R. M. Vil’fand, S. V. Emelina, V. A. Tischenko, M. A. Tolstykh, V. M. Khan
{"title":"Statistical Correction of the SL-AV Model Long-term Forecasts of Surface Air Temperature for the Territory of Northern Eurasia","authors":"R. M. Vil’fand, S. V. Emelina, V. A. Tischenko, M. A. Tolstykh, V. M. Khan","doi":"10.3103/s1068373924050017","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>For the territory of Northern Eurasia, a scheme for the statistical correction of surface air temperature forecasts has been developed for periods of 1–4 months on the basis of the SL-AV model using the MOS concept. For statistical correction of operational temperature forecasts, the regression parameters and EOF expansion coefficients obtained by cross-validation on historical forecasts were used. Due to the internal relationships of the model output data, the proposed scheme allows improving the skill of surface characteristic forecasts. A significant improvement in the skill of deterministic air temperature forecasts by using statistical correction is manifested in transition seasons. The scheme of statistical correction is constantly evolving. Further development of the statistical correction technology involves the use of neural networks and forecast indices of atmospheric circulation.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"61 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Meteorology and Hydrology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.3103/s1068373924050017","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
For the territory of Northern Eurasia, a scheme for the statistical correction of surface air temperature forecasts has been developed for periods of 1–4 months on the basis of the SL-AV model using the MOS concept. For statistical correction of operational temperature forecasts, the regression parameters and EOF expansion coefficients obtained by cross-validation on historical forecasts were used. Due to the internal relationships of the model output data, the proposed scheme allows improving the skill of surface characteristic forecasts. A significant improvement in the skill of deterministic air temperature forecasts by using statistical correction is manifested in transition seasons. The scheme of statistical correction is constantly evolving. Further development of the statistical correction technology involves the use of neural networks and forecast indices of atmospheric circulation.
期刊介绍：
Russian Meteorology and Hydrology is a peer reviewed journal that covers topical issues of hydrometeorological science and practice: methods of forecasting weather and hydrological phenomena, climate monitoring issues, environmental pollution, space hydrometeorology, agrometeorology.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
