Supporting data for Baldwin et al 2019 "Temporally Compound Heat Waves and Global Warming: An Emerging Hazard"

Baldwin, Jane W; Dessy, Jay Benjamin; Vecchi, Gabriel A; Oppenheimer, Michael; Jia, Liwei; Gudgel, Richard G; Paffendorf, Karen
Issue date: 17 February 2019
Cite as:
Baldwin, Jane W, Dessy, Jay Benjamin, Vecchi, Gabriel A, Oppenheimer, Michael, Jia, Liwei, Gudgel, Richard G, & Paffendorf, Karen. (2021). Supporting data for Baldwin et al 2019 "Temporally Compound Heat Waves and Global Warming: An Emerging Hazard" [Data set]. GFDL Data Portal. https://doi.org/10.34770/xajd-5n64
@electronic{baldwin_jane_w_2021,
  author      = {Baldwin, Jane W and
                Dessy, Jay Benjamin and
                Vecchi, Gabriel A and
                Oppenheimer, Michael and
                Jia, Liwei and
                Gudgel, Richard G and
                Paffendorf, Karen},
  title       = {{Supporting data for Baldwin et al 2019 "
                Temporally Compound Heat Waves and Globa
                l Warming: An Emerging Hazard"}},
  publisher   = {{GFDL Data Portal}},
  year        = 2021,
  url         = {https://doi.org/10.34770/xajd-5n64}
}
Abstract:

This data is compiled to support a publication in the journal Earth's Future: Baldwin et al 2019 "Temporally Compound Heat Waves and Global Warming: An Emerging Hazard". The GCM GFDL CM2.5-FLOR was used to produce the raw climate model data. The model code for FLOR is freely available and can be downloaded at https://www.gfdl.noaa.gov/cm2-5-and-flor/. Code used to calculate the derived heat wave statistics data and produce figures in the paper is available at https://github.com/janewbaldwin/Compound-Heat-Waves The heat wave statistics derived output for only one definition is provided (daily minimum temperature, 90th percentile threshold, temporal structure 3114) which is the definition used the most in the paper figures. Statistics for the other definitions can be created by running the HWSTATS code provided in the corresponding github folder, which includes python scripts which do the analysis and PBS job scheduling and submission scripts which show how to run the python scripts. For more information on this, please see the github readme.

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Description:

A full description of the structure of the dataset and how to reproduce the figures in the manuscript are given in the dataset README file. This dataset is too large to download directly from this item page. You can access and download the data via Globus at this link: https://app.globus.org/file-manager?origin_id=dc43f461-0ca7-4203-848c-33a9fc00a464&origin_path=%2Fxajd-5n64%2F (See https://docs.globus.org/how-to/get-started/ for instructions on how to use Globus; sign-in is required).

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# Filename Description Filesize
1 README.txt 6.05 KB