Skill assessment of seasonal forecasts for crop breeding in the Nordic and Baltic region

In Northern Europe, crop growth conditions are specific due to harsh local climate and day length. The NorBalFoodSec project aims at increasing food security in the Nordic and Baltic regions by increasing knowledge on how to better adapt crop breeding and agricultural production to future climates. As part of the project, tailored seasonal climate forecasts relevant for agri-food production are developed and issued to crop breeders to improve the quality of crop management. The limitations in predictability of key variables for growing season, i.e. temperature and precipitation, are investigated and the findings presented.  We have post-processed and evaluated the skill of temperature and precipitation from SEAS5 seasonal forecast system from ECMWF using the CSTools package for R, which implements most of commonly used methods from the literature. These methods range from the simple bias removal to the ensemble calibration methods that correct the bias, the overall forecast variance and the ensemble spread. In addition, we have explored EMOS (nonhomogeneous regression) that makes it easier to add additional information. For precipitation, downscaling methods from CSTools were also explored.  

The skill of the forecasts varies depending on the season and the temporal and spatial aggregation of the forecast data. The use of different verification measures also leads to different estimates of how long the forecast is still skillful: Simpler, non-proper, measures, such as anomaly correlation, indicate skillful forecasts for up to four months, while stricter, proper, measures, such as CRPS, indicate skillful forecasts for only one to two months. Therefore, engaging in discussions with users is crucial to understand what types of forecasts would be most beneficial for them. As the next step, indicators will be developed for breeders based on these variables, such as the widely used Growing Degree Days (GDD) and novel indicators tailored to specific regional needs.