WP5: Drift Modelling and Prediction
For activities in Arctic waters or to predict the drift of icebergs, oil-spills and other pollutants, forecasts of ocean currents, sea surface temperature, the position of the sea-ice edge, and weather forecast are important.
CIRFA improves short-term ocean and weather forecasts for Norwegian coastal and offshore areas and quantifies their uncertainty.
Ocean, sea ice and weather forecasts at high latitudes are challenging due to few observations of oceanic ‘weather’. One way to resolve the lack of observations is including (assimilating) high-resolution satellite data into ocean and sea ice models.
Because of observational uncertainties, the forecasts have to be probabilistic; presenting a range of possible outcomes based on multiple slightly different model runs – also known as ensemble prediction systems (EPS).
Hence, CIRFA is developing new algorithms for data assimilation and ensemble forecasting that may become part of operational ocean and weather forecasts. Forecasting models that are currently used by MET Norway are adapted and tested in their new configurations.
Quantification of forecast skill in ocean current predictions from the Barents-2.5 EPS.
Improving SAR-based wind retrieval algorithms in polar low and extreme wind situations.
Application of the Ensemble Kalman Filter data assimilation scheme in the regional ocean and ice forecast model Barents-2.5.
Application of ensemble forecast methods in trajectory modeling.
Assimilation of sea surface temperature observations from various platforms in the coastal forecast model NorKyst.
The impact of observations in a high-resolution ocean assimilation system for the Norwegian coastal and shelf seas