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DOI | 10.1002/2016JD025489 |
Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile-based probabilistic forecasts | |
Shastri, Hiteshri1; Ghosh, Subimal1,2; Karmakar, Subhankar1,3 | |
2017-02-16 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES |
ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2017 |
卷号 | 122期号:3 |
文章类型 | Article |
语种 | 英语 |
国家 | India |
英文摘要 | Forecasting of extreme precipitation events at a regional scale is of high importance due to their severe impacts on society. The impacts are stronger in urban regions due to high flood potential as well high population density leading to high vulnerability. Although significant scientific improvements took place in the global models for weather forecasting, they are still not adequate at a regional scale (e. g., for an urban region) with high false alarms and low detection. There has been a need to improve the weather forecast skill at a local scale with probabilistic outcome. Here we develop a methodology with quantile regression, where the reliably simulated variables from Global Forecast System are used as predictors and different quantiles of rainfall are generated corresponding to that set of predictors. We apply this method to a flood-prone coastal city of India, Mumbai, which has experienced severe floods in recent years. We find significant improvements in the forecast with high detection and skill scores. We apply the methodology to 10 ensemble members of Global Ensemble Forecast System and find a reduction in ensemble uncertainty of precipitation across realizations with respect to that of original precipitation forecasts. We validate our model for the monsoon season of 2006 and 2007, which are independent of the training/calibration data set used in the study. We find promising results and emphasize to implement such data-driven methods for a better probabilistic forecast at an urban scale primarily for an early flood warning. |
领域 | 气候变化 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000396119200013 |
WOS关键词 | INDIAN-SUMMER MONSOON ; CLIMATE-CHANGE ; PREDICTION SYSTEMS ; WEATHER RESEARCH ; HEAVY RAINFALL ; WRF MODEL ; IMPACTS ; MUMBAI ; SCALE ; VARIABILITY |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/32318 |
专题 | 气候变化 |
作者单位 | 1.Indian Inst Technol, Interdisciplinary Program Climate Studies, Powai, India; 2.Indian Inst Technol, Dept Civil Engn, Powai, India; 3.Indian Inst Technol, Ctr Environm Sci & Engn, Powai, India |
推荐引用方式 GB/T 7714 | Shastri, Hiteshri,Ghosh, Subimal,Karmakar, Subhankar. Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile-based probabilistic forecasts[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2017,122(3). |
APA | Shastri, Hiteshri,Ghosh, Subimal,&Karmakar, Subhankar.(2017).Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile-based probabilistic forecasts.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,122(3). |
MLA | Shastri, Hiteshri,et al."Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile-based probabilistic forecasts".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 122.3(2017). |
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