The methodology
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.

Location of weather stations in Brazil, plus rainfall data for a sample area

Gridded rainfall data for the sample area, Brazil

Colour-coded map of January rainfall data for the sample area
Map of average January rainfall, northeastern Brazil

Applying this procedure to all the IIASA data, the Agrometeorology Group has produced a series of global climate images.

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:

Annual average rainfall total
Animation of monthly rainfall total (156K)
Average monthly rainfall total (mm):  Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec

Annual average temperature
Animation of monthly temperature (139K)
Average monthly temperature (°C):  Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec

Annual average sunshine fraction
Animation of monthly sunshine fraction (127K)
Average monthly sunshine fraction (%):  Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec

Derived products

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.

Climate classification
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:

Average monthly temperature of the warmest month
Average monthly temperature of the coldest month
Average thermal amplitude between coldest and warmest months
Number of months with average temperature exceeding 10° C
Winter and summer rains

Computer elaboration of these inputs produces:

Koeppen's Climate Classification map

The Koeppen system assigns codes to the main climates: Tropical (A), Dry (B), Temperate (C), Cold (D) and Polar (E).

Brief guide to Koeppen Climate Classification system (text)

Each of the main climate classes are divided into sub-classes based mainly on the distribution of rainfall and temperature over the year:

A: Tropical

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

B: Dry

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.

C: Temperate

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.

D: Cold

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).

E: Polar

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.

Biomass potential
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.)

Map of biomass potential
Temperature-limited biomass potential
Rainfall-limited biomass potential

Downloading the digital maps and technical data

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 software IDRISI.

Download...
1. Georeferenced maps (1.5MB)
Includes data sets for biomass, rainfall, sunshine fraction, temperature and Koeppen climate classification, with colour palletes and 'read me'

2. Windisp Version 4.0 (2.02MB)
Contains sample satellite images, maps and color tables. Download also Windisp manual (Word 97 or PDF). For detailed information on Windisp, see GIEWS/Software

References

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.