An Emulator of Stratocumulus Cloud Response to Two Cloud-Controlling Factors Accounting for Internal Variability

IF 4.4 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Rachel W. N. Sansom, Ken S. Carslaw, Jill S. Johnson, Lindsay Lee
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引用次数: 0

Abstract

Large uncertainties persist in modeling shallow, low clouds because of many interacting nonlinear processes and multiple cloud-controlling environmental factors. In addition, sharp changes in behavior occur when environmental thresholds are met. Model studies that follow a traditional approach of exploring the effects of factors “one-at-a-time” are unable to capture interactions between factors. We simulate a stratocumulus cloud based on the Second Dynamics and Chemistry of Marine Stratocumulus field study using a large-eddy simulation model coupled with a two-moment cloud microphysics scheme. The simulations are used to train a Gaussian process emulator, which we then use to visualize the relationships between two cloud-controlling factors and domain-averaged cloud properties. Only 29 model simulations were required to train the emulators, which then predicted cloud properties at thousands of new combinations of the two factors. Emulator response surfaces of cloud liquid water path and cloud fraction show two behavioral regimes, one of thin and patchy yet steady stratocumulus and one of thick, growing stratocumulus with cloud fraction near 1. Internal variability (initial-condition uncertainty) creates unrealistic “bumpy” response surfaces. However, we show that the variability causing the bumpiness can be characterized in an emulator “nugget term” that is adjusted to match the distribution of a small number of initial-condition ensemble simulations at various points on the surface, thereby allowing a smoother, deterministic response surface to be constructed. Accounting for variability allows the transition between regimes, and the joint interactions of parameters, to be visualized in a more deterministic way that has not been done before.

Abstract Image

层积云对两种云控制因素反应的模拟器,考虑内部变异性
由于许多相互作用的非线性过程和多种云控制环境因素,浅层低云的建模仍然存在很大的不确定性。此外,当达到环境阈值时,行为会发生急剧变化。按照 "一次性 "探索各因素影响的传统方法进行的模型研究无法捕捉各因素之间的相互作用。我们在第二次海洋层积云动力学和化学实地研究的基础上,利用大涡流模拟模型和双瞬云微物理方案对层积云进行了模拟。模拟结果用于训练高斯过程模拟器,然后我们用它来直观显示两个云控制因子与域平均云属性之间的关系。训练模拟器只需要 29 次模型模拟,然后模拟器就能预测这两个因素的数千种新组合下的云特性。云液态水路径和云分数的模拟器响应面显示了两种行为模式,一种是薄而分散但稳定的层积云,另一种是厚而不断扩大的层积云,云分数接近 1。内部变率(初始条件的不确定性)造成了不切实际的 "凹凸不平 "的响应表面。不过,我们的研究表明,造成凹凸不平的变异性可以用仿真器的 "金块项 "来描述,通过调整仿真器的 "金块项",使其与表面上各点的少量初始条件集合模拟分布相匹配,从而构建出更平滑、更确定的响应表面。考虑到变异性,就能以一种更加确定的方式直观地显示不同状态之间的过渡以及参数之间的共同作用,这在以前是从未有过的。
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来源期刊
Journal of Advances in Modeling Earth Systems
Journal of Advances in Modeling Earth Systems METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
11.40
自引率
11.80%
发文量
241
审稿时长
>12 weeks
期刊介绍: The Journal of Advances in Modeling Earth Systems (JAMES) is committed to advancing the science of Earth systems modeling by offering high-quality scientific research through online availability and open access licensing. JAMES invites authors and readers from the international Earth systems modeling community. Open access. Articles are available free of charge for everyone with Internet access to view and download. Formal peer review. Supplemental material, such as code samples, images, and visualizations, is published at no additional charge. No additional charge for color figures. Modest page charges to cover production costs. Articles published in high-quality full text PDF, HTML, and XML. Internal and external reference linking, DOI registration, and forward linking via CrossRef.
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