Analysis of meteorological and climatic data allows to provide near real-time information about the crop state, in quality and quantity, with the possibility of early warning on alarm/alert situations so that timely interventions can be planned and undertaken. Crop forecasting philosophy is based on various kind of data collected from different sources: meteorological data, agrometeorological (phenology, yield), soil (water holding capacity), remotely sensed, agricultural statistics. Based on meteorological and agronomic data, several indices are derived which are deemed to be relevant variables in determining crop yield, for instance crop water satisfaction, surplus and excess moisture, average soil moisture, etc.

Crop forecasting is the art of predicting crop yields (tons/ha) and production before the harvest actually takes place, typically a couple of months in advance. Crop forecasting relies on computer programmes that describe the plant-environment interactions in quantitative terms. Such programmes are called "models", and they attempt to simulate plant-weather-soil interactions. They need, therefore, information and data on the most important factors that affect crop yields - the model inputs. After passing "through" the model, the inputs are converted to a number of outputs, such as maps of crop conditions and yields.

EC-FAO Food Security Information for Action Programme This website provides access to Food Security related information and resources produced by the EC-FAO Food Security Information for Action Programme..
Agrometeorological crop forecasting CROP FORECASTING is the art of predicting crop yields (tons/ha) and production before the harvest actually takes place, typically a couple of months in advance..
Weather conditions by Region Conditions during various seasons. Yeald and precipitations are mapped for different years. Data sources are NOAA and FAO. Maps are prepared by FAO/NRCB, Agrometeorology Group.
Length of the growing season by Region The length of the "growing season" or "growing period" (LGS or LGP) is the period (in days) during a year when precipitation exceeds half the potential evapotranspiration.
	Sahel Weather and Crop Situation (GIEWS)
	Database on food and agriculture for Africa (GIEWS)
2006 - Remote Sensing Support to Crop Yield Forecast and Area Estimates [PDF, 1,899 kb] Slide show on "An illustration of some non-parametric yield forecasting applications in Zimbabwe".
2006 - Non-parametric Crop Yield Forecasting, a Didactic case Study for Zimbabwe [PDF, 596 kb] Paper presented at the EU/JRC meeting on Remote Sensing Support to Crop Yield Forecast and Area Estimates.
2006 - INSAM, Agrometeorological forecasting [PDF, 1,387 kb] Agrometeorological forecasting covers all aspects of forecasting in agrometeorology. Therefore, the scope of agrometeorological forecasting very largely coincides with the scope of agrometeorology itself..
	2003 - Non-parametric crop yield forecasting [345 kb]
	2001 - Coordinating role of FAO in developing tools and methods to support food-security activities in National Agrometeorological Services [192 kb]
	2001 - An Introduction to the Art of Agrometeorological Crop Yield Forecasting using Multiple Regression [408 kb]
	2000 - Handbook for defining and setting up a Food Security Information and Early Warning System [935 kb]
	1998 - FAO Crop Yield Forecasting Philosophy in National Food Early Warning Systems [166 kb]
	1998 - Agrometeorological Crop Yield Forecasting Methods [114 kb]
	1998 - Agrometeorological Models and Remote Sensing for crop Monitoring and Forecasting in Asia and the Pacific [114 kb]
	1996 - Crops Weather and Satellites: Interfacing in the Jungle [116 kb]
	Crop-Yield Weather Modelling [670 kb]