Abstract. In studying the mass balance of polar ice sheets, fluctuations in firn density near the surface is a major uncertainty. In this paper, we explore these variations at locations on the Greenland Ice Sheet and at the Dome C location in Antarctica. Borehole in situ measurements, snow radar echoes, microwave brightness temperatures, and modeling results from the Community Firn Model (CFM) are used. It is shown that firn density profiles can be represented using three processes: “long-scale” and “short-scale” density variations and “refrozen layers”. Consistency with this description is observed in the dynamic range of airborne 0.5–2 GHz brightness temperatures and snow radar echo peaks in measurements performed in Greenland in 2017. Based on these insights, a new analytical partially coherent model is implemented to explain the microwave brightness temperatures using the three-scale description of the firn. Short- and long-scale firn processes are modeled as a 3D continuous random medium with finite vertical and horizontal correlation lengths as opposed to past 1D randomly layered medium descriptions. Refrozen layers are described as deterministic sheets with planar interfaces, with the number of refrozen-layer interfaces determined by radar observations. Firn density and correlation length parameters used in forward modeling to match measured 0.5–2 GHz brightness temperatures in Greenland show consistency with similar parameters in CFM predictions. Model predictions also are in good agreement with multi-angle 1.4 GHz vertically and horizontally polarized brightness temperature measured by the Soil Moisture and Ocean Salinity (SMOS) satellite at Dome C, Antarctica. This work shows that co-located active and passive microwave measurements can be used to infer polar firn properties that can be compared with predictions of the CFM. In particular, 0.5–2 GHz brightness temperature measurements are shown to be sensitive to long-scale firn density fluctuations with density standard deviations in the range of 0.01–0.06 g cm−3 and vertical correlation lengths of 6–20 cm.
摘要在研究极地冰盖的质量平衡时，地表附近冷杉密度的波动是一个主要的不确定性。在这篇论文中，我们探索了格陵兰冰盖和南极洲圆顶C位置的这些变化。钻孔现场测量、雪雷达回波、微波亮度温度以及社区冷杉模型（CFM）的建模结果均已使用。研究表明，冷杉密度剖面可以用三个过程来表示：“长尺度”和“短尺度”密度变化以及“再冻结层”。在空中0.5–2的动态范围内观察到与该描述一致 2017年在格陵兰岛进行的测量中，GHz亮度温度和雪雷达回波峰值。基于这些见解，使用firn的三尺度描述，实现了一个新的分析部分相干模型来解释微波亮度温度。与过去的1D随机分层介质描述相反，短尺度和长尺度firn过程被建模为具有有限垂直和水平相关长度的3D连续随机介质。再冻结层被描述为具有平面界面的确定性薄片，再冻结层界面的数量由雷达观测确定。正向建模中使用的Firn密度和相关长度参数与测量的0.5–2相匹配 格陵兰岛的GHz亮度温度与CFM预测中的类似参数一致。模型预测也与多角度1.4非常一致 由南极圆顶C的土壤湿度和海洋盐度（SMOS）卫星测量的GHz垂直和水平偏振亮度温度。这项工作表明，位于同一位置的有源和无源微波测量可以用来推断极性firn特性，这些特性可以与CFM的预测进行比较。特别是0.5–2 GHz亮度温度测量对长尺度firn密度波动敏感，密度标准偏差在0.01–0.06范围内 g cm−3，垂直相关长度为6–20 厘米
{"title":"Polar firn properties in Greenland and Antarctica and related effects on microwave brightness temperatures","authors":"Haokui, Xu, Brooke, Medley, Leung, Tsang, Joel, T., Johnson, Kenneth, C., Jezek, Macro Brogioni, L. Kaleschke","doi":"10.5194/tc-17-2793-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2793-2023","url":null,"abstract":"Abstract. In studying the mass balance of polar ice sheets, fluctuations in firn density near the surface is a major uncertainty. In this paper, we explore these variations at locations on the Greenland Ice Sheet and at the Dome C location in Antarctica. Borehole in situ measurements, snow radar echoes, microwave brightness temperatures, and modeling results from the Community Firn Model (CFM) are used. It is shown that firn density profiles can be represented using three processes: “long-scale” and “short-scale” density variations and “refrozen layers”. Consistency with this description is observed in the dynamic range of airborne 0.5–2 GHz brightness temperatures and snow radar echo peaks in measurements performed in Greenland in 2017. Based on these insights, a new analytical partially coherent model is implemented to explain the microwave brightness temperatures using the three-scale description of the firn. Short- and long-scale firn processes are modeled as a 3D continuous random medium with finite vertical and horizontal correlation lengths as opposed to past 1D randomly layered medium descriptions. Refrozen layers are described as deterministic sheets with planar interfaces, with the number of refrozen-layer interfaces determined by radar observations. Firn density and correlation length parameters used in forward modeling to match measured 0.5–2 GHz brightness temperatures in Greenland show consistency with similar parameters in CFM predictions. Model predictions also are in good agreement with multi-angle 1.4 GHz vertically and horizontally polarized brightness temperature measured by the Soil Moisture and Ocean Salinity (SMOS) satellite at Dome C, Antarctica. This work shows that co-located active and passive microwave measurements can be used to infer polar firn properties that can be compared with predictions of the CFM. In particular, 0.5–2 GHz brightness temperature measurements are shown to be sensitive to long-scale firn density fluctuations with density standard deviations in the range of 0.01–0.06 g cm−3 and vertical correlation lengths of 6–20 cm.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42460978","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. Glacier mass balance is typically estimated using a range of in situ measurements, remote sensing measurements, and physical and temperature index modelling techniques. With improved data collection and access to large datasets, data-driven techniques have recently gained prominence in modelling natural processes. The most common data-driven techniques used today are linear regression models and, to some extent, non-linear machine learning models such as artificial neural networks. However, the entire host of capabilities of machine learning modelling has not been applied to glacier mass balance modelling. This study used monthly meteorological data from ERA5-Land to drive four machine learning models: random forest (ensemble tree type), gradient-boosted regressor (ensemble tree type), support vector machine (kernel type), and artificial neural networks (neural type). We also use ordinary least squares linear regression as a baseline model against which to compare the performance of the machine learning models. Further, we assess the requirement of data for each of the models and the requirement for hyperparameter tuning. Finally, the importance of each meteorological variable in the mass balance estimation for each of the models is estimated using permutation importance. All machine learning models outperform the linear regression model. The neural network model depicted a low bias, suggesting the possibility of enhanced results in the event of biased input data. However, the ensemble tree-based models, random forest and gradient-boosted regressor, outperformed all other models in terms of the evaluation metrics and interpretability of the meteorological variables. The gradient-boosted regression model depicted the best coefficient of determination value of 0.713 and a root mean squared error of 1.071 m w.e. The feature importance values associated with all machine learning models suggested a high importance of meteorological variables associated with ablation. This is in line with predominantly negative mass balance observations. We conclude that machine learning techniques are promising in estimating glacier mass balance and can incorporate information from more significant meteorological variables as opposed to a simplified set of variables used in temperature index models.
摘要冰川质量平衡通常使用一系列现场测量、遥感测量以及物理和温度指数建模技术来估计。随着数据收集和大型数据集访问的改进，数据驱动技术最近在自然过程建模方面变得突出。今天使用的最常见的数据驱动技术是线性回归模型，在某种程度上，还有非线性机器学习模型，如人工神经网络。然而，机器学习建模的全部能力尚未应用于冰川质量平衡建模。本研究使用ERA5 Land的月度气象数据驱动了四个机器学习模型：随机森林（集合树类型）、梯度增强回归器（集合树型）、支持向量机（核型）和人工神经网络（神经型）。我们还使用普通最小二乘线性回归作为基线模型来比较机器学习模型的性能。此外，我们评估了每个模型的数据需求和超参数调整的需求。最后，使用排列重要性来估计每个模型的质量平衡估计中每个气象变量的重要性。所有的机器学习模型都优于线性回归模型。神经网络模型描述了低偏差，表明在输入数据有偏差的情况下，结果可能会增强。然而，基于集合树的模型，随机森林和梯度增强回归器，在评估指标和气象变量的可解释性方面优于所有其他模型。梯度增强回归模型的最佳决定系数为0.713，均方根误差为1.071 m w.e.与所有机器学习模型相关的特征重要性值表明与消融相关的气象变量具有高度重要性。这与主要的负质量平衡观测结果一致。我们得出的结论是，机器学习技术在估计冰川质量平衡方面很有前景，并且可以结合来自更重要的气象变量的信息，而不是温度指数模型中使用的一组简化变量。
{"title":"Modelling point mass balance for the glaciers of the Central European Alps using machine learning techniques","authors":"Ritu Anilkumar, R. Bharti, D. Chutia, S. Aggarwal","doi":"10.5194/tc-17-2811-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2811-2023","url":null,"abstract":"Abstract. Glacier mass balance is typically estimated using a range of in situ measurements, remote sensing measurements, and physical and temperature index modelling techniques. With improved data collection and access to large datasets, data-driven techniques have recently gained prominence in modelling natural processes. The most common data-driven techniques used today are linear regression models and, to some extent, non-linear machine learning models such as artificial neural networks. However, the entire host of capabilities of machine learning modelling has not been applied to glacier mass balance modelling. This study used monthly meteorological data from ERA5-Land to drive four machine learning models: random forest (ensemble tree type), gradient-boosted regressor (ensemble tree type), support vector machine (kernel type), and artificial neural networks (neural type). We also use ordinary least squares linear regression as a baseline model against which to compare the performance of the machine learning models. Further, we assess the requirement of data for each of the models and the requirement for hyperparameter tuning. Finally, the importance of each meteorological variable in the mass balance estimation for each of the models is estimated using permutation importance. All machine learning models outperform the linear regression model. The neural network model depicted a low bias, suggesting the possibility of enhanced results in the event of biased input data. However, the ensemble tree-based models, random forest and gradient-boosted regressor, outperformed all other models in terms of the evaluation metrics and interpretability of the meteorological variables. The gradient-boosted regression model depicted the best coefficient of determination value of 0.713 and a root mean squared error of 1.071 m w.e. The feature importance values associated with all machine learning models suggested a high importance of meteorological variables associated with ablation. This is in line with predominantly negative mass balance observations. We conclude that machine learning techniques are promising in estimating glacier mass balance and can incorporate information from more significant meteorological variables as opposed to a simplified set of variables used in temperature index models.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48880296","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}
Justyna Czekirda, B. Etzelmüller, S. Westermann, K. Isaksen, F. Magnin
Abstract. The ground thermal regime and permafrost development have an important influence on geomorphological processes in periglacial regions and ultimately landscape development. About 10 % of unstable rock slopes in Norway are potentially underlain by widespread permafrost. Permafrost thaw and degradation may play a role in slope destabilisation, and more knowledge about rock wall permafrost in Norway is needed to investigate possible links between the ground thermal regime, geomorphological activity and natural hazards. We assess spatio-temporal permafrost variations in selected rock walls in Norway over the last 120 years. Ground temperature is modelled using the two-dimensional ground heat flux model CryoGrid 2D along nine profiles crossing instrumented rock walls in Norway. The simulation results show the distribution of permafrost is sporadic to continuous along the modelled profiles. Results suggest that ground temperature at 20 m depth in steep rock faces increased by 0.2 ∘C per decade on average since the 1980s, and rates of change increase with elevation within a single rock wall section. Heat flow direction is primarily vertical within mountains in Norway. Nevertheless, narrow ridges may still be sensitive to even small differences in ground surface temperature and may have horizontal heat fluxes. This study further demonstrates how rock wall temperature increase rates and rock wall permafrost distribution are influenced by factors such as surface air temperature uncertainties; surface offsets arising from the incoming shortwave solar radiation; snow conditions on, above and below rock walls; and rock wall geometry and size together with adjacent blockfield-covered plateaus or glaciers.
{"title":"Post-Little Ice Age rock wall permafrost evolution in Norway","authors":"Justyna Czekirda, B. Etzelmüller, S. Westermann, K. Isaksen, F. Magnin","doi":"10.5194/tc-17-2725-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2725-2023","url":null,"abstract":"Abstract. The ground thermal regime and permafrost development have an important influence on geomorphological processes in periglacial regions and ultimately\u0000landscape development. About 10 % of unstable rock slopes in Norway are potentially underlain by widespread permafrost. Permafrost thaw and\u0000degradation may play a role in slope destabilisation, and more knowledge about rock wall permafrost in Norway is needed to investigate possible links\u0000between the ground thermal regime, geomorphological activity and natural hazards. We assess spatio-temporal permafrost variations in selected rock\u0000walls in Norway over the last 120 years. Ground temperature is modelled using the two-dimensional ground heat flux model CryoGrid 2D along nine\u0000profiles crossing instrumented rock walls in Norway. The simulation results show the distribution of permafrost is sporadic to continuous along the\u0000modelled profiles. Results suggest that ground temperature at 20 m depth in steep rock faces increased by 0.2 ∘C per decade on average\u0000since the 1980s, and rates of change increase with elevation within a single rock wall section. Heat flow direction is primarily vertical within\u0000mountains in Norway. Nevertheless, narrow ridges may still be sensitive to even small differences in ground surface temperature and may have\u0000horizontal heat fluxes. This study further demonstrates how rock wall temperature increase rates and rock wall permafrost distribution are\u0000influenced by factors such as surface air temperature uncertainties; surface offsets arising from the incoming shortwave solar radiation; snow\u0000conditions on, above and below rock walls; and rock wall geometry and size together with adjacent blockfield-covered plateaus or glaciers.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43752463","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}
C. Deschamps-Berger, S. Gascoin, D. Shean, Hannah Besso, Ambroise Guiot, J. López‐Moreno
Abstract. The unprecedented precision of satellite laser altimetry data from the NASA ICESat-2 mission and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystem and water resource monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for 3 years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) offers a poor temporal and spatial coverage, limiting its potential utility. However, using a digital terrain model from airborne lidar surveys as the snow-off elevation source yielded a snow depth accuracy of ∼ 0.2 m (bias) and precision of ∼ 1 m (random error) across the basin, with an improved precision of 0.5 m for low slopes (< 10∘), compared to eight reference airborne lidar snow depth maps. Snow depths derived from ICESat-2 ATL06 and a satellite photogrammetry digital elevation model have a larger bias and reduced precision, partly induced by increased errors in forested areas. These various combinations of repeated ICESat-2 snow surface elevation measurements with satellite or airborne products will enable tailored approaches to map snow depth and estimate water resource availability in mountainous areas with limited snow depth observations.
{"title":"Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data","authors":"C. Deschamps-Berger, S. Gascoin, D. Shean, Hannah Besso, Ambroise Guiot, J. López‐Moreno","doi":"10.5194/tc-17-2779-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2779-2023","url":null,"abstract":"Abstract. The unprecedented precision of satellite laser altimetry data from the NASA ICESat-2 mission and the increasing availability of high-resolution\u0000elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystem and water resource monitoring. We\u0000retrieved snow depth over the upper Tuolumne basin (California, USA) for 3 years by differencing ICESat-2 ATL06 snow-on elevations and various\u0000snow-off digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) offers a poor temporal and spatial coverage,\u0000limiting its potential utility. However, using a digital terrain model from airborne lidar surveys as the snow-off elevation source yielded a snow depth\u0000accuracy of ∼ 0.2 m (bias) and precision of ∼ 1 m (random error) across the basin, with an improved precision\u0000of 0.5 m for low slopes (< 10∘), compared to eight reference airborne lidar snow depth maps. Snow depths derived from ICESat-2\u0000ATL06 and a satellite photogrammetry digital elevation model have a larger bias and reduced precision, partly induced by increased errors in\u0000forested areas. These various combinations of repeated ICESat-2 snow surface elevation measurements with satellite or airborne products will enable\u0000tailored approaches to map snow depth and estimate water resource availability in mountainous areas with limited snow depth observations.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44574281","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. Vertical shear is recognized today as a key component of the stress balance of ice shelves. However, the first ice shelf models were built on the neglect of vertical shear. Partly due to its historical treatment, it remains common to discuss vertical shear as though it were still considered negligible in ice shelf models. Here, we offer a historical perspective on the changing treatment of vertical shear over time, and we emphasize the term's non-negligibility in current ice shelf modeling. We illustrate our discussion in the simplest context of an analytic, isothermal, shallow-ice-shelf model.
{"title":"Brief communication: Is vertical shear in an ice shelf (still) negligible?","authors":"C. Miele, T. Bartholomaus, E. Enderlin","doi":"10.5194/tc-17-2701-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2701-2023","url":null,"abstract":"Abstract. Vertical shear is recognized today as a key component of the stress balance of ice shelves. However, the first ice shelf models were built on the neglect of vertical shear. Partly due to its historical treatment, it remains common to discuss vertical shear as though it were still considered negligible in ice shelf models. Here, we offer a historical perspective on the changing treatment of vertical shear over time, and we emphasize the term's non-negligibility in current ice shelf modeling. We illustrate our discussion in the simplest context of an analytic, isothermal, shallow-ice-shelf model.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42882766","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}
N. Raoult, S. Charbit, C. Dumas, F. Maignan, C. Ottlé, V. Bastrikov
Abstract. Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000–2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model–data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model–data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters.
{"title":"Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals","authors":"N. Raoult, S. Charbit, C. Dumas, F. Maignan, C. Ottlé, V. Bastrikov","doi":"10.5194/tc-17-2705-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2705-2023","url":null,"abstract":"Abstract. Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000–2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model–data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model–data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46741346","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}
K. Hogan, K. Warburton, A. Graham, J. Neufeld, D. Hewitt, J. Dowdeswell, R. Larter
Abstract. Improvements in the resolution of sea-floor mapping techniques have revealed extremely regular, sub-metre-scale ridge landforms produced by the tidal flexure of ice-shelf grounding lines as they retreated very rapidly (i.e. at rates of several kilometres per year). Guided by such novel sea-floor observations from Thwaites Glacier, West Antarctica, we present three mathematical models for the formation of these corrugation ridges at a tidally migrating grounding line (that is retreating at a constant rate), where each ridge is formed by either constant till flux to the grounding line, till extrusion from the grounding line, or the resuspension and transport of grains from the grounding-zone bed. We find that both till extrusion (squeezing out till like toothpaste as the ice sheet re-settles on the sea floor) and resuspension and transport of material can qualitatively reproduce regular, delicate ridges at a retreating grounding line, as described by sea-floor observations. By considering the known properties of subglacial sediments, we agree with existing schematic models that the most likely mechanism for ridge formation is till extrusion at each low-tide position, essentially preserving an imprint of the ice-sheet grounding line as it retreated. However, when realistic (shallow) bed slopes are used in the simulations, ridges start to overprint one another, suggesting that, to preserve the regular ridges that have been observed, grounding line retreat rates (driven by dynamic thinning?) may be even higher than previously thought.
{"title":"Towards modelling of corrugation ridges at ice-sheet grounding lines","authors":"K. Hogan, K. Warburton, A. Graham, J. Neufeld, D. Hewitt, J. Dowdeswell, R. Larter","doi":"10.5194/tc-17-2645-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2645-2023","url":null,"abstract":"Abstract. Improvements in the resolution of sea-floor mapping\u0000techniques have revealed extremely regular, sub-metre-scale ridge landforms\u0000produced by the tidal flexure of ice-shelf grounding lines as they retreated\u0000very rapidly (i.e. at rates of several kilometres per year). Guided by such\u0000novel sea-floor observations from Thwaites Glacier, West Antarctica, we\u0000present three mathematical models for the formation of these corrugation\u0000ridges at a tidally migrating grounding line (that is retreating at a\u0000constant rate), where each ridge is formed by either constant till flux to\u0000the grounding line, till extrusion from the grounding line, or the\u0000resuspension and transport of grains from the grounding-zone bed. We find\u0000that both till extrusion (squeezing out till like toothpaste as the ice\u0000sheet re-settles on the sea floor) and resuspension and transport of\u0000material can qualitatively reproduce regular, delicate ridges at a\u0000retreating grounding line, as described by sea-floor observations. By\u0000considering the known properties of subglacial sediments, we agree with\u0000existing schematic models that the most likely mechanism for ridge formation\u0000is till extrusion at each low-tide position, essentially preserving an\u0000imprint of the ice-sheet grounding line as it retreated. However, when\u0000realistic (shallow) bed slopes are used in the simulations, ridges start to\u0000overprint one another, suggesting that, to preserve the regular ridges that\u0000have been observed, grounding line retreat rates (driven by dynamic\u0000thinning?) may be even higher than previously thought.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46220229","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}
Hyein Jeong, A. Turner, A. Roberts, M. Veneziani, S. Price, X. Asay-Davis, Luke P. van Roekel, Wuyin Lin, P. Caldwell, Hyo‐Seok Park, J. Wolfe, A. Mametjanov
Abstract. Antarctic coastal polynyas produce dense shelf water, a primary source of Antarctic Bottom Water that contributes to the global overturning circulation. This paper investigates Antarctic dense water formation in the high-resolution version of the Energy Exascale Earth System Model (E3SM-HR). The model is able to reproduce the main Antarctic coastal polynyas, although the polynyas are smaller in area compared to observations. E3SM-HR also simulates several occurrences of open-ocean polynyas (OOPs) in the Weddell Sea at a higher rate than what the last 50 years of the satellite sea ice observational record suggests, but similarly to other high-resolution Earth system model simulations. Furthermore, the densest water masses in the model are formed within the OOPs rather than on the continental shelf as is typically observed. Biases related to the lack of dense water formation on the continental shelf are associated with overly strong atmospheric polar easterlies, which lead to a strong Antarctic Slope Front and too little exchange between on- and off-continental shelf water masses. Strong polar easterlies also produce excessive southward Ekman transport, causing a build-up of sea ice over the continental shelf and enhanced ice melting in the summer season. This, in turn, produces water masses on the continental shelf that are overly fresh and less dense relative to observations. Our results indicate that high resolution alone is insufficient for models to properly reproduce Antarctic dense water; the large-scale polar atmospheric circulation around Antarctica must also be accurately simulated.
{"title":"Southern Ocean polynyas and dense water formation in a high-resolution, coupled Earth system model","authors":"Hyein Jeong, A. Turner, A. Roberts, M. Veneziani, S. Price, X. Asay-Davis, Luke P. van Roekel, Wuyin Lin, P. Caldwell, Hyo‐Seok Park, J. Wolfe, A. Mametjanov","doi":"10.5194/tc-17-2681-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2681-2023","url":null,"abstract":"Abstract. Antarctic coastal polynyas produce dense shelf water, a primary source of Antarctic Bottom Water that contributes to the global overturning\u0000circulation. This paper investigates Antarctic dense water formation in the high-resolution version of the Energy Exascale Earth System Model\u0000(E3SM-HR). The model is able to reproduce the main Antarctic coastal polynyas, although the polynyas are smaller in area compared to\u0000observations. E3SM-HR also simulates several occurrences of open-ocean polynyas (OOPs) in the Weddell Sea at a higher rate than what the last\u000050 years of the satellite sea ice observational record suggests, but similarly to other high-resolution Earth system model simulations. Furthermore,\u0000the densest water masses in the model are formed within the OOPs rather than on the continental shelf as is typically observed. Biases related to\u0000the lack of dense water formation on the continental shelf are associated with overly strong atmospheric polar easterlies, which lead to a strong\u0000Antarctic Slope Front and too little exchange between on- and off-continental shelf water masses. Strong polar easterlies also produce excessive\u0000southward Ekman transport, causing a build-up of sea ice over the continental shelf and enhanced ice melting in the summer season. This, in turn,\u0000produces water masses on the continental shelf that are overly fresh and less dense relative to observations. Our results indicate that high\u0000resolution alone is insufficient for models to properly reproduce Antarctic dense water; the large-scale polar atmospheric circulation around\u0000Antarctica must also be accurately simulated.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43811419","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}
Benjamin Richaud, K. Fennel, E. Oliver, M. DeGrandpre, T. Bourgeois, Xianmin Hu, Youyu Lu
Abstract. The Arctic Ocean is generally undersaturated in CO2 and acts as a net sink of atmospheric CO2. This oceanic uptake is strongly modulated by sea ice, which can prevent air–sea gas exchange and has major impacts on stratification and primary production. Moreover, carbon is stored in sea ice with a ratio of alkalinity to dissolved inorganic carbon that is larger than in seawater. It has been suggested that this storage amplifies the seasonal cycle of seawater pCO2 and leads to an increase in oceanic carbon uptake in seasonally ice-covered regions compared to those that are ice-free. Given the rapidly changing ice scape in the Arctic Ocean, a better understanding of the link between the seasonal cycle of sea ice and oceanic uptake of CO2 is needed. Here, we investigate how the storage of carbon in sea ice affects the air–sea CO2 flux and quantify its dependence on the ratio of alkalinity to inorganic carbon in ice. To this end, we present two independent approaches: a theoretical framework that provides an analytical expression of the amplification of carbon uptake in seasonally ice-covered oceans and a simple parameterization of carbon storage in sea ice implemented in a 1D physical–biogeochemical ocean model. Sensitivity simulations show a linear relation between ice melt and the amplification of seasonal carbon uptake. A 30 % increase in carbon uptake in the Arctic Ocean is estimated compared to ice melt without amplification. Applying this relationship to different future scenarios from an earth system model that does not account for the effect of carbon storage in sea ice suggests that Arctic Ocean carbon uptake is underestimated by 5 % to 15 % in these simulations.
{"title":"Underestimation of oceanic carbon uptake in the Arctic Ocean: ice melt as predictor of the sea ice carbon pump","authors":"Benjamin Richaud, K. Fennel, E. Oliver, M. DeGrandpre, T. Bourgeois, Xianmin Hu, Youyu Lu","doi":"10.5194/tc-17-2665-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2665-2023","url":null,"abstract":"Abstract. The Arctic Ocean is generally undersaturated in CO2 and acts as a net sink of atmospheric CO2. This oceanic uptake is strongly modulated by sea ice, which can prevent air–sea gas exchange and has major impacts on stratification and primary production. Moreover, carbon is stored in sea ice with a ratio of alkalinity to dissolved inorganic carbon that is larger than in seawater. It has been suggested that this storage amplifies the seasonal cycle of seawater pCO2 and leads to an increase in oceanic carbon uptake in seasonally ice-covered regions compared to those that are ice-free. Given the rapidly changing ice scape in the Arctic Ocean, a better understanding of the link between the seasonal cycle of sea ice and oceanic uptake of CO2 is needed. Here, we investigate how the storage of carbon in sea ice affects the air–sea CO2 flux and quantify its dependence on the ratio of alkalinity to inorganic carbon in ice. To this end, we present two independent approaches: a theoretical framework that provides an analytical expression of the amplification of carbon uptake in seasonally ice-covered oceans and a simple parameterization of carbon storage in sea ice implemented in a 1D physical–biogeochemical ocean model. Sensitivity simulations show a linear relation between ice melt and the amplification of seasonal carbon uptake. A 30 % increase in carbon uptake in the Arctic Ocean is estimated compared to ice melt without amplification. Applying this relationship to different future scenarios from an earth system model that does not account for the effect of carbon storage in sea ice suggests that Arctic Ocean carbon uptake is underestimated by 5 % to 15 % in these simulations.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44294675","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}
Edward H. Bair, J. Dozier, K. Rittger, T. Stillinger, W. Kleiber, R. Davis
Abstract. Given the tradeoffs between spatial and temporal resolution, questions about resolution optimality are fundamental to the study of global snow. Answers to these questions will inform future scientific priorities and mission specifications. Heterogeneity of mountain snowpacks drives a need for daily snow cover mapping at the slope scale (≤30 m) that is unmet for a variety of scientific users, ranging from hydrologists to the military to wildlife biologists. But finer spatial resolution usually requires coarser temporal or spectral resolution. Thus, no single sensor can meet all these needs. Recently, constellations of satellites and fusion techniques have made noteworthy progress. The efficacy of two such recent advances is examined: (1) a fused MODIS–Landsat product with daily 30 m spatial resolution and (2) a harmonized Landsat 8 and Sentinel 2A and B (HLS) product with 3–4 d temporal and 30 m spatial resolution. State-of-the-art spectral unmixing techniques are applied to surface reflectance products from 1 and 2 to create snow cover and albedo maps. Then an energy balance model was run to reconstruct snow water equivalent (SWE). For validation, lidar-based Airborne Snow Observatory SWE estimates were used. Results show that reconstructed SWE forced with 30 m resolution snow cover has lower bias, a measure of basin-wide accuracy, than the baseline case using MODIS (463 m cell size) but greater mean absolute error, a measure of per-pixel accuracy. However, the differences in errors may be within uncertainties from scaling artifacts, e.g., basin boundary delineation. Other explanations are (1) the importance of daily acquisitions and (2) the limitations of downscaled forcings for reconstruction. Conclusions are as follows: (1) spectrally unmixed snow cover and snow albedo from MODIS continue to provide accurate forcings for snow models and (2) finer spatial and temporal resolution through sensor design, fusion techniques, and satellite constellations are the future for Earth observations, but existing moderate-resolution sensors still offer value.
{"title":"How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?","authors":"Edward H. Bair, J. Dozier, K. Rittger, T. Stillinger, W. Kleiber, R. Davis","doi":"10.5194/tc-17-2629-2023","DOIUrl":"https://doi.org/10.5194/tc-17-2629-2023","url":null,"abstract":"Abstract. Given the tradeoffs between spatial and temporal resolution, questions about\u0000resolution optimality are fundamental to the study of global snow. Answers\u0000to these questions will inform future scientific priorities and mission\u0000specifications. Heterogeneity of mountain snowpacks drives a need for daily\u0000snow cover mapping at the slope scale (≤30 m) that is unmet for a\u0000variety of scientific users, ranging from hydrologists to the military to\u0000wildlife biologists. But finer spatial resolution usually requires coarser\u0000temporal or spectral resolution. Thus, no single sensor can meet all these\u0000needs. Recently, constellations of satellites and fusion techniques have\u0000made noteworthy progress. The efficacy of two such recent advances is\u0000examined: (1) a fused MODIS–Landsat product with daily 30 m spatial\u0000resolution and (2) a harmonized Landsat 8 and Sentinel 2A and B (HLS) product with\u00003–4 d temporal and 30 m spatial resolution. State-of-the-art spectral unmixing\u0000techniques are applied to surface reflectance products from 1 and 2 to\u0000create snow cover and albedo maps. Then an energy balance model was run to\u0000reconstruct snow water equivalent (SWE). For validation, lidar-based\u0000Airborne Snow Observatory SWE estimates were used. Results show that\u0000reconstructed SWE forced with 30 m resolution snow cover has lower bias, a\u0000measure of basin-wide accuracy, than the baseline case using MODIS (463 m\u0000cell size) but greater mean absolute error, a measure of per-pixel\u0000accuracy. However, the differences in errors may be within uncertainties\u0000from scaling artifacts, e.g., basin boundary delineation. Other explanations\u0000are (1) the importance of daily acquisitions and (2) the limitations of\u0000downscaled forcings for reconstruction. Conclusions are as follows: (1) spectrally\u0000unmixed snow cover and snow albedo from MODIS continue to provide accurate\u0000forcings for snow models and (2) finer spatial and temporal resolution\u0000through sensor design, fusion techniques, and satellite constellations are\u0000the future for Earth observations, but existing moderate-resolution sensors\u0000still offer value.\u0000","PeriodicalId":56315,"journal":{"name":"Cryosphere","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42209943","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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