Data and Scripts to "Are Sudden Stratospheric Warmings Generic? Insights from an idealized GCM", Journal of the Atmospheric Sciences (2016)

Published: 19 October 2016| Version 1 | DOI: 10.17632/pbf8tvprfk.1
Contributor:
Martin Jucker

Description

Dataset accompanies the paper "Are Sudden Stratospheric Warmings Generic? Insights from an idealized GCM", and contains full zonal mean model data, the derived sudden warming composites, and the scripts used for analysis and visualization of the data.

Files

Steps to reproduce

COMPLETE DATASET CREATION: For complete reproduction from scratch, download the GCM from http://dx.doi.org/10.5281/zenodo.31010, and the simulation structure and input files from http://dx.doi.org/10.6084/m9.figshare.1320613.v2 . Run the model within every subdirectory of `sswruns.zip`, with the provided inputs. This will re-generate all initial 4D model output. Unpack `postproc.zip`. For each simulation, run `treatrun.sh`, which will use the compiled fortran routines within `postproc.zip`. To re-create the database, unpack `matlab_scripts.zip`, and run `SSW_create_database.m`. This will create the zonal mean evolution data files needed to re-create all figures. RE-CRATE FIGURES FROM PROCESSED DATA: Download all files. Make sure the absolute paths to the data files are correct in every script used. Usually, that means setting the variable `datadir` near the top of each script. Also install the `aostools` package (http://dx.doi.org/10.5281/zenodo.47244) Run the iPython scripts. Parameter settings for different plot choices are mostly towards the beginning of each script. NOTE: The here provided data is created from the initial raw 4D model output. The same data is used for the planetary vs. all waves study of Figure 7. This data is about 2TB, and therefore much too big for any online repository. It is stored by the author and can be provided on request. It can be re-created with the above description.

Institutions

Princeton University

Categories

Atmospheric Science, Climate Dynamics, Numerical Modeling

Licence