The Greenland Ice Sheet has a total volume of 2900000 km3. In recent decades, the ice-sheet has been losing mass rapidly and has nearly doubled its contribution to sea-level rise. One main contributing factor has been the recent widespread acceleration of the tidewater glaciers that terminate in deep and narrow glacial fjords. However, our understanding of the subsurface water properties causing this acceleration has been extremely limited owing to the lack of observations around these locations. We hypothesize that while the ice-sheet is not coupled to the ocean in the current General Circulation Models (GCMs), they can still be used to improve our understanding of the subsurface warming around these regions. In this study, we first evaluate two GCMs (HADGEM2-ES and GISS-E2-R) around three tidewater glacier locations, by interpolating the high resolution CTD data to the GCM grid. Our results substantiate that GISS-E2-R performs better than the HADGEM2-ES model along the Western Margin. However, along the Eastern Margin, we find that the HADGEM2-ES model is more consistent with the observations. The modelled spatio-temporal variability of water masses was investigated in a Pre-Industrial and Historical simulation, later used to quantify the evolution of subsurface warming under a future warming (RCP 8.5) scenario. Our results show that the Kangerlussuaq glacier (shelf) is more sensitive to greenhouse gas (GHG) forcings than Helheim and Jakobshavn. With respect to the Pre-Industrial climate, the mean warming of the Kangerlussuaq shelf under the RCP 8.5 scenario is 3.76°C, which is considerably greater than Helheim (2.38°C) and Jakobshavn (1.92°C). This is predominantly driven by the subsurface Return Waters of the Arctic Atlantic which are seen to warm the most under a future warming (RCP 8.5) scenario. For each of the three simulation, we decompose the Ocean Heat Content (OHC) time-series into intrinsic oscillatory modes so as to discern and quantify the high frequency variability from the multi-year/decadal variability and trends in the OHC. Where the contribution from the high-frequency modes to the total energy contained in the OHC signal is considerable in a Pre-Industrial scenario; the Historical and RCP 8.5 derived OHC are seen to contain a very dominant low-frequency response to GHG forcings, which contains (almost) all of the energy contained in the signal. For the RCP 8.5 scenario, we infer that at Kangerlussuaq, such a response is considerably greater than other locations. Furthermore, a consistent long-term increasing trend is seen in the upper ocean heat content for Kangerlussuaq, throughout the 21st century (1.01 × 10^8 J/m^2/month), unlike our inferences from other locations. This trend is found to be an order of magnitude higher than Helheim (2.36 × 10^7 J/m^2/month) and Jakobshavn (1.27 × 10^7 J/m^2/month). Our results also indicate that sea-ice free months at the Nares Strait (A.D. 2055 onwards) allows for a relatively greater mixing of the Lincoln Sea and Baffin Bay waters, which is consistent with the decline and stagnation of the rising OHC at Jakobshavn.

Establishing an accurate global unified vertical reference frame (VRF) is a long-standing objective of geodesy. However, that objective has still not been achieved. One particular application where the lack of such a VRF is evident, is the improvement of hydrodynamic models by assimilating total water levels acquired by tide gauges. Indeed, to facilitate a straightforward assimilation requires that both the observed and modeled water levels refer to the same vertical datum. The required accuracy is high; it is expected to be in the order of 1centimeter. The best alternative VRF for the area of interest, the northwest European continental shelf, is the European Vertical Reference Frame 2019 (EVRF2019). The EVRF2019, however, still lacks complete coverage and the required accuracy. The key reason is that it is solely based on geopotential differences from spirit leveling/gravimetry, which are not available between benchmarks separated by large water bodies. This thesis exploits model-based hydrodynamic leveling to provide these differences. The specific objective is to assess the potential of including these data in realizing of European Vertical Reference System (EVRS).@en

The GRACE Follow-On mission is using classical K-Bandranging (KBR) and a new laser-ranging interferometry (LRI) method. The lattergives ranging data two orders of magnitude more accurate compared to theclassical K-Band ranging data (Dahl C et al. 2016). This gives a newopportunity for analyzing KBR noise by defining KBR noise as the differencebetween the KBR and LRI ranging data. In order to get a realization of KBR noise, the KBR andLRI epochs should be aligned and outliers have to be removed. An interpolation on the LRI data to make the LRI epochsaligned with the KBR epochs did not give sufficient results. Therefore only theoverlapping epochs were used as input for the next step of outlier detection, atotal of 2,250,000 epochs. The outlier detection method starts by taking theabsolute difference between the KBR and LRI range-rates. The largestdifferences were investigated where the original range-rate was compared to anestimation of the true value. This ‘true’ value is found by the use of a thirddegree polynomial function through the six range-rates that lie next to thesuspected outlier. The outlier detection method removes LRI range-rates thatdiffer more than 2.0*10-8 m/s from the estimated true value and KBRrange-rates that differ more than 7.7*10-7 m/s. 3764 LRI epochs and362 KBR epochs were labelled as outliers. After the outlier detection a histogram was made for theKBR range-rate noise. It was found that in order to get a normal distributionof KBR range-rate noise, the interval had to be in the range of <-3*10-7 m/s, 3*10-7m/s>. 59,000 still fell out of this noise range. 54,000 of these pointsformed 10 major clusters together where a subtraction of the KBR and LRIrange-rates did not give a realization of noise, but a trend similar to theoriginal signal and are therefore likely related to a clocking error. These54,000 points were therefore also removed from the dataset. To the remaining KBR range-rate noise values a thresholdof 3  was applied, removing an additional 4972 noisevalues that were larger than 4.03*10-7 m/s. Finally , an estimation of the PSD of the KBR range-ratenoise  was made and compared to an oldPSD image of December 2008 of  the GRACEmission. The PSD plot of this project shows three peaks between 10-4Hz and 10-3 Hz. These peaks are not present in the PSD plot found inliterature of the GRACE mission. Except from the second and the third peak, thePSD values of the KBR range-rate noise of this project were lower, up to twoorders of magnitude in the lower frequency range (around 10-4 Hz)and one order of magnitude in the higher frequency range (around 10-1Hz).

Accurate estimates of terrestrial water storage variations (TWSV) are critical for a variety of applications, e.g., model calibration and climate studies. This study aims to find the added value of river run-off data for regularizing GRACE mascon solution, from which TWSV can be estimated. Most subbasins of the Mississippi Basin show an exponential relationship between run-off and TWSV with moderate to good predictive value. The mean value of the explained variance (R^2) for the models is 0.4, when excluding the Lower Mississippi and Middle Missouri subbasins the mean value increases to 0.5. The Lower Mississippi and Middle Missouri subbasins are the only subbasins with no clear correlation between run-off and storage, most likely due to aquifer depletion. Since ready-to-used GRACE mascon solutions cannot be modified, the mascon method developed at the Geoscience and Remote Sensing Department of the Delft University of Technology is used in this study. This study proposes modifications to tailor this method to the Mississippi Basin and mass anomalies of hydrological origin. After applying standard Tikhonov regularization, the exponential relationship is used to determine the most probable model outcome for each subbasin, adding a new term to the estimator. The resulting GRACE mascon solutions (Tikhonov and run-off regularized solutions) have a root-mean-square deviation (RMSD) of around 3.5 cm when compared to ready-to-use mascon solutions from the Jet Propulsion Laboratory and Goddard Space Flight Center. The run-off regularized solutions show smaller deviation (on average 7 %) than the Tikhonov regularized solutions with respect to an independent validation data set. The largest difference between the Tikhonov and run-off regularized solutions occur in the dryer subbasins (Platte, Middle, and Upper Missouri, and Upper Mississippi subbasin). These areas show a stronger inter-annual trend in TWSV, these trends are captured better by the run-off regularized solutions. Additional research, co-estimating the regularization bias, shows that the run-off regularized solutions induce less bias into the solutions. This study shows that using run-off data when processing GRACE data could be of added value, especially in semi-humid to arid areas, since the TWSV in these areas is more susceptible to inter-annual variations.