We discuss a simple ensemble spread method, a local Pa method that includes different observational errors in the selection, and a method combining both, all of which belong to the ensemble based techniques. They are based on output from the Local Ensemble Transform Kalman Filter (LETKF, Hunt, 2005), which is an accurate and efficient type of ensemble Kalman filter. These methods have already been proven to be accurate and efficient in Lorenz-40 variable model (Liu et al., 2006). With 15 ensemble members, they reach smaller analysis error than that of singular vector method implemented with a 1024 member ensemble Kalman filter method (Hansen et al, 2000).
Here, we further explore these different adaptive strategies on the SPEEDY model (Molteni, 2003), which is a primitive equation global model with a simple but complete set of physical parameterizations. We will compare these strategies with the system used at NCEP for operational adaptive observations (ETKF), evaluating these strategies in selecting the optimal flight routes rather than single targets. With this realistic model we will explore the use of interactive adaptive observation strategies for satellite observing systems including “observing 10% of the area to obtain 90% of the impact” as required for future lidar wind instruments. The best strategies to follow for tropical and extratropical adaptive observations, which may be quite different, will be also explored.