{"title":"Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system","authors":"Ting Liu, Wenxiu Zhong","doi":"10.1007/s13131-023-2239-x","DOIUrl":null,"url":null,"abstract":"<p>Upper ocean heat content (OHC) has been widely recognized as a crucial precursor to high-impact climate variability, especially for that being indispensable to the long-term memory of the ocean. Assessing the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate forecasts. Recently developed retrospective forecast experiments, based on a Community Earth System Model ensemble prediction system, offer a great opportunity to comprehensively explore OHC predictability. Our results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction extends. The spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill, indicating that the persistence of OHC serves as the primary predictive signal for its predictability. The decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean, particularly within tropical regions. Additionally, notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC variability. The potential predictability of OHC generally surpasses the actual prediction skill at all lead times, highlighting significant room for improvement in current OHC predictions, especially for the North Indian Ocean and the Atlantic Ocean. Achieving such improvements necessitates a collaborative effort to enhance the quality of ocean observations, develop effective data assimilation methods, and reduce model bias.</p>","PeriodicalId":6922,"journal":{"name":"Acta Oceanologica Sinica","volume":"51 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Oceanologica Sinica","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s13131-023-2239-x","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
Upper ocean heat content (OHC) has been widely recognized as a crucial precursor to high-impact climate variability, especially for that being indispensable to the long-term memory of the ocean. Assessing the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate forecasts. Recently developed retrospective forecast experiments, based on a Community Earth System Model ensemble prediction system, offer a great opportunity to comprehensively explore OHC predictability. Our results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction extends. The spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill, indicating that the persistence of OHC serves as the primary predictive signal for its predictability. The decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean, particularly within tropical regions. Additionally, notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC variability. The potential predictability of OHC generally surpasses the actual prediction skill at all lead times, highlighting significant room for improvement in current OHC predictions, especially for the North Indian Ocean and the Atlantic Ocean. Achieving such improvements necessitates a collaborative effort to enhance the quality of ocean observations, develop effective data assimilation methods, and reduce model bias.
期刊介绍:
Founded in 1982, Acta Oceanologica Sinica is the official bi-monthly journal of the Chinese Society of Oceanography. It seeks to provide a forum for research papers in the field of oceanography from all over the world. In working to advance scholarly communication it has made the fast publication of high-quality research papers within this field its primary goal.
The journal encourages submissions from all branches of oceanography, including marine physics, marine chemistry, marine geology, marine biology, marine hydrology, marine meteorology, ocean engineering, marine remote sensing and marine environment sciences.
It publishes original research papers, review articles as well as research notes covering the whole spectrum of oceanography. Special issues emanating from related conferences and meetings are also considered. All papers are subject to peer review and are published online at SpringerLink.