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Hybrid modeling of evapotranspiration: Inferring stomatal and aerodynamic resistances using combined physics-based and machine learning

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ElGhawi,  Reda
IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Max Planck Society;
Atmosphere-Biosphere Coupling, Climate and Causality, Dr. Alexander J. Winkler, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Kraft,  Basil
Global Diagnostic Modelling, Dr. Martin Jung, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Reimers,  Christian
Atmosphere-Biosphere Coupling, Climate and Causality, Dr. Alexander J. Winkler, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Reichstein,  Markus
Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Winkler,  Alexander
Atmosphere-Biosphere Coupling, Climate and Causality, Dr. Alexander J. Winkler, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

ElGhawi, R., Kraft, B., Reimers, C., Reichstein, M., Körner, M., Gentine, P., et al. (2022). Hybrid modeling of evapotranspiration: Inferring stomatal and aerodynamic resistances using combined physics-based and machine learning. ESSOAr. doi:10.1002/essoar.10512258.1.


Cite as: https://hdl.handle.net/21.11116/0000-000A-F1B4-A
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