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.

Static GPS measurements and elevation model in the hinterland of Neumayer

As part of the CryoSat Cal/Val activities and the pre-site survey for an ice core drilling contributing to the International Partnerships in Ice Core Sciences (IPICS), ground based kinematic GPS measurements were conducted in early 2007 in the vicinity of the German overwintering station Neumayer (8.25° W and 70.65° S). The investigated area comprises the regions of the ice tongues Halvfarryggen and Søråsen, which rise from the Ekströmisen to a maximum of about 760 m surface elevation, and have an areal extent of about 100 km x 50 km each. Available digital elevation models (DEMs) from radar altimetry and the Antarctic Digital Database show elevation differences of up to hundreds of meters in this region, which necessitated an accurate survey of the conditions on-site. An improved DEM of the Ekströmisen surroundings is derived by a combination of highly accurate ground based GPS measurements, satellite derived laser altimetry data (ICESat), airborne radar altimetry (ARA), and radio echo sounding (RES). The DEM presented here achieves a vertical accuracy of about 1.3 m and can be used for improved ice dynamic modeling and mass balance studies.

Static GPS measurements in the vicinity of EDML and an elevation model for Dronning Maud Land

The knowledge of ice sheet surface topography and the location of the ice divides are essential for ice dynamic modeling. An improved digital elevation model (DEM) of Dronning Maud Land (DML), Antarctica, is presented in this paper. It is based on ground-based kinematic GPS profiles, airborne radar altimetry, and data of the airborne radio-echo sounding system, as well as spaceborne laser altimetry from NASA's Ice, Cloud and land Elevation Satellite (ICESat). The accuracy of ICESat ice sheet altimetry data in the area of investigation is discussed. The location of the ice divides is derived from aspect calculation of the topography and is verified with several velocity data derived from repeated static GPS measurements.