Towards operational Seasonal Forecasting: statistical downscaling precipitation based on analogue techniques over Iberian Peninsula

Downscaling techniques are part of post-processing tools that can improve the potential of seasonal forecast systems for planning in the water resources and agriculture sectors, providing early seasonal anomalies several months in advance (Buontempo et al., 2018). The algorithm presented here is based on analogue synoptic past model circulation variables (predictors) which are linked to the locally observed variable of interest (predictand) through the use of a Euclidean distance metric and multivariate regression. These relationships have been employed to derive, from large-scale atmospheric low-resolution variables (1º x 1º), high-resolution daily precipitation (5km x 5km), covering peninsular Spain and the Balearic Islands. As observations, the AEMET dataset ROCIO_IBEB (Peral et al., 2017) with 5 km of horizontal resolution, has been used.

To assess the performance of the algorithm, the first part of this work presents the evaluation of the ERA5 downscaled precipitation for the period 1997-2016. ROCIO_IBEB was used both to calibrate the method (1981-1996) and to validate the results (1997-2016). Moreover, the analogue techniques have been applied to different realizations of System Models across various seasons. The 20-year hindcast (1997–2016) based on 25 ensemble members has been considered as the model-climatological reference.

The validation results reveal a small bias, low RMSE values and good correspondence of percentiles. For accumulated seasonal precipitation, the following verification scores were computed: forecasted anomaly, lower and upper forecasted probabilities and the ROC area for both the lower and upper terciles. The results demonstrate an enhanced spatial resolution in the probability of occurrence relative to the raw System Models, along with high ROC area values—both spatially and in percentage terms. These findings indicate that, at least during certain seasons and over the Iberian Peninsula, the downscaling algorithm developed by AEMET adds significant value to seasonal forecasts.