Visualization of uncertainties and forecast skill in user-tailored seasonal climate predictions for agriculture

Seasonal climate forecast products potentially have a high value for users of different sectors. During the first phase (2012-2015) of the project CLIMANDES (a pilot project of the Global Framework for Climate Services led by WMO [http://www.wmo.int/gfcs/climandes]), a demand study conducted with Peruvian farmers indicated a large interest in seasonal climate information for agriculture. The study further showed that the required information should by precise, timely, and understandable. In addition to the actual forecast, two complex measures are essential to understand seasonal climate predictions and their limitations correctly: forecast uncertainty and forecast skill. The former can be sampled by using an ensemble of climate simulations, the latter derived by comparing forecasts of past time periods to observations.