Operational data assimilation and marine forecasting based on ENVISAT data covering Danish waters (2006 – 2007)
Lars Boye Hansen(1), Jacob V. Tornfeldt Sørensen(2), Anders C. Erichsen(2), Mai-Britt Kronborg(2), Janus Larsen(2) and Hanne Kaas(2)
(1) GRAS Ltd, Øster Voldgade 10, 1350 Copenhagen K, Denmark
(2) DHI Water - Environment - Health, Agern Allé 5, 2970 Hørsholm, Denmark
Marine forecasting of physical and biological variables is increasingly being used to assist decision making by authorities and industry. For this purpose, data assimilation is an ideal framework for constraining the models by measured marine variables. Earth observation sea surface temperature (SST) and chlorophyll-a data provide a unique data set in this respect. It has a high spatial resolution, but introduces the challenge of handling information that is patchy in space and irregular in time.
In this contribution we present examples of the performance of the operational forecast models for the Danish territorial waters including parts of the North Sea, the inner Danish waters and the Baltic area. Near real time SST and chlorophyll-a data are fed into the system via a simplified Kalman Filter approach, in which the dynamical model is basically performing an intelligent patch interpolation of the measured variables. Prior to the assimilation the EO data are interpreted by use of the model variables themselves and an additional surface layer turbulence description, thus transforming the measurements into the model space. The performance of the EO assimilation approach is compared to the existing operational services at both locations.
The system performance is demonstrated and compared to available in-situ measurements covering the period 2006 and 2007.
Keywords: ESA European
Space Agency - Agence spatiale europeenne,
observation de la terre, earth observation,
satellite remote sensing,
teledetection, geophysique, altimetrie, radar,
chimique atmospherique, geophysics, altimetry, radar,