Articles | Volume 13, issue 6
https://doi.org/10.5194/essd-13-3057-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-13-3057-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The AntSMB dataset: a comprehensive compilation of surface mass balance field observations over the Antarctic Ice Sheet
School of Geography and Environment, Shandong Normal University,
Jinan 250014, China
Minghu Ding
Tibetan Plateau and Polar Meteorology Institute, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Carleen H. Reijmer
Institute for Marine and Atmospheric research Utrecht, Utrecht
University, Utrecht, the Netherlands
Paul C. J. P. Smeets
Institute for Marine and Atmospheric research Utrecht, Utrecht
University, Utrecht, the Netherlands
Shugui Hou
School of Oceanography, Shanghai Jiao Tong University, Shanghai
200240, China
Cunde Xiao
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Beijing Normal University, Beijing 100875, China
Related authors
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
Short summary
Short summary
Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Peter Kuipers Munneke, and Michiel R. van den Broeke
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-88, https://doi.org/10.5194/essd-2025-88, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper describes the 154 station-years of in situ measurements from the 19 IMAU automatic weather stations that operated on the Antarctic ice sheet between 1995 and 2022. These stations also recorded all four components of net surface radiation and surface height change, which allows for the quantification of the surface energy-and-mass balance at hourly resolution. This data is invaluable for the evaluation of weather and climate models, and for the detection of climatological changes.
Tong Zhang, Wei Yang, Yuzhe Wang, Chuanxi Zhao, Qingyun Long, and Cunde Xiao
EGUsphere, https://doi.org/10.5194/egusphere-2025-659, https://doi.org/10.5194/egusphere-2025-659, 2025
Short summary
Short summary
This study investigates the 2018 Sedongpu glacier detachment in Southeastern Tibet using a two-dimensional ice flow model that includes an ice stiffness and basal slip positive feedback mechanism. The model simulates rapid transitions in glacier flow, triggering detachment when ice stress exceeds yield strength. The results, including ice speed and duration, align with observations, demonstrating the potential for early warning of similar hazards in the region.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
Short summary
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
Short summary
Short summary
How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
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.
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.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
Short summary
Short summary
Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Marte G. Hofsteenge, Nicolas J. Cullen, Carleen H. Reijmer, Michiel van den Broeke, Marwan Katurji, and John F. Orwin
The Cryosphere, 16, 5041–5059, https://doi.org/10.5194/tc-16-5041-2022, https://doi.org/10.5194/tc-16-5041-2022, 2022
Short summary
Short summary
In the McMurdo Dry Valleys (MDV), foehn winds can impact glacial meltwater production and the fragile ecosystem that depends on it. We study these dry and warm winds at Joyce Glacier and show they are caused by a different mechanism than that found for nearby valleys, demonstrating the complex interaction of large-scale winds with the mountains in the MDV. We find that foehn winds increase sublimation of ice, increase heating from the atmosphere, and increase the occurrence and rates of melt.
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.
Jiajia Wang, Hongxi Pang, Shuangye Wu, Spruce W. Schoenemann, Ryu Uemura, Alexey Ekaykin, Martin Werner, Alexandre Cauquoin, Sentia Goursaud Oger, Summer Rupper, and Shugui Hou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-384, https://doi.org/10.5194/essd-2022-384, 2022
Revised manuscript not accepted
Short summary
Short summary
Stable water isotopic observations in surface snow over Antarctica provide a basis for validating isotopic models and interpreting Antarctic ice core records. This study presents a new compilation of Antarctic surface snow isotopic dataset based on published and unpublished sources. The database has a wide range of potential applications in studying spatial distribution of water isotopes, model validation, and reconstruction and interpretation of Antarctic ice core records.
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.
Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
Short summary
Short summary
We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Wangbin Zhang, Shugui Hou, Shuang-Ye Wu, Hongxi Pang, Sharon B. Sneed, Elena V. Korotkikh, Paul A. Mayewski, Theo M. Jenk, and Margit Schwikowski
The Cryosphere, 16, 1997–2008, https://doi.org/10.5194/tc-16-1997-2022, https://doi.org/10.5194/tc-16-1997-2022, 2022
Short summary
Short summary
This study proposes a quantitative method to reconstruct annual precipitation records at the millennial timescale from the Tibetan ice cores through combining annual layer identification based on LA-ICP-MS measurement with an ice flow model. The reliability of this method is assessed by comparing our results with other reconstructed and modeled precipitation series for the Tibetan Plateau. The assessment shows that the method has a promising performance.
Tao Xu, Hongxi Pang, Zhaojun Zhan, Wangbin Zhang, Huiwen Guo, Shuangye Wu, and Shugui Hou
Hydrol. Earth Syst. Sci., 26, 117–127, https://doi.org/10.5194/hess-26-117-2022, https://doi.org/10.5194/hess-26-117-2022, 2022
Short summary
Short summary
In this study, we presented stable isotopes in atmospheric water vapor and precipitation for five extreme winter precipitation events in Nanjing, southeastern China, from December 2018 to February 2019. Our results imply that multiple moisture sources and the rapid shift among them are important conditions for sustaining extreme precipitation events, especially in the relatively cold and dry winter.
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.
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Bert Wouters, Jakob F. Steiner, Emile J. Nieuwstraten, Walter W. Immerzeel, and Michiel R. van den Broeke
The Cryosphere, 15, 2601–2621, https://doi.org/10.5194/tc-15-2601-2021, https://doi.org/10.5194/tc-15-2601-2021, 2021
Short summary
Short summary
We developed a method to estimate the aerodynamic properties of the Greenland Ice Sheet surface using either UAV or ICESat-2 elevation data. We show that this new method is able to reproduce the important spatiotemporal variability in surface aerodynamic roughness, measured by the field observations. The new maps of surface roughness can be used in atmospheric models to improve simulations of surface turbulent heat fluxes and therefore surface energy and mass balance over rough ice worldwide.
Shugui Hou, Wangbin Zhang, Ling Fang, Theo M. Jenk, Shuangye Wu, Hongxi Pang, and Margit Schwikowski
The Cryosphere, 15, 2109–2114, https://doi.org/10.5194/tc-15-2109-2021, https://doi.org/10.5194/tc-15-2109-2021, 2021
Short summary
Short summary
We present ages for two new ice cores reaching bedrock, from the Zangser Kangri (ZK) glacier in the northwestern Tibetan Plateau and the Shulenanshan (SLNS) glacier in the western Qilian Mountains. We estimated bottom ages of 8.90±0.57/0.56 ka and 7.46±1.46/1.79 ka for the ZK and SLNS ice core respectively, constraining the time range accessible by Tibetan ice cores to the Holocene.
Ling Fang, Theo M. Jenk, Thomas Singer, Shugui Hou, and Margit Schwikowski
The Cryosphere, 15, 1537–1550, https://doi.org/10.5194/tc-15-1537-2021, https://doi.org/10.5194/tc-15-1537-2021, 2021
Short summary
Short summary
The interpretation of the ice-core-preserved signal requires a precise chronology. Radiocarbon (14C) dating of the water-insoluble organic carbon (WIOC) fraction has become an important dating tool. However, this method is restricted by the low concentration in the ice. In this work, we report first 14C dating results using the dissolved organic carbon (DOC) fraction. The resulting ages are comparable in both fractions, but by using the DOC fraction the required ice mass can be reduced.
Eric Keenan, Nander Wever, Marissa Dattler, Jan T. M. Lenaerts, Brooke Medley, Peter Kuipers Munneke, and Carleen Reijmer
The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, https://doi.org/10.5194/tc-15-1065-2021, 2021
Short summary
Short summary
Snow density is required to convert observed changes in ice sheet volume into mass, which ultimately drives ice sheet contribution to sea level rise. However, snow properties respond dynamically to wind-driven redistribution. Here we include a new wind-driven snow density scheme into an existing snow model. Our results demonstrate an improved representation of snow density when compared to observations and can therefore be used to improve retrievals of ice sheet mass balance.
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
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.
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.
Baojuan Huai, Michiel R. van den Broeke, and Carleen H. Reijmer
The Cryosphere, 14, 4181–4199, https://doi.org/10.5194/tc-14-4181-2020, https://doi.org/10.5194/tc-14-4181-2020, 2020
Short summary
Short summary
This study presents the surface energy balance (SEB) of the Greenland Ice Sheet (GrIS) using a SEB model forced with observations from automatic weather stations (AWSs). We correlate ERA5 with AWSs to show a significant positive correlation of GrIS summer surface temperature and melt with the Greenland Blocking Index and weaker and opposite correlations with the North Atlantic Oscillation. This analysis may help explain melting patterns in the GrIS with respect to circulation anomalies.
Cited articles
Altnau, S., Schlosser, E., Isaksson, E., and Divine, D.: Climatic signals from 76 shallow firn cores in Dronning Maud Land, East Antarctica, The Cryosphere, 9, 925–944, https://doi.org/10.5194/tc-9-925-2015, 2015.
Agosta, C., Amory, C., Kittel, C., Orsi, A., Favier, V., Gallée, H., van den Broeke, M. R., Lenaerts, J. T. M., van Wessem, J. M., van de Berg, W. J., and Fettweis, X.: Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes, The Cryosphere, 13, 281–296, https://doi.org/10.5194/tc-13-281-2019, 2019.
Anschütz, H., Müller, K., Isaksson, E., McConnell, J. R., Fischer,
H., Miller, H., Albert, M., and Winther, J.-G.: Revisiting sites of the
South Pole Queen Maud Land Traverses in East Antarctica: Accumulation data
from shallow firn cores, J. Geophys. Res., 114, D24106,
https://doi.org/10.1029/2009JD012204, 2009.
Arthern, R. J., Winebrenner, D. P., and Vaughan, D. G.: Antarctic snow
accumulation mapped using polarization of 4.3-cm wavelength microwave
emission, J. Geophys. Res., 111, D06107,
https://doi.org/10.1029/2004JD005667, 2006.
Behrangi, A., Christensen, M., Richardson, M., Lebsock, M., Stephens, G.,
Huffman, G. J., Bolvin, D., Adler, R. F., Gardner, A., Lambrigtsen, B., and
Fetzer, E.: Status of high-latitude precipitation estimates from
observations and reanalyses, J. Geophys. Res.-Atmos., 121, 4468–4486,
https://doi.org/10.1002/2015JD024546, 2016.
Braaten, D.: A detailed assessment of snow accumulation in katabatic wind areas on the Ross Ice Shelf, Antarctica, J. Geophys. Res., 102, 30047–30058, 1997.
Braaten, D.: Direct measurements of episodic snow accumulation on the Antarctic polar plateau, J. Geophys. Res., 105, 10119–10128, 2000.
Bromwich, D. H., Nicolas, J. P., and Monaghan, A. J.: An assessment of
precipitation changes over Antarctica and the Southern Ocean since 1989 in
contemporary global reanalyses, J. Climate, 24, 4189–4209.
https://doi.org/10.1175/2011JCLI4074.1, 2011.
Cohen, L., Dean, S., and Renwick, J.: Synoptic weather types for the Ross
Sea region, Antarctica, J. Climate, 26, 636–649,
https://doi.org/10.1175/JCLI-D-11-00690.1, 2013.
Dalaiden, Q., Goosse, H., Klein, F., Lenaerts, J. T. M., Holloway, M., Sime, L., and Thomas, E. R.: How useful is snow accumulation in reconstructing surface air temperature in Antarctica? A study combining ice core records and climate models, The Cryosphere, 14, 1187–1207, https://doi.org/10.5194/tc-14-1187-2020, 2020.
Dattler, M. E., Lenaerts, J. T. M., and Medley, B.: Significant spatial
variability in radar-derived West Antarctic accumulation linked to surface
winds and topography, Geophys. Res. Lett., 46, 126–134,
https://doi.org/10.1029/2019GL085363, 2019.
Ding, M., Xiao, C., Li, Y., Ren, J., Hou, S., Jin, B., and Sun, B.: Spatial
variability of surface mass balance along a traverse route from Zhongshan
station to Dome A, Antarctica, J. Glaciol., 57, 658–666,
https://doi.org/10.3189/002214311797409820, 2011.
Ding, M., Xiao, C., Li, C., Qin, D., Jin, B., Shi, G., Xie, A., and Cui, X.:
Surface mass balance and its climate significance from the coast to Dome A,
East Antarctica, Sci. China: Earth Sci., 58, 1787–1797,
https://doi.org/10.1007/s11430-015-5083-9, 2015.
Ding, M., Xiao, W., Xiao, C., Yang, J., Zhang, D., Li, R., and Zhang, T.: The snowfall history of Lambert Glacier basin during the past 300 years inferred from an ice core at LGB69, East Antarctica, 37, 1111–1118, https://doi.org/10.11928/j.issn.1001-7410.2017.05.18, 2017 (in Chinese).
Doran, P. T., McKay, C. P., Clow, G. D., Dana, G. L., Fountain, A. G., Nylen, T., and Lyons, W. B.: Valley floor climate observations from the McMurdo dry valleys, Antarctica, 1986–2000, J. Geophys. Res., 107, 4772, https://doi.org/10.1029/2001JD002045, 2002.
Eisen, O., Frezzotti, M., Genthon, C., Isaksson, E., Magand, O., van den Broeke, M. R., Dixon, D. A., Ekaykin, A., Holmlund, P., Kameda, T., Karlof, L., Kaspari, S., Lipenkov, V. Y., Oerter, H., Takahashi, S., and Vaughan, D. G.: Ground-based measurements of spatial and temporal variability of snow accumulation in East Antarctica, Rev. Geophys., 46, 26367, https://doi.org/10.1029/2006RG000218, 2008.
Favier, V., Agosta, C., Parouty, S., Durand, G., Delaygue, G., Gallée, H., Drouet, A.-S., Trouvilliez, A., and Krinner, G.: An updated and quality controlled surface mass balance dataset for Antarctica, The Cryosphere, 7, 583–597, https://doi.org/10.5194/tc-7-583-2013, 2013.
Frezzotti, M., Pourchet, M., Flora, O., Gandolfi, S., Gay, M., Urbini, S.,
Vincent, C., Becagli, S., Gragnani, R., Proposito, M., Severi, M., Traversi,
R., Udisti, R., and Fily, M.: Spatial and temporal variability of snow
accumulation in East Antarctica from traverse data, J. Glaciol., 51,
113–124, https://doi.org/10.3189/172756505781829502, 2005.
Frezzotti, M., Urbini, S., Proposito, M., Scarchilli, C., and Gandolfi, S.:
Spatial and temporal variability of surface mass balance near Talos Dome,
East Antarctica, J. Geophys. Res., 112, F02032,
https://doi.org/10.1029/2006JF000638, 2007.
Frezzotti, M., Scarchilli, C., Becagli, S., Proposito, M., and Urbini, S.: A synthesis of the Antarctic surface mass balance during the last 800 yr, The Cryosphere, 7, 303–319, https://doi.org/10.5194/tc-7-303-2013, 2013.
Fountain, A. G., Nylen, T. H., Monaghan, A., Basaigic, H. J., and Bromwich, D.: Snow in the McMurdo Dry Valleys, Antarctica, Int. J. Climatol., 30, 633–642, https://doi.org/10.1002/joc.1933, 2010.
Genthon, C., Magand, O., Krinner, G., and Fily, M.: Do climate models
underestimate snow accumulation on the Antarctic plateau? A re-evaluation
of/from in situ observations in East Wilkes and Victoria Lands, Ann.
Glaciol., 50, 61–65, https://doi.org/10.3189/172756409787769735, 2009.
Gorodetskaya, I. V., van Lipzig, N. P. M., van den Broeke, M. R., Mangold,
A., Boot, W., and Reijmer, C. H.: Meteorological regimes and accumulation
patterns at Utsteinen, Dronning Maud Land, East Antarctica: Analysis of two
contrasting years. J. Geophys. Res.-Atmos., 118, 1700–1715,
https://doi.org/10.1002/jgrd.50177, 2013.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., De Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5
global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Huai, B., Wang, Y., Ding, M., Zhang, J., and Dong, X.: An assessment of
recent global atmospheric reanalyses for Antarctic near surface air
temperature, Atmos. Res., 226, 181–191,
https://doi.org/10.1016/j.atmosres.2019.04.029, 2019.
Isaksson, E. and Melvold, K.: Trends and patterns in the recent accumulation
and oxygen isotope in coastal Dronning Maud Land, Antarctica:
interpretations from shallow ice cores, Ann. Glaciol., 35, 175–180, 2002.
Kameda, T., Motoyama, H., Fujita, S., and Takahashi S.: Temporal and spatial variability of surface mass balance at Dome Fuji, East Antarctica, by the stake method from 1995 to 2006, J. Glaciol., 54, 107–116, 2008.
Kanagaratnam, P., Gogineni, S., Ramasami, V., and Braaten, D.: A wideband radar for high-resolution mapping of near-surface internal layers in glacial ice, IEEE T. Geosci. Remote Sens., 42, 483–490, 2004.
Kanagaratnam, P., Markus, T., Lytle, V., Heavey, B., Jansen, P., Prescott, G., and Gogineni, S. P.: Ultrawideband radar measurements of thickness of snow over sea ice, IEEE T. Geosci. Remote Sens., 45, 2715–2724, 2007.
Kaspari, S., Mayewski, P. A., Dixon, D. A., Spikes, V. B., Sneed, S. B.,
Handley, M. J., and Hamilton, G. S.: Climate variability in West Antarctica
derived from annual accumulation-rate records from ITASE firn/ice cores,
Ann. Glaciol., 39, 585–594, https://doi.org/10.3189/172756404781814447,
2004.
Khodzher, T. V., Golobokova, L. P., Osipov, E. Yu., Shibaev, Yu. A., Lipenkov, V. Ya., Osipova, O. P., and Petit, J. R.: Spatial–temporal dynamics of chemical composition of surface snow in East Antarctica along the Progress station–Vostok station transect, The Cryosphere, 8, 931–939, https://doi.org/10.5194/tc-8-931-2014, 2014.
Le Meur, E., Magand, O., Arnaud, L., Fily, M., Frezzotti, M., Cavitte, M., Mulvaney, R., and Urbini, S.: Spatial and temporal distributions of surface mass balance between Concordia and Vostok stations, Antarctica, from combined radar and ice core data: first results and detailed error analysis, The Cryosphere, 12, 1831–1850, https://doi.org/10.5194/tc-12-1831-2018, 2018.
Leuschen, C.: IceBridge Snow Radar L1B Geolocated Radar Echo Strength Profiles, 18 October 2009, 19 November 2010, 9–12 November 2011, Boulder, Colorado USA, NASA DAAC at the National Snow and Ice Data Center, 2010.
Li, Y., Cole-Dai, J., and Zhou, L.: Glaciochemical evidence in an East
Antarctica ice core of a recent (AD 1450–1850) neoglacial episode, J.
Geophys. Res., 114, D08117, https://doi.org/10.1029/2008JD011091, 2009.
Liu, Y., Li, F., Hao, W., Barriot, J. P., and Wang, Y.: Evaluation of
synoptic snowfall on the Antarctic Ice Sheet based on CloudSat, in-Situ
observations and atmospheric reanalysis datasets, Remote Sens., 11, 1686,
https://doi.org/10.3390/rs11141686, 2019.
Magand, O., Genthon, C., Fily, M., Krinner, G., Picard, G., Frezzotti, M.,
and Ekaykin, A. A.: An up-to-date quality-controlled surface mass balance
data set for the 90–180∘ E Antarctica sector and 1950–2005
period, J. Geophys. Res., 112, D12106, https://doi.org/10.1029/2006JD007691,
2007.
Mayewski, P. and Dixon, D. A.: US International Trans-Antarctic Scientific
Expedition (US ITASE) Glaciochemical Data, Version 2, US_ITASE_Core Info-SWE-Density_2013.xlsx,
National Snow and Ice Data Center, Boulder, Colorado, USA, 2013.
Mayewski, P., Frezzotti, M., Bertler, N. A. N., van Ommen, T., Hamilton, G.
S., Jacka T. H., Welch, B., Frey, M., Qin, D., Ren, J., Simöes, J.,
Fily, M., Oerter, H., Nishio, F., Isaksson, E., Mulvaney, R., Holmund, P.,
Lipenkov, V., and Goodwin, I.: The International Trans-Antarctic Scientific
Expedition (ITASE): An Overview, Ann. Glaciol., 41, 180–185, 2005.
McMorrow, A., Curran, M., van Ommen, T., Morgan, V., Pook, M., and Allison, I.: Intercomparison of firn core and meteorological data, Antarct. Sci., 13, 329–337, 2001.
Medley, B. and Thomas, E. R.: Increased snowfall over the Antarctic Ice
Sheet mitigated 20th century sea-level rise, Nat. Clim. Change, 9, 34–39,
https://doi.org/10.1038/s41558-018-0356-x, 2019.
Medley, B., Joughin, I., Das, S. B., Steig, E. J., Conway, H., Gogineni, S.,
Criscitiello, A. S., McConnell, J. R., Smith, B. E., van den Broeke, M. R.,
Lenaerts, J. T. M., Bromwich, D. H., and Nicolas, J. P.: Airborne-radar and
ice-core observations of annual snow accumulation over Thwaites Glacier,
West Antarctica confirm the spatiotemporal variability of global and
regional atmospheric models, Geophys. Res. Lett., 40, 3649–3654,
https://doi.org/10.1002/grl.50706, 2013.
Medley, B., Joughin, I., Smith, B. E., Das, S. B., Steig, E. J., Conway, H., Gogineni, S., Lewis, C., Criscitiello, A. S., McConnell, J. R., van den Broeke, M. R., Lenaerts, J. T. M., Bromwich, D. H., Nicolas, J. P., and Leuschen, C.: Constraining the recent mass balance of Pine Island and Thwaites glaciers, West Antarctica, with airborne observations of snow accumulation, The Cryosphere, 8, 1375–1392, https://doi.org/10.5194/tc-8-1375-2014, 2014.
Montgomery, L., Koenig, L., and Alexander, P.: The SUMup dataset: compiled measurements of surface mass balance components over ice sheets and sea ice with analysis over Greenland, Earth Syst. Sci. Data, 10, 1959–1985, https://doi.org/10.5194/essd-10-1959-2018, 2018.
Monaghan, A. J., Bromwich, D. H., Fogt, R. L., Wang, S.-H., Mayewski, P. A.,
Dixon, D. A., Ekaykin, A., Frezzotti, M., Goodwin, I., Isaksson, E.,
Kaspari, S. D., Morgan, V. I., Oerter, H., Van Ommen, T. D., Van der Veen,
C. J., and Wen, J.: Insignificant Change in Antarctic Snowfall Since the
International Geophysical Year, Science, 313, 827–831,
https://doi.org/10.1126/science.1128243, 2006a.
Monaghan, A. J., Bromwich, D. H., and Wang, S-H.: Recent trends in Antarctic
snow accumulation from Polar MM5 simulations, Philis. T. Roy. Soc. A., 364,
1683–1708, https://doi.org/10.1098/rsta.2006.1795, 2006b.
Motoyama, H., Furukawa, T., Fujita, S., Shinbori, K., Tanaka, Y., Li, Y.,
Chung, J.-W., Nakazawa, F., Fukui, K., Enomoto, H., Sugiyama, S., Asano, H.,
Takeda, Y., Hirabayashi, M., Nishimura, D., Masunaga, T., Kuramoto, T.,
Kobashi, T., Kusaka, R., Kinase, T., Ikeda, C., Suzuki, T., Ohno, H.,
Hoshina, Y., Hayakawa, Y., and Kameda, T.: Glaciological Data Collected by
the 48th–54th Japanese Antarctic Research Expeditions during 2007–2013,
JARE Data Rep., 341, Glaciology, 35, 1–44, 2015.
Müller, K., Sinisalo, A., Anschütz, H., Hamran, S.-E., Hagen, J.-O., McConnell, J. R., and Pasteris, D. R.: An 860 km surface mas sbalance profile on the East Antarctic plateau derived by GPR,
Ann. Glaciol., 55, 1–8, https://doi.org/10.3189/172756410791392718, 2010.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML76S05_11, https://doi.org/10.1594/PANGAEA.708113, 2008a.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML77S05_12, https://doi.org/10.1594/PANGAEA.708114, 2008b.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML78S05_13, https://doi.org/10.1594/PANGAEA.708115, 2008c.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML79S05_14, https://doi.org/10.1594/PANGAEA.708116, 2008d.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML80S05_15, https://doi.org/10.1594/PANGAEA.708117, 2008e.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML81S05_16, https://doi.org/10.1594/PANGAEA.708118, 2008f.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML82S05_17, https://doi.org/10.1594/PANGAEA.708119, 2008g.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML83S05_18, https://doi.org/10.1594/PANGAEA.708120, 2008h.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML84S05_19, https://doi.org/10.1594/PANGAEA.708121, 2008i.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML85S05_20, https://doi.org/10.1594/PANGAEA.708122, 2008j.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML86S05_21, https://doi.org/10.1594/PANGAEA.708123, 2008k.
Oerter, H.: Annual means of δ18O and accumulation rates of snow pit
DML87S05_22, https://doi.org/10.1594/PANGAEA.708124, 2008l.
Palerme, C., Kay, J. E., Genthon, C., L'Ecuyer, T., Wood, N. B., and Claud, C.: How much snow falls on the Antarctic ice sheet?, The Cryosphere, 8, 1577–1587, https://doi.org/10.5194/tc-8-1577-2014, 2014.
Rignot, E., Velicogna, I., van den Broeke, M. R., Monaghan, A. J., and
Lenaerts, J. T.: Acceleration of the contribution of the Greenland and
Antarctic ice sheets to sea level rise, Geophys. Res. Lett., 38, L05503,
https://doi.org/10.1029/2011GL046583, 2011.
Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M., van Wessem, M.
J., and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from
1979–2017, P. Natl. Acad. Sci. USA, 116, 1095–1103, https://doi.org/10.1073/pnas.1812883116,
2019.
Reijmer, C. H. and Van den Broeke, M. R.: Temporal and spatial variability
of the surface mass balance in Dronning Maud Land, Antarctica, as derived
from automatic weather stations, J. Glaciol., 49, 512–520,
https://doi.org/10.3189/172756503781830494, 2003.
Reijmer, C. H., Greuell, W., and Oerlemans, J.: The annual cycle of
meteorological variables and the surface energy balance on Berkner Island,
Antarctica, Ann. Glaciol., 29, 49–54, 1999.
Rodriguez-Morales, F., Gogineni, S., Leuschen, C. J., Paden, J. D., Li, J., Lewis, C. C., Panzer, B., Alvestegui, D. G.-G., Patel, A., Byers, K., Crowe, R., Player K., Hale, R. D., Arnold, E. J., Smith, L., Gifford, C. M., Braaten, D., and Panton, C.: Advanced Multi-Frequency Radar Instrumentation for Polar Research, IEEE T. Geosci. Rem. Sens., 52, 2824–2842, https://doi.org/10.1109/TGRS.2013.2266415, 2014.
Shepherd, A., Ivins, E. R., A. G., Barletta, V. R., Bentley, M. J.,
Bettadpur, S., Briggs, K. H., Bromwich, D. H., Forsberg, R., Galin, N.,
Horwath, M., Jacobs, S., Joughin, I., King, M. A., Lenaerts, J. T. M., Li,
J., Ligtenberg, S. R. M., Luckman, A., Luthcke, S. B., McMillan, M.,
Meister, R., Milne, G., Mouginot, J., Muir, A., Nicolas, J. P., Paden, J.,
Payne, A. J., Pritchard, H., Rignot, E., Rott, H., Sørensen, L. S.,
Scambos, T. A., Scheuchl, B., Schrama, E. J. O., Smith, B., Sundal, A. V.,
van Angelen, J. H., van de Berg, W. J., van den Broeke, M. R., Vaughan, D.
G., Velicogna, I., Wahr, J., Whitehouse, P. L., Wingham, D. J., Yi, D.,
Young, D., and Zwally, H. J.: A reconciled estimate of ice-sheet mass
balance, Science, 338, 1183–1189, https://doi.org/10.1126/science.1228102,
2012.
Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M.,
Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G.,
Nowicki, S., Payne, T., Scambos, T., Schlegel, N., A, G., Agosta, C.,
Ahlstrøm, A., Babonis, G., Barletta, V., Blazquez, A., Bonin, J., Csatho,
B., Cullather, R., Felikson, D., Fettweis, X., Forsberg, R., Gallee, H.,
Gardner, A., Gilbert, L., Groh, A., Gunter, B., Hanna, E., Harig, C., Helm,
V., Horvath, A., Horwath, M., Khan, S., Kjeldsen, K. K., Konrad, H., Langen,
P., Lecavalier, B., Loomis, B., Luthcke, S., McMillan, M., Melini, D.,
Mernild, S., Mohajerani, Y., Moore, P., Mouginot, J., Muir, A., Nagler, T.,
Nield, G., Nilsson, J., Noel, B., Otosaka, I., Peltier, R., Pie, N.,
Rietbroek, R., Rott, H., Sandberg-Sørensen, L., Sasgen, I., Save, H.,
Schrama, E., Schroder, L., Seo, K.-W., Simonsen, S., Slater, T., Spada, G.,
Sutterley, T., Talpe, M., Tarasov, L., van de Berg, W. J., van der Wal, W.,
van Wessem, M., Vishwakarma, B. D., Wiese, D., Wouters, B., Wu, X., and
Zwally, J.: Mass balance of the Antarctic Ice Sheet from 1992 to 2017,
Nature, 558, 219–222, https://doi.org/10.1038/s41586-018-0179-y, 2018.
Spikes, V. B., Hamilton, G. S., Arcone, S. A., Kaspari, S., and Mayewski, P. A.: Variability in accumulation rates from GPR profiling on the West Antarctic plateau, Ann. Glaciol., 39, 238–244, 2004.
Stenni, B., Curran, M. A. J., Abram, N. J., Orsi, A., Goursaud, S., Masson-Delmotte, V., Neukom, R., Goosse, H., Divine, D., van Ommen, T., Steig, E. J., Dixon, D. A., Thomas, E. R., Bertler, N. A. N., Isaksson, E., Ekaykin, A., Werner, M., and Frezzotti, M.: Antarctic climate variability on regional and continental scales over the last 2000 years, Clim. Past, 13, 1609–1634, https://doi.org/10.5194/cp-13-1609-2017, 2017.
Thiery, W., Gorodetskaya, I. V., Bintanja, R., Van Lipzig, N. P. M., Van den Broeke, M. R., Reijmer, C. H., and Kuipers Munneke, P.: Surface and snowdrift sublimation at Princess Elisabeth station, East Antarctica, The Cryosphere, 6, 841–857, https://doi.org/10.5194/tc-6-841-2012, 2012.
Thomas, E. R. and Bracegirdle, T. J.: Precipitation pathways for five new
ice core sites in Ellsworth Land, West Antarctica, Clim. Dynam., 44,
2067–2078, https://doi.org/10.1007/s00382-014-2213-6, 2015.
Thomas, E. R., van Wessem, J. M., Roberts, J., Isaksson, E., Schlosser, E., Fudge, T. J., Vallelonga, P., Medley, B., Lenaerts, J., Bertler, N., van den Broeke, M. R., Dixon, D. A., Frezzotti, M., Stenni, B., Curran, M., and Ekaykin, A. A.: Regional Antarctic snow accumulation over the past 1000 years, Clim. Past, 13, 1491–1513, https://doi.org/10.5194/cp-13-1491-2017, 2017.
Van den Broeke, M. R., Reijmer, C. H., and van de Wal, R. S. W.: A study of
the surface mass balance in Dronning Maud Land, Antarctica, using automatic
weather station. J. Glaciol., 50, 565–582,
https://doi.org/10.3189/172756504781829756, 2004.
Van de Berg, W. J., Van den Broeke, M. R., Reijmer, C. H., and Van
Meijgaard, E.: Reassessment of the Antarctic surface mass balance using
calibrated output of a regional atmospheric climate model, J. Geophys. Res.,
111, D11104, https://doi.org/10.1029/2005JD006495, 2006.
van Lipzig, N. P. M., Turner, J., Colwell, S. R., and van den Broeke, M. R.: The near-surface wind field over the Antarctic continent, Int. J. Climatol., 24, 1973–1982, 2004.
Vaughan, D. G. and Russell, J.: Compilation of surface mass balance
measurements in Antarctica, Internal Rep., ES4, 56, 1–56, 1997.
Vaughan, D. G., Bamber, J. L., Giovinetto, M., Russell, J., and Cooper, A.
P. R.: Reassessment of net surface mass balance in Antarctica, J. Climate,
12, 933–946, https://doi.org/10.1175/1520-0442(1999)012<0933:RONSMB>2.0.CO;2, 1999.
Vaughan, D. G., Anderson, P. S., King, J. C., Mann, G. W., Mobbs, S. D., and
Ladkin R. S.: Imaging of firn isochrones across an Antarctic ice rise and
implications for patterns of snow accumulation rate, J. Glaciol., 50,
413–418, 2004.
van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018.
Wang, Y., Hou, S., Sun, W., Lenaerts, J. T. M., van den Broeke, M. R., and
van Wessem, J. M.: Recent surface mass balance from Syowa Station to Dome F,
East Antarctica: comparison of field observations, atmospheric reanalyses,
and a regional atmospheric climate model, Clim. Dynam., 45, 2885–2899,
https://doi.org/10.1007/s00382-015-2512-6, 2015.
Wang, Y., Ding, M., van Wessem, J., Schlosser, E., Altnau, S., van den
Broeke, M. R., Lenaerts, J. T. M., Thomas, E. R., Isaksson, E., Wang, J.,
and Sun, W.: A comparison of Antarctic Ice Sheet surface mass balance from
atmospheric climate models and in situ observations, J. Climate., 29,
5317–5337, 2016.
Wang, Y., Huai, B., Thomas, E. R., van den Broeke, M. R., van Wessem, J. M.,
and Schlosser, E.: A new 200-year spatial reconstruction of West Antarctic
surface mass balance, J. Geophys. Res.-Atmos., 124, 5282–5295,
https://doi.org/10.1029/2018JD029601, 2019.
Wang, Y., Hou, S., Ding, M., and Sun, W.: On the performance of twentieth
century reanalysis products for Antarctic snow accumulation, Clim. Dynam., 54,
435–455, https://doi.org/10.1007/s00382-019-05008-4, 2020.
Wang, Y., Ding, M., Reijmer C., Smeets P., Hou, S., and Xiao, C.: A
comprehensive dataset of surface mass balance field observations over the
Antarctic Ice Sheet version 1.0. A Big Earth Data Platform for Three Poles,
2021.
Winski, D. A., Fudge, T. J., Ferris, D. G., Osterberg, E. C., Fegyveresi, J. M., Cole-Dai, J., Thundercloud, Z., Cox, T. S., Kreutz, K. J., Ortman, N., Buizert, C., Epifanio, J., Brook, E. J., Beaudette, R., Severinghaus, J., Sowers, T., Steig, E. J., Kahle, E. C., Jones, T. R., Morris, V., Aydin, M., Nicewonger, M. R., Casey, K. A., Alley, R. B., Waddington, E. D., Iverson, N. A., Dunbar, N. W., Bay, R. C., Souney, J. M., Sigl, M., and McConnell, J. R.: The SP19 chronology for the South Pole Ice Core – Part 1: volcanic matching and annual layer counting, Clim. Past, 15, 1793–1808, https://doi.org/10.5194/cp-15-1793-2019, 2019.
Xiao, C., Ren, J., Qin, D. H., Li, Z. Q., Sun, W. Z., and Allison, I.:
Complexity of the climatic regime over the Lambert Glacier basin of the East
Antarctic Ice Sheet: Firn core evidences, J. Glaciol., 47, 160–163,
https://doi.org/10.3189/172756501781832539, 2001.
Zhang, Y., Wang, Y., Huai, B., Ding, M., and Sun, W.: Skill of the two 20th
century reanalyses in representing Antarctic near-surface air temperature,
Int. J. Climatol., 38, 11, 4225–4238, https://doi.org/10.1002/joc.5563, 2018.
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.
Accurate observation of surface mass balance (SMB) under climate change is essential for the...
Special issue
Altmetrics
Final-revised paper
Preprint