It is important to distinguish between “data” and “information”. Data are directly measured variables that represent incoming solar radiation, air temperature, precipitation, etc. Information is the result of utilizing a statistical simulation or other type of model, such that the output can be used to make a decision. Climatic data can be displayed by point (e.g. meteorological station), by region (e.g. country), by continent (e.g. Africa), for the entire globe. They can be used to define the climate of a specific location and to assess its potential and constraints in terms of natural resources. Climatic data can be also estimated at locations for which no observations are available through a spatial interpolation process.

Global climate grids
A variety of gridded global climate datasets is provided covering different periods within 1951-2000 and based on different data sources (Climatic Research Unit, CRU; Global Precipitation Climatology Center, GPCC). The datasets are provided as tables of comma separated values (on a common grid with 0.5°x0.5° resolution) as well as resampled georeferenced IDA images and GeoTIFF files (5’x5’ resolution).<more>

 Climate data

Global climatic and real-time meteorological stations data from different sources are received under various forms (e.g. hand-written report, formatted and non-formatted text, spreadsheet, ASCII text, spatially interpolated data, etc.). <more>

 Climate maps

The global climate maps are based on data of mean monthly values of temperature, precipitation and cloudiness prepared in 1991 by R. Leemans and W. Cramer and published by the International Institute for Applied Systems Analysis (IIASA). <more>

 Spatial interpolation

The spatial interpolation of agroclimatic data aims at estimating the value of rainfall, temperature, or any other agroclimatic parameter at a given site based on the observations at neighbouring locations. <more>

 Methods and tools

Related links and publications <more>


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