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The impact of resolving sub-kilometer processes on aerosol-cloud interactions in global model simulations
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  • Christopher Ryutaro Terai,
  • Michael S. Pritchard,
  • Peter N. Blossey,
  • Christopher S. Bretherton
Christopher Ryutaro Terai
University of California - Irvine

Corresponding Author:crterai@gmail.com

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Michael S. Pritchard
University of California, Irvine
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Peter N. Blossey
University of Washington
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Christopher S. Bretherton
University of Washington
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Sub-kilometer processes are critical to the physics of aerosol-cloud interaction but have been dependent on parameterizations in global model simulations. We thus report the strength of aerosol-cloud interaction in the Ultra-Parameterized Community Atmosphere Model (UPCAM), a multiscale climate model that uses coarse exterior resolution to embed explicit cloud resolving models with enough resolution (250-m horizontal, 20-m vertical) to quasi-resolve sub-kilometer eddies. To investigate the impact on aerosol-cloud interactions, UPCAMâ\euro™s simulations are compared to a coarser multi-scale model with 3 km horizontal resolution. UPCAM produces cloud droplet number concentrations ($N_\mathrm{d}$) and cloud liquid water path (LWP) values that are higher than the coarser model but equally plausible compared to observations. Our analysis focuses on the Northern Hemisphere midlatitude oceans, where historical aerosol increases have been largest. We find similarities in the overall radiative forcing from aerosol-cloud interactions in the two models, but this belies fundamental underlying differences. The radiative forcing from increases in LWP is weaker in UPCAM, whereas the forcing from increases in $N_\mathrm{d}$ is larger. Surprisingly, the weaker LWP increase is not due to a weaker increase in LWP in raining clouds, but a combination of weaker increase in LWP in non-raining clouds and a smaller fraction of raining clouds in UPCAM. The implication is that as global modeling moves towards finer than storm-resolving grids, nuanced model validation of ACI statistics conditioned on the existence of precipitation and good observational constraints on the baseline probability of precipitation will become key for tighter constraints and better conceptual understanding.