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Cyanobacteria in polar environments face environmental challenges, including cold temperatures and extreme light seasonality with small diurnal variation, which has implications for polar circadian clocks. However, polar cyanobacteria remain underrepresented in available genomic data, and there are limited opportunities to study their genetic adaptations to these challenges. This paper presents four new Antarctic cyanobacteria metagenome-assembled genomes (MAGs) from microbial mats in Lake Vanda in the McMurdo Dry Valleys in Antarctica. The four MAGs were classified as Leptolyngbya sp. BulkMat.35, Pseudanabaenaceae cyanobacterium MP8IB2.15, Microcoleus sp. MP8IB2.171, and Leptolyngbyaceae cyanobacterium MP9P1.79. The MAGs contain 2.76 Mbp - 6.07 Mbp, and the bin completion ranges from 74.2-92.57%. Furthermore, the four cyanobacteria MAGs have average nucleotide identities (ANIs) under 90% with each other and under 77% with six existing polar cyanobacteria MAGs and genomes. This suggests that they are novel cyanobacteria and demonstrates that polar cyanobacteria genomes are underrepresented in reference databases and there is continued need for genome sequencing of polar cyanobacteria. Analyses of the four novel and six existing polar cyanobacteria MAGs and genomes demonstrate they have genes coding for various cold tolerance mechanisms and most standard circadian rhythm genes with the Leptolyngbya sp. BulkMat.35 and Leptolyngbyaceae cyanobacterium MP9P1.79 contained kaiB3, a divergent homolog of kaiB.

Rapid changes in the densely distributed lakes on the Tibetan Plateau (TP) reflect the responses of terrestrial water resources to climate change. Timely and accurate monitoring of lake dynamics is essential for formulating adaptation strategies to manage water and protect public facility safety sustainably. Interfered by the numerous glaciers and snow mountains and limited by the acquisition and computing capacities of massive satellite data, annual inventories of all the lakes ranging from mini to large on the TP are still lacking. Here, we annually mapped these lake areas using all the Landsat imagery, a robust algorithm for detecting surface water according to multiple spectral indices, and Google Earth Engine. We further proposed an effective approach for accurately identifying the glaciers, snow, and mountain shadows in satellite imagery by introducing the characteristics of image luminosity and terrain slope, and removing their data noise remained in the lake maps to generate an annual precise dataset (Lake_TP) of the approximately 9,000 lakes over 0.1 km2 on the TP during 1991–2023. We revealed a rapid expansion of lakes with significant spatial heterogeneity, with 6,590 newly increased and 2,851 disappeared lakes found. The total lake areas (554.1 km2/yr) and numbers (77.9/yr) continuously and significantly increased in the period. The growth in lake numbers dominated by small lakes mainly happened before 2005, while the increases in lake areas dominated by large lakes lasted the whole period after 1995. The most significant increases in lake areas and numbers happened in the north of the Inner Basin and Yangtze, the hotspot of lake changes identified in the study. The dataset is expected to promote our understanding of the complete lake evolution process and the dynamic response of the cryosphere to the changing climate. The method proposed is also applicable to continuously monitoring the dynamics of lakes with higher accuracies in other alpine regions around the world. The Lake_TP dataset is publicly available at https://doi.org/10.5281/zenodo.10686952 (Zhou et al. 2024). [ABSTRACT FROM AUTHOR]

The integration of data from multiple satellite altimetry missions, each offering unique observational characteristics, has enabled us to discern both short-term variability and long-term climate trends affecting Greenland's peripheral glaciers and the Greenland Ice Sheet (GrIS). Our methodology, adapted and informed by lessons learned from our similar efforts in Antarctica, ensures the consistency and reliability of the derived elevation change dataset. The data covers the years 1992–2023 and is made publicly available as part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project. Our analysis of the dataset reveals significant patterns of mass loss across the GrIS. We find that the ice sheet and peripheral glaciers have experienced an average mass loss of -173 ± 19 Gt a-1 and -23 ± 5 Gt a-1 respectively over the 1992–2022 time period (given temporal availability of selected firn models), with notable variations over time. Specifically, the early years of the record exhibit a positive mass balance, likely due to anomalously positive surface mass balance. However, this trend shifts in subsequent years, with a pronounced increase in mass loss rates, highlighting the accelerating impact of a changing climate on ice sheet dynamics and surface mass balance. Moreover, our analysis underscores the importance of considering peripheral glaciers in addition to the continental ice sheet when assessing overall mass trends. By incorporating data from peripheral glaciers, we provide a more comprehensive understanding of Greenland's total contributions to global sea level rise. Our findings reveal not only the magnitude of mass loss but also its evolution over time, emphasizing the need for continued monitoring and research to better understand the impacts of climate change on Earth's cryosphere. [ABSTRACT FROM AUTHOR]

Climate warming is constantly causing hydro-meteorological perturbations, especially in high-altitude mountainous regions, which lead to the occurrences of landslides. The impact of climatic variables (i.e., precipitation and temperature) on the distribution of landslides in the eastern regions of the Himalayas is poorly understood. To address this, the current study analyzes the relationship between the spatial distribution of landslide characteristics and climatic variables from 2013 to 2021. Google Earth Engine (GEE) was employed to make landslide inventories using satellite data. The results show that 2163, 6927, and 9601 landslides were heterogeneously distributed across the study area in 2013, 2017, and 2021, respectively. The maximum annual temperature was positively correlated with the distribution of landslides, whereas precipitation was found to have a non-significant impact on the landslide distribution. Spatially, most of the landslides occurred in areas with maximum annual precipitation ranging from 800 to 1600 mm and maximum annual temperature above 15°C. However, in certain regions, earthquake disruptions marginally affected the occurrence of landslides. Landslides were highly distributed in areas with elevations ranging between 3000 and 5000 m above sea level, and many landslides occurred near the lower permafrost limit and close to glaciers. The latter indicates that temperature change-induced freeze-thaw action influences landslides in the region. Temperature changes have shown a positive correlation with the number of landslides within elevations, indicating that temperature affects their spatial distribution. Various climate projections suggest that the region will experience further warming, which will increase the likelihood of landslides in the future. Thus, it is crucial to enhance ground observation capabilities and climate datasets to effectively monitor and mitigate landslide risks. [ABSTRACT FROM AUTHOR]

The root zone is a vital part of the Earth system and a key element in hydrology, ecology, agronomy, and land surface processes. However, its definition varies across disciplines, creating barriers to interdisciplinary understanding. Moreover, characterizing the root zone is challenging due to a lack of consensus on definitions, estimation methods, and their merits and limitations. This opinion paper provides a holistic definition of the root zone from a hydrology perspective, including its moisture storage, deficit, and storage capacity. We demonstrate that the root zone plays a critical role in the biosphere, pedosphere, rhizosphere, lithosphere, atmosphere, and cryosphere of the Earth system. We underscore the limitations of the traditional reductionist approach in modelling this complex and dynamic zone and advocate for a shift towards a holistic, ecosystem-centred approach. We argue that a holistic approach offers a more systematic, simple, dynamic, scalable, and observable way to describe and predict the role of the root zone in Earth system science. [ABSTRACT FROM AUTHOR]

Climate-sensitive northern cryosphere inland waters emit greenhouse gases (GHGs) into the atmosphere, yet their total emissions remain poorly constrained. We present a data-driven synthesis of GHG emissions from northern cryosphere inland waters considering water body types, cryosphere zones, and seasonality. We find that annual GHG emissions are dominated by carbon dioxide (1149.21307.5 1004.8 teragrams of CO2; medianQ3 Q1) and methane (14.218.5 10.1 teragrams of CH4), while the nitrous oxide emission (5.412.2 -1.4 gigagrams of N2O) is minor. The annual CO2-equivalent (CO2e) GHG emissions from northern cryosphere inland waters total 1.51.8 1.3 or 2.32.8 1.8 petagrams of CO2e using the 100-or 20-year global warming potentials, respectively. Rivers emit 64% more CO2e GHGs than lakes, despite having only one-fifth of their surface area. The continuous permafrost zone contributed half of the inland water GHG emissions. Annual CO2e emissions from northern cryosphere inland waters exceed the region's terrestrial net ecosystem exchange, highlighting the important role of inland waters in the cryospheric land-aquatic continuum under a warming climate. [ABSTRACT FROM AUTHOR]

Climate change is increasingly predisposing polar regions to large landslides. Tsunamigenic landslides have occurred recently in Greenland (Kalaallit Nunaat), but none have been reported from the eastern fjords. In September 2023, we detected the start of a 9-day-long, global 10.88-millihertz (92-second) monochromatic very-long-period (VLP) seismic signal, originating from East Greenland. In this study, we demonstrate how this event started with a glacial thinning-induced rock-ice avalanche of 25 × 106 cubic meters plunging into Dickson Fjord, triggering a 200-meter-high tsunami. Simulations show that the tsunami stabilized into a 7-meter-high long-duration seiche with a frequency (11.45 millihertz) and slow amplitude decay that were nearly identical to the seismic signal. An oscillating, fjord-transverse single force with a maximum amplitude of 5 × 1011 newtons reproduced the seismic amplitudes and their radiation pattern relative to the fjord, demonstrating how a seiche directly caused the 9-day-long seismic signal. Our findings highlight how climate change is causing cascading, hazardous feedbacks between the cryosphere, hydrosphere, and lithosphere. [ABSTRACT FROM AUTHOR]

A holistic review is given of the Southern Ocean dynamic system, in the context of the crucial role it plays in the global climate and the profound changes it is experiencing. The review focuses on connections between different components of the Southern Ocean dynamic system, drawing together contemporary perspectives from different research communities, with the objective of closing loops in our understanding of the complex network of feedbacks in the overall system. The review is targeted at researchers in Southern Ocean physical science with the ambition of broadening their knowledge beyond their specific field, and aims at facilitating better‐informed interdisciplinary collaborations. For the purposes of this review, the Southern Ocean dynamic system is divided into four main components: large‐scale circulation; cryosphere; turbulence; and gravity waves. Overviews are given of the key dynamical phenomena for each component, before describing the linkages between the components. The reviews are complemented by an overview of observed Southern Ocean trends and future climate projections. Priority research areas are identified to close remaining loops in our understanding of the Southern Ocean system. Plain Language Summary: The United Nations has identified 2021–2030 as the Decade of Ocean Science, with a goal to improve predictions of ocean and climate change. Improved understanding of the Southern Ocean is crucial to this effort, as it is the central hub of the global ocean. The Southern Ocean is the formation site for much of the dense water that fills the deep ocean, sequesters the majority of anthropogenic heat and carbon, and controls the flux of heat to Antarctica. The large‐scale circulation of the Southern Ocean is strongly influenced by interactions with sea ice and ice shelves, and is mediated by smaller scale processes, including eddies, waves, and mixing. The complex interplay between these dynamic processes remains poorly understood, limiting our ability to understand, model and predict changes to the Southern Ocean, global climate and sea level. This article provides a holistic review of Southern Ocean processes, connecting the smallest scales of ocean mixing to the global circulation and climate. It seeks to develop a common language and knowledge‐base across the Southern Ocean physical science community to facilitate knowledge‐sharing and collaboration, with the aim of closing loops on our understanding of one of the world's most dynamic regions. Key Points: Contemporary perspectives are reviewed on the different components of the Southern Ocean dynamic system from distinct research communitiesKey connections between different components of Southern Ocean dynamics are highlightedCross‐cutting priorities for future Southern Ocean physical science are identified [ABSTRACT FROM AUTHOR]

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year‐to‐year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in‐situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics‐based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in‐situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics‐based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in‐situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time‐series estimations of snow depth were observed. These results can be applied to any physics‐based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments. Plain Language Summary: Snowpacks in cold regions often occur in repeated, year‐to‐year patterns, regardless of the amount of snow that has fallen during the winter. This is due to complex landscape and climate interactions, like the shape and angles of the topography, the direction of the prevailing winter winds, and vegetation cover. Previous studies have used snow pattern maps with models to create more accurate estimations of the snowpack. This study uses machine learning (ML) to create the snow pattern maps, along with previously determined methods for integrating those patterns into estimations of snow depth and snow water content. We spent multiple winter fieldwork campaigns taking measurements of the snowpack, including point‐based snow depth and snow water content measurements, and plane‐based measurements of snow depth over large areas. These measurements were used to compare with our simulated snowpack characteristics. The hybrid approach, one that used ML plus physics‐based models, produced better spatial representations of the snowpack than results when ML was not used. Additionally, the hybrid approach generated improvements to modeled snow drift regions in the study area. These results show that ML and physics‐based models can be used together to create better spatial representations of snowpack characteristics in cold regions. Key Points: Machine learning, coupled with physics‐based process models, can predict snow patterns with lower error than the process model aloneWhen machine learning and physics‐based process models were used together, drifted snow areas were improved in the model outputsImprovements in root mean squared error were found at 61% of snow depth observation sites throughout the year [ABSTRACT FROM AUTHOR]

Runoff from rapidly melting mountain glaciers is a dominant source of riverine organic carbon in many high‐latitude and high‐elevation regions. Glacier dissolved organic carbon is highly bioavailable, and its composition likely reflects internal (e.g., autotrophic production) and external (i.e., atmospheric deposition) sources. However, the balance of these sources across Earth's glaciers is poorly understood, despite implications for the mineralization and assimilation of glacier organic carbon within recipient ecosystems. We assessed the molecular‐level composition of dissolved organic matter from 136 mountain glacier outflows from 11 regions covering six continents using ultrahigh resolution 21 T mass spectrometry. We found substantial diversity in organic matter composition with coherent and predictable (80% accuracy) regional patterns. Employing stable and radiocarbon isotopic analyses, we demonstrate that these patterns are inherently linked to atmospheric deposition and in situ production. In remote regions like Greenland and New Zealand, the glacier organic matter pool appears to be dominated by in situ production. However, downwind of industrial centers (e.g., Alaska and Nepal), fossil fuel combustion byproducts likely underpin organic matter composition, resulting in older and more aromatic material being exported downstream. These findings highlight that the glacier carbon cycle is spatially distinct, with ramifications for predicting the dynamics and fate of glacier organic carbon concurrent with continued retreat and anthropogenic perturbation. Plain Language Summary: The controls on glacier organic matter composition globally remain poorly constrained, despite the importance of this material for downstream carbon cycling, and freshwater and marine ecosystems. We present the first systematic global analysis of glacier dissolved organic matter and demonstrate that its composition is largely determined by the relative balance of organic material derived from in situ production versus atmospheric deposition. As a result, globally, glaciers can be considered a diverse organic matter pool, exporting regionally distinct material to recipient ecosystems. Glaciers relatively dominated by atmospheric‐derived organics export older and more stable material with ramifications for the fate of glacier‐derived carbon in recipient ecosystems. Ultimately, this work highlights glaciers globally as having a dynamic role in carbon cycling. Key Points: Glacier dissolved organic matter is diverse but with an underlying compositional uniformity suggesting universal controls on compositionComposition appears driven by the relative balance of in situ production versus atmospheric deposition derived organic matterGlacier dissolved organic matter composition is predictable by region and linked to source [ABSTRACT FROM AUTHOR]

The author discursively thinks through three questions. “What is “man” as a physical system?” “What are the unchanging properties of this physical system, or what is equal to “man”?” “What are the changing properties of this physical system, or what is happiness?” The following results were obtained. (1) “Man” as a physical system is a derivative (emergent) property or relation, which is described by the formula “Psukhe exists/is (eimí) in the “habitual” molecular manner (díken).” (2) The unchanging properties or otherwise légo form the only rightful (themitós) for the molecular physical system that the formula “Zo? breathes/makes cool (psýcho) and in this way/manner (trópos) exists/is (eimí) in the expanding universe” describes. It has been proven that the cryosphere, biosphere, and noosphere are a few equal emergent molecular state-spaces that “move (work) together as one” to advance and protect the hegemonía of the molecular physical system in an expanding universe. (3) The changing properties or otherwise noiéo is the property or attitude to advance “moderate things,” i.e., molecular fields and particles in astronomical, tectonic, and geochemical events, and to protect oneself from “immoderate things,” i.e., anything that destroys molecular identity and individuality. The changing properties produce and guarantee the physical state we call “happiness, well-being, outward prosperity,” i.e. the right and duty to “pull together” equals, but always and only on the basis of what is right/just (díkaios/iustus).

Cold environments are the most widespread extreme habitats in the world. However, the role of wastewater treatment plants (WWTPs) in the cryosphere as hotspots in antibiotic resistance dissemination has not been well established. Hence, a snapshot of the resistomes of WWTPs in cold environments, below 5 °C, was provided to elucidate their role in disseminating antibiotic resistance genes (ARGs) to the receiving waterbodies. The resistomes of two natural environments from the cold biosphere were also determined. Quantitative PCR analysis of the aadA, aadB, ampC, blaSHV, blaTEM, dfrA1, ermB, fosA, mecA, qnrS, and tetA(A) genes indicated strong prevalences of these genetic determinants in the selected environments, except for the mecA gene, which was not found in any of the samples. Notably, high abundances of the aadA, ermB, and tetA(A) genes were found in the influents and activated sludge, highlighting that WWTPs of the cryosphere are critical hotspots for disseminating ARGs, potentially worsening the resistance of bacteria to some of the most commonly prescribed antibiotics. Besides, the samples from non-disturbed cold environments had large quantities of ARGs, although their ARG profiles were highly dissimilar. Hence, the high prevalences of ARGs lend support to the fact that antibiotic resistance is a common issue worldwide, including environmentally fragile cold ecosystems. [ABSTRACT FROM AUTHOR]

Ice caves are characterised by specific microclimate, defined by the external climate as well as cave morphology (hence the location). They are unique components of Earth’s heritage. The ice formed there holds important paleoclimatic information and can be used to assess the global warming effect on the cryosphere in non-glaciated areas. We present an example from Wielka Śnieżna, the deepest cave system in the Polish Tatra Mountains, located in Tatra National Park (Tatrzański Park Narodowy). There have been no recent studies completed on the topic in this location. We provide the first contemporary results of temperature measurements by analysing microclimatic patterns and their response to global warming. There is ongoing ablation of the Ice Fall located in one of the lower entrances (Śnieżna) showing that the ice level has decreased by around 2 m in the last 10 years. The cave is under a minor human impact as it can be accessed only by professional cavers. However, some practices impact the balance of this fragile environment. By comparing our results with the outside temperature records, we aim to understand how dependent the cave microclimate is on the external fluctuations and changes. The ice in the Śnieżna is expected to be gone in the current century.Highlights: Perennial ice surface inside the Wielka Śnieżna Cave decreases due to global warming, with an average rate of 20 cm per year in the last decade. Local microclimate is controlled by cave morphology and dependent on seasonal changes of airflow and clogging the cave entrance by snow. Collected thermal data did not indicate that the caving activity have a negative impact on cave ice with limited entries in accordance with the restrictions of the Tatra National Park. [ABSTRACT FROM AUTHOR]

Abstract Background Lake Bonney, which is divided into a west lobe (WLB) and an east lobe (ELB), is a perennially ice-covered lake located in the McMurdo Dry Valleys of Antarctica. Despite previous reports on the microbial community dynamics of ice-covered lakes in this region, there is a paucity of information on the relationship between microbial genomic diversity and associated nutrient cycling. Here, we applied gene- and genome-centric approaches to investigate the microbial ecology and reconstruct microbial metabolic potential along the depth gradient in Lake Bonney. Results Lake Bonney is strongly chemically stratified with three distinct redox zones, yielding different microbial niches. Our genome enabled approach revealed that in the sunlit and relatively freshwater epilimnion, oxygenic photosynthetic production by the cyanobacterium Pseudanabaena and a diversity of protists and microalgae may provide new organic carbon to the environment. CO-oxidizing bacteria, such as Acidimicrobiales, Nanopelagicales, and Burkholderiaceae were also prominent in the epilimnion and their ability to oxidize carbon monoxide to carbon dioxide may serve as a supplementary energy conservation strategy. In the more saline metalimnion of ELB, an accumulation of inorganic nitrogen and phosphorus supports photosynthesis despite relatively low light levels. Conversely, in WLB the release of organic rich subglacial discharge from Taylor Glacier into WLB would be implicated in the possible high abundance of heterotrophs supported by increased potential for glycolysis, beta-oxidation, and glycoside hydrolase and may contribute to the growth of iron reducers in the dark and extremely saline hypolimnion of WLB. The suboxic and subzero temperature zones beneath the metalimnia in both lobes supported microorganisms capable of utilizing reduced nitrogens and sulfurs as electron donors. Heterotrophs, including nitrate reducing sulfur oxidizing bacteria, such as Acidimicrobiales (MAG72) and Salinisphaeraceae (MAG109), and denitrifying bacteria, such as Gracilimonas (MAG7), Acidimicrobiales (MAG72) and Salinisphaeraceae (MAG109), dominated the hypolimnion of WLB, whereas the environmental harshness of the hypolimnion of ELB was supported by the relatively low in metabolic potential, as well as the abundance of halophile Halomonas and endospore-forming Virgibacillus. Conclusions The vertical distribution of microbially driven C, N and S cycling genes/pathways in Lake Bonney reveals the importance of geochemical gradients to microbial diversity and biogeochemical cycles with the vertical water column.

Background: Lake Bonney, which is divided into a west lobe (WLB) and an east lobe (ELB), is a perennially ice-covered lake located in the McMurdo Dry Valleys of Antarctica. Despite previous reports on the microbial community dynamics of ice-covered lakes in this region, there is a paucity of information on the relationship between microbial genomic diversity and associated nutrient cycling. Here, we applied gene- and genome-centric approaches to investigate the microbial ecology and reconstruct microbial metabolic potential along the depth gradient in Lake Bonney. Results: Lake Bonney is strongly chemically stratified with three distinct redox zones, yielding different microbial niches. Our genome enabled approach revealed that in the sunlit and relatively freshwater epilimnion, oxygenic photosynthetic production by the cyanobacterium Pseudanabaena and a diversity of protists and microalgae may provide new organic carbon to the environment. CO-oxidizing bacteria, such as Acidimicrobiales, Nanopelagicales, and Burkholderiaceae were also prominent in the epilimnion and their ability to oxidize carbon monoxide to carbon dioxide may serve as a supplementary energy conservation strategy. In the more saline metalimnion of ELB, an accumulation of inorganic nitrogen and phosphorus supports photosynthesis despite relatively low light levels. Conversely, in WLB the release of organic rich subglacial discharge from Taylor Glacier into WLB would be implicated in the possible high abundance of heterotrophs supported by increased potential for glycolysis, beta-oxidation, and glycoside hydrolase and may contribute to the growth of iron reducers in the dark and extremely saline hypolimnion of WLB. The suboxic and subzero temperature zones beneath the metalimnia in both lobes supported microorganisms capable of utilizing reduced nitrogens and sulfurs as electron donors. Heterotrophs, including nitrate reducing sulfur oxidizing bacteria, such as Acidimicrobiales (MAG72) and Salinisphaeraceae (MAG109), and denitrifying bacteria, such as Gracilimonas (MAG7), Acidimicrobiales (MAG72) and Salinisphaeraceae (MAG109), dominated the hypolimnion of WLB, whereas the environmental harshness of the hypolimnion of ELB was supported by the relatively low in metabolic potential, as well as the abundance of halophile Halomonas and endospore-forming Virgibacillus. Conclusions: The vertical distribution of microbially driven C, N and S cycling genes/pathways in Lake Bonney reveals the importance of geochemical gradients to microbial diversity and biogeochemical cycles with the vertical water column. [ABSTRACT FROM AUTHOR]

Investigating the changes in snow cover caused by climate change is extremely important and has attracted increasing attention in cryosphere and climate research. Optimal remote sensing-based snow datasets can provide long-term daily and global spatial-temporal snow-cover distribution at regional and global scales. However, the application of these snow-cover products is inevitably limited because of the space–time discontinuities caused by cloud obscuration, which poses a significant challenge in snowpack-related studies, especially in High Mountain Asia (HMA), an area that has high-elevation mountains, complex terrain, and harsh environments and has fewer observation stations. To address this issue, we developed an improved five-step hybrid cloud removal strategy by integrating the daily merged snow-cover probability (SCP) algorithm, eight-day merged SCP algorithm, decision tree algorithm, temporal downscaling algorithm, and optimal threshold segmentation algorithm to produce a 21-year, daily cloud-free snow-cover dataset using two daily MODIS snow-cover products over the HMA. The accuracy assessment demonstrated that the newly developed cloud-free snow-cover product achieved a mean overall accuracy of 93.80%, based on daily classified snow depth observations from 86 meteorological stations over 10 years. The time series of the daily percentage of binary snow-cover over HMA was analyzed during this period, indicating that the maximum snow cover tended to change more dramatically than the minimum snow cover. The annual snow-cover duration (SCD) experienced an insignificantly increasing trend over most of the northeastern and southwestern HMA (e.g., Qilian, eastern Kun Lun, the east of Inner Tibet, the western Himalayas, the central Himalayas, and the Hindu Kush) and an insignificant declining trend over most of the northwestern and southeastern HMA (e.g., the eastern Himalayas, Hengduan, the west of Inner Tibet, Pamir, Hissar Alay, and Tien). This new high-quality snow-cover dataset will promote studies on climate systems, hydrological modeling, and water resource management in this remote and cold region. [ABSTRACT FROM AUTHOR]

Cryospheric hazards - in this case, thaw slumps (TS) and thermo-erosion gullies (TEG) - are phenomena typical of permafrost-dominated landscapes. Open datasets informing about their spatial, temporal and size distributions in the Arctic are still uncommon, as opposed to the systematic availability of this information for geomorphic processes in mid- to low- latitudes. To date, only the most populated region of Svalbard was covered with TS and TEG inventories. Here, we extend the respective information to most of the Archipelago, totalling 8491 polygons, out of which 3679 are TSs and 4812 are TEGs. These have been manually mapped from aerial photographs throughout Svalbard across the 14 largest ice-free regions. The SvalCryo inventory is highly relevant as the Arctic environment undergoes alarming changes in response to global warming. The idea behind the two inventories is to support the geoscientific community in the quest to evaluate the environmental response to climate change, by creating a baseline for change monitoring, and ultimately to serve as basis for susceptibility, hazard and risk assessment models. [ABSTRACT FROM AUTHOR]

Climate warming exacerbates the degradation of the mountain cryosphere, including glacier retreat, permafrost degradation, and snow cover reduction. These changes dramatically alter the local and downstream hydrological regime, posing significant threats to basin-scale water resource management and sustainable development. However, this issue is still not adequately addressed, particularly in mountainous catchments. We developed an integrated cryospheric–hydrologic model, the FLEX-Cryo model, to comprehensively consider glaciers, snow cover, and frozen soil and their dynamic impacts on hydrological processes. Taking the mountainous Hulu catchment located in the upper Heihe River of China as a case study, we utilized the state-of-the-art climate change projection data under two scenarios (SSP2-4.5 and SSP5-8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate the future changes in the mountainous cryosphere and their impacts on hydrology. Our findings showed that under the medium-emission scenario (SSP2-4.5) and high-emission scenario (SSP5-8.5), by the end of the 21st century, the glacier will completely melt out around the years 2051 and 2045, respectively. The annual maximum snow water equivalent is projected to decrease by 41.4 % and 46.0 %, while the duration of snow cover will be reduced by approximately 45 and 70 d. The freeze onset of seasonally frozen soil is expected to be delayed by 10 and 22 d, while the thaw onset of permafrost is likely to advance by 19 and 32 d. Moreover, the maximum freeze depth of seasonally frozen soil is projected to decrease by 5.2 and 10.9 cm per decade, and the depth of the active layer will increase by 8.2 and 15.5 cm per decade. Regarding hydrology, catchment total runoff exhibits a decreasing trend, and the tipping point of glacier runoff occurs approximately between 2019 and 2021. Permafrost degradation will likely reduce the duration of low runoff in the early thawing season; the discontinuous baseflow recession gradually transitions into linear recessions, and the baseflow increases. Our results highlight the significant changes expected in the mountainous cryosphere and hydrology in the future. These findings enhance our understanding of cold-region hydrological processes and have the potential to assist local and downstream water resource management in addressing the challenges posed by climate change. [ABSTRACT FROM AUTHOR]

It is increasingly recognized that light-absorbing impurities (LAI) deposited on snow and ice affect their albedo and facilitate melting processes leading to various feedback loops, such as the ice albedo feedback mechanism. Black carbon (BC) is often considered the most important LAI, but some areas can be more impacted by high dust emissions. Iceland is one of the most important high latitude sources for the Arctic due to high emissions and the volcanic nature of the dust. We studied optical properties of volcanic dust from Iceland and Chile to understand how it interacts with the Sun's radiation and affects areas of deposition as LAI. Optical properties of dust samples were measured at the laboratory of the Finnish Geospatial Research Institute (FGI) using the latest setup of the FGI's goniospectrometer. We found that, depending on the particle size, the albedo of dry volcanic dust on the visible spectrum is as low as 0.03, similar to that of BC, and the albedo decreases with increasing particle size. Wet dust reduces its albedo by 66% compared to dry sample. This supports the comparability of their albedo reducing effects to BC as LAIs, and highlights their significant role in albedo reduction of snow and ice areas. The potential use of the results from our measurements is diverse, including their use as a ground truth reference for Earth Observation and remote sensing studies, estimating climate change over time, as well as measuring other ecological effects caused by changes in atmospheric composition or land cover. [ABSTRACT FROM AUTHOR]

This study presents a detailed theoretical assessment of the information content of passive polarimetric observations over snow scenes, using a global sensitivity analysis (GSA) method. Conventional sensitivity studies focus on varying a single parameter while keeping all other parameters fixed. In contrast, the GSA correctly addresses the covariance of state parameters across their entire parameter space, hence favoring a more correct interpretation of inversion algorithms and the optimal design of their state vectors. The forward simulations exploit a vector radiative transfer model to obtain the Stokes vector emerging at the top of the atmosphere for different solar zenith angles, when the bottom boundary consists of a vertically resolved snowpack of non-spherical grains. The presence of light-absorbing particulates (LAPs), either embedded in the snow or aloft in the atmosphere above in the form of aerosols, is also considered. The results are presented for a set of wavelengths spanning the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) region of the spectrum. The GSA correctly captures the expected, high sensitivity of the reflectance to LAPs in the VIS–NIR and to grain size at different depths in the snowpack in the NIR–SWIR. With adequate viewing geometries, mono-angle measurements of total reflectance in the VIS–SWIR (akin to those of the Moderate Resolution Imaging Spectroradiometer, MODIS) resolve grain size in the top layer of the snowpack sufficiently well. The addition of multi-angle polarimetric observations in the VIS–NIR provides information on grain shape and microscale roughness. The simultaneous sensitivity in the VIS–NIR to both aerosols and snow-embedded impurities can be disentangled by extending the spectral range to the SWIR, which contains information on aerosol optical depth while remaining essentially unaffected when the same particulates are mixed with the snow. Multi-angle polarimetric observations can therefore (i) effectively partition LAPs between the atmosphere and the surface, which represents a notorious challenge for snow remote sensing based on measurements of total reflectance only and (ii) lead to better estimates of grain shape and roughness and, in turn, the asymmetry parameter, which is critical for the determination of albedo. The retrieval uncertainties are minimized when the degree of linear polarization is used in place of the polarized reflectance. The Sobol indices, which are the main metric for the GSA, were used to select the state parameters in retrievals performed on data simulated for multiple instrument configurations. Improvements in retrieval quality with the addition of measurements of polarization, multi-angle views, and different spectral channels reflect the information content, identified by the Sobol indices, relative to each configuration. The results encourage the development of new remote sensing algorithms that fully leverage multi-angle and polarimetric capabilities of modern remote sensors. They can also aid flight planning activities, since the optimal exploitation of the information content of multi-angle measurements depends on the viewing geometry. The better characterization of surface and atmospheric parameters in snow-covered regions advances research opportunities for scientists of the cryosphere and ultimately benefits albedo estimates in climate models. [ABSTRACT FROM AUTHOR]

Understanding the drivers of iceberg calving from Antarctic ice shelves is important for future sea level rise projections. Ocean waves promote calving by imposing stresses and strains on the shelves. Previous modeling studies of ice shelf responses to ocean waves have focused on highly idealized geometries with uniform ice thickness and a flat seabed. This study leverages on a recently developed mathematical model that incorporates spatially varying geometries, combined with measured ice shelf thickness and seabed profiles, to conduct a statistical assessment of how 15 Antarctic ice shelves respond to ocean waves over a broad range of relevant wave periods, from swell to infragravity waves to very long period waves. The results show the most extreme responses at a given wave period are generated by features in the ice shelves and/or seabed geometries, depending on the wave regime. Relationships are determined between the median ice shelf response and the median shelf front thickness or the median water cavity depth. The findings provide further evidence of the role of ocean waves in large‐scale calving events for certain ice shelves (particularly the Wilkins) and indicate a possible role of ocean waves in calving events for other shelves (Larsen C and Conger). Further, the relationships determined provide a method to assess the potential for increased calving as ice shelves evolve with climate change, and, hence, contribute to assessments of future sea level rise. Plain Language Summary: Antarctic ice shelves are the floating extensions of the Antarctic Ice Sheet. They play a critical role in many Southern Ocean processes. In particular, they help maintain the stability of the Antarctic Ice Sheet by moderating the flow of grounded ice into the Southern Ocean. Climate change is causing them to thin and retreat, which is a major threat to global sea levels. Iceberg calving accounts for half of ice shelf loss, and ocean waves contribute to the calving process by rhythmically bending ice shelves. The influence of ocean waves on calving is expected to increase as the shelves and their surrounding sea ice barriers become weaker. Therefore, quantifying the responses of ice shelves to ocean waves is needed to project the future of the shelves and, hence, sea level rise. In this study, we use a recently developed mathematical model to analyze the responses of 15 Antarctic ice shelves to ocean waves, ranging from storm waves to tsunamis. We show how features in the geometry can create large responses that could drive calving events, and we derive simple relationships between the responses and the geometry to aid projections of future scenarios. Key Points: Crevasses and seabed protrusions create large ice shelf flexure in response to ocean wavesIce shelves that have experienced large scale calving events had much greater responses to swell than typical shelvesMedian ice shelf responses to swell are strongly correlated to median shelf front thicknesses [ABSTRACT FROM AUTHOR]

The state and fate of snow on sea ice are crucial in the mass and energy balance of sea ice. The function of atmospheric rivers (ARs) on snow depth over sea ice has not been measured thus far, limiting the understanding of the mechanism of snow depth changes. Here, the effect of ARs on snow depth changes was explored. We found that increased AR frequency is responsible for winter‐autumn snow accumulation and spring‐summer snow melting. The 2 m air temperature (T2m), rainfall, snowfall, mean net longwave radiation (NLR), mean net shortwave radiation (NSR) and cloud radiative effect (CRE) during ARs explain the changes in snow depth triggered by AR occurrence. This work helps us understand how ARs affect snow depth changes through related physical processes, promotes an understanding of climate systems and provides a theoretical basis for snow treatment in sea ice models. Plain Language Summary: Snowpack, one of the most essential parts of the cryosphere, affects the energy exchange between sea ice and the atmosphere, thus contributing to sea ice change and the global climate system. Atmospheric rivers (ARs) are long and narrow transient corridors of water vapor. Because ARs transmit more than 90% of water vapor to high latitudes, increasing scientific and societal interest has focused on the impact of ARs on sea ice. However, little attention has been given to the relationship between ARs and snow depth. Therefore, reliable ARs and snow depths from 2002 to 2022 were obtained. We found that increased ARs drive autumn‐winter snow depth increases and spring‐summer snow depth decreases based on ARs and snow depth records. ARs cause changes in snow depth by altering physical processes related to ARs (e.g., 2 m air temperature (T2m), rainfall, snowfall, mean net longwave radiation (NLR), mean net shortwave radiation (NSR) and the cloud radiative effect (CRE)). Key Points: A novel snow depth record over Arctic sea ice was generated using the triple collocation methodMore frequent atmospheric rivers (ARs) lead to autumn‐winter snow depth increases and spring‐summer snow depth reductionsThe 2 m air temperature, rainfall, snowfall, and cloud radiative effect (CRE) are important in the AR‐induced changes in snow depth [ABSTRACT FROM AUTHOR]

The VIIRS instrument on the JPSS-2 (renamed NOAA-21 upon reaching orbit) spacecraft was launched in November 2022, making it the third sensor in the VIIRS series, following those onboard the SNPP and NOAA-20 spacecrafts, which are operating nominally. As a multi-disciplinary instrument, the VIIRS provides the worldwide user community with high-quality imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. This study provides an early assessment of the calibration stability and radiometric consistency of the NOAA-21 VIIRS RSBs using the latest NASA SIPS C2 L1B products. Vicarious approaches are employed, relying on reflectance data obtained from the Libya-4 desert and Dome C sites, deep convective clouds, and simultaneous nadir overpasses, as well as intercomparison with the first two VIIRS instruments using MODIS as a transfer radiometer. The impact of existing band spectral differences on sensor-to-sensor comparison is corrected using scene-specific a priori hyperspectral observations from the SCIAMACHY sensor onboard the ENVISAT platform. The results indicate that the overall radiometric performance of the newly launched NOAA-21 VIIRS is quantitatively comparable to the NOAA-20 for the VIS and NIR bands. For some SWIR bands, the measured reflectances are lower by more than 2%. An upward adjustment of 6.1% in the gain of band M11 (2.25 µm), based on lunar intercomparison results, generates more consistent results with the NOAA-20 VIIRS. [ABSTRACT FROM AUTHOR]

Lake ice thickness (LIT) is a sensitive indicator of climate change, identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic-aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow–ice and ice–water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LIT and FFSAR_LIT retracker, respectively. We found that LIT retrievals from Sentinel-6 high-resolution SAR data at different posting rates are fully consistent with the LIT estimations obtained from thermodynamic lake ice model simulations and from low-resolution mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, demonstrating the continuity between LRM and SAR LIT retrievals. By comparing the Sentinel-6 SAR LIT estimates to optical/radar images, we found that the Sentinel-6 LIT measurements are fully consistent with the evolution of the lake surface conditions, accurately capturing the seasonal transitions of ice formation and melt. The uncertainty in the LIT estimates obtained with Sentinel-6 UFSAR data at 20 Hz is in the order of 5 cm, meeting the GCOS requirements for LIT measurements. This uncertainty is significantly smaller, by a factor of 2 to 3 times, than the uncertainty obtained with LRM data. The FFSAR processing at 140 Hz provides even better LIT estimates, with 20% smaller uncertainties. The LIT retracker analysis performed on data at the higher posting rate (140 Hz) shows increased performance in comparison to the 20 Hz data, especially during the melt transition period, due to the increased statistics. The LIT analysis has been performed over two representative lakes, Great Slave Lake and Baker Lake (Canada), demonstrating that the results are robust and hold for lake targets that differ in terms of size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions. [ABSTRACT FROM AUTHOR]

Quantitative understanding of the land water loading is a prerequisite to the construction of reliable tectonic deformation velocity field in the Tibetan Plateau (TP). Here, for the first time, we image the three‐dimensional crustal loading deformation velocity field of each land water component in the TP. Our results reveal that the loading signal strength of the six land water components ranks from largest to smallest as groundwater, glacier, lake, soil water, permafrost, and snow, with the maximum vertical velocity close to ±1.60 mm/yr and the maximum horizontal velocity exceeding 0.40 mm/yr. All land water components can achieve a strong enough vertical loading velocity exceeding the present‐day Global Positioning System (GPS) velocity at some sites. But for horizontal loading, apparent impacts are only from glacier, lake and groundwater, however, are very limited, with the absolute ratio of loading velocity to GPS velocity being smaller than 5% at almost all the sites. Plain Language Summary: The crustal kinematic characteristics and uplift mechanism of the Tibetan Plateau (TP) have been widely studied based on the three‐dimensional deformation velocity field from Global Positioning System (GPS) measurements. However, except for tectonic signal, the land water loading effect is also involved in GPS observation and may lead to the biased tectonic interpretation of GPS deformation velocity field. In this study, we construct a set of three‐dimensional crustal loading deformation velocity fields for the TP based on the state‐of‐the‐art multi‐component land water mass change fields constrained by multi‐source data spanning ∼20 years. Results reveal that the loading signal strength of the six land water components ranks from largest to smallest as groundwater, glacier, lake, soil water, permafrost, and snow. We find that all land water components can achieve a strong enough vertical loading velocity exceeding the present‐day GPS vertical velocity at some sites, but show very limited horizontal loading. Our results could provide loading correction reference for the construction of high‐accuracy TP tectonic deformation velocity field. Key Points: We image the three‐dimensional crustal deformation velocity fields of the Tibetan Plateau due to multi‐component land water loadingEvident loading is from groundwater, glacier, and lake, with the maximum vertical and horizontal velocities exceeding ±1.0 mm/yr and 0.2 mm/yr, respectivelyAll land water components can achieve a vertical loading velocity exceeding the Global Positioning System velocity at some sites, but show very limited horizontal loading [ABSTRACT FROM AUTHOR]

Against the backdrop of climate change and the "dual carbon" goals, enhancing the ecological efficiency of cryospheric tourism is crucial not only for the high-quality development of the tourism industry itself but also for the protection of the ecological environment and the promotion of green sustainable development in the cryospheric region. In light of this, this study, taking climate change as its background and based on the perspective of carbon emission constraints, integrates multidimensional factors such as "climate change, carbon emission constraints, and cryospheric resources" into a unified measurement framework to construct a model for evaluating the ecological efficiency of tourism in the cryosphere. Specifically, the model considers inputs, expected outputs, and unexpected outputs. Subsequently, employing the super-efficiency slack-based measure (SBM) model, this study measures the tourism ecological efficiency (TEE) of three provinces (Xinjiang, Qinghai, Tibet) in the cryosphere from 2013 to 2021 and utilizes the Malmquist–Luenberger index and gray correlation model to reveal their dynamic changes, efficiency decomposition, and influencing factors. The results indicate that: (1) The overall mean of TEE in the cryosphere is between 0.2428 and 1.2142, Over the study period, the average annual growth rate and corresponding confidence interval were 14.74%, (−8.61%, 64.23%), showing a significant fluctuating growth trend. Among them, Xinjiang stands out, with its mean scores ranging from 0.2418 to 1.6229, surpassing the overall average level of the cryosphere. (2) During the study period, the overall dynamic efficiency of tourism ecology in the cryosphere increased by 21.54%, driven by the synergy of technological progress (TC), pure technical efficiency (PET), and scale efficiency (SE). For each province, the dynamic efficiency of tourism ecology has improved, but to varying degrees. (3) Regarding the driving factors of TEE in the cryosphere, each driving factor is closely related to TEE, ranked from large to small as follows: carbon emission structure, level of economic development, infrastructure, intensity of technological input, industrial structure, resource endowment, and environmental regulation. This article holds theoretical and practical significance for promoting the high-quality development of polar tourism and achieving synergistic progress between the economy and environment. [ABSTRACT FROM AUTHOR]

Runoff and evapotranspiration (ET) are pivotal constituents of the water, energy, and carbon cycles. This research presents a 5-km monthly gridded runoff and ET dataset for 1998–2017, encompassing seven headwaters of Tibetan Plateau rivers (Yellow, Yangtze, Mekong, Salween, Brahmaputra, Ganges, and Indus) (hereinafter TPRED). The dataset was generated using the advanced cryosphere-hydrology model WEB-DHM, yielding a Nash coefficient ranging from 0.77 to 0.93 when compared to the observed discharges. The findings indicate that TPRED's monthly runoff notably outperforms existing datasets in capturing hydrological patterns, as evidenced by robust metrics such as the correlation coefficient (CC) (0.944–0.995), Bias (−0.68-0.53), and Root Mean Square Error (5.50–15.59 mm). Additionally, TPRED's monthly ET estimates closely align with expected seasonal fluctuations, as reflected by a CC ranging from 0.94 to 0.98 when contrasted with alternative ET products. Furthermore, TPRED's annual values exhibit commendable concordance with operational products across multiple dimensions. Ultimately, the TPRED will have great application on hydrometeorology, carbon transport, water management, hydrological modeling, and sustainable development of water resources. [ABSTRACT FROM AUTHOR]

Constraining the role of microbes in the structural iron (Fe) reduction of iron-bearing minerals improves our understanding of sediments and ice sheets as a source of dissolved Fe (dFe) to the oceans. However, bio-mediated structural Fe-reduction has yet to be studied in cryospheric environments. Here, we show that the Fe reducing psychrophile bacterium Shewanella vesiculosa, isolated from sea ice in Antarctica, reduced structural Fe in nontronite (NAu-2) and maghemite (γ-Fe 2 O 3), common mineral phases in glacial ice, and marine sediments in Antarctica, during two freeze–thaw cycles (−10 °C to +15 °C), resulting in the release of dFe. The modification of turbostratically disordered nontronite (ferric iron dominant phase) to discrete ordered illite-like structure (ferrous iron dominant phase), and the aggregation of altered small maghemite particles with neoformation of vivianite (Fe 3 (PO 4) 2 ·nH 2 O) indicated the microbially induced reductive dissolution of nontronite and maghemite, respectively. The biotic Fe-reduction gradually decreased and ceased as the temperature approached freezing (−8 °C), however the rection reactivated in the thawing cycle (−7 to +15 °C). No discernable biotic Fe-reduction was measured for either mineral under freezing conditions, suggesting that temperature limits the activity of the microbes. Further, and regardless of temperatures during two freeze–thaw cycles, Fe-reduction was not observed in abiotic control. Overall, these results highlight the importance of microbially induced Fe reduction during seasonal freeze–thaw cycles of ice and sediments in continuous supplying bioavailable dFe to cryospheric environments and the often Fe-limited polar oceans. [ABSTRACT FROM AUTHOR]

Because Antarctic surface melt is mostly driven by local processes, its simulation necessitates high‐resolution regional climate models (RCMs). However, the current horizontal resolution of RCMs (≈25–30 km) is inadequate for capturing small‐scale melt processes. To address this limitation, we present SUPREME (SUPer‐REsolution‐based Melt Estimation over Antarctica), a deep learning method to downscale surface melt to 5.5 km resolution using a physically‐informed super‐resolution model. The physical information integrated into the model originates from observations tied to surface melt, specifically remote sensing‐derived albedo and elevation. These remote sensing data, in addition to a Regional Atmospheric Climate Model (RACMO) run at 27 km resolution, account for the diverse drivers of surface melt across Antarctica, facilitating effective generalization beyond the training region of the Antarctic Peninsula. A comparison of SUPREME with a dynamically downscaled RACMO run at 5.5 km over the Antarctic Peninsula shows high accuracy, with average yearly RMSE and bias of 5.5 mm w.e. yr−1 and 4.5 mm w.e. yr−1, respectively. Validation at five automatic weather stations reveals SUPREME's marked improvement with substantially lower average RMSE (81 mm w.e.) compared to RACMO 27 km (129 mm w.e.). Beyond the training region, SUPREME aligns more closely with remote sensing products associated with surface melt than super‐resolution models lacking physical constraints. While further validation of SUPREME is needed, our study highlights the potential of super‐resolution techniques with physical constraints for high‐resolution surface melt monitoring in Antarctica, providing insights into the impacts of localized melting on processes affecting ice shelf integrity such as hydrofracturing. Plain Language Summary: To improve surface melt monitoring in Antarctica, high‐resolution climate models are essential. Existing models, like the Regional Atmospheric Climate Model (RACMO), do not have a fine enough spatial resolution to capture small‐scale melt processes. To overcome this, we introduce SUPREME (SUPer‐REsolution‐based Melt Estimation over Antarctica), a method that refines surface melt data to a higher resolution of 5.5 km using an advanced super‐resolution model. We enhance this model with physical information derived from observations directly related to surface melt, specifically using albedo and elevation data from remote sensing. By incorporating these observations, along with RACMO data at 27 km resolution, we account for the various triggers of surface melt across Antarctica. SUPREME accurately predicts high‐resolution surface melt beyond the training region of the Antarctic Peninsula, showing promising results compared to existing melt observations. Further validation is needed, but this approach, combining super‐resolution techniques and remote sensing data, holds potential for accurate surface melt monitoring in Antarctica. This may advance our understanding of the impacts of localized features on processes affecting ice shelf integrity such as meltwater‐induced hydrofracturing. Key Points: Our method downscales Antarctic surface melt from a regional climate model, employing a physically‐informed super‐resolution architectureThe super‐resolution model relies on physical information derived from remote sensing data, specifically surface albedo and elevationIncorporating physical information boosts model generalization, enabling accurate high‐resolution surface melt beyond the training region [ABSTRACT FROM AUTHOR]

Changes in the thermal conditions of the ocean surface, the interface for air‐sea exchange, are critical for understanding global climate and environmental change. Here we explore the evolution of sea surface temperature (SST) and the meridional SST gradient (STG) at orbital timescales since 4 million years ago (Ma), along with interactions between SSTs, the cryosphere, and the global carbon cycle. We observe orbital eccentricity and obliquity influences on SST evolution and infer that SST changes may have played a key role in atmospheric CO2 and cryosphere changes through key climate transitions in the past 4 Ma. We find a major equator‐to‐pole STG increase in the Northern Hemisphere (NH) close to the initiation of major NH glaciation (at ∼2.7 Ma). In addition, we find substantial increases in the obliquity sensitivity (Sobl) of NH STG at ∼2.7 Ma and in Southern Hemisphere (SH) STG at ∼1 Ma, which may be responses to important expansions of NH and SH ice sheets, respectively. Phase analysis shows that SST changes typically lead global ice volume changes throughout the last 4 Ma. SST changes also lead atmospheric CO2 changes since ∼1.5 Ma, which indicates that SST changes either drove, or directly reflect, processes that changed ocean‐atmosphere carbon exchange and, thus, atmospheric CO2 concentrations. Overall, our study emphasizes that SST changes were a critical component of climate change throughout the last 4 Ma. Plain Language Summary: A compilation of global sea surface temperature (SST) records indicates that SST mainly fluctuated on orbital eccentricity and obliquity timescales during the last 4 million years. The compilation also reveals an important impact of meridional ocean circulation changes on global climate since 4 Ma, with a particularly notable change in the equator‐to‐pole SST gradient during the initiation of major Northern Hemisphere glaciations at ∼2.7 Ma. Finally, we find that SST changes played a key role in the atmospheric CO2 changes associated with global climate transformations. Key Points: Orbital forcing of global sea surface temperatures (SST) evolutionEnhancement of the obliquity signal in the global SSTs at ∼2.7 Ma is closely associated with the NH glaciationChanges in SST may drive processes of ocean‐atmosphere carbon exchange that alter atmospheric CO2 concentrations [ABSTRACT FROM AUTHOR]

Estimating permafrost distribution in high‐mountain areas is challenging. In these situations, rock glaciers, provide valuable insights into permafrost distribution and are often used as proxies for identifying permafrost occurrence. Integrating various climatological and topographical conditioning factors with rock glaciers enables inferring the distribution of permafrost in these environments. This study utilized three machine learning models such as random forest (RF), support vector (SVM), and artificial neural network (ANN), and one statistical model, namely, the frequency ratio (FR), to assess the permafrost probability over the northern Kargil region of Indian Himalayas. Among 198 rock glaciers identified through high‐resolution images from Google Earth, 70% are used as training dataset, rest 30% as testing dataset. The study considered eight factors: slope, aspect, elevation, curvature, mean annual land surface temperature (MA‐LST), mean annual normalized difference snow index (MA‐NDSI), mean annual normalized difference water index (MA‐NDWI), and lithology for mapping. Furthermore, the SHapley Additive exPlanations (SHAP) test assessed the variable importance for model performance. The results revealed that the RF model performs best for permafrost probability mapping, followed by the SVM, FR, and ANN models. The study also found that 11% of the total geographic area has a high and very high probability of permafrost occurrence. [ABSTRACT FROM AUTHOR]

Permafrost is strongly associated with human well‐being and has become a frontier of cryospheric science. Professor Guodong Cheng is one of the most outstanding geocryologists in China. He was elected as an academician of the Chinese Academy of Sciences in 1993 and served as the president of the International Permafrost Association from 1993–1998. In the early 1980s, Professor Cheng proposed the hypothesis of the repeated‐segregation mechanism for the formation of thick‐layered ground ice near the permafrost table. Subsequently, in the early 2000s, he proposed the "proactive roadbed cooling" concept and led the successful development of a series of specific engineering measures that were fully applied in the Qinghai–Tibet Railway Project. Furthermore, he developed a conceptual model to describe the influences of changing permafrost on the groundwater system and discovered the "sink‐holing effect" (channeling with improved hydraulic conductivity of warming permafrost). Professor Cheng has also developed theories on the three‐dimensional zonation and proposed a classification system and an altitude model for high‐altitude permafrost distribution. On this special occasion of Professor Cheng's 80th birthday, this paper summarizes his outstanding achievements on permafrost science, hoping the permafrost research community will carry forward the momentum to further advance permafrost science worldwide. [ABSTRACT FROM AUTHOR]

Leveraging Gravity Recovery and Climate Experiment mascon products spanning from April 2002 to September 2023, we, for the first time, ascertain the substantial influence of cryospheric mass variations on Earth's Chandler wobble (CW). Further, in contrast to traditional analysis conducted in the excitation domain, this study focuses on the polar motion domain and incorporates the wavelet analysis technique. Our findings reveal some intriguing phenomena: Between 2006 and 2020, the cryosphere contributed an average amplitude of approximately 4.85 mas to CW, equivalent to 5.05%, with its impact escalating to about 11 mas from 2018 to 2022, representing a fourfold rise in its contribution ratio to approximately 20%. This marked surge can be attributed to the more erratic glacier mass balance results from ongoing climate change. Moreover, there is a pronounced decrease in the CW signal post‐2018, which starkly contrasts with cryospheric contribution, suggesting a potential linkage to climate change yet warrants further investigation. Plain Language Summary: The Earth wobbles as it rotates like a spinning top. The largest of these wobbles, known as Chandler wobble, represents a free oscillation within the Earth's solid mantle. It undergoes subtle yet fluctuating temporal variations and is partially influenced by climate‐related fluid layers, including the atmosphere and ocean. This study explores the impact of the cryosphere—specifically the mass change in the Antarctic and Greenland ice sheets and global alpine glaciers—on the Chandler wobble. By analyzing gravity satellite (GRACE and its follow‐on) data from 2002 to 2023, we ascertain for the first time that cryospheric variations can substantially affect this wobble. Furthermore, employing advanced data analysis techniques enables us to unveil an intensified influence of the cryosphere in recent years that has captured our attention. Such intensification can be attributed to ongoing climate shifts, which led to increasingly irregular mass variations within the cryosphere. These findings enhance our understanding of how the cryosphere dynamics influence Earth's wobble, providing insights into the broader impacts of climate change. Key Points: For the first time, we confirm the substantial excitation of the cryosphere on Chandler wobbleUsing innovative approaches, we reveal its time‐varying contribution to Chandler wobble, which remarkably surged to about 11 mas by 2022We emphasize the growing impact of climate change on Chandler wobble, indicated by the increasingly erratic cryospheric dynamics [ABSTRACT FROM AUTHOR]

Continuously monitoring and mapping glacial lake variation is of great importance for determining changes in water resources and potential hazards in alpine cryospheric regions. The semi-automated glacial lake mapping methods used currently are hampered by inherent subjectivity and inefficiency. This study used improved YOLOv5 strategies to extract glacial lake boundaries from Sentinel-2 imagery. These strategies include using the space-to-depth technique to identify small glacial lakes, and adopting the coordinate attention and the convolution block attention modules to improve mapping performance and adaptability. In terms of glacial lake extraction, the improved YOLOv5-seg network achieved values of 0.95, 0.93, 0.96, and 0.94 for precision (P), recall (R), mAP_0.5, and the F1 score, respectively, indicating an overall improvement in performance of 12% compared to that of the newest YOLOv8 networks. In High Mountain Asia (HMA), 23,108 glacial lakes with a total area of 1847.5 km² were identified in imagery from 2022 using the proposed method. Compared with the use of manual interpretation for lake boundary extraction in test sites of HMA, the proposed method achieved values of 0.89, 0.87, and 0.86 for P, R, and the F1 score, respectively. Our proposed deep learning method has improved accuracy in glacial lake extraction because it can address the challenge represented by frozen or high-turbidity glacial lakes in HMA. [ABSTRACT FROM AUTHOR]

After peak snowmelt, baseflow is the primary contributor to streamflow in snow-dominated watersheds. These low flows provide important water for municipal, agricultural, and recreational purposes once peak flows have been allocated. This study examines the correlation between peak snow water equivalent (SWE), post-peak SWE precipitation, and baseflow characteristics, including any yearly lag in baseflow. To reflect the hydrologic processes that are occurring in snow-dominated watersheds, we propose using a melt year (MY) beginning with the onset of snowmelt contributions (the first deviation from baseflow) and ending with the onset of the following year's snowmelt contributions. We identified the beginning of an MY and extracted the subsequent baseflow values using flow duration curves (FDCs) for 12 watersheds of varying sizes across Colorado, USA. Based on the findings, peak SWE and summer rain both dictate baseflow, especially for the larger watersheds evaluated, as identified by higher correlations with the MY-derived baseflow. Lags in the correlation between baseflow and peak SWE are best identified when low-snow years are investigated separately from high-snow years. The MY is a different and more effective approach to calculating baseflow using FDCs in snow-dominated watersheds in Colorado. [ABSTRACT FROM AUTHOR]

Seasonal precipitation estimation in ungauged mountainous areas is essential for understanding and modeling a physical variable of interest in many environmental applications (hydrology, ecology, and cryospheric studies). Precipitation lapse rates (PLRs), defined as the increasing or decreasing rate of precipitation amounts with the elevation, play a decisive role in high-altitude precipitation estimation. However, the documentation of PLR in mountainous regions remains weak even though their utilization in environmental applications is frequent. This article intends to assess the spatial variability and the spatial-scale dependence of seasonal PLRs in a varied and complex topographical region. At the regional scale (10 000 km 2), seven different precipitation products are compared in their ability to reproduce the altitude dependence of the annual/seasonal precipitation of 1836 stations located in France. The convection-permitting regional climate model (CP-RCM) AROME is the best in this regard, despite severe precipitation overestimation in high altitudes. The fine resolution of AROME allows for a precise assessment of the influence of altitude on winter and summer precipitation on 23 massifs at the sub-regional scale (∼ 1000 km 2) and 2748 small catchments (∼ 100 km 2) through linear regressions. With AROME, PLRs are often higher in winter at the catchment scale. The variability in the PLR is higher in high-altitude regions such as the French Alps, with higher PLRs at the border than inside the massifs. This study emphasizes the interest of conducting a PLR investigation at a fine scale to reduce spatial heterogeneity in the seasonal precipitation–altitude relationships. [ABSTRACT FROM AUTHOR]

The increasing commercial, industrial, and medical applications of plastics cannot be halted during the coming years. Microplastics are a new class of plastic pollutants which have emerged as escalating environmental threats. The persistence, effects, and removal of MPs present in soil, water, and numerous organisms have become an important research field. However, atmospheric microplastics (AMPs), which are subcategorized into deposited and suspended, remain largely unexplored. This review presents the recent developments and challenges involved in fully understanding suspended and deposited AMPs. The evaluation of indoor suspended MP fibers needs to be critically investigated to understand their implications for human health. Furthermore, the transportation of AMPs to isolated locations, such as cryospheric regions, requires immediate attention. The major challenges associated with AMPs, which have hindered advancement in this field, are inconsistency in the available data, limited knowledge, and the lack of standardized methodologies for the sampling and characterization techniques of AMPs. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is a climate-sensitive and ecologically fragile area. Studying drought and its effects on vegetation over the TP is of great significance for ecological conservation. However, there were large uncertainties in previous studies on the drought characteristics and their impacts on alpine vegetation in this region. This study explored the drought changes and their impacts on alpine vegetation during the growing season over the TP in 1982–2018. The results showed that the TP has experienced a wetting trend in most regions of the TP. Correspondingly, the vegetation has become greener in most areas. The wetting and drying trend in the growing season changed around 1995. Before 1995, the TP experienced an overall drying trend with a spatial pattern of a drying trend in the northern regions and a wetting trend in the southern regions, while it showed an overall wetting trend after 1995, with a reversed spatial pattern to that before 1995. After 1995, wetting and drying trends affected the vegetation in 61% of the TP. However, before 1995, the NDVI presented an increasing trend in most areas of the TP under a drying trend. Therefore, a drying trend was not the primary factor affecting vegetation growth in this period. Instead, changes in the cryosphere induced by warming could be the main factor. In addition, the distribution of vegetation across the TP was primarily influenced by drought intensity, which had the greatest impact on sparse vegetation, followed by meadow and grassland. This study enhances our understanding of the impact of drought changes on alpine vegetation on the TP. [ABSTRACT FROM AUTHOR]

Understanding the hydrological processes on the Tibetan Plateau (TP) under climate change is an important scientific question. The frequent multiphase transfer exacerbates the complexity of hydrological processes on the TP, which brings equifinality problem to hydrological models and causes large uncertainties in quantifying the contributions of runoff components. Tracer‐aided hydrological models are helpful for improving model performances and have been adopted in cryospheric regions, but the influence of frozen soil has yet to be considered. This study adopted the Tracer‐aided Tsinghua Representative Elementary Watershed model (THREW‐T) in a typical cold basin with widespread frozen soil on the TP. The model structure was diagnosed with isotope by identifying the influences of frozen soil. A simplified catchment‐scale frozen soil module was incorporated into the model. Results showed that: (a) The THREW‐T model cannot simultaneously simulate baseflow and stream water isotope well. The imbalance of simulations on two objectives could be attributed to the influence of frozen soil, resulting in seasonal variation of soil‐related parameters, which was not considered in the model. (b) Incorporating the frozen soil module significantly improved the balance of baseflow and isotope simulation, simultaneously producing low baseflow and high contribution of subsurface runoff during wet seasons. (c) The frozen soil had little influence on the annual streamflow, but changed the runoff seasonality by reducing baseflow during dry seasons and increasing subsurface runoff during wet seasons. The frozen soil module was still simplified, and further work is needed to improve the physical representation of soil freeze‐thaw process. This study highlights the value of tracer‐aided hydrological modeling method on diagnosing model structure by identifying the influence of specific processes such as frozen soil. Plain Language Summary: Soil freeze‐thaw process has important impact on hydrological processes by influencing the hydraulic properties of soil, leading to complex hydrological processes in cold regions and uncertainties in hydrological modeling. Tracer‐aided hydrological models incorporating the simulations of tracers (e.g., stable isotope in water) are helpful for improving model performances, but their values on identifying the impact of frozen soil and reducing related uncertainties are inadequately explored. In this study, we found that the Tracer‐aided Tsinghua Representative Elementary Watershed model (THREW‐T) cannot achieve good simulation of baseflow and stream water isotope simultaneously. We attributed the imbalance of two objectives to the seasonal variation of soil‐related parameters caused by frozen soil, which was not considered in the original model. We developed a simplified frozen soil module to characterize the variations of soil storage and hydraulic conductivity. The model incorporated with this module performed well on the baseflow and isotope simulations, by simulating low baseflow during dry seasons and high contribution of subsurface runoff during wet seasons simultaneously. Given that the streamflow could be simulated well even if not considering frozen soil, this study highlights the value of tracer‐aided modeling on diagnosing model structure by identifying the hydrological impact of frozen soil. Key Points: Frozen soil resulted in the imbalanced simulation on baseflow and isotope of THREW‐T modelThe developed frozen soil module improved the balance of simulations on multiple objectivesThe tracer‐aided modeling method has significant value on diagnosing model structure and identifying the hydrological impact of frozen soil [ABSTRACT FROM AUTHOR]

Climate change is increasingly affecting components of the terrestrial cryosphere with its adverse impacts in the Arctic regions of our planet are already well documented. In this context, it is regarded today as a key scientific priority to develop methodologies and operational tools that can assist towards advancing our monitoring capabilities and improving our decision-making competences in Arctic regions. In particular, the Arctic coasts are the focal point in this respect, due to their strong connection to the physical environment, society, and the economy in such areas. Geoinformation, namely Earth Observation (EO) and Geographical Information Systems (GISs), provide the way forward towards achieving this goal. The present review, which to our knowledge is the first of its kind, aims at delivering a critical consideration of the state-of-the-art approaches exploiting EO datasets and GIS for mapping the Arctic coasts properties. It also furnishes a reflective discussion on the scientific gaps and challenges that exist that require the attention of the scientific and wider community to allow exploitation of the full potential of EO/GIS technologies in this domain. As such, the present study also serves as a valuable contribution towards pinpointing directions for the design of effective policies and decision-making strategies that will promote environmental sustainability in the Arctic regions. [ABSTRACT FROM AUTHOR]

It has been previously proposed that glacial inception represents a bifurcation transition between interglacial and glacial states and is governed by the nonlinear dynamics of the climate–cryosphere system. To trigger glacial inception, the orbital forcing (defined as the maximum of summer insolation at 65° N and determined by Earth's orbital parameters) must be lower than a critical level, which depends on the atmospheric CO2 concentration. While paleoclimatic data do not provide a strong constraint on the dependence between CO2 and critical insolation, its accurate estimation is of fundamental importance for predicting future glaciations and the effect that anthropogenic CO2 emissions might have on them. In this study, we use the novel Earth system model of intermediate complexity CLIMBER-X with interactive ice sheets to produce a new estimation of the critical insolation– CO2 relationship for triggering glacial inception. We perform a series of experiments in which different combinations of orbital forcing and atmospheric CO2 concentration are maintained constant in time. We analyze for which combinations of orbital forcing and CO2 glacial inception occurs and trace the critical relationship between them, separating conditions under which glacial inception is possible from those where glacial inception is not materialized. We also provide a theoretical foundation for the proposed critical insolation– CO2 relation. We find that the use of the maximum summer insolation at 65° N as a single metric for orbital forcing is adequate for tracing the glacial inception bifurcation. Moreover, we find that the temporal and spatial patterns of ice sheet growth during glacial inception are not always the same but depend on the critical insolation and CO2 level. The experiments evidence the fact that during glacial inception, ice sheets grow mostly in North America, and only under low CO2 conditions are ice sheets also formed over Scandinavia. The latter is associated with a weak Atlantic Meridional Overturning Circulation (AMOC) for low CO2. We find that the strength of AMOC also affects the rate of ice sheet growth during glacial inception. [ABSTRACT FROM AUTHOR]

Global warming is one of the primary causes contributing to melting glaciers and shrinking of glaciers moth. Because of the glacier retreat, more lakes increase the risk of flooding in people's homes and lives. Several studies on the surging glaciers have been conducted by researchers using various techniques, as well as with the aid of multiple models like the Normalized Differential Water Index (NDWI). The Number of glacial lakes is increasing in the Himalayan region due to climate change (rise of the temperature). Some glacial lakes are potentially dangerous so monitoring is very necessary. It is necessary to evaluate such vulnerable lakes. Therefore, current work is carried out to identify such glacial lakes present in the Teesta River Basin (Eastern Himalaya). Spatiotemporal Landsat data for the last four decades at intervals of ten years from 1990 to 2020 has been considered which was cloud-free and spatial resolution of 30 meters. The dataset mentioned above was used for lake identification and delineation. The findings indicate the presence of lakes with respective areas of 275 (18.90 km²), 337 (24.92 km²), 295 (22.96 km²), and 419 (31.44 km²). It has also been observed that the growth rate is increasing with approximate water spread from 1990 to 2000 (+129%), 2000 to 2010 (+106%), and 2010 to 2020 (+136%). The present study aimed to identify such glacial lakes based on their water spreading area, which is an essential step followed in the study of GLOF (Glacial Lake Outburst Flood) as it will be helpful in the identification of hazardous lakes. In that study, we found that eleven glacial lakes are in the potentially dangerous category situated in the upper Teesta Basin due to the presence of glaciers, which gives a clear reason for the time-to-time assessment of such lakes. By the conducted study it has been observed that the number of glacial lakes has increased, due to which water spread has also increased in the area. It can also be demonstrated that GIS (Geographical Information System), along with remote sensing, is one of the best tools for assessing and monitoring such change detection and differentiation of hazardous glacial lakes in the cryosphere, along with the supporting data. [ABSTRACT FROM AUTHOR]

Boulders are ubiquitous on rocky planets and provide valuable information about planetary processes. The abundance, size, and distribution of boulders offer insights into the primary processes that form them and the secondary processes that modify their position and size. However, the roles of varying environmental processes, including cryospheric processes, are poorly known. In this study, we analyze over 20 million boulders in the northern lowlands of Mars (50–70°N) to evaluate their distribution and identify environmental factors that might influence their clustering. We used spatial statistics to quantify the degree of boulder clustering across the northern plains. We found two latitudinal trends: overall decreasing clustering with increasing latitude (50–70°N) and a sub‐trend of increased clustering at higher latitudes (65–70°N). Our findings suggest that boulder distribution patterns are linked to the latitude‐dependent mantle (LDM) and subsurface ice. Boulders exhibit higher spatial clustering at higher latitudes, where the ice is thick and continuously present, and the LDM is more pristine. Lower clustering occurs at lower latitudes or regions where the ice loss is likely during interglacial periods, and the LDM degrades, exposing more boulders of varying sizes. We also discovered an anomalous region where boulder clustering is nearly random, located on the edge of the Alba Mons Patera. This area displays distinct geophysical characteristics compared to the rest of the lowlands. Although these characteristics do not indicate a specific process for the variation of boulder distribution in this study, the data suggest a coupling between cryospheric processes and boulder evolution, warranting further research. Plain Language Summary: Boulders are common on rocky planets and can provide important information about boulder‐forming processes and displacement. We studied over 20 million boulders on the northern plains of Mars to learn more about how they are distributed across the planet and what factors might influence their placement. We found that boulders are more likely clustered in areas with more ice below the surface. We also discovered an area north of Alba Mons where boulders seem to be scattered randomly, and the surface properties are different than elsewhere in the northern plains. This may be due to the repeated deposition and removal of ice in this area, but more research is needed to fully understand these patterns. Key Points: The level of boulder clustering follows latitudinally varying mantle distribution and degradation statesThe topographic, geophysical, and surface characteristics of northern Alba Patera indicate a higher presence of subsurface iceLandscape ages across the Martian northern lowlands may affect variations in boulder distributions [ABSTRACT FROM AUTHOR]

Sources and fluxes of methane to the atmosphere from permafrost are significant but poorly constrained in global climate models. We present data collected from the variable permafrost setting of the outer Mackenzie River Delta, including observations of aquatic methane seepage, core determinations of in situ methane occurrence and seep gas isotope geochemistry. The sources and locations of in situ geologic methane occurrence and aquatic and atmospheric gas release appear to be controlled by the regional geology and permafrost conditions. Where permafrost is >250 m thick, thermogenic gas deposits at depth are isolated by laterally continuous, low permeability ice‐bearing sediments with few through‐going thawed taliks. Thus, the observed in situ methane and aquatic gas seepage appears to be dominated by microbial methane. In contrast, where permafrost is <80 m thick, taliks are more likely to be through‐going, providing permeable conduits from depth and migration pathways for both thermogenic and biogenic gas. Continuous annual fluid sampling of two lakes and a river channel documents aquatic methane flux from microbial sources, more deeply buried thermogenic sources, and mixtures of both. Using estimates of in situ methane concentration from deep core samples and observations of in situ free gas occurrences, we conclude that the reservoir of in situ geologic methane within ice bonded permafrost is substantial and that this methane is presently migrating with ongoing atmospheric release. It is our assessment that the permafrost setting, and processes described are sensitive to future climate change as the permafrost warms. Plain Language Summary: Methane is released from permafrost, yet the amount and sources of the methane are poorly understood. This paper presents data on methane released from water environments and stored in soil from the permafrost areas of the outer Mackenzie River Delta, NWT. It also uses isotope geochemistry to determine the source (type) of the methane ‐ either biogenic (produced by living organisms) or thermogenic (produced by breaking down of organic matter by heat). The sources and locations of the methane gas release appear to be controlled by the regional geology and permafrost conditions. We conclude that the methane stored within and beneath the ice bonded permafrost is substantial and that this methane is presently migrating to aquatic systems with ongoing atmospheric release. It is our assessment that this permafrost setting and the potential for increased methane release are sensitive to future climate change as the permafrost warms. Key Points: A unique annual record of dissolved methane geochemistry documents active microbial and geologic methane sources in a delta lake and channelSeep gas chemistry, geophysical, and core data allow appraisal of permafrost controls on subsurface methane dynamics in the Mackenzie DeltaThe large inventory of stored methane and the dynamic permafrost processes described are potentially responsive to future climate change [ABSTRACT FROM AUTHOR]

ABSTRACTWe present a field-based reconstruction of the geomorphology in the Subtropical Andean mountains of the Limarí basin, semiarid central Chile (30–31° S). Fieldwork campaigns and remote-sensing analysis served for detailed geomorphological mapping at four formerly glaciated valleys in the heads of the Combarbalá and Río Hurtado sub-basins. We identify a mosaic of glacial, periglacial, and paraglacial landforms. Glacial landforms include a massive dead-ice moraine complex, with thermokarst and debris-filled fractures suggesting former ice-cored moraine degradation. This landform is superimposed by transversal and arcuate ridges suggesting active-ice processes. Periglacial landforms such as rock glaciers, gelifluction, and protalus lobes occur in cirques and U-shaped valleys, but also on moraine deposits. Paraglacial processes are indicated by talus accumulation in those formerly glaciated slopes. The geomorphological imprint is evidence for the interaction and succession between glacial, periglacial, and paraglacial dynamics from the Late Pleistocene to the present.

Antarctic ice shelves are losing mass at drastically different rates, primarily due to differing rates of oceanic heat supply to their bases. However, a generalized theory for the inflow of relatively warm water into ice shelf cavities is lacking. This study proposes such a theory based on a geostrophically constrained inflow, combined with a threshold bathymetric elevation, the Highest Unconnected isoBath (HUB), that obstructs warm water access to ice shelf grounding lines. This theory captures ∼ 90% of the variance in melt rates across a suite of idealized process‐oriented ocean/ice shelf simulations with quasi‐randomized geometries. Applied to observations of ice shelf geometries and offshore hydrography, the theory captures ∼80% of the variance in measured ice shelf melt rates. These findings provide a generalized theoretical framework for melt resulting from buoyancy‐driven warm water access to geometrically complex Antarctic ice shelf cavities. Plain Language Summary: The floating extensions of Antarctic glaciers ("ice shelves") are losing ice at drastically different rates. A large component of this ice loss is due to melting from below by relatively warm ocean waters, which typically lie hundreds of meters below the surface. Previous studies have attempted to predict ice shelf melt rates using knowledge of the interface between the ice and the ocean. However, these relationships struggle to capture the variations in melt rates around Antarctica, in part because they do not account for obstruction of warm water access by variations in the shae of the seafloor. In this study we introduce a theory for the rate at which warm waters access Antarctica's ice shelves, which indirectly predicts how much the ice shelf melts. This theory is grounded in the assumption that the ocean flow beneath cavities is dominated by the rotation of the earth, and utilizes a novel quantification of seafloor obstruction of warm water inflows. We show that this theory is successful at predicting melt in simulations of ice shelves of different shapes, and in observations of real ice shelves. This work provides a theoretical grounding for melt resulting from warm subsurface waters flowing underneath Antarctic ice shelves. Key Points: We introduce a new theoretical framework for inflow of warm water into ice shelf cavities based on geostrophically‐constrained circulationA new metric, the Highest Unconnected Isobath (HUB), quantifies bathymetric barriers to warm water access in complex geometriesOur HUB‐informed theoretical framework is able to accurately predict melt rates across a suite of idealized models and observational data [ABSTRACT FROM AUTHOR]

Long‐term records of the flow patterns and dynamics of surge‐type glaciers improve our understanding of their underlying dynamic processes, and are critical to better resolve their contribution to a changing cryosphere. We adapt a modeling approach designed to emulate glacier surging and fold kinematics using the full Stokes ice‐flow model Elmer/Ice to simulate surging of the Dusty Glacier, located in the St. Elias Mountains, Canada. We combine distributed mass‐balance and numerical ice‐flow models to reconstruct the fold kinematics of the 2001–2003 surge of the Dusty Glacier by comparing model results to Landsat‐7 and Sentinel‐2 imagery, and assess the sensitivity of centennial‐scale modeled glacier structure to different mass balance and sliding parameterizations. This study demonstrates the feasibility of using the approach to reconstruct the surface structure kinematics of a surge‐type glacier in nature, highlighting its potential application to other surge‐type glaciers and regions. Plain Language Summary: Glaciers can exhibit irregular flow patterns that complicate predictions of their evolution over the coming decades and centuries. We present a method for reproducing iconic surface structures known as folded medial moraines using glaciological modeling. These moraines are wavy flow patterns found on surge‐type glaciers, highlighted by sediment deposited onto the ice that traces their path. By reconstructing these patterns, the underlying climate and sliding conditions that contributed to the glacier's past flow can be identified. Improving our knowledge of these conditions can help improve glacier flow models. We demonstrate that our methodology successfully reconstructs the flow patterns present on a large surge‐type glacier in Yukon, Canada, and explore its past flow history, and possible future, based on these results. Key Points: We use a distributed mass‐balance model and Elmer/Ice to reconstruct the 2001–2003 surge kinematics of the Dusty Glacier, Yukon, CanadaWe explore the centennial‐scale sensitivity of glacier surface fold geometry to mass balance and sliding parameterizationsThis study is a proof‐of‐concept for further model reconstructions of the past dynamics of surge‐type glaciers [ABSTRACT FROM AUTHOR]

The snowline exhibits significant seasonal shifts upward and downward, reflecting the ever-changing dynamics of the seasons and being influenced by climate variations, which can vary annually. These fluctuations profoundly impact the cryosphere, biota, and ecosystem processes in high mountain regions. Despite the critical role of snowline variations, comprehensive information on how actual climate variability affects snow cover trends in the central mountain range of the western Himalayas is scarce. In the 'Pindari' region of the Uttarakhand district, India, which is part of the Himalayas, these challenges are exacerbated by the unchecked growth of anthropogenic activities and the broader impacts of climate change. This study analyses snowline variations in the Pindari glacial region from 1972 to 2018. The findings revealed that the snowline elevation significantly shifted upward between 1972 and 2018. Notably, this research revealed a decrease in snow-covered areas of approximately 5.01 km2 over the course of 46 years. This decrease is attributed to a direct response to the increasing number of high-temperature events that occurred during this extended period. This study emphasizes the urgent need for conservation measures in the study region and similar high mountains to combat global warming and safeguard the snowline, which serves as a visible proxy indicator to safeguard high-altitude Himalayan glaciers. [ABSTRACT FROM AUTHOR]