A Workshop on the Role of the upper ocean in medium and extended range forecasting was held at ECMWF on 13 to 15 November 2002.
The ocean plays an important role in seasonal forecasting. The best known process is El Nino with its origins in the tropical Pacific where air-sea interaction is strong, but there is evidence emerging of partly predictable phenomena in the Atlantic and Indian oceans also. At shorter time scales, ocean-atmosphere interaction may be important in for example tropical storm prediction and the intraseasonal oscillation. With developments in the ocean observation system and in data assimilation and modelling, the potential for making and using upper ocean forecasts has improved substantially.
This meeting covered 4 main themes:
- Discussion of significant phenomena which involve air/sea coupling on the timescales from hours to months.
- The use of ocean forecasts on these timescales.
- New methods of observing the ocean and challenges in assimilating data in ocean models.
- Recent advances in ocean and ice modelling and requirements for further progress.
POAMA: Bureau of Meteorology Coupled Model Seasonal Forecast System
Dealing with systematic error in ocean assimilation
Seasonal prediction at the Met Office
Sea surface temperature modification of low-level winds
D B Chelton
Modeling sea-ice and its interactions with the ocean and the atmosphere
Impact of sea state on atmosphere and ocean
P A E M Janssen
Upper ocean model physics development
Seasonal forecasting at NASA's Seasonal-to-Interannual Prediction Project (NSIPP)
M M Rienecker
Seasonal forecasting at ECMWF
The role of the Atlantic Ocean in climate forecasting
R T Sutton
3D-Var and 4D-Var approaches to ocean data assimilation
A T Weaver
Air-sea interaction on intraseasonal timescales and its implication for the representation of the upper ocean for medium and extended range prediction
S J Woolnough
The role of the Indian Ocean in climate forecasting with a particular emphasis on summer conditions in East Asia
The MERCATOR approach to real-time ocean data assimilation and forecasting
P de Mey
Ensemble Kalman filters, sequential importance resampling and beyond
P-J van Leeuwen