Description: The movement of large masses, originating from hydrological and oceanographic variations, causes detectable variations in gravity and surface deformation. These may be detected by satellite gravimetry and a network of permanent GPS stations respectively. Alternatively, additional information on ocean bottom pressure(OBP) variations may be retrieved from simulations. Joint inversions offer a way to combine different data sources in order to obtain improved estimates of surface loading. This technique can be used to compensate for weaknesses in one dataset, by the strengths of the others. But what happens when one datasets is taken out of the equation? Here, we compute a joint inversion using a GPS+GRACE+OBP combination. Additionally, we purposely deteriorate the solution by removing either data from GRACE or OBP. The accuracy and resolution of the solutions is discussed. Furthermore, regions are identified where the restricted inversion is consistent with the full inversion, and where the results show strong hydrological signals.

Description: Using individual data sources, the retrieval of geocenter motion remains challenging. Geocenter motion retrieved from GPS range measurements are sensitive to errors induced by orbit modelling. On the other hand, Satellite Laser Ranging (SLR) measurements are generally more accurate but its observational groundnetwork is sparse compared to GPS. An additional problem is that the movement of the groundstations (GPS/SLR) is strongly affected by surface loading which have spatial resolutions finer than that what can be resolved by GPS/SLR alone. In contrast to GPS and SLR, GRACE cannot resolve geocenter motion directly. It does however play a crucial role in reducing the spatial aliasing of loading signal in sparse networks. In this study we investigate a surface loading inversion with GRACE+GPS+SLR data to solve for low degree surface loading, including geocenter motion. We quantify how SLR data are weighed against GPS and GRACE, and discuss the potential benefits of this approach. Geocenter motion estimates from other GPS+GRACE combinations are additionally presented for comparison. Furthermore, we investigate the changes from using the upcoming release GFZ RL05 GRACE data in the inversion.

Description: Using individual data sources, the retrieval of geocenter motion remains challenging. Geocenter motion retrieved from GPS range measurements are sensitive to errors induced by orbit modelling. On the other hand, Satellite Laser Ranging (SLR) measurements are generally more accurate but its observational groundnetwork is sparse compared to GPS. An additional problem is that the movement of the groundstations (GPS/SLR) is strongly affected by surface loading which have spatial resolutions finer than that what can be resolved by GPS/SLR alone. In contrast to GPS and SLR, GRACE cannot resolve geocenter motion directly. It does however play a crucial role in reducing the spatial aliasing of loading signal in sparse networks. In this study we investigate a surface loading inversion with GRACE+GPS+SLR data to solve for low degree surface loading, including geocenter motion. We quantify how SLR data are weighed against GPS and GRACE, and discuss the potential benefits of this approach. Geocenter motion estimates from other GPS+GRACE combinations are additionally presented for comparison. Furthermore, we investigate the changes from using the upcoming release GFZ RL05 GRACE data in the inversion.

Description: Since their development in the 1970s Pressure Inverted Echo Sounders (PIES) have been used to address numerous oceanographic questions. PIES measure ocean bottom pressure and acoustic round trip travel time which is a vertically integrated function of density. Since 2003 the Alfred Wegener Institute (AWI) operates an array of six PIES along the Good Hope line south of Africa. The Good Hope line is a ground track of satellite altimeter Jason 1 and 2 across the Antarctic Circumpolar Current (ACC) and the PIES were deployed at cross over points of the ascending and descending track. The rst part of this thesis uses the Gravest Empirical Mode (GEM) method to derive Sea Surface Height (SSH) anomalies and baroclinic ACC transport. The derived total SSH anomalies were compared to two different satellite altimetry product. The AVISO product is a smoothed and gridded combination of data from different satellites while the openADB database provides the along track measured data without any smoothing or gridding. The correlation of the total (broclinic+barotropic) SSH anomaly with satellite altimetry results higher correlation coecients for the gridded AVISO product (0.33-0.92) compared to the along track openADB (0.24-0.92) product. Dividing the total SSH anomaly into baroclinic and barotropic part results a contribution of the barotropic component in the order of 30-60%. The highest barotropic components are found inbetween the fronts. Calculating the baroclinic ACC transports results a mean of 147± 2.4 Sv for the deployment period 2007-2008 and 142±1.9 Sv respectively for the period 2008-2010. Both the mean and standard deviation compare well with previous observations and model results. In conclusion the PIES derived SSH anomaly showed a significant contribution of the barotropic component to the total variability and a better correlation with the (smoother) gridded satellite altimetry product. The derived baroclinic ACC transport is in close agreement with previous measurements. It canbe derived with higher temporal resolution than in previous studies. The second part of this thesis investigates how insitu ocean bottom pressure (OBP) can improve a least square inversion of GPS (Global Positioning System) data, GRACE (Gravity Recovery and Climate Experiment ) data and modeled OBP used to derive global ocean mass changes. The inversion combines the information provided the different datasets and ts a mathematical model through it. The difference between the model and the data is minimized in a least square sense. The inversion with in-situ OBP locally improves the correlation with the Bottom Pressurerecorders (BPRs) but does only slightly in uence global parameters like the global mean ocean mass or the geocenter motion. In conclusion there are to less BPRs which are furthermore irregular distributed in time and space to significantly improve the inversion.

Description: To study the Antarctic Circumpolar Current (ACC) volume transport several cruises have taken place. The results of these cruises show snapshots without information about the time variability. To investigate the time variability of the ACC the Alfred Wegener Institute operates an array of Pressure Inverted Echo Sounders (PIES) along a satellite altimeter ground track south of Africa. PIES monitor ocean bottom pressure and acoustic travel time across the water column. A Gravest Empirical Mode (GEM, Meinen and Watts 1998) was applied to determine the geostrophic transport between the PIES. These time series were used to compute a transfer function between satellite Sderived transport and geostrophic transport. Satellite altimetry offers the possibility to calculate ACC transport between 1992 and 2010. A mean transport of 115 Sv and a variability of 7 Sv were derived for the Topex/Poseidon, Jason 1 and Jason 2 time period. A wavelet analysis shows that the ACC transport highly correlates with the winter and spring SAM index, whereas a direct correlation on a monthly scale could not be shown.