Ocean ensemble forecasting and adaptive sampling

Abstract

An ocean adaptive sampling algorithm, derived from the Ensemble Transform Kalman Filter (ETKF) technique, is illustrated in this Chapter using the glider observations collected during the Autonomous Ocean Sampling Network (AOSN) II field campaign. This algorithm can rapidly obtain the prediction error covariance matrix associated with a particular deployment of the observation and quickly assess the ability of a large number of future feasible sequences of observations to reduce the forecast error variance. The uncertainty in atmospheric forcing is represented by using a time-shift technique to generate a forcing ensemble from a single deterministic atmospheric forecast. The uncertainty in t..