Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'

Ombadi, Mohammed; Risser, Mark; Rhoades, Alan; Varadharajan, Charuleka

doi:10.15485/1987525

Title: Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'

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Abstract

This package contains the main codes, sample input data and main result files to reproduce the analysis and results presented in the article: “Ombadi et al. (2023), A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature”. The folder consists of the following: (1) “Raw data”: a folder that contains sample input data which is used in some of the codes for demonstration purposes. It also contains data that was not pre-processed such as Elevation data; (2) “Results”: this folder contains files of the main results presented in the paper including: “Annual-Max-Series”, “Change-rainfall-extremes”, “Change-snow-fraction”, “Warming levels_By scenario_model_year” and “Masks”. Description of these folders is detailed in the "Readme.rtf" file; (3) Python jupyter notebooks (Extract_Annual Max Series (AMS).ipynb, Elevation-dependent amplification of rainfall extremes.ipynb, Sensitivity_to_global_warming.ipynb) demonstrate the main steps of analysis. Further description of those notebooks is provided in the "Readme.rtf" file; (4) R code for extreme value analysis (Extreme_Value_Analysis.R). The sample and pre-processed dataset in "Raw data" is obtained from publicly available repositories of CMIP6 and ERA5 datasets; see Methods for more detail. This research was supported by Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract no. DE-AC02-05CH11231 for the CASCADE Scientificmore »« less

Authors:

;

Lawrence Berkeley National Laboratory; Lawrence Berkeley National Laboratory
Lawrence Berkeley National Laboratory

Publication Date:: Wed Jun 28 04:00:00 UTC 2023

DOE Contract Number:: AC02-05CH11231

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem; iNAIADS

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > LIQUID PRECIPITATION > RAIN; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SNOW/ICE; snowfall_flux

OSTI Identifier:: 1987525

DOI:: https://doi.org/10.15485/1987525

Citation Formats


                    Ombadi, Mohammed, Risser, Mark, Rhoades, Alan, and Varadharajan, Charuleka. Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'.  United States: N. p., 2023. 
        Web.  doi:10.15485/1987525.

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                    Ombadi, Mohammed, Risser, Mark, Rhoades, Alan, & Varadharajan, Charuleka. Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'.  United States.  doi:https://doi.org/10.15485/1987525

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                    Ombadi, Mohammed, Risser, Mark, Rhoades, Alan, and Varadharajan, Charuleka. 2023.  
"Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'".  United States.  doi:https://doi.org/10.15485/1987525.  https://www.osti.gov/servlets/purl/1987525. Pub date:Wed Jun 28 04:00:00 UTC 2023

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@article{osti_1987525,

  title        = {Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'},

  author       = {Ombadi, Mohammed and Risser, Mark and Rhoades, Alan and Varadharajan, Charuleka},

  abstractNote = {This package contains the main codes, sample input data and main result files to reproduce the analysis and results presented in the article: “Ombadi et al. (2023), A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature”. The folder consists of the following: (1) “Raw data”: a folder that contains sample input data which is used in some of the codes for demonstration purposes. It also contains data that was not pre-processed such as Elevation data; (2) “Results”: this folder contains files of the main results presented in the paper including: “Annual-Max-Series”, “Change-rainfall-extremes”, “Change-snow-fraction”, “Warming levels_By scenario_model_year” and “Masks”. Description of these folders is detailed in the "Readme.rtf" file; (3) Python jupyter notebooks (Extract_Annual Max Series (AMS).ipynb, Elevation-dependent amplification of rainfall extremes.ipynb, Sensitivity_to_global_warming.ipynb) demonstrate the main steps of analysis. Further description of those notebooks is provided in the "Readme.rtf" file; (4) R code for extreme value analysis (Extreme_Value_Analysis.R). The sample and pre-processed dataset in "Raw data" is obtained from publicly available repositories of CMIP6 and ERA5 datasets; see Methods for more detail. This research was supported by Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract no. DE-AC02-05CH11231 for the CASCADE Scientific Focus (funded by the Regional and Global Model Analysis Program area within the Earth and Environmental Systems Modeling Program) and the iNAIADS Early Career Research Project (funded by the Environmental Systems Science program).},

  doi          = {10.15485/1987525},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Jun 28 04:00:00 UTC 2023},

  month        = {Wed Jun 28 04:00:00 UTC 2023}

}

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DOI: https://doi.org/10.15485/1987525

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