Climate Modeling, Simulation and Prediction: Advances in climate modeling, simulation, and prediction techniques, including improvements in spatial and temporal resolution, parameterizations, and incorporation of feedback (land-ocean-atmosphere) mechanisms through hybrid AI-physics-based models and/or post-processing methods.

Climate Observations and Data Excellence: improving the quality, coverage, and accessibility of climate observations through innovative data integration and fusion techniques. This includes leveraging diverse observational datasets from ground-based stations, satellites, remote sensing platforms, and other sources to enhance our understanding of climate dynamics and variability.

Integrated Assessment Modeling of Climate-Economic Systems: Developing integrated assessment models that combine climate science, economics, and social sciences to evaluate the impacts of climate policies, emissions scenarios, and adaptation strategies on socio-economic systems at global, regional, and local scale.

Climate Data Visuanimation and Communication: Designing innovative data visualization and animation tools and communication strategies to effectively convey complex climate science findings to policymakers, stakeholders, and the public, fostering informed decision-making and public engagement.

Extreme Weather Events: Utilize big data to enhance our understanding of the causes and impacts of extreme weather events such as dust storms, hurricanes, droughts, heatwaves, and heavy precipitation, including their frequency, intensity, and spatio-temporal distribution.

Non-Conventional Climate Adaptation Tools: identifying, developing, and evaluating non-conventional climate adaptation tools and strategies that complement traditional approaches to enhance resilience to climate change impacts. This encompasses innovative data-driven approaches, technologies, practices, and interventions aimed at reducing vulnerabilities and enhancing adaptive capacity across various sectors.