Deep learning and Process Understanding for Data-Driven Earth System Science

Tuesday 30th January 2024 17:00 CET

 

Prof. Dr. Markus Reichstein

ABSTRACT

For a better understanding of the Earth system we need a stronger integration of observations and (mechanistic) models. Classical model-data integration approaches start with a model structure and try to estimate states or parameters via data assimilation and inverse modelling, respectively. Sometimes, several model structures are employed and evaluated, e.g. in Bayesian model averaging, but still parametric model structures are assumed.Recently, Reichstein et al. (2019) proposed a fusion of machine learning and mechanistic modelling approaches into so-called hybrid modelling. Ideally, this combines scientific consistency with the versatility of data driven approaches and is expected to allow for better predictions and better understanding of the system, e.g. by inferring unobserved variables. This talk will elaborateon developments of this concept and illustrate its promise but also challenges with examples on biosphere-atmosphere exchange, and carbon and water cycles from the ecosystem to the global scale.

LECTURER SHORT CV

Markus Reichstein is Director of the Biogeochemical Integration Department at the Max-Planck-Institute for Biogeochemistry. His main research interests revolve around the response and feedback of ecosystems (vegetation and soils) to climatic variability with an Earth system perspective. Of specific interest is the interplay of climate extremes with ecosystem and societal resilience. He is addressing these topics with a combination of artificial intelligence and system modelling approaches to exploit the wealth of experimental, ground- and satellite-based Earth observations.

Markus studied Ecology with Botany, Chemistry and Computer Science as minors and obtained his PhD in Plant Ecology at the University of Bayreuth, Germany. Since 2013 Markus is Professor for Global Geoecology at the FSU Jena, and founding Director at the Michael-Stifel-Center Jena for Data-driven and Simulation Science. He is fellow within the excellence network ELLIS (European Laboratory for Learning and Intelligent Systems) and founding director of the ELLIS Unit Jena established in 2021. He has been serving as lead author of the IPCC special report on Climate Extremes (SREX), as member of the German Commitee Future Earth on Sustainability Research, and the Thuringian Panel on Climate. Recent awards include the Piers J. Sellers Mid-Career Award by the American Geophysical Union (2018), an ERC Synergy Grant (2019) and the Gottfried Wilhelm Leibniz Preis (2020).

ZOOM LINK & PASSCODE

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Meeting ID: 982 3185 0331
Passcode: 405011

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