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

Spencer Lunderman, Matthias Morzfeld, Franziska Glassmeier, Graham Feingold

Research output: Contribution to journalArticleScientificpeer-review

Abstract

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.

Original languageEnglish
Article number132500
Number of pages13
JournalPhysica D: Nonlinear Phenomena
Volume410
DOIs
Publication statusPublished - 2020

Keywords

  • Bayesian inversion
  • Large-eddy simulation
  • Markov chain Monte Carlo
  • Predator–prey dynamics
  • Stratocumulus clouds

Fingerprint Dive into the research topics of 'Estimating parameters of the nonlinear cloud and rain equation from a large-eddy simulation'. Together they form a unique fingerprint.

Cite this