C. Heuzé, G.K. Carvajal and L.E.B. Eriksson (2017), “Optimisation of sea surface current retrieval using a maximum cross correlation technique on modelled sea surface temperature“, Journal of Atmospheric and Oceanic Technology, vol 34, pp 2245–2255, doi: 10.1175/JTECH-D-17-0029.1
Prior to using retrieval algorithms on real satellite images , we here first quantify the biases introduced by various sea surface current retrieval algorithms using a modelled hourly reference sea surface temperature field. We study four European seas, two with strong currents (the North Sea and the Channel) and two with weak currents (the Bay of Biscay and the western Mediterranean Sea), over one week per season of 2016.
The main finding is that weak currents are tricky to retrieve: too small a time interval between your sea surface ‘images’ and the algorithm picks nothing; too large, and the patterns that the algorithm tries to track have already been destroyed by eddies. Regions with strong currents in contrast are very accurately retrieved, whatever the setting or the season.
This paper is related to:
- Heuzé et al. (2017c), which applies the same retrieval algorithm on actual satellite images in the Mediterranean Sea, and compares satellite-inferred currents with in-situ buoy data;
- Heuzé et al. (2015c), which uses the same bias-quantification method to evaluate algorithms used to re-gridd Argo float data in the Southern Ocean.