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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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