Ocean forecast intervention using combined visualisation of oceanographic and remote sensed data

Current developments in oceanographic forecasting and remote sensing will provide potential users with such large volumes of data that it will be difficult to interpret and assimilate manually. One such user is that of the oceanographic forecaster who must control the assimilation of oceanographic data from a diverse range of sources to produce a single forecast sequence. This paper describes the development of a research prototype system, to aid the forecasters´ role and that tests new concepts in the assimilation of wide varieties of data sources including individual sensor observations, satellite imagery, ocean forecast model predictions, meteorological and tidal data. Data may be position based, area based or grid based and may vary with time. Analysis techniques have been developed which allow direct comparison of data from a variety of disparate sources