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README_figure_S12.6
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# -- Figure S12.6 of Chapter 12 IPCC AR6
# -- Author: Jerome Servonnat
# -- Contact: jerome.servonnat at lsce.ipsl.fr
# -----------------------------------------------------
##########################################################################
### ---------------------------------------------------------------------------------------------------------------------
### In this README you will find the different steps to do IPCC AR6 WGI Figure S12.6
### Creator: Jerome Servonnat - LSCE-IPSL
### Contact: jerome.servonnat at lsce.ipsl.fr
### Last updated on: March 6th, 2023
### --------------------------------------------------------------------------------------------------------------------
### Information on the softwares used
### - Softwares Versions:
### - python 2.7
### - CliMAF 1.2.13 (https://github.com/rigoudyg/climaf/tree/V1.2.13_JS_lastfix)
### - ncl 6.6.2
### - cdo 1.9.6
### - nco 4.5.2
### - R 3.6.3
### - Python and R packages of the used conda environment listed in Figures/scripts/env_list.txt
###
### - Operating System: Scientific Linux release 6.10 (Carbon)
### ----------------------------------------------------------------------------------------------------
###
### License: Apache 2.0
###
### ----------------------------------------------------------------------------------------------------
### How to cite:
### When citing this code, please include both the code citation and the following citation for the related report component:
### Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1767–1926, doi: 10.1017/9781009157896.014.
##########################################################################
#
## -- Note 1: The paths provided below are relative to main root path: https://github.com/IPCC-WG1/Chapter-12/blob/main/Figures
## ! if the path is not specified, the file is in the same directory as this README file
# -- Presentation of the figure
The figure S12.6 shows regional averages over the AR6 regions (land) for the Vousdoukas et al. 2018 and the Kirezci et al., 2020 datasets.
The climate indicator is the extreme total water level for RCP4.5 and RCP8.5 for:
- recent past
- mid-term horizon
- long-term horizon
# -- Step 1: computing the regional averages
We compute the regional averages for the Vousdoukas et al. 2018 dataset with Compute_averages_AR6_regions_ETWL.ipynb
They are stored in data/Figure_S12.6 in the json files:
- Vousdoukas_ETWL_by_AR6_region_modern.json
- Vousdoukas_ETWL_by_AR6_region_RCP45_2050.json
- Vousdoukas_ETWL_by_AR6_region_RCP45_2100.json
- Vousdoukas_ETWL_by_AR6_region_RCP85_2050.json
- Vousdoukas_ETWL_by_AR6_region_RCP85_2100.json
The regional averages for the Kirezci et al. 2020 dataset were already provided in Kirezci_ESL.csv
# -- Step 2: do the figure
We do figure S12.6 with the R notebook Barplots_ETWL.ipynb.
It draws the panels for all the regions and do the multiplot figs/Satellite_barplots/Figure_S12.6_ETWL_satellite.[png,pdf]
Some final editing is done after that (like adding the colored squares around the panels).