CryospherePub Date : 2023-08-31DOI: 10.5194/tc-17-3695-2023
Ellen M. Buckley, S. Farrell, U. Herzfeld, M. Webster, T. Trantow, O. Baney, K. Duncan, Huiling Han, M. Lawson
{"title":"Observing the evolution of summer melt on multiyear sea ice with ICESat-2 and Sentinel-2","authors":"Ellen M. Buckley, S. Farrell, U. Herzfeld, M. Webster, T. Trantow, O. Baney, K. Duncan, Huiling Han, M. Lawson","doi":"10.5194/tc-17-3695-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3695-2023","url":null,"abstract":"Abstract. We investigate sea ice conditions during the 2020 melt season, when warm air temperature anomalies in spring led to early melt onset, an extended melt season, and the second-lowest September minimum Arctic ice extent observed. We focus on the region of the most persistent ice cover and examine melt pond depth retrieved from Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) using two distinct algorithms in concert with a time series of melt pond fraction and ice concentration derived from Sentinel-2 imagery to obtain insights about the melting ice surface in three dimensions. We find the melt pond fraction derived from Sentinel-2 in the study region increased rapidly in June, with the mean melt pond fraction peaking at 16 % ± 6 % on 24 June 2020, followed by a slow decrease to 8 % ± 6 % by 3 July, and remained below 10 % for the remainder of the season through 15 September. Sea ice concentration was consistently high (>95 %) at the beginning of the melt season until 4 July, and as floes disintegrated, it decreased to a minimum of 70 % on 30 July and then became more variable, ranging from 75 % to 90 % for the remainder of the melt season. Pond depth increased steadily from a median depth of 0.40 m ± 0.17 m in early June and peaked at 0.97 m ± 0.51 m on 16 July, even as melt pond fraction had already started to decrease. Our results demonstrate that by combining high-resolution passive and active remote sensing we now have the ability to track evolving melt conditions and observe changes in the sea ice cover throughout the summer season.","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48700667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-28DOI: 10.5194/tc-17-3617-2023
D. Monteiro, S. Morin
{"title":"Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets","authors":"D. Monteiro, S. Morin","doi":"10.5194/tc-17-3617-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3617-2023","url":null,"abstract":"Abstract. Assessing past distributions, variability and trends in the mountain snow cover and its first-order drivers, temperature and precipitation, is key for a wide range of studies and applications.\u0000In this study, we compare the results of various modeling systems (global and regional reanalyses ERA5, ERA5-Land, ERA5-Crocus, CERRA-Land, UERRA MESCAN-SURFEX and MTMSI and regional climate model simulations CNRM-ALADIN and CNRM-AROME driven by the global reanalysis ERA-Interim) against observational references (in situ, gridded observational datasets and satellite observations) across the European Alps from 1950 to 2020. The comparisons are performed in terms of monthly and seasonal snow cover variables (snow depth and snow cover duration) and their main atmospherical drivers (near-surface temperature and precipitation). We assess multi-annual averages of regional and subregional mean values, their interannual variations, and trends over various timescales, mainly for the winter period (from November through April). ERA5, ERA5-Crocus, MESCAN-SURFEX, CERRA-Land and MTMSI offer a satisfying description of the monthly snow evolution. However, a spatial comparison against satellite observation indicates that all datasets overestimate the snow cover duration, especially the melt-out date. CNRM-AROME and CNRM-ALADIN simulations and ERA5-Land exhibit an overestimation of the snow accumulation during winter, increasing with elevations. The analysis of the interannual variability and trends indicates that modeling snow cover dynamics remains complex across multiple scales and that none of the models evaluated here fully succeed to reproduce this compared to observational reference datasets. Indeed, while most of the evaluated model outputs perform well at representing the interannual to multi-decadal winter temperature and precipitation variability, they often fail to address the variability in the snow depth and snow cover duration. We discuss several artifacts potentially responsible for incorrect long-term climate trends in several reanalysis products (ERA5 and MESCAN-SURFEX), which we attribute primarily to the heterogeneities of the observation datasets assimilated. Nevertheless, many of the considered datasets in this study exhibit past trends in line with the current state of knowledge. Based on these datasets, over the last 50 years (1968–2017) at a regional scale, the European Alps have experienced a winter warming of 0.3 to 0.4 ∘C per decade, stronger at lower elevations, and a small reduction in winter precipitation, homogeneous with elevation. The decline in the winter snow depth and snow cover duration ranges from −7 % to −15 % per decade and from −5 to −7 d per decade, respectively, both showing a larger decrease at low and intermediate elevations. Overall, we show that no modeling strategy outperforms all others within our sample and that upstream choices (horizontal resolution, heterogeneity of the observations used for data assimilation ","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44149107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-26DOI: 10.5194/tc-17-3593-2023
Hannah J. Picton, C. Stokes, S. Jamieson, D. Floricioiu, L. Krieger
{"title":"Extensive and anomalous grounding line retreat at Vanderford Glacier, Vincennes Bay, Wilkes Land, East Antarctica","authors":"Hannah J. Picton, C. Stokes, S. Jamieson, D. Floricioiu, L. Krieger","doi":"10.5194/tc-17-3593-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3593-2023","url":null,"abstract":"Abstract. Wilkes Land, East Antarctica, has been losing mass at an accelerating rate over recent decades in response to enhanced oceanic forcing. Overlying the Aurora Subglacial Basin, it has been referred to as the “weak underbelly” of the East Antarctic Ice Sheet and is drained by several major outlet glaciers. Despite their potential importance, few of these glaciers have been studied in detail. This includes the six outlet glaciers which drain into Vincennes Bay, a region recently discovered to have the warmest intrusions of modified Circumpolar Deep Water (mCDW) ever recorded in East Antarctica. Here, we use satellite imagery; differential synthetic aperture radar interferometry (DInSAR); and remotely sensed datasets of ice-surface velocity, ice-surface elevation and grounding line position to investigate ice dynamics between 1963 and 2022. Our results support previous observations of extensive grounding line retreat at Vanderford Glacier, measured at 18.6 km between 1996 and 2020. The persistent grounding line retreat, averaging 0.8 km yr−1, places Vanderford Glacier as the fastest retreating glacier in East Antarctica, and the third fastest in Antarctica, across decadal timescales. Such rapid retreat is consistent with the hypothesis that warm mCDW is able to access deep cavities formed below the Vanderford Ice Shelf, driving high rates of basal melting close to the grounding line. With a retrograde slope observed inland along the Vanderford Trench, such oceanic forcing may have significant implications for the future stability of Vanderford Glacier.","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46974393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-25DOI: 10.5194/tc-17-3553-2023
L. Bouvet, N. Calonne, F. Flin, C. Geindreau
{"title":"Heterogeneous grain growth and vertical mass transfer within a snow layer under a temperature gradient","authors":"L. Bouvet, N. Calonne, F. Flin, C. Geindreau","doi":"10.5194/tc-17-3553-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3553-2023","url":null,"abstract":"Abstract. Inside a snow cover, metamorphism plays a key role in snow evolution at different scales. This study focuses on the impact of temperature gradient metamorphism on a snow layer in its vertical extent. To this end, two cold-laboratory experiments were conducted to monitor a snow layer evolving under a temperature gradient of 100 K m−1 using X-ray tomography and environmental sensors. The first experiment shows that snow evolves differently in the vertical: in the end, coarser depth hoar is found in the center part of the layer, with covariance lengths about 50 % higher compared to the top and bottom areas. We show that this heterogeneous grain growth could be related to the temperature profile, to the associated crystal growth regimes, and to the local vapor supersaturation. In the second experiment, a non-disturbing sampling method was applied to enable a precise observation of the basal mass transfer in the case of dry boundary conditions. An air gap, characterized by a sharp drop in density, developed at the base and reached more than 3 mm after a month. The two reported phenomena, heterogeneous grain growth and basal mass loss, create heterogeneities in snow – in terms of density, grain and pore size, and ice morphology – from an initial homogeneous layer. Finally, we report the formation of hard depth hoar associated with an increase in specific surface area (SSA) observed in the second experiment with higher initial density. These microscale effects may strongly impact the snowpack behavior, e.g., for snow transport processes or snow mechanics.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45586344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-25DOI: 10.5194/tc-17-3575-2023
Yanan Wang, B. Hwang, A. Bateson, Y. Aksenov, C. Horvat
{"title":"Summer sea ice floe perimeter density in the Arctic: high-resolution optical satellite imagery and model evaluation","authors":"Yanan Wang, B. Hwang, A. Bateson, Y. Aksenov, C. Horvat","doi":"10.5194/tc-17-3575-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3575-2023","url":null,"abstract":"Abstract. Size distribution of sea ice floes is an important\u0000component for sea ice thermodynamic and dynamic processes, particularly in\u0000the marginal ice zone. Recently processes related to the floe size\u0000distribution (FSD) have been incorporated into sea ice models, but the\u0000sparsity of existing observations limits the evaluation of FSD models, thus\u0000hindering model improvements. In this study, perimeter density has been\u0000applied to characterise the floe size distribution for evaluating three FSD\u0000models – the Waves-in-Ice module and Power law Floe Size Distribution (WIPoFSD)\u0000model and two branches of a fully prognostic floe size-thickness\u0000distribution model: CPOM-FSD and FSDv2-WAVE. These models are evaluated\u0000against a new FSD dataset derived from high-resolution satellite imagery in\u0000the Arctic. The evaluation shows an overall overestimation of floe perimeter\u0000density by the models against the observations. Comparison of the floe\u0000perimeter density distribution with the observations shows that the models\u0000exhibit a much larger proportion for small floes (radius <10–30 m) but a much smaller proportion for large floes (radius >30–50 m). Observations and the WIPoFSD model both show a negative\u0000correlation between sea ice concentration and the floe perimeter density,\u0000but the two prognostic models (CPOM-FSD and FSDv2-WAVE) show the opposite\u0000pattern. These differences between models and the observations may be\u0000attributed to limitations in the observations (e.g. the image resolution is\u0000not sufficient to detect small floes) or limitations in the model\u0000parameterisations, including the use of a global power-law exponent in the\u0000WIPoFSD model as well as too weak a floe welding and enhanced wave fracture\u0000in the prognostic models.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42170408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-24DOI: 10.5194/tc-17-3535-2023
Monika Pfau, G. Veh, W. Schwanghart
{"title":"Cast shadows reveal changes in glacier surface elevation","authors":"Monika Pfau, G. Veh, W. Schwanghart","doi":"10.5194/tc-17-3535-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3535-2023","url":null,"abstract":"Abstract. Increased rates of glacier retreat and thinning need\u0000accurate local estimates of glacier elevation change to predict future\u0000changes in glacier runoff and their contribution to sea level rise. Glacier\u0000elevation change is typically derived from digital elevation models (DEMs)\u0000tied to surface change analysis from satellite imagery. Yet, the rugged\u0000topography in mountain regions can cast shadows onto glacier surfaces,\u0000making it difficult to detect local glacier elevation changes in remote\u0000areas. A rather untapped resource comprises precise, time-stamped metadata on\u0000the solar position and angle in satellite images. These data are useful for\u0000simulating shadows from a given DEM. Accordingly, any differences in shadow\u0000length between simulated and mapped shadows in satellite images could\u0000indicate a change in glacier elevation relative to the acquisition date of\u0000the DEM. We tested this hypothesis at five selected glaciers with long-term\u0000monitoring programmes. For each glacier, we projected cast shadows onto the\u0000glacier surface from freely available DEMs and compared simulated shadows to\u0000cast shadows mapped from ∼40 years of Landsat images. We\u0000validated the relative differences with geodetic measurements of glacier\u0000elevation change where these shadows occurred. We find that shadow-derived\u0000glacier elevation changes are consistent with independent photogrammetric\u0000and geodetic surveys in shaded areas. Accordingly, a shadow cast on Baltoro\u0000Glacier (the Karakoram, Pakistan) suggests no changes in elevation between 1987\u0000and 2020, while shadows on Great Aletsch Glacier (Switzerland) point to\u0000negative thinning rates of about 1 m yr−1 in our sample. Our estimates\u0000of glacier elevation change are tied to occurrence of mountain shadows and\u0000may help complement field campaigns in regions that are difficult to access.\u0000This information can be vital to quantify possibly varying\u0000elevation-dependent changes in the accumulation or ablation zone of a given\u0000glacier. Shadow-based retrieval of glacier elevation changes hinges on the\u0000precision of the DEM as the geometry of ridges and peaks constrains the\u0000shadow that we cast on the glacier surface. Future generations of DEMs with\u0000higher resolution and accuracy will improve our method, enriching the\u0000toolbox for tracking historical glacier mass balances from satellite and\u0000aerial images.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46068225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-24DOI: 10.5194/tc-17-3505-2023
Brian Groenke, M. Langer, J. Nitzbon, S. Westermann, Guillermo Gallego, J. Boike
{"title":"Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer","authors":"Brian Groenke, M. Langer, J. Nitzbon, S. Westermann, Guillermo Gallego, J. Boike","doi":"10.5194/tc-17-3505-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3505-2023","url":null,"abstract":"Abstract. Long-term measurements of permafrost temperatures do not provide a complete picture of the Arctic subsurface thermal regime. Regions with warmer\u0000permafrost often show little to no long-term change in ground temperature due to the uptake and release of latent heat during freezing and\u0000thawing. Thus, regions where the least warming is observed may also be the most vulnerable to permafrost degradation. Since direct measurements of\u0000ice and liquid water contents in the permafrost layer are not widely available, thermal modeling of the subsurface plays a crucial role in\u0000understanding how permafrost responds to changes in the local energy balance. In this work, we first analyze trends in observed air and permafrost\u0000temperatures at four sites within the continuous permafrost zone, where we find substantial variation in the apparent relationship between long-term\u0000changes in permafrost temperatures (0.02–0.16 K yr−1) and air temperature (0.09–0.11 K yr−1). We then apply recently\u0000developed Bayesian inversion methods to link observed changes in borehole temperatures to unobserved changes in latent heat and active layer\u0000thickness using a transient model of heat conduction with phase change. Our results suggest that the degree to which recent warming trends correlate\u0000with permafrost thaw depends strongly on both soil freezing characteristics and historical climatology. At the warmest site, a 9 m\u0000borehole near Ny-Ålesund, Svalbard, modeled active layer thickness increases by an average of 13 ± 1 cm K−1 rise in mean\u0000annual ground temperature. In stark contrast, modeled rates of thaw at one of the colder sites, a borehole on Samoylov Island in the Lena River\u0000delta, appear far less sensitive to temperature change, with a negligible effect of 1 ± 1 cm K−1. Although our study is limited to\u0000just four sites, the results urge caution in the interpretation and comparison of warming trends in Arctic boreholes, indicating significant\u0000uncertainty in their implications for the current and future thermal state of permafrost.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49470057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-24DOI: 10.5194/tc-17-3485-2023
E. Zhang, G. Catania, D. Trugman
{"title":"AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini","authors":"E. Zhang, G. Catania, D. Trugman","doi":"10.5194/tc-17-3485-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3485-2023","url":null,"abstract":"Abstract. Ice sheet marine margins via outlet glaciers are susceptible to climate change and are expected to respond through retreat, steepening, and acceleration, although with significant spatial heterogeneity. However, research on ice–ocean interactions has continued to rely on decentralized, manual mapping of features at the ice–ocean interface, impeding progress in understanding the response of glaciers and ice sheets to climate change. The proliferation of remote-sensing images lays the foundation for a better understanding of ice–ocean interactions and also necessitates the automation of terminus delineation. While deep learning (DL) techniques have already been applied to automate the terminus delineation, none involve sufficient quality control and automation to enable DL applications to “big data” problems in glaciology. Here, we build on established methods to create a fully automated pipeline for terminus delineation that makes several advances over prior studies. First, we leverage existing manually picked terminus traces (16 440) as training data to significantly improve the generalization of the DL algorithm. Second, we employ a rigorous automated screening module to enhance the data product quality. Third, we perform a thoroughly automated uncertainty quantification on the resulting data. Finally, we automate several steps in the pipeline allowing data to be regularly delivered to public databases with increased frequency. The automation level of our method ensures the sustainability of terminus data production. Altogether, these improvements produce the most complete and high-quality record of terminus data that exists for the Greenland Ice Sheet (GrIS). Our pipeline has successfully picked 278 239 termini for 295 glaciers in Greenland from Landsat 5, 7, 8 and Sentinel-1 and Sentinel-2 images, spanning the period from 1984 to 2021. The pipeline has been tested on glaciers in Greenland with an error of 79 m. The high sampling frequency and the controlled quality of our terminus data will enable better quantification of ice sheet change and model-based parameterizations of ice–ocean interactions.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46563151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-24DOI: 10.5194/tc-17-3461-2023
A. Chung, F. Parrenin, D. Steinhage, R. Mulvaney, C. Martín, M. Cavitte, D. Lilien, V. Helm, Drew Taylor, P. Gogineni, C. Ritz, M. Frezzotti, Charles R. O'Neill, H. Miller, D. Dahl-Jensen, O. Eisen
{"title":"Stagnant ice and age modelling in the Dome C region, Antarctica","authors":"A. Chung, F. Parrenin, D. Steinhage, R. Mulvaney, C. Martín, M. Cavitte, D. Lilien, V. Helm, Drew Taylor, P. Gogineni, C. Ritz, M. Frezzotti, Charles R. O'Neill, H. Miller, D. Dahl-Jensen, O. Eisen","doi":"10.5194/tc-17-3461-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3461-2023","url":null,"abstract":"Abstract. The European Beyond EPICA project aims to extract a continuous ice core of up to 1.5 Ma, with a maximum age density of 20 kyr m−1 at Little Dome C (LDC).\u0000We present a 1D numerical model which calculates the age of the ice around Dome C. The model inverts for basal conditions and accounts either for melting or for a layer of stagnant ice above the bedrock. It is constrained by internal reflecting horizons traced in radargrams and dated using the EPICA Dome C (EDC) ice core age profile. We used three different radar datasets ranging from a 10 000 km2 airborne survey down to 5 km long ground-based radar transects over LDC. We find that stagnant ice exists in many places, including above the LDC relief where the new Beyond EPICA drill site (BELDC) is located. The modelled thickness of this layer of stagnant ice roughly corresponds to the thickness of the basal unit observed in one of the radar surveys and in the autonomous phase-sensitive radio-echo sounder (ApRES) dataset. At BELDC, the modelled stagnant ice thickness is 198±44 m and the modelled oldest age of ice is 1.45±0.16 Ma at a depth of 2494±30 m. This is very similar to all sites situated on the LDC relief, including that of the Million Year Ice Core project being conducted by the Australian Antarctic Division.\u0000The model was also applied to radar data in the area 10–15 km north of EDC (North Patch), where we find either a thin layer of stagnant ice (generally <60 m) or a negligible melt rate (<0.1 mm yr−1). The modelled maximum age at North Patch is over 2 Ma in most places, with ice at 1.5 Ma having a resolution of 9–12 kyr m−1, making it an exciting prospect for a future Oldest Ice drill site.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42337698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CryospherePub Date : 2023-08-23DOI: 10.5194/tc-17-3443-2023
Sheng Fan, D. Prior, B. Pooley, H. Bowman, Lucy Davidson, D. Wallis, S. Piazolo, Chao Qi, D. Goldsby, T. Hager
{"title":"Grain growth of natural and synthetic ice at 0 °C","authors":"Sheng Fan, D. Prior, B. Pooley, H. Bowman, Lucy Davidson, D. Wallis, S. Piazolo, Chao Qi, D. Goldsby, T. Hager","doi":"10.5194/tc-17-3443-2023","DOIUrl":"https://doi.org/10.5194/tc-17-3443-2023","url":null,"abstract":"Abstract. Grain growth can modify the microstructure of natural ice, including the\u0000grain size and crystallographic preferred orientation (CPO). To better\u0000understand grain-growth processes and kinetics, we compared microstructural\u0000data from synthetic and natural ice samples of similar starting grain sizes\u0000that were annealed at the solidus temperature (0 ∘C) for\u0000durations of a few hours to 33 d. The synthetic ice has a homogeneous\u0000initial microstructure characterized by polygonal grains, little\u0000intragranular distortion, few bubbles, and a near-random CPO. The natural\u0000ice samples were subsampled from ice cores acquired from the Priestley\u0000Glacier, Antarctica. This natural ice has a heterogeneous microstructure\u0000characterized by a considerable number of air bubbles, widespread\u0000intragranular distortion, and a CPO. During annealing, the average grain\u0000size of the natural ice barely changes, whereas the average grain size of\u0000the synthetic ice gradually increases. These observations demonstrate that\u0000grain growth in natural ice can be much slower than in synthetic ice and\u0000therefore that the grain-growth law derived from synthetic ice cannot be\u0000directly applied to estimate the grain-size evolution in natural ice with a\u0000different microstructure. The microstructure of natural ice is characterized\u0000by many bubbles that pin grain boundaries. Previous studies suggest that\u0000bubble pinning provides a resisting force that reduces the effective driving\u0000force of grain-boundary migration and is therefore linked to the inhibition\u0000of grain growth observed in natural ice. As annealing progresses, the number\u0000density (number per unit area) of bubbles on grain boundaries in the natural\u0000ice decreases, whilst the number density of bubbles in the grain interiors\u0000increases. This observation indicates that some grain boundaries sweep\u0000through bubbles, which should weaken the pinning effect and thus reduce the\u0000resisting force for grain-boundary migration. Some of the Priestley ice\u0000grains become abnormally large during annealing. We speculate that the\u0000contrast of dislocation density amongst neighbouring grains, which favours\u0000the selected growth of grains with low dislocation densities, and\u0000bubble pinning, which inhibits grain growth, are tightly associated with\u0000abnormal grain growth. The upper 10 m of the Priestley ice core has a weaker\u0000CPO and better-developed second maximum than deeper samples. The similarity\u0000of this difference to the changes observed in annealing experiments suggests\u0000that abnormal grain growth may have occurred in the upper 10 m of the\u0000Priestley Glacier during summer warming.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44962585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}