A real-time assimilation algorithm applied to near-surface ocean winds

Anders Malmberg, Jan Holst and Ulla Holst

Centre for Mathematical Sciences
Mathematical Statistics
Lund Institute of Technology,
Lund University,

ISSN 1403-9338
Marine operations depend on the ability to forecast suddenly appearing storms and failures often cause great damage. As a part of a sea state alarm study, meteorological forecasts overlaid with satellite measurements sent to ships have been found to be a useful tool. In this paper we present a real-time assimilation algorithm that extends this tool using statistical methods. The algorithm is applied to near-surface ocean zonal wind speeds.
The meteorological model is emulated using a Kalman filter technique. Together with a spatio-temporal state-space model the filter allows us to obtain forecasts which are overlaid with satellite measurements using a kriging method. Examples of overlays together with their statistical uncertainties are presented and discussed.
Key words:
Spatio-temporal process; Kalman filter; Real-time assimilation; Near-surface ocean winds