Melt Season Research Articles

Surface energy and mass balance of Mera Glacier (Nepal, Central Himalaya) and their sensitivity to temperature and precipitation

Abstract The sensitivity of glacier mass balance to temperature and precipitation variations is crucial for informing models that simulate glaciers’ response to climate change. In this study, we simulate the glacier-wide mass balance of Mera Glacier with a surface energy-balance model, driven by in situ meteorological data, from 2016 to 2020. The analysis of the share of the energy fluxes of the glacier shows the radiative fluxes account for almost all the energy available during the melt season (May–October). However, turbulent fluxes are significant outside the monsoon (June–September). On an annual scale, melt is the dominant mass flux at all elevations, but 44% of the melt refreezes across the glacier. By reshuffling the available observations, we create 180 synthetic series of hourly meteorological forcings to force the model over a wide range of plausible climate conditions. A +1 (−1)°C change in temperature results in a −0.75 ± 0.17 (+0.93 ± 0.18) m w.e. change in glacier-wide mass balance and a +20 (−20)% change in precipitation results in a +0.52 ± 0.10 (−0.60 ± 0.11) m w.e. change. Our study highlights the need for physical-based approaches to produce consistent forcing datasets, and calls for more meteorological and glaciological measurements in High Mountain Asia.

Boron to salinity ratios in the Fram Strait entering the Central Arctic: The role of sea ice formation and future predictions

The Arctic Ocean's sea ice loss dynamically impacts carbon uptake potential, as assessed through measured carbonate parameters, such as total alkalinity. In the open ocean, boron (B) is the third largest contributor to alkalinity via borate and is usually accounted for through the conservative boron to salinity ratio (B/S), and not directly measured. Here, we present findings on non-conservative boron dynamics, that results in significant B/S deviations, observed in ice melt zone waters, snow, slush, brine, and annual sea ice (n = 169) in the Fram Strait entering the Central Arctic. These samples were collected during the onset of the melt season on the 2023 ARTofMELT expedition, covering a wide practical salinity range (2–59). Barring snow, the average B/S ratio across the study was 0.1321 ± 0.0032 mg kg−1 ‰−1, similar to the mean B/S ratio measured amongst several polar water masses near Iceland, as well as the accepted B/S for other ocean regions. Results indicate minor deviations from accepted B/S ratios (indicating conservative behavior) across the sample practical salinity range and reflect an uncertainty in the borate contribution to total alkalinity of less than 2.9 μmol kg−1 at in-situ temperatures. B fractionation appears to occur during sea ice formation, causing greater B in the sea ice reservoir whereas brine, slush, lead, and under-ice water reservoirs are depleted in B. As such, under-ice and lead, brine, and slush samples all had measured B/S ratios (0.1305 ± 0.0011, 0.1305 ± 0.0018, and 0.1304 ± 0.0017 mg kg−1 ‰−1, respectively) lower than the established ratio whereas the average sea ice B/S ratio (0.1331 ± 0.0035 mg kg−1 ‰−1) was closest to accepted values (0.1336 ± 0.0005 mg kg−1 ‰−1). Arctic open ocean samples also had a lower B/S ratio (0.1304 ± 0.0014 mg kg−1 ‰−1). Our findings, together with a previous Arctic B ice study, suggest that B (probably in the form of B(OH)4−) is incorporated into authigenic CaCO3 minerals, replacing CO32− within the mineral lattice during sea ice formation. This process consequentially lowers the B/S ratio in the open Arctic Ocean, compared to the established global ocean ratio. Nevertheless, the incorporation of B into the sea ice reservoir does not fully account for the deficit of B in the Arctic Ocean samples, suggesting further accounting of B Arctic pathways is necessary. In future climate scenarios involving increased sea ice melt, the transition from multiyear to annual sea ice, permafrost thaw, and increased riverine discharge, the behavior of B in the Arctic Ocean is expected to become more dynamic.

A century of variability of heatwave-driven streamflow in melt-driven basins and implications under climate change

Abstract Meltwater runoff from snow and glaciers in high mountain regions supports the water needs of hundreds of millions of people, but extreme events such as heatwaves modify the timing and magnitude of water available for downstream communities and ecosystems. The streamflow response to heatwaves depends strongly on heatwave timing and temperature, and the amount of snow and glacier ice available to melt. However, as ongoing climate change continues to alter both seasonal melt patterns and the frequency and intensity of heatwaves, it is not well understood how such streamflow responses will evolve relative to the seasonal cycle of streamflow. We address this knowledge gap by using long-term meteorological and hydrological datasets to characterize spatial and temporal heterogeneity in the streamflow sensitivity to heatwaves at six basins with >80 years of observations in Western Canada. We use years with earlier freshets and less snowfall as proxies of anticipated climate change, and apply a metric to describe how the streamflow sensitivity to heatwaves varies across years with different hydro-climatological characteristics. We find that in future proxy years relative to baseline years, nival streamflow is more sensitive to early spring heatwaves but less sensitive to late spring and summer heatwaves. Relative to baseline years, late spring heatwaves in future proxy years generate a smaller fraction of peak streamflow that is diminished as the freshet progresses. Our findings imply that future heatwave-driven peak flows in spring may be lessened by the diminished streamflow sensitivity to heatwaves in late spring, but this may be partially offset by excess melt during future heatwaves that are longer and hotter.

Modelling lateral meltwater flow and superimposed ice formation atop Greenland's near-surface ice slabs

Abstract At high elevations on the Greenland ice sheet meltwater percolates and refreezes in place, and hence does not contribute to mass loss. However, meltwater generation and associated surface runoff is occurring from increasingly higher altitudes, causing changes in firn stratigraphy that have led to the presence of near-surface ice slabs. These ice slabs force meltwater to flow laterally instead of percolating downwards. Here we present a simple, physics-based quasi-2-D model to simulate lateral meltwater runoff and superimposed ice (SI) formation on top of ice slabs. Using an Eulerian Darcy flow scheme, the model calculates how far meltwater can travel within a melt season and when it appears at the snow surface. Results show that lateral flow is a highly efficient runoff mechanism, as lateral outflow exceeds locally generated meltwater in all model gridcells, with total meltwater discharge sometimes reaching more than 30 times the average amount of in situ generated melt. SI formation, an important process in the formation and thickening of the ice slabs, can retain up to 40% of the available meltwater, and generally delays the appearance of visible runoff. Validating the model against field- or remote-sensing data remains challenging, but the results presented here are a first step towards a more comprehensive understanding and description of the hydrological system in the accumulation zone of the southwestern Greenland ice sheet.

A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks

Our understanding of the impact of climate change on water availability and natural hazards in high-mountain regions is limited due to the spatial and temporal scarcity of ground observations of precipitation and snow. Freely available, satellite-based information about the snowpack is currently mainly limited to indirect measurements of snow-covered area or very coarse-scale snow water equivalent (SWE), but only for flat areas in lowlands without vegetation cover. Novel space-based laser altimeters, such as ICESat-2, have the potential to provide high-resolution snow depth data in worldwide mountain regions where no ground observations exist. However, these space-based laser altimeters come with spatial gaps between ground tracks, obtained without repetition at a give location. To overcome these drawbacks, here, we present a combined probabilistic data assimilation and deep learning approach to reconstruct spatio-temporal SWE from observations of snow depth along ground tracks, imitating ICESat-2 tracks in view of a potential future global application.Our approach is based on assimilating SWE and snow cover information in a degree-day model with an iterative ensemble smoother (IES) which allows temporally reconstructing SWE along hypothetical ground tracks separated by 3 km. As input, the degree-day model uses daily precipitation and downscaled air temperature from the ERA5 reanalysis. A feedforward neural network (FNN) is then used for spatial propagation of the daily mean and standard deviation of the updated SWE ensemble members obtained from the IES. The combined IES-FNN approach provides uncertainty-aware spatio-temporally continuous estimates of SWE.We tested our approach in the alpine Dischma valley (Switzerland) using high-resolution snow depth maps obtained from photogrammetric techniques mounted on airplanes and unmanned aerial system observations. Our results show that the IES-FNN model provides reliable estimates at a resolution of approximately 100 m. Even assimilating only one SWE observation during the year (combined with satellite-based melt-out date estimates) produces satisfying results when evaluating the IES-FNN SWE reconstructions on independent dates and smaller (<4 km2) areas: mean absolute error of 86 mm (78 mm) at Schürlialp (Latschüelfurgga) for average SWE of 180 mm (254 mm), and average spatial linear correlation with the reference SWE of 0.51 (0.48). However, the assimilated SWE observation must not be too early in the accumulation season or too late in the melt season when the snowpack is starting or ending to accumulate or melt, respectively. Smaller distances between ground tracks (1500 m and 500 m) show improved performance of the IES-FNN approach in space, with no significant improvement in terms of temporal reconstruction.Applying the IES-FNN approach to e.g., real ICESat-2 data, remains challenging due to the higher uncertainties associated with these data. However, the approach we propose remains potentially very helpful in addressing the problem of scarcity of ground observations of precipitation and snow in high-mountain regions.

Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling

Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant.

Numerical simulation of the vibration response of the permafrost subgrade under harmonic irregularity in the Qinghai-Tibet Railway

Abstract Harmonic excitation can significantly increase the dynamic response of wheel-rail interactions when a train passes. In this study, based on the train-track vertical coupled dynamics model (ZL-TNTLM) and ABAQUS, a unified train-track-subgrade coupled dynamics model is established. Field measurement data corroborated its accuracy and reliability. The analysis focused on the dynamic response of the permafrost subgrade of the Qinghai-Tibet Railway (QTR) to harmonic excitation, including the track-sleeper force and vertical dynamic stress. This study examined the influences of the wavelength, wave depth, and railhead depression on the dynamic response of a subgrade. The results indicated that single-harmonic excitation amplifies the track-sleeper forces and the vertical dynamic stress in the subgrade, particularly near the harmonic centre. Additionally, axle load variations and seasonal thawing broaden the dynamic stress range on the subgrade, with harmonic excitation exacerbating this impact, thereby increasing the risk to the stability of the ice-rich permafrost layer. A decrease in wavelength and increase in wave depth result in a greater number of affected sleepers, intensifying the vertical vibrations of the subgrade, especially in the medium- and high-frequency ranges of vertical dynamic stress. Notably, wavelengths between 1 and 2 m significantly exacerbate the adverse effects on the ice-rich permafrost layer. Shorter wavelengths also induce higher-frequency vibrations. These findings offer valuable insights for the design, operation, and maintenance of permafrost subgrade systems under irregular excitation.

Incidence angle dependency and seasonal evolution of L and C-band SAR backscatter over landfast sea ice

Abstract We estimate sea-ice type specific incidence angle (IA) dependencies for dual polarized (HH/HV) L and C-band synthetic aperture radar (SAR) for the winter, melt onset and advanced melt seasons for level and deformed ice, using time-series of Advanced Land Observing Satellite-2 (ALOS-2) and Sentinel-1 imagery off the north-east coast of Greenland. The IA dependencies are used to radiometrically correct the L and C-band backscatter time-series, which enables analysis of their seasonal evolution. From this, we observe that the L-band backscatter intensity increases for both ice types at the transition from winter to melt onset. We use these results to estimate ice type separability and to train an IA aware Bayesian classifier at both frequencies. These results show that while both frequencies are capable of distinguishing level and deformed ice during the winter, only L-band SAR can reliably make this separation during the melt onset season. During the advanced melt season, the overall classification accuracies are similarly low for L and C-band. This study demonstrates the potential of L-band SAR for sea-ice mapping, which is highly relevant in the light of several upcoming L-band SAR missions.

Supraglacial lake evolution and its drivers in Dronning Maud Land, East Antarctica

Abstract Supraglacial lakes on Antarctic ice shelves can have far-reaching implications for ice-sheet stability, highlighting the need to understand their dynamics, controls and role in the ice-sheet mass budget. We combine a detailed satellite-based record of seasonal lake evolution in Dronning Maud Land with a high-resolution simulation from the regional climate model Modèle Atmosphérique Régional to identify drivers of lake variability between 2014 and 2021. Correlations between summer lake extents and climate parameters reveal complex relationships that vary both in space and time. Shortwave radiation contributes positively to the energy budget during summer melt seasons, but summers with enhanced longwave radiation are more prone to surface melting and ponding, which is further enhanced by advected heat from summer precipitation. In contrast, previous winter precipitation has a negative effect on summer lake extents, presumably by increasing albedo and pore space, delaying the accumulation of meltwater. Downslope katabatic or föhn winds promote ponding around the grounding zones of some ice shelves. At a larger scale, we find that summers during periods of negative southern annular mode are associated with increased ponding in Dronning Maud Land. The high variability in seasonal lake extents indicates that these ice shelves are highly sensitive to future warming or intensified extreme events.

Capacity of a set of CMIP6 models to simulate Arctic sea ice drift

Abstract Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We analyze the seasonal cycles, distribution, and evolution of sea ice in different regions from 1979 to 2014. We compare the output from selected CMIP6 models with reference data for sea ice motion. We also discuss the correlations between sea ice motion(SIM) and sea ice thickness (SIT) in reference data, and how CMIP6 models explain them. We select EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, MPI-ESM1-2-HR, and NorESM2-LM for CMIP6 study. We compare outputs with reference data: Sea ice extent (SIE) from NSIDC; SIT from PIOMAS; and SIM from the IABP buoy data. Analytical techniques include Theil-Sen and Ordinary least squares (OLS) regression. Most selected CMIP6 models have seasonal cycles of SIM lagging behind IABP observations by 1-2 month and overestimate central Arctic SIM magnitude, with MPI-ESM1-2-HR having the highest discrepancy and NorESM2-LM lowest. The models show better simulation of SIM in the ice melting season than in the growing season. Models perform worse at capturing regional differences in SIM evolution and are overly conservative when simulating the increasing trend in ice motion, especially in coastal Arctic seas during summer. There is significant negative correlation between SIT and SIM in October.

Glacier melting promotes methane emission via increased methanogenic activity in the foreland alpine meadow

Annual glacier melting alters hydrothermal conditions of the foreland alpine meadows, and causes significant fluctuations in methane (CH4) flux. Previously we found that Tibetan glacier foreland alpine meadow shifts to CH4 source from sink during the melting season, but the potential mechanisms remain unclear. This study, via combination of in-situ measurement of seasonal CH4 flux and survey of microbial species that may involve in CH4 metabolism, explores the causes of glacier melting on CH4 flux in a glacier foreland alpine meadow on Tibetan Plateau. We determined a pronounced CH4 emission (13.95 μg·m−2·h−1) in August (melting season) but CH4 uptake in June (−3.76 μg·m−2·h−1) and October (−17.77 μg·m−2·h−1), and 1.4-fold higher soil moisture in August than the other two months. This showed a direct correlation of CH4 flux with glacier melting increased soil water. Additionally, glacier melting caused more CH4 fluxes increase in hollows than in hummocks. Amplicon sequencing determined 126-fold higher abundance of mcrA, the methanogenic marker gene, in August than in June and October, and a higher relative abundance of a fungal phylum Mortierellomycota and syntrophic bacteria that convert the fatty acids, the degradation intermediates of organic complexes to CO2 and acetate, the methanogenic substrates like in August. However, no seasonal variation of pmoA, the marker gene of aerobic methanotrophs, was observed. It appears that glacier melting promotes the CH4 producing but not the consuming microorganisms, thus leading to increased CH4 emission. The findings of this work indicate that global warming resulted glacier melting would increase global CH4 emissions, and in turn worsens global warming, so an alarming positive feedback loop.

Rapid Acidification of the Arctic Chukchi Sea Waters Driven by Anthropogenic Forcing and Biological Carbon Recycling

AbstractThe acidification of coastal waters is distinguished from the open ocean because of much stronger synergistic effects between anthropogenic forcing and local biogeochemical processes. However, ocean acidification research is still rather limited in polar coastal oceans. Here, we present a 16 year (2002–2018) observational dataset in the Chukchi Sea during the rapid sea‐ice melting season to determine the long‐term changes in pH and aragonite saturation state (Ωarag). We found that pH and Ωarag significantly declined in the water column with average rates of −0.0095 ± 0.0027 years−1 and −0.0333 ± 0.0098 years−1, respectively, and are 4–6 times faster than those solely due to increasing atmospheric CO2. We attributed the rapid acidification to the increased dissolved inorganic carbon owing to a combination of ice melt‐induced increased atmospheric CO2 invasion and subsurface remineralization induced by a stronger surface biological production as a result of the increased inflow of the nutrient‐rich Pacific water.

The role of the cryosphere for runoff in a highly glacierised alpine catchment, an approach with a coupled model and in situ data

Abstract Runoff from heavily glacierised catchments, its seasonality and the contribution from different storage units are highly relevant for assessing the seasonal and long-term water supply and flood prediction. Modelling studies on runoff from such basins often use simulated meteorological input (e.g. downscaling products) based on remote observations. We investigate the contribution of snow, firn and ice to runoff in the Vernagtferner basin (Ötztal Alps) from 2020 to 2022, using a physical modelling chain driven by a local observation network. We use the SNOWPACK model to simulate snow/ice development at observation sites and the Alpine3D model to calculate accumulation and melt at the catchment scale. Basin discharge is estimated using a gridded version of the HBV-ETH model. This approach largely reproduces observed glacier mass balances, while modelled and measured basin discharge are in good agreement. Snowmelt dominates discharge in the early melt season, while ice melt becomes increasingly important during summer. This is in strong contrast to the near-equilibrium mass balances in the 1980s, when ice melt played a minor role for annual discharge. The strong reduction of the accumulation area leads to a fundamental change from a snowmelt regime to an ice melt regime, which is especially pronounced in 2022.

Ecological patterns of benthic foraminiferal communities driven by seasonal and spatial environmental gradients in an Arctic fjord

AbstractArctic fjords, being transitional areas between glacier‐covered land and the ocean, are characterized by strong environmental gradients. The seasonal melting of glaciers generates strong turbidity and primary production antagonist gradients, which can affect benthic habitats. Two sampling campaigns were carried out in Kongsfjorden (Svalbard, Arctic Ocean) in May and August 2021 to investigate seasonal changes in benthic foraminifera spatial distribution and ecosystem functioning along a longitudinal transect of 10 km from the Kronebreen tidewater glacier front. Concurrently, organic matter quantity and biochemical composition, sediment grain size, and physical parameters of the water masses were investigated as possible driving factors of benthic ecosystem responses. In a previous study, three statistically determined foraminiferal biozonations (glacier proximal, medial, and distal) were observed on the basis of their species content within the closest 10 km from the glacier front, presenting similar assemblages in both seasons. Our results indicate that foraminiferal distribution at the local scale is mainly driven by physical and geochemical gradients induced by melting waters and sediment discharges from the tidewater glacier occurring during summer. Due to the climate change, the melting season is expected to last longer and increasing global temperature will much probably accelerate the melting processes. Our findings strongly support the use of foraminifera as bioindicators to monitor the effects of ongoing climate change on the benthic ecosystems of Arctic fjords and, accessorily, as proxies for reconstructing glacier front positions in the recent past.

Spatial Distribution of Thaw Depth in Palsas Estimated From Optical Unoccupied Aerial Systems Data

ABSTRACTMaximum seasonal thaw depth, referred to as active layer thickness (ALT), is one of the key parameters used to monitor permafrost conditions. ALT maps based on interpolation of point measurements or derived from coarse or moderate spatial resolution satellite data often hide small‐scale spatial variations in thaw depth resulting from differences in surface characteristics and microtopography. To model and predict changes in hydrological and biogeochemical processes in permafrost areas accurately, high‐resolution remote sensing‐based estimations of ALT are needed. Therefore, we applied random forest (RF) regression on a set of topographical and spectral vegetation indices derived from optical unoccupied aerial systems data, Landsat 8 land surface temperature (LST) data, and field measurements to estimate thaw depths in palsas at three mires in north‐west Finland. We also analyzed differences in thaw depths between mires located at different elevations, between dome and plateau‐shaped palsas, and between different vegetation and surface cover classes. The RF models resulted in root mean square errors from 2.4 to 5.7 cm between predicted and observed thaw depths and the R2 values of 0.57–0.96. Height from the surrounding fen surface and LST were the most important variables in thaw depth models, although high‐accuracy results were also achieved without LST. The mean thaw depths did not differ between the sites with lowest and highest elevation, whereas the thaw depths were significantly deeper in dome‐shaped palsas compared to plateaus. The thaw depths were significantly different between vegetation cover classes only on plateau‐shaped palsas. The results indicate the high impact of the topography on the palsa thaw depth, thus highlighting the importance of accurate elevation models in spatial modeling of palsa ALT. The methodology presented in this study can be applied to other permafrost regions where field measurements of ALT are accompanied with high‐resolution topographical and multispectral data.

Inland Summer Speedup at Zachariæ Isstrøm, Northeast Greenland, Driven by Subglacial Hydrology

AbstractThe Northeast Greenland Ice Stream (NEGIS) has experienced substantial dynamic thinning in recent years. Here, we examine the evolving behavior of NEGIS, with focus on summer speedup at Zachariae Isstrøm, one of the NEGIS outlet glaciers, which has exhibited rapid retreat and acceleration, indicative of its vulnerability to changing climate conditions. Through a combination of Sentinel‐1 data, in‐situ GPS observations, and numerical ice flow modeling from 2007, we investigate the mechanisms driving short‐term changes. Our analysis reveals a summer speedup in ice flow both near the terminus and inland, with satellite data detecting changes up to 60 km inland, while GPS data capture changes up to 190 km inland along the glacier center line. We attribute this summer speedup to variations in subglacial hydrology, where surface meltwater runoff influences basal friction over the melt season. Incorporating subglacial hydrology into numerical models makes it possible to replicate observed ice velocity patterns.

Summer heat wave in 2022 led to rapid warming of permafrost in the central Qinghai-Tibet Plateau

Extreme events with increasing frequency and intensity are significantly affecting the permafrost environment. Analysis using the ERA5-Land reanalysis data revealed that the permafrost region of the central Qinghai-Tibet Plateau (QTP) experienced the summer heat wave in 2022. Four active layer sites experienced maximum active layer thicknesses (ALT) in 2022 (mean: 207.7 cm), which was 20% higher than the mean ALT during 2000–2021 (mean: 175.9 cm). The mean annual ground temperature (MAGT) observed in 2022 was also the highest, exceeding the average of the previous years by 10%. The contribution fraction of heat wave to the seasonal thaw depth of active layer was quantified using Stefan model with ranging from 6.6% to 13.6%, and the maximum contribution fraction occurs in 2022. These findings are helpful to better understand the impact processes of extreme events on the active layer and permafrost.

Chlorophyll Production in the Amundsen Sea Boosts Heat Flux to Atmosphere and Weakens Heat Flux to Ice Shelves

AbstractThe Amundsen Sea in West Antarctica features rapidly thinning ice shelves, large polynyas, and sizable spring phytoplankton blooms. Although considerable effort has gone into characterizing heat fluxes between the Amundsen Sea, its associated ice shelves, and the overlying atmosphere, the effect of the phytoplankton blooms on the distribution of heat remains poorly understood. In this modeling study, we implement a feedback from biogeochemistry onto physics into MITgcm‐BLING and use it to show that high levels of chlorophyll—concentrated in the Amundsen Sea Polynya and the Pine Island Polynya—have the potential to increase springtime surface warming in polynyas by steepening the attenuation profile of solar radiation with depth. The chlorophyll‐associated warm anomaly (on average between +0.2C and +0.3C) at the surface is quickly dissipated to the atmosphere, by increases in longwave, latent and sensible heat loss from open water areas. Outside of the coastal polynyas, the summertime warm anomaly leads to an average sea ice thinning of 1.7 cm across the region, and stimulates up to 20% additional seasonal melting near the fronts of ice shelves. The accompanying cold anomaly, caused by shading of deeper waters, persists year‐round and affects a decrease in the volume of Circumpolar Deep Water on the continental shelf. This cooling ultimately leads to an average sea ice thickening of 3.5 cm and, together with associated changes to circulation, reduces basal melting of Amundsen Sea ice shelves by approximately 7% relative to the model scenario with no phytoplankton bloom.

Toward long-term monitoring of regional permafrost thaw with satellite interferometric synthetic aperture radar

Abstract. Active-layer thickness (ALT) is estimated for a study area in northern Alaska's continuous-permafrost zone using satellite data from Sentinel-1 (radar) and ICESat-2 (lidar) for the period 2017 to 2022. Synthetic aperture radar (SAR) interferograms were generated using the Short Baseline Subset (SBAS) approach. Displacement time series over the thaw season (June–September) are fit well with a linear model (root mean square error (RMSE) scatter is less than 7 mm) and show maximum seasonal subsidence of 20–60 mm. ICESat-2 products were used to validate the interferometric synthetic aperture radar (InSAR) displacement time series. ALT was estimated from measured subsidence using a widely used model exploiting the volume difference between ice and water, reaching a maximum depth in our study area of 1.5 m. Estimated ALT is in good agreement with in situ and other remotely sensed data but is sensitive to assumed thaw season onset, indicating the need for reliable surface temperature data. Our results suggest the feasibility of long-term permafrost monitoring with satellite InSAR. However, the C-band (∼55 mm center wavelength) Sentinel radar is sensitive to vegetation cover and, in our studies, was not successful for similar monitoring in the heavily treed discontinuous-permafrost zone of central Alaska.

Estimates of carbon sequestration potential in an expanding Arctic fjord (Hornsund, Svalbard) affected by dark plumes of glacial meltwater

Abstract. In polar regions, glaciers are retreating onto land, gradually widening ice-free coastal waters, which are known to act as new sinks of atmospheric carbon. However, the increasing delivery of inorganic suspended particulate matter (iSPM) with meltwater might significantly impact their capacity to contribute to carbon sequestration. Here, we present an analysis of satellite, meteorological, and SPM data as well as results of a coupled physical–biogeochemical model (1D GOTM-ECOSMO-E2E-Polar) with a newly implemented iSPM group to show the impact of iSPM on the ecosystem dynamics in a warming polar fjord (Hornsund, European Arctic) with numerous shallow-grounded marine-terminating glaciers. Our results indicate that with a longer melt season (9 d per decade, 1979–2022), the loss of sea ice cover (44 d per decade, 1982–2021) and the formation of new marine habitats after the retreat of marine-terminating glaciers (around 100 km2 in 1976–2022, a 38 % increase in the total area), glacial meltwater has transported increasing loads of iSPM from land (3.7 g m−3 per decade, reconstructed for 1979–2022). The simulated light limitation induced by the iSPM input delayed and decreased the peaks in phytoplankton, zooplankton, and macrobenthos. The newly ice-free areas still markedly contributed to plankton primary and secondary production and carbon burial in sediments (5.1, 2.0, and 0.9 Gg C yr−1, respectively, on average for 2005–2009 in the iSPM scenario). However, these values would have been 5.0, 2.1, and 0.1 Gg C yr−1 higher, respectively, without the iSPM input. Since carbon burial was the least affected by iSPM (a decrease of around 16 %, in comparison to 50 % for plankton primary and secondary production), the impact of marine ice loss and enhanced land–ocean connectivity should be investigated further in the context of carbon fluxes in expanding polar fjords.