Mean dynamic topography and oceanographic parameters estimated from an inverse model and satellite geodesy, with link to model result in one single NetCDF file (392 MB), including the inverse data error covariance

Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.

Oceanographic data in the Greenland Sea and around Svalbard in 1991-1993

The Arctic Ocean is connected with the North Atlantic Ocean by the Fram Strait between Greenland and Svalbard. The strait is located in the northern part of the Greenland Sea. In the eastern part of the strait, warm saline water flows northward as the West Spitsbergen Current; while in the western part, cold less-saline water flows southward as the East Greenland Current. The northwestern part of the Greenland Sea is normally covered with sea ice even in summer. Furthermore, this region is regarded as a major area where the Arctic sea ice is discharged into mid latitude oceans. Thus, this area plays an important role in heat and salt exchange processes in the Arctic marine system. The reveal exchange processes of water masses and ocean-atmosphere interaction in high-latitude oceans, a number of international research programs have been focused on the Greenland Sea and its surrounding waters. As one of the international Arctic research programs, oceanographic studies have been executed in cooperation with the Norsk Polarinstitutt and other institutes under the leadership of the National Institute of Polar Research since 1991. Japanese scientists have been carrying out field observations in and around Svalbard. The observations include not only physical measurements but also biological surveys. This report presents physical oceanographic data obtained in the Greenland Sea in 1992 and 1993, and data around Svalbard from 1991 to 1993.