Terrestrial Cryosphere Research Articles

Spatial-temporal variation of river ice coverage in the Yenisei river from 2002 to 2021

River ice is an essential component of the terrestrial cryosphere, which is sensitive to global and regional climate change. The Yenisei River provides the largest river inflow to the Arctic Ocean, heavily affected by the cold climate. Data on the ice cover in the Arctic great rivers are insufficient due to the absence of a river ice database with high spatiotemporal resolution. In this study, the daily river ice coverage (RIC, defined as the fraction of river ice pixels to river pixels in a grid cell) in the Yenisei River was estimated from 2002 to 2021 in a 12.5 × 12.5 km grid, by utilizing a cloud removal method for Moderate Resolution Imaging Spectroradiometer (MODIS) data. Based on Landsat imagery reference, the RIC correlations (Pearson’s R) were 0.77, 0.84, and 0.97 for three separate validation regions. Over the past 20 years, 82.8 % of the grid cells experienced a decreasing ice cover, with 21.9 % significant at the 0.05 level. The mean winter air temperature was the key predictor (R2 = 0.48, P < 0.01), better than the accumulated negative air temperature (R2 = 0.42, P < 0.01). The spatial distribution of winter RIC exhibited a latitudinal gradient (R2 = 0.64, P < 0.01). River ice responded to temperature variation in a non-linear way, depending on latitude, with high sensitivity in the southern part of the watershed. In Lake Baikal in the river basin, the distribution of ice cover was also affected by stream inflows. The results provide a comprehensive insight into the spatial–temporal variations of the Yenisei River and explore the key factor of changes in river ice, enhancing our ability to understand the response of Arctic great rivers to climate change.

Geoinformation Technology in Support of Arctic Coastal Properties Characterization: State of the Art, Challenges, and Future Outlook

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.

Full Polarimetric GNSS-R Assessment of the Freeze and Thaw States of the Terrestrial Cryosphere

Full Polarimetric GNSS-R Assessment of the Freeze and Thaw States of the Terrestrial Cryosphere

Retrieving freeze-thaw states using deep learning with remote sensing data in permafrost landscapes

The soil freeze–thaw (FT) cycle is a critical component of the terrestrial cryosphere and plays a significant role in hydrological, ecological, climatic, and biogeochemical processes within permafrost landscapes. The FT states can be monitored with in-situ field measurements, but these procedures are costly and limited to single chosen sites. Remote sensing data provides the opportunity to collect information repeatedly across extensive geographical areas. To explore a more effective way to monitor the FT states in the terrestrial cryosphere, in this study, we used microwave and optical remote sensing data and introduced the Deep Learning approach to simulate the soil FT states in the western part of Nunavik, Canada.Two networks, Multilayer Perceptron (MLP) and Convolutional Neural Network (CNN), were trained and tested with over 35,000 and approximately 54,000 randomly selected data samples, respectively. The trained CNN networks outperformed the MLP networks, achieving the highest testing accuracy of 95.67% and the highest validation accuracy of 87.28% based on ground truth data from 32 measurement stations from all seasons across the year. This study proposed the reference periods concept for convenient labeling in data preparation and tested different combinations of influence variables to achieve better transferability of the method for future studies. Our findings offer a more effective way to monitor FT states in the terrestrial cryosphere, offering valuable insights into the consequences of climate change on permafrost landscapes. Moreover, the suggested deep learning approach can be easily expanded when additional input sources are accessible. This expansion has the potential to further improve the model's performance for the FT retrieval.

Coupled Changes in the Arctic Carbon Cycle Between the Land, Marine, and Social Domains

AbstractThe Arctic has experienced rapid change associated with warming since the 1970s. The rapid retreat of the terrestrial cryosphere can release a large amount greenhouse gas from the permafrost regions into the air, and the sea ice decline will affect the CO2 and CH4 balance in the ocean. Changes in the Arctic provide feedback mechanisms that can also impinge on the global ocean’s thermohaline circulation. During the past years, the overall natural processes in the Arctic have been studied although the magnitude and timing of carbon release from the cryosphere changes require further investigation. However, few studies have been conducted to link the natural and social systems in the Arctic. Scientists and policymakers must consider the coupled Arctic land, ocean, and social systems in their decisions for coping with climate change.

Coastal permafrost was massively eroded during the Bølling-Allerød warm period

The Bølling-Allerød interstadial (14,700–12,900 years before present), during the last deglaciation, was characterized by rapid warming and sea level rise. Yet, the response of the Arctic terrestrial cryosphere during this abrupt climate change remains thus far elusive. Here we present a multi-proxy analysis of a sediment record from the northern Svalbard continental margin, an area strongly influenced by sea ice export from the Arctic, to elucidate sea level - permafrost erosion connections. We show that permafrost-derived material rich in biospheric carbon became the dominant source of sediments at the onset of the Bølling-Allerød, despite the lack of direct connections with permafrost deposits. Our results suggest that the abrupt temperature and sea level rise triggered massive erosion of coastal ice-rich Yedoma permafrost, possibly from Siberian and Alaskan coasts, followed by long-range sea ice transport towards the Fram Strait and the Arctic Ocean gateway. Overall, we show how coastal permafrost is susceptible to large-scale remobilization in a scenario of rapid climate variability.

The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere

Abstract. The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice–water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2, and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Different model components, characterized by their process representations and parameterizations, are realized as classes (i.e., objects) in CryoGrid. Standardized communication protocols between these classes ensure that they can be stacked vertically. For example, the CryoGrid community model features several classes with different complexity for the seasonal snow cover, which can be flexibly combined with a range of classes representing subsurface materials, each with their own set of process representations (e.g., soil with and without water balance, glacier ice). We present the CryoGrid architecture as well as the model physics and defining equations for the different model classes, focusing on one-dimensional model configurations which can also interact with external heat and water reservoirs. We illustrate the wide variety of simulation capabilities for a site on Svalbard, with point-scale permafrost simulations using, e.g., different soil freezing characteristics, drainage regimes, and snow representations, as well as simulations for glacier mass balance and a shallow water body. The CryoGrid community model is not intended as a static model framework but aims to provide developers with a flexible platform for efficient model development. In this study, we document both basic and advanced model functionalities to provide a baseline for the future development of novel cryosphere models.

PermaBN: A Bayesian Network framework to help predict permafrost thaw in the Arctic

Rising global temperatures are a threat to the current state of the Arctic. In particular, permafrost degradation has been impacting the terrestrial cryosphere in many ways, including effects on carbon cycling and the global climate, regional hydrological connectivity and ecosystem dynamics, as well as human health and infrastructure. However, the ability to simulate permafrost dynamics under future climate projections is limited, and model outputs are often associated with large uncertainties. A model structured on a Bayesian Network is presented to address existing limitations in the representation of physically complex processes and the limited availability of observational data. A strength of Bayesian methods over more traditional modeling methods is the ability to integrate various types of evidence (i.e., observations, model outputs, expert assessments) into a single model by mapping the evidence into probability distributions. Here, we outline PermaBN, a new modeling framework, to simulate permafrost thaw in the continuous permafrost region of the Arctic. Pre-validation and expert assessment validation results show that the model produces estimations of permafrost thaw depth that are consistent with current research, i.e., thaw depth increases during the snow-free season under initial conditions favoring warming temperatures, lowered soil moisture conditions, and low active layer ice content. Using a case study from northwestern Canada to evaluate PermaBN, we show that model performance is enhanced when certainty about the system components increases for known scenarios described by observations directly integrated into the model; in this case, insulation properties from vegetation were integrated to the model. Overall, PermaBN could provide informative predictions about permafrost dynamics without high computational cost and with the ability to integrate multiple types of evidence that traditional physics-based models sometimes do not account for, allowing PermaBN to be applied to carbon modeling studies, infrastructure hazard assessments, and policy decisions aimed at mitigation of, and adaptation to, permafrost degradation.

Retrieving Freeze/Thaw Cycles Using Sentinel-1 Data in Eastern Nunavik (Québec, Canada)

In the terrestrial cryosphere, freeze/thaw (FT) state transitions play an important and measurable role in climatic, hydrological, ecological, and biogeochemical processes in permafrost landscapes. Active and passive microwave remote sensing has shown a principal capacity to provide effective monitoring of landscape FT dynamics. The study presents a seasonal threshold approach, which examines the timeseries progression of remote sensing measurements relative to signatures acquired during seasonal frozen and thawed reference states. This is used to estimate the FT state from the Sentinel-1 database and applied and evaluated for the region of Eastern Nunavik (Québec, Canada). An optimization process of the threshold is included. In situ measurements from the meteorological station network were used for the validation process. Overall, acceptable estimation accuracy (&gt;70%) was achieved in most tests; on the best-performing sites, an accuracy higher than 90% was reached. The performance of the seasonal threshold approach over the study region was further discussed with consideration of land cover, spatial heterogeneity, and soil depth. This work is dedicated to providing more accurate data to capture the spatiotemporal heterogeneity of freeze/thaw transitions and to improving our understanding of related processes in permafrost landscapes.

Holocene sea-ice dynamics in Petermann Fjord in relation to ice tongue stability and Nares Strait ice arch formation

Abstract. The Petermann 2015 expedition to Petermann Fjord and adjacent Hall Basin recovered a transect of cores, extending from Nares Strait to underneath the 48 km long ice tongue of Petermann glacier, offering a unique opportunity to study ice–ocean–sea ice interactions at the interface of these realms. First results suggest that no ice tongue existed in Petermann Fjord for large parts of the Holocene, raising the question of the role of the ocean and the marine cryosphere in the collapse and re-establishment of the ice tongue. Here we use a multi-proxy approach (sea-ice-related biomarkers, total organic carbon and its carbon isotopic composition, and benthic and planktonic foraminiferal abundances) to explore Holocene sea ice dynamics at OD1507-03TC-41GC-03PC in outer Petermann Fjord. Our results are in line with a tight coupling of the marine and terrestrial cryosphere in this region and, in connection with other regional sea ice reconstructions, give insights into the Holocene evolution of ice arches and associated landfast ice in Nares Strait. The late stages of the regional Holocene Thermal Maximum (6900–5500 cal yr BP) were marked by reduced seasonal sea ice concentrations in Nares Strait and the lack of ice arch formation. This was followed by a transitional period towards Neoglacial cooling from 5500–3500 cal yr BP, where a southern ice arch might have formed, but an early seasonal breakup and late formation likely caused a prolonged open water season and enhanced pelagic productivity in Nares Strait. Between 3500 and 1400 cal yr BP, regional records suggest the formation of a stable northern ice arch only, with a short period from 2500–2100 cal yr BP where a southern ice arch might have formed intermittently in response to atmospheric cooling spikes. A stable southern ice arch, or even double arching, is also inferred for the period after 1400 cal yr BP. Thus, both the inception of a small Petermann ice tongue at ∼ 2200 cal yr BP and its rapid expansion at ∼ 600 cal yr BP are preceded by a transition towards a southern ice arch regime with landfast ice formation in Nares Strait, suggesting a stabilizing effect of landfast sea ice on Petermann Glacier.

Global Data Gaps in Our Knowledge of the Terrestrial Cryosphere

The IPCC Special Report on Oceans and Cryosphere in a Changing Climate identified major gaps in our knowledge of snow and glacier ice in the terrestrial cryosphere. These gaps are limiting our ability to predict the future of the energy and water balance of the Earth's surface, which in turn affect regional climate, biodiversity and biomass, the freezing and thawing of permafrost, the seasonal supply of water for one sixth of the global population, the rate of global sea level rise and the risk of riverine and coastal flooding. Snow and ice are highly susceptible to climate change but although their spatial extents are routinely monitored, the fundamental property of their water content is remarkably poorly observed. Specifically, there is a profound lack of basic but problematic observations of the amount of water supplied by snowfall and of the volume of water stored in glaciers. As a result, the climatological precipitation of the mountain cryosphere is, for example, biassed low by 50–100%, and biases in the volume of glacier ice are unknown but are likely to be large. More and better basic observations of snow and ice water content are urgently needed to constrain climate models of the cryosphere, and this requires a transformation in the capabilities of snow-monitoring and glacier-surveying instruments. I describe new solutions to this long-standing problem that if deployed widely could achieve this transformation.

Cryospheric water regime by its functions and services in China

The terrestrial cryosphere functions to provide critical freshwater and serve societies and ecosystems, driving nature's contributions to people (NCP). This becomes increasingly important for the oasis areas in Northwest China. The cryospheric meltwater is in demand to support the economy and reduce poverty, accompanied by growing requirements to protect the environment. We intend to investigate the contributions of cryospheric meltwater by analyzing the spatial functions and services pertinent to provisioning meltwater in China. Based on the currently available datasets during the 2000s of glaciers, snow cover, and permafrost, spatial clustering was utilized to analyze the contributions at the third-level basin scale. Further assessment is carried out for the exposure of primary, secondary, and tertiary industrial sectors to cryospheric meltwater, which reflects the spatiality of potential services that cryospheric meltwater may provide. In results, we spatially cluster the contribution of cryospheric meltwater into six function zones and twenty-seven sub-zones, in association with the degree of their reliance on glaciers, snow cover, and permafrost. Considering the sector's exposure, we further spatially cluster the contribution areas into eleven service zones concerning the potential service of cryospheric meltwater. Generally, the cryosphere contributes approximately 8.3% of the total water resource in China, with function zones mainly distributed in northeastern China, Qinghai−Tibet Plateau (QTP), and other arid regions of Northwest China with various significance. The overall contribution ratios of the glacier, snow cover, and permafrost to cryospheric meltwater are about 35.6%, 56.5%, and 7.9%, respectively. By looking into the service zones, the cryospheric meltwater mainly contributes to the primary industry in Northwest China and QTP, even though it has less significant effects on all other industrial sectors, while the services to the ecosystem are mainly located in QTP and high mountain regions. The results offer an overarching view on the contributions of cryospheric meltwater in China.

Patterns in Microbial Assemblages Exported From the Meltwater of Arctic and Sub-Arctic Glaciers.

Meltwater streams connect the glacial cryosphere with downstream ecosystems. Dissolved and particulate matter exported from glacial ecosystems originates from contrasting supraglacial and subglacial environments, and exported microbial cells have the potential to serve as ecological and hydrological indicators for glacial ecosystem processes. Here, we compare exported microbial assemblages from the meltwater of 24 glaciers from six (sub)Arctic regions – the southwestern Greenland Ice Sheet, Qeqertarsuaq (Disko Island) in west Greenland, Iceland, Svalbard, western Norway, and southeast Alaska – differing in their lithology, catchment size, and climatic characteristics, to investigate spatial and environmental factors structuring exported meltwater assemblages. We found that 16S rRNA gene sequences of all samples were dominated by the phyla Proteobacteria, Bacteroidetes, and Actinobacteria, with Verrucomicrobia also common in Greenland localities. Clustered OTUs were largely composed of aerobic and anaerobic heterotrophs capable of degrading a wide variety of carbon substrates. A small number of OTUs dominated all assemblages, with the most abundant being from the genera Polaromonas, Methylophilus, and Nitrotoga. However, 16–32% of a region’s OTUs were unique to that region, and rare taxa revealed unique metabolic potentials and reflected differences between regions, such as the elevated relative abundances of sulfur oxidizers Sulfuricurvum sp. and Thiobacillus sp. at Svalbard sites. Meltwater alpha diversity showed a pronounced decrease with increasing latitude, and multivariate analyses of assemblages revealed significant regional clusters. Distance-based redundancy and correlation analyses further resolved associations between whole assemblages and individual OTUs with variables primarily corresponding with the sampled regions. Interestingly, some OTUs indicating specific metabolic processes were not strongly associated with corresponding meltwater characteristics (e.g., nitrification and inorganic nitrogen concentrations). Thus, while exported assemblage structure appears regionally specific, and probably reflects differences in dominant hydrological flowpaths, OTUs can also serve as indicators for more localized microbially mediated processes not captured by the traditional characterization of bulk meltwater hydrochemistry. These results collectively promote a better understanding of microbial distributions across the Arctic, as well as linkages between the terrestrial cryosphere habitats and downstream ecosystems.

Cryosphere carbon dynamics control early Toarcian global warming and sea level evolution

The Earth's cryosphere represents a huge climate-sensitive carbon reservoir capable of releasing carbon dioxide (CO2) and methane (CH4) from permafrost soils or gas reservoirs capped by permafrost and ice caps upon rising global temperatures. Carbon release from these reservoirs has the potential to further accelerate global warming. Present day cryosphere demise is a focus of scientific research. The potential role of cryosphere carbon reservoirs in Mesozoic climate perturbations is even lesser known and currently underinvestigated. In contrast to previous views of a constantly warm Early Jurassic period, virtually lacking a cryosphere, recent studies have identified icehouse conditions for this time interval. Following these icehouse conditions, global warming occurred during the early Toarcian (~183 Ma) and was accompanied by a major carbon cycle anomaly as manifested in recurring negative carbon isotope excursions (CIEs). We propose that an initially volcanic-driven gentle rise of atmospheric temperature in the Early Toarcian triggered a melt-down of Earth's cryosphere which during the preceding Pliensbachian had expanded to the mid-latitudes and thus was highly vulnerable to warming. The rapid release of greenhouse gases, mainly as 13C-depleted CH4, or its oxidation product CO2, is recorded in the carbon isotope ratios of sedimentary organic matter and carbonates. Toarcian sediments display a series of orbitally-forced negative CIEs characterized by a frequency shift from eccentricity to obliquity cycles comparable to Pleistocene climate rhythms. This pattern is explained by a self-sustaining destabilization of labile cryosphere carbon reservoirs which started at mid-latitudes where eccentricity is most effective and then rhythmically progressed poleward to latitudes where obliquity dominates. The hitherto underestimated presence of a temperature-sensitive Pliensbachian cryosphere constituted an essential precondition for the early Toarcian climate change and its associated sea-level rise. The Pliensbachian cooling had transferred water into the terrestrial cryosphere causing a severe sea-level fall. Transgressive pulses at the Pliensbachian-Toarcian boundary and in the early Toarcian occurred concomitant to rising global temperatures and resulted from the meltdown of continental ice caps. This ice-volume effect and the massive discharge of freshwater into the oceans is well preserved in the exceptionally low δ18O values of carbonates formed during the cryosphere demise and sea-level increase. Carbon and oxygen isotope ratios, climate and sea-level shifts thus underpin the presence of an Early Jurassic cryosphere and thereby highlight the role of glacio-eustatic mechanisms as main drivers of late Pliensbachian to early Toarcian geodynamics.

Multi-year particle fluxes in Kongsfjorden, Svalbard

Abstract. High-latitude regions are warming faster than other areas due to reduction of snow cover and sea ice loss and changes in atmospheric and ocean circulation. The combination of these processes, collectively known as polar amplification, provides an extraordinary opportunity to document the ongoing thermal destabilisation of the terrestrial cryosphere and the release of land-derived material into the aquatic environment. This study presents a 6-year time series (2010–2016) of physical parameters and particle fluxes collected by an oceanographic mooring in Kongsfjorden (Spitsbergen, Svalbard). In recent decades, Kongsfjorden has been experiencing rapid loss of sea ice coverage and retreat of local glaciers as a result of the progressive increase in ocean and air temperatures. The overarching goal of this study was to continuously monitor the inner fjord particle sinking and to understand to what extent the temporal evolution of particulate fluxes was linked to the progressive changes in both Atlantic and freshwater input. Our data show high peaks of settling particles during warm seasons, in terms of both organic and inorganic matter. The different sources of suspended particles were described as a mixing of glacier carbonate, glacier siliciclastic and autochthonous marine input. The glacier releasing sediments into the fjord was the predominant source, while the sediment input by rivers was reduced at the mooring site. Our time series showed that the seasonal sunlight exerted first-order control on the particulate fluxes in the inner fjord. The marine fraction peaked when the solar radiation was at a maximum in May–June while the land-derived fluxes exhibited a 1–2-month lag consistent with the maximum air temperature and glacier melting. The inter-annual time-weighted total mass fluxes varied by 2 orders of magnitude over time, with relatively higher values in 2011, 2013, and 2015. Our results suggest that the land-derived input will remarkably increase over time in a warming scenario. Further studies are therefore needed to understand the future response of the Kongsfjorden ecosystem alterations with respect to the enhanced release of glacier-derived material.

Simulation of permafrost changes on the Qinghai–Tibet Plateau, China, over the past three decades

ABSTRACTPermafrost is one of the largest elements of the terrestrial cryosphere and is extremely sensitive to climate change. Based on mean annual ground temperature (MAGT) data from 189 boreholes on the Qinghai–Tibet Plateau (QTP), terrain factors, and climate data from China Meteorological Forcing Dataset, we propose a new mean annual ground air temperature (MAGAT) statistical model between meteorological parameters with subsurface temperatures to simulate permafrost distribution and variation of MAGT on the QTP over the past three decades (1981–2010). Validation of the model with MAGT data from 13 boreholes and permafrost maps of the QTP indicated that the MAGAT model is applicable to simulate the distribution and evolution of permafrost on the QTP. Simulation results show that the spatiotemporal MAGT of permafrost significantly increased by 0.37°C, or 0.25°C/10 yr, and the total area of permafrost decreased by 2.48 × 105 km2 on the QTP over the past three decades. Regionally, the changes of permafrost in the southwestern QTP were greater than other regions of the QTP.

Soil-frost-enabled soil-moisture–precipitation feedback over northern high latitudes

Abstract. Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. The currently observed global warming is most pronounced in the Arctic region and is projected to persist during the coming decades due to anthropogenic CO2 input. This warming will certainly have effects on the ecosystems of the vast permafrost areas of the high northern latitudes. The quantification of such effects, however, is still an open question. This is partly due to the complexity of the system, including several feedback mechanisms between land and atmosphere. In this study we contribute to increasing our understanding of such land–atmosphere interactions using an Earth system model (ESM) which includes a representation of cold-region physical soil processes, especially the effects of freezing and thawing of soil water on thermal and hydrological states and processes. The coupled atmosphere–land models of the ESM of the Max Planck Institute for Meteorology, MPI-ESM, have been driven by prescribed observed SST and sea ice in an AMIP2-type setup with and without newly implemented cold-region soil processes. Results show a large improvement in the simulated discharge. On the one hand this is related to an improved snowmelt peak of runoff due to frozen soil in spring. On the other hand a subsequent reduction in soil moisture enables a positive feedback to precipitation over the high latitudes, which reduces the model's wet biases in precipitation and evapotranspiration during the summer. This is noteworthy as soil-moisture–atmosphere feedbacks have previously not been the focus of research on the high latitudes. These results point out the importance of high-latitude physical processes at the land surface for regional climate.

Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of which is almost comparable to that due to CO2 (2.83 W m-2) increases since 1750. Our results thus highlight the necessity of realistic representation of snow albedo in the model and demonstrate the use of satellite-based snow albedo to improve model behaviors, which opens new avenues for constraining snow albedo feedback in earth system models.

A ground temperature map of the North Atlantic permafrost region based on remote sensing and reanalysis data

Abstract. Permafrost is a key element of the terrestrial cryosphere which makes mapping and monitoring of its state variables an imperative task. We present a modeling scheme based on remotely sensed land surface temperatures and reanalysis products from which mean annual ground temperatures (MAGT) can be derived at a spatial resolution of 1 km at continental scales. The approach explicitly accounts for the uncertainty due to unknown input parameters and their spatial variability at subgrid scale by delivering a range of MAGTs for each grid cell. This is achieved by a simple equilibrium model with only few input parameters which for each grid cell allows scanning the range of possible results by running many realizations with different parameters. The approach is applied to the unglacierized land areas in the North Atlantic region, an area of more than 5 million km2 ranging from the Ural Mountains in the east to the Canadian Archipelago in the west. A comparison to in situ temperature measurements in 143 boreholes suggests a model accuracy better than 2.5 °C, with 139 considered boreholes within this margin. The statistical approach with a large number of realizations facilitates estimating the probability of permafrost occurrence within a grid cell so that each grid cell can be classified as continuous, discontinuous and sporadic permafrost. At its southern margin in Scandinavia and Russia, the transition zone between permafrost and permafrost-free areas extends over several hundred km width with gradually decreasing permafrost probabilities. The study exemplifies the unexploited potential of remotely sensed data sets in permafrost mapping if they are employed in multi-sensor multi-source data fusion approaches.

Coming in from the cold: potential microbial threats from the terrestrial cryosphere

Edwards, A. (2015). Coming in from the cold: Potential microbial threats from the terrestrial cryosphere. Frontiers in Earth Science, 1-4. [This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.]