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ISLAS focuses on improving the understanding of the hydrological cycle by utilizing stable water isotopes to trace moisture sources and phase changes. The project aims to enhance climate models and predictions by providing new observational data from the Nordic Seas.
The hydrological cycle, with its feedbacks related to water vapour and clouds, is the largest source of uncertainty in weather prediction and climate models.
Particularly processes that occur on scales smaller than the model grid lead to errors, which can compensate one another, making them difficult to detect and correct for.
Undetectable compensating errors critically limit the understanding of hydrological extremes, the response of the water cycle to a changing climate, and the interpretation…
UNIVERSITETET I BERGEN
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