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climate

101 record(s)
 
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  • The FGGD CV of LGP map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains an average coefficient of variation of LGP for the pixel area over the period 1901-1996. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

  • The FGGD climate constraints map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains a class value for the degree to which climate constrains agricultural production potential in the pixel area. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

  • The FGGD CV of LGP map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains an average coefficient of variation of LGP for the pixel area over the period 1901-1966. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

  • The FGGD thermal climate zone map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains a class value for the dominant thermal climate found in the pixel. The underlying temperature data are from the Climate Research Unit (CRU) at the University of East Anglia-Norwich, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

  • The FGGD LGP zone map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains a class value for the dominant LGP zone found in the pixel. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

  • Dryland map derived from the Aridity index map (P/PET).

  • April 1st-Decadal Rainfall 1996. The APR1_95 grid data layer is comprised of 1152x1152 derivative raster precipitation features derived based on 8 kilometers data originally from EDC. 2nd and 3rd Decadal Rainfall from January to December is also available for download. Acronyms and Abbreviations: EDC - USGS EROS (Earth Resources Observation Systems) Data Center

  • April 1st-Decadal Short Mean Rainfall. The APR1_SM grid data layer is comprised of 1152x1152 derivative raster precipitation features derived based on 8 kilometers data originally from EDC. 2nd and 3rd Decadal Rainfall from January to December is also available for download. Acronyms and Abbreviations: EDC - USGS EROS (Earth Resources Observation Systems) Data Center

  • The Food and Agriculture Organization of the United Nations (FAO) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), has developed a system that enables rational land-use planning on the basis of an inventory of land resources and evaluation of biophysical limitations and potentials. This is referred to as the Agro-ecological Zones (AEZ) methodology.

  • The Global Climate Risk Index 2020 analyses to what extent countries and regions have been affected by impacts of weather-related loss events (storms, floods, heat waves etc.). The most recent data available - for 2018 - were taken into account in this map. Source: The Climate Risk Index is based on data from Munich RE. Germanwatch