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Experiment outputs are now available from the Coupled Model Intercomparison Project's 6th phase (CMIP6) and the past climate experiments defined in the Model Intercomparison Project's 4th phase (PMIP4). All of this output is freely available from the Earth System Grid Federation (ESGF). Yet there are overheads in analysing this resource that may prove complicated or prohibitive. Here we document the steps taken by ourselves to produce ensemble analyses covering past and future simulations. We outline the strategy used to curate, adjust the monthly calendar aggregation and process the information downloaded from the ESGF. The results of these steps were used to perform analysis for several of the initial publications arising from PMIP4. We provide post-processed fields for each simulation, such as climatologies and common measures of variability. Example scripts used to visualise and analyse these fields is provided for several important case studies.

License: GNU General Public License v3.0

Shell 0.20% NCL 7.49% Jupyter Notebook 92.16% Dockerfile 0.14%

pmip_p2fvar_analyzer's Introduction

PMIP4 past2future analyzer

This repository contains materials to lower the entry barriers to analyzing climate model simulations created for the Palaeoclimate Model Intercomparison Project. It is described in Zhao et al (2021) entitled "Workflow and tools to analyze the PMIP4-CMIP6 ensemble", which is under consideration for publication at Geoscientific Model Development at https://doi.org/10.5194/gmd-2021-290.

There is information about what this repository contains and what you can do with at ReadTheDocs. However you're welcome to just poke around.

It contains several elements of summary data for PMIP4-CMIP6 and PMIP3-CMIP5, which we hope will be useful. These are stored in two locations depending on their format. 2D fields of surface temperature and precipitation come bundled with the repository (for annual mean, summer and winter). These are stored in a zipped tape archive in data_netcdfs/, which is automatically unpacked. Common metric and indices that can be quanified by a single number are collected together in a series of spreadsheets. These spreadsheets are stored in the directory data_frames/ as csv files. Additionally this directory contians the DOIs of all of the simulations, so to make it easier to incorporate these citations into any publications.

Using this repository

You are welcome to use this resource as a repository of summary data, and download individual files. The most convenient manner to do this is to clone the repository with git, or download a zip file of it, using the button above. It would be great if you would contribute your own analysis scripts to the effort, which you can do by forking the repository and then sending us a pull request.

We have invested some effort into making this resource be more than just place to hold data and code, but to also become a research tool in itself. You can download a docker image of this whole repository. This image not includes the code and data, but also bundles in all the required software needed to interact visually with the data through Jupyter and create your own plots of the data.

The docker image is available from Docker Hub - see ReadTheDocs for instructions...

DOI

pmip_p2fvar_analyzer's People

Contributors

annizhao1994 avatar chrisbrierley avatar

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