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{"Abstract":["This folder contains the code needed to generate the plots and data for "Characteristics of a Multi-model Ensemble of Mock-Walker Simulations", a manuscript submitted to the Journal of Advances in Modeling Earth Systems (JAMES).\n\n \n\nAll code except for Figure 17 is run in Python.\n\n \n\nFor all codes, the variable "codeDirectory" should be set to the file location of the codes to run properly.  This is primarily to properly import code from "Utilities/"\n\n \n\nGeneral programs useful for handling RCEMIP data are given in \n\n"Utilities/".\n\n-Utilities/metFormulas.py: various meteorological formulas\n\n-Utilities/generalUtilities.py and Utilities/dsTools.py: basic processing tools\n\n-Utilities/extract*.py: imports RCEMIP data from directories specified in generalUtilities.py\n\n \n\nOrganization metric data is calculated by the codes in METRICS/A-*/.\n\nThe metric files are saved in METRICS/nc-mw/.  The current metric importation is designed to require the files in this folder rather than importing data directly from Utilities/aggRecalc/aggregation_metrics_mw.csv as several codes require timeseries of the values of the metrics.\n\n____________________________________________________________\n\n \n\nFigure Generation\n\nFigure 1: DemonstrateSST/demonstrateSST.py\n\n    -Saved as DemonstrateSST/demonstrateSST.png.\n\n \n\nFigure 2, 3, S1, S2: images/rlut_pr_mw_multimodel.py, function createImages().\n\n    -Stored in images/CRM/ and images/GCM/.\n\n \n\nFigure 4, S3-S6 [fourier, hovmoller]: ClassifyScenes/hovmollerWithClassifications.py\n\n    -Saved in ClassifyScenes/hovmollerWithPie/.\n\n    -4: 300dT1p25-crh-slice-sametime.pdf\n\n    -S3-S6: -crh-slice-sametime.pdf\n\n    A version of this code that omits the pie charts and does not require [fourier] is hovmoller/hovmoller.py.\n\n \n\nFigure 5, 8, 12, S7-S10: Metrics/multiplot.py.  \n\n    Files are saved as Metrics/Metrics-.pdf\n\n    -5 and S7-S10: SST is one of the five Simulations\n\n    -8: SST is T\n\n    -12: SST is DT\n\n \n\nFigure 6: ClassifyScenes/hovmollerClassFourierDiscretePoster.py.  \n\n    -Saved as ClassifyScenes/classFourierDemo/Plots/mw/SAM-CRM/SAM-CRM-300dT1p25-crh.png\n\n \n\nFigure 7, S11 [fourier]: ClassifyScenes/classDiscreteVsMetrics.py.  \n\n    -Saved as ClassifyScenes/metricViolinPlot/CRM/CRM_all_Lorg.pdf and ./CRM_all_Iorg.pdf.\n\n \n\nFigure 9: [fourier]: ClassifyScenes/plotPercentilesByCategory.py, method createFrequencyPieCharts().\n\n    -Saved as ClassifyScenes/pieCharts/CRM.pdf.\n\n \n\nFigure 10: [fourierContinuous]: ClassifyScenes/plotPercentilesByCategory.py, method createVarianceBarChartsPoster().\n\n    -Saved as ClassifyScenes/pieCharts/Bar-CRM-Variance.pdf.\n\n \n\nFigure 11, S12: Metrics/iorgBoxPlots.py, method changeMultiPanel().\n\n    -Saved as Metrics/BoxPlots/change/metricChangeCombined295305shared.pdf and ...all.pdf\n\n \n\nFigure 13, S13, S14: DomainStatistics/BoxPlots.py.\n\n    -13: DomainStatistics/boxplots-domainmean-T.pdf\n\n \n\nFigure 14-16, S15-S18 [isccp]: ISCCP/histograms.py, method plotHistMultimodel()\n\n    -Saved in histPlot/Multimodel-ISCCP-CRM__GCM.png\n\n    -14, S15-S18: is one of the Simulations\n\n    -15: is "changeT"\n\n    -16: is "changeDT"\n\n \n\nFigure 17: A-Statistics/plot_climatesensitivity.m.  \n\n    -This function requires some files from RCEMIP-I which are not included in this repository.\n\n    -Saved as A-Statistics/Fig_lambda_I_II.pdf.  \n\n    -Note: this is a MATLAB code.\n\n \n\nFigure 18 [percentiles]: Percentiles/plotPercentiles.py, method plotPercentileRatioVsAgg().\n\n    -Must be run twice for the two subpanels.\n\n    -Saved in percentilePlots/percentileRatioVsAgg/mw/pr/Ichange/, with the files corresponding to input parameters.\n\n \n\nFigure S19-S22 [percentiles]: Percentiles/plotSpaceTimeCorrelations.py, method correlatePercentileVsAggChanges().\n\n    -Must be run twice for the two subpanels.\n\n    -Saved in percentilePlots/LinearArithmetic/correlatePercentileAggChange/mw/pr/Change/.\n\n \n\nFigure S23 [scaling]: Scaling/BoxPlots.py\n\n    -Saved in scalingPlots/LinearArithmetic/BoxPlots/avgAbove/separateDyn2/mw/coarse15km/shift1/\n\n        File name matches *-def-*-99.9.pdf\n\n    -Generates two needed files, 305dT1p25-295dT1p25/ for S23a and 300dT2p5-300dT0p625/ for S23b\n\n \n\nFigure S24-S27 [scaling]: Scaling/ComponentsVsAgg.py, method componentsVsAggSubplots()\n\n    -Saved at scalingPlots/LinearArithmetic/componentsVsAgg/def-shift1/mw/coarse15km//Combined/\n\n    -S24 and S26: File name contains Ichange\n\n    -S25 and S27: File name contains Lchange\n\n__________________________________________________\n\n \n\n[fourier]: This code requires the discrete Fourier classification.  These classifications are generated by ClassifyScenes/hovmollerClassFourierDiscrete.py and saved in ClassifyScenes/classDS//.\n\n[fourierContinuous]: This code requires the continuous Fourier classification.  This is calculated by ClassifyScenes/hovmollerClassFourierContinuous.py and saved in ClassifyScenes/classDSContinuous//.\n\n[hovmoller]: This code requires hovmoller data.  This data is calculated by running hovmoller/createDatasets.py, with data stored in hovmoller/2D-Timeseries//.\n\n    -These data are created and saved in the 2D-Timeseries/ folder of the repository, which must be loaded in as hovmoller/2D-Timeseries/.\n\n[isccp]: This code requires use of the ISCCP data.\n\n    -CRMs: ISCCP data calculated via the Approximate ISCCP Simulator (Stauffer and Wing 2023) within ISCCP/tau2023.py.\n\nData is saved in two separate folders, isccp_mw/ and isccp_large/, which must be loaded in as ISCCP/isccpData/mw/ and ISCCP/isccpData/large/, respectively.\n\n    -GCMs: ISCCP data was saved by three models during running (CNRM-CM6, E3SM, UKMO-GA7.1)\n\n    From the ISCCP data, histograms are calculated by ISCCP/histograms.py method generateHistograms() (for CRMs) and generateHistogramsGCM() (for GCMs).\n\n        These are saved at ISCCP/hist//.\n\n[percentiles]: This code requires precipitation percentile tables.  These are calculated by Utilities/calcPercentiles.py and saved in  Percentiles/.\n\n[scaling]: This code requires the scaling JSON files in Scaling/scalingJsons.py. This code also requires [percentiles].\n\n    -To create these files, first run Scaling/calculatePercentileProfiles-accumulate-coarsen-parallel.py. This creates the composite profiles in Scaling/scalingParallel/.\n\n    -Then, run Scaling/separateComponentsDecomposeDyn.py to create the JSONs.\n\n    -The scaling profile creation code takes a long time to run and outputs large files.  Scaling/scalingParallel.py is uploaded as a separate folder within the repository to decrease the required file size."]} 

This codebase contains data and code needed to generate plots for O'Donnell, G. L. and A. A. Wing (2024). Precipitation Extremes and their Modulation by Convective Organization in RCEMIP. Journal of Advances in Modeling Earth Systems, 16(11), e2024MS004535. https://doi.org/10.1029/2024MS004535   PrecipExtremesInRCEMIP/: Python code and most derived data, including tables of percentiles of precipitation for each model at numerous spatiotemporal scales scalingProfiles_{domain}/: Profiles of temperature, humidity, and vertical velocity conditioned on extreme precipitation, saved as .nc files   RCEMIP data can be found at http://hdl.handle731.net/21.14101/d4beee8e-6996-453e-bbd1-ff53b6874c0e or at https://swiftbrowser.dkrz.de/public/dkrz_70a517a8-039d-4a1b-a30d-841923f8bc7a/RCEMIP/