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Analysis code for paper: Changes in clouds and thermodynamics under solar geoengineering and implications for required solar reduction

Russotto, Rick

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.

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 
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.

Files (434.1 kB)
Name Size
analyzeKernelResults.py
md5:5f081a7b19add6ab7bcbe5d43635288a
36.0 kB Download
APRP.py
md5:07df5a23dd3b97176a2be4eee09c3b78
26.8 kB Download
barGraphsV2.py
md5:2af1bab571320fbc1ef07751fdb950cf
21.2 kB Download
calculateClimatologiesForRadiativeKernels.py
md5:8580dd1c53994253a5bc1117713abc74
26.4 kB Download
cloudFractionMaps.py
md5:ab6cd5df0d64c4502d270d2930e10539
26.6 kB Download
cloudFractionZonalMeanProfiles.py
md5:aa7c201a1993514b23832fe2f3fe27e7
12.3 kB Download
correctCESM_rlut.py
md5:299e377bff92effb4d828b83135a7f44
2.6 kB Download
find_rlut_correction.py
md5:43d5235759e7e0e13a299e4d6b9e531e
5.4 kB Download
geomipFunctions.py
md5:92dfe6518bc89061c64fe5256dd1b72a
38.0 kB Download
husZonalMeanProfiles.py
md5:8c3f9e230896fcf1e0ff05ee4a5ded00
12.2 kB Download
isG1ReductionCorrelatedWithECS.py
md5:c336087bfa8dc43b0b2ffbf1edafb3f8
13.4 kB Download
LICENSE
md5:d3812ce9b8c6fecc64f5849315f08c05
70 Bytes Download
lowCloudPredictorMaps.py
md5:bac84f5b75a2591163cf7399c05eb9b7
26.0 kB Download
mapLWCRE.py
md5:70a5764bf28bb7de9a497d19db593103
26.1 kB Download
multiModelMeanAPRP.py
md5:20e6499f3dac4d66f9ddb7d35a532677
16.2 kB Download
multiModelMeanCloudsV2.py
md5:90504930edb0c57190d15450560a0869
12.3 kB Download
multiModelMeanPredictorsV2.py
md5:cf67f3ea8ab92140f6ddad613be4141b
8.0 kB Download
rapidVsFeedbackAPRP.py
md5:d67614db5cb42968a0ae8d97ac76d908
21.4 kB Download
saveModelLatsLons.py
md5:1c1a11277ec40641ea5b1308dae9d1e9
2.4 kB Download
scriptUsingAPRPonGeoMIP.py
md5:3f4bfa3b8a70e58f119eae223b91d9dd
46.6 kB Download
taZonalMeanProfiles.py
md5:2c0e80958b9622a4ff9ca2f3f1d2396a
12.4 kB Download
zonalMeanCloudFraction_CSIRO.py
md5:ee6654aabed65efc8290130fba4a22ed
16.7 kB Download
zonalMeanCloudFraction_HadGEM2-ES.py
md5:a4481c2f6b82f9c88f219c70ae6f8c91
25.2 kB Download
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