Session 1 and Session 2:
While internationally coordinated efforts like the WCRP Coupled Model Intercomparison Project (CMIP) have led to significant advances in modelling and understanding the effects of climate change on global scales and in the open ocean, the climate-change induced impacts on coastal ocean regions remain poorly understood. This is because global climate models often lack the necessary scales and processes representation to properly resolve the regional dynamics and ecosystems of coastal seas. Downscaling information from global climate models enables the capture of the complex interplay between local-scale processes and larger-scale ocean/climate patterns, and to provide increasingly relevant climate change information on regional to local scales. This session will explore the challenges and technical demands of downscaling future projections for the coastal ocean, a region where land, ocean, and human populations are intricately linked. Specifically, the session will delve into best practices for downscaling, such as: - Types of downscaling methodologies, their advantages, limitation and potential pitfalls.
- Representing the tight coupling between land, atmosphere and ocean in the coastal regions; and how to proceed with forcing ocean-only models when fully consistent information for atmosphere, land and hydrology is unavailable.
- Methodologies for the effective propagation of information from global climate models to regional models.
- Bias correction approaches tailored for regional downscaling; and how to reduce propagation of unrealistic conditions from global climate models while preserving climate variability and trends.
- Restrictions on downscaling ensemble size due to computational constraints, strategies for tailoring a smaller ensemble to capture large uncertainty bounds and potential use of methods for extending the ensemble size using statistical or machine learning approaches.The session will also provide a brief overview of the goals of the "Future Coastal Ocean Climates" (FLAME) initiative and the importance of building a coordinated research community towards a Global Coastal Ocean Model Intercomparison Programme.