Assessment of Warm and Dry Bias over ARM SGP Site in E3SMv2 and E3SM-MMF

Author:

Lee Jungmin M.1ORCID,Tao Cheng1,Hannah Walter M.1,Xie Shaocheng1,Bader David C.1

Affiliation:

1. a Lawrence Livermore National Laboratory, Livermore, California

Abstract

Abstract Many climate models exhibit a dry and warm bias over the central United States during the summer months, including the Energy Exascale Earth System Model (E3SM) and its Multiscale Modeling Framework (MMF) configuration. Understanding the causes of this bias is important to shine a light on this common model error and reduce the uncertainty in future projections. In this study, we use E3SMv2 and E3SM-MMF to assess how parameterized and resolved convection affect temperature and precipitation biases over the Southern Great Plains site of the Atmospheric Radiation Measurement program. Both configurations overestimate near-surface temperature and underestimate precipitation at the ARM SGP site. The bias is associated with a lack of low-level clouds during days without precipitation and too much incoming solar radiation causing the surface to warm. Low-level cloud fraction in E3SM-MMF during the nonprecipitating days is lower in comparison to E3SMv2 and observation, consistent with the larger warm bias. We also find that the underestimated precipitation can be characterized as “too frequent, too weak” in E3SMv2 and “too rare, too intense” in E3SM-MMF. These deficiencies conspire to sustain the warm and dry bias over the central United States.

Funder

Office of Science

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference38 articles.

1. Chen, X., and S. Xie, 1996: ARM Best Estimate data products. ARM Data Center, accessed 13 December 2022, https://doi.org/10.5439/1333228.

2. Role of clouds and land-atmosphere coupling in midlatitude continental summer warm biases and climate change amplification in CMIP5 simulations;Cheruy, F.,2014

3. An improved double-Gaussian closure for the subgrid vertical velocity probability distribution function;Fitch, A. C.,2019

4. The 2015 Plains Elevated Convection at Night field project;Geerts, B.,2017

5. Advanced two-moment bulk microphysics for global models. Part I: Off-line tests and comparison with other schemes;Gettelman, A.,2015

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