Assimilation of sea surface temperature by MET Norway's coastal ocean forecasting model Norkyst

  • The Norwegian Meteorological Institute (MET Norway) and the Norwegian Institute of Marine Research (IMR) have developed an ocean forecasting model specifically for Norway coastal area, called Norkyst. This model enables MET Norway to provide forecasts such as Sea Surface Temperature (SST) and ocean currents, which are crucial for oil spill response, search and rescue operations, and plankton dispersion tracking. Norkyst assimilates near real-time SST products from OSI SAF catalogue to enhance its forecasting capabilities.

    • artist impression displaying the Norkyst modelisation of Norway coastal areas.
  • Figure 1: Artist's impression of the Norkyst coastal model.

  • To produce a reliable forecast, models need to assimilate observation data. Norkyst assimilate both in situ data from a wide range of sources, and satellite data. While in situ data have less bias, and are giving information closer to the coast line, the satellite data allow a wider coverage of the measurements, even from remote areas. The two are then complementary (fig 2).

    As the model is able to handle observation data at their correct time and location, the MET norway team decided to use satellite data with a few processing, provided on the native satellite swath grid (level 2P products), rather than more processed ones where the data has been spatiotemporally resampled (for instance, the data has been sampled to lower the effect of day/time variability) and the gaps mainly due to the cloud cover have been virtually filled (Level 3 and level 4 satellites products). The choice of L2P data allow as well to keep a high spatiotemporal resolution for each data.

    A specific setup of Norkyst (Norkyst_DA), with reduced horizontal resolution is used for data assimilation. It is based on Regional Ocean Modeling System (ROMS) with a physical space 4D-variational data assimilation scheme. The 2.4 km horizontal resolution was selected to match the scale of available observations, including OSI SAF products.


  • two maps showing assimilated data to Norkyst for the 10/06/2024. the upper one shows the satellite data while the lower one the in-situ data.
    assimilated SST
  • Figure 2: Assimilated surface temperature data for the 1/06/2024. | a. map displaying the 1 199 866 assimilated satellite sea surface temperature measurement. | b. map displaying the 1 740 assimilated in situ surface temperature measurement.
    (daily data available online)

  • L2P data come however with less bias corrections than the more processed ones. To overcome this, Norkyst uses data from a wide range of different satellites:

    • OSI SAF products made from the Advanced Very-High-Resolution Radiometer (AVHRR) aboard Metop-B and Metop-C (OSI-204-b, OSI-204-c and OSI-205-a)
    • EUMETSAT (headquarter) produced Copernicus products from the Sea and Land Surface Temperature Radiometer (SLSTR) aboard Sentinel-3A and sentinel-3B.
    • NOAA products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard NOAA-20 and NPP
    • JAXA products from the Advanced Microwave Scanning Radiometer 2 (ASMR2) aboard GCOM-W1

    Being a passive microwave sensor, ASMR2 give valuable observation data on cloudy condition. However, compare to the other sensors here used, which are infrared sensors, its spatial resolution is much coarser. This has to be taken into account by the model during the assimilation process. A specific mode, called supermod operator, has been introduced into the Regional Ocean Modeling System algorithm to handle that issue.

    Additionally, SST products from different satellites and sensors are subject to regional and temporal biases, originating from both retrieval process and algorithms. To handle these, AVHRR products, together with the VIIRS/NOAA-20 are assimilated, while the SLSTR ones and the VIIRS/NPP are used as reference for a SST bias correction scheme, and, together with data from drifting buoys, for data validation.

    The whole assimilation procedure has been described in a dedicated article by S.C. Iversen, A.K. Sperrevik and O. Groux.


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