The global climate maps presented here are based on data for 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). The IIASA data correspond to an
imaginary "net" covering the Earth's surface with a mesh size
of 0.5 degrees. This is equivalent to about 60 km - an area of about
3,600 sq. km - at the equator.
Monthly climatic data for each cell in the net are
provided by weather stations and consist of an average, or "normal",
value of monthly climate elements. Using spatial extrapolation, a value
is computed for each cell based on the neighbouring station values.
FAO's Agrometeorology Group converted the IIASA tables into grids:
Then, using Image Display and Analysis (IDA) software, it assigned to
the estimated value of each cell a colour code: for instance, yellow
for monthly rainfall below 95mm, and green above.
Applying this procedure to all the IIASA data,
the Agrometeorology Group has produced a series of global climate
|Raw data maps
The IIASA database includes three key climatic elements: average monthly
rainfall total, average monthly temperature, and monthly average sunshine.
For each of the stations used in the gridding exercise, data have been
assembled over a long time period - usually between 1961 and 1990 - and then
averaged. Annual totals for rainfall, and the averages for temperature and
sunshine, were derived from the monthly values. We present here the
complete set of raw data maps:
Sunshine fraction is
the percentage of time when bright sunshine is recorded during the day.
It is directly linked to cloudiness, with full cloud cover being equal
to 0% of sunshine fraction.
Two products derived by the FAO Agrometeorology Group from the IIASA data
sets are a "climate classification" according to Koeppen,
and "Potential biomass" according to Lieth.
The most widely used system of climate classification is that of the
German climatologist Koeppen (1936) - virtually all more recent classifications
are refinements or variants of the "Koeppen system". The
classification is based on monthly rainfall and temperatures, including
the following five inputs:
Computer elaboration of these inputs produces:
The Koeppen system assigns codes to
the main climates: Tropical (A), Dry (B), Temperate (C), Cold (D) and Polar
Each of the main climate classes are divided
into sub-classes based mainly on the distribution of rainfall and temperature
over the year:
Temperature of the coldest month is
greater than 18°C. Reddish tones (e.g. Central Africa, Southeast Asia)
are areas with no dry season and at least 60 mm of rainfall in the driest month.
Areas indicated with blue tones have monsoon-type climates - a short dry season but
sufficient moisture to keep ground wet throughout the year. Yellow indicates zones -
such as Northeastern Brazil - with a distinct dry season (one month with
precipitation less than 60 mm); green represents an isothermal subtype,
with an annual range of temperature less than 5°C
Annual evaporation exceeds
annual precipitation. Colours correspond to dominant vegetation
types. Zones shaded in greys and blue have a steppe climate, while those
in shades of orange are desert. Zones in yellow (for example, coastal
Namibia) are desert areas with a cool, dry climate; the
temperature of the warmest month does not exceed 18°C.
Average temperature of
the coldest month < 18°C and > -3°C , and the average
temperature of warmest month exceeds 10°C.
Note that, since the Temperate class is defined only by temperature range,
the "raw" temperate climate extends into other areas - e.g.
Australia, North Africa - which, owing to severely limited rainfall, are
classified as Dry (B) climates. Temperate areas shaded in blues (e.g.
Northern India) have a winter dry season with at least 10 times as much
precipitation in the wettest summer month as in the driest winter month.
Areas indicated in magenta are characterized by a summer dry season - at
least three times as much rain falls in the wettest month of winter as in
the driest month of summer, the latter having less than 30mm precipitation.
Green tones (Northern Europe, Eastern USA) indicate areas with at least
30 mm. of precipitation in the driest month.
Average temperature of the warmest month > 10°C and that
of coldest month < -3°C. This climate class has two main
subclasses: areas with at least 30mm of rain in the driest month
(indicated in green), and those with a winter dry season - at least
ten times as much precipitation in the wettest month of summer as in
the driest month of winter (blue tones).
Average temperature of the warmest month < 10°C.
Zones indicated in violet (e.g. Siberia) are tundra with an average
temperature in the warmest month greater than 0°C, while those
in blue-green (the coast of Greenland) have no month with temperature
above 10°C. A subtype of the latter subclass is the Greenland
interior (light blue), where the average temperature of the coldest
month is less than -38°C.
Potential biomass is the amount of plant biomass that can be accumulated
in one year under the assumption of ideal conditions prevailing for photosynthesis,
i.e. absorption of solar energy by plants and storage of the energy as plant
material. The map given below uses one of the earliest methods, developed
by H. Lieth and published in 1972.
Although this approach is now largely superseded by more complex approaches
involving solar energy conversion efficiencies, Lieth's method is interesting
in that it clearly shows whether temperature - cold or warm - or water is
the main limiting factor. (The unit of measurement is grams of dry matter per
sq. metre per year.)
|Downloading the digital maps and
FAO's Environment and Natural Resources Service (SDRN) is making the global
climate data base available as geo-referenced digital images and maps. The
data are in Image Display and Analysis (IDA) format, DOS-based public domain
software developed jointly by FAO and USAID's Famine Early Warning System
(FEWS) for displaying, processing and analysing satellite images.
The data can be analysed using WinDisp
view sample screen), a Windows-based successor to IDA that was developed
with funding from the European Union as part of the FAO Global Information and Early
Warning System (GIEWS) Workstation Project.
The SADC Food Security Technical Unit, FAO-ARTEMIS, USAID-FEWS, the USGS
EROS Data Center and the US Forest Service have contributed funds to add
additional analytical features to WinDisp.
WinDisp contains all the analytical functions of IDA, as well as many new
additional features that provide a simpler, yet more powerful interface in
the Windows environment. It allows users to extract statistics from
images by polygons (usually administrative boundaries), to compare
differences, convert formats and export images to ASCII grids and the GIS
Georeferenced maps (1.5MB)
Includes data sets for biomass, rainfall, sunshine fraction, temperature
and Koeppen climate classification, with colour palletes and 'read me'
Windisp Version 4.0 (2.02MB)
Contains sample satellite images, maps and color tables. Download also Windisp manual
For detailed information on Windisp, see
Leemans, R. and Cramer, W., 1991. "The IIASA database for mean monthly
values of temperature, precipitation and cloudiness on a global terrestrial
grid". Research Report RR-91-18. November 1991. International Institute of
Applied Systems Analyses, Laxenburg, pp. 61.
Lieth, H., 1972. "Modelling the primary productivity of the earth. Nature and
resources", UNESCO, VIII, 2:5-10.
Produced by the Agrometeorology
Group of FAO's Sustainable Development Department. Text: R. Gommes.
GIFs: F. Petrassi, G. Thomas. Thanks to Thorsten Lemke (GraphicConverter).
For further information, contact Agromet@fao.org