Satellite surface colour image
Entcho Demirov's Research Page

Model simulations of North Atlantic Ocean

The development of new sampling technologies has substantially increased observation capabilities for ocean sciences during the last two decades. Presently the in-situ data streams and new satellite-borne sensors provide substantial new information on the ocean structure and dynamics. One fundamental conclusion of ocean observational studies is that the ocean environment can not be understood by studying one element in isolation. The combined effects of many processes interact in complex ways to influence the behavior of other components. The oceans are complex system where interdisciplinary problems (biology, chemistry, physics and geology) interact in a wide range - from millimeters to the size of the oceans and seconds to millenia.

The recent ocean studies also showed that no matter how comprehensive is the observing system, many aspects of ocean's behavior will be very difficult to understand solely from observations. Ocean general circulartion models made a significant advance in improving the realism of the ocean simulations over the past few decades and presently they are playing an increasingly important role in testing ideas in ocean studies. They are now widely used in scenarios studies of the response of coupled ocean and atmosphere system to global warming, studies of coupled physical and ecosystem evolution, operational ocean forecasting and prediction. Although the models become important tools in ocean studies, presently it is understood that the existing models have certain limits of accuracy of simulations and prediction of ocean characteristics. Data assimilation is an approach that aims to decrease the model uncertainty and increase the realism of model simulations. The availability of large amount of observations, and recent development in modeling and data assimilation provide unprecedented capabilities to put together a full picture, in space and time of the complex ocean. The objectives of my research projects is to implement model and data assimilation scheme for realistic ocean and sea-ice simulations and to conduct a model study of the interannual and decadal variability of the Labrador Sea.