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CRUCLIM 30-year Average Bioclimate Time Series (1915 - 1995): Mapped climate data with global extent at 30 arcminute resolution

A time series of 30-year average bioclimatic maps at 5-year intervals from 1915 - 1995. Data are mapped at 30 acrminute resolution (0.5 degree) and cover the entire extent of globe. These maps are derived from monthly estimates of mean minimum temperature, mean maximum temperature and total precipitation from 1901 - 2014 which were originally created by the Climatic Research Unit (CRU) at the University of East Anglia.
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    Data record related to this publication CRUCLIM 30-year Average Bioclimate Time Series (1915 - 1995): Mapped climate data with global extent at 30 arcminute resolution
    Data Publication title CRUCLIM 30-year Average Bioclimate Time Series (1915 - 1995): Mapped climate data with global extent at 30 arcminute resolution
  • Description

    A time series of 30-year average bioclimatic maps at 5-year intervals from 1915 - 1995. Data are mapped at 30 acrminute resolution (0.5 degree) and cover the entire extent of globe. These maps are derived from monthly estimates of mean minimum temperature, mean maximum temperature and total precipitation from 1901 - 2014 which were originally created by the Climatic Research Unit (CRU) at the University of East Anglia.

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  • Other Descriptors
    • Descriptor

      A set of 19 bioclimatic variables, calculated according to the WorldClim method. They are coded as follows: CRUCLIM_01 = Annual Mean Temperature, CRUCLIM_02 = Mean Diurnal Range, CRUCLIM_03 = Isothermality (CRUCLIM_02/CRUCLIM_07), CRUCLIM_04 = Temperature Seasonality (Standard Deviation), CRUCLIM_05 = Max Temperature of Warmest Month, CRUCLIM_06 = Min Temperature of Coldest Month, CRUCLIM_07 = Temperature Annual Range (CRUCLIM_05-CRUCLIM_06), CRUCLIM_08 = Mean Temperature of Wettest Quarter, CRUCLIM_09 = Mean Temperature of Driest Quarter, CRUCLIM_10 = Mean Temperature of Warmest Quarter, CRUCLIM_11 = Mean Temperature of Coldest Quarter, CRUCLIM_12 = Annual Precipitation, CRUCLIM_13 = Precipitation of Wettest Month, CRUCLIM_14 = Precipitation of Driest Month, CRUCLIM_15 = Precipitation Seasonality (Coefficient of Variation), CRUCLIM_16 = Precipitation of Wettest Quarter, CRUCLIM_17 = Precipitation of Driest Quarter, CRUCLIM_18 = Precipitation of Warmest Quarter, CRUCLIM_19 = Precipitation of Coldest Quarter These aggregated data layers are derived from the dataset CRU TS 3.23; whenever these bioclimatic variables are used in a publication the original data should also be cited as: University of East Anglia, Climatic Research Unit (CRU) Time-Series (TS) Version 3.23 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2014). Centre for Environmental Data Analysis, 09 November 2015. DOI for source data citation: http://dx.doi.org/10.5285/4c7fdfa6-f176-4c58-acee-683d5e9d2ed5

      • Descriptor type Full
    • Data type dataset
  • Keywords
    • bioclimate
    • Climatic Research Unit
    • CRU
    • time Series
    • climate
    • global
  • Funding source
  • Research grant(s)/Scheme name(s)
    • -
    • Research themes
    Tropical Ecosystems, Conservation and Climate Change
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    Temporal (time) coverage
  • Start Date
  • End Date
    • Time Period Contemporary
    Spatial (location) coverage
  • Locations
    • Global
- Data
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  • Related publications
      Name Harris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2013) Updated high-resolution grids of monthly climatic observations - the CRU TS3.10 Dataset. International Journal of Climatology, 34(3). pp. 623-642.
    • URL http://dx.doi.org/10.1002/joc.3711
    • Notes Describes the creation of the monthly average climate surfaces which were aggregated to create CRUCLIM bioclimatic variables
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- License
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    The data will be licensed under CC BY: Attribution 3.0 AU
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  • Data owners
      Collin Storlie
- Citation
    Citation Storlie, Collin (2016): CRUCLIM 30-year Average Bioclimate Time Series (1915 - 1995): Mapped climate data with global extent at 30 arcminute resolution. James Cook University. https://doi.org/10.4225/28/570DDDE168124