Robust impact model projections in mountains: downscaling approaches, calibration strategies, model intercomparisons and uncertainty assessments
Impact models are fundamental tools to predict future changes in the mountain hydrosphere, cryosphere, and biosphere. Their projections form the backbone of climate adaptation policies. It is therefore crucial that their uncertainties are well constrained and communicated to stakeholders. However, recent studies have shown that the uncertainties provided by individual impact models are likely to be underestimated, not least because of a tacit agreement that most of the uncertainty stems from climate projections.
In this session, we aim to bring together impact model users and developers from all disciplines of mountain science to discuss the difficult topic of uncertainty. We welcome contributions around the following topics:
– dynamical and statistical downscaling approaches
– parameter uncertainty quantification
– model intercomparisons
– communicating uncertainties
– identification of key gaps to reduce and quantify uncertainty
This session is open to anyone interested in an exchange of experiences and struggles with uncertainty in complex mountain settings.
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Full Title: Robust impact model projections in mountains: downscaling approaches, calibration strategies, model intercomparisons and uncertainty assessments
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First Author: Fabien Maussion
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Co-Authors: Lilian Schuster, Shawn Marshall and Martin Ménégoz
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Assigned Synthesis Workshop: 3. Challenges in implementing the Sendai Framework in Mountain Environments
Keywords: impact models, climate projections, uncertainty, precipitation, glaciology, hydrology, ecology