Assimilating en-route Lagrangian observations

We investigate the assimilation of data that are collected while Lagrangian ocean instruments are in transit between surfacings. We introduce an observation operator that takes these data into account in addition to the data that are typically assimilated. A key point is that the subsurface, en-route paths of these ocean instruments are estimated as part of the assimilation scheme. We present a twin experiment model scenario that lets us compare the improvement by assimilating en-route data over traditional data alone. We make this comparison and present results for both sequential filtering and smoothing.