Cloud and precipitation processes act to modulate feedback and forcing in the extratropics (Gettelman and Sherwood 2016). We will investigate whether a moisture convergence-mediated linkage between aerosol-cloud adjustments and cloud feedback emerges across different versions of the Energy Exascale Earth System Model (E3SM). We will do this across different E3SM versions as well as intermediate development versions and tailored sensitivity tests in E3SMv3. This investigation will yield insight into E3SM behavior. It will also provide insight across Earth System Models (ESMs) with two-moment microphysics that can link cloud feedback and aerosol-cloud adjustment processes.

Observational evaluation of ESM behavior plays an important role in understanding the strength of any linkage revealed through the examination of ESM behavior. We will contrast E3SM simulations with observations from US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) sites, synoptic variability, and decadal trends. We will leverage machine-learning techniques to link specific parameterized processes and observational diagnostics to climate projections in E3SM. We will leverage the E3SM single-column model (SCM) and the EMC2 instrument simulator (Silber et al. 2022) to compare ARM observations to E3SM. The synoptic state will be examined using cyclone compositing to isolate cloud and precipitation processes from meteorological variability.

Fusing observations with ESM simulations allows the evaluation of how causality flows from warming and anthropogenic aerosol to clouds and precipitation. Based on this evaluation, we can understand how microphysical processes affect observed climate-scale variability and how this affects climate projection by ESMs.  We have a limited number of E3SM versions with which we can evaluate these linkages. We will build on these emergent relationships by (i) conducting a set of tailored parameter perturbation experiments in E3SMv3 and (ii) using machine learning emulation to fill in non-linear relationships between diagnostics across these scales and the climate-scale behavior of E3SM.

• Gettelman, A., and S. C. Sherwood, 2016: Processes Responsible for Cloud Feedback. Current Climate Change Reports, 1–11, https://doi.org/10.1007/s40641-016-0052-8 
• Silber, I., R. C. Jackson, A. M. Fridlind, A. S. Ackerman, S. Collis, J. Verlinde, and J. Ding, 2022: The Earth Model Column Collaboratory (EMC2) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models. Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022