Improve our comprehension of the mechanisms driving the climate variability in the Mediterranean region, and especially those at the basis of the tropical and extratropical as well as polar and mid-latitudes teleconnections, and their impact on the predictability at different time scales (seasonal-to-decadal).
A thorough evaluation of the state-of-the-art climate forecast systems and of the most recent and comprehensive observational databases will provide information on the main sources of predictability for surface climate variables over the Mediterranean and how these are captured by models. Sensitivity studies with improved or idealized representations of boundary components (land surface, tropical oceans) in participating GCMs, will help to assess key processes, including teleconnections, in climate predictability over the target region. The process-understanding analysis will underpin the development of advanced forecast post-processing methodologies, i.e. calibration, regionalisation, automatic and objective selection… Another fundamental goal will be the development of empirical forecast systems based on the analyses of the predictability sources and tailored for specific applications.
Provide a set of generalized methods and ready-to-use tools for forecast verification and comprehensive skill assessments – including those for user-oriented applications – for downscaling, calibration and bias adjustment of the forecasts, and develop methodologies of optimal forecast combination to provide a single source of information.
Such tools will be freely available and addressed to practical users from both public and private sectors. The project will refine state-of-the-art methodologies to extract relevant information from dynamical climate prediction systems and assess their robustness and uncertainty. This includes correcting for model systematic errors on the basis of process-understanding, extracting reliable model information for user-relevant variables at user-relevant scales, extensively comparing different sources of climate information from both dynamical and empirical prediction systems and combining and synthesizing these sources of climate information into a reduced set suitable forecasts for applications.
Provide prototypes of climate services products based on end-user tailored climate forecasts at seasonal and multi-annual timescales, in relevant economic sectors for the Mediterranean, such as wind energy, water management (hydrology), and agriculture and forestry (and fire risk).
In particular, forecasts of variables and indicators relevant to the considered sectors will be provided by applying the tools and the methods (downscaling, calibration, bias correction, forecast combination) developed in the project. The design of such climate service prototypes will benefit from previous projects results such as EUPORIAS, MOSES, CLIM-RUN, etc. During MEDSCOPE, users’ satisfaction and feedback will be evaluated to ensure that the prototypes meet the community needs (primarily MedCOF), building upon the partners’ experience on social science applied to climate services (e.g. FP7 EUPORIAS, and Copernicus-EU SECTEUR and QA4Seas).