyangtzeriverbasinbasedonensembleprecipitationforecasting AT jianlin predictionandapplicationofarearainfallintheyangtzeriverbasinbasedonensembleprecipitationforecasting AT hongjunbao predictionandapplicationofarearainfallintheyangtzeriverbasinbasedonensembleprecipitationforecasting |