Estimating parameters of the nonlinear cloud and rain equation from a large-eddy simulation

PHYSICA D-NONLINEAR PHENOMENA

卷:410

Article

Lunderman, Spencer¹  Morzfeld, Matthias²  Glassmeier, Franziska^3,4,5  Feingold, Graham⁴ 

[1] Univ Arizona, Dept Math, Tucson, AZ 85721 USA

[2] Univ Calif San Diego, Inst Geophys & Planetary Phys, Scripps Inst Oceanog, San Diego, CA 92103 USA

[3] Wageningen Univ, Dept Environm Sci, Wageningen, Netherlands

[4] NOAA, Chem Sci Lab Earth Syst Res Labs, Silver Spring, MD USA

[5] Delft Univ Technol, Fac Civil Engn & Geosci, Dept Geosci & Remote Sensing, Delft, Netherlands

关键词: Predator-prey dynamics;    Large-eddy simulation;    Stratocumulus clouds;    Bayesian inversion;    Markov chain Monte Carlo;   

DOI  :  10.1016/j.physd.2020.132500

来源: Elsevier

【 摘 要 】

Predator-prey dynamics have been suggested as simplified models of stratocumulus clouds, with rain acting as a predator of the clouds. We describe a mathematical and computational framework for estimating the parameters of a simplified model from a large eddy simulation (LES). In our method, we extract cycles of cloud growth and decay from the LES and then search for parameters of the simplified model that lead to similar cycles. We implement our method via Markov chain Monte Carlo. Required error models are constructed based on variations of the LES cloud cycles. This computational framework allows us to test the robustness of our overall approach and various assumptions, which is essential for the simplified model to be useful. Our main conclusion is that it is indeed possible to calibrate a predator-prey model so that it becomes a reliable, robust, but simplified representation of selected aspects of a LES. In the future, such models may then be used as a quantitative tool for investigating important questions in cloud microphysics. (C) 2020 Elsevier B.V. All rights reserved.

【 授权许可】

Free