GOAPP Discussion Group, January 15, 2008
Location: Gordon Riley Conference Room, Department of Oceanography, 3rd Floor LSC
Title: Predicting Mesoscale Ocean Variability using a New Scheme for Assimilating Altimeter and ARGO Data
Discussion Leader: Yimin Liu
A computationally-efficient, sequential scheme is described for the assimilation of sea level measured by altimeters and vertical profiles of temperature and salinity measured by Argo floats. The scheme is multivariate (e.g. the assimilation of sea level influences the contribution of the hydrographic observations and vice versa) and the update is completed in a single step. The scheme also allows for (i) correction of temperature and salinity biases, and (ii) estimation of time-dependent background error covariance parameters. Two North Atlantic applications are presented to assess the skill of the scheme.
In the first application the background field is taken to be the seasonal climatology of Yashayaev~(2000) and skill is assessed by the ability to recover Argo profiles observed within a given distance of the analysis point but not assimilated. In the second application the background is a forecast made by an eddy permitting model of the North Atlantic. In this case skill is assessed by the forecast skill of the ocean model with lead times up to 60 days. For both applications it is shown that the scheme has useful practical skill when predicting mesoscale variability.
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