{"title":"EnKF集合对EnVar混合同化的影响","authors":"V. S. Prasad, C. Johny, J. Sodhi, E. Rajagopal","doi":"10.1117/12.2222771","DOIUrl":null,"url":null,"abstract":"Performance of an EnVar hybrid data assimilation system based on 3D Var NGFS (NCMRWF Global Forecast System) of T574 configuration and Ensemble Kalman Filter is investigated. The experiment is conducted during the Indian monsoon season (June-September) 2015 and compared against operational GSI 3D Var system. Two way coupled dual resolution hybrid system with 80 member ensemble of T254L64 configuration are used and forecasts are done for 10days. In hybrid experiment 75% weight is given to ensemble covariance and 25% for static covariance. The forecast skill of experiments over different spatial domains is compared against observations and respective analysis. The hybrid experiment produced significant improvement in forecasts compared to 3D Var in all fields except lower level temperature over tropical regions. Improvement is also seen in the prediction of extreme rainfall events. The prediction of monsoon onset and track of cyclone Ashobaa with hybrid and 3D var system is discussed.","PeriodicalId":165733,"journal":{"name":"SPIE Asia-Pacific Remote Sensing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact of EnVar hybrid assimilation using EnKF ensembles\",\"authors\":\"V. S. Prasad, C. Johny, J. Sodhi, E. Rajagopal\",\"doi\":\"10.1117/12.2222771\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Performance of an EnVar hybrid data assimilation system based on 3D Var NGFS (NCMRWF Global Forecast System) of T574 configuration and Ensemble Kalman Filter is investigated. The experiment is conducted during the Indian monsoon season (June-September) 2015 and compared against operational GSI 3D Var system. Two way coupled dual resolution hybrid system with 80 member ensemble of T254L64 configuration are used and forecasts are done for 10days. In hybrid experiment 75% weight is given to ensemble covariance and 25% for static covariance. The forecast skill of experiments over different spatial domains is compared against observations and respective analysis. The hybrid experiment produced significant improvement in forecasts compared to 3D Var in all fields except lower level temperature over tropical regions. Improvement is also seen in the prediction of extreme rainfall events. The prediction of monsoon onset and track of cyclone Ashobaa with hybrid and 3D var system is discussed.\",\"PeriodicalId\":165733,\"journal\":{\"name\":\"SPIE Asia-Pacific Remote Sensing\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SPIE Asia-Pacific Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2222771\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SPIE Asia-Pacific Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2222771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
研究了基于T574结构的三维Var NGFS (NCMRWF全球预报系统)和集成卡尔曼滤波的EnVar混合数据同化系统的性能。该实验在印度季风季节(2015年6 - 9月)进行,并与GSI 3D Var系统进行了比较。采用80元T254L64结构的双向耦合双分辨率混合系统,进行了10天的预报。混合实验中,整体协方差权重为75%,静态协方差权重为25%。将不同空间域的试验预报能力与观测结果和各自的分析结果进行了比较。与3D Var相比,混合试验在除热带地区较低温度外的所有领域的预测都有显著改善。对极端降雨事件的预测也有所改善。讨论了混合var系统和三维var系统对气旋Ashobaa季风发生和路径的预测。
Impact of EnVar hybrid assimilation using EnKF ensembles
Performance of an EnVar hybrid data assimilation system based on 3D Var NGFS (NCMRWF Global Forecast System) of T574 configuration and Ensemble Kalman Filter is investigated. The experiment is conducted during the Indian monsoon season (June-September) 2015 and compared against operational GSI 3D Var system. Two way coupled dual resolution hybrid system with 80 member ensemble of T254L64 configuration are used and forecasts are done for 10days. In hybrid experiment 75% weight is given to ensemble covariance and 25% for static covariance. The forecast skill of experiments over different spatial domains is compared against observations and respective analysis. The hybrid experiment produced significant improvement in forecasts compared to 3D Var in all fields except lower level temperature over tropical regions. Improvement is also seen in the prediction of extreme rainfall events. The prediction of monsoon onset and track of cyclone Ashobaa with hybrid and 3D var system is discussed.