SUNSET: SUbseasoNal to decadal climate forecast post-processIng and asSEssmenT suite

Climate services that rely on the provision of climate forecasts at sub-seasonal, seasonal or decadal time scales (S2S2D) are widely exploited these days. To make them helpful for decision-making, state-of-the-art climate forecast model outputs are tailored to user needs. The conjunction of scientific knowledge and scientific exploration to fulfil users' needs determines the post-processing workflow, from selecting the datasets to visualising the product. 

Consequently, scientists need to perform different combinations of possible workflows to evaluate the quality of the final products, ensuring the results are meaningful and that best practices (such as cross-validation strategies) are followed. For instance, essential climate variables (ECVs) can be calibrated before computing an indicator, or the indicator based on ECVs could be calibrated instead. Furthermore, several combinations of forecast systems and observation-based datasets can be explored to provide the most convenient product. On the other hand, the required computational resources can be a limitation depending on the total data size involved in the post-processing workflow.

To efficiently and flexibly handle all the requirements when exploring and delivering climate services based on S2S2D predictions, the Earth Sciences department of the Barcelona Supercomputing Center has developed the SUbseasoNal to decadal climate forecast post-processIng and asSEssmenT suite, so-called SUNSET. This suite takes advantage of existing software packages and tools (such as startR, CSTools, s2dv, CSDownscale and Autosubmit) to facilitate the definition of the workflow and its parallelisation on HPC machines when available.

To tailor climate products for each application and sector (e.g. agriculture, energy, water management, or health), the scientist can decide on the post-processing required steps, such as region selection, regridding method and resolution, anomaly calculation, and downscaling and bias-adjustment methods. SUNSET also allows the creation and visualisation of climate forecast products, such as maps for the most likely tercile. It performs the verification of the products using deterministic and probabilistic metrics, which can be visualised with maps and summarised with scorecards. The storage of final numerical outputs is also designed to consider the need to be ingested by third-party applications or impact models.

SUNSET is available in a public repository licensed under the GPLv3 license, and it is under continuous development. The suite is being used in scientific projects such as CERISE, where the next generation of the Copernicus Climate Change Service seasonal climate forecasts are under development.