Software Open Access
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.
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 |
shellKernelCalculations.py
md5:cabbef86cf7bd999733857f8d6697573 |
39.4 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 |
All versions | This version | |
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Views | 271 | 75 |
Downloads | 572 | 116 |
Data volume | 13.7 MB | 2.9 MB |
Unique views | 239 | 68 |
Unique downloads | 290 | 71 |