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 |