Code for the Nature Communications article "The role of cyclonic activity in tropical temperature-rainfall scaling"
This repository contains the code to reproduce the results and figures of the following article published in Nature Communications:
Traxl, D., Boers, N., Rheinwalt, A., Bookhagen, B., The role of cyclonic activity in tropical temperature-rainfall scaling, Nature Communications, 2021.
https://doi.org/10.5281/zenodo.5593095
All data necessary to run the scripts in this repository are publicly available. For rainfall estimates, we used the Tropical Rainfall Measuring Mission (TRMM) 3B42 V7 dataset, available trough
https://disc.gsfc.nasa.gov/datasets/TRMM_3B42_7/summary
and downloaded from
https://disc2.gesdisc.eosdis.nasa.gov/s4pa/TRMM_L3/TRMM_3B42.7/
For temperature estimates, we used the ERA5 reanalysis dataset, downloaded from
https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels
For sea surface temperatures, we used the NOAA OI SST V2 High Resolution Dataset, available through
https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html
and downloaded from
ftp://ftp.cdc.noaa.gov/Datasets/noaa.oisst.v2.highres/
For tropical cyclone tracks, we used the International Best Track Archive for Climate Stewardship (IBTRACS), available through
https://www.ncdc.noaa.gov/ibtracs/
and downloaded from
https://www.ncei.noaa.gov/data/international-best-track-archive-for-climate-stewardship-ibtracs/v04r00/access/netcdf/IBTrACS.ALL.v04r00.nc
The scripts to process the data are located in the data_processing subfolder, and have to be run in the indicated order.
To reproduce the figures of the article, run
- fig1a_gl_sxt_vs_r_fits.py
- fig1b_SXT_mean_of_all_time_map.py
- fig2_fig4_glcp_burst_analysis.py
- fig3a_gl_grad_stats_mean.py
- fig3bc_gl_grad_vs_r_fits.py
Note that all scripts in the data_processing subfolder need to be executed before running the scripts to create the figures.
Dominik Traxl (dominik.traxl@posteo.org)