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  • title: Comparing Data-Driven and Mechanistic Models for Predicting Phenology in Deciduous Broadleaf Forests
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            Comparing Data-Driven and Mechanistic Models for Predicting Phenology in Deciduous Broadleaf Forests
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            Comparing Data-Driven and Mechanistic Models for Predicting Phenology in Deciduous Broadleaf Forests

            Dec 15, 2023

            Speakers

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            Christian Reimers

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            DHR

            David Hafezi Rachti

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            GL

            Guohua Liu

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            About

            Understanding the future climate is crucial for informed policy decisions on climatechange prevention and mitigation. Earth system models play an important rolein predicting future climate, requiring accurate representation of complex sub-processes that span multiple time scales and spatial scales. One such process thatlinks seasonal and interannual climate variability to cyclical biological events istree phenology in deciduous forests. Phenological dates, such as the start andend of the growing…

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            NeurIPS 2023

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