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On the reliability of large ensembles simulating stratospheric polar vortex

License: MIT License

Jupyter Notebook 99.78% Python 0.17% TeX 0.06%
cmip6 climate climate-data climate-data-analysis python stratosphere climate-ana atmospheric-science

reliability_le's Introduction

DOI License

Large ensemble assessment of Arctic SPV

A. Kuchar, M. Öhlert, R. Eichinger, Ch. Jacobi

In review in WCD.

Code used to process and visualise the model and other data outputs in order to reproduce figures in the manuscript. Model data are available via the Multi-Model Large Ensemble Archive (MMLEA) provided by the US CLIVAR (Climate and Ocean - Variability, Predictability, and Change) working group on large ensembles (Deser et al., 2020) as well as ensembles from the Coupled Model Intercomparison Project 6 (CMIP6; Eyring et al., 2016).

All datasets already preprocessed can be found here.

Notebooks for each individual figure as well as for two data tables are in the code/ directory, while the figures themselves are in the plots/ directory.

Figures

# Figure Notebook / Script Dependencies
1 Geopotential height climatology at 10 hPa gh10_visualization.ipynb
2 ROC for displacements and splits in CanESM5 ROC_values.ipynb
3 Rank histograms of aspect ratio at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
4 Rank histograms of centroid latitude at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
5 Rank histograms of centroid longitude at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
6 Rank histograms of kurtosis at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
7 Rank histograms of objective area at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
8 AOC for displacement and split events roc_diagrams.py
9 Scatter plots of modal centroid latitude and frequency of displacement SSWs, and modal aspect ratio and frequency of split SSWs SSW_frequency_vs_mode_Hallet2021_MPI-ESMs-final.ipynb ERA5_SSW.ipynb

Tables

# Figure Notebook Dependencies
1 Analyzed climate model ensembles from CMIP5 and CMIP6
S1 Summary table including metrics: bias, spread and AOC ROC_values.ipynb rank_histograms.py
S2 List of SSWs in ERA5 ERA5_SSWs_export_latex.ipynb ERA5_SSW.ipynb, get_ERA5_moments-netcdf.ipynb

Supplementary figures

# Figure Notebook / Script Dependencies
S1 ROC curves for displacement events roc_diagrams_plots.py rank_histograms.py
S2 ROC curves for split events roc_diagrams_plots.py rank_histograms.py
S3 Rank histograms of aspect ratio at 50 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S4 Rank histograms of centroid latitude at 50 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S5 Rank histograms of centroid longitude at 50 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S6 Rank histograms of kurtosis at 50 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S7 Rank histograms of objective area at 50 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S8 Rank histograms of aspect ratio at 100 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S9 Rank histograms of centroid latitude at 100 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S10 Rank histograms of centroid longitude at 100 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S11 Rank histograms of kurtosis at 100 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
S12 Rank histograms of objective area at 100 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py

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