To quantify the turbulent transport at gray zone length scales between 1 and 10 km, the Lagrangian evolution of the CONSTRAIN cold air outbreak case was simulated with seven large eddy models. The case is characterized by rather large latent and sensible heat fluxes and a rapid deepening rate of the boundary layer. In some models the entrainment velocity exceeds 4 cm/s. A significant fraction of this growth is attributed to a strong longwave radiative cooling of the inversion layer. The evolution and the timing of the breakup of the stratocumulus cloud deck differ significantly among the models. Sensitivity experiments demonstrate that a decrease in the prescribed cloud droplet number concentration and the inclusion of ice microphysics both act to speed up the thinning of the stratocumulus by enhancing the production of precipitation. In all models the formation of mesoscale fluctuations is clearly evident in the cloud fields and also in the horizontal wind velocity. Resolved vertical fluxes remain important for scales up to 10 km. The simulation results show that the resolved vertical velocity variance gradually diminishes with a coarsening of the horizontal mesh, but the total vertical fluxes of heat, moisture, and momentum are only weakly affected. This is a promising result as it demonstrates the potential use of a mesh size-dependent turbulent length scale for convective boundary layers at gray zone model resolutions.

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Being one of the major consequences of anthropogenic climate change, sea level rise forms a threat for many coastal areas and their inhabitants. Because all processes that cause sea-level changes have a spatially-varying fingerprint, local sea-level changes deviate substantially from the global mean. As a consequence, there is no single location on the earth that is subject to the global-mean sea-level change. To understand and forecast future changes in both global and regional sea level, a thorough understanding of its major underlying processes and their regional fingerprints is necessary. Nowadays, remote sensing from satellite altimetry provides an accurate estimate of changes in sea level on global and regional scales (Leuliette et al., 2004; Nerem et al., 2010; Ablain et al., 2017). The emergence of satellite gravimetry, in the form of the GRACE mission (Tapley et al., 2004), and the global coverage of in-situ subsurface temperature and salinity observations by the Argo programme (Roemmich et al., 2009; Roemmich and Gilson, 2009) has resulted in an extensive increase of our understanding of sea-level changes over the past decade, and the reliability of the estimates of the individual processes behind sea-level changes has reached the level where we can almost fully explain the observed sea-level changes from these contributors (Rietbroek et al., 2016; Leuliette and Miller, 2009; Dieng et al., 2015; Leuliette, 2015; Kleinherenbrink et al., 2016). However, before this period the spatially-varying signals have been sampled only sparsely by in-situ observations, mainly by means of tide gauges, which limits our current understanding of sea-level changes on global and regional scales. This thesis aims to find an answer to the question whether the sum of the underlying processes that cause sea-level changes can explain the observations, not only on a global scale, which has been assessed a multitude of times (Moore et al., 2011; Church et al., 2011; Gregory et al., 2013; Jevrejeva et al., 2016b), but also on scales of individual ocean basins and coastal regions. The assessment of this so-called sea-level budget has been done for two regional cases, and for the global ocean and individual basins. Furthermore, the effect of ocean bottom deformation on the difference between relative and geocentric observations has been quantified. Finally, we have applied an alternative approach to time-series analysis, in which the various contributors of sealevel variability are co-estimated with a time-varying trend using a Kalman filter and smoother approach, on tide gauge observations.@en

In this paper we discuss our efforts to perform precision orbit determination (POD) of CryoSat-2 which depends on Doppler and satellite laser ranging tracking data. A dAll processes that affect sea level show distinct regional patterns, and therefore, sea-level changes show considerable spatial variability. This spatial variability forms a challenge when reconstructing global and regional sea-level changes from tide gauges, which are only available at a limited number of locations and are mostly located along coasts in the northern hemisphere. We can improve estimates of global and regional sea-level changes from tide-gauge records by explicitly taking the expected spatial variability into account. From estimates of global ice mass loss and land water storage changes, spatial sea-level fingerprints can be computed, which identify whether sea-level changes at specific tide-gauge locations are expected to be representative for global-mean or basin-mean sea-level changes. Furthermore, developments in altimetry and GPS now allow for reliable estimates of local vertical land motion (VLM) at an increased number of tide gauges. We reconstruct global and regional sea-level changes since 1958 by combining the expected sea-level fingerprints with observations from tide gauges and GPS stations. The spatial sea-level fingerprints associated with glacial isostatic adjustment (GIA) and present-day ice mass loss and land water storage are used to detect and correct possible biases due to the uneven spatial sampling of the tide-gauge observations. The fingerprints that emerge from GIA and present-day mass redistribution have an earth-deformation component, which is also observed as VLM. Hence, care must be taken when combining spatial sea-level fingerprints with VLM observations to avoid double-counting of solid-earth deformation. By separating observed land motion into known and unknown sources, this double-counting is avoided. For most ocean basins, the reconstructed sea-level changes can be explained by the combined effects of GIA, present-day mass redistribution, and ocean density effects. A substantial part of the observed decadal variability can be explained by ocean density variations, while trends and accelerations are mostly driven by ice and land water storage changes. The only exception is the South Atlantic Ocean. In this basin, reconstructed sea level cannot be reconciled with the underlying processes, which is probably related to the sparse tide-gauge coverage in this region. When the regional sea-level estimates are merged into a global-mean estimate, we find a GMSL trend of 1.5 0.2 mm/yr, and an acceleration of 0.07 0.02 mm/yr2. Both the global-mean trend and the acceleration can be explained by the sum of contributing processes, and hence, the global sea-level budget since 1958 can be considered closed without requiring a contribution of deep-ocean thermal expansion or pre-1990 Antarctic mass loss, although substantial uncertainty remains due to the sparsely-observed South Atlantic Ocean. ynamic orbit model is set-up and the residuals between the model and the tracking data is evaluated. The average r.m.s. of the 10 second averaged Doppler tracking pass residuals is approximately 0.39 mm/s; and the average of the laser tracking pass residuals becomes 1.42 cm. We discuss three improvements that have brought the orbit accuracy to this level, it concerns the way we implement temporal gravity accelerations observed by GRACE; the implementation of ITRF2014 coordinates and velocities for the DORIS beacons and the SLR tracking sites. We also discuss an adjustment of the SLR retroreflector position within the satellite reference frame. An unexpected result is that we find a systematic difference between the median of the 10s Doppler tracking residuals which displays a statistically significant pattern in the South Atlantic Anomaly area where the median of the velocity residuals varies in the range of -0.15 to +0.15 mm/s@en

Different sea level reconstructions show a spread in sea level rise over the last six decades and it is not yet certain whether the sum of contributors explains the reconstructed rise. Possible causes for this spread are, among others, vertical land motion at tide-gauge locations and the sparse sampling of the spatially variable ocean. To assess these open questions, reconstructed sea level and the role of the contributors are investigated on a local, basin, and global scale. High-latitude seas are excluded. Tide-gauge records are combined with observations of vertical land motion, independent estimates of ice-mass loss, terrestrial water storage, and barotropic atmospheric forcing in a self-consistent framework to reconstruct sea level changes on basin and global scales, which are compared to the estimated sum of contributing processes. For the first time, it is shown that for most basins the reconstructed sea level trend and acceleration can be explained by the sum of contributors, as well as a large part of the decadal variability. The sparsely sampled South Atlantic Ocean forms an exception. The global-mean sea level reconstruction shows a trend of 1.5 ± 0.2 mm yr^-1 over 1958-2014 (1σ), compared to 1.3 ± 0.1 mm yr^-1 for the sum of contributors. Over the same period, the reconstruction shows a positive acceleration of 0.07 ± 0.02 mm yr^-2, which is also in agreement with the sum of contributors, which shows an acceleration of 0.07 ± 0.01 mm yr^-2. Since 1993, both reconstructed sea level and the sum of contributors show good agreement with altimetry estimates.

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Tide gauge (TG) records are affected by vertical land motion (VLM), causing them to observe relative instead of geocentric sea level. VLM can be estimated from global navigation satellite system (GNSS) time series, but only a few TGs are equipped with a GNSS receiver. Hence, (multiple) neighboring GNSS stations can be used to estimate VLM at the TG. This study compares eight approaches to estimate VLM trends at 570 TG stations using GNSS by taking into account all GNSS trends with an uncertainty smaller than 1mm yr^-1 within 50km. The range between the methods is comparable with the formal uncertainties of the GNSS trends. Taking the median of the surrounding GNSS trends shows the best agreement with differenced altimetry-tide gauge (ALT-TG) trends. An attempt is also made to improve VLM trends from ALT-TG time series. Only using highly correlated along-track altimetry and TG time series reduces the SD of ALT-TG time series by up to 10%. As a result, there are spatially coherent changes in the trends, but the reduction in the root mean square (RMS) of differences between ALT-TG and GNSS trends is insignificant. However, setting correlation thresholds also acts like a filter to remove problematic TG time series. This results in sets of ALT-TG VLM trends at 344-663 TG locations, depending on the correlation threshold. Compared to other studies, we decrease the RMS of differences between GNSS and ALT-TG trends (from 1.47 to 1.22mm yr^-1), while we increase the number of locations (from 109 to 155), Depending on the methods the mean of differences between ALT-TG and GNSS trends vary between 0.1 and 0.2mm yr^-1. We reduce the mean of the differences by taking into account the effect of elastic deformation due to present-day mass redistribution. At varying ALT-TG correlation thresholds, we provide new sets of trends for 759 to 939 different TG stations. If both GNSS and ALT-TG trend estimates are available, we recommend using the GNSS trend estimates because residual ocean signals might correlate over long distances. However, if large discrepancies ( > 3mm yr^-1) between the two methods are present, local VLM differences between the TG and the GNSS station are likely the culprit and therefore it is better to take the ALT-TG trend estimate. GNSS estimates for which only a single GNSS station and no ALT-TG estimate are available might still require some inspection before they are used in sea level studies.

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The glacial isostatic adjustment (GIA) signal at present day is constrained via the joint inversion of geodetic observations and GIA models for a region encompassing northern Europe, the British Isles, and the Barents Sea. The constraining data are Global Positioning System (GPS) vertical crustal velocities and GRACE (Gravity Recovery and Climate Experiment) gravity data. When the data are inverted with a set of GIA models, the best-fit model for the vertical motion signal has a χ 2 value of approximately 1 and a maximum a posteriori uncertainty of 0.3-0.4mm yr-1. An elastic correction is applied to the vertical land motion rates that accounts for present-day changes to terrestrial hydrology as well as recent mass changes of ice sheets and glaciered regions. Throughout the study area, mass losses from Greenland dominate the elastic vertical signal and combine to give an elastic correction of up to +0.5mm yr-1 in central Scandinavia. Neglecting to use an elastic correction may thus introduce a small but persistent bias in model predictions of GIA vertical motion even in central Scandinavia where vertical motion is dominated by GIA due to past glaciations. The predicted gravity signal is generally less well-constrained than the vertical signal, in part due to uncertainties associated with the correction for contemporary ice mass loss in Svalbard and the Russian Arctic. The GRACE-derived gravity trend is corrected for present-day ice mass loss using estimates derived from the ICESat and CryoSat missions, although a difference in magnitude between GRACE-inferred and altimetry-inferred regional mass loss rates suggests the possibility of a non-negligible GIA response here either from millennial-scale or Little Ice Age GIA.

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Rising sea levels due to climate change can have severe consequences for coastal populations and ecosystems all around the world. Understanding and projecting sea-level rise is especially important for low-lying countries such as the Netherlands. It is of specific interest for vulnerable ecological and morphodynamic regions, such as the Wadden Sea UNESCO World Heritage region. Here we provide an overview of sea-level projections for the 21st century for the Wadden Sea region and a condensed review of the scientific data, understanding and uncertainties underpinning the projections. The sea-level projections are formulated in the framework of the geological history of the Wadden Sea region and are based on the regional sea-level projections published in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). These IPCC AR5 projections are compared against updates derived from more recent literature and evaluated for the Wadden Sea region. The projections are further put into perspective by including interannual variability based on long-Term tide-gauge records from observing stations at Den Helder and Delfzijl. We consider three climate scenarios, following the Representative Concentration Pathways (RCPs), as defined in IPCC AR5: The RCP2.6 scenario assumes that greenhouse gas (GHG) emissions decline after 2020; the RCP4.5 scenario assumes that GHG emissions peak at 2040 and decline thereafter; and the RCP8.5 scenario represents a continued rise of GHG emissions throughout the 21st century. For RCP8.5, we also evaluate several scenarios from recent literature where the mass loss in Antarctica accelerates at rates exceeding those presented in IPCC AR5. For the Dutch Wadden Sea, the IPCC AR5-based projected sea-level rise is 0.07±0.06m for the RCP4.5 scenario for the period 2018-30 (uncertainties representing 5-95%), with the RCP2.6 and RCP8.5 scenarios projecting 0.01m less and more, respectively. The projected rates of sea-level change in 2030 range between 2.6mma^-1 for the 5th percentile of the RCP2.6 scenario to 9.1mma^-1 for the 95th percentile of the RCP8.5 scenario. For the period 2018-50, the differences between the scenarios increase, with projected changes of 0.16±0.12m for RCP2.6, 0.19±0.11m for RCP4.5 and 0.23±0.12m for RCP8.5. The accompanying rates of change range between 2.3 and 12.4mma^-1 in 2050. The differences between the scenarios amplify for the 2018-2100 period, with projected total changes of 0.41±0.25m for RCP2.6, 0.52±0.27m for RCP4.5 and 0.76±0.36m for RCP8.5. The projections for the RCP8.5 scenario are larger than the high-end projections presented in the 2008 Delta Commission Report (0.74m for 1990-2100) when the differences in time period are considered. The sea-level change rates range from 2.2 to 18.3mma^-1 for the year 2100. We also assess the effect of accelerated ice mass loss on the sea-level projections under the RCP8.5 scenario, as recent literature suggests that there may be a larger contribution from Antarctica than presented in IPCC AR5 (potentially exceeding 1m in 2100). Changes in episodic extreme events, such as storm surges, and periodic (tidal) contributions on (sub-)daily timescales, have not been included in these sea-level projections. However, the potential impacts of these processes on sea-level change rates have been assessed in the report.

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In this paper, we present a novel Kalman filter approach to combine a hydrodynamic model-derived lowest astronomical tide (LAT) surface with tide gauge record-derived LAT values. In the approach, tidal water levels are assimilated into the model. As such, the combination is guided by the model physics. When validating the obtained “Kalman-filtered LAT realization” at all tide gauges, we obtained an overall root-mean-square (RMS) difference of 15.1 cm. At the tide gauges not used in the data assimilation, the RMS is 17.9 cm. We found that the assimilation reduces the overall RMS difference by ∼31% and ∼22%, respectively. In the Dutch North Sea and Wadden Sea, the RMS differences are 6.6 and 14.8 cm (all tide gauges), respectively. Furthermore, we address the problem of LAT realization in intertidal waters where LAT is not defined. We propose to replace LAT by pseudo-LAT, which we suggest to realize similarly as LAT except that all water level boundary conditions and assimilated tidal water levels have to be enlarged by a constant value that is removed afterwards. Using this approach, we obtained a smooth reference surface for the Dutch Wadden Sea that fits LAT at the North Sea boundary within a few centimeters.@en

Present-day mass redistribution increases the total ocean mass and, on average, causes the ocean bottom to subside elastically. Therefore, barystatic sea level rise is larger than the resulting global mean geocentric sea level rise, observed by satellite altimetry and GPS-corrected tide gauges. We use realistic estimates of mass redistribution from ice mass loss and land water storage to quantify the resulting ocean bottom deformation and its effect on global and regional ocean volume change estimates. Over 1993-2014, the resulting globally averaged geocentric sea level change is 8% smaller than the barystatic contribution. Over the altimetry domain, the difference is about 5%, and due to this effect, barystatic sea level rise will be underestimated by more than 0.1 mm/yr over 1993-2014. Regional differences are often larger: up to 1 mm/yr over the Arctic Ocean and 0.4 mm/yr in the South Pacific. Ocean bottom deformation should be considered when regional sea level changes are observed in a geocentric reference frame.

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Melting glaciers, ice caps and ice sheets have made an important contribution to sea-level rise through the last century. Self-attraction and loading effects driven by shrinking ice masses cause a spatially varying redistribution of ocean waters that affects reconstructions of past sea level from sparse observations. We model the solid-earth response to ice mass changes and find significant vertical deformation signals over large continental areas. We show how deformation rates have been strongly varying through the last century, which implies that they should be properly modelled before interpreting and extrapolating recent observations of vertical land motion and sea-level change.

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The rate at which global mean sea level (GMSL) rose during the 20th century is uncertain, with little consensus between various reconstructions that indicate rates of rise ranging from 1.3 to 2 mm•y^-1. Here we present a 20th-century GMSL reconstruction computed using an area-weighting technique for averaging tide gauge records that both incorporates up-to-date observations of vertical land motion (VLM) and corrections for local geoid changes resulting from ice melting and terrestrial freshwater storage and allows for the identification of possible differences compared with earlier attempts. Our reconstructed GMSL trend of 1.1 ± 0.3 mm•y^-1 (1s) before 1990 falls below previous estimates, whereas our estimate of 3.1 ± 1.4 mm•y^-1 from 1993 to 2012 is consistent with independent estimates from satellite altimetry, leading to overall acceleration larger than previously suggested. This feature is geographically dominated by the Indian Ocean-Southern Pacific region, marking a transition from lower-than-average rates before 1990 toward unprecedented high rates in recent decades. We demonstrate that VLM corrections, area weighting, and our use of a common reference datum for tide gauges may explain the lower rates compared with earlier GMSL estimates in approximately equal proportion. The trends and multidecadal variability of our GMSL curve also compare well to the sum of individual contributions obtained from historical outputs of the Coupled Model Intercomparison Project Phase 5. This, in turn, increases our confidence in process-based projections presented in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.

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Sea-level rise and decadal variability along the northwestern coast of the North Atlantic Ocean are studied in a self-consistent framework that takes into account the effects of solid-earth deformation and geoid changes due to large-scale mass redistribution processes. Observations of sea and land level changes from tide gauges and GPS are compared to the cumulative effect of GIA, present-day mass redistribution, and ocean dynamics over a 50 year period (1965–2014). GIA explains the majority of the observed sea-level and land motion trends, as well as almost all interstation variability. Present-day mass redistribution resulting from ice melt and land hydrology causes both land uplift and sea-level rise in the region. We find a strong correlation between decadal steric variability in the Subpolar Gyre and coastal sea level, which is likely caused by variability in the Labrador Sea that is propagated southward. The steric signal explains the majority of the observed decadal sea-level variability and shows an upward trend and a significant acceleration, which are also found along the coast. The sum of all contributors explains the observed trends in both sea-level rise and vertical land motion in the region, as well as the decadal variability. The sum of contributors also explains the observed acceleration within confidence intervals. The sea-level acceleration coincides with an accelerating density decrease at high latitudes.

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The mass and steric components of sea level changes have been separated in the Tropical Asian Seas (TAS) using a statistically optimal combination of Jason satellite altimetry, GRACE satellite gravimetry, and ocean reanalyses. Using observational uncertainties, statistically optimally weighted time series for both components have been obtained in four regions within the TAS over the period January 2005 to December 2012. The mass and steric sea level variability is regressed with the first two principal components (PC1&2) of Pacific equatorial wind stress and the Dipole Mode Index (DMI). Sea level in the South China Sea is not affected by any of the indices. Steric variability in the TAS is largest in the deep Banda and Celebes seas and is affected by both PCs and the DMI. Mass variability is largest on the continental shelves, which is primarily controlled by PC1. We argue that a water flux from the Western Tropical Pacific Ocean is the cause for mass variability in the TAS. The steric trends are about 2 mm yr⁻¹ larger than the mass trends in the TAS. A significant part of the mass trend can be explained by the aforementioned indices and the nodal cycle. Trends obtained from fingerprints of mass redistribution are statistically equal to mass trends after subtracting the nodal cycle and the indices. Ultimately, the effect of omitting the TAS in global sea level budgets is estimated to be 0.3 mm yr⁻¹.

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Comprehensive understanding of trends and variability in coastal mean sea level is vital for protecting shores under a changing climate. To understand the behavior of coastal relative sea level (RSL), it is crucial to identify all relevant processes. We combine data from various geophysical models and observations to determine whether the trends and decadal variability observed in relative sea level at tide gauges can be explained by the sum of all known contributors. A key contributor to RSL is vertical land motion, which is caused by glacial isostatic adjustment (GIA), solid earth response to surface loading, tectonics, and local effects. We explicitly model low-frequency loading effects to correct GPS records, which leads to a more consistent trend than only using GIA models. Secondly, we create sea level fingerprints based on estimates of ice melt and changes in land hydrology, which provide the RSL contribution due to large-scale mass transport. Since coastal areas are often located on shallow continental shelves, steric effects will generally be small, and a large fraction of the decadal sea level variability will have a remote steric origin. Therefore, we determine a relation between coastal sea level and deep sea steric variability. For the period 1950-2012, we find that for many locations, including the European coast, the observed and modeled RSL time series agree well on decadal and secular scales. @en

One of the primary observational data sets of sea level is represented by the tide gauge record. We propose a new method to estimate variability on decadal time scales from tide gauge data by using a state space formulation, which couples the direct observations to a predefined state space model by using a Kalman filter. The model consists of a time-varying trend and seasonal cycle, and variability induced by several physical processes, such as wind, atmospheric pressure changes and teleconnection patterns. This model has two advantages over the classical least-squares method that uses regression to explain variations due to known processes: a seasonal cycle with time-varying phase and amplitude can be estimated, and the trend is allowed to vary over time. This time-varying trend consists of a secular trend and low-frequency variability that is not explained by any other term in the model. As a test case, we have used tide gauge data from stations around the North Sea over the period 1980-2013. We compare a model that only estimates a trend with two models that also remove intra-annual variability: one by means of time series of wind stress and sea level pressure, and one by using a two-dimensional hydrodynamic model. The last two models explain a large part of the variability, which significantly improves the accuracy of the estimated time-varying trend. The best results are obtained with the hydrodynamic model. We find a consistent low-frequency sea level signal in the North Sea, which can be linked to a steric signal over the northeastern part of the Atlantic.

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Long-term trends and decadal variability of sea level in the North Sea and along the Norwegian coast have been studied over the period 1958–2014. We model the spatially nonuniform sea level and solid earth response to large-scale ice melt and terrestrial water storage changes. GPS observations, corrected for the solid earth deformation, are used to estimate vertical land motion. We find a
clear correlation between sea level in the North Sea and along the Norwegian coast and open ocean steric variability in the Bay of Biscay and west of Portugal, which is consistent with the presence of wind-driven coastally trapped waves. The observed nodal cycle is consistent with tidal equilibrium. We are able to explain the observed sea level trend over the period 1958–2014 well within the standard error of the sum of all contributing processes, as well as the large majority of the observed decadal sea level variability.@en