Weather and Climate Monitoring and Prediction Systems in the Context of Agriculture

Climate forecasts show the potential to improve agriculture's ability to withstand climate shocks, but it is still uncertain how farmers will use this data in crop management decisions plus whether doing so will profit them. This volume introduces the most commonly used forecasting strategies in agriculture, like probability forecasting, real-time forecasting and ultra-short distance forecasting. These determine the pattern of planting dates and crop varieties, the latter being more common where more extensive weather forecasting methods exist. Hybrid strategies usually use more input elements (such as crop varieties) to define the strategy (such as sowing period). Production estimates indicate that, in most cases, using forecasted values can increase production with relatively minimal loss. The impact depends on the nature of actual rainy season, the forecast accuracy and the kind of response. In wet years, with the consolidation of the policy and accurate forecast, the positive response will be higher. This proves that climate prediction can help farmers acclimatize to climate variability, particularly to help them take advantage of the expected favorable conditions. The realization of possible advantages is related to the context of greater variety selection and enhanced selection. Even so, modern advances in weather modeling have improved the ability to accurately forecast rainfall through dynamic forecasting and statistical techniques.