Introduction

Andean farmers plant their fields before and during the initial months of the rainy season, avoiding planting all of their fields on a specific date or with the same crop. This traditional technique reduces climatic risks that occur as a result of the high interannual climate variability and also assures a minimum production for self-consumption during years of poor production. Farmers make decisions according to their expectation and based on previous experiences of risk and they have developed their own systems for weather and seasonal climate forecasting based on meteorological and astronomical phenomena as well as biological behavior of wild species (Baigorria 2005). However, in comparison to other Andean areas, studies in La EncaƱada and Tambomayo show that these indicators are more related to short-term decision-making such as when to apply agro-chemicals, than what, when, where and how to plant and crop. Although formal weather and seasonal climate forecasts are available from the Peruvian National Service of Meteorology and Hydrology, these are used only in a few cases, due to the inadequate spatial resolution and the lack of training to interpret them properly. Similarly, but at a different level, the extension offices provide general-purpose recommendations without using these forecasts.

In the present case study, the translation of a seasonal climate forecast from global circulation models into a map with the optimal planting dates for different crops was performed. This required downscaling of the forecasts and applying crop growth simulation models to evaluate the impact of expected seasonal-climate conditions and crop management on crop yields. These models increased the value of the seasonal climate forecasts, making available this kind of information in appropriate agricultural terms to stakeholders not deeply involved in climatology.

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