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DFG-project FOR2131

The DFG-funded research unit FOR2131 (“Data assimilation for improved characterization of fluxes across compartmental interfaces”) develops data assimilation methods to most accurately predict states, parameters, and fluxes in the coupled subsurface-land surface-atmosphere system including the identification of the most sensitive observations, upscaling and downscaling approaches, and model scaling in order to arrive at integrated models that are operable with these methodologies.

Data assimilation is a methodology to optimally merge measurements and model simulations on the basis of mathematical-statistical principles. Novel in this project is that a data assimilation framework is developed for a model that includes the subsurface, land surface and atmosphere. This implies that observations made in a certain terrestrial compartment (for example land surface) also can improve states for other terrestrial compartments (for example subsurface). This is called coupled data assimilation. Data value will be an important topic in the project. The methods will be tested on a virtual catchment (which mimics the real-world catchment Neckar), and the real-world catchment Rur. Project partners are the Universities of Bonn (Prof. C. Simmer), Hannover (Prof. I. Neuweiler), Hamburg (Prof. F. Ament), Tübingen (Prof. O. Cirpka), Augsburg (Prof. Kunstmann) and Potsdam (Prof. Attinger).


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