Understanding Precipitation Bias Sensitivities in E3SM-Multi-scale
Modeling Framework from a Dilution Framework
Abstract
We investigate a set of Energy Exascale Earth System Model Multi-scale
Modeling Framework (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 ITCZ rainfall and too
little over the Amazon. Systematic MMF improvements include more
on-equatorial rainfall across the Warm Pool. Interesting sensitivities
to 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 1024 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.