Linking Earth Observation and Ecosystem Models in Time and Space - Enhancing Data Availability.
Lebreton, Carole; Stelzer, Kerstin; Kraemer, Uwe; Brockmann, Carsten
Brockmann Consult GmbH, GERMANY

Due to several factors (satellite revisiting time, clouds, flagged pixels...), Earth Observation cannot always deliver on a daily basis each pixel of a given region with a valid value. For a user that means that one cannot rely on daily data (when covered by the satellite), but needs to rely on weekly and sometimes even monthly means for their region of interest, in order to have a complete field to work with. Not only users, but also scientists working with numerical models often require available data for all grid cells when using Earth Observation data as forcings for their biogeochemical models.

In this context, establishing the link between Earth Observation and ecosystem models is currently supported by the European FP7 project CoBiOS and the German DeMarine project co-funded by DLR. Within CoBiOS, MERIS and MODIS data are used as forcings to the ECOHAM model of University Hamburg. In DeMarine EO data are used within a data assimilation frame provided by the Alfred Wegener Institute to the HBM model of BSH (Bundesamt für Seeschifffahrt und Hydrographie). Furthermore, we investigate different techniques for gap filling which cover simple temporal gap filling, application of the DINEOF method and investigating the potential Neural Net approach. We present here results and comparisons of these methods, as well as applications in validation and forcings for ecosystem models.

This development has important practical relevance for the operational services of Brockmann Consult (BC). BC provides through its GeoInformation services portfolio a wide range of Ocean Colour Earth Observations (EO) derived products (value-added products and thematic information) to users and partners. These products can for example be maps of Chlorophyll-a concentration, or time series at a specific location over varying time scales. Currently, we are enlarging the portfolio by establishing the link between EO data and ecosystem modelling in order to better fulfil user needs.