Analysis and plotting scripts for paper by R.D. Russotto and T.P. Ackerman in Atmos. Chem. Phys. special issue on the Geoengineering Model Intercomparison Project. (new version: adds "shellKernelCalculations.py", which had been accidentally omitted from the upload) DOI for paper: 10.5194/acp-2018-345 Python code was written by Rick Russotto. The APRP.py module was based in part on Matlab scripts provided by Yen-Ting Hwang. The vertical regridding code was based in part on the "convert_sigma_to_pres" algorithm by Dan Vimont, available at http://www.aos.wisc.edu/~dvimont/matlab/. If you use any of this code, please acknowledge where it came from. Python scripts were run using Python 2.7.9. Versions of packages used: -Matplotlib 1.5.1 -NumPy 1.8.2 -NetCDF4 1.1.0 Which scripts make which figures in the paper: Figure 1: isG1ReductionCorrelatedWithECS.py Figure 2: taZonalMeanProfiles.py Figure 3: husZonalMeanProfiles.py Figure 4: cloudFractionZonalMeanProfiles.py Figure 5: multiModelMeanCloudsV2.py Figure 6: multiModelMeanPredictorsV2.py Figure 7: multiModelMeanAPRP.py Figures 8, S9, S10, S11: analyzeKernelResults.py Figures 9, S12: mapLWCRE.py Figures 10, 11: barGraphsV2.py Figures S1, S2, S3: cloudFractionMaps.py Figures S4, S5: lowCloudPredictorMaps.py Figures S6, S7, S8: scriptUsingAPRPonGeoMIP.py Figure S13: rapidVsFeedbackAPRP.py Other scripts and modules that the above scripts depend on: APRP.py calculateClimatologiesForRadiativeKernels.py correctCESM_rlut.py find_rlut_correction.py geomipFunctions.py saveModelLatsLons.py shellKernelCalculations.py zonalMeanCloudFraction_CSIRO.py zonalMeanCloudFraction_HadGEM2-ES.py A standalone version of the APRP code can be found at https://github.com/rdrussotto/pyAPRP, with further documentation.