Dazhi Xi, Ning Lin, Renzhi Jing, Patrick Harr, Michael Oppenheimer
{"title":"Uncertainties Inherent from Large-Scale Climate Projections in the Statistical Downscaling Projection of North Atlantic Tropical Cyclone Activity","authors":"Dazhi Xi, Ning Lin, Renzhi Jing, Patrick Harr, Michael Oppenheimer","doi":"10.1175/jcli-d-23-0475.1","DOIUrl":null,"url":null,"abstract":"Abstract North Atlantic tropical cyclone (TC) activity under a high-emission scenario is projected using a statistical synthetic storm model coupled with nine Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models. The ensemble projection shows that the annual frequency of TCs generated in the basin will decrease from 15.91 (1979-2014) to 12.16 (2075-2100), and TC activity will shift poleward and coast-ward. The mean of lifetime maximum intensity will increase from 66.50 knots to 75.04 knots. Large discrepancies in TC frequency and intensity projections are found among the nine CMIP6 climate models. The uncertainty in the projection of wind shear is the leading cause of the discrepancies in the TC climatology projection, dominating the uncertainties in the projection of thermodynamic parameters such as potential intensity and saturation deficit. The uncertainty in the projection of wind shear may be related to the different projections of horizontal gradient of vertically integrated temperature in the climate models, which can be induced by different parameterizations of physical processes including surface process, sea ice, and cloud feedback. Informed by the uncertainty analysis, a surrogate model is developed to provide the first-order estimation of TC activity in climate models based on large-scale environmental features.","PeriodicalId":15472,"journal":{"name":"Journal of Climate","volume":"30 1","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Climate","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/jcli-d-23-0475.1","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract North Atlantic tropical cyclone (TC) activity under a high-emission scenario is projected using a statistical synthetic storm model coupled with nine Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models. The ensemble projection shows that the annual frequency of TCs generated in the basin will decrease from 15.91 (1979-2014) to 12.16 (2075-2100), and TC activity will shift poleward and coast-ward. The mean of lifetime maximum intensity will increase from 66.50 knots to 75.04 knots. Large discrepancies in TC frequency and intensity projections are found among the nine CMIP6 climate models. The uncertainty in the projection of wind shear is the leading cause of the discrepancies in the TC climatology projection, dominating the uncertainties in the projection of thermodynamic parameters such as potential intensity and saturation deficit. The uncertainty in the projection of wind shear may be related to the different projections of horizontal gradient of vertically integrated temperature in the climate models, which can be induced by different parameterizations of physical processes including surface process, sea ice, and cloud feedback. Informed by the uncertainty analysis, a surrogate model is developed to provide the first-order estimation of TC activity in climate models based on large-scale environmental features.
期刊介绍:
The Journal of Climate (JCLI) (ISSN: 0894-8755; eISSN: 1520-0442) publishes research that advances basic understanding of the dynamics and physics of the climate system on large spatial scales, including variability of the atmosphere, oceans, land surface, and cryosphere; past, present, and projected future changes in the climate system; and climate simulation and prediction.