Articles | Volume 15, issue 2
https://doi.org/10.5194/tc-15-883-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-883-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Feb 2021
Research article |
| 19 Feb 2021
| 19 Feb 2021
Trends and spatial variation in rain-on-snow events over the Arctic Ocean during the early melt season
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 100049, China
Cunde Xiao
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Beijing Normal University, Beijing 100875, China
Jiping Liu
Department of Atmospheric and Environmental Sciences, University at
Albany, State University of New York, Albany, NY, USA
Qiang Wang
Alfred Wegener Institute Helmholtz Centre for Polar and Marine
Research, Bremerhaven, Germany
Shifeng Pan
College of atmospheric science, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Physical Oceanography Laboratory, Ocean University of China, 238
Songling Road, Qingdao 266100, China
Xiaojun Yuan
Lamont-Doherty Earth Observatory, Columbia University, 61 Route 9W,
Palisades, NY 10964, USA
Minghu Ding
Institute of Tibetan Plateau and Polar Meteorology, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Feng Zhang
Institute of Atmospheric Sciences, Fudan University, Shanghai 200438,
China/Shanghai Qi Zhi Institute, Shanghai 200232, China
Kai Xue
College of Resources and Environment, University of Chinese Academy of
Sciences, Beijing 100049, China
Peter A. Bieniek
International Arctic Research Center, University of Alaska Fairbanks,
Fairbanks, AK 99775-7340, USA
Hajo Eicken
International Arctic Research Center, University of Alaska Fairbanks,
Fairbanks, AK 99775-7340, USA
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
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.
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 %).
Tingfeng Dou, Cunde Xiao, Jiping Liu, Wei Han, Zhiheng Du, Andrew R. Mahoney, Joshua Jones, and Hajo Eicken
The Cryosphere, 13, 1233–1246, https://doi.org/10.5194/tc-13-1233-2019, https://doi.org/10.5194/tc-13-1233-2019, 2019
Short summary
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.
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
Tianming Ma, Zhuang Jiang, Minghu Ding, Pengzhen He, Yuansheng Li, Wenqian Zhang, and Lei Geng
The Cryosphere, 18, 4547–4565, https://doi.org/10.5194/tc-18-4547-2024, https://doi.org/10.5194/tc-18-4547-2024, 2024
Short summary
Short summary
We constructed a box model to evaluate the isotope effects of atmosphere–snow water vapor exchange at Dome A, Antarctica. The results show clear and invisible diurnal changes in surface snow isotopes under summer and winter conditions, respectively. The model also predicts that the annual net effects of atmosphere–snow water vapor exchange would be overall enrichments in snow isotopes since the effects in summer appear to be greater than those in winter at the study site.
Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana Loza, Wonsun Park, Woncheol Roh, Dmitry V. Sein, Sahil Sharma, Dmitry Sidorenko, Jun-Hyeok Son, Malte F. Stuecker, Qiang Wang, Gyuseok Yi, Martina Zapponini, Thomas Jung, and Axel Timmermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-2491, https://doi.org/10.5194/egusphere-2024-2491, 2024
Short summary
Short summary
Based on a series of storm-resolving greenhouse warming simulations conducted with the AWI-CM3 model at 9 km global atmosphere, 4–25 km ocean resolution, we present new projections of regional climate change, modes of climate variability and extreme events. The 10-year-long high resolution simulations for the 2000s, 2030s, 2060s, 2090s were initialized from a coarser resolution transient run (31 km atmosphere) which follows the SSP5-8.5 greenhouse gas emission scenario from 1950–2100 CE.
Lijing Chen, Lei Zhang, Yong She, Zhaoliang Zeng, Yu Zheng, Biao Tian, Wenqian Zhang, Zhaohui Liu, and Minghu Ding
EGUsphere, https://doi.org/10.5194/egusphere-2024-798, https://doi.org/10.5194/egusphere-2024-798, 2024
Short summary
Short summary
AOD at Zhongshan Station varies seasonally, with lower values in summer and higher values in winter. Winter and spring AOD increases due to reduced fine mode particles, while summer and autumn increases are linked to particle growth. Duirnal AOD variation correlates positively with temperature but negatively with wind speed and humidity. Backward trajectory shows aerosols on high (low) AOD days primarily originate from the ocean (interior Antarctica).
Yueli Chen, Yun Xie, Xingwu Duan, and Minghu Ding
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-195, https://doi.org/10.5194/essd-2024-195, 2024
Revised manuscript under review for ESSD
Short summary
Short summary
Rainfall erosivity map is crucial for identifying key areas of water erosion. Due to the limited historical precipitation data, there are certain biases in rainfall erosivity estimates in China. This study develops a new rainfall erosivity map for mainland China using 1-minute precipitation data from 60,129 weather stations, revealing that areas exceeding 4000 MJ·mm·ha−1·h−1·yr−1 of annual rainfall erosivity mainly concentrated in the southern China and southern Tibetan Plateau.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tong Zhang, William Colgan, Agnes Wansing, Anja Løkkegaard, Gunter Leguy, William H. Lipscomb, and Cunde Xiao
The Cryosphere, 18, 387–402, https://doi.org/10.5194/tc-18-387-2024, https://doi.org/10.5194/tc-18-387-2024, 2024
Short summary
Short summary
The geothermal heat flux determines how much heat enters from beneath the ice sheet, and thus impacts the temperature and the flow of the ice sheet. In this study we investigate how much geothermal heat flux impacts the initialization of the Greenland ice sheet. We use the Community Ice Sheet Model with two different initialization methods. We find a non-trivial influence of the choice of heat flow boundary conditions on the ice sheet initializations for further designs of ice sheet modeling.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
Short summary
Short summary
We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Elizabeth R. Thomas, Diana O. Vladimirova, Dieter R. Tetzner, B. Daniel Emanuelsson, Nathan Chellman, Daniel A. Dixon, Hugues Goosse, Mackenzie M. Grieman, Amy C. F. King, Michael Sigl, Danielle G. Udy, Tessa R. Vance, Dominic A. Winski, V. Holly L. Winton, Nancy A. N. Bertler, Akira Hori, Chavarukonam M. Laluraj, Joseph R. McConnell, Yuko Motizuki, Kazuya Takahashi, Hideaki Motoyama, Yoichi Nakai, Franciéle Schwanck, Jefferson Cardia Simões, Filipe Gaudie Ley Lindau, Mirko Severi, Rita Traversi, Sarah Wauthy, Cunde Xiao, Jiao Yang, Ellen Mosely-Thompson, Tamara V. Khodzher, Ludmila P. Golobokova, and Alexey A. Ekaykin
Earth Syst. Sci. Data, 15, 2517–2532, https://doi.org/10.5194/essd-15-2517-2023, https://doi.org/10.5194/essd-15-2517-2023, 2023
Short summary
Short summary
The concentration of sodium and sulfate measured in Antarctic ice cores is related to changes in both sea ice and winds. Here we have compiled a database of sodium and sulfate records from 105 ice core sites in Antarctica. The records span all, or part, of the past 2000 years. The records will improve our understanding of how winds and sea ice have changed in the past and how they have influenced the climate of Antarctica over the past 2000 years.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Shanice T. Bailey, C. Spencer Jones, Ryan P. Abernathey, Arnold L. Gordon, and Xiaojun Yuan
Ocean Sci., 19, 381–402, https://doi.org/10.5194/os-19-381-2023, https://doi.org/10.5194/os-19-381-2023, 2023
Short summary
Short summary
This study explores the variability of water mass transformation within the Weddell Gyre (WG). The WG is the largest source of Antarctic Bottom Water (AABW). Changes to our climate can modify the mechanisms that transform waters to become AABW. In this study, we computed water mass transformation volume budgets by using three ocean models and a mathematical framework developed by Walin. Out of the three models, we found one to be most useful in studying the interannual variability of AABW.
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, 14, 5349–5365, https://doi.org/10.5194/essd-14-5349-2022, https://doi.org/10.5194/essd-14-5349-2022, 2022
Short summary
Short summary
A dataset of the radiogenic strontium and neodymium isotopic compositions from the three poles (the third pole, the 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 sources and sinks. The purpose of this dataset is to try to determine the variable transport pathways of dust at three poles.
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, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
Short summary
Short summary
The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
John E. Walsh, Hajo Eicken, Kyle Redilla, and Mark Johnson
The Cryosphere, 16, 4617–4635, https://doi.org/10.5194/tc-16-4617-2022, https://doi.org/10.5194/tc-16-4617-2022, 2022
Short summary
Short summary
Indicators for the start and end of annual breakup 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 breakup, especially at locations where landfast ice is prominent. However, the trends towards earlier breakup and later freeze-up are unmistakable over the post-1979 period in synthesized metrics of the coastal breakup/freeze-up indicators.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
Short summary
Short summary
We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, https://doi.org/10.5194/gmd-15-5829-2022, 2022
Short summary
Short summary
Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.
Yueli Chen, Xingwu Duan, Minghu Ding, Wei Qi, Ting Wei, Jianduo Li, and Yun Xie
Earth Syst. Sci. Data, 14, 2681–2695, https://doi.org/10.5194/essd-14-2681-2022, https://doi.org/10.5194/essd-14-2681-2022, 2022
Short summary
Short summary
We reconstructed the first annual rainfall erosivity dataset for the Tibetan Plateau in China. The dataset covers 71 years in a 0.25° grid. The reanalysis precipitation data are employed in combination with the densely spaced in situ precipitation observations to generate the dataset. The dataset can supply fundamental data for quantifying the water erosion, and extend our knowledge of the rainfall-related hazard prediction on the Tibetan Plateau.
Kees Nederhoff, Li Erikson, Anita Engelstad, Peter Bieniek, and Jeremy Kasper
The Cryosphere, 16, 1609–1629, https://doi.org/10.5194/tc-16-1609-2022, https://doi.org/10.5194/tc-16-1609-2022, 2022
Short summary
Short summary
Diminishing sea ice is impacting waves across the Arctic region. Recent work shows the effect of the sea ice on offshore waves; however, effects within the nearshore are less known. This study characterizes the wave climate in the central Beaufort Sea coast of Alaska. We show that the reduction of sea ice correlates strongly with increases in the average and extreme waves. However, found trends deviate from offshore, since part of the increase in energy is dissipated before reaching the shore.
Yunhe Wang, Xiaojun Yuan, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, and Haijun Huang
The Cryosphere, 16, 1141–1156, https://doi.org/10.5194/tc-16-1141-2022, https://doi.org/10.5194/tc-16-1141-2022, 2022
Short summary
Short summary
We develop a regional linear Markov model consisting of four modules with seasonally dependent variables in the Pacific sector. The model retains skill for detrended sea ice extent predictions for up to 7-month lead times in the Bering Sea and the Sea of Okhotsk. The prediction skill, as measured by the percentage of grid points with significant correlations (PGS), increased by 75 % in the Bering Sea and 16 % in the Sea of Okhotsk relative to the earlier pan-Arctic model.
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, https://doi.org/10.5194/gmd-15-335-2022, 2022
Short summary
Short summary
Structured-mesh ocean models are still the most mature in terms of functionality due to their long development history. However, unstructured-mesh ocean models have acquired new features and caught up in their functionality. This paper continues the work by Scholz et al. (2019) of documenting the features available in FESOM2.0. It focuses on the following two aspects: (i) partial bottom cells and embedded sea ice and (ii) dealing with mixing parameterisations enabled by using the CVMix package.
Qiang Wang, Sergey Danilov, Longjiang Mu, Dmitry Sidorenko, and Claudia Wekerle
The Cryosphere, 15, 4703–4725, https://doi.org/10.5194/tc-15-4703-2021, https://doi.org/10.5194/tc-15-4703-2021, 2021
Short summary
Short summary
Using simulations, we found that changes in ocean freshwater content induced by wind perturbations can significantly affect the Arctic sea ice drift, thickness, concentration and deformation rates years after the wind perturbations. The impact is through changes in sea surface height and surface geostrophic currents and the most pronounced in warm seasons. Such a lasting impact might become stronger in a warming climate and implies the importance of ocean initialization in sea ice prediction.
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.
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
Short summary
Short summary
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.
Shiming Xu, Jialiang Ma, Lu Zhou, Yan Zhang, Jiping Liu, and Bin Wang
Geosci. Model Dev., 14, 603–628, https://doi.org/10.5194/gmd-14-603-2021, https://doi.org/10.5194/gmd-14-603-2021, 2021
Short summary
Short summary
A multi-resolution tripolar grid hierarchy is constructed and integrated in CESM (version 1.2.1). The resolution range includes 0.45, 0.15, and 0.05°. Based on atmospherically forced sea ice experiments, the model simulates reasonable sea ice kinematics and scaling properties. Landfast ice thickness can also be systematically shifted due to non-convergent solutions to an
elastic–viscous–plastic (EVP) model. This work is a framework for multi-scale modeling of the ocean and sea ice with CESM.
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
Short summary
Short summary
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.
Claudia Wekerle, Tore Hattermann, Qiang Wang, Laura Crews, Wilken-Jon von Appen, and Sergey Danilov
Ocean Sci., 16, 1225–1246, https://doi.org/10.5194/os-16-1225-2020, https://doi.org/10.5194/os-16-1225-2020, 2020
Short summary
Short summary
The high-resolution ocean models ROMS and FESOM configured for the Fram Strait reveal very energetic ocean conditions there. The two main currents meander strongly and shed circular currents of water, called eddies. Our analysis shows that this region is characterised by small and short-lived eddies (on average around a 5 km radius and 10 d lifetime). Both models agree on eddy properties and show similar patterns of baroclinic and barotropic instability of the West Spitsbergen Current.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, https://doi.org/10.5194/gmd-13-4595-2020, 2020
Short summary
Short summary
This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
Short summary
Short summary
The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
J. Su, P. Yu, Y. Qin, G. Zhang, and M. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 893–898, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-893-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-893-2020, 2020
Dmitry Sidorenko, Sergey Danilov, Nikolay Koldunov, Patrick Scholz, and Qiang Wang
Geosci. Model Dev., 13, 3337–3345, https://doi.org/10.5194/gmd-13-3337-2020, https://doi.org/10.5194/gmd-13-3337-2020, 2020
Short summary
Short summary
Computation of barotropic and meridional overturning streamfunctions for models formulated on unstructured meshes is commonly preceded by interpolation to a regular mesh. This operation destroys the original conservation, which can be then be artificially imposed to make the computation possible. An elementary method is proposed that avoids interpolation and preserves conservation in a strict model sense.
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
Short summary
Short summary
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 %).
Patrick Scholz, Dmitry Sidorenko, Ozgur Gurses, Sergey Danilov, Nikolay Koldunov, Qiang Wang, Dmitry Sein, Margarita Smolentseva, Natalja Rakowsky, and Thomas Jung
Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, https://doi.org/10.5194/gmd-12-4875-2019, 2019
Short summary
Short summary
This paper is the first in a series documenting and assessing important key components of the Finite-volumE Sea ice-Ocean Model version 2.0 (FESOM2.0). We assess the hydrographic biases, large-scale circulation, numerical performance and scalability of FESOM2.0 compared with its predecessor, FESOM1.4. The main conclusion is that the results of FESOM2.0 compare well to FESOM1.4 in terms of model biases but with a remarkable performance speedup with a 3 times higher throughput.
Özgür Gürses, Vanessa Kolatschek, Qiang Wang, and Christian Bernd Rodehacke
The Cryosphere, 13, 2317–2324, https://doi.org/10.5194/tc-13-2317-2019, https://doi.org/10.5194/tc-13-2317-2019, 2019
Short summary
Short summary
The warming of the Earth's climate system causes sea level rise. In Antarctica, ice streams flow into the sea and develop ice shelves. These are floating extensions of the ice streams. Ocean water melts these ice shelves. It has been proposed that a submarine wall could shield these ice shelves from the warm water. Our model simulation shows that the wall protects ice shelves. However, the warm water flows to neighboring ice shelves. There, enhanced melting reduces the effectiveness of the wall.
Thomas Rackow, Dmitry V. Sein, Tido Semmler, Sergey Danilov, Nikolay V. Koldunov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, https://doi.org/10.5194/gmd-12-2635-2019, 2019
Short summary
Short summary
Current climate models show errors in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. These errors are larger than the signals we aim to predict. With the AWI Climate Model, we show that increasing resolution to resolve eddies can lead to major reductions in deep ocean errors. AWI's next-generation (CMIP6) model configuration will thus use locally eddy-resolving computational grids for projecting climate change.
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
Short summary
Short summary
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.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Wei Han, Zhiheng Du, Andrew R. Mahoney, Joshua Jones, and Hajo Eicken
The Cryosphere, 13, 1233–1246, https://doi.org/10.5194/tc-13-1233-2019, https://doi.org/10.5194/tc-13-1233-2019, 2019
Short summary
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.
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
Short summary
Short summary
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.
S. Li, F. Zhang, Q.-R. Yu, K. L. Chan, C. Hou, R. Guo, and M. Duan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 47–52, https://doi.org/10.5194/isprs-archives-XLII-3-W5-47-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-47-2018, 2018
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
Short summary
Short summary
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.
Qiang Wang, Claudia Wekerle, Sergey Danilov, Xuezhu Wang, and Thomas Jung
Geosci. Model Dev., 11, 1229–1255, https://doi.org/10.5194/gmd-11-1229-2018, https://doi.org/10.5194/gmd-11-1229-2018, 2018
Short summary
Short summary
For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer. The high resolution also improves the ocean surface circulation, mainly through a better representation of the Canadian Arctic Archipelago.
Yuzhe Wang, Tong Zhang, Jiawen Ren, Xiang Qin, Yushuo Liu, Weijun Sun, Jizu Chen, Minghu Ding, Wentao Du, and Dahe Qin
The Cryosphere, 12, 851–866, https://doi.org/10.5194/tc-12-851-2018, https://doi.org/10.5194/tc-12-851-2018, 2018
Short summary
Short summary
We combine in situ measurements and an ice flow model to study the thermomechanical features of Laohugou Glacier No. 12, the largest valley glacier on Qilian Shan. We reveal that this glacier, once considered to be extremely continental or cold, is actually polythermal with a lower temperate ice layer over a large region of the ablation area. Strain heating and latent heat due to meltwater refreezing in the firn zone play critical roles in controlling the thermal regime of this glacier.
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
Short summary
Short summary
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.
Sergey Danilov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 10, 765–789, https://doi.org/10.5194/gmd-10-765-2017, https://doi.org/10.5194/gmd-10-765-2017, 2017
Short summary
Short summary
Numerical models of global ocean circulation are used to learn about future climate. The ocean circulation is characterized by processes on different spatial scales which are still beyond the reach of present computers. We describe a new model setup that allows one to vary a model's spatial resolution and hence focus the computational power on regional dynamics, reaching a better description of local processes in areas of interest.
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
Short summary
Short summary
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.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
Short summary
Short summary
The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
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
Short summary
Short summary
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.
S. Danilov, Q. Wang, R. Timmermann, N. Iakovlev, D. Sidorenko, M. Kimmritz, T. Jung, and J. Schröter
Geosci. Model Dev., 8, 1747–1761, https://doi.org/10.5194/gmd-8-1747-2015, https://doi.org/10.5194/gmd-8-1747-2015, 2015
Short summary
Short summary
Unstructured meshes allow multi-resolution modeling of ocean dynamics. Sea ice models formulated on unstructured meshes are a necessary component of ocean models intended for climate studies. This work presents a description of a finite-element sea ice model which is used as a component of a finite-element sea ice ocean circulation model. The principles underlying its design can be of interest to other groups pursuing ocean modelling on unstructured meshes.
D. Ji, L. Wang, J. Feng, Q. Wu, H. Cheng, Q. Zhang, J. Yang, W. Dong, Y. Dai, D. Gong, R.-H. Zhang, X. Wang, J. Liu, J. C. Moore, D. Chen, and M. Zhou
Geosci. Model Dev., 7, 2039–2064, https://doi.org/10.5194/gmd-7-2039-2014, https://doi.org/10.5194/gmd-7-2039-2014, 2014
Q. Wang, S. Danilov, D. Sidorenko, R. Timmermann, C. Wekerle, X. Wang, T. Jung, and J. Schröter
Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, https://doi.org/10.5194/gmd-7-663-2014, 2014
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
Discipline: Other | Subject: Arctic (e.g. Greenland)
Characterizing southeast Greenland fjord surface ice and freshwater flux to support biological applications
Early spring subglacial discharge plumes fuel under-ice primary production at a Svalbard tidewater glacier
Arctic freshwater fluxes: sources, tracer budgets and inconsistencies
Dynamic ocean topography of the northern Nordic seas: a comparison between satellite altimetry and ocean modeling
Twila A. Moon, Benjamin Cohen, Taryn E. Black, Kristin L. Laidre, Harry L. Stern, and Ian Joughin
The Cryosphere, 18, 4845–4872, https://doi.org/10.5194/tc-18-4845-2024, https://doi.org/10.5194/tc-18-4845-2024, 2024
Short summary
Short summary
The complex geomorphology of southeast Greenland (SEG) creates dynamic fjord habitats for top marine predators, featuring glacier-derived floating ice, pack and landfast sea ice, and freshwater flux. We study the physical environment of SEG fjords, focusing on surface ice conditions, to provide a regional characterization that supports biological research. As Arctic warming persists, SEG may serve as a long-term refugium for ice-dependent wildlife due to the persistence of regional ice sheets.
Tobias Reiner Vonnahme, Emma Persson, Ulrike Dietrich, Eva Hejdukova, Christine Dybwad, Josef Elster, Melissa Chierici, and Rolf Gradinger
The Cryosphere, 15, 2083–2107, https://doi.org/10.5194/tc-15-2083-2021, https://doi.org/10.5194/tc-15-2083-2021, 2021
Short summary
Short summary
We describe the impact of subglacial discharge in early spring on a sea-ice-covered fjord on Svalbard by comparing a site influenced by a shallow tidewater glacier with two reference sites. We found a moderate under-ice phytoplankton bloom at the glacier front, which we attribute to subglacial upwelling of nutrients; a strongly stratified surface layer; and higher light penetration. In contrast, sea ice algae biomass was limited by low salinities and brine volumes.
Alexander Forryan, Sheldon Bacon, Takamasa Tsubouchi, Sinhué Torres-Valdés, and Alberto C. Naveira Garabato
The Cryosphere, 13, 2111–2131, https://doi.org/10.5194/tc-13-2111-2019, https://doi.org/10.5194/tc-13-2111-2019, 2019
Short summary
Short summary
We compare control volume and geochemical tracer-based methods of estimating the Arctic Ocean freshwater budget and find both methods in good agreement. Inconsistencies arise from the distinction between
Atlanticand
Pacificwaters in the geochemical calculations. The definition of Pacific waters is particularly problematic due to the non-conservative nature of the nutrients underpinning the definition and the low salinity characterizing waters entering the Arctic through Bering Strait.
Felix L. Müller, Claudia Wekerle, Denise Dettmering, Marcello Passaro, Wolfgang Bosch, and Florian Seitz
The Cryosphere, 13, 611–626, https://doi.org/10.5194/tc-13-611-2019, https://doi.org/10.5194/tc-13-611-2019, 2019
Short summary
Short summary
Knowledge of the dynamic ocean topography (DOT) enables studying changes of ocean surface currents. The DOT can be derived by satellite altimetry measurements or by models. However, in polar regions, altimetry-derived sea surface heights are affected by sea ice. Model representations are consistent but impacted by the underlying functional backgrounds and forcing models. The present study compares results from both data sources in order to investigate the potential for a combination of the two.
Cited articles
Alaska Climate Research Center: ACIS Daily Data Browser, available at: http://climate.gi.alaska.edu/acis_data, last access: 28 July 2020.
Belington, P. R. and Robinson, D. K.: Data Reduction and Error Analysis for
the Physical Sciences, edn. 3, McGraw-Hill Education, University of California, 320 pp., 2003.
Bi, H., Yang, Q., Liang, X., Zhang, L., Wang, Y., Liang, Y., and Huang, H.: Contributions of advection and melting processes to the decline in sea ice in the Pacific sector of the Arctic Ocean, The Cryosphere, 13, 1423–1439, https://doi.org/10.5194/tc-13-1423-2019, 2019.
Bieniek, P. A., Bhatt, U. S., Walsh, J. E., Lader, R., Griffith, B., Roach, J. K., and Thoman, R. L.: Assessment of Alaska rain-on-snow events using dynamical downscaling, J. Appl. Meteorol. Climatol., 57, 1847–1863, https://doi.org/10.1175/JAMC-D-17-0276.1, 2018.
Bintanja, R. and Andry, O.: Towards a rain-dominated Arctic, Nat. Clim.
Change, 7, 263–267, 2017.
Birsan, M. V., Molnar, P., Burlando, P., and Faundler, M. P.: Streamflow
trends in Switzerland, J. Hydrol., 314, 312–329, 2005.
Boisvert, L. N., Webster, M. A., Petty, A. A., Markus, T., Bromwich, D. H., and Cullather, R. I.: Intercomparison of
precipitation estimates over the Arctic Ocean and its peripheral seas from
reanalyses, J. Climate, 31, 8441–8462, 2018.
Box, G. E. P., Hunter, J. S., and Hunter, W. G.: Statistics for
Experimenters: Design, Innovation, and Discovery, edn. 2, John Wiley &
Sons Inc., USA, 672 pp., 2005.
Casson, N. J., Eimers, M. C., and Buttle, J. M.: The contribution of
rain-on-snow events to nitrate export in the forested landscape of
southcentral Ontario, Canada, Hydrol. Process., 24, 1985–1993, 2010.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim
reanalysis: configuration and performance of the data assimilation system,
Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011 (data available at: https://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/, last access: 12 August 2020).
Dou, T., Xiao, C., Liu, J., Han, W., Du, Z., Mahoney, A. R., Jones, J., and Eicken, H.: A key factor initiating surface ablation of Arctic sea ice: earlier and increasing liquid precipitation, The Cryosphere, 13, 1233–1246, https://doi.org/10.5194/tc-13-1233-2019, 2019.
Dutra, E., Schär, C., Viterbo, P., and Miranda, P. M. A.: Land
atmosphere coupling associated with snow cover, Geophys. Res. Lett., 38,
L15707, https://doi.org/10.1029/2011GL048435, 2011.
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.
Ferraro, R. R., Peters-Lidard, C. D., Hernandez, C., Turk, F. J., Aires, F.,
Prigent, C., Lin, X., Boukabara, S.-A., Furuzawa, F. A., Gopalan, K.,
Harrison, K. W., Karbou, F., Li, L., Liu, C., Masunaga, H., Moy, L.,
Ringerud, S., Skofronick-Jackson, G. M., Tian, Y., and Wang, N.-Y.: An
Evaluation of Microwave Land Surface Emissivities Over the Continental
United States to Benefit GPM-Era Precipitation Algorithms,
IEEE T. Geosci. Remote, 51, 378–398, 2013.
Fetterer, F., Knowles, K., Meier, W., Savoie, M., and Windnagel, A. K.: Sea Ice Index, Version 3 (Boulder, CO: NSIDC National Snow and Ice Data Center), https://doi.org/10.7265/N5K072F8, 2017.
Førland, E. J., Isaksen, K., Lutz, J., Hanssen-Bauer, I., Schuler, T. V.,
Dobler, A., Gjelten, H. M., and Vikhamar-Schuler, D.: Measured and Modeled
Historical Precipitation Trends for Svalbard, J. Hydrometeorol., 21,
1279–1296, https://doi.org/10.1175/JHM-D-19-0252.1, 2020.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Gloersen, P., Campbell, W. J., Cavalieri, D. J., Comiso, J. C., Parkinson,
C., and Zwally, H. J.: Satellite passive microwave observations and analysis
of Arctic and Antarctic sea ice, 1978–1987, Ann. Glaciol., 17, 149–154, 1993.
Han, W., Xiao, C., Dou, T., and Ding, M.: Arctic has been going through a
transition from solid precipitation to liquid precipitation in spring,
Chinese Sci. Bull., 63, 1154–1162, https://doi.org/10.1360/N972018-00088, 2018 (in Chinese).
Hegyi, B. M. and Deng Y.: Dynamical and thermodynamical impacts of high- and
low-frequency atmospheric eddies on the initial melt of Arctic sea ice, J. Climate, 30, 865–883, 2017.
Hersbach, H. and Dee, D.: ERA5 reanalysis is in production, ECMWF Newsletter
147, ECMWF, available at:
https://www.ecmwf.int/en/newsletter/147/news/era5-reanalysis-production
(last access: 24 March 2017), 2016 (data available at: https://cds.climate.copernicus.eu/cdsapp#/dataset/reanalysis-era5-single-levels-monthlymeans?tab=form, last access: 12 August 2020).
Huang, Y., Dong, X., Xi, B., and Deng, Y.: A survey of the atmospheric
physical processes key to the onset of Arctic sea ice melt in spring,
Clim. Dynam., 52, 4907–4922, 2019.
Jeong, D. I., Sushama, L., and Khaliq, M. N.: Attribution of spring snow
water equivalent (SWE) changes over the northern hemisphere to anthropogenic
effects, Clim. Dynam., 48, 3645–3658, https://doi.org/10.1007/s00382-016-3291-4, 2016.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40 Year Reanalysis Project, B. Am. Meteorol. Soc., 77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Kapsch, M. L., Graversen, R. G., Tjernström, M., and Bintanja, R.: The
effect of downwelling longwave and shortwave radiation on Arctic summer sea
ice, J. Climate, 29, 1143–1159, 2016.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.: The JRA-55 Reanalysis: General specifications and basic characteristics, J. Meteorol. Soc. Jpn., 93, 5–48, https://doi.org/10.2151/jmsj.2015-001,
2015 (data available at: https://climatedataguide.ucar.edu/climate-data/jra-55, last access: 12 August 2020).
Kug, J. S., Choi, D. H., Jin, F. F., Kwon, W. T., and Ren, H. L.: Role of
synoptic eddy feedback on polar climate responses to the anthropogenic
forcing, Geophys. Res. Lett., 37, L14704, https://doi.org/10.1029/2010GL043673, 2010.
Kwok, R., Cunningham, G. F., Kacimi, S., Webster, M. A., Kurtz, N. T., and
Petty, A. A.: Decay of the snow cover over Arctic sea ice from ICESat-2
acquisitions during summer melt in 2019, Geophys. Res. Lett., 47,
e2020GL088209, https://doi.org/10.1029/2020GL088209, 2020.
Lee, H. J., Kwon, M. O., and Yeh, S. W.: Impact of poleward moisture
transport from the North Pacific on the acceleration of sea ice loss in the
Arctic since 2002, J. Climate, 30, 6757–6769, 2017.
Leeuw, J. D., Methven, J., and Blackburn, M.: Evaluation of ERA-Interim
reanalysis precipitation products using England and Wales observations,
Q. J. Roy. Meteorol. Soc., 141, 798–806, https://doi.org/10.1002/qj.2395, 2015.
Lindsay, R., Wensnahan, M., Schweiger, A., and Zhang, J.: Evaluation of
Seven Different Atmospheric Reanalysis Products in the Arctic, J. Climate,
27, 2588–2606, 2014.
Liu, Z. and Schweiger, A.: Synoptic conditions, clouds, and sea ice melt
onset in the beaufort and chukchi seasonal ice zone, J. Climate, 30,
6999–7016, 2017.
Markus, T. and Cavalieri, D. J.: An enhancement of the NASA Team sea ice
algorithm, IEEE T. Geosci. Remote, 38, 1387–1398, 2000.
Markus, T., Stroeve, J. C., and Miller, J.: Recent changes in Arctic sea ice
melt onset, freezeup, and melt season length, J. Geophys. Res., 114, C12024,
https://doi.org/10.1029/2009JC005436, 2009.
McCabe, G. J., Clark, M. P., and Hay, L. E.: Rain-on-snow events in the
western United States, B. Am. Meteorol. Soc., 88, 319–328, 2007.
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,
https://doi.org/10.1002/2016GL069330, 2016.
Neumann, R. B., Moorberg, C. J., Lundquist, J. D., Turner, J. C., Waldrop, M. P., McFarland, J. W., Euskirchen, E. S., Edgar, C. W., and Turetsky, R.: Warming effects of spring rainfall increase methane emissions from thawing permafrost, Geophys. Res. Lett., 46, https://doi.org/10.1029/2018GL081274, 2019.
Oltmanns, M., Straneo, F., and Tedesco, M.: Increased Greenland melt triggered by large-scale, year-round cyclonic moisture intrusions, The Cryosphere, 13, 815–825, https://doi.org/10.5194/tc-13-815-2019, 2019.
Parkinson, C. L. and Comiso, J. C.: On the 2012 record low Arctic sea ice
cover: Combined impact of preconditioning and an August storm, Geophys. Res.
Lett., 40, 1356–1361, https://doi.org/10.1002/grl.50349, 2013.
Peeters, B., Pedersen, Å. Ø., Loe, L. E., Isaksen, K., Veiberg, V.,
Stien, A., Kohler, J., Gallet, J.-C., Aanes, R., and Hansen, B. B.: Spatiotemporal patterns of rain-on-snow and basal ice in high Arctic Svalbard: detection of a climate-cryosphere regime shift,
Environ. Res. Lett., 14, 015002, https://doi.org/10.1088/1748-9326/aaefb3, 2019.
Perovich, D. K., Bruce, C. E., and Richter-Menge, J. A.: Observations of the
annual cycle of sea ice temperature, Geophys. Res. Lett., 24, 555–558, 1997.
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. O. 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.
Peterson, B., McClelland, J., Curry, R., Holmes, R., Walsh, J., and Agaard,
K.: Trajectory shifts in the Arctic and sub-Arctic freshwater cycle,
Science, 313, 1061–1066, 2006.
Petrich, C., Eicken, H., Zhang, J., Krieger, J. R., Fukamachi, Y., and Ohshima, K. I.: Coastal landfast sea ice decay and break-up in northernAlaska: Key processes and seasonal prediction, J. Geophys. Res., 117, C02003, https://doi.org/10.1029/2011JC007339, 2012.
Praetorius, S., Rugenstein, M., Persad, G., and Caldeira, K.: Global and
Arctic climate sensitivity enhanced by changes in North Pacific heat flux,
Nat. Commun., 9, 3124, https://doi.org/10.1038/s41467-018-05337-8, 2018.
Putkonen, J. and Roe, G.: Rain-on-snow events impact soil temperatures and
affect ungulate survival, Geophys. Res. Lett., 30, 1188, https://doi.org/10.1029/2002GL016326, 2003.
Rawlins, M. A., Steele, M., Holland, M. M., Adam, J. C., Cherry, J. E., Francis, J. A., Groisman, P. Y., Hinzman, L. D., Huntington, T. G., Kane, D. L., Kimball, J. S., Kwok, R., Lammers, R. B., Lee, C. M., Lettenmaier, D. P., McDonald, K. C., Podest, E., Pundsack, J. W., Rudels, B., Serreze, M. C., Shiklomanov, A., Skagseth, Ø., Troy, T. J., Vörösmarty, C. J., Wensnahan, M., Wood, E. F., Woodgate, R., Yang, D., Zhang, K., and Zhang, T.: Analysis of the Arctic system for freshwater cycle intensification: observations and expectations,
J. Climate, 23, 5715–5737, 2010.
Reichle, R. H., Draper, C. S., Liu, Q., Girotto, M., Mahanama, S. P. P.,
Koster, R. D., and De Lannoy, G. J. M.: Assessment of MERRA-2 Land Surface
Hydrology Estimates, J. Climate, 30, 2937–2960, 2017.
Renard, B., Lang, M., Bois, P., Dupeyrat, A., Mestre, O., Niel, H., Sauquet, E., Prudhomme, C., Parey, S., Paquet, E., Neppel, L., Gaihard, J.: Regional methods for trend detection: Assessing field significance and regional consistency, Water Resour. Res., 44, W08419, https://doi.org/10.1029/2007WR006268, 2008.
Rennert, K., Roe, G., Putkonen, J., and Bitz, C. M.: Soil thermal and
ecological impacts of rain on snow events in the circumpolar Arctic, J. Climate, 22, 2302–2315, 2009.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L. Kim, G. K., Bloom, S., Chen, J., Collins, D., Conaty, A., da Silva, A., Gu, W., Joiner, J., Koster, R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder, C. R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen, J.: MERRA: NASA's Modern-Era Retrospective Analysis for Research and Applications, J. Climate, 24,
3624–3648, https://doi.org/10.1175/JCLI-D-11-00015.1, 2011 (data available at: https://disc.sci.gsfc.nasa.gov/datasets?page=1&keywords=merra, last access: 12 August 2020).
Schröder, D., Feltham, D. L., Flocco, D., and Tsamados, M.: September
Arctic sea-ice minimum predicted by spring melt-pond fraction, Nat. Clim.
Change, 4, 353–357, 2014.
Screen, J. A. and Simmonds, I.: Declining summer snowfall in the Arctic:
causes, impacts and feedbacks, Clim. Dynam., 38, 2243–2256, 2012.
Serreze, M. C., Crawford, A. D., Stroeve, J. C., Barrett, A. P., and
Woodgate, R. A.: Variability, trends, and predictability of seasonal sea ice
retreat and advance in the Chukchi Sea, J. Geophys. Res.-Oceans, 121,
7308–7325, https://doi.org/10.1002/2016JC011977, 2016.
Sotiropoulou, G., Sedlar, J., Forbes, R., and Tjernström, M.: Summer
Arctic clouds in the ECMWF forecast model: An evaluation of cloud
parameterization schemes, Q. J. Roy. Meteorol. Soc., 142, 387–400, 2015.
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.
Vikhamar-Schuler, D., Isaksen, K., Haugen, J. E., Tømmervik, H., Luks, B., Schuler, T. V., and Bjerke, J. W.: Changes in Winter warming events in the Nordic Arctic Region, J. Climate, 29, 6223–6244, https://doi.org/10.1175/JCLI-D-15-0763.1, 2016.
Wang, C., Graham, R. M., Wang, K., Gerland, S., and Granskog, M. A.: Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution, The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, 2019.
Warren, S. G., Rigor, I. G., Untersteiner, N., Radionov, V. F., Bryazgin, N.
N., Aleksandrov, Y. I., and Colony, R.: Snow depth on Arctic sea ice, J.
Climate, 12, 1814–1829, 1999.
Webster, M. A., Rigor, I. G., 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.-Oceans, 119, 5395–5406, https://doi.org/10.1002/2014JC009985,
2014.
Webster, M. A., Parker, C., Boisvert, L., and Kwok, R.: The role of cyclone
activity in snow accumulation on arctic sea ice, Nat. Commun., 10, 1–12, 2019.
White, D., Hinzman, L., Alessa, L., Cassano, J., Chambers, M., Falkner, K., Francis, J., Gutowski Jr., W. J., Holland, M., Holmes, R. M., Huntington, H., Kane, D., Kliskey, A., Lee, C., McClelland, J., Peterson, B., Scott Rupp, T., Straneo, F., Steele, M., Woodgate, R., Yang, D., Yoshikawa, K., and Zhang, T.: The Arctic freshwater system:
changes and impacts, J. Geophys. Res., 112, G02S54,
https://doi.org/10.1029/2006JG000353, 2007.
Short summary
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.
Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing...
