Rainbows and climate change: a tutorial on climate model diagnostics and parameterization

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Geoscientific Model Development Pub Date : 2023-09-01 DOI:10.5194/gmd-16-4937-2023
A. Gettelman
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Abstract

Abstract. Earth system models (ESMs) must represent processes below the grid scale of a model using representations (parameterizations) of physical and chemical processes. As a tutorial exercise to understand diagnostics and parameterization, this work presents a representation of rainbows for an ESM: the Community Earth System Model version 2 (CESM2). Using the “state” of the model, basic physical laws, and some assumptions, we generate a representation of this unique optical phenomenon as a diagnostic output. Rainbow occurrence and its possible changes are related to cloud occurrence and rain formation, which are critical uncertainties for climate change prediction. The work highlights issues which are typical of many diagnostic parameterizations such as assumptions, uncertain parameters, and the difficulty of evaluation against uncertain observations. Results agree qualitatively with limited available global “observations” of rainbows. Rainbows are seen in expected locations in the subtropics over the ocean where broken clouds and frequent precipitation occur. The diurnal peak is in the morning over ocean and in the evening over land. The representation of rainbows is found to be quantitatively sensitive to the assumed amount of cloudiness and the amount of stratiform rain. Rainbows are projected to have decreased, mostly in the Northern Hemisphere, due to aerosol pollution effects increasing cloud coverage since 1850. In the future, continued climate change is projected to decrease cloud cover, associated with a positive cloud feedback. As a result the rainbow diagnostic projects that rainbows will increase in the future, with the largest changes at midlatitudes. The diagnostic may be useful for assessing cloud parameterizations and is an exercise in how to build and test parameterizations of atmospheric phenomena.
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彩虹与气候变化:气候模型诊断和参数化教程
摘要地球系统模型(ESM)必须使用物理和化学过程的表示(参数化)来表示模型网格尺度以下的过程。作为理解诊断和参数化的教程练习,本工作介绍了ESM的彩虹表示:社区地球系统模型版本2(CESM2)。利用模型的“状态”、基本物理定律和一些假设,我们生成了这种独特光学现象的表示,作为诊断输出。彩虹的出现及其可能的变化与云的出现和降雨的形成有关,这是气候变化预测的关键不确定性。这项工作强调了许多诊断参数化的典型问题,如假设、不确定参数和针对不确定观测进行评估的困难。结果与有限的全球彩虹“观测”结果一致。在海洋上空的亚热带地区,预计会出现彩虹,那里云层破碎,降水频繁。白天的高峰出现在海洋上空的早晨和陆地上空的傍晚。彩虹的呈现在数量上对假设的云量和层雨的数量是敏感的。自1850年以来,由于气溶胶污染的影响,云层覆盖率不断增加,预计降雨量将减少,主要发生在北半球。未来,持续的气候变化预计将减少云层覆盖,这与积极的云层反馈有关。因此,彩虹诊断预测未来彩虹将增加,其中中纬度的变化最大。该诊断可能有助于评估云参数化,也是如何构建和测试大气现象参数化的练习。
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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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