S. Oveisgharan, Robert Zinke, Zachary Hoppinen, Hans Peter Marshall
Abstract. Snow water equivalent (SWE) is identified as the key element of the snowpack that impacts rivers' streamflow and water cycle. Both active and passive microwave remote sensing methods have been used to retrieve SWE, but there does not currently exist a SWE product that provides useful estimates in mountainous terrain. Active sensors provide higher-resolution observations, but the suitable radar frequencies and temporal repeat intervals have not been available until recently. Interferometric synthetic aperture radar (InSAR) has been shown to have the potential to estimate SWE change. In this study, we apply this technique to a long time series of 6 d temporal repeat Sentinel-1 C-band data from the 2020–2021 winter. The retrievals show statistically significant correlations both temporally and spatially with independent in situ measurements of SWE. The SWE change measurements vary between −5.3 and 9.4 cm over the entire time series and all the in situ stations. The Pearson correlation and RMSE between retrieved SWE change observations and in situ stations measurements are 0.8 and 0.93 cm, respectively. The total retrieved SWE in the entire 2020–2021 time series shows an SWE error of less than 2 cm for the nine in situ stations in the scene. Additionally, the retrieved SWE using Sentinel-1 data is well correlated with lidar snow depth data, with correlation of more than 0.47. Low temporal coherence is identified as the main reason for degrading the performance of SWE retrieval using InSAR data. We also show that the performance of the phase unwrapping algorithm degrades in regions with low temporal coherence. A higher frequency such as L-band improves the temporal coherence and SWE ambiguity. SWE retrieval using C-band Sentinel-1 data is shown to be successful, but faster revisit is required to avoid low temporal coherence. Global SWE retrieval using radar interferometry will have a great opportunity with the upcoming L-band 12 d repeat-pass NASA-ISRO Synthetic Aperture Radar (NISAR) data and the future 6 d repeat-pass Radar Observing System for Europe in L-band (ROSE-L) data.
摘要雪水当量(SWE)被认为是影响河流流量和水循环的关键雪层要素。主动式和被动式微波遥感方法都被用来检索雪水当量,但目前还没有一种雪水当量产品能为山区地形提供有用的估算。有源传感器可提供更高分辨率的观测数据,但直到最近才有合适的雷达频率和时间重复间隔。干涉合成孔径雷达 (InSAR) 已被证明具有估算 SWE 变化的潜力。在本研究中,我们将这一技术应用于 2020-2021 年冬季的 6 天时间重复哨兵-1 C 波段长时间序列数据。检索结果表明,无论从时间上还是从空间上,SWE 都与独立的原地测量值有显著的统计相关性。在整个时间序列和所有原位站中,SWE 变化测量值在 -5.3 到 9.4 厘米之间。检索到的 SWE 变化观测值与原位站测量值之间的皮尔逊相关性和均方根误差分别为 0.8 厘米和 0.93 厘米。在整个 2020-2021 年时间序列中,9 个原地站的 SWE 误差均小于 2 厘米。此外,使用哨兵 1 号数据检索的西南降水量与激光雷达雪深数据相关性良好,相关性超过 0.47。低时间一致性被认为是降低使用 InSAR 数据检索 SWE 性能的主要原因。我们还发现,在低时间相干性区域,相位解包算法的性能也会下降。更高的频率(如 L 波段)可改善时间一致性和 SWE 模糊性。使用 C 波段哨兵-1 数据进行 SWE 检索证明是成功的,但需要更快的重访以避免低时间相干性。即将发布的 L 波段 12 d 重复通量的 NASA-ISRO 合成孔径雷达(NISAR)数据和未来的 L 波段 6 d 重复通量的欧洲雷达观测系统(ROSE-L)数据将为利用雷达干涉测量进行全球 SWE 检索提供绝佳机会。
{"title":"Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry","authors":"S. Oveisgharan, Robert Zinke, Zachary Hoppinen, Hans Peter Marshall","doi":"10.5194/tc-18-559-2024","DOIUrl":"https://doi.org/10.5194/tc-18-559-2024","url":null,"abstract":"Abstract. Snow water equivalent (SWE) is identified as the key element of the snowpack that impacts rivers' streamflow and water cycle. Both active and passive microwave remote sensing methods have been used to retrieve SWE, but there does not currently exist a SWE product that provides useful estimates in mountainous terrain. Active sensors provide higher-resolution observations, but the suitable radar frequencies and temporal repeat intervals have not been available until recently. Interferometric synthetic aperture radar (InSAR) has been shown to have the potential to estimate SWE change. In this study, we apply this technique to a long time series of 6 d temporal repeat Sentinel-1 C-band data from the 2020–2021 winter. The retrievals show statistically significant correlations both temporally and spatially with independent in situ measurements of SWE. The SWE change measurements vary between −5.3 and 9.4 cm over the entire time series and all the in situ stations. The Pearson correlation and RMSE between retrieved SWE change observations and in situ stations measurements are 0.8 and 0.93 cm, respectively. The total retrieved SWE in the entire 2020–2021 time series shows an SWE error of less than 2 cm for the nine in situ stations in the scene. Additionally, the retrieved SWE using Sentinel-1 data is well correlated with lidar snow depth data, with correlation of more than 0.47. Low temporal coherence is identified as the main reason for degrading the performance of SWE retrieval using InSAR data. We also show that the performance of the phase unwrapping algorithm degrades in regions with low temporal coherence. A higher frequency such as L-band improves the temporal coherence and SWE ambiguity. SWE retrieval using C-band Sentinel-1 data is shown to be successful, but faster revisit is required to avoid low temporal coherence. Global SWE retrieval using radar interferometry will have a great opportunity with the upcoming L-band 12 d repeat-pass NASA-ISRO Synthetic Aperture Radar (NISAR) data and the future 6 d repeat-pass Radar Observing System for Europe in L-band (ROSE-L) data.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"117 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139843635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alison Delhasse, J. Beckmann, C. Kittel, X. Fettweis
Abstract. The Greenland Ice Sheet is a key contributor to sea level rise. By melting, the ice sheet thins, inducing higher surface melt due to lower surface elevations, accelerating the melt coming from global warming. This process is called the melt–elevation feedback and can be considered by using two types of models: either (1) atmospheric models, which can represent the surface mass balance (SMB), or SMB estimates resulting from simpler models such as positive degree day models or (2) ice sheet models representing the surface elevation evolution. The latter ones do not represent the surface mass balance explicitly as well as polar-oriented climate models. A new coupling between the MAR (Modèle Atmosphérique Régional) regional climate model and the PISM (Parallel Ice Sheet Model) ice sheet model is presented here following the CESM2 (Community Earth System Model; SSP5-8.5, Shared Socioeconomic Pathway) scenario until 2100 at the MAR lateral boundaries. The coupling is extended to 2200 with a stabilised climate (+7 ∘C compared to 1961–1990) by randomly sampling the last 10 years of CESM2 to force MAR and reaches a sea level rise contribution of 64 cm. The fully coupled simulation is compared to a one-way experiment where surface topography remains fixed in MAR. However, the surface mass balance is corrected for the melt–elevation feedback when interpolated on the PISM grid by using surface mass balance vertical gradients as a function of local elevation variations (offline correction). This method is often used to represent the melt–elevation feedback and prevents a coupling which is too expensive in computation time. In the fully coupled MAR simulation, the ice sheet morphology evolution (changing slope and reducing the orographic barrier) induces changes in local atmospheric patterns. More specifically, wind regimes are modified, as well as temperature lapse rates, influencing the melt rate through modification of sensible heat fluxes at the ice sheet margins. We highlight mitigation of the melt lapse rate on the margins by modifying the surface morphology. The lapse rates considered by the offline correction are no longer valid at the ice sheet margins. If used (one-way simulation), this correction implies an overestimation of the sea level rise contribution of 2.5 %. The mitigation of the melt lapse rate on the margins can only be corrected by using a full coupling between an ice sheet model and an atmospheric model.
{"title":"Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback","authors":"Alison Delhasse, J. Beckmann, C. Kittel, X. Fettweis","doi":"10.5194/tc-18-633-2024","DOIUrl":"https://doi.org/10.5194/tc-18-633-2024","url":null,"abstract":"Abstract. The Greenland Ice Sheet is a key contributor to sea level rise. By melting, the ice sheet thins, inducing higher surface melt due to lower surface elevations, accelerating the melt coming from global warming. This process is called the melt–elevation feedback and can be considered by using two types of models: either (1) atmospheric models, which can represent the surface mass balance (SMB), or SMB estimates resulting from simpler models such as positive degree day models or (2) ice sheet models representing the surface elevation evolution. The latter ones do not represent the surface mass balance explicitly as well as polar-oriented climate models. A new coupling between the MAR (Modèle Atmosphérique Régional) regional climate model and the PISM (Parallel Ice Sheet Model) ice sheet model is presented here following the CESM2 (Community Earth System Model; SSP5-8.5, Shared Socioeconomic Pathway) scenario until 2100 at the MAR lateral boundaries. The coupling is extended to 2200 with a stabilised climate (+7 ∘C compared to 1961–1990) by randomly sampling the last 10 years of CESM2 to force MAR and reaches a sea level rise contribution of 64 cm. The fully coupled simulation is compared to a one-way experiment where surface topography remains fixed in MAR. However, the surface mass balance is corrected for the melt–elevation feedback when interpolated on the PISM grid by using surface mass balance vertical gradients as a function of local elevation variations (offline correction). This method is often used to represent the melt–elevation feedback and prevents a coupling which is too expensive in computation time. In the fully coupled MAR simulation, the ice sheet morphology evolution (changing slope and reducing the orographic barrier) induces changes in local atmospheric patterns. More specifically, wind regimes are modified, as well as temperature lapse rates, influencing the melt rate through modification of sensible heat fluxes at the ice sheet margins. We highlight mitigation of the melt lapse rate on the margins by modifying the surface morphology. The lapse rates considered by the offline correction are no longer valid at the ice sheet margins. If used (one-way simulation), this correction implies an overestimation of the sea level rise contribution of 2.5 %. The mitigation of the melt lapse rate on the margins can only be corrected by using a full coupling between an ice sheet model and an atmospheric model.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"75 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139843760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Claudio Stefanini, G. Macelloni, M. Leduc-Leballeur, Vincent Favier, Benjamin Pohl, G. Picard
Abstract. This study explores the seasonal variations in snow grain size on the East Antarctic Plateau, where dry metamorphism occurs, by using microwave radiometer observations from 2000 to 2022. Local meteorological conditions and large-scale atmospheric phenomena have been considered in order to explain some peculiar changes in the snow grains. We find that the highest ice divide is the region with the largest grain size in the summer, mainly because the wind speed is low. Moreover, some extreme grain size values with respect to the average (over +3σ) were identified. In these cases, the ERA5 reanalysis revealed a high-pressure blocking close to the onsets of the summer increase in the grain size. It channels moisture intrusions from the mid-latitudes, through atmospheric rivers that cause major snowfall events over the plateau. If conditions of weak wind and low temperature occur during the following weeks, dry snow metamorphism is facilitated, leading to grain growth. This determines anomalous high maximums of the snow grain size at the end of summer. These phenomena confirm the importance of moisture intrusion events in East Antarctica and their impact on the physical properties of the ice sheet surface, with a co-occurrence of atmospheric rivers and seasonal changes in the grain size with a significance of over 95 %.
{"title":"Extreme events of snow grain size increase in East Antarctica and their relationship with meteorological conditions","authors":"Claudio Stefanini, G. Macelloni, M. Leduc-Leballeur, Vincent Favier, Benjamin Pohl, G. Picard","doi":"10.5194/tc-18-593-2024","DOIUrl":"https://doi.org/10.5194/tc-18-593-2024","url":null,"abstract":"Abstract. This study explores the seasonal variations in snow grain size on the East Antarctic Plateau, where dry metamorphism occurs, by using microwave radiometer observations from 2000 to 2022. Local meteorological conditions and large-scale atmospheric phenomena have been considered in order to explain some peculiar changes in the snow grains. We find that the highest ice divide is the region with the largest grain size in the summer, mainly because the wind speed is low. Moreover, some extreme grain size values with respect to the average (over +3σ) were identified. In these cases, the ERA5 reanalysis revealed a high-pressure blocking close to the onsets of the summer increase in the grain size. It channels moisture intrusions from the mid-latitudes, through atmospheric rivers that cause major snowfall events over the plateau. If conditions of weak wind and low temperature occur during the following weeks, dry snow metamorphism is facilitated, leading to grain growth. This determines anomalous high maximums of the snow grain size at the end of summer. These phenomena confirm the importance of moisture intrusion events in East Antarctica and their impact on the physical properties of the ice sheet surface, with a co-occurrence of atmospheric rivers and seasonal changes in the grain size with a significance of over 95 %.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"44 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zachary Hoppinen, S. Oveisgharan, Hans-Peter Marshall, Ross Mower, Kelly Elder, C. Vuyovich
Abstract. This study evaluates using interferometry on low-frequency synthetic aperture radar (SAR) images to monitor snow water equivalent (SWE) over seasonal and synoptic scales. We retrieved SWE changes from nine pairs of SAR images, mean 8 d temporal baseline, captured by an L-band aerial platform, NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), over central Idaho as part of the NASA SnowEx 2020 and 2021 campaigns. The retrieved SWE changes were compared against coincident in situ measurements (SNOTEL and snow pits from the SnowEx field campaign) and to 100 m gridded SnowModel modeled SWE changes. The comparison of in situ to retrieved measurements shows a strong Pearson correlation (R=0.80) and low RMSE (0.1 m, n=64) for snow depth change and similar results for SWE change (RMSE = 0.04 m, R=0.52, n=57). The comparison between retrieved SWE changes to SnowModel SWE change also showed good correlation (R=0.60, RMSD = 0.023 m, n=3.2×106) and especially high correlation for a subset of pixels with no modeled melt and low tree coverage (R=0.72, RMSD = 0.013 m, n=6.5×104). Finally, we bin the retrievals for a variety of factors and show decreasing correlation between the modeled and retrieved values for lower elevations, higher incidence angles, higher tree percentages and heights, and greater cumulative melt. This study builds on previous interferometry work by using a full winter season time series of L-band SAR images over a large spatial extent to evaluate the accuracy of SWE change retrievals against both in situ and modeled results and the controlling factors of the retrieval accuracy.
摘要。本研究评估了在低频合成孔径雷达(SAR)图像上使用干涉测量法监测季节和天气尺度的雪水当量(SWE)的情况。作为 NASA SnowEx 2020 年和 2021 年活动的一部分,我们从爱达荷州中部上空由 L 波段航空平台(NASA 无人驾驶飞行器合成孔径雷达 (UAVSAR))捕获的九对 SAR 图像(平均 8 天时间基线)中检索了 SWE 变化。将检索到的 SWE 变化与重合的原地测量值(SNOTEL 和 SnowEx 野外作业中的雪坑)以及 100 米网格化 SnowModel 模拟的 SWE 变化进行了比较。原位测量值与检索测量值的比较结果显示,雪深变化的皮尔逊相关性强(R=0.80),均方根误差小(0.1 米,n=64),而 SWE 变化的结果类似(均方根误差 = 0.04 米,R=0.52,n=57)。检索到的 SWE 变化与 SnowModel SWE 变化之间的比较也显示出良好的相关性(R=0.60,RMSD = 0.023 m,n=3.2×106),尤其是对于没有模型融化和树木覆盖率低的像素子集,相关性更高(R=0.72,RMSD = 0.013 m,n=6.5×104)。最后,我们对各种因素的检索结果进行了分类,结果表明,在海拔较低、入射角度较高、树木比例和高度较高以及累积融化量较大的情况下,建模值与检索值之间的相关性降低。本研究在以往干涉测量工作的基础上,利用大空间范围内整个冬季的 L 波段合成孔径雷达图像时间序列,对照原地和模拟结果,评估了 SWE 变化检索的准确性,以及检索准确性的控制因素。
{"title":"Snow water equivalent retrieval over Idaho – Part 2: Using L-band UAVSAR repeat-pass interferometry","authors":"Zachary Hoppinen, S. Oveisgharan, Hans-Peter Marshall, Ross Mower, Kelly Elder, C. Vuyovich","doi":"10.5194/tc-18-575-2024","DOIUrl":"https://doi.org/10.5194/tc-18-575-2024","url":null,"abstract":"Abstract. This study evaluates using interferometry on low-frequency synthetic aperture radar (SAR) images to monitor snow water equivalent (SWE) over seasonal and synoptic scales. We retrieved SWE changes from nine pairs of SAR images, mean 8 d temporal baseline, captured by an L-band aerial platform, NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), over central Idaho as part of the NASA SnowEx 2020 and 2021 campaigns. The retrieved SWE changes were compared against coincident in situ measurements (SNOTEL and snow pits from the SnowEx field campaign) and to 100 m gridded SnowModel modeled SWE changes. The comparison of in situ to retrieved measurements shows a strong Pearson correlation (R=0.80) and low RMSE (0.1 m, n=64) for snow depth change and similar results for SWE change (RMSE = 0.04 m, R=0.52, n=57). The comparison between retrieved SWE changes to SnowModel SWE change also showed good correlation (R=0.60, RMSD = 0.023 m, n=3.2×106) and especially high correlation for a subset of pixels with no modeled melt and low tree coverage (R=0.72, RMSD = 0.013 m, n=6.5×104). Finally, we bin the retrievals for a variety of factors and show decreasing correlation between the modeled and retrieved values for lower elevations, higher incidence angles, higher tree percentages and heights, and greater cumulative melt. This study builds on previous interferometry work by using a full winter season time series of L-band SAR images over a large spatial extent to evaluate the accuracy of SWE change retrievals against both in situ and modeled results and the controlling factors of the retrieval accuracy.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"59 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Violaine Coulon, A. Klose, C. Kittel, T. Edwards, Fiona Turner, R. Winkelmann, F. Pattyn
Abstract. We use an observationally calibrated ice-sheet model to investigate the future trajectory of the Antarctic ice sheet related to uncertainties in the future balance between sub-shelf melting and ice discharge, on the one hand, and the surface mass balance, on the other. Our ensemble of simulations, forced by a panel of climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), suggests that the ocean will be the primary driver of short-term Antarctic mass loss, initiating ice loss in West Antarctica already during this century. The atmosphere initially plays a mitigating role through increased snowfall, leading to an Antarctic contribution to global mean sea-level rise by 2100 of 6 (−8 to 15) cm under a low-emission scenario and 5.5 (−10 to 16) cm under a very high-emission scenario. However, under the very high-emission pathway, the influence of the atmosphere shifts beyond the end of the century, becoming an amplifying driver of mass loss as the ice sheet's surface mass balance decreases. We show that this transition occurs when Antarctic near-surface warming exceeds a critical threshold of +7.5 ∘C, at which the increase in surface runoff outweighs the increase in snow accumulation, a signal that is amplified by the melt–elevation feedback. Therefore, under the very high-emission scenario, oceanic and atmospheric drivers are projected to result in a complete collapse of the West Antarctic ice sheet along with significant grounding-line retreat in the marine basins of the East Antarctic ice sheet, leading to a median global mean sea-level rise of 2.75 (6.95) m by 2300 (3000). Under a more sustainable socio-economic pathway, we find that the Antarctic ice sheet may still contribute to a median global mean sea-level rise of 0.62 (1.85) m by 2300 (3000). However, the rate of sea-level rise is significantly reduced as mass loss is likely to remain confined to the Amundsen Sea Embayment, where present-day climate conditions seem sufficient to commit to a continuous retreat of Thwaites Glacier.
{"title":"Disentangling the drivers of future Antarctic ice loss with a historically calibrated ice-sheet model","authors":"Violaine Coulon, A. Klose, C. Kittel, T. Edwards, Fiona Turner, R. Winkelmann, F. Pattyn","doi":"10.5194/tc-18-653-2024","DOIUrl":"https://doi.org/10.5194/tc-18-653-2024","url":null,"abstract":"Abstract. We use an observationally calibrated ice-sheet model to investigate the future trajectory of the Antarctic ice sheet related to uncertainties in the future balance between sub-shelf melting and ice discharge, on the one hand, and the surface mass balance, on the other. Our ensemble of simulations, forced by a panel of climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), suggests that the ocean will be the primary driver of short-term Antarctic mass loss, initiating ice loss in West Antarctica already during this century. The atmosphere initially plays a mitigating role through increased snowfall, leading to an Antarctic contribution to global mean sea-level rise by 2100 of 6 (−8 to 15) cm under a low-emission scenario and 5.5 (−10 to 16) cm under a very high-emission scenario. However, under the very high-emission pathway, the influence of the atmosphere shifts beyond the end of the century, becoming an amplifying driver of mass loss as the ice sheet's surface mass balance decreases. We show that this transition occurs when Antarctic near-surface warming exceeds a critical threshold of +7.5 ∘C, at which the increase in surface runoff outweighs the increase in snow accumulation, a signal that is amplified by the melt–elevation feedback. Therefore, under the very high-emission scenario, oceanic and atmospheric drivers are projected to result in a complete collapse of the West Antarctic ice sheet along with significant grounding-line retreat in the marine basins of the East Antarctic ice sheet, leading to a median global mean sea-level rise of 2.75 (6.95) m by 2300 (3000). Under a more sustainable socio-economic pathway, we find that the Antarctic ice sheet may still contribute to a median global mean sea-level rise of 0.62 (1.85) m by 2300 (3000). However, the rate of sea-level rise is significantly reduced as mass loss is likely to remain confined to the Amundsen Sea Embayment, where present-day climate conditions seem sufficient to commit to a continuous retreat of Thwaites Glacier.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"44 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alison Delhasse, J. Beckmann, C. Kittel, X. Fettweis
Abstract. The Greenland Ice Sheet is a key contributor to sea level rise. By melting, the ice sheet thins, inducing higher surface melt due to lower surface elevations, accelerating the melt coming from global warming. This process is called the melt–elevation feedback and can be considered by using two types of models: either (1) atmospheric models, which can represent the surface mass balance (SMB), or SMB estimates resulting from simpler models such as positive degree day models or (2) ice sheet models representing the surface elevation evolution. The latter ones do not represent the surface mass balance explicitly as well as polar-oriented climate models. A new coupling between the MAR (Modèle Atmosphérique Régional) regional climate model and the PISM (Parallel Ice Sheet Model) ice sheet model is presented here following the CESM2 (Community Earth System Model; SSP5-8.5, Shared Socioeconomic Pathway) scenario until 2100 at the MAR lateral boundaries. The coupling is extended to 2200 with a stabilised climate (+7 ∘C compared to 1961–1990) by randomly sampling the last 10 years of CESM2 to force MAR and reaches a sea level rise contribution of 64 cm. The fully coupled simulation is compared to a one-way experiment where surface topography remains fixed in MAR. However, the surface mass balance is corrected for the melt–elevation feedback when interpolated on the PISM grid by using surface mass balance vertical gradients as a function of local elevation variations (offline correction). This method is often used to represent the melt–elevation feedback and prevents a coupling which is too expensive in computation time. In the fully coupled MAR simulation, the ice sheet morphology evolution (changing slope and reducing the orographic barrier) induces changes in local atmospheric patterns. More specifically, wind regimes are modified, as well as temperature lapse rates, influencing the melt rate through modification of sensible heat fluxes at the ice sheet margins. We highlight mitigation of the melt lapse rate on the margins by modifying the surface morphology. The lapse rates considered by the offline correction are no longer valid at the ice sheet margins. If used (one-way simulation), this correction implies an overestimation of the sea level rise contribution of 2.5 %. The mitigation of the melt lapse rate on the margins can only be corrected by using a full coupling between an ice sheet model and an atmospheric model.
{"title":"Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback","authors":"Alison Delhasse, J. Beckmann, C. Kittel, X. Fettweis","doi":"10.5194/tc-18-633-2024","DOIUrl":"https://doi.org/10.5194/tc-18-633-2024","url":null,"abstract":"Abstract. The Greenland Ice Sheet is a key contributor to sea level rise. By melting, the ice sheet thins, inducing higher surface melt due to lower surface elevations, accelerating the melt coming from global warming. This process is called the melt–elevation feedback and can be considered by using two types of models: either (1) atmospheric models, which can represent the surface mass balance (SMB), or SMB estimates resulting from simpler models such as positive degree day models or (2) ice sheet models representing the surface elevation evolution. The latter ones do not represent the surface mass balance explicitly as well as polar-oriented climate models. A new coupling between the MAR (Modèle Atmosphérique Régional) regional climate model and the PISM (Parallel Ice Sheet Model) ice sheet model is presented here following the CESM2 (Community Earth System Model; SSP5-8.5, Shared Socioeconomic Pathway) scenario until 2100 at the MAR lateral boundaries. The coupling is extended to 2200 with a stabilised climate (+7 ∘C compared to 1961–1990) by randomly sampling the last 10 years of CESM2 to force MAR and reaches a sea level rise contribution of 64 cm. The fully coupled simulation is compared to a one-way experiment where surface topography remains fixed in MAR. However, the surface mass balance is corrected for the melt–elevation feedback when interpolated on the PISM grid by using surface mass balance vertical gradients as a function of local elevation variations (offline correction). This method is often used to represent the melt–elevation feedback and prevents a coupling which is too expensive in computation time. In the fully coupled MAR simulation, the ice sheet morphology evolution (changing slope and reducing the orographic barrier) induces changes in local atmospheric patterns. More specifically, wind regimes are modified, as well as temperature lapse rates, influencing the melt rate through modification of sensible heat fluxes at the ice sheet margins. We highlight mitigation of the melt lapse rate on the margins by modifying the surface morphology. The lapse rates considered by the offline correction are no longer valid at the ice sheet margins. If used (one-way simulation), this correction implies an overestimation of the sea level rise contribution of 2.5 %. The mitigation of the melt lapse rate on the margins can only be corrected by using a full coupling between an ice sheet model and an atmospheric model.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"47 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139783942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Supraglacial lakes (SGLs) play an important role in debris-covered glacier (DCG) systems by enabling efficient interactions between the supraglacial, englacial, and subglacial environments. Developing a better understanding of the short-term and long-term development of these features is needed to constrain DCG evolution and the hazards posed to downstream communities, ecosystems, and infrastructure from rapid drainage. In this study, we present an analysis of supraglacial lakes on eight DCGs in the Khumbu region of Nepal by automating SGL identification in PlanetScope, Sentinel-2, and Landsat 5–9 images. We identify a regular annual cycle in SGL area, with lakes covering approximately twice as much area during their maximum annual extent (in the pre-monsoon season) than their minimum annual extent (in the post-monsoon season). The high spatiotemporal resolution of PlanetScope imagery (∼ daily, 3 m) shows that this cycle is driven by the appearance and expansion of small lakes in the upper debris-covered regions of these glaciers throughout the winter. Decadal-scale expansion of large, near-terminus lakes was identified on four of the glaciers (Khumbu, Lhotse, Nuptse, and Ambulapcha), while the remaining four showed no significant increases over the study period. The seasonal variation in SGL area is of comparable or greater magnitude as decadal-scale changes, highlighting the importance of accounting for this seasonality when interpreting long-term records of SGL changes from sparse observations. The complex spatiotemporal patterns revealed in our analysis are not captured in existing regional-scale glacial lake databases, suggesting that more targeted efforts are needed to capture the true variability of SGLs on large scales.
{"title":"Seasonal to decadal dynamics of supraglacial lakes on debris-covered glaciers in the Khumbu region, Nepal","authors":"Lucas Zeller, D. McGrath, S. McCoy, J. Jacquet","doi":"10.5194/tc-18-525-2024","DOIUrl":"https://doi.org/10.5194/tc-18-525-2024","url":null,"abstract":"Abstract. Supraglacial lakes (SGLs) play an important role in debris-covered glacier (DCG) systems by enabling efficient interactions between the supraglacial, englacial, and subglacial environments. Developing a better understanding of the short-term and long-term development of these features is needed to constrain DCG evolution and the hazards posed to downstream communities, ecosystems, and infrastructure from rapid drainage. In this study, we present an analysis of supraglacial lakes on eight DCGs in the Khumbu region of Nepal by automating SGL identification in PlanetScope, Sentinel-2, and Landsat 5–9 images. We identify a regular annual cycle in SGL area, with lakes covering approximately twice as much area during their maximum annual extent (in the pre-monsoon season) than their minimum annual extent (in the post-monsoon season). The high spatiotemporal resolution of PlanetScope imagery (∼ daily, 3 m) shows that this cycle is driven by the appearance and expansion of small lakes in the upper debris-covered regions of these glaciers throughout the winter. Decadal-scale expansion of large, near-terminus lakes was identified on four of the glaciers (Khumbu, Lhotse, Nuptse, and Ambulapcha), while the remaining four showed no significant increases over the study period. The seasonal variation in SGL area is of comparable or greater magnitude as decadal-scale changes, highlighting the importance of accounting for this seasonality when interpreting long-term records of SGL changes from sparse observations. The complex spatiotemporal patterns revealed in our analysis are not captured in existing regional-scale glacial lake databases, suggesting that more targeted efforts are needed to capture the true variability of SGLs on large scales.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"89 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139793880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Melling, A. Leeson, M. McMillan, Jennifer Maddalena, Jade S. Bowling, Emily Glen, Louise Sandberg Sørensen, M. Winstrup, Rasmus Lørup Arildsen
Abstract. Supraglacial lakes form on the Greenland ice sheet in the melt season (May to October) when meltwater collects in surface depressions on the ice. Supraglacial lakes can act as a control on ice dynamics since, given a large enough volume of water and a favourable stress regime, hydrofracture of the lake can occur, which enables water transfer from the ice surface to the bedrock, where it can lubricate the base. The depth (and thus volume) of these lakes is typically estimated by applying a radiative transfer equation (RTE) to optical satellite imagery. This method can be used at scale across entire ice sheets but is poorly validated due to a paucity of in situ depth data. Here we intercompare supraglacial lake depth detection by means of ArcticDEM digital elevation models, ICESat-2 photon refraction, and the RTE applied to Sentinel-2 images across five lakes in southwest Greenland. We found good agreement between the ArcticDEM and ICESat-2 approaches (Pearson's r=0.98) but found that the RTE overestimates lake depth by up to 153 % using the green band (543–578 nm) and underestimates lake depth by up to 63 % using the red band (650–680 nm). Parametric uncertainty in the RTE estimates is substantial and is dominated by uncertainty in estimates of reflectance at the lakebed, which are derived empirically. Uncertainty in lake depth estimates translates into a poor understanding of total lake volume, which could mean that hydrofracture likelihood is poorly constrained, in turn affecting ice velocity predictions. Further laboratory studies to constrain spectral radiance loss in the water column and investigation of the potential effects of cryoconite on lakebed reflectance could improve the RTE in its current format. However, we also suggest that future work should explore multi-sensor approaches to deriving lake depth from optical satellite imagery, which may improve depth estimates and will certainly result in better-constrained uncertainties.
{"title":"Evaluation of satellite methods for estimating supraglacial lake depth in southwest Greenland","authors":"L. Melling, A. Leeson, M. McMillan, Jennifer Maddalena, Jade S. Bowling, Emily Glen, Louise Sandberg Sørensen, M. Winstrup, Rasmus Lørup Arildsen","doi":"10.5194/tc-18-543-2024","DOIUrl":"https://doi.org/10.5194/tc-18-543-2024","url":null,"abstract":"Abstract. Supraglacial lakes form on the Greenland ice sheet in the melt season (May to October) when meltwater collects in surface depressions on the ice. Supraglacial lakes can act as a control on ice dynamics since, given a large enough volume of water and a favourable stress regime, hydrofracture of the lake can occur, which enables water transfer from the ice surface to the bedrock, where it can lubricate the base. The depth (and thus volume) of these lakes is typically estimated by applying a radiative transfer equation (RTE) to optical satellite imagery. This method can be used at scale across entire ice sheets but is poorly validated due to a paucity of in situ depth data. Here we intercompare supraglacial lake depth detection by means of ArcticDEM digital elevation models, ICESat-2 photon refraction, and the RTE applied to Sentinel-2 images across five lakes in southwest Greenland. We found good agreement between the ArcticDEM and ICESat-2 approaches (Pearson's r=0.98) but found that the RTE overestimates lake depth by up to 153 % using the green band (543–578 nm) and underestimates lake depth by up to 63 % using the red band (650–680 nm). Parametric uncertainty in the RTE estimates is substantial and is dominated by uncertainty in estimates of reflectance at the lakebed, which are derived empirically. Uncertainty in lake depth estimates translates into a poor understanding of total lake volume, which could mean that hydrofracture likelihood is poorly constrained, in turn affecting ice velocity predictions. Further laboratory studies to constrain spectral radiance loss in the water column and investigation of the potential effects of cryoconite on lakebed reflectance could improve the RTE in its current format. However, we also suggest that future work should explore multi-sensor approaches to deriving lake depth from optical satellite imagery, which may improve depth estimates and will certainly result in better-constrained uncertainties.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"20 S4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139793544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Melling, A. Leeson, M. McMillan, Jennifer Maddalena, Jade S. Bowling, Emily Glen, Louise Sandberg Sørensen, M. Winstrup, Rasmus Lørup Arildsen
Abstract. Supraglacial lakes form on the Greenland ice sheet in the melt season (May to October) when meltwater collects in surface depressions on the ice. Supraglacial lakes can act as a control on ice dynamics since, given a large enough volume of water and a favourable stress regime, hydrofracture of the lake can occur, which enables water transfer from the ice surface to the bedrock, where it can lubricate the base. The depth (and thus volume) of these lakes is typically estimated by applying a radiative transfer equation (RTE) to optical satellite imagery. This method can be used at scale across entire ice sheets but is poorly validated due to a paucity of in situ depth data. Here we intercompare supraglacial lake depth detection by means of ArcticDEM digital elevation models, ICESat-2 photon refraction, and the RTE applied to Sentinel-2 images across five lakes in southwest Greenland. We found good agreement between the ArcticDEM and ICESat-2 approaches (Pearson's r=0.98) but found that the RTE overestimates lake depth by up to 153 % using the green band (543–578 nm) and underestimates lake depth by up to 63 % using the red band (650–680 nm). Parametric uncertainty in the RTE estimates is substantial and is dominated by uncertainty in estimates of reflectance at the lakebed, which are derived empirically. Uncertainty in lake depth estimates translates into a poor understanding of total lake volume, which could mean that hydrofracture likelihood is poorly constrained, in turn affecting ice velocity predictions. Further laboratory studies to constrain spectral radiance loss in the water column and investigation of the potential effects of cryoconite on lakebed reflectance could improve the RTE in its current format. However, we also suggest that future work should explore multi-sensor approaches to deriving lake depth from optical satellite imagery, which may improve depth estimates and will certainly result in better-constrained uncertainties.
{"title":"Evaluation of satellite methods for estimating supraglacial lake depth in southwest Greenland","authors":"L. Melling, A. Leeson, M. McMillan, Jennifer Maddalena, Jade S. Bowling, Emily Glen, Louise Sandberg Sørensen, M. Winstrup, Rasmus Lørup Arildsen","doi":"10.5194/tc-18-543-2024","DOIUrl":"https://doi.org/10.5194/tc-18-543-2024","url":null,"abstract":"Abstract. Supraglacial lakes form on the Greenland ice sheet in the melt season (May to October) when meltwater collects in surface depressions on the ice. Supraglacial lakes can act as a control on ice dynamics since, given a large enough volume of water and a favourable stress regime, hydrofracture of the lake can occur, which enables water transfer from the ice surface to the bedrock, where it can lubricate the base. The depth (and thus volume) of these lakes is typically estimated by applying a radiative transfer equation (RTE) to optical satellite imagery. This method can be used at scale across entire ice sheets but is poorly validated due to a paucity of in situ depth data. Here we intercompare supraglacial lake depth detection by means of ArcticDEM digital elevation models, ICESat-2 photon refraction, and the RTE applied to Sentinel-2 images across five lakes in southwest Greenland. We found good agreement between the ArcticDEM and ICESat-2 approaches (Pearson's r=0.98) but found that the RTE overestimates lake depth by up to 153 % using the green band (543–578 nm) and underestimates lake depth by up to 63 % using the red band (650–680 nm). Parametric uncertainty in the RTE estimates is substantial and is dominated by uncertainty in estimates of reflectance at the lakebed, which are derived empirically. Uncertainty in lake depth estimates translates into a poor understanding of total lake volume, which could mean that hydrofracture likelihood is poorly constrained, in turn affecting ice velocity predictions. Further laboratory studies to constrain spectral radiance loss in the water column and investigation of the potential effects of cryoconite on lakebed reflectance could improve the RTE in its current format. However, we also suggest that future work should explore multi-sensor approaches to deriving lake depth from optical satellite imagery, which may improve depth estimates and will certainly result in better-constrained uncertainties.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"7 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139853199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Supraglacial lakes (SGLs) play an important role in debris-covered glacier (DCG) systems by enabling efficient interactions between the supraglacial, englacial, and subglacial environments. Developing a better understanding of the short-term and long-term development of these features is needed to constrain DCG evolution and the hazards posed to downstream communities, ecosystems, and infrastructure from rapid drainage. In this study, we present an analysis of supraglacial lakes on eight DCGs in the Khumbu region of Nepal by automating SGL identification in PlanetScope, Sentinel-2, and Landsat 5–9 images. We identify a regular annual cycle in SGL area, with lakes covering approximately twice as much area during their maximum annual extent (in the pre-monsoon season) than their minimum annual extent (in the post-monsoon season). The high spatiotemporal resolution of PlanetScope imagery (∼ daily, 3 m) shows that this cycle is driven by the appearance and expansion of small lakes in the upper debris-covered regions of these glaciers throughout the winter. Decadal-scale expansion of large, near-terminus lakes was identified on four of the glaciers (Khumbu, Lhotse, Nuptse, and Ambulapcha), while the remaining four showed no significant increases over the study period. The seasonal variation in SGL area is of comparable or greater magnitude as decadal-scale changes, highlighting the importance of accounting for this seasonality when interpreting long-term records of SGL changes from sparse observations. The complex spatiotemporal patterns revealed in our analysis are not captured in existing regional-scale glacial lake databases, suggesting that more targeted efforts are needed to capture the true variability of SGLs on large scales.
{"title":"Seasonal to decadal dynamics of supraglacial lakes on debris-covered glaciers in the Khumbu region, Nepal","authors":"Lucas Zeller, D. McGrath, S. McCoy, J. Jacquet","doi":"10.5194/tc-18-525-2024","DOIUrl":"https://doi.org/10.5194/tc-18-525-2024","url":null,"abstract":"Abstract. Supraglacial lakes (SGLs) play an important role in debris-covered glacier (DCG) systems by enabling efficient interactions between the supraglacial, englacial, and subglacial environments. Developing a better understanding of the short-term and long-term development of these features is needed to constrain DCG evolution and the hazards posed to downstream communities, ecosystems, and infrastructure from rapid drainage. In this study, we present an analysis of supraglacial lakes on eight DCGs in the Khumbu region of Nepal by automating SGL identification in PlanetScope, Sentinel-2, and Landsat 5–9 images. We identify a regular annual cycle in SGL area, with lakes covering approximately twice as much area during their maximum annual extent (in the pre-monsoon season) than their minimum annual extent (in the post-monsoon season). The high spatiotemporal resolution of PlanetScope imagery (∼ daily, 3 m) shows that this cycle is driven by the appearance and expansion of small lakes in the upper debris-covered regions of these glaciers throughout the winter. Decadal-scale expansion of large, near-terminus lakes was identified on four of the glaciers (Khumbu, Lhotse, Nuptse, and Ambulapcha), while the remaining four showed no significant increases over the study period. The seasonal variation in SGL area is of comparable or greater magnitude as decadal-scale changes, highlighting the importance of accounting for this seasonality when interpreting long-term records of SGL changes from sparse observations. The complex spatiotemporal patterns revealed in our analysis are not captured in existing regional-scale glacial lake databases, suggesting that more targeted efforts are needed to capture the true variability of SGLs on large scales.\u0000","PeriodicalId":509217,"journal":{"name":"The Cryosphere","volume":"71 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139853780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}