Ice Sheet Surface Research Articles

Validation and Analysis of the ICESat-2 ATL11 Product: A Case Study of Lake Vostok

Elevation changes are crucial input data for mass balance assessment based on satellite altimetry. However, due to the accuracy limitations of altimetry data and mass conversion models, a significant uncertainty remains in estimating the mass balance of the Antarctic ice sheet, especially in East Antarctica. The ICESat-2 photon altimetry satellite enhances the precision of ice sheet surface elevation measurements to an accuracy of 2–4 cm. This improvement is particularly beneficial for detecting subtle elevation changes in East Antarctica. The ATL11 product from ICESat-2 offers a time series of ice surface elevations across Antarctica, enabling direct calculation of elevation change rates. To evaluate the capability of the ATL11 product in accurately depicting detailed elevation changes within the local terrain, we selected the Vostok Subglacial Lake as the validation region. Our research involves comparing fitted surface elevation change rates with in-situ data, while also considering surface mass balance, wind, and surface elevation to analyze the factors contributing to small differences in elevation changes within the local lake area. This analysis aims to identify the factors contributing to the minor variations in elevation changes within the local lake area. According to our analysis, the Vostok Lake surface elevation change rate is 2.00 ± 0.77 cm yr−1 from April 2019 to June 2023, with an average period of 356 ± 81 days. The results demonstrate that the ATL11 elevation product sequence has the potential to accurately characterize subtle elevation changes and seasonal variations in the Antarctic ice sheet.

An extreme precipitation event over Dronning Maud Land, East Antarctica - A case study of an atmospheric river event using the Polar WRF Model

Extreme precipitation events (EPEs) are crucial in Antarctica, impacting the Antarctic ice sheet's surface mass balance and stability. Comprehensive case studies are essential for better understanding these events and the underlying processes driving them. Here, we investigate an extreme snowfall event in Dronning Maud Land (DML), East Antarctica on November 8 and 9, 2015. This event contributed approximately 22 % of the annual accumulation in less than two days and exhibited high spatial variability in precipitation distribution. We employed a high-resolution atmospheric model specifically optimized for the polar regions (Polar WRF) and ERA5 reanalysis data to analyze the event in detail. Our findings highlight the importance of a blocking high-pressure ridge of record strength that effectively blocked and diverted a strong extratropical cyclone into DML, ultimately leading to the heavy snowfall event. The sudden deepening of the cyclone was initiated by a ‘jet streak’ in the upper atmosphere that steered the system southeastwards towards the Antarctic coast. Notably, we observed an anomalously high poleward moisture transport in the form of a strong atmospheric river on November 7, 2015. This atmospheric river originated in the South Atlantic Ocean and tracked poleward from the 30°S-40°S latitude band. Vertical cross-sections of the model outputs indicate that most of the precipitation was concentrated in regions with steep orography along the path of the atmospheric river. This interaction between the atmospheric river and the steep terrain led to the uplift of maritime air, resulting in heavy snowfall. This study highlights the significance of extreme upper and lower atmospheric conditions in driving intense moisture transport towards coastal DML. The interaction between the atmospheric river and the steep orography contributed to heavy snowfall, underscoring the importance of considering orographic influences in understanding EPEs in Antarctica.

Assessment of various microwave brightness temperature products and methods for surface melt detection over Greenland ice sheet

Microwave brightness temperature have widely been used for the detection of the ice sheet's surface melt conditions and understanding their spatio-temporal variability. In this study, we investigated the sensitivity of microwave brightness temperature products from three different sensors, namely, Advanced Microwave Scanning Radiometer-2 (AMSR2), Special Sensor Microwave Imager/Sounder (SSMIS) and Indian scatterometer satellite (SCATSAT-1) for surface melt detection over the Greenland ice sheet (GrIS). In-situ air temperature measurements from GC-Net AWSs were used for sensitivity and inter-comparison analysis. Our findings show that brightness temperature (Tb) from SSMIS better correlates (Pcoef = 0.81 for 19 GHz) with air temperature measurements in comparison to AMSR2 (Pcoef = 0.7 for 18 GHz) and SCATSAT-1 (Pcoef = 0.67). However, interestingly, AMSR2 and SCATSAT-1 uniquely discriminated the surface conditions during pre- and post-melt period, due to their heterogeneity in Tb values during the two period. Error analysis with respect to AWS melt days shows that SSMIS 19 GHz Tb (Tb/SSMIS/19H) products with TED method giving the most promising observations. A wide variability in Tb values is observed during the melt season across the various AWS sites depending upon the elevation, location and frequency. During our study period, using Tb/SSMIS/19H for TED method, we observed the highest melt extent area for the extreme melt event in year 2019 (∼1.12 million km2), followed by another melt event year 2021 when it went as high as ∼1.02 million km2.

A comparative study of mass balance in the Lambert Glacier and Amery Ice Shelf along the Chinese inland traverse during 2019–2023 using altimetry, gravity, and in-situ observations

Abstract. The new photon-counting laser altimetry satellite ICESat-2 was successfully launched on September 15, 2018 with an unprecedented ice surface elevation measurement accuracy of 2–4 cm. It is meaningful for accurately estimating volumetric changes in the Antarctic Ice Sheet. Cross-validation of different types of data, especially comparison with in-situ data, is important for the ice sheet mass balance results of a new satellite. This paper proposes an elevation-difference method of grid elevation change rate model, based on ICESat-2 ATL11 elevation time series data, to distinguish the linear change trend of ice sheet surface elevation from the elevation change resulting from periodic precipitation. In order to compare the estimated elevation-change rate with the flux computed from in-situ snow stake velocity measurements and GRACE-FO gravity survey data, we made corrections for firn air content, elastic, and glacier isostatic adjustment. Based on the ATL11 data from 2019 to 2023, our results show that the ice sheet change in Basin 11 along the CHINARE traverse is from ~0.019 m yr−1 to ~0.121 m yr−1, and the mass balance in the upstream of the traverse in Basin 11 is ~1.9±0.2 Gt yr−1. It is comparable to ~2.4±1.2 Gt yr−1 from GRACE-FO during the same time period. Furthermore, the flux across traverse-11.9±1.1 Gt yr−1 is comparable to that of ~-9.7±0.9 Gt yr−1 across the same flux gate during 1997–2009 which is calculated based on GNSS-derived ice velocity observations, considering the time period difference and uncertainties.

Influence of Supraglacial Lakes on Accuracy of Inversion of Greenland Ice Sheet Surface Melt Data in Different Passive Microwave Bands

The occurrence of Supraglacial Lakes (SGLs) may influence the signals acquired with microwave radiometers, which may result in a degree of uncertainty when employing microwave radiometer data for the detection of surface melt. Accurate monitoring of surface melting requires a reasonable assessment of this uncertainty. However, there is a scarcity of research in this field. Therefore, in this study, we computed surface melt in the vicinity of Automatic Weather Stations (AWSs) by employing Defense Meteorological Satellite Program (DMSP) Ka-band data and Soil Moisture and Ocean Salinity (SMOS) satellite L-band data and extracted SGL pixels by utilizing Sentinel-2 data. A comparison between surface melt results derived from AWS air temperature estimates and those obtained with remote sensing inversion in the two different bands was conducted for sites below the mean snowline elevation during the summers of 2016 to 2020. Compared with sites with no SGLs, the commission error (CO) of DMSP morning and evening data at sites where these water bodies were present increased by 36% and 30%, respectively, and the number of days with CO increased by 12 and 3 days, respectively. The omission error (OM) of SMOS morning and evening data increased by 33% and 32%, respectively, and the number of days with OM increased by 17 and 21 days, respectively. Identifying the source of error is a prerequisite for the improvement of surface melt algorithms, for which this study provides a basis.

Ice acceleration and rotation in the Greenland Ice Sheet interior in recent decades

In the past two decades, mass loss from the Greenland ice sheet has accelerated, partly due to the speedup of glaciers. However, uncertainty in speed derived from satellite products hampers the detection of inland changes. In-situ measurements using stake surveys or GPS have lower uncertainties. To detect inland changes, we repeated in-situ measurements of ice-sheet surface velocities at 11 historical locations first measured in 1959, located upstream of Jakobshavn Isbræ, west Greenland. Here, we show ice velocities have increased by 5–15% across all deep inland sites. Several sites show a northward deflection of 3–4.5° in their flow azimuth. The recent appearance of a network of large transverse surface crevasses, bisecting historical overland traverse routes, may indicate a fundamental shift in local ice dynamics. We suggest that creep instability—a coincident warming and softening of near-bed ice layers—may explain recent acceleration and rotation, in the absence of an appreciable change in local driving stress.

Alpine topography of the Gamburtsev Subglacial Mountains, Antarctica, mapped from ice sheet surface morphology

Abstract. Landscapes buried beneath the Antarctic Ice Sheet preserve information about the geologic and geomorphic evolution of the continent both before and during the wide-scale glaciation that began roughly 34×106 years ago. Since the inception of this ice sheet, some areas have remained cold-based and non-erosive, preserving ancient landscapes remarkably intact. The Gamburtsev Subglacial Mountains in central East Antarctica are one such landscape, maintaining evidence of tectonic, fluvial and glacial controls on their distinctly alpine morphology. The central Gamburtsev Mountains have previously been surveyed using airborne ice-penetrating radar; however, many questions remain as to their evolution and their influence on the East Antarctic Ice Sheet, including where in the region to drill for a 1.5×106 year-long “oldest-ice” core. Here, we derive new maps of the planform geometry of the Gamburtsev Subglacial Mountains from satellite remote sensing datasets of the ice sheet surface, based on the relationship between bed roughness and ice surface morphology. Automated and manual approaches to mapping were tested and validated against existing radar data and elevation models. Manual mapping was more effective than automated approaches at reproducing bed features observed in radar data, but a hybrid approach is suggested for future work. The maps produced here show the detail of mountain ridges and valleys on wavelengths significantly smaller than the spacing of existing radar flightlines, and mapping has extended well beyond the confines of existing radar surveys. Morphometric analysis of the mapped landscape reveals that it constitutes a preserved (>34 Ma) dendritic valley network, with some evidence for modification by topographically confined glaciation prior to ice sheet inception. The planform geometry of the landscape is a significant control on locations of basal melting, subglacial hydrological flows and the stability of the ice sheet over time, so the maps presented here may help to guide decisions about where to search for oldest ice.

The Effect of Physically Based Ice Radiative Processes on Greenland Ice Sheet Albedo and Surface Mass Balance in E3SM

AbstractA significant portion of surface melt on the Greenland Ice Sheet (GrIS) is due to dark ice regions in the ablation zone, where solar absorption is influenced by the physical properties of the ice, light absorbing constituents (LACs), and the overlying crustal surface or melt ponds. Earth system models (ESMs) typically prescribe the albedo of ice surfaces as a constant value in the visible and near‐infrared spectral regions. This work advances ESM ice radiative transfer modeling by (a) incorporating a physically based radiative transfer model (SNow, ICe and Aerosol Radiation model Adding‐Doubling Version 4; SNICAR‐ADv4) into the Energy Exascale Earth System Model (E3SM), (b) determining spatially and temporally varying bare ice physical properties over the GrIS ablation zone from satellite observations to inform SNICAR‐ADv4, and (c) assessing the impacts on simulated GrIS albedo and surface mass balance associated with modeling of more realistic bare ice albedo. GrIS‐wide bare ice albedo in E3SMv2 is overestimated by ∼4% in the visible and ∼7% in the near‐infrared wavelengths compared to the Moderate Resolution Imaging Spectroradiometer. Our bare ice physical property retrieval method found that LACs, ice crustal surfaces, and melt ponds reduce visible albedo by 30% in the bare ice region of the GrIS ablation zone. The realistic bare ice albedo reduces surface mass balance by ∼145 Gt, or 0.4 mm of sea‐level equivalent between 2000 and 2021 compared to the default E3SM. This work highlights the importance of simulating bare ice albedo accurately and realistically to improve our ability to quantify changes in the GrIS surface mass and radiative energy budgets.

The distinctive weathering crust habitat of a High Arctic glacier comprises discrete microbial micro-habitats.

Sunlight penetrates the ice surfaces of glaciers and ice sheets, forming a water-bearing porous ice matrix known as the weathering crust. This crust is home to a significant microbial community. Despite the potential implications of microbial processes in the weathering crust for glacial melting, biogeochemical cycles, and downstream ecosystems, there have been few explorations of its microbial communities. In our study, we used 16S rRNA gene sequencing and shotgun metagenomics of a Svalbard glacier surface catchment to characterise the microbial communities within the weathering crust, their origins and destinies, and the functional potential of the weathering crust metagenome. Our findings reveal that the bacterial community in the weathering crust is distinct from those in upstream and downstream habitats. However, it comprises two separate micro-habitats, each with different taxa and functional categories. The interstitial porewater is dominated by Polaromonas, influenced by the transfer of snowmelt, and exported via meltwater channels. In contrast, the ice matrix is dominated by Hymenobacter, and its metagenome exhibits a diverse range of functional adaptations. Given that the global weathering crust area and the subsequent release of microbes from it are strongly responsive to climate projections for the rest of the century, our results underscore the pressing need to integrate the microbiome of the weathering crust with other communities and processes in glacial ecosystems.

Lessons learned from shallow subglacial bedrock drilling campaigns in Antarctica

Abstract We review successes and challenges from five recent subglacial bedrock drilling campaigns intended to find evidence for Antarctic Ice Sheet retreat during warm periods in the geologic past. Insights into times when the polar ice sheets were smaller than present serve as guiding information for modeling efforts that aim to predict the rate and magnitude of future sea level rise that would accompany major retreat of the Antarctic Ice Sheet. One method to provide direct evidence for the timing of deglaciations and minimum extent of prior ice sheets is to extract subglacial bedrock cores for cosmogenic nuclide analysis from beneath the modern ice sheet surface. Here we summarize the lessons learned from five field seasons tasked with obtaining bedrock cores from shallow depths (<120 m beneath ice surface) across West Antarctica since 2016. We focus our findings on drilling efforts and technology and geophysical surveys with ground-penetrating radar. Shallow subglacial drilling provides a high risk, high reward means to test for past instabilities of the Antarctic Ice Sheet, and we highlight key challenges and solutions to increase the likelihood of success for future subglacial drilling efforts in polar regions.

Alpine glacier algal bloom during a record melt year.

Glacier algal blooms dominate the surfaces of glaciers and ice sheets during summer melt seasons, with larger blooms anticipated in years that experience the greatest melt. Here, we characterize the glacier algal bloom proliferating on Morteratsch glacier, Switzerland, during the record 2022 melt season, when the Swiss Alps lost three times more ice than the decadal average. Glacier algal cellular abundance (cells ml-1), biovolume (μm3 cell-1), photophysiology (Fv/Fm, rETRmax), and stoichiometry (C:N ratios) were constrained across three elevations on Morteratsch glacier during late August 2022 and compared with measurements of aqueous geochemistry and outputs of nutrient spiking experiments. While a substantial glacier algal bloom was apparent during summer 2022, abundances ranged from 1.78 × 104 to 8.95 × 105 cells ml-1 of meltwater and did not scale linearly with the magnitude of the 2022 melt season. Instead, spatiotemporal heterogeneity in algal distribution across Morteratsch glacier leads us to propose melt-water-redistribution of (larger) glacier algal cells down-glacier and presumptive export of cells from the system as an important mechanism to set overall bloom carrying capacity on steep valley glaciers during high melt years. Despite the paradox of abundant glacier algae within seemingly oligotrophic surface ice, we found no evidence for inorganic nutrient limitation as an important bottom-up control within our study site, supporting our hypothesis above. Fundamental physical constraints may thus cap bloom carrying-capacities on valley glaciers as 21st century melting continues.

Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning

Abstract. Surface melt on the Greenland ice sheet has been increasing in intensity and extent over the last decades due to Arctic atmospheric warming. Surface melt depends on the surface energy balance, which includes the atmospheric forcing but also the thermal budget of the snow, firn and ice near the ice sheet surface. The temperature of the ice sheet subsurface has been used as an indicator of the thermal state of the ice sheet's surface. Here, we present a compilation of 4612 measurements of firn and ice temperature at 10 m below the surface (T10 m) across the ice sheet, spanning from 1912 to 2022. The measurements are either instantaneous or monthly averages. We train an artificial neural network model (ANN) on 4597 of these point observations, weighted by their relative representativity, and use it to reconstruct T10 m over the entire Greenland ice sheet for the period 1950–2022 at a monthly timescale. We use 10-year averages and mean annual values of air temperature and snowfall from the ERA5 reanalysis dataset as model input. The ANN indicates a Greenland-wide positive trend of T10 m at 0.2 ∘C per decade during the 1950–2022 period, with a cooling during 1950–1985 (−0.4 ∘C per decade) followed by a warming during 1985–2022 (+0.7 ∘ per decade). Regional climate models HIRHAM5, RACMO2.3p2 and MARv3.12 show mixed results compared to the observational T10 m dataset, with mean differences ranging from −0.4 ∘C (HIRHAM) to 1.2 ∘C (MAR) and root mean squared differences ranging from 2.8 ∘C (HIRHAM) to 4.7 ∘C (MAR). The observation-based ANN also reveals an underestimation of the subsurface warming trends in climate models for the bare-ice and dry-snow areas. The subsurface warming brings the Greenland ice sheet surface closer to the melting point, reducing the amount of energy input required for melting. Our compilation documents the response of the ice sheet subsurface to atmospheric warming and will enable further improvements of models used for ice sheet mass loss assessment and reduce the uncertainty in projections.

Disentangling the drivers of future Antarctic ice loss with a historically calibrated ice-sheet model

Abstract. We use an observationally calibrated ice-sheet model to investigate the future trajectory of the Antarctic ice sheet related to uncertainties in the future balance between sub-shelf melting and ice discharge, on the one hand, and the surface mass balance, on the other. Our ensemble of simulations, forced by a panel of climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), suggests that the ocean will be the primary driver of short-term Antarctic mass loss, initiating ice loss in West Antarctica already during this century. The atmosphere initially plays a mitigating role through increased snowfall, leading to an Antarctic contribution to global mean sea-level rise by 2100 of 6 (−8 to 15) cm under a low-emission scenario and 5.5 (−10 to 16) cm under a very high-emission scenario. However, under the very high-emission pathway, the influence of the atmosphere shifts beyond the end of the century, becoming an amplifying driver of mass loss as the ice sheet's surface mass balance decreases. We show that this transition occurs when Antarctic near-surface warming exceeds a critical threshold of +7.5 ∘C, at which the increase in surface runoff outweighs the increase in snow accumulation, a signal that is amplified by the melt–elevation feedback. Therefore, under the very high-emission scenario, oceanic and atmospheric drivers are projected to result in a complete collapse of the West Antarctic ice sheet along with significant grounding-line retreat in the marine basins of the East Antarctic ice sheet, leading to a median global mean sea-level rise of 2.75 (6.95) m by 2300 (3000). Under a more sustainable socio-economic pathway, we find that the Antarctic ice sheet may still contribute to a median global mean sea-level rise of 0.62 (1.85) m by 2300 (3000). However, the rate of sea-level rise is significantly reduced as mass loss is likely to remain confined to the Amundsen Sea Embayment, where present-day climate conditions seem sufficient to commit to a continuous retreat of Thwaites Glacier.

Extreme events of snow grain size increase in East Antarctica and their relationship with meteorological conditions

Abstract. This study explores the seasonal variations in snow grain size on the East Antarctic Plateau, where dry metamorphism occurs, by using microwave radiometer observations from 2000 to 2022. Local meteorological conditions and large-scale atmospheric phenomena have been considered in order to explain some peculiar changes in the snow grains. We find that the highest ice divide is the region with the largest grain size in the summer, mainly because the wind speed is low. Moreover, some extreme grain size values with respect to the average (over +3σ) were identified. In these cases, the ERA5 reanalysis revealed a high-pressure blocking close to the onsets of the summer increase in the grain size. It channels moisture intrusions from the mid-latitudes, through atmospheric rivers that cause major snowfall events over the plateau. If conditions of weak wind and low temperature occur during the following weeks, dry snow metamorphism is facilitated, leading to grain growth. This determines anomalous high maximums of the snow grain size at the end of summer. These phenomena confirm the importance of moisture intrusion events in East Antarctica and their impact on the physical properties of the ice sheet surface, with a co-occurrence of atmospheric rivers and seasonal changes in the grain size with a significance of over 95 %.

A stochastic parameterization of ice sheet surface mass balance for the Stochastic Ice-Sheet and Sea-Level System Model (StISSM v1.0)

Abstract. Many scientific and societal questions that draw on ice sheet modeling necessitate sampling a wide range of potential climatic changes and realizations of internal climate variability. For example, coastal planning literature demonstrates a demand for probabilistic sea level projections with quantified uncertainty. Further, robust attribution of past and future ice sheet change to specific processes or forcings requires a full understanding of the space of possible ice sheet behaviors. The wide sampling required to address such questions is computationally infeasible with sophisticated numerical climate models at the resolution required to accurately force ice sheet models. Stochastic generation of climate forcing of ice sheets offers a complementary alternative. Here, we describe a method to construct a stochastic generator for ice sheet surface mass balance varying in time and space. We demonstrate the method with an application to Greenland Ice Sheet surface mass balance for 1980–2012. We account for spatial correlations among glacier catchments using sparse covariance techniques, and we apply an elevation-dependent downscaling to recover gridded surface mass balance fields suitable for forcing an ice sheet model while including feedback from changing ice sheet surface elevation. The efficiency gained in the stochastic method supports large-ensemble simulations of ice sheet change in a new stochastic ice sheet model. We provide open source Python workflows to support use of our stochastic approach for a broad range of applications.

Surface mass balance and climate of the Last Glacial Maximum Northern Hemisphere ice sheets: simulations with CESM2.1

Abstract. The Last Glacial Maximum (LGM, from ∼26 to 20 ka BP) was the most recent period with large ice sheets in Eurasia and North America. At that time, global temperatures were 5–7 ∘C lower than today, and sea level ∼125 m lower. LGM simulations are useful to understand earth system dynamics, including climate–ice sheet interactions, and to evaluate and improve the models representing those dynamics. Here, we present two simulations of the Northern Hemisphere ice sheet climate and surface mass balance (SMB) with the Community Earth System Model v2.1 (CESM2.1) using the Community Atmosphere Model v5 (CAM5) with prescribed ice sheets for two time periods that bracket the LGM period: 26 and 21 ka BP. CESM2.1 includes an explicit simulation of snow/firn compaction, albedo, refreezing, and direct coupling of the ice sheet surface energy fluxes with the atmosphere. The simulated mean snow accumulation is lowest for the Greenland and Barents–Kara Sea ice sheets (GrIS, BKIS) and highest for British and Irish (BIIS) and Icelandic (IcIS) ice sheets. Melt rates are negligible for the dry BKIS and GrIS, and relatively large for the BIIS, North American ice sheet complex (NAISC; i.e. Laurentide, Cordilleran, and Innuitian), Scandinavian ice sheet (SIS), and IcIS, and are reduced by almost a third in the colder (lower temperature) 26 ka BP climate compared with 21 ka BP. The SMB is positive for the GrIS, BKIS, SIS, and IcIS during the LGM (26 and 21 ka BP) and negative for the NAISC and BIIS. Relatively wide ablation areas are simulated along the southern (terrestrial), Pacific and Atlantic margins of the NAISC, across the majority of the BIIS, and along the terrestrial southern margin of the SIS. The integrated SMB substantially increases for the NAISC and BIIS in the 26 ka BP climate, but it does not reverse the negative sign. Summer incoming surface solar radiation is largest over the high interior of the NAISC and GrIS, and minimum over the BIIS and southern margin of NAISC. Summer net radiation is maximum over the ablation areas and minimum where the albedo is highest, namely in the interior of the GrIS, northern NAISC, and all of the BKIS. Summer sensible and latent heat fluxes are highest over the ablation areas, positively contributing to melt energy. Refreezing is largest along the equilibrium line altitude for all ice sheets and prevents 40 %–50 % of meltwater entering the ocean. The large simulated melt for the NAISC suggests potential biases in the climate simulation, ice sheet reconstruction, and/or highly non-equilibrated climate and ice sheet at the LGM time.

A New Spatially and Temporally Continuous Antarctic Ice-Sheet Surface Temperature Retrieval Method From Passive Microwave Swath Data

A New Spatially and Temporally Continuous Antarctic Ice-Sheet Surface Temperature Retrieval Method From Passive Microwave Swath Data

The undiscovered biosynthetic potential of the Greenland Ice Sheet microbiome.

The Greenland Ice Sheet is a biome which is mainly microbially driven. Several different niches can be found within the glacial biome for those microbes able to withstand the harsh conditions, e.g., low temperatures, low nutrient conditions, high UV radiation in summer, and contrasting long and dark winters. Eukaryotic algae can form blooms during the summer on the ice surface, interacting with communities of bacteria, fungi, and viruses. Cryoconite holes and snow are also habitats with their own microbial community. Nevertheless, the microbiome of supraglacial habitats remains poorly studied, leading to a lack of representative genomes from these environments. Under-investigated extremophiles, like those living on the Greenland Ice Sheet, may provide an untapped reservoir of chemical diversity that is yet to be discovered. In this study, an inventory of the biosynthetic potential of these organisms is made, through cataloging the presence of biosynthetic gene clusters in their genomes. There were 133 high-quality metagenome-assembled genomes (MAGs) and 28 whole genomes of bacteria obtained from samples of the ice sheet surface, cryoconite, biofilm, and snow using culturing-dependent and -independent approaches. AntiSMASH and BiG-SCAPE were used to mine these genomes and subsequently analyze the resulting predicted gene clusters. Extensive sets of predicted Biosynthetic Gene Clusters (BGCs) were collected from the genome collection, with limited overlap between isolates and MAGs. Additionally, little overlap was found in the biosynthetic potential among different environments, suggesting specialization of organisms in specific habitats. The median number of BGCs per genome was significantly higher for the isolates compared to the MAGs. The most talented producers were found among Proteobacteria. We found evidence for the capacity of these microbes to produce antimicrobials, carotenoid pigments, siderophores, and osmoprotectants, indicating potential survival mechanisms to cope with extreme conditions. The majority of identified BGCs, including those in the most prevalent gene cluster families, have unknown functions, presenting a substantial potential for bioprospecting. This study underscores the diverse biosynthetic potential in Greenland Ice Sheet genomes, revealing insights into survival strategies and highlighting the need for further exploration and characterization of these untapped resources.

Higher Antarctic ice sheet accumulation and surface melt rates revealed at 2 km resolution

Antarctic ice sheet (AIS) mass loss is predominantly driven by increased solid ice discharge, but its variability is governed by surface processes. Snowfall fluctuations control the surface mass balance (SMB) of the grounded AIS, while meltwater ponding can trigger ice shelf collapse potentially accelerating discharge. Surface processes are essential to quantify AIS mass change, but remain poorly represented in climate models typically running at 25-100 km resolution. Here we present SMB and surface melt products statistically downscaled to 2 km resolution for the contemporary climate (1979-2021) and low, moderate and high-end warming scenarios until 2100. We show that statistical downscaling modestly enhances contemporary SMB (3%), which is sufficient to reconcile modelled and satellite mass change. Furthermore, melt strongly increases (46%), notably near the grounding line, in better agreement with in-situ and satellite records. The melt increase persists by 2100 in all warming scenarios, revealing higher surface melt rates than previously estimated.

Toward a real validation of passive microwave snowmelt detection algorithms over the Antarctic Ice sheet

Antarctic Ice Sheet (AIS) surface snowmelt can profoundly impact climatological and hydrological processes, as well as energy and mass balances. Passive microwave remote sensing has proven highly effective in detecting snowmelt, and the accuracy of the algorithms is typically assessed using air temperature (Tair). Nonetheless, the occurrence of snowmelt cannot be solely determined by Tair being above the melting point, it can only provide evaluation of the algorithms rather than a real validation. This study is the first to conduct a reliable validation of six commonly used algorithms by using the melt rate data from a surface energy balance model, including the cross-polarized gradient ratio (XPGR) algorithm, the diurnal amplitude variation (DAV) algorithm, the Microwave Emission Model of Layered Snowpacks based (MEMLS-based) algorithm, the constant threshold algorithm (CTA), the Ashcraft and Long Algorithm (ALA), and the M + 30 K (M30 hereafter) algorithm. Results suggest that the M30 algorithm and MEMLS-based algorithm have overall better performances, with high overall accuracies (with a value of 95.81 % and 95.56 %) and high kappa coefficient (with a value of 0.69 and 0.68). Though Tair is not reliable for evaluating the algorithms, a threshold of Tair = − 0.8 ℃ can serve as an alternative criterion in the absence of melt rate data. Additionally, two algorithms with the highest accuracy were selected to investigate interannual snowmelt trends in the Antarctic and the sub-regions. The results show a significant increase in melt extent and density in the Wilkes and Adelie sub-region during the period 1979–2020.