Qiuying Fu , Zhenya Song , Zhongkai Bo , Ying Bao , Chan Joo Jang , Yajuan Song
{"title":"Assessment of the FIO-CPS v2.0 in predicting 2-meter air temperature over China","authors":"Qiuying Fu , Zhenya Song , Zhongkai Bo , Ying Bao , Chan Joo Jang , Yajuan Song","doi":"10.1016/j.dynatmoce.2023.101391","DOIUrl":null,"url":null,"abstract":"<div><p>The climate prediction<span> system is an essential tool for predicting climatological state and variability. Systematic evaluation of the output is critical for assessing the prediction performance and making improvement. In this study, we evaluate the prediction capability of the First Institute of Oceanography-Climate Prediction System version 2.0 (FIO-CPS v2.0), a short-term climate prediction system, on the 2-meter air temperature over China using five criteria, namely prediction score (PS), prediction consistency (PC), correlation coefficient<span> (CC), root mean square error (RMSE), and distance between indices of simulation and observation (DISO). The results showed that FIO-CPS v2.0 has higher accuracy in summer, and its performance varies with different lead times depending on the evaluation criteria used. Higher overall prediction skill was mostly found in the northeastern region during July and September, and the southeastern coastal region during June–September. Our findings provide insights into the prediction ability of the FIO-CPS v2.0 on air temperature and may help to facilitate its development.</span></span></p></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"103 ","pages":"Article 101391"},"PeriodicalIF":1.9000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dynamics of Atmospheres and Oceans","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377026523000428","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
The climate prediction system is an essential tool for predicting climatological state and variability. Systematic evaluation of the output is critical for assessing the prediction performance and making improvement. In this study, we evaluate the prediction capability of the First Institute of Oceanography-Climate Prediction System version 2.0 (FIO-CPS v2.0), a short-term climate prediction system, on the 2-meter air temperature over China using five criteria, namely prediction score (PS), prediction consistency (PC), correlation coefficient (CC), root mean square error (RMSE), and distance between indices of simulation and observation (DISO). The results showed that FIO-CPS v2.0 has higher accuracy in summer, and its performance varies with different lead times depending on the evaluation criteria used. Higher overall prediction skill was mostly found in the northeastern region during July and September, and the southeastern coastal region during June–September. Our findings provide insights into the prediction ability of the FIO-CPS v2.0 on air temperature and may help to facilitate its development.
期刊介绍:
Dynamics of Atmospheres and Oceans is an international journal for research related to the dynamical and physical processes governing atmospheres, oceans and climate.
Authors are invited to submit articles, short contributions or scholarly reviews in the following areas:
•Dynamic meteorology
•Physical oceanography
•Geophysical fluid dynamics
•Climate variability and climate change
•Atmosphere-ocean-biosphere-cryosphere interactions
•Prediction and predictability
•Scale interactions
Papers of theoretical, computational, experimental and observational investigations are invited, particularly those that explore the fundamental nature - or bring together the interdisciplinary and multidisciplinary aspects - of dynamical and physical processes at all scales. Papers that explore air-sea interactions and the coupling between atmospheres, oceans, and other components of the climate system are particularly welcome.