Understanding Precipitation Bias Sensitivities in E3SM‐Multi‐Scale Modeling Framework From a Dilution Framework
2023
Nana Liu | Michael S. Pritchard | Andrea M. Jenney | Walter M. Hannah
Abstract We investigate a set of Energy Exascale Earth System Model Multi‐scale modeling framework (MMF) (E3SM‐MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud‐resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on‐equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time‐mean precipitation pattern over the tropics. The 2D E3SM‐MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture‐precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.
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