Data assimilation of range-and-depth-averaged sound speed from acoustic tomography measurements in Fram Strait

Abstract

The 2010-2012 Acoustic Technology for Observing the Interior of the Arctic Ocean (ACOBAR) experiment provided acoustic tomography data along three 167-301 km long sections in Fram Strait between Greenland and Spitsbergen. Ocean sound speed data were assimilated into a regional numerical ocean model using the Massachusetts Institute of Technology General Circulation Model-Estimating the Circulation and Climate of the Ocean four-dimensional variational (MITgcm-ECCO 4DVAR) assimilation system. The resulting state estimate matched the assimilated sound speed time series, the root mean squared (RMS) error of the sound speed estimate (~0.4 m s−1) is smaller than the uncertainty of the measurement (~0.8 m s−1). Data assimilation improved modeled range-and-depth-averaged ocean temperatures at the 78°50’N oceanographic mooring section in Fram Strait. The RMS error of the state estimate (0.21°C) is comparable to the uncertainty of the interpolated mooring section (0.23°C). Lack of depth information in the assimilated ocean sound speed measurements caused an increased temperature bias in the upper ocean (0-500 m). The correlations with the mooring section were not improved as short-term variations in the mooring measurements and the ocean state estimate do not always coincide in time. This is likely due to the small-scale eddying and non-linearity of the ocean circulation in Fram Strait. Furthermore, the horizontal resolution of the state estimate (4.5 km) is eddy-permitting, rather than eddy resolving. Thus, the state estimate cannot represent the full ocean dynamics of the region. This study is the first to demonstrate the usefulness of large-scale acoustic measurements for improving ocean state estimates at high latitudes.