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Weather and Climate Extremes

ISSN: 2212-0947

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Datasets associated with articles published in Weather and Climate Extremes

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1970
2024
1970 2024
7 results
  • Data for: Characterization of long period return values of extreme daily temperature and precipitation in the CMIP6 models: Part 2, projections of future change.
    netcdf files of the multi-model average changes in extreme precipitation and temperature where the file name describes the details: cmip5 or cmip6 refers to model generation. TXx hot days TXn cold days TNN cold nights TNX warm nights Rx1day wet days Temperature changes are in degrees C, Precipitation changes in percent Global warming levels are 1.5, 2, 3 and 4C above preindustrial global mean surface temperature All results are over land only. If return value is in the name, that is the 20 year return value changes. Examples: land_change_TXx_cmip6_ensemble_mean_warming_level_40.nc contains the CMIP6 multi-model average change in average hot day temperatures (TXx) at 4C above preindustrial percent_change_Rx1day_annual_return_value_cmip5_ensemble_mean_warming_level_15.nc contains the CMIP5 multi-model average percent change in 20 year return values of Rx1day at 4C above preindustrial
    • Dataset
  • Data for: Regionally-Stratified Tornadoes: Moisture Source Physical Reasoning and Climate Trends
    Derived data are provided for the 11 figures contained in the manuscript. Each data set contains the figure number it was used in. Data formats include netCDF, shapefiles, and serialized python data. Alternative data formats may be available upon request from the corresponding author. Trajectories used in the 3d matrix (Figure 1) are in ASCII format, within the TAR file. Raw data, including climate scale trajectories (1981-2017), reanalysis, and statistical significance bootstrap data (10,000-members per analysis), greatly exceeded the 10GB limit for Mendeley uploads, but are available from the authors upon request.
    • Dataset
  • Data for: Predictive Livestock Early Warning System (PLEWS): Implications for animal production and animal/public health
    Supplementary material_FCI_3month_average_contingency_final_jan_31_2017_pixel_ave_new This data is the forage condition indices on three monthly average for counties in Kenya.
    • Dataset
  • Data for: Yield Risks in Global Maize Markets: Historical Evidence and Future Projections in Key Regions of the World
    Country-level historic observations of growing season climate (temperature and precipitation) during 1941-2014 and country-level historic and future projections of growing season climate during 1961-2099. Country-level historic observations of maize yields during 1951-2014 and country-level historic and future projections of maize yields during 1961-2099 produced by the AgMip-GGCMI project.
    • Dataset
  • NCEP1 Cyclone tracks
    The dataset is a series of excel spreadsheets in .csv format that have difference characteristics of cyclones/ low pressure systems for Australia. Data has also been manipulated in MATLAB, ARCGIS and Abode Illustrator. Therefore, there is a variety of spatial files, code and figures. There is also a lot of raw climate data that was sourced from external websites. This includes sub-daily rainfall, daily rainfall, climate indices, wind and temperature as well as various TC databases.
    • Dataset
  • NCEP1 Cyclone tracks
    The dataset is a series of excel spreadsheets in .csv format that have difference characteristics of cyclones/ low pressure systems for Australia. Data has also been manipulated in MATLAB, ARCGIS and Abode Illustrator. Therefore, there is a variety of spatial files, code and figures. There is also a lot of raw climate data that was sourced from external websites. This includes sub-daily rainfall, daily rainfall, climate indices, wind and temperature as well as various TC databases.
    • Dataset
  • Daily large hail probability on a global scale (1979 to 2015), Version 2, link to netCDF files
    This is an updated version of a dataset that contains daily gridded hail hazard estimates on a global scale for the period 1979 to 2015. It is based on the presence of environmental conditions in which large hail (diameter >2.5 cm) has been observed. The data is provided on a global grid with 0.7°x07° grid spacing. The hail risk varies between zero and one where one means a high probability that the location will experience large hail on a corresponding day.
    • Tabular Data
    • Dataset