A Framework to Decompose Wind-Driven Biases in Climate Models Applied to CCSM/CESM in the Eastern Pacific

Author:

Larson Sarah M.1,Kirtman Ben P.2,Vimont Daniel J.1

Affiliation:

1. Atmospheric and Oceanic Sciences Department, and Nelson Institute Center for Climatic Research, University of Wisconsin–Madison, Madison, Wisconsin

2. Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

Abstract

Annual cycle biases in climate models are suspected to be largely wind driven along the equator, with winds first driving SST changes that then influence the overlying atmospheric circulation. This study utilizes an experimental approach to test the hypothesis that seasonally varying climatological wind stress directly contributes to the SST and ITCZ biases in the eastern equatorial Pacific. Results show that removing the wind stress annual cycle from the ocean forcing, without constraining the atmosphere and ocean dynamics or buoyancy coupling in the NCAR CCSM4/CESM1.2.0 models, results in a remarkable reduction in the SST annual cycle and springtime ITCZ biases. Improvements in the SST occur primarily because wind-driven errors in the variability of horizontal temperature advection are damped. The ITCZ problem is closely tied to biases in the wind-driven near-equatorial SST. Additional model experiments and analyses reveal that the contributions from zonal and meridional wind stress to the biases are locally forced within 10°S–10°N and additive, suggesting that the biases are driven by independent processes. The zonal and meridional components drive different aspects of the SST annual cycle bias and contribute to the springtime ITCZ bias in different zonal locations. Both the atmosphere and ocean components of the model, separately, are shown to produce unfavorable ocean surface conditions for the simulation of a realistic springtime ITCZ, deeming this a coupled problem. Results show that wind stress may act as a pathway for process-based errors in climate models to directly drive SST and ITCZ biases.

Funder

National Science Foundation

Publisher

American Meteorological Society

Subject

Atmospheric Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3