Improving Alpine Flood Prediction through Hydrological Process Characterization and Uncertainty Analysis

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As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

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ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

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Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

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Flood, farms and credit: The role of branch banking in the era of climate change

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Using Iran's unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietar ...

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The role of secondary ice production in mixed-phase clouds

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Clouds are omnipresent in the Earth's atmosphere. Their phase composition significantly modulates their interaction with solar and terrestrial radiation, as well as precipitation formation. Particularly for clouds containing both phases, known as mixed-pha ...

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The surface mass balance (SMB) of large polar ice sheets and of snow and ice surfaces in general are incompletely understood because of the complexity of processes involved. One such process, drifting and blowing snow, has only been considered in a very si ...

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Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results

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Accurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban-focussed la ...

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Improved extended-range prediction of persistent stratospheric perturbations using machine learning

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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

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eLIFE SCIENCES PUBL LTD2023

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