Future Sea Level Rise Research Articles

Implications of anomalous relative sea-level rise for the peopling of Remote Oceania

Beginning ~3,500 to 3,300 y B.P., humans voyaged into Remote Oceania. Radiocarbon-dated archaeological evidence coupled with cultural, linguistic, and genetic traits indicates two primary migration routes: a Southern Hemisphere and a Northern Hemisphere route. These routes are separated by low-lying, equatorial atolls that were settled during secondary migrations ~1,000 y later after their exposure by relative sea-level fall from a mid-Holocene highstand. High volcanic islands in the Federated States of Micronesia (Pohnpei and Kosrae) also lie between the migration routes and settlement is thought to have occurred during the secondary migrations despite having been above sea level during the initial settlement of Remote Oceania. We reconstruct relative sea level on Pohnpei and Kosrae using radiocarbon-dated mangrove sediment and show that, rather than falling, there was a ~4.3-m rise over the past ~5,700 y. This rise, likely driven by subsidence, implies that evidence for early settlement could lie undiscovered below present sea level. The potential for earlier settlement invites reinterpretation of migration pathways into Remote Oceania and monument building. The UNESCO World Heritage sites of Nan Madol (Pohnpei) and Leluh (Kosrae) were constructed when relative sea level was ~0.94 m (~770 to 750 y B.P.) and ~0.77 m (~640 to 560 y B.P.) lower than present, respectively. Therefore, it is unlikely that they were originally constructed as islets separated by canals filled with ocean water, which is their prevailing interpretation. Due to subsidence, we propose that these islands and monuments are more vulnerable to future relative sea-level rise than previously identified.

An assessment of basal melt parameterisations for Antarctic ice shelves

Abstract. Ocean-induced ice-shelf melt is one of the largest uncertainty factors in the Antarctic contribution to future sea-level rise. Several parameterisations exist, linking oceanic properties in front of the ice shelf to melt at the base of the ice shelf, to force ice-sheet models. Here, we assess the potential of a range of these existing basal melt parameterisations to emulate basal melt rates simulated by a cavity-resolving ocean model on the circum-Antarctic scale. To do so, we perform two cross-validations, over time and over ice shelves respectively, and re-tune the parameterisations in a perfect-model approach, to compare the melt rates produced by the newly tuned parameterisations to the melt rates simulated by the ocean model. We find that the quadratic dependence of melt to thermal forcing without dependency on the individual ice-shelf slope and the plume parameterisation yield the best compromise, in terms of integrated shelf melt and spatial patterns. The box parameterisation, which separates the sub-shelf circulation into boxes, the PICOP parameterisation, which combines the box and plume parameterisation, and quadratic parameterisations with dependency on the ice slope yield basal melt rates further from the model reference. The linear parameterisation cannot be recommended as the resulting integrated ice-shelf melt is comparably furthest from the reference. When using offshore hydrographic input fields in comparison to properties on the continental shelf, all parameterisations perform worse; however, the box and the slope-dependent quadratic parameterisations yield the comparably best results. In addition to the new tuning, we provide uncertainty estimates for the tuned parameters.

Evaluation of Potential Seawater Intrusion in the Coastal Aquifers System of Benin and Effect of Countermeasures Considering Future Sea Level Rise

In the present study, a three-dimensional SEAWAT model was developed to generally simulate the impact of climate change and anthropogenic activities on seawater intrusion (SWI) in the coastal region of Benin by the end of 2050. The model was calibrated and validated from 2015 to 2020, considering groundwater head and salt concentration measured in 30 wells. After calibration, a sensitivity analysis was performed with the model parameters (hydraulic conductivity, recharge, storage coefficient and boundary conditions). For the calibration, model computed and observed values displayed good correlation, approximatively 0.82 with a root mean square error (RMSE) of 0.97 m and 13.38 mg/L for groundwater head and salt concentration, respectively. The simulation results indicate that freshwater head had declined by 1.65 m from 2015 to 2020 (taking reference from the average groundwater head in 2015: 27.08 m), while the seawater intrusion area increased in the same period by an average of 1.92 km2 (taking reference from the seawater intrusion area in 2015: 20.03 km2). The model is therefore used to predict groundwater level decline and seawater intrusion area increase by the end of 2050, considering the predicted sea level rise (SLR) and estimated groundwater pumping rate. Furthermore, the interface fresh groundwater–saltwater change was studied using the SHARP interface developed by USGS in 1990. The interface variation was found to be influenced by the distance from shoreline, sea level, groundwater level and geological formation hydraulic conductivity. Finally, the 3D model was used to simulate the effect of a managed aquifer recharge system on reducing SWI rate in the study region.

Through an Ice Sheet, Darkly

Through an Ice Sheet, Darkly

The future of coastal monitoring through satellite remote sensing

AbstractSatellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.

Sea level rise vulnerability assessment for State wildlife areas surrounding Humboldt Bay, northern California

Humboldt Bay has the highest rate of sea level rise (SLR) in California (47.2 cm/century). Due to compaction and tectonic subsidence, former tidelands and pastures behind dikes surrounding Humboldt Bay are lower in elevation than bay waters at high tide. Adaptation to future climate change and SLR requires that resource managers understand vulnerability and risk to each wildlife area at a local level, because adaptation to SLR is a risk-based management strategy against an uncertain future requiring site-specific solutions. We conducted a vulnerability assessment of the shoreline of three State wildlife areas surrounding Humboldt Bay: Elk River (ERWA), Fay Slough (FSWA), and Mad River Slough (MRSWA). Breaching of shorelines that border each refuge has the potential to flood a diversity of wetland communities, wildlife habitats, and critical infrastructure within the historic tidal inundation footprint. The total length of diked 1-m shoreline segments potentially impacted by SLR was 6.2 km. The relationship between vulnerability and elevation of diked shoreline segments was significantly correlated for all wildlife areas. Vulnerability of diked shoreline was significantly affected by the type of surface covering. MRSWA had the highest percentage of shoreline fortified with concrete and rock (62.2% [2,876 m]), followed by ERWA (0.3% [2,815 m]). ERWA and FSWA had the greatest percentage of shoreline anchored by vegetation (99.3% [2,834 m] and 91.5% [3,385 m], respectively); FSWA had the highest percentage of unvegetated (i.e., exposed) shoreline (7.4% [252 m]); and ERWA had the highest percentage (86.6% [436 m]) of diked shoreline followed by FSWA (69.2% [633 m]) and MRSWA (33.0% [276 m]). The highest overall ratings of shoreline vulnerability were at ERWA (91.7%), followed by FSSWA (72,4%), and MRSWA (34.4%). Issues related to retention of unique characteristics of each wildlife area, natural resources and species at risk, and adaptive planning for future SLR are discussed.

Inclusions in ice layers formed by melting and refreezing processes in a Greenland ice core

AbstractIn recent decades, surface melting on the inland Greenland ice sheet has increased, leading to significant meltwater-refreezing in the snow and firn. Increased knowledge of the physical and chemical characteristics of these melt features (i.e., ice layers) is needed to help estimate future global sea-level rise. Here, using a combination of microscopy and spectroscopy, we investigate the size, shape, location, and chemical compositions of inclusions in 12 ice layers of the SIGMA-A ice core in the northwestern Greenland ice sheet (78°03′06″N, 67°37′42″W, 1490 m a.s.l.). In the ice layers, we found inclusions exceeding 30 μm diameter that could only be formed by melting–refreezing, which we classify into columnar-, particle-, and rod-like inclusions. We propose that the smaller columnar- and particle-like inclusions of solid Na2SO4⋅10H2O and CaSO4⋅2H2O form first, within the ice grains, followed by the larger rod-like inclusions of brines with mainly Na+and Cl−in grain boundaries. Our results suggest a new proxy that may help identify past warm climates in deeper ice cores in Greenland and for studying future ice sheet melting behavior.

The contribution of Humboldt Glacier, northern Greenland, to sea-level rise through 2100 constrained by recent observations of speedup and retreat

Abstract. Humboldt Glacier, northern Greenland, has retreated and accelerated through the 21st century, raising concerns that it could be a significant contributor to future sea-level rise. We use a data-constrained ensemble of three-dimensional higher-order ice sheet model simulations to estimate the likely range of sea-level rise from the continued retreat of Humboldt Glacier. We first solve for basal traction using observed ice thickness, bed topography, and ice surface velocity from the year 2007 in a PDE-constrained (partial differential equation) optimization. Next, we impose calving rates to match mean observed retreat rates from winter 2007–2008 to winter 2017–2018 in a transient calibration of the exponent in the power-law basal friction relationship. We find that power-law exponents in the range of 1/7–1/5 – rather than the commonly used 1/3–1 – are necessary to reproduce the observed speedup over this period. We then tune an iceberg calving parameterization based on the von Mises stress yield criterion in another transient-calibration step to approximate both observed ice velocities and terminus position in 2017–2018. Finally, we use the range of basal friction relationship exponents and calving parameter values to generate the ensemble of model simulations from 2007–2100 under three climate forcing scenarios from CMIP5 (two RCP8.5 forcings, Representative Concentration Pathway) and CMIP6 (one SSP5-8.5 forcing, Shared Socioeconomic Pathway). Our simulations predict 5.2–8.7 mm of sea-level rise from Humboldt Glacier, significantly higher than a previous estimate (∼ 3.5 mm) and equivalent to a substantial fraction of the 40–140 mm predicted by ISMIP6 from the whole Greenland Ice Sheet. Our larger future sea-level rise prediction results from the transient calibration of our basal friction law to match the observed speedup, which requires a semi-plastic bed rheology. In many simulations, our model predicts the growth of a sizable ice shelf in the middle of the 21st century. Thus, atmospheric warming could lead to more retreat than predicted here if increased surface melt promotes hydrofracture of the ice shelf. Our data-constrained simulations of Humboldt Glacier underscore the sensitivity of model predictions of Greenland outlet glacier response to warming to choices of basal shear stress and iceberg calving parameterizations. Further, transient calibration of these parameterizations, which has not typically been performed, is necessary to reproduce observed behavior. Current estimates of future sea-level rise from the Greenland Ice Sheet could, therefore, contain significant biases.

River Deltas and Sea-Level Rise

Future sea-level rise poses an existential threat for many river deltas, yet quantifying the effect of sea-level changes on these coastal landforms remains a challenge. Sea-level changes have been slow compared to other coastal processes during the instrumental record, such that our knowledge comes primarily from models, experiments, and the geologic record. Here we review the current state of science on river delta response to sea-level change, including models and observations from the Holocene until 2300 CE. We report on improvements in the detection and modeling of past and future regional sea-level change, including a better understanding of the underlying processes and sources of uncertainty. We also see significant improvements in morphodynamic delta models. Still, substantial uncertainties remain, notably on present and future subsidence rates in and near deltas. Observations of delta submergence and land loss due to modern sea-level rise also remain elusive, posing major challenges to model validation. ▪ There are large differences in the initiation time and subsequent delta progradation during the Holocene, likely from different sea-level and sediment supply histories. ▪ Modern deltas are larger and will face faster sea-level rise than during their Holocene growth, making them susceptible to forced transgression. ▪ Regional sea-level projections have been much improved in the past decade and now also isolate dominant sources of uncertainty, such as the Antarctic ice sheet. ▪ Vertical land motion in deltas can be the dominant source of relative sea-level change and the dominant source of uncertainty; limited observations complicate projections. ▪ River deltas globally might lose 5% (∼35,000 km2) of their surface area by 2100 and 50% by 2300 due to relative sea-level rise under a high-emission scenario.

An ensemble of Antarctic deglacial simulations constrained by geological observations

The Antarctic ice sheet has the potential to make a significant contribution to future sea-level rise. Understanding this potential and making projections of future ice sheet mass change requires use of numerical models. Confidence in model projections can be improved by hindcasting: testing the model against past ice sheet changes. Robust deglacial model reconstructions are also used to correct satellite gravimetric measurements of current change for glacial isostatic adjustment processes. Here we present a new model ensemble of post-Last Glacial Maximum Antarctic deglaciation reconstructions. The ensemble is generated using the Parallel Ice Sheet Model (PISM) in which we vary a range of parameters including key glaciological controls, basal sediment strength, mantle viscosity, and climate forcing. We test the ensemble results against a database of geological constraints, and develop a new scoring scheme that allows us to determine metrics of model performance against past ice sheet grounding line extent, ice sheet thickness, and thinning rates, as well as present-day ice sheet configuration. We discuss the parameter combinations that lead to the highest-scoring simulations and we also compare our ensemble performance with existing published deglacial models, using the same scoring scheme. Exploring the characteristics of the highest-scoring ensemble members highlights some key features of deglacial behaviour including a relatively narrow range of past excess ice volumes at the LGM, Holocene retreat behind present-day grounding lines with commensurate volume minima, and readvance behaviours. The comparison also allows us to identify areas where more geological data would have high constraining power for ice sheet models.

Regional sea-level highstand triggered Holocene ice sheet thinning across coastal Dronning Maud Land, East Antarctica

The East Antarctic Ice Sheet stores a vast amount of freshwater, which makes it the single largest potential contributor to future sea-level rise. However, the lack of well-constrained geological records of past ice sheet changes impedes model validation, hampers mass balance estimates, and inhibits examination of ice loss mechanisms. Here we identify rapid ice-sheet thinning in coastal Dronning Maud Land from Early to Middle Holocene (9000–5000 years ago) using a deglacial chronology based on in situ cosmogenic nuclide surface exposure dates from central Dronning Maud Land, in concert with numerical simulations of regional and continental ice-sheet evolution. Regional sea-level changes reproduced from our refined ice-load history show a highstand at 9000–8000 years ago. We propose that sea-level rise and a concomitant influx of warmer Circumpolar Deep Water triggered ice shelf breakup via the marine ice sheet instability mechanism, which led to rapid thinning of upstream coastal ice sheet sectors.

Coastal Vulnerability Assessment for Future Sea Level Rise and a Comparative Study of Two Pocket Beaches in Seasonal Scale, Ios Island, Cyclades, Greece

The coastal zone may be considered as the location where the marine and land environments interact dynamically and coexist with human societies. Globally, natural and human systems are being severely threatened by the sea level rise related to climate change. The outcome between the dynamic relationship of coastal environments and marine processes, and the future sea level rise as predicted by scientific reports, is the vulnerability of coastal areas such as sandy beaches, pocket beaches and low-lying coastal areas. The current research aims to assess the coastal vulnerability of Ios Island, Cyclades, Greece for the next 100 years and to identify areas that are comparatively more vulnerable to future sea level changes. Moreover, the seasonal changes concerning sedimentological and morphological characteristics of two pocket beaches of Ios Island, Mylopotas and Magganari, are also examined. From the application of the Coastal Vulnerability Index, 92.37% of the total length of the coastline of Ios Island is characterized by a very low vulnerability as it consists of rocky shores and cliffs, while sandy and pocket beaches are characterized by a very high vulnerability. From the fieldworks and data processing, the seasonal changes mainly concern the seabed’s topography, the sediments’ texture of the collected sand samples, the foreshore and backshore topography, as well as seasonal shoreline displacement, using the Digital Shoreline Analysis System tool (DSAS).

Ice thickness distribution of Himalayan glaciers inferred from DInSAR-based glacier surface velocity.

Retrieval of glacier ice thickness is extremely important for monitoring water resources and predicting glacier dynamics and changes. The inter-annual glacier ice thickness observations (more than 5years) exploit the glacier mass changes. Ice thickness is one of the important parameters to predict the future sea-level rise. Without adequate knowledge and precise information of glacier ice thickness distribution, future sea-level changes cannot be accurately assessed. In this study, we use an existing flow model to estimate the ice thickness of the High Mountain Asia (HMA) glaciers, using remote sensing techniques. The glacier ice velocity is one of the significant parameters in the Laminar flow model to retrieve the ice thickness. The glacier ice velocity is derived by utilizing the Differential SAR Interferometry (DInSAR) technique. The most optimum DInSAR data (ALOS-2/PALSAR-2) is used for estimating the ice velocity of the HMA glaciers. The ice thickness is mainly estimated for five different states in the HMA region, namely Himachal Pradesh, Uttarakhand, Sikkim, Bhutan, and Arunachal Pradesh. Most of the states are observed with a mean ice thickness of 100m. Five benchmark glaciers (Samudra Tapu, Bara Shigri, Chhota Shigri, Sakchum, and Gangotri glaciers) are also selected for validating our results with the existing thickness information. The issues related to velocity-based ice thickness inversion are also emphasized in this study. The high-velocity rate due to the influx of melting water from adjacent glaciers causes an increment in the flow rate. This abnormal velocity derives erroneous ice thickness measurements. This is one of the major problems to be considered in the velocity-based thickness-derived procedures. Finally, the investigation suggests the inclusion of the velocity influencing parameters in the physical-based models for an accurate ice thickness inversion.

Perturbation analysis of the rank-size rule for municipalities squeezed in a prefecture: Effects of the archipelagoes, rapidly increasing rural depopulation, ethnic minority issues, and future sea-level rise due to global warming

Perturbation analysis of the rank-size rule is made for municipalities that are squeezed in a prefecture. Specifically, attention is focused on Japanese prefectures, for which effects of the archipelagoes, municipal consolidations, and coastal inundations due to the future sea-level rise are examined. In each prefecture, typically tens of municipalities are closely packed with a unique configuration that has been arranged according to a self-organized process. With a mind to sustainable development goals, analysis is made from three points of view. First, comparisons between the results of the mainland and those of the entire prefecture with territorial islands suggest that historical interactions over a long period become a key factor to enhance the statistical rule. Next, to cope with rapidly increasing rural depopulation, simulations are made on the basis of three consolidatory schemes. Of prefectures with extremely depopulated areas, particular emphasis is laid on Fukushima Prefecture, the east coast of which was damaged by the nuclear disaster on 11 March 2011. Lastly, analysis is made implying perturbations due to global warming. Among three parameters that characterize the rank-size relation, stabilities are confirmed for the scaling exponent.

Seasonal land-ice-flow variability in the Antarctic Peninsula

Abstract. Recent satellite-remote sensing studies have documented the multi-decadal acceleration of the Antarctic Ice Sheet in response to rapid rates of ice-sheet retreat and thinning. Unlike the Greenland Ice Sheet, where historical, high-temporal-resolution satellite and in situ observations have revealed distinct changes in land-ice flow within intra-annual timescales, observations of similar seasonal signals are limited in Antarctica. Here, we use high-spatial- and high-temporal-resolution Copernicus Sentinel-1A/B synthetic aperture radar observations acquired between 2014 and 2020 to provide the first evidence for seasonal flow variability of the land ice feeding George VI Ice Shelf (GVIIS), Antarctic Peninsula. Our observations reveal a distinct austral summertime (December–February) speed-up of ∼0.06±0.005 m d−1 (∼ 22±1.8 m yr−1) at, and immediately inland of, the grounding line of the glaciers nourishing the ice shelf, which constitutes a mean acceleration of ∼15 % relative to baseline (time-series-averaged) rates of flow. These findings are corroborated by independent, optically derived velocity observations obtained from Landsat 8 imagery. Both surface and oceanic forcing mechanisms are outlined as potential controls on this seasonality. Ultimately, our findings imply that similar surface and/or ocean forcing mechanisms may be driving seasonal accelerations at the grounding lines of other vulnerable outlet glaciers around Antarctica. Assessing the degree of seasonal ice-flow variability at such locations is important for quantifying accurately Antarctica's future contribution to global sea-level rise.

The Impact of Future Sea-Level Rise on Low-Lying Subsiding Coasts: A Case Study of Tavoliere Delle Puglie (Southern Italy)

Low-lying coastal zones are highly subject to coastal hazards as a result of sea-level rise enhanced by natural or anthropogenic land subsidence. A combined analysis using sea-level data and remote sensing techniques allows the estimation of the current rates of land subsidence and shoreline retreat, supporting the development of quantified relative sea-level projections and flood maps, which are appropriate for specific areas. This study focuses on the coastal plain of Tavoliere delle Puglie (Apulia, Southern Italy), facing the Adriatic Sea. In this area, land subsidence is mainly caused by long-term tectonic movements and sediment compaction driven by high anthropogenic pressure, such as groundwater exploitation and constructions of buildings. To assess the expected effects of relative sea-level rise for the next decades, we considered the following multidisciplinary source data: (i) sea-level-rise projections for different climatic scenarios, as reported in the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, (ii) coastal topography from airborne and terrestrial LiDAR data, (iii) Vertical Land Movement (VLM) from the analysis of InSAR and GNSS data, and (iv) shoreline changes obtained from the analysis of orthophotos, historic maps, and satellite images. To assess the expected evolution of the coastal belt, the topographic data were corrected for VLM values, assuming that the rates of land subsidence will remain constant up to 2150. The sea-level-rise projections and expected flooded areas were estimated for the Shared Socioeconomic Pathways SSP1-2.6 and SSP5-8.5, corresponding to low and high greenhouse-gas concentrations, respectively. From our analysis, we estimate that in 2050, 2100, and 2150, up to 50.5 km2, 118.7 km2 and 147.7 km2 of the coast could be submerged, respectively, while beaches could retreat at rates of up to 5.8 m/yr. In this area, sea-level rise will be accelerated by natural and anthropogenic land subsidence at rates of up to −7.5 ± 1.7 mm/yr. Local infrastructure and residential areas are thus highly exposed to an increasing risk of severe inundation by storm surges and sea-level rise in the next decades.

Ice Sheet and Climate Processes Driving the Uncertainty in Projections of Future Sea Level Rise: Findings From a Structured Expert Judgement Approach.

The ice sheets covering Antarctica and Greenland present the greatest uncertainty in, and largest potential contribution to, future sea level rise. The uncertainty arises from a paucity of suitable observations covering the full range of ice sheet behaviors, incomplete understanding of the influences of diverse processes, and limitations in defining key boundary conditions for the numerical models. To investigate the impact of these uncertainties on ice sheet projections we undertook a structured expert judgement study. Here, we interrogate the findings of that study to identify the dominant drivers of uncertainty in projections and their relative importance as a function of ice sheet and time. We find that for the 21st century, Greenland surface melting, in particular the role of surface albedo effects, and West Antarctic ice dynamics, specifically the role of ice shelf buttressing, dominate the uncertainty. The importance of these effects holds under both a high-end 5°C global warming scenario and another that limits global warming to 2°C. During the 22nd century the dominant drivers of uncertainty shift. Under the 5°C scenario, East Antarctic ice dynamics dominate the uncertainty in projections, driven by the possible role of ice flow instabilities. These dynamic effects only become dominant, however, for a temperature scenario above the Paris Agreement 2°C target and beyond 2100. Our findings identify key processes and factors that need to be addressed in future modeling and observational studies in order to reduce uncertainties in ice sheet projections.

Inverting ice surface elevation and velocity for bed topography and slipperiness beneath Thwaites Glacier

Abstract. There is significant uncertainty over how ice sheets and glaciers will respond to rising global temperatures. Limited knowledge of the topography and rheology of the ice–bed interface is a key cause of this uncertainty as models show that small changes in the bed can have a large influence on predicted rates of ice loss. Most of our detailed knowledge of bed topography comes from airborne and ground-penetrating radar observations. However, these direct observations are not spaced closely enough to meet the requirements of ice-sheet models, so interpolation and inversion methods are used to fill in the gaps. Here we present the results of a new inversion of surface elevation and velocity data over Thwaites Glacier, West Antarctica, for bed topography and slipperiness (i.e. the degree of basal slip for a given level of drag). The inversion is based on a steady-state linear perturbation analysis of the shallow-ice-stream equations. The method works by identifying disturbances to surface flow which are caused by obstacles or sticky patches in the bed and can therefore be applied wherever the shallow-ice-stream equations hold and where surface data are available, even where the ice thickness is not well known. We assess the performance of the inversion for topography with the available radar data. Although the topographic output from the inversion is less successful where the bed slopes steeply, it compares well with radar data from the central trunk of the glacier for medium-wavelength features (5–50 km). This method could therefore be useful as an independent test of other interpolation methods such as mass conservation and kriging. We do not have data to allow us to assess the success of the slipperiness results from our inversions, but we provide maps that may guide future seismic data collection across Thwaites Glacier. The methods presented here show significant promise for using high-resolution satellite datasets, calibrated by sparser field datasets, to generate high-resolution bed topography products across the ice sheets and therefore contribute to reduced uncertainty in predictions of future sea-level rise.

Variability in Antarctic surface climatology across regional climate models and reanalysis datasets

Abstract. Regional climate models (RCMs) and reanalysis datasets provide valuable information for assessing the vulnerability of ice shelves to collapse over Antarctica, which is important for future global sea level rise estimates. Within this context, this paper examines variability in snowfall, near-surface air temperature and melt across products from the Met Office Unified Model (MetUM), Regional Atmospheric Climate Model (RACMO) and Modèle Atmosphérique Régional (MAR) RCMs, as well as the ERA-Interim and ERA5 reanalysis datasets. Seasonal and trend decomposition using LOESS (STL) is applied to split the monthly time series at each model grid cell into trend, seasonal and residual components. Significant systematic differences between outputs are shown for all variables in the mean and in the seasonal and residual standard deviations, occurring at both large and fine spatial scales across Antarctica. Results imply that differences in the atmospheric dynamics, parametrisation, tuning and surface schemes between models together contribute more significantly to large-scale variability than differences in the driving data, resolution, domain specification, ice sheet mask, digital elevation model and boundary conditions. Despite significant systematic differences, high temporal correlations are found for snowfall and near-surface air temperature across all products at fine spatial scales. For melt, only moderate correlation exists at fine spatial scales between different RCMs and low correlation between RCM and reanalysis outputs. Root mean square deviations (RMSDs) between all outputs in the monthly time series for each variable are shown to be significant at fine spatial scales relative to the magnitude of annual deviations. Correcting for systematic differences results in significant reductions in RMSDs, suggesting the importance of observations and further development of bias-correction techniques.

A Two-Period Model of Coastal Urban Adaptation Supported by Climate Services

Coastal zones are experiencing rapid urbanization at unprecedented rates. At the same time, coastal cities are the most prone to climate-related vulnerability, including impacts of sea-level rise and climate-related coastal hazards under the present and projected future climate. Decision making about coastal urban climate adaptation can be informed by coastal climate services based on modeling tools. We develop a two-period coastal urban adaptation model in which two periods—the present and the future—are distinguished. In the model, a city agent anticipates sea-level rise and related coastal flood hazards with adverse impacts in the future period that, through damages, will reduce the urban income. However, the magnitude of future sea-level rise and induced damages are characterized by uncertainty. The urban planning agent has to make an investment decision under uncertainty: whether to invest in climate adaptation (in the form of construction of coastal protection) or not, and if so, how much. The decision making of the urban agent is derived from intertemporal maximization of expected time-discounted consumption. An exact solution in the closed form is derived for an analytically tractable particular case, for which it is shown that investment decisions depend discontinuously on the value of a single non-dimensional model indicator. When this indicator exceeds a certain threshold value, the urban agent discontinuously switches from the ‘business-as-usual’ (BaU) strategy when no adaptation investment is taken to a proactive adaptation. The role of coastal climate services in informing the decision making on adaptation strategies is discussed.