Ellen M. Buckley, S. Farrell, U. Herzfeld, M. Webster, T. Trantow, O. Baney, K. Duncan, Huiling Han, M. Lawson
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.
{"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}
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. In 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
{"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}
Hannah J. Picton, C. Stokes, S. Jamieson, D. Floricioiu, L. Krieger
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.
{"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}
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.
摘要在积雪内部，变质作用在不同尺度的积雪演化中起着关键作用。本文研究了温度梯度变质作用对雪层垂直范围的影响。为此，利用x射线断层扫描和环境传感器进行了两个冷室实验，以监测在100 K m−1温度梯度下雪层的演变。第一个实验表明，雪在垂直方向上的演变是不同的:最后，在层的中心部分发现较粗的深度灰，协方差长度比顶部和底部区域高约50%。我们发现，这种非均匀晶粒生长可能与温度分布、相关的晶体生长机制和局部蒸汽过饱和有关。在第二个实验中，采用了一种非干扰采样方法，以便在干边界条件下精确观察基础传质。一个以密度急剧下降为特征的气隙在底部形成，一个月后达到3毫米以上。报道的两种现象，非均匀颗粒生长和基础质量损失，在密度、颗粒和孔隙大小以及冰形态方面，从最初的均匀层产生了雪的非均匀性。最后，我们报告了在初始密度较高的第二次实验中观察到的与比表面积(SSA)增加相关的硬深度灰的形成。这些微观效应可能会强烈影响积雪行为，例如雪的运输过程或雪的力学。
{"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}
Yanan Wang, B. Hwang, A. Bateson, Y. Aksenov, C. Horvat
Abstract. Size distribution of sea ice floes is an important component for sea ice thermodynamic and dynamic processes, particularly in the marginal ice zone. Recently processes related to the floe size distribution (FSD) have been incorporated into sea ice models, but the sparsity of existing observations limits the evaluation of FSD models, thus hindering model improvements. In this study, perimeter density has been applied to characterise the floe size distribution for evaluating three FSD models – the Waves-in-Ice module and Power law Floe Size Distribution (WIPoFSD) model and two branches of a fully prognostic floe size-thickness distribution model: CPOM-FSD and FSDv2-WAVE. These models are evaluated against a new FSD dataset derived from high-resolution satellite imagery in the Arctic. The evaluation shows an overall overestimation of floe perimeter density by the models against the observations. Comparison of the floe perimeter density distribution with the observations shows that the models exhibit 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 correlation between sea ice concentration and the floe perimeter density, but the two prognostic models (CPOM-FSD and FSDv2-WAVE) show the opposite pattern. These differences between models and the observations may be attributed to limitations in the observations (e.g. the image resolution is not sufficient to detect small floes) or limitations in the model parameterisations, including the use of a global power-law exponent in the WIPoFSD model as well as too weak a floe welding and enhanced wave fracture in the prognostic models.
{"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}
Abstract. Increased rates of glacier retreat and thinning need accurate local estimates of glacier elevation change to predict future changes in glacier runoff and their contribution to sea level rise. Glacier elevation change is typically derived from digital elevation models (DEMs) tied to surface change analysis from satellite imagery. Yet, the rugged topography in mountain regions can cast shadows onto glacier surfaces, making it difficult to detect local glacier elevation changes in remote areas. A rather untapped resource comprises precise, time-stamped metadata on the solar position and angle in satellite images. These data are useful for simulating shadows from a given DEM. Accordingly, any differences in shadow length between simulated and mapped shadows in satellite images could indicate a change in glacier elevation relative to the acquisition date of the DEM. We tested this hypothesis at five selected glaciers with long-term monitoring programmes. For each glacier, we projected cast shadows onto the glacier surface from freely available DEMs and compared simulated shadows to cast shadows mapped from ∼40 years of Landsat images. We validated the relative differences with geodetic measurements of glacier elevation change where these shadows occurred. We find that shadow-derived glacier elevation changes are consistent with independent photogrammetric and geodetic surveys in shaded areas. Accordingly, a shadow cast on Baltoro Glacier (the Karakoram, Pakistan) suggests no changes in elevation between 1987 and 2020, while shadows on Great Aletsch Glacier (Switzerland) point to negative thinning rates of about 1 m yr−1 in our sample. Our estimates of glacier elevation change are tied to occurrence of mountain shadows and may help complement field campaigns in regions that are difficult to access. This information can be vital to quantify possibly varying elevation-dependent changes in the accumulation or ablation zone of a given glacier. Shadow-based retrieval of glacier elevation changes hinges on the precision of the DEM as the geometry of ridges and peaks constrains the shadow that we cast on the glacier surface. Future generations of DEMs with higher resolution and accuracy will improve our method, enriching the toolbox for tracking historical glacier mass balances from satellite and aerial images.
{"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}
Brian Groenke, M. Langer, J. Nitzbon, S. Westermann, Guillermo Gallego, J. Boike
Abstract. Long-term measurements of permafrost temperatures do not provide a complete picture of the Arctic subsurface thermal regime. Regions with warmer permafrost often show little to no long-term change in ground temperature due to the uptake and release of latent heat during freezing and thawing. Thus, regions where the least warming is observed may also be the most vulnerable to permafrost degradation. Since direct measurements of ice and liquid water contents in the permafrost layer are not widely available, thermal modeling of the subsurface plays a crucial role in understanding how permafrost responds to changes in the local energy balance. In this work, we first analyze trends in observed air and permafrost temperatures at four sites within the continuous permafrost zone, where we find substantial variation in the apparent relationship between long-term changes in permafrost temperatures (0.02–0.16 K yr−1) and air temperature (0.09–0.11 K yr−1). We then apply recently developed Bayesian inversion methods to link observed changes in borehole temperatures to unobserved changes in latent heat and active layer thickness using a transient model of heat conduction with phase change. Our results suggest that the degree to which recent warming trends correlate with permafrost thaw depends strongly on both soil freezing characteristics and historical climatology. At the warmest site, a 9 m borehole near Ny-Ålesund, Svalbard, modeled active layer thickness increases by an average of 13 ± 1 cm K−1 rise in mean annual ground temperature. In stark contrast, modeled rates of thaw at one of the colder sites, a borehole on Samoylov Island in the Lena River delta, appear far less sensitive to temperature change, with a negligible effect of 1 ± 1 cm K−1. Although our study is limited to just four sites, the results urge caution in the interpretation and comparison of warming trends in Arctic boreholes, indicating significant uncertainty in their implications for the current and future thermal state of permafrost.
摘要对永久冻土温度的长期测量并不能提供北极地下热状况的完整情况。由于冷冻和解冻过程中潜热的吸收和释放，具有温暖永久冻土的地区通常表现出很少或没有长期的地面温度变化。因此，观测到的变暖最少的地区也可能最容易受到永久冻土退化的影响。由于对永久冻土层中的冰和液态水含量的直接测量还不广泛，地下的热建模在理解永久冻土如何应对当地能量平衡的变化方面发挥着至关重要的作用。在这项工作中，我们首先分析了连续多年冻土带内四个地点观测到的空气和永久冻土温度的趋势，在那里我们发现永久冻土温度长期变化之间的明显关系有很大变化（0.02–0.16 K yr−1）和空气温度（0.09–0.11 K 年-1）。然后，我们应用最近开发的贝叶斯反演方法，使用具有相变的热传导瞬态模型，将观测到的钻孔温度变化与未观测到的潜热和活动层厚度变化联系起来。我们的研究结果表明，最近的变暖趋势与永久冻土融化的相关性在很大程度上取决于土壤冻结特征和历史气候学。在最热的地点 斯瓦尔巴群岛Ny-Ålesund附近的mborehole，模拟的活性层厚度平均增加了13 ± 1. 厘米 年平均地面温度上升K−1。与此形成鲜明对比的是，在其中一个较冷的地点，Lena河三角洲Samoylov岛上的一个钻孔，模拟的解冻率似乎对温度变化的敏感性要低得多，其影响可以忽略不计 ± 1. 厘米 K−1。尽管我们的研究仅限于四个地点，但研究结果敦促在解释和比较北极钻孔的变暖趋势时保持谨慎，这表明它们对永久冻土当前和未来的热状态的影响具有重要意义。
{"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}
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.
{"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}
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
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). We 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. The 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.
摘要欧洲Beyond EPICA项目旨在在Little Dome C (LDC)提取高达1.5 Ma的连续冰芯，最大年龄密度为20 kyr m - 1。我们提出了一个一维数值模型来计算c丘周围冰的年龄。该模型对基础条件进行了反演，并考虑了基岩上方的融化或停滞冰层。它受到内部反射层线图的限制，并使用EPICA Dome C (EDC)冰芯年龄剖面进行测定。我们使用了三种不同的雷达数据集，范围从1万平方公里的航空测量到LDC上空5公里长的地面雷达样带。我们发现在许多地方都存在滞冰，包括在新的Beyond EPICA钻探点(BELDC)所在的最不发达地区上方。该滞冰层的模拟厚度大致与雷达测量和自主相敏无线电回声测深(ApRES)数据集中观测到的基本单位厚度相对应。在BELDC，模拟的停滞冰厚度为198±44 m，模拟的最老冰年龄为1.45±0.16 Ma，深度为2494±30 m。这与位于最不发达国家地形上的所有地点非常相似，包括澳大利亚南极司正在进行的百万年冰芯项目的地点。该模型还应用于EDC (north Patch)以北10-15公里地区的雷达数据，在那里我们发现一层薄薄的停滞冰(通常<60 m)或可以忽略不计的融化速率(<0.1 mm yr - 1)。在北斑的大部分地方，模拟的最大年龄超过2 Ma, 1.5 Ma的冰的分辨率为9-12 kyr m - 1，这使它成为未来最古老冰钻探地点的一个令人兴奋的前景。
{"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}
Sheng Fan, D. Prior, B. Pooley, H. Bowman, Lucy Davidson, D. Wallis, S. Piazolo, Chao Qi, D. Goldsby, T. Hager
Abstract. Grain growth can modify the microstructure of natural ice, including the grain size and crystallographic preferred orientation (CPO). To better understand grain-growth processes and kinetics, we compared microstructural data from synthetic and natural ice samples of similar starting grain sizes that were annealed at the solidus temperature (0 ∘C) for durations of a few hours to 33 d. The synthetic ice has a homogeneous initial microstructure characterized by polygonal grains, little intragranular distortion, few bubbles, and a near-random CPO. The natural ice samples were subsampled from ice cores acquired from the Priestley Glacier, Antarctica. This natural ice has a heterogeneous microstructure characterized by a considerable number of air bubbles, widespread intragranular distortion, and a CPO. During annealing, the average grain size of the natural ice barely changes, whereas the average grain size of the synthetic ice gradually increases. These observations demonstrate that grain growth in natural ice can be much slower than in synthetic ice and therefore that the grain-growth law derived from synthetic ice cannot be directly applied to estimate the grain-size evolution in natural ice with a different microstructure. The microstructure of natural ice is characterized by many bubbles that pin grain boundaries. Previous studies suggest that bubble pinning provides a resisting force that reduces the effective driving force of grain-boundary migration and is therefore linked to the inhibition of grain growth observed in natural ice. As annealing progresses, the number density (number per unit area) of bubbles on grain boundaries in the natural ice decreases, whilst the number density of bubbles in the grain interiors increases. This observation indicates that some grain boundaries sweep through bubbles, which should weaken the pinning effect and thus reduce the resisting force for grain-boundary migration. Some of the Priestley ice grains become abnormally large during annealing. We speculate that the contrast of dislocation density amongst neighbouring grains, which favours the selected growth of grains with low dislocation densities, and bubble pinning, which inhibits grain growth, are tightly associated with abnormal grain growth. The upper 10 m of the Priestley ice core has a weaker CPO and better-developed second maximum than deeper samples. The similarity of this difference to the changes observed in annealing experiments suggests that abnormal grain growth may have occurred in the upper 10 m of the Priestley Glacier during summer warming.
{"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}
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