Recent glacier surface snowpack melt in Novaya Zemlya and Severnaya Zemlya derived from active and passive microwave remote sensing data

The warming rate in the Russian High Arctic (RHA) (36~158˚E, 73~82˚N) is outpacing the pan-Arctic average, and its effect on the small glaciers across this region needs further examination. The temporal variation and spatial distribution of surface melt onset date (MOD) and total melt days (TMD) throughout the Novaya Zemlya (NovZ) and Severnaya Zemlya (SevZ) archipelagoes serve as good indicators of ice mass ablation and glacier response to regional climate change in the RHA. However, due to the harsh environment, long-term glaciological observations are limited, necessitating the application of remotely sensed data to study the surface melt dynamics. The high sensitivity to liquid water and the ability to work without solar illumination and penetrate non-precipitating clouds make microwave remote sensing an ideal tool to detect melt in this region. This work extracts resolution-enhanced passive and active microwave data from different periods and retrieves a decadal melt record for NovZ and SevZ. The high correlation among passive and active data sets instills confidence in the results. The mean MOD is June 20th on SevZ and June 10th on NovZ during the period of 1992-2012. The average TMDs are 47 and 67 days on SevZ and NovZ from 1995 to 2011, respectively. NovZ had large interannual variability in the MOD, but its TMD generally increased. SevZ MOD is found to be positively correlated to local June reanalysis air temperature at 850hPa geopotential height and occurs significantly earlier (~0.73 days/year, p-value \u3c 0.01) from 1992 to 2011. SevZ also experienced a longer TMD trend (~0.75 days/year, p-value \u3c 0.05) from 1995 to 2011. Annual mean TMD on both islands are positively correlated with regional summer mean reanalysis air temperature and negatively correlated to local sea ice extent. These strong correlations might suggest that the Russian High Arctic glaciers are vulnerable to the continuously diminishing sea ice extent, the associated air temperature increase and amplifying positive ice-albedo feedback, which are all projected to continue into the future

Surface melt on the Shackleton Ice Shelf, East Antarctica (2003–2021)

Melt on the surface of Antarctic ice shelves can potentially lead to their disintegration, accelerating the flow of grounded ice to the ocean and raising global sea levels. However, the current understanding of the processes driving surface melt is incomplete, increasing uncertainty in predictions of ice shelf stability and thus of Antarctica's contribution to sea-level rise. Previous studies of surface melt in Antarctica have usually focused on either a process-level understanding of melt through energy-balance investigations or used metrics such as the annual number of melt days to quantify spatiotemporal variability in satellite observations of surface melt. Here, we help bridge the gap between work at these two scales. Using daily passive microwave observations from the AMSR-E and AMSR-2 sensors and the machine learning approach of a self-organising map, we identify nine representative spatial distributions (“patterns”) of surface melt on the Shackleton Ice Shelf in East Antarctica from 2002/03–2020/21. Combined with output from the RACMO2.3p3 regional climate model and surface topography from the REMA digital elevation model, our results point to a significant role for surface air temperatures in controlling the interannual variability in summer melt and also reveal the influence of localised controls on melt. In particular, prolonged melt along the grounding line shows the importance of katabatic winds and surface albedo. Our approach highlights the necessity of understanding both local and large-scale controls on surface melt and demonstrates that self-organising maps can be used to investigate the variability in surface melt on Antarctic ice shelves.</p

Sea-ice surface properties and their impact on the under-ice light field from remote sensing data and in-situ measurements

The surface properties of sea ice dominate many key processes and drive important feedback mechanisms in the polar oceans of both hemispheres. Examining Arctic and Antarctic sea ice, the distinctly different dominant sea-ice and snow properties in spring and summer are apparent. While Arctic sea ice features a seasonal snow cover with widespread surface ponding in summer, a year-round snow cover and strong surface flooding at the snow/ice interface is observed on Antarctic sea ice. However, substantial knowledge gaps exist about the spatial distribution and temporal evolution of these properties, and their impacts on exchange processes across the atmosphere/ocean interface. This thesis aims to overcome these limitations by quantifying the influence of surface properties on the energy and mass budgets in the ice-covered oceans. Remote sensing data and in-situ observations are combined to derive the seasonal cycle of dominant sea-ice surface characteristics, and their relation to the transfer of solar radiation from the atmosphere through snow and sea ice into the upper ocean. This thesis shows that characteristics of the solar radiation under Arctic sea ice can be described directly as a function of sea-ice surface properties as, e.g., sea-ice type and melt pond coverage. Using this parameterization, an Arctic-wide calculation of solar radiation through sea ice identifies the surface melt onset as the main driver of the annual sea-ice mass and energy budgets. In contrast, an analysis of the spring-summer transition of Antarctic sea ice using passive microwave satellite observations indicates widespread diurnal freeze-thaw cycles in the top snow layers. While the associated temporary thawing is identified as the predominant melt process, subsequent continuous melt in deeper snow layers is rarely found on Antarctic sea ice. Instead of directly influencing the snow depth on Antarctic sea ice, these melt processes rather modify the internal stratigraphy and vertical density structure of the snowpack. An additional analysis of satellite scatterometer observations reveals that snow volume loss on Antarctic sea ice is mainly driven by changes in the lower snowpack, due to the widespread presence of sea-ice surface flooding and snow-ice formation prior to changes in the upper snowpack. As a consequence, the largely heterogeneous and metamorphous Antarctic snowpack prevents a direct correlation between surface properties and the respective characteristics of the penetrating solar radiation under the sea ice. However, surface flooding is identified as the key process governing the variability of the under-ice light regime on small scales. Overall, this thesis highlights that the mass and energy budgets of Antarctic sea ice are determined by processes at the snow/ice interface as well as the temporal evolution of physical snowpack properties. These results are in great contrast to presented studies on Arctic sea ice, where seasonally alternating interactions at the atmosphere/snow- or atmosphere/sea-ice interface control both the energy and mass budgets. An improved understanding of the seasonal cycle of dominant sea-ice and snow surface characteristics in the Arctic and Antarctic is crucial for future investigations retrieving sea-ice variables, such as sea-ice thickness and snow depth, from recent microwave satellite observations

Snowmelt detection over the Greenland ice sheet from SSM/I brightness temperature daily variations

We propose a technique for monitoring snowmelt over the Greenland ice sheet between 1992 and 2005 based on the difference between ascending and descending brightness temperatures (DAV) measured either at 19.35- or 37- GHz by the Special Sensor Microwave Imager (SSM/I). Wet snow is detected when both brightness temperatures and DAV values exceed fixed thresholds. Differently from existing techniques, a multi-frequency approach allows detection of wet snow at different depths and intensities, providing a tool for improving climatological and hydrological applications. Air temperature values either recorded by ground based stations or derived from model are used for calibrating and validating the technique. Results are compared with those obtained using backscattering coefficients recorded by the NASA's Quick Scatterometer (QuikSCAT) during an extreme melting event occurring on June 2002. Long-term results show that snowmelt extent has been increasing at a rate of ∼40,000 Km² per year for the past 14 years

Remote sensing of surface melt on Antarctica: opportunities and challenges

Surface melt is an important driver of ice shelf disintegration and its consequent mass loss over the Antarctic Ice Sheet. Monitoring surface melt using satellite remote sensing can enhance our understanding of ice shelf stability. However, the sensors do not measure the actual physical process of surface melt, but rather observe the presence of liquid water. Moreover, the sensor observations are influenced by the sensor characteristics and surface properties. Therefore, large inconsistencies can exist in the derived melt estimates from different sensors. In this study, we apply state-of-the-art melt detection algorithms to four frequently used remote sensing sensors, i.e., two active microwave sensors, which are Advanced Scatterometer (ASCAT) and Sentinel-1, a passive microwave sensor, i.e., Special Sensor Microwave Imager/Sounder (SSMIS), and an optical sensor, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS). We intercompare the melt detection results over the entire Antarctic Ice Sheet and four selected study regions for the melt seasons 2015-2020. Our results show large spatiotemporal differences in detected melt between the sensors, with particular disagreement in blue ice areas, in aquifer regions, and during wintertime surface melt. We discuss that discrepancies between sensors are mainly due to cloud obstruction and polar darkness, frequency-dependent penetration of satellite signals, temporal resolution, and spatial resolution, as well as the applied melt detection methods. Nevertheless, we argue that different sensors can complement each other, enabling improved detection of surface melt over the Antarctic Ice Sheet

Diurnal variations in the UV albedo of arctic snow

The relevance of snow for climate studies is based on its physical properties, such as high surface reflectivity. Surface ultraviolet (UV) albedo is an essential parameter for various applications based on radiative transfer modeling. Here, new continuous measurements of the local UV albedo of natural Arctic snow were made at Sodankylä (67&amp;deg;22&apos;N, 26&amp;deg;39&apos;E, 179 m a.s.l.) during the spring of 2007. The data were logged at 1-min intervals. The accumulation of snow was up to 68 cm. The surface layer thickness varied from 0.5 to 35 cm with the snow grain size between 0.2 and 2.5 mm. The midday erythemally weighted UV albedo ranged from 0.6 to 0.8 in the accumulation period, and from 0.5 to 0.7 during melting. During the snow melt period, under cases of an almost clear sky and variable cloudiness, an unexpected diurnal decrease of 0.05 in albedo soon after midday, and recovery thereafter, was detected. This diurnal decrease in albedo was found to be asymmetric with respect to solar midday, thus indicating a change in the properties of the snow. Independent UV albedo results with two different types of instruments confirm these findings. The measured temperature of the snow surface was below 0&amp;deg;C on the following mornings. Hence, the reversible diurnal change, evident for ~1–2 h, could be explained by the daily metamorphosis of the surface of the snowpack, in which the temperature of the surface increases, melting some of the snow to liquid water, after which the surface freezes again

UV albedo of arctic snow in spring

International audienceThe relevance of snow for climate studies is based on its physical properties, such as high surface reflectivity. Surface ultraviolet (UV) albedo is an essential parameter for various applications based on radiative transfer modeling. Here, new continuous measurements of the local UV albedo of natural Arctic snow were made at Sodankylä (67.37° N, 26.63° E, 179 m a.s.l.) during the spring of 2007. The data were logged at 1-min intervals. The accumulation of snow was up to 68 cm. The surface layer thickness varied from 0.5 to 35 cm with the snow grain size between 0.2 and 2.5 mm. The midday erythemally weighted UV albedo ranged from 0.6 to 0.8 in the accumulation period and 0.5?0.7 during melting. During the snow melt period, under cases of an almost clear sky and variable cloudiness, an unexpected diurnal decrease of 0.05 in albedo soon after midday, and recovery thereafter, was detected. This diurnal decrease in albedo was found to be asymmetric with respect to solar midday, thus indicating a change in the properties of the snow. Independent UV albedo results with two different types of instruments confirm these findings. The measured temperature of the snow surface was below 0°C on the following mornings. Hence, the reversible diurnal change, evident for ~1?2 h, could be explained by the daily metamorphosis of the surface of the snowpack, in which the temperature of the surface increases, melting some of the snow to liquid water, after which the surface freezes again

Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

Télédétection micro-onde de surfaces enneigées en milieu arctique : étude des processus de surface de la calotte glaciaire Barnes, Nunavut, Canada

Résumé : La région de l'archipel canadien, située en Arctique, connaît actuellement d'importants changements climatiques, se traduisant notamment par une augmentation des températures, une réduction de l'étendue de la banquise marine et du couvert nival terrestre ou encore une perte de masse significative des calottes glaciaires disséminées sur les îles de l'archipel. Parmi ces calottes glaciaires, la calotte Barnes, située en Terre de Baffin, ne fait pas exception comme le montrent les observations satellitaires qui témoignent d'une importante perte de masse ainsi que d'une régression de ses marges, sur les dernières décennies. Bien que les calottes glaciaires de l'archipel canadien ne représentent que quelques dizaines de centimètres d'élévation potentielle du niveau des mers, leur perte de masse est une composante non négligeable de l'augmentation actuelle du niveau des mers. Les projections climatiques laissent à penser que cette contribution pourrait rester significative dans les décennies à venir. Cependant, afin d'estimer les évolutions futures de ces calottes glaciaires et leur impact sur le climat ou le niveau des mers, il est nécessaire de caractériser les processus physiques tels que les modifications du bilan de masse de surface. Cette connaissance est actuellement très limitée du fait notamment du sous-échantillonnage des régions arctiques en terme de stations météorologiques permanentes. Une autre particularité de certaines calottes de l'archipel canadien, et de la calotte Barnes en particulier, est de présenter un processus d'accumulation de type glace surimposée, ce phénomène étant à prendre en compte dans l'étude des processus de surface. Pour pallier au manque de données, l'approche retenue a été d'utiliser des données de télédétection, qui offrent l'avantage d'une couverture spatiale globale ainsi qu'une bonne répétitivité temporelle. En particulier les données acquises dans le domaine des micro-ondes passives sont d'un grand intérêt pour l'étude de surfaces enneigées. En complément de ces données, la modélisation du manteau neigeux, tant d'un point de vue des processus physiques que de l'émission électromagnétique permet d'avoir accès à une compréhension fine des processus de surface tels que l'accumulation de la neige, la fonte, les transferts d'énergie et de matière à la surface, etc. Ces différents termes sont regroupés sous la notion de bilan de masse de surface. L'ensemble du travail présenté dans ce manuscrit a donc consisté à développer des outils permettant d'améliorer la connaissance des processus de surface des calottes glaciaires du type de celles que l'on rencontre dans l'archipel canadien, l'ensemble du développement méthodologique ayant été réalisé sur la calotte Barnes à l'aide du schéma de surface SURFEX-CROCUS pour la modélisation physique et du modèle DMRT-ML pour la partie électromagnétique. Les résultats ont tout d'abord permis de mettre en évidence une augmentation significative de la durée de fonte de surface sur la calotte Barnes (augmentation de plus de 30% sur la période 1979-2010), mais aussi sur la calotte Penny, elle aussi située en Terre de Baffin et qui présente la même tendance (augmentation de l'ordre de 50% sur la même période). Ensuite, l'application d'une chaîne de modélisation physique contrainte par diverses données de télédétection a permis de modéliser de manière réaliste le bilan de masse de surface de la dernière décennie, qui est de +6,8 cm/an en moyenne sur la zone sommitale de la calotte, qui est une zone d'accumulation. Enfin, des tests de sensibilité climatique sur ce bilan de masse ont permis de mettre en évidence un seuil à partir duquel cette calotte voit disparaître sa zone d'accumulation. Les modélisations effectuées suggèrent que ce seuil a de fortes chances d'être atteint très prochainement, pour une augmentation de température moyenne inférieure à 1°C, ce qui aurait pour conséquence une accélération de la perte de masse de la calotte. // Abstract : Significant climate change is curently monitored in the Arctic, and especially in the region of the canadian arctic archipellago. This climate warming leads to recession of seaice extent and seasonnal snow cover, and also to large mass loss of the archipellago’s ice caps. One of the most southern ice cap, the Barnes Ice Cap, located on the Baffin Island, is no exception to significant mass loss and margins recession as satellite observations exhibited over the last decades. Despite the relative low sea level potential of the small ice caps located in the canadian arctic achipellago in regards to major ice sheets, Antarctica and Greenland, their contribution to the current sea level rise is significant. Climate projections show that this contribution could accelerate significant over the next decades. However, to estimate the future evolution of these ice caps and their impact on climate or sea level rise, a better characterisation of the surface processes such as the evolution of the surface mass balance is needed. This knowledge is currently very limited, mainly due to the sparse covering of automatic weather stations or in-situ measurements over the Arctic. Furthermore, several ice caps, among with the Barnes Ice Cap, present a superimposed ice accumulation area which particularities have to be taken into account in the surface processes studies. Given the lack of in-situ data, the approach choosen in this work is to use remote sensing data, that have the advantage to offer a good spatial and temporal coverage. In particular, passive microwave data are very suitable for snowy surfaces studies. To complement these data, physical and electromagnetic snowpack modeling provide a fine characterisation of surface processes such as snow accumulation. The whole work presented in this manuscript thus consisted in developping specific tools to improve the understanding of surface processes of small arctic ice caps. This methodological development was performed and applied on the Barnes Ice Cap using the surface scheme SURFEX-CROCUS and the electromagnetic model DMRT-ML. First results highlight a significant increase in surface melt duration over the past 3 decades on the Barnes Ice Cap (increase of more than 30% over 1979-2010 period). A similar trend is also monitored over the Penny Ice Cap, located in the south part of the Baffin Island (increase of more than 50% over the same period). Then, the surface mass balance over the last decade was modeled by using a physical based modeling chain constrained by remote sensing data. The results give a mean net accumulation of +6,8 cm y−1 on the summit area of the ice cap. Finaly, sensitivity tests, performed to investigate the climatic sensitivity of the surface mass balance, highlight a threshold effect that may lead to a complete disapearence of the accumulation area of the Barnes Ice Cap. With a temperature increase less than 1°C, modeling results suggest it is likely that the threshold will be reached rapidly leading to an increase in mass loss from the ice cap