Data from: Insensitivity of the cloud response to surface warming under radical changes to boundary layer turbulence and cloud microphysics: results from the ultraparameterized CAM

This data set contains the simulation outputs used in the study summarized below: We study the cloud response to a +4K surface warming in a new multiscale climate model that uses enough interior resolution to begin explicitly resolving boundary layer turbulence (i.e., ultraparameterization or UP). UP's predictions are compared against those from standard superparameterization (SP). The mean cloud radiative effect feedback turns out to be remarkably neutral across all of our simulations, despite some radical changes in both cloud microphysical parameter settings and cloud‐resolving model grid resolution. The overall low cloud response to warming is a positive low cloud feedback over land, a negative feedback (driven by cloud optical depth increase) at high latitudes, and weak feedback over the low‐latitude oceans. The most distinct effects of UP result from tuning decisions impacting high‐latitude cloud feedback. UP's microphysics is tuned to optimize the model present‐day, top‐of‐atmosphere radiation fluxes against CERES observations, by lowering the cloud ice‐liquid phase shift temperature ramp, adjusting the ice/liquid autoconversion rate, and increasing the ice fall speed. This reduces high‐latitude low cloud amounts and damps the optical depth feedback at high latitudes, leading to a slightly more positive global cloud feedback compared to SP. A sensitivity test that isolates these microphysical impacts from UP's grid resolution confirms that the microphysical settings are mostly responsible for the differences between SP and UP cloud feedback.This data set contains simulation data from "Insensitivity of the cloud response to surface warming under radical changes to boundary layer turbulence and cloud microphysics: results from the ultraparameterized CAM." All instructions and information are provided in the attached Readme.txt file. Please download the latest version for the full data set. Funding provided by: U.S. Department of EnergyCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000015Award Number: DE-SC001254