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.

Kazumi Kubota Professor, Shimonoseki City University, Yamaguchi, Japan

Title: From awareness to action: A three‑lever, CMIP‑aligned roadmap to decarbonize and climate‑proof Japan’s healthcare sector.

Abstract: Healthcare faces a dual mandate: protect people from intensifying climate hazards while cutting its own footprint. Globally, healthcare produces 4%–5% of greenhouse gas emissions, largely from supply chains. England’s National Health Service has paired targets with tools—procurement standards, clinical guidance, estates upgrades, and transparent measurement—to deliver early wins. Japan now stands at an implementation frontier: a November 2025 Health and Global Policy Institute survey of 152 organizations shows high awareness but limited “how‑to” knowledge and little action. This Opinion proposes a sequenced roadmap—Education, Measurement, Incentives—aligned with CMIP’s regularly updated climate data. Priorities are climate‑health content in continuing education, a minimum viable measurement set aligned with standards, and procurement, finance, and recognition to deliver reductions and resilience within 12–36 months. Aligning operations to CMIP’s cadence can position Japan’s health sector as a credible contributor to national climate goals and provide a scalable template for others.

Zongpeng Song Senior Engineer, China Meteorological Administration, Beijing, China

Title: Projecting the evolutionary path of China’s photovoltaic potential using CMIP climate models.

Abstract: This study provides a national-scale projection of China’s photovoltaic (PV) potential by combining CMIP6 model accuracy assessment with long-term turning-point detection. Based on rate-of-change evaluation against historical observations, four models (ACCESS-CM2, ACCESS-ESM1.5, IPSL-CM6A-LR, and KIOST-ESM) are identified as most reliable, and their ensemble mean (MM4) is used to examine PV potential from 1984 to 2100. Under low- and medium-emission scenarios, PV potential shows sustained growth with turning points around 2034 and 2028. In contrast, under the high-emission SSP585 scenario, MM4 reveals a critical turning point in 2035 followed by a multi-decadal decline until 2094, driven by a dual temperature-induced constraint: direct reductions in PV module efficiency and indirect suppression of surface irradiance through enhanced water vapor and cloud optical effects. These radiative feedbacks ultimately dominate the long-term trajectory of PV potential under SSP585. Compared with MM4, the remaining models (MM11) yield more optimistic projections but likely overestimate future PV potential. Overall, the identified turning points reflect a shift from aerosol-driven brightening to warming-driven declines, underscoring the need for high-accuracy models and adaptive strategies under high-emission pathways.