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.

SIRGAS reference frame realization SIR11P01

To estimate the kinematics of the SIRGAS reference frame, the Deutsches Geodätisches Forschungsinstitut (DGFI) as the IGS Regional Network Associate Analysis Centre for SIRGAS (IGS RNNAC SIR), yearly computes a cumulative (multi-year) solution containing all available weekly solutions delivered by the SIRGAS analysis centres. These cumulative solutions include those models, standards, and strategies widely applied at the time in which they were computed and cover different time spans depending on the availability of the weekly solutions. This data set corresponds to the multi-year solution SIR11P01. It is based on the combination of the weekly normal equations covering the time span from 2000-01-02 (GPS week 1043) to 2011-04-16 (GPS week 1631), when the IGS08 reference frame was introduced. It refers to ITRF2008, epoch 2005.0 and contains 230 stations with 269 occupations. Its precision was estimated to be ±1.0 mm (horizontal) and ±2.4 mm (vertical) for the station positions, and ±0.7 mm/a (horizontal) and ±1.1 mm/a (vertical) for the constant velocities. Computation strategy and results are in detail described in Sánchez and Seitz (2011). The IGS RNAAC SIR computation of the SIRGAS reference frame is possible thanks to the active participation of many Latin American and Caribbean colleagues, who not only make the measurements of the stations available, but also operate SIRGAS analysis centres processing the observational data on a routine basis (more details in http://www.sirgas.org). The achievements of SIRGAS are a consequence of a successful international geodetic cooperation not only following and meeting concrete objectives, but also becoming a permanent and self-sustaining geodetic community to guarantee quality, reliability, and long-term stability of the SIRGAS reference frame. The SIRGAS activities are strongly supported by the International Association of Geodesy (IAG) and the Pan-American Institute for Geography and History (PAIGH). The IGS RNAAC SIR highly appreciates all this support.

(Table S1) Flux gate discharge and centerline discharge of Helheim, Kangerdlugssuaq and Jakobshavn glacier, Greenland

Acceleration of Greenland's three largest outlet glaciers, Helheim, Kangerdlugssuaq and Jakobshavn Isbræ, accounted for a substantial portion of the ice sheet's mass loss over the past decade. Rapid changes in their discharge, however, make their cumulative mass-change uncertain. We derive monthly mass balance rates and cumulative balance from discharge and surface mass balance (SMB) rates for these glaciers from 2000 through 2010. Despite the dramatic changes observed at Helheim, the glacier gained mass over the period, due primarily to the short duration of acceleration and a likely longer-term positive balance. In contrast, Jakobshavn Isbræ lost an equivalent of over 11 times the average annual SMB and loss continues to accelerate. Kangerdlugssuaq lost over 7 times its annual average SMB, but loss has returned to the 2000 rate. These differences point to contrasts in the long-term evolution of these glaciers and the danger in basing predictions on extrapolations of recent changes.