EXPECT will identify and quantify the mechanisms by which physical processes govern regional climatic changes, including extremes, on inter-annual to multi-decadal time scales. It will do so by exploiting newly available climate simulations and Earth Observations (EOs), and by combining machine learning (ML) with physical methods. The research targets fundamental knowledge gaps related to atmospheric circulation and land-atmosphere interactions, which represent major limitations in current climate predictions and projections, and in particular in understanding changes in European summer extremes. To underpin the research, and benefitting the wider research community, EXPECT develops tools to efficiently analyse a variety of large data sets in combination that are hosted in different repositories across institutions. This facilitates the exploitation of recent investments into high-resolution climate models and EO data. EXPECT further builds data science capacity for the scientifically robust, efficient and reproducible analysis of the massive data assets, including novel ML approaches, and provides training for the climate science community and the next generation of researchers in particular. EXPECT will thus deliver significant scientific and technological advances for society and the climate science community that will last well beyond the project, in support of WCRP’s strategic objectives.
Responding to a call to “Further climate knowledge through advanced science and technologies”, the primary pathway to impact is the generation of new understanding and knowledge, and to publish the results in the peer-reviewed scientific literature to make it available for IPCC and other climate assessment reports. In addition, the project develops new technology for data analysis and an Open Science Platform to enable the wider climate science community beyond the project. We also have a strong focus on communicating the outcomes to policy-makers and the public.
