Observability of Flow-Dependent Structure Functions for Use in Data Assimilation

Abstract One of the objectives of data assimilation is to produce initial conditions that will improve the quality of forecasts. Studies on singular vectors and sensitivity studies have shown that small changes to the initial conditions can sometimes lead to exponential error growth. This has motivated research to include flow-dependent structures within the assimilation that would have the characteristics to correctly predict the growth or decay of meteorological systems. This relates to the characterization of precursors to atmospheric instability. In this paper, the observability of such structures by observations is discussed. Several studies have shown that deploying observations over regions where changes in the initial conditions may impact the forecast the most do not lead to the expected benefit. In this paper, it is shown that given the small magnitude of the signal to be detected, it is important to take into account the accuracy of the observations. If the signal-to-noise ratio is too low, obs...