Naoki Mizukami Associate Scientist, National Centre for Atmospheric Research (NCAR), Boulder, United States

Title: CMIP based hydrologic projection in the Pacific Northwest for Hydrologic System Vulnerability Assessments

Abstract: Climate data from the Coupled Model Intercomparison Project-Phase (CMIP) is increasingly used for regional and national water infrastructure planning under future climate scenarios. The climate-hydrologic modeling chain, which produces high-resolution hydrologic projections, begins with selecting multiple Earth System Models (ESMs), followed by downscaling the ESM outputs to kilometer-scale resolution, and using  the downscaled climate data to derive hydrologic model(s). Each step offers various methodological options–such as different ESM selections, downscaling methods, and hydrologic models–enabling producing ensemble, century-long hydro-climate traces for use for water resources impact assessment, such as reservoir simulations. This work aims to produce approximately 30 ensemble hydrologic traces from 1950 to 2099 across river reaches in the US Pacific Northwest. These support vulnerability assessments and resilience planning for many reservoirs of the US Army Corps of Engineers and its regional partners. A key novelty in our modelling chain is the use of a computationally efficient dynamical weather modelling for downscaling, rather than traditional, statistical methods. Additionally, we apply a calibrated, catchment based hydrology-river model to simulate river discharge at ~10 km scale river reaches. This presentation will show evaluation of historical streamflow simulations at ~ 200 reference river flow sites, and characterise future hydrologic variability and extremes. Our main focus is on assessment of projected change in high flow and flow seasonality and its uncertainty at inflow points for major reservoirs in the Pacific Northwest. Our findings suggest that increases in high flow exceed annual or seasonal mean, indicating intensification of extreme flood events under future conditions. We will also demonstrate how these projections are used for reservoir modelling for planning.

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Jamel Chahed Professor, University of Tunis El Manar, Tunisia

Title: Climate Modelling Beyond Prediction: Reinforcing a Phenomenological Perspective on Uncertainty and Responsibility

Abstract: This presentation offers a reflection on the core arguments and insights developed in the article “Advanced Climate Modeling Frameworks: State-of-the-Art Techniques, Uncertainties, and the Principle of Responsibility” (Modeling Earth Systems and Environment, July 2025). Beyond summarizing technical advancements in GCM-ESM coupling, sub-grid parameterization, downscaling, ensemble models processing, and the integration of data-driven and AI, the presentation will emphasize a key conceptual proposition: the need to reinforce a phenomenological interpretation of climate models. Rather than viewing models merely as predictive machines, they are approached as cognitive instruments shaped by assumptions, simplifications, and epistemological commitments. The talk will explore how this perspective reframes current debates around uncertainty, bias correction, ensemble strategies, and hybrid physical-AI architectures. It argues that phenomenological awareness enhances not only model interpretability but also scientific integrity, especially when model outputs influence policy and risk communication. Several recommendations will be discussed, including: improving transparency in how sub-grid processes are conceptualised, recognising the epistemic status of models as structured approximations rather than empirical realities, and promoting a modelling culture that combines technical rigour with interpretive humility. The presentation aims to stimulate a dialogue on how the CMIP community might further integrate reflexivity, clarity, and responsibility into modelling practices, acknowledging that better science arises not only from better algorithms, but from a deeper understanding of what modelling means.