了解云模拟从 E3SM 版本 1 到版本 2 的变化

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, J. Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, Meng Zhang
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引用次数: 1

摘要

摘要本研究记录了能源超大规模地球系统模式(ESM)第 2 版(ESMv2)模拟的云层,并试图了解与 E3SMv1 相比,导致云层模型行为变化的原因。具体做法是分析使用 E3SMv1 和 v2 进行的 165 年历史模拟中最近 30 年(1985-2014 年)的数据,并进行四项敏感性测试,以隔离模型参数选择变化在湍流、浅对流和云宏观物理参数化(云层统一二项式,CLUBB)、微观物理参数化(MG2)和深对流方案(ZM)方面的影响,以及模型物理在对流触发方面的变化。结果表明,ESMv2 显著改善了亚热带沿岸层积云和光学深度大于 3.6 的层积云向积云过渡区云的模拟,其中短波云辐射效应(SWCRE)也得到了改善,并改善了南大洋(SO)的模拟,但其他热带和亚热带海洋低云的模拟总体上略有下降。E3SMv1 在这些地区表现较好的部分原因是其模拟的光学稀薄低云和中间低云之间的误差补偿,而 E3SMv2 实际上改进了对光学中间低云的模拟。灵敏度测试表明,低云的变化主要是由于 CLUBB 的调整造成的。ZM 调整的影响主要是光学中间云和厚高云,有助于改善 SWCRE 和长波云辐射效应 (LWCRE)。MG2 调整和新的对流触发主要对高纬度和 SO 有影响。与 CLUBB 调整和 ZM 调整相比,它们对云的影响相对较小。本研究通过利用多个数据集和云反馈模式相互比较项目(CFMIP)观测模拟器包(COSP)诊断工具以及灵敏度测试,对 E3SMv2 模拟的云层有了更深入的了解。加深了解将有利于未来 E3SM 的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding changes in cloud simulations from E3SM version 1 to version 2
Abstract. This study documents clouds simulated by the Energy Exascale Earth System Model (E3SM) version 2 (E3SMv2) and attempts to understand what causes the model behavior change in clouds relative to E3SMv1. This is done by analyzing the last 30-year (1985–2014) data from the 165-year historical simulations using E3SMv1 and v2 and four sensitivity tests to isolate the impact of changes in model parameter choices in its turbulence, shallow convection, and cloud macrophysics parameterization (Cloud Layers Unified By Binormals, CLUBB); microphysical parameterization (MG2); and deep-convection scheme (ZM), as well as model physics changes in convective triggering. It is shown that E3SMv2 significantly improves the simulation of subtropical coastal stratocumulus clouds and clouds with optical depth larger than 3.6 over the stratocumulus-to-cumulus transition regimes, where the shortwave cloud radiative effect (SWCRE) is also improved, and the Southern Ocean (SO) while seeing an overall slight degradation in low clouds over other tropical and subtropical oceans. The better performance in E3SMv1 over those regions is partially due to error compensation between its simulated optically thin and intermediate low clouds for which E3SMv2 actually improves simulation of optically intermediate low clouds. Sensitivity tests indicate that the changes in low clouds are primarily due to the tuning done in CLUBB. The impact of the ZM tuning is mainly on optically intermediate and thick high clouds, contributing to an improved SWCRE and longwave cloud radiative effect (LWCRE). The impact of the MG2 tuning and the new convective trigger is primarily on the high latitudes and the SO. They have a relatively smaller impact on clouds than CLUBB tuning and ZM tuning do. This study offers additional insights into clouds simulated in E3SMv2 by utilizing multiple data sets and the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) diagnostic tool as well as sensitivity tests. The improved understanding will benefit future E3SM developments.
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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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