Skip to content

On the reliability of large ensembles simulating stratospheric polar vortex

License

Notifications You must be signed in to change notification settings

VACILT/reliability_LE

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

License

On the reliability of large ensembles simulating the Northern Hemispheric winter stratospheric polar vortex

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

Submitted to ?.

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 Rank histograms of aspect ratio at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
2 Rank histograms of centroid latitude at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
3 Rank histograms of centroid longitude at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
4 Rank histograms of kurtosis at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
5 Rank histograms of objective area at 10 hPa summary_plots.py rank_histograms.py, rank_frequency_test.py, bias_spread.py
6 AOC for displacement and split events roc_diagrams.py

Tables

# Figure Notebook Dependencies
1 Analyzed climate model ensembles from CMIP5 and CMIP6

Supplementary figures

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