Cornelis Slobbe

Coastal cities are increasingly exposed to flooding as sea level rises and as compound extremes involving tides, storm surge, waves, and river discharge act together. Reliable estimation of extreme coastal water levels is therefore fundamental to flood risk assessment, forecasting, and coastal management, yet it remains constrained by sparse in-situ networks and by the partial, scale-dependent representations that satellite altimetry and hydrodynamic models each provide. Over the past decade, advances in coastal altimetry and in regional-to-global hydrodynamic modelling have expanded the information available for coastal water-level estimation, but their combined use remains dominated by region-specific applications, and globally consistent methodologies are still emerging. Here we review approaches for combining satellite altimetry and hydrodynamic models across four interconnected domains: the detection of coastal sea-level and sea-state extremes from along-track altimetry; strategies for integrating altimetry with hydrodynamic models; vertical referencing and datum consistency; and validation and uncertainty characterisation, particularly in data-sparse settings. We argue that the central challenge is not how to merge two sources of information, but how to ensure that they represent commensurable quantities. No single integration strategy is universally optimal, and differences in process representation, sampling, and vertical reference must be treated explicitly rather than absorbed into residual error. While satellite altimetry does not resolve wave-driven processes at the shoreline and hydrodynamic models often approximate baroclinic and compound contributions, consistent vertical referencing and coherent propagation of uncertainty can render altimetry- and model-derived estimates comparable. Progress therefore depends less on combining datasets more widely than on defining when such combinations are physically meaningful, vertically consistent, uncertainty-aware, and transferable across coastal regimes, laying the foundation towards globally consistent estimation of coastal water levels.

Coastal cities are increasingly exposed to flooding as sea level rises and as compound extremes involving tides, storm surge, waves, and river discharge act together. Reliable estimation of extreme coastal water levels is therefore fundamental to flood risk assessment, forecasting, and coastal management, yet it remains constrained by sparse in-situ networks and by the partial, scale-dependent representations that satellite altimetry and hydrodynamic models each provide. Over the past decade, advances in coastal altimetry and in regional-to-global hydrodynamic modelling have expanded the information available for coastal water-level estimation, but their combined use remains dominated by region-specific applications, and globally consistent methodologies are still emerging. Here we review approaches for combining satellite altimetry and hydrodynamic models across four interconnected domains: the detection of coastal sea-level and sea-state extremes from along-track altimetry; strategies for integrating altimetry with hydrodynamic models; vertical referencing and datum consistency; and validation and uncertainty characterisation, particularly in data-sparse settings. We argue that the central challenge is not how to merge two sources of information, but how to ensure that they represent commensurable quantities. No single integration strategy is universally optimal, and differences in process representation, sampling, and vertical reference must be treated explicitly rather than absorbed into residual error. While satellite altimetry does not resolve wave-driven processes at the shoreline and hydrodynamic models often approximate baroclinic and compound contributions, consistent vertical referencing and coherent propagation of uncertainty can render altimetry- and model-derived estimates comparable. Progress therefore depends less on combining datasets more widely than on defining when such combinations are physically meaningful, vertically consistent, uncertainty-aware, and transferable across coastal regimes, laying the foundation towards globally consistent estimation of coastal water levels.

State space models are well‐suited for time series in which the evolution of variables cannot be well represented by deterministic basis functions. A key challenge in using state space models is the selection of the noise variance parameters. To better understand their impact on the model's filtering behavior, we derive the frequency response of several commonly used state space models by utilizing the connection between the Kalman smoother and regularized least squares problems. We show that the frequency response reveals distinguishing spectral features between competing state space models and explains the flattening of the log‐likelihood function when the ratio of observation to disturbance variance becomes large. Using Dutch tide gauge data, we illustrate how the frequency response can be used to make informed decisions about the variance parameters, which could in turn support more reliable interpretations of time series data.

In recent decades, satellite radar altimetry has been widely used to assess volume changes over the Greenland Ice Sheet. In particular, melt events result in drastic changes in the volume scattering of firn, which induces a pronounced change in the parameters derived from radar altimeter data. Due to the recent and increasingly frequent melt events over Greenland, the impacts of these events on the firn condition, i.e. the formation of ice lenses and reduction in firn air content, need to be better understood. This study therefore exploits the ability of long-term CryoSat-2 data to indicate changes in firn volume scattering in order to assess the spatiotemporal firn condition variations in Greenland. More specifically, this study utilises the leading edge width (LeW) parameter derived from CryoSat-2 Low Resolution Mode data, which has been proven to be a parameter strongly sensitive to changes in volume scattering, and assesses its variation between September 2010 and September 2024. With a combined analysis of remote sensing observations, in situ observations, and outputs from regional climate models, our study demonstrates that the LeW drop induced by extreme melt events in the interior of Greenland experiences a gradual recovery, which can potentially be explained by new-snow deposition. However, in many high-elevation regions of Greenland where firn layers were originally dry, the recent recurrence of extensive melt has prevented a full recovery of the firn volume scattering to pre-2012 conditions, indicating a persistent increase in firn density under a changing climate. Finally, our study also confirms the utility of radar altimeter data for long-term monitoring of the impact of melt and refreezing events on the properties of the upper firn layer.

Measurements of tides are relatively sparse in the Arctic. This paper studies GNSS buoy tracks to complement existing data. Existing methods to perform tidal harmonic analysis of the buoy data are inadequate in the Arctic region because these methods for tidal analysis combine data from multiple buoy tracks, which is often infeasible in the Arctic. Moreover, we find that there are significant spatial and temporal variations in amplitudes and phases in baroclinic zones. To address these complexities, we introduce a new approach–Model‐derived Fitting Method–to estimate the tidal current constituents (TCC) from a single buoy trajectory. Our study assesses the proposed method by analyzing GNSS buoy data from three Arctic regions characterized by barotropic or baroclinic tidal currents. Through detailed case studies in the Barents Sea, Chukchi Sea, and Baffin Bay, our approach demonstrates accuracy, robustness, and operational capabilities. In the Barents Sea, TCC estimates from two buoys were compared at a common location within their trajectories and compared against model estimates. In the Chukchi Sea's barotropic dominant zone, our method's estimates were evaluated against nearby ADCP mooring data. In Baffin Bay, known for baroclinic currents, a synthetic evaluation confirmed the method's effectiveness. Our study also highlights that phase variations along buoy trajectories can lead to frequency shifts in the spectrum, similar to the Doppler shift effect, particularly notable in regions with baroclinic tides.

Mangroves are more and more recognized for nature‐based mitigation of flood risks in low‐lying coastal zones, which host a disproportionately large part of the global population. Aerial roots, branches, and canopy of mangrove trees exert friction on the water flow, thereby reducing the propagation of high water levels through the forest. Field measurements of high water level attenuation rates are limited so far to mangrove forests situated at higher‐latitude subtropical settings, where aerial roots are much sparser and lower than in low‐latitude tropical mangroves. Here, for the first time, we measured high water level attenuation in a tropical Rhizophora forest, where aerial roots are several meters high and water levels never exceeded the aerial root height. Our measurements reveal attenuation rates between 42 ± 9.8 and 46 ± 9.8 cm km⁻¹, which are the highest attenuation rates ever recorded in a mangrove forest, but an exponential rate is more suited to quantify high water level attenuation. In contrast to observations inside the mangrove forest, our observations showed that the propagation of high water levels through a 20 km long tidal channel fringed by wide mangrove areas was amplified, but that high water level amplification was reduced for higher tides with deeper flooding of the fringing mangroves. Our results provide the first empirical assessment of flood protection by tropical Rhizophora mangroves. As Rhizophora is globally the most common genus among mangroves, we propose that our reported high attenuation rates should be incorporated in future assessments of nature‐based flood risk mitigation by mangroves.

In recent decades, satellite radar altimetry has been widely used to assess volume changes over the Greenland Ice Sheet. Especially, melt events result in drastic changes in volume scattering of firn, which induces a pronounced change in parameters derived from radar altimetry. Due to the recent and increasingly frequent melt events over Greenland, the impacts of these events on the firn condition i.e. formation of ice lenses and reduction of firn air content, need to be better understood. This study therefore exploits the ability of long-term CryoSat-2 data in indicating changes in firn volume scattering, in order to assess the spatio-temporal firn condition variations in Greenland. More specifically, this study utilises the leading edge width (LeW) parameter derived from CryoSat-2 Low Resolution Mode, which has been proven to be the parameter most sensitive to changes in volume scattering, and assesses its variation between January 2011 and August 2021. With a combined analysis of remote sensing observations, in situ observations and outputs from regional climate models, our study demonstrates that the LeW drop induced by extreme melt events in the interior of Greenland experiences a gradual recovery, which can potentially be explained by new snow deposition. However, in many high-elevation regions of Greenland where firn layers were originally dry, due to the recently recurring extensive melt, the firn volume scattering does not fully recover to the original state before the 2012 melt, indicating a long-lived increase in Greenland’s firn density in a changing climate. Finally, our study also confirms the capability of using radar altimeter data to monitor changes in volume scattering properties of firn in the long-term.

In recent decades, satellite radar altimetry has been widely used to assess volume changes over the Greenland Ice Sheet. Especially, melt events result in drastic changes in volume scattering of firn, which induces a pronounced change in parameters derived from radar altimetry. Due to the recent and increasingly frequent melt events over Greenland, the impacts of these events on the firn condition i.e. formation of ice lenses and reduction of firn air content, need to be better understood. This study therefore exploits the ability of long-term CryoSat-2 data in indicating changes in firn volume scattering, in order to assess the spatio-temporal firn condition variations in Greenland. More specifically, this study utilises the leading edge width (LeW) parameter derived from CryoSat-2 Low Resolution Mode, which has been proven to be the parameter most sensitive to changes in volume scattering, and assesses its variation between January 2011 and August 2021. With a combined analysis of remote sensing observations, in situ observations and outputs from regional climate models, our study demonstrates that the LeW drop induced by extreme melt events in the interior of Greenland experiences a gradual recovery, which can potentially be explained by new snow deposition. However, in many high-elevation regions of Greenland where firn layers were originally dry, due to the recently recurring extensive melt, the firn volume scattering does not fully recover to the original state before the 2012 melt, indicating a long-lived increase in Greenland’s firn density in a changing climate. Finally, our study also confirms the capability of using radar altimeter data to monitor changes in volume scattering properties of firn in the long-term.

In recent decades, satellite radar altimetry has been widely used to assess volume changes over the Greenland Ice Sheet. Especially, melt events result in drastic changes in volume scattering of firn, which induces a pronounced change in parameters derived from radar altimetry. Due to the recent and increasingly frequent melt events over Greenland, the impacts of these events on the firn condition i.e. formation of ice lenses and reduction of firn air content, need to be better understood. This study therefore exploits the ability of long-term CryoSat-2 data in indicating changes in firn volume scattering, in order to assess the spatio-temporal firn condition variations in Greenland. More specifically, this study utilises the leading edge width (LeW) parameter derived from CryoSat-2 Low Resolution Mode, which has been proven to be the parameter most sensitive to changes in volume scattering, and assesses its variation between January 2011 and August 2021. With a combined analysis of remote sensing observations, in situ observations and outputs from regional climate models, our study demonstrates that the LeW drop induced by extreme melt events in the interior of Greenland experiences a gradual recovery, which can potentially be explained by new snow deposition. However, in many high-elevation regions of Greenland where firn layers were originally dry, due to the recently recurring extensive melt, the firn volume scattering does not fully recover to the original state before the 2012 melt, indicating a long-lived increase in Greenland’s firn density in a changing climate. Finally, our study also confirms the capability of using radar altimeter data to monitor changes in volume scattering properties of firn in the long-term.

In recent decades, satellite radar altimetry has been widely used to assess volume changes over the Greenland Ice Sheet. Especially, melt events result in drastic changes in volume scattering of firn, which induces a pronounced change in parameters derived from radar altimetry. Due to the recent and increasingly frequent melt events over Greenland, the impacts of these events on the firn condition i.e. formation of ice lenses and reduction of firn air content, need to be better understood. This study therefore exploits the ability of long-term CryoSat-2 data in indicating changes in firn volume scattering, in order to assess the spatio-temporal firn condition variations in Greenland. More specifically, this study utilises the leading edge width (LeW) parameter derived from CryoSat-2 Low Resolution Mode, which has been proven to be the parameter most sensitive to changes in volume scattering, and assesses its variation between January 2011 and August 2021. With a combined analysis of remote sensing observations, in situ observations and outputs from regional climate models, our study demonstrates that the LeW drop induced by extreme melt events in the interior of Greenland experiences a gradual recovery, which can potentially be explained by new snow deposition. However, in many high-elevation regions of Greenland where firn layers were originally dry, due to the recently recurring extensive melt, the firn volume scattering does not fully recover to the original state before the 2012 melt, indicating a long-lived increase in Greenland’s firn density in a changing climate. Finally, our study also confirms the capability of using radar altimeter data to monitor changes in volume scattering properties of firn in the long-term.