Research article
15 Apr 2019
Research article
| 15 Apr 2019
A key factor initiating surface ablation of Arctic sea ice: earlier and increasing liquid precipitation
Tingfeng Dou et al.
Related authors
Minghu Ding, Tong Zhang, Diyi Yang, Ian Allison, Tingfeng Dou, and Cunde Xiao
The Cryosphere, 15, 4201–4206, https://doi.org/10.5194/tc-15-4201-2021, https://doi.org/10.5194/tc-15-4201-2021, 2021
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Measurement of snow heat conductivity is essential to establish the energy balance between the atmosphere and firn, but it is still not clear in Antarctica. Here, we used data from three automatic weather stations located in different types of climate and evaluated nine schemes that were used to calculate the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity–density relationship was optimal at all sites, and the performance of each varied with depth.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
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Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
Tingfeng Dou, Zhiheng Du, Shutong Li, Yulan Zhang, Qi Zhang, Mingju Hao, Chuanjin Li, Biao Tian, Minghu Ding, and Cunde Xiao
The Cryosphere, 13, 3309–3316, https://doi.org/10.5194/tc-13-3309-2019, https://doi.org/10.5194/tc-13-3309-2019, 2019
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The meltwater scavenging coefficient (MSC) determines the BC enrichment in the surface layer of melting snow and therefore modulates the BC-snow-albedo feedbacks. This study presents a new method for MSC estimation over the sea-ice area in Arctic. Using this new method, we analyze the spatial variability of MSC in the western Arctic and demonstrate that the value in Canada Basin (23.6 % ± 2.1 %) ≈ that in Greenland (23.0 % ± 12.5 %) > that in Chukchi Sea (17.9 % ± 5.0 %) > that in Elson Lagoon (14.5 % ± 2.6 %).
C. Xiao, R. Li, S. B. Sneed, T. Dou, and I. Allison
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-3611-2013, https://doi.org/10.5194/tcd-7-3611-2013, 2013
Revised manuscript not accepted
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-188, https://doi.org/10.5194/essd-2022-188, 2022
Preprint under review for ESSD
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This paper introduces a unique multiyear dataset and the monitoring capability of the PANDA automatic weather station network which includes eleven automatic weather stations (AWS) across Prydz Bay-Amery Ice Shelf-dome area from the coast to the summit of the East Antarctica ice sheet. All AWSs in this network measure air temperature, relative humidity, air pressure, wind speed and wind direction at 1-hour intervals.
Fengguan Gu, Qinghua Yang, Frank Kauker, Changwei Liu, Guanghua Hao, Chao-Yuan Yang, Jiping Liu, Petra Heil, Xuewei Li, and Bo Han
The Cryosphere, 16, 1873–1887, https://doi.org/10.5194/tc-16-1873-2022, https://doi.org/10.5194/tc-16-1873-2022, 2022
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The sea ice thickness was simulated by a single-column model and compared with in situ observations obtained off Zhongshan Station in the Antarctic. It is shown that the unrealistic precipitation in the atmospheric forcing data leads to the largest bias in sea ice thickness and snow depth modeling. In addition, the increasing snow depth gradually inhibits the growth of sea ice associated with thermal blanketing by the snow.
Zhiheng Du, Jiao Yang, Lei Wang, Ninglian Wang, Anders Svensson, Zhen Zhang, Xiangyu Ma, Yaping Liu, Shimeng Wang, Jianzhong Xu, and Cunde Xiao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-91, https://doi.org/10.5194/essd-2022-91, 2022
Preprint under review for ESSD
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A dataset of the radiogenic strontium and neodymium isotopic compositions from in key cryospheric regions at the three poles (Third Pole, Arctic and Antarctica), were integrated to obtain new findings. The dataset enables us to map the standardized locations in the three poles, while the use of sorting criteria related to the sample type permits us to trace the dust source and sink. This dataset is to try to determine the variable transport pathways of dust at three poles.
John E. Walsh, Hajo Eicken, Kyle Redilla, and Mark Johnson
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-21, https://doi.org/10.5194/tc-2022-21, 2022
Preprint under review for TC
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Indicators for the start and end of annual break-up and freeze-up of sea ice at various coastal locations around the Arctic are developed. Relative to broader offshore areas, some of the coastal indicators show an earlier freeze-up and later break-up, especially at locations where shorefast ice is prominent. However, the trends towards earlier break-up and later freeze-up are unmistakable over the post-1979 period in synthesized metrics of the coastal break-up/freeze-up indicators.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
Geosci. Model Dev., 15, 1155–1176, https://doi.org/10.5194/gmd-15-1155-2022, https://doi.org/10.5194/gmd-15-1155-2022, 2022
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We present an improved coupled modeling system for Arctic sea ice prediction. We perform Arctic sea ice prediction experiments with improved/updated physical parameterizations, which show better skill in predicting sea ice state as well as atmospheric and oceanic state in the Arctic compared with its predecessor. The improved model also shows extended predictive skill of Arctic sea ice after the summer season. This provides an added value of this prediction system for decision-making.
Mengzhen Qi, Yan Liu, Jiping Liu, Xiao Cheng, Yijing Lin, Qiyang Feng, Qiang Shen, and Zhitong Yu
Earth Syst. Sci. Data, 13, 4583–4601, https://doi.org/10.5194/essd-13-4583-2021, https://doi.org/10.5194/essd-13-4583-2021, 2021
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A total of 1975 annual calving events larger than 1 km2 were detected on the Antarctic ice shelves from August 2005 to August 2020. The average annual calved area was measured as 3549.1 km2, and the average calving rate was measured as 770.3 Gt yr-1. Iceberg calving is most prevalent in West Antarctica, followed by the Antarctic Peninsula and Wilkes Land in East Antarctica. This annual iceberg calving dataset provides consistent and precise calving observations with the longest time coverage.
Minghu Ding, Tong Zhang, Diyi Yang, Ian Allison, Tingfeng Dou, and Cunde Xiao
The Cryosphere, 15, 4201–4206, https://doi.org/10.5194/tc-15-4201-2021, https://doi.org/10.5194/tc-15-4201-2021, 2021
Short summary
Short summary
Measurement of snow heat conductivity is essential to establish the energy balance between the atmosphere and firn, but it is still not clear in Antarctica. Here, we used data from three automatic weather stations located in different types of climate and evaluated nine schemes that were used to calculate the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity–density relationship was optimal at all sites, and the performance of each varied with depth.
Xiaoxu Shi, Dirk Notz, Jiping Liu, Hu Yang, and Gerrit Lohmann
Geosci. Model Dev., 14, 4891–4908, https://doi.org/10.5194/gmd-14-4891-2021, https://doi.org/10.5194/gmd-14-4891-2021, 2021
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The ice–ocean heat flux is one of the key elements controlling sea ice changes. It motivates our study, which aims to examine the responses of modeled climate to three ice–ocean heat flux parameterizations, including two old approaches that assume one-way heat transport and a new one describing a double-diffusive ice–ocean heat exchange. The results show pronounced differences in the modeled sea ice, ocean, and atmosphere states for the latter as compared to the former two parameterizations.
Yetang Wang, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Shugui Hou, and Cunde Xiao
Earth Syst. Sci. Data, 13, 3057–3074, https://doi.org/10.5194/essd-13-3057-2021, https://doi.org/10.5194/essd-13-3057-2021, 2021
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Accurate observation of surface mass balance (SMB) under climate change is essential for the reliable present and future assessment of Antarctic contribution to global sea level. This study presents a new quality-controlled dataset of Antarctic SMB observations at different temporal resolutions and is the first ice-sheet-scale compilation of multiple types of measurements. The dataset can be widely applied to climate model validation, remote sensing retrievals, and data assimilation.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
Short summary
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Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
Minghu Ding, Biao Tian, Michael C. B. Ashley, Davide Putero, Zhenxi Zhu, Lifan Wang, Shihai Yang, Chuanjin Li, and Cunde Xiao
Earth Syst. Sci. Data, 12, 3529–3544, https://doi.org/10.5194/essd-12-3529-2020, https://doi.org/10.5194/essd-12-3529-2020, 2020
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Dome A, is one of the harshest environments on Earth.To evaluate the characteristics of near-surface O3, continuous observations were carried out in 2016. The results showed different patterns between coastal and inland Antarctic areas that were characterized by high concentrations in cold seasons and at night. Short-range transport accounted for the O3 enhancement events (OEEs) during summer at DA, rather than efficient local production, which is consistent with previous studies.
Marc Oggier, Hajo Eicken, Meibing Jin, and Knut Høyland
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-52, https://doi.org/10.5194/tc-2020-52, 2020
Publication in TC not foreseen
O3 enhancement events(OEEs) at Dome A, East Antarctica
Minghu Ding, Biao Tian, Michael Ashley, Zhenxi Zhu, Lifan Wang, Shihai Yang, Chuanjin Li, Cunde Xiao, and Dahe Qin
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1042, https://doi.org/10.5194/acp-2019-1042, 2020
Revised manuscript not accepted
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In 2016, the first observation of near-surface ozone was made at Dome A, the inaccessible pole. And based on the ERA-interim meteorological reanalysis data, we clearly found that there was strong transportation from stratosphere to troposphere during polar night at Dome A. This work provides unique information of ozone variation in Dome A and expands our knowledge in Antarctica.
Tingfeng Dou, Zhiheng Du, Shutong Li, Yulan Zhang, Qi Zhang, Mingju Hao, Chuanjin Li, Biao Tian, Minghu Ding, and Cunde Xiao
The Cryosphere, 13, 3309–3316, https://doi.org/10.5194/tc-13-3309-2019, https://doi.org/10.5194/tc-13-3309-2019, 2019
Short summary
Short summary
The meltwater scavenging coefficient (MSC) determines the BC enrichment in the surface layer of melting snow and therefore modulates the BC-snow-albedo feedbacks. This study presents a new method for MSC estimation over the sea-ice area in Arctic. Using this new method, we analyze the spatial variability of MSC in the western Arctic and demonstrate that the value in Canada Basin (23.6 % ± 2.1 %) ≈ that in Greenland (23.0 % ± 12.5 %) > that in Chukchi Sea (17.9 % ± 5.0 %) > that in Elson Lagoon (14.5 % ± 2.6 %).
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019, https://doi.org/10.5194/tc-13-3209-2019, 2019
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Sea ice volume export through the Fram Strait has been studied using varied methods, however, mostly in winter months. Here we report sea ice volume estimates that extend over summer seasons. A recent developed sea ice thickness dataset, in which CryoSat-2 and SMOS sea ice thickness together with SSMI/SSMIS sea ice concentration are assimilated, is used and evaluated in the paper. Results show our estimate is more reasonable than that calculated by satellite data only.
Yifan Ding, Xiao Cheng, Jiping Liu, Fengming Hui, and Zhenzhan Wang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-208, https://doi.org/10.5194/tc-2019-208, 2019
Preprint withdrawn
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This study develops a new melt pond fraction (MPF) data set over sea ice on Arctic-wide scale, using a method of ensemble-based deep neural network. Based on the new dataset, we analyze the spatial-temporal variations of MPF on different ice types and the prediction of MPF to the Arctic sea ice extent in recent years. The new dataset may help improve the prediction of the Arctic sea ice minimum by assimilating the MPF in models.
Dyre O. Dammann, Leif E. B. Eriksson, Son V. Nghiem, Erin C. Pettit, Nathan T. Kurtz, John G. Sonntag, Thomas E. Busche, Franz J. Meyer, and Andrew R. Mahoney
The Cryosphere, 13, 1861–1875, https://doi.org/10.5194/tc-13-1861-2019, https://doi.org/10.5194/tc-13-1861-2019, 2019
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We validate TanDEM-X interferometry as a tool for deriving iceberg subaerial morphology using Operation IceBridge data. This approach enables a volumetric classification of icebergs, according to volume relevant to iceberg drift and decay, freshwater contribution, and potential impact on structures. We find iceberg volumes to generally match within 7 %. These results suggest that TanDEM-X could pave the way for future interferometric systems of scientific and operational iceberg classification.
Dyre Oliver Dammann, Leif E. B. Eriksson, Joshua M. Jones, Andrew R. Mahoney, Roland Romeiser, Franz J. Meyer, Hajo Eicken, and Yasushi Fukamachi
The Cryosphere, 13, 1395–1408, https://doi.org/10.5194/tc-13-1395-2019, https://doi.org/10.5194/tc-13-1395-2019, 2019
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We evaluate single-pass synthetic aperture radar interferometry (InSAR) as a tool to assess sea ice drift and deformation. Initial validation shows that TanDEM-X phase-derived drift speed corresponds well with ground-based radar-derived motion. We further show that InSAR enables the identification of potentially important short-lived dynamic processes otherwise difficult to observe, with possible implication for engineering and sea ice modeling.
Dyre O. Dammann, Leif E. B. Eriksson, Andrew R. Mahoney, Hajo Eicken, and Franz J. Meyer
The Cryosphere, 13, 557–577, https://doi.org/10.5194/tc-13-557-2019, https://doi.org/10.5194/tc-13-557-2019, 2019
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We present an approach for mapping bottomfast sea ice and landfast sea ice stability using Synthetic Aperture Radar Interferometry. This is the first comprehensive assessment of Arctic bottomfast sea ice extent with implications for subsea permafrost and marine habitats. Our pan-Arctic analysis also provides a new understanding of sea ice dynamics in five marginal seas of the Arctic Ocean relevant for strategic planning and tactical decision-making for different uses of coastal ice.
Yuanyuan Zhang, Xiao Cheng, Jiping Liu, and Fengming Hui
The Cryosphere, 12, 3747–3757, https://doi.org/10.5194/tc-12-3747-2018, https://doi.org/10.5194/tc-12-3747-2018, 2018
Claudine Hauri, Seth Danielson, Andrew M. P. McDonnell, Russell R. Hopcroft, Peter Winsor, Peter Shipton, Catherine Lalande, Kathleen M. Stafford, John K. Horne, Lee W. Cooper, Jacqueline M. Grebmeier, Andrew Mahoney, Klara Maisch, Molly McCammon, Hank Statscewich, Andy Sybrandy, and Thomas Weingartner
Ocean Sci., 14, 1423–1433, https://doi.org/10.5194/os-14-1423-2018, https://doi.org/10.5194/os-14-1423-2018, 2018
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The Arctic Ocean is changing rapidly. In order to track these changes, we developed and deployed a long-term marine ecosystem observatory in the Chukchi Sea. It helps us to better understand currents, waves, sea ice, salinity, temperature, nutrient and carbon concentrations, oxygen, phytoplankton blooms and export, zooplankton abundance and vertical migration, and the occurrence of fish and marine mammals throughout the year, even during the ice covered winter months.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
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We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Rebecca J. Rolph, Andrew R. Mahoney, John Walsh, and Philip A. Loring
The Cryosphere, 12, 1779–1790, https://doi.org/10.5194/tc-12-1779-2018, https://doi.org/10.5194/tc-12-1779-2018, 2018
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Using thresholds of physical climate variables developed from community observations, together with two large-scale datasets, we have produced local indices directly relevant to the impacts of a reduced sea ice cover on Alaska coastal communities. We demonstrate how community observations can inform use of large-scale datasets to derive these locally relevant indices.
Lu Zhou, Shiming Xu, Jiping Liu, and Bin Wang
The Cryosphere, 12, 993–1012, https://doi.org/10.5194/tc-12-993-2018, https://doi.org/10.5194/tc-12-993-2018, 2018
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This work proposes a new data synergy method for the retrieval of sea ice thickness and snow depth by using colocating L-band passive remote sensing and active laser altimetry. Physical models are adopted for the retrieval, including L-band radiation model and buoyancy relationship. Covariability of snow depth and total freeboard is further utilized to mitigate resolution differences and improve retrievability. The method can be applied to future campaigns including ICESat-2 and WCOM.
Nancy A. N. Bertler, Howard Conway, Dorthe Dahl-Jensen, Daniel B. Emanuelsson, Mai Winstrup, Paul T. Vallelonga, James E. Lee, Ed J. Brook, Jeffrey P. Severinghaus, Taylor J. Fudge, Elizabeth D. Keller, W. Troy Baisden, Richard C. A. Hindmarsh, Peter D. Neff, Thomas Blunier, Ross Edwards, Paul A. Mayewski, Sepp Kipfstuhl, Christo Buizert, Silvia Canessa, Ruzica Dadic, Helle A. Kjær, Andrei Kurbatov, Dongqi Zhang, Edwin D. Waddington, Giovanni Baccolo, Thomas Beers, Hannah J. Brightley, Lionel Carter, David Clemens-Sewall, Viorela G. Ciobanu, Barbara Delmonte, Lukas Eling, Aja Ellis, Shruthi Ganesh, Nicholas R. Golledge, Skylar Haines, Michael Handley, Robert L. Hawley, Chad M. Hogan, Katelyn M. Johnson, Elena Korotkikh, Daniel P. Lowry, Darcy Mandeno, Robert M. McKay, James A. Menking, Timothy R. Naish, Caroline Noerling, Agathe Ollive, Anaïs Orsi, Bernadette C. Proemse, Alexander R. Pyne, Rebecca L. Pyne, James Renwick, Reed P. Scherer, Stefanie Semper, Marius Simonsen, Sharon B. Sneed, Eric J. Steig, Andrea Tuohy, Abhijith Ulayottil Venugopal, Fernando Valero-Delgado, Janani Venkatesh, Feitang Wang, Shimeng Wang, Dominic A. Winski, V. Holly L. Winton, Arran Whiteford, Cunde Xiao, Jiao Yang, and Xin Zhang
Clim. Past, 14, 193–214, https://doi.org/10.5194/cp-14-193-2018, https://doi.org/10.5194/cp-14-193-2018, 2018
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Temperature and snow accumulation records from the annually dated Roosevelt Island Climate Evolution (RICE) ice core show that for the past 2 700 years, the eastern Ross Sea warmed, while the western Ross Sea showed no trend and West Antarctica cooled. From the 17th century onwards, this dipole relationship changed. Now all three regions show concurrent warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea.
Megan O'Sadnick, Malcolm Ingham, Hajo Eicken, and Erin Pettit
The Cryosphere, 10, 2923–2940, https://doi.org/10.5194/tc-10-2923-2016, https://doi.org/10.5194/tc-10-2923-2016, 2016
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Non-destructive in situ monitoring of sea-ice microstructure is of value to sea-ice research and operations but remains elusive to date. We relate in situ measurements of sea-ice dielectric properties at frequencies of 10 to 95 Hz to ice temperature, salinity, and microstructure. Results support the possible use of low-frequency electric measurements to monitor the seasonal evolution of brine volume fraction, pore volume, and connectivity of pore space in sea ice.
Chao-Yuan Yang, Jiping Liu, Yongyun Hu, Radley M. Horton, Liqi Chen, and Xiao Cheng
The Cryosphere, 10, 2429–2452, https://doi.org/10.5194/tc-10-2429-2016, https://doi.org/10.5194/tc-10-2429-2016, 2016
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The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales.
S. Xu, B. Wang, and J. Liu
Geosci. Model Dev., 8, 3471–3485, https://doi.org/10.5194/gmd-8-3471-2015, https://doi.org/10.5194/gmd-8-3471-2015, 2015
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This article applies Schwarz-Christoffel (SC) conformal mappings for single-connected and multiple-connected regions to the generation of general orthogonal grids for OGCMs, to achieve 1) the enlarged lat-lon proportion, 2) the removal of landmass and easier load balancing, 3) better spatial resolution on continental boundaries, and 4) alignment of grid lines to large-scale coastlines. The generated grids could be readily utilized by the majority of OGCMs that support general orthogonal grids.
T. Kaminski, F. Kauker, H. Eicken, and M. Karcher
The Cryosphere, 9, 1721–1733, https://doi.org/10.5194/tc-9-1721-2015, https://doi.org/10.5194/tc-9-1721-2015, 2015
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We present a quantitative network design study of the Arctic sea ice-ocean system. For a demonstration, we evaluate two idealised hypothetical flight transects derived from NASA’s Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. It further quantifies the complementarity of combining two flight transects.
C. Xiao, R. Li, S. B. Sneed, T. Dou, and I. Allison
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-3611-2013, https://doi.org/10.5194/tcd-7-3611-2013, 2013
Revised manuscript not accepted
Related subject area
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The Cryosphere, 16, 2183–2202, https://doi.org/10.5194/tc-16-2183-2022, https://doi.org/10.5194/tc-16-2183-2022, 2022
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This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results show that the simplest models are, under certain conditions, able to reproduce the surface temperature just as well as the most complex models. Moreover, the diversity of surface parameters of the models has a strong impact on the temporal variability of the components of the simulated surface energy balance.
Edward H. Bair, Jeff Dozier, Charles Stern, Adam LeWinter, Karl Rittger, Alexandria Savagian, Timbo Stillinger, and Robert E. Davis
The Cryosphere, 16, 1765–1778, https://doi.org/10.5194/tc-16-1765-2022, https://doi.org/10.5194/tc-16-1765-2022, 2022
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Understanding how snow and ice reflect solar radiation (albedo) is important for global climate. Using high-resolution topography, darkening from surface roughness (apparent albedo) is separated from darkening by the composition of the snow (intrinsic albedo). Intrinsic albedo is usually greater than apparent albedo, especially during melt. Such high-resolution topography is often not available; thus the use of a shade component when modeling mixtures is advised.
Gauthier Vérin, Florent Domine, Marcel Babin, Ghislain Picard, and Laurent Arnaud
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-76, https://doi.org/10.5194/tc-2022-76, 2022
Revised manuscript accepted for TC
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Snow physical properties on Arctic sea ice are monitored during the melt season. As snow grains grow and the snowpack thickness is reduced, the surface albedo decreases. The extra absorbed energy accelerates melting. Radiative transfer modeling shows that more radiation is then transmitted to the snow-sea ice interface. A sharp increase in transmitted radiation takes place when the snowpacks thins significantly and this coincides with the initiation of the phytoplankton bloom in the sea water.
Alvaro Robledano, Ghislain Picard, Laurent Arnaud, Fanny Larue, and Inès Ollivier
The Cryosphere, 16, 559–579, https://doi.org/10.5194/tc-16-559-2022, https://doi.org/10.5194/tc-16-559-2022, 2022
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Topography controls the surface temperature of snow-covered, mountainous areas. We developed a modelling chain that uses ray-tracing methods to quantify the impact of a few topographic effects on snow surface temperature at high spatial resolution. Its large spatial and temporal variations are correctly simulated over a 50 km2 area in the French Alps, and our results show that excluding a single topographic effect results in cooling (or warming) effects on the order of 1 °C.
Annelies Voordendag, Marion Réveillet, Shelley MacDonell, and Stef Lhermitte
The Cryosphere, 15, 4241–4259, https://doi.org/10.5194/tc-15-4241-2021, https://doi.org/10.5194/tc-15-4241-2021, 2021
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Minghu Ding, Tong Zhang, Diyi Yang, Ian Allison, Tingfeng Dou, and Cunde Xiao
The Cryosphere, 15, 4201–4206, https://doi.org/10.5194/tc-15-4201-2021, https://doi.org/10.5194/tc-15-4201-2021, 2021
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Measurement of snow heat conductivity is essential to establish the energy balance between the atmosphere and firn, but it is still not clear in Antarctica. Here, we used data from three automatic weather stations located in different types of climate and evaluated nine schemes that were used to calculate the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity–density relationship was optimal at all sites, and the performance of each varied with depth.
Luuk D. van der Valk, Adriaan J. Teuling, Luc Girod, Norbert Pirk, Robin Stoffer, and Chiel C. van Heerwaarden
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-171, https://doi.org/10.5194/tc-2021-171, 2021
Revised manuscript accepted for TC
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Most large-scale hydrological and climate models struggle to capture the spatially highly variable wind-driven melt of patchy snow cover. In the field, we observe that 60–80 % of the total melt is wind-driven at the upwind edge of a snow patch, while it does not contribute at the downwind edge. Our idealized simulations show such variation to be caused by independent-of-patch-size reducing air temperature over snow patches and allow to study the role of wind-driven snowmelt also on larger scales.
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
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The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
Marion Réveillet, Shelley MacDonell, Simon Gascoin, Christophe Kinnard, Stef Lhermitte, and Nicole Schaffer
The Cryosphere, 14, 147–163, https://doi.org/10.5194/tc-14-147-2020, https://doi.org/10.5194/tc-14-147-2020, 2020
Cheng Dang, Charles S. Zender, and Mark G. Flanner
The Cryosphere, 13, 2325–2343, https://doi.org/10.5194/tc-13-2325-2019, https://doi.org/10.5194/tc-13-2325-2019, 2019
Hanneke Luijting, Dagrun Vikhamar-Schuler, Trygve Aspelien, Åsmund Bakketun, and Mariken Homleid
The Cryosphere, 12, 2123–2145, https://doi.org/10.5194/tc-12-2123-2018, https://doi.org/10.5194/tc-12-2123-2018, 2018
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Knowledge of the snow reservoir is important for energy production and water resource management. In this study, a detailed snow model is run over southern Norway with two different sets of forcing data. The results show that forcing data consisting of post-processed data from a numerical weather model (observations assimilated into the raw weather predictions) are most promising for snow simulations when larger regions are evaluated.
Keith S. Jennings, Timothy G. F. Kittel, and Noah P. Molotch
The Cryosphere, 12, 1595–1614, https://doi.org/10.5194/tc-12-1595-2018, https://doi.org/10.5194/tc-12-1595-2018, 2018
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We show through observations and simulations that cold content, a key part of the snowpack energy budget, develops primarily through new snowfall. We also note that cold content damps snowmelt rate and timing at sub-seasonal timescales, while seasonal melt onset is controlled by the timing of peak cold content and total spring precipitation. This work has implications for how cold content is represented in snow models and improves our understanding of its effect on snowmelt processes.
Cited articles
Alt, B. T.: Developing synoptic analogs for extreme mass balance conditions
on Queen Elizabeth Island ice caps, J. Clim. Appl. Meteor., 26,
1605–1623, 1987.
Bintanja, R. and Andry, O.: Towards a rain-dominated Arctic, Nat. Clim.
Change., 7, 263–267, 2017.
Blazey, B. A., Holland, M. M., and Hunke, E. C.: Arctic Ocean sea ice snow
depth evaluation and bias sensitivity in CCSM, The Cryosphere, 7, 1887–1900,
https://doi.org/10.5194/tc-7-1887-2013, 2013.
Comiso, J. C. and Nishio, F.: Trends in the sea ice cover using enhanced
and compatible AMSR-E, SSM/I, and SMMR data, J. Geophys. Res., 113, C02S07,
https://doi.org/10.1029/2007JC004257, 2008.
Dingman, S. L.: Physical hydrology, 3rd edition, Waveland Press, Inc.
223–226, 2015.
Domine, F., Sparapani, R., Ianniello, A., and Beine, H. J.: The origin of sea
salt in snow on Arctic sea ice and in coastal regions, Atmos. Chem. Phys., 4,
2259–2271, https://doi.org/10.5194/acp-4-2259-2004, 2004.
Domine, F., Gallet, J. C., Bock, J., and Morin, S.: Structure, specific
surface area and thermal conductivity of the snowpack around Barrow, Alaska,
J. Geophys. Res., 117, D00R14, https://doi.org/10.1029/2011JD016647, 2012.
Douglas, T. A., Domine, F., Barret, M., Anastasio, C., Beine, H. J.,
Bottenheim, J., Grannas, A., Houdier, S., Netcheva, S., Rowland, G.,
Staebler, R., and Steffen, A.: Frost flowers growing in the Arctic
ocean-atmosphere-sea ice-snow interface: 1. Chemical composition, J.
Geophys. Res., 117, D00R09, https://doi.org/10.1029/2011JD016460, 2012.
Druckenmiller, M. L. and Haas, C.: Integrated Ice Observation Programs, Book
Chapter, Sea-Ice Handbook, edited by: Eicken, H., University of Alaska Press, 2009.
Eicken, H.:
Automated ice mass balance site (SIZONET), Arctic Data Center,
https://doi.org/10.18739/A2D08X, 2016.
Eicken, H., Grenfell, T. C., Perovich, D. K., Richter-Menge, J. A., and Frey, K.:
Hydraulic controls of summer Arctic pack ice albedo, J. Geophys. Res., 109,
C08007, https://doi.org/10.1029/2003JC001989, 2004.
Eicken, H., Gradinger, R., Heinrichs, T., Johnson, M. A., Lovecraft, A. L.,
and Kaufman, M.: Automated ice mass balance site (SIZONET), UCAR/NCAR – CISL –
ACADIS, Dataset, https://doi.org/10.5065/D6MW2F2H, 2012.
Geldsetzer, T., Langlois, A., and Yackel, J. J.: Dielectric properties of
brine-wetted snow on first-year sea ice, Cold Reg. Sci.
Technol., 58, 47–56, 2009.
Giles, K. A., Laxon, S. W., and Ridout, A. L.: Circumpolar thinning of
Arctic sea ice following the 2007 record ice extent minimum, Geophys. Res.
Lett., 35, L22502, https://doi.org/10.1029/2008GL035710, 2008.
Hall, D. K., Chang, A. T. C., and Foster, J. L.: Detection of the depth-hoar
layer in the snow-pack of the Arctic coastal plain of Alaska, U.S.A, using
satellite data, J. Glaciol., 32, 87–94, 1986.
Kwok, R. and Untersteiner, N.: The thinning of Arctic sea ice, Phys.
Today, 64, 36–41, 2011.
Kwok, R., Cunningham, G. F., Wensnahan, M., Rigor, I., Zwally, H. J., and
Yi, D.: Thinning and volume loss of the Arctic Ocean sea ice cover:
2003–2008, J. Geophys. Res., 114, C07005, https://doi.org/10.1029/2009JC005312, 2009.
Launiainen, J. and Chengm B. A.: simple non-iterative algorithm for
calculating turbulent bulk fluxes in diabatic conditions over water,
snow/ice and ground surface, Rep. Ser. Geophys., 33, p. 16, 1995.
Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J., Willatt, R.,
Cullen, R., Kwok, R., Schweiger, A., Zhang, J., Haas, C., Hendricks, S.,
Krishfield, R., Kurtz, N., Farrell, S., and Davidson, M.: CryoSat-2
estimates of Arctic sea ice thickness and volume, Geophys. Res. Lett., 40,
732–737, https://doi.org/10.1002/grl.50193, 2013.
Martin, S.: A field study of brine drainage and oil entrapment in first-year
sea ice, J. Glaciol., 22, 473–502, 1979.
Maslanik, J., Drobot, S., Fowler, C., Emery, W., and Barry, R.: On the
Arctic climate paradox and the continuing role of atmospheric circulation in
affecting sea ice conditions, Geophys. Res. Lett., 34, L03711,
https://doi.org/10.1029/2006GL028269, 2007.
Maslanik, J., Stroeve, J., Fowler, C., and Emery, W.: Distribution and
trends in Arctic sea ice age through spring 2011, Geophys. Res. Lett., 38,
L13502, https://doi.org/10.1029/2011GL047735, 2011.
Maykut, G. A.: The surface heat and mass balance, in: The geophysics of sea ice,
edited by: Untersteiner, N., New York, Plenum Press, 395–463, 1986.
Maykut, G. A. and Untersteiner, N.: Some results from a time dependent
thermodynamic model of sea ice, J. Geophys. Res., 76, 1550–1575, 1971.
Mortin, J., Svensson, G., Graversen, R. G., Kapsch, M. L., Stroeve, J. C.,
and Boisvert, L. N.: Melt onset over Arctic sea ice controlled by
atmospheric moisture transport, Geophys. Res. Lett., 43, 6636–6642, 2016.
Nghiem, S. V., Rigor, I. G., Perovich, D. K., Clemente-Colón, P.,
Weatherly, J. W., and Neumann, G.: Rapid reduction of Arctic perennial sea
ice, Geophys. Res. Lett., 34, L19504, https://doi.org/10.1029/2007GL031138, 2007.
Notz, D.: The future of ice sheets and sea ice: Between reversible retreat
and unstoppable loss, P. Natl. Acad. Sci. USA, 106, 20590–20595, 2009.
Perovich, D. K. and Polashenski, C.: Albedo evolution of seasonal Arctic
sea ice, Geophys. Res. Lett., 39, L08501, https://doi.org/10.1029/2012GL051432, 2012.
Perovich, D. K., Bruce, C. E., and Richter-Menge, J. A.: Observations of the
annual cycle of sea ice 824 temperature, Geophys. Res. Lett., 24,
555–558, 1997.
Perovich, D. K., Grenfell, T. C., Light, B., and Hobbs, P. V.: Seasonal
evolution of the albedo of multiyear Arctic sea ice, J. Geophys. Res.,
107, 8044, https://doi.org/10.1029/2000JC000438, 2002.
Perovich, D., Polashenski, C., Arntsen, A., and Stwertka, C.: Anatomy of
a late spring snowfall on sea ice, Geophys. Res. Lett., 44, 2802–2809,
https://doi.org/10.1002/2016GL071470, 2017.
Persson, P. and Ola, G.: Onset and end of the summer melt season over sea ice:
thermal structure and surface energy perspective from SHEBA, Clim. Dynam., 39,
1349–1371, 2012.
Persson, P., Ola, G., Ruffieux, D., and Fairall, C. W.: Recalculations of pack ice
and lead surface energy budgets during LEADEX 92, J. Geophys. Res., 102,
25085–25089, 1997.
Petrich, C., Eicken, H., Polashenski, C. M., Sturm, M., Harbeck, J. P.,
Perovich, D. K., and Finnegan, D. C.: Snow dunes: A controlling factor of
melt pond distribution on Arctic sea ice, J. Geophys. Res., 117, C09029,
https://doi.org/10.1029/2012JC008192, 2012.
Screen, J. A. and Simmonds, I.: Declining summer snowfall in the Arctic:
Causes, impacts and feedbacks, Clim. Dynam., 38, 2243–2256, 2012.
Sharp, M. and Wang, L.: A five-year record of summer melt on Eurasian
Arctic ice caps, J. Climate, 22, 133–145, 2009.
Stone, R. S., Dutton, E. G., Harris, J. M., and Longenecker, D.: Earlier spring
snowmelt in northern Alaska as an indicator of climate change, J. Geophys.
Res., 107, 4089, https://doi.org/10.1029/2000JD000286, 2002.
Stroeve, J., Holland, M. M., Meier, W., Scambos, T., and Serreze, M.: Arctic
sea ice decline: Faster than forecast, Geophys. Res. Lett., 34, L09501,
https://doi.org/10.1029/2007GL029703, 2007.
Stroeve, J. C., Holland, M. M., Kay, J. E., Malanik, J., and Barrett, A. P.:
The Arctic's rapidly shrinking sea ice cover: A research synthesis, Clim.
Change, 110, 1005–1027, 2012.
Stroeve, J. C., Markus, T., Boisvert, L., Miller, J., and Barrett, A.:
Changes in Arctic melt season and implications for sea ice loss, Geophys.
Res. Lett., 41, 1216–1225, 2014.
Sturm, M., Perovich, D. K., and Holmgren, J.: Thermal conductivity and heat
transfer through the snow on the ice of the Beaufort Sea, J. Geophys. Res.,
107, 8043, https://doi.org/10.1029/2000JC000409, 2002.
Tucker III, W. B., Perovich, D. K., Gow, A. J., Weeks, W. F., and Drinkwater,
M. R.: Physical properties of sea ice relevant to remote sensing, in: Microwave Remote Sensing of Sea Ice,
edited by: Carsey, F., Geophysical Monograph, American Geophysical Union, 9–28, Chapter 2, 1992.
Wang, L., Sharp, M. J., Rivard, B., Marshall, S., and Burgess, D.: Melt
season duration on Canadian Arctic ice caps, 2000–2004, Geophys. Res.
Lett., 32, L19502, https://doi.org/10.1029/2005GL023962, 2005.
Webster, M. A., Rigor, I., Nghiem, S. V., Kurtz, N. T., Farrell, S. L.,
Perovich, D. K., and Sturm, M.: Interdecadal changes in snow depth on Arctic
sea ice, J. Geophys. Res., 119, 5395–5406, https://doi.org/10.1002/2014JC009985, 2014.
Yen, Y.: Review of thermal properties of snow, ice and sea ice, US Army Cold
Regions Research and Engineering Laboratory, Report 81–10, Hanover, NH,
USA, 1981.
Short summary
The variability and potential trends of rain-on-snow events over Arctic sea ice and their role in sea-ice losses are poorly understood. This study demonstrates that rain-on-snow events are a critical factor in initiating the onset of surface melt over Arctic sea ice, and onset of spring rainfall over sea ice has shifted to earlier dates since the 1970s, which may have profound impacts on ice melt through feedbacks involving earlier onset of surface melt.
The variability and potential trends of rain-on-snow events over Arctic sea ice and their role...