Designing and Building Cutting-Edge Technology
To achieve these objectives, EXPECT utilises advanced climate simulations, Earth observations, and machine learning techniques to bridge existing knowledge gaps related to atmospheric circulation and land-atmosphere interactions, and their roles in driving extreme weather and climate events. The project leverages recent investments in high-resolution climate models and Earth observation data, and it develops tools that can efficiently analyse large and diverse datasets sourced from various institutions.
Advancing Data Science Capacity and Climate Research
EXPECT also aims to enhance data science skills by ensuring wide access to knowledge and technology, promoting further exploitation of the project’s developments, and incorporating new machine learning methodologies. By training the next generation of climate researchers, EXPECT will generate long-lasting scientific and technological advancements that benefit society and support the global climate science community.
4 key themes
EXPECT is structured around four key themes, each tackling a specific aspect of climate research—from bridging different data sources to generate new climate knowledge and enhancing predictions to understanding and predicting climate hazards and building the infrastructure necessary for efficient data analysis. Through these themes, EXPECT aims to bridge the gap between new and existing data and cutting-edge scientific insights, ultimately helping society better respond to the challenges of a changing climate.
Underpinning infrastructure for the efficient and flexible analysis of large climate datasets
ClimateResearchNet
EXPECT is a member of the ClimateResearchNet, a dynamic network dedicated to enhancing the communication of climate science and ensuring that research findings reach policymakers, businesses, and society more efficiently.