Numerical models are very important tools for predicting ocean parameters such as water levels and currents, waves and swell, salinity and temperature and wind and air pressure. However, these models are only accurate if they are continuously calibrated. In this respect, remote sensing data sets are extremely useful for updating the model results. Remote sensing data alone are not reliable for a continuous supply of these parameters as many images have to be discarded because of clouds, but satellite images are excellent for providing calibration input for numerical models. This is because the satellites collect data instantaneously from large areas and because parameters such as sea surface, wide speed etc. can be derived with a high accuracy.

GRAS is providing near real-time Sea Surface Temperature to numerical forecasting models run by the DHI – Water & Environment. The Sea Surface Temperature maps are assimilated into the model to correct or adjust the model output. Chlorophyll-a data can also be assimilated into ocean models.  Click here to get more information about the Waterforecast.

Data before assimilation

Data after assimilation

Remote Sensing data input