Jupyter notebooks, Python scripts, and data files used to make figures analyzing tropical cyclones (TCs) in the NASA GISS-E3 global climate model. Much of this code was adapted from Matlab code written by Jeffrey Strong.
This code is for a paper to be submitted to Journal of Advances in Modeling Earth Systems in 2021 by Rick Russotto, Jeffrey Strong, Suzana Camargo, Adam Sobel, Gregory Elsaesser, Maxwell Kelley, Anthony Del Genio, Yumin Moon, and Daehyun Kim. The code and data will be uploaded to Zenodo upon acceptance of the paper.
Vesions of libraries used for paper: Python 3.6.12, NumPy 1.19.2, Matplotlib 3.2.0 (including Basemap), Pandas 1.1.5, XArray 0.16.2, SciPy 1.5.2
Figure 1: Plot_Tracks.ipynb
Figure 2: Plot_Density.ipynb
Figures 3-7: Plot_Statistics.ipynb
Figures 8-9: Plot_Storm_Tangential.ipynb
Figure 10: Plot_Radial_Profiles.ipynb
Figures 11-12: Sensitivity_Test_Plots.ipynb
Figure 13: Intermediate_Error_Plots_v2.ipynb
Figures 14, S2: Intermediate_Error_Plots_v3.ipynb
Read_Zhao_TCs.ipynb (for modeled TCs)
Preprocess_IBTrACS.ipynb (for observed TCs)
Storm_Centered_Plots.py
Storm_Centered_V1_Prec.py
Retrieve_Utan_Vtan.py
Figures 10 and S1 depend on Matlab scripts (not included here) developed by Yumin Moon for paper in Journal of Climate, Moon et al. (2020), https://doi.org/10.1175/JCLI-D-19-0172.1, and adapted by Jeffrey Strong for this study.
Figures 11-14 and S2 depend on Matlab scripts developed by Jeffrey Strong (not included here) for processing climate variables in the model results and comparing to observations.
YuminEtAl_Figs.mat
JS_C180_ParamSensTest.mat
JS_C180v2_ParamSensTest.mat
(Post NetCDF files here after saving)
zhao_tracks_v1.nc
zhao_tracks_v2.nc
(Observed TC data from IBTrACS project available at https://www.ncdc.noaa.gov/ibtracs/index.php?name=ib-v4-access)
storm_centered_peak_intensity_v1.nc
storm_centered_peak_intensity_v2.nc
storm_centered_reference_winds_v1.nc
storm_centered_reference_winds_v2.nc
storm_centered_peak_intensity_prec_v1.nc