#A03 Parametric sensitivity and optimization in ACME-V1 atmosphere

Abstract

The ACME V1 (NE30_L72) atmosphere model has included many new features in the physics parameterizations. Complex nonlinear interactions between those new features create a big challenge for understanding the model behaviors and tuning. Using the one-at-a-time method, we often encounter cases where the tuning of one parameter leads to an offset of the accomplishment from the tuning of another parameter, or the improvement in one target variable leads to degradation of model fidelity in another target variable. The PPE simulations provide an opportunity to evaluate and optimize model fidelity in a comprehensive and systematic manner.

In this set of simulations, 18 parameters in various physical processes were perturbed simultaneously using the Latin Hypercube sampling method. This poster presents the results from the analysis that aimed at quantifying the model response to the most sensitive parameters and estimating the maximum likelihood of model parameter space for a number of important fidelity metrics. We calculated the posterior probabilities of all 18 parameters and identified the optimal parameter sets with multiple interest objectives based on short ensemble simulation results and corresponded global mean observations. Results from this analysis provide a more complete picture of the model behavior and improve our understanding of model physics associated with model parameters and their interactions.