PICO
The increasing availability of remotely sensed observations, combined with advances in computational capacity, is driving modelling and observational glacier studies towards increasingly large spatial scales. Such large-scale perspectives are of particular relevance, as they impact cross-country policy decisions and shape public discourse. Glaciers play a key role in present-day sea-level rise, seasonal water availability, natural hazards susceptibility and in touristic attractiveness. To tackle the spatial challenge, AI-informed techniques have become of particular interest in terms of computational feasibility, both for data processing and modelling.
This session focuses on advances in observing and modelling mountain glaciers and ice caps at the regional to global scale. We invite both observation- and modelling-based contributions, which may include, but are not limited to, the following topics:
• Observation and modelling results that reveal previously underappreciated regional differences in glacier changes or in their dynamics.
• Large-scale impact studies, including glacier contribution to sea level change, susceptibility to natural hazards or changes in water availability from glacierised regions.
• Advances in large-scale modelling (reconciling machine learning (ML) with classical approaches, including physical processes, improving/extending strategies for data assimilation/inverse approaches, refining climatic downscaling, increasing representativeness, etc.)
• Advances in large-scale monitoring (ML-boosted monitoring and interpretation, multi-sensor homogenisation, meta-analysis of ground-based data, process inferences, etc.)
• Development and dissemination of regional to global glacier datasets.
Thomas Shaw