Articles | Volume 23, issue 15
https://doi.org/10.5194/acp-23-8683-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-8683-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Aug 2023
Research article |
| 08 Aug 2023
| 08 Aug 2023
The characteristics of atmospheric boundary layer height over the Arctic Ocean during MOSAiC
Shijie Peng
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Qinghua Yang
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Matthew D. Shupe
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
Physical Sciences Laboratory, National Oceanic and Atmospheric Administration (NOAA), Boulder, CO, USA
Xingya Xi
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Bo Han
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Dake Chen
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Sandro Dahlke
Helmholtz Centre for Polar and Marine Research, Alfred Wegener Institute (AWI), Potsdam, Germany
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
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Chengyan Liu, Zhaomin Wang, Dake Chen, Xianxian Han, Hengling Leng, Xi Liang, Liangjun Yan, Xiang Li, Craig Stevens, Andrew Hogg, Kazuya Kusahara, Kaihe Yamazaki, Kay Ohshima, Meng Zhou, Xiao Cheng, Dongxiao Wang, Changming Dong, Jiping Liu, Qinghua Yang, Xichen Li, Ruibo Lei, Minghu Ding, Zhaoru Zhang, Dujuan Kang, Di Qi, Tongya Liu, Jihai Dong, Lu An, Ru Chen, Tong Zhang, Xiaoming Hu, Bo Han, Haibo Bi, Qi Shu, Longjiang Mu, Shiming Xu, Hu Yang, Hailong Liu, Tingfeng Dou, Zhixuan Feng, Lei Zheng, Xueyuan Tang, Guitao Shi, Yongqing Cai, Bingrui Li, Yang Wu, Xia Lin, Wenjin Sun, Yu Liu, Kai Yu, Yu Zhang, Weizeng Shao, Xiaoyu Wang, Shaojun Zheng, Chengyi Yuan, Chunxia Zhou, Jian Liu, Yang Liu, Yue Xia, Xiaoyu Pan, Jiabao Zeng, Kechen Liu, Jiahao Fan, Chen Cheng, and Qi Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-6487, https://doi.org/10.5194/egusphere-2025-6487, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We developed a high-resolution computer model to simulate how the ocean, sea ice, and ice shelves interact around Antarctica. This helps us understand their critical role in global climate and sea-level rise. Our model successfully captures essential features like major currents and seasonal ice changes. Despite some remaining biases, it provides a useful tool for predicting future changes in this vital and rapidly evolving region.
Ziying Yang, Jiping Liu, Mirong Song, Yongyun Hu, Qinghua Yang, Ke Fan, Rune Grand Graversen, and Lu Zhou
The Cryosphere, 19, 6381–6402, https://doi.org/10.5194/tc-19-6381-2025, https://doi.org/10.5194/tc-19-6381-2025, 2025
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Antarctic sea ice has changed rapidly in recent years. Here we developed a deep learning model trained by multiple climate variables for extended seasonal Antarctic sea ice prediction. Our model shows high predictive skills up to 6 months in advance, particularly in predicting extreme events. It also shows skillful predictions at the sea ice edge and year-to-year sea ice changes. Variable importance analyses suggest what variables are more important for prediction at different lead times.
Manfred Wendisch, Benjamin Kirbus, Davide Ori, Matthew D. Shupe, Susanne Crewell, Harald Sodemann, and Vera Schemann
Atmos. Chem. Phys., 25, 15047–15076, https://doi.org/10.5194/acp-25-15047-2025, https://doi.org/10.5194/acp-25-15047-2025, 2025
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Aircraft observations of air parcels moving into and out of the Arctic are reported. From the data, heating and cooling as well as drying and moistening of the air masses along their way into and out of the Arctic could be measured for the first time. These data are used to evaluate if weather prediction models are able to accurately represent these air mass transformations. This work helps to model the future Arctic climate changes, which may have an impact for mid-latitude weather as well.
Cristofer Jimenez, Albert Ansmann, Kevin Ohneiser, Hannes Griesche, Ronny Engelmann, Martin Radenz, Julian Hofer, Dietrich Althausen, Daniel A. Knopf, Sandro Dahlke, Johannes Bühl, Holger Baars, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 25, 12955–12981, https://doi.org/10.5194/acp-25-12955-2025, https://doi.org/10.5194/acp-25-12955-2025, 2025
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We studied the water and ice phases of Arctic mixed-phase clouds (MPCs) using dual FOV polarization lidar and Doppler radar on board Polarstern during the MOSAiC expedition. Two long-lasting Arctic MPCs and year-round statistics show persistent droplet activation and dominant immersion freezing, indicating well-filled cloud condensation nuclei and ice-nucleating particle reservoirs. These findings help explain MPC longevity and may improve cloud life cycle representation in weather and climate models.
Lexie Goldberger, Maxwell Levin, Carlandra Harris, Andrew Geiss, Matthew D. Shupe, and Damao Zhang
Atmos. Meas. Tech., 18, 5393–5414, https://doi.org/10.5194/amt-18-5393-2025, https://doi.org/10.5194/amt-18-5393-2025, 2025
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This study leverages machine learning models to classify cloud thermodynamic phases using multi-sensor remote sensing data collected at the Department of Energy Atmospheric Radiation Measurement North Slope of Alaska observatory. We evaluate model performance, feature importance, and application of the model to another observatory and quantify how the models respond to instrument outages.
Yanjun Li, Violaine Coulon, Javier Blasco, Gang Qiao, Qinghua Yang, and Frank Pattyn
The Cryosphere, 19, 4373–4390, https://doi.org/10.5194/tc-19-4373-2025, https://doi.org/10.5194/tc-19-4373-2025, 2025
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We incorporate ice damage processes into an ice-sheet model and apply the new model to Thwaites Glacier. The upgraded model more accurately captures the observed ice mass loss of Thwaites Glacier over 1990–2020. Our simulations show that ice damage has a notable impact on the ice mass loss, grounding-line retreat, ice velocity, and ice thickness of the Thwaites Glacier basin. This study highlights the necessity for incorporating ice damage into ice-sheet models.
Yugo Kanaya, Roberto Sommariva, Alfonso Saiz-Lopez, Andrea Mazzeo, Theodore K. Koenig, Kaori Kawana, James E. Johnson, Aurélie Colomb, Pierre Tulet, Suzie Molloy, Ian E. Galbally, Rainer Volkamer, Anoop Mahajan, John W. Halfacre, Paul B. Shepson, Julia Schmale, Hélène Angot, Byron Blomquist, Matthew D. Shupe, Detlev Helmig, Junsu Gil, Meehye Lee, Sean C. Coburn, Ivan Ortega, Gao Chen, James Lee, Kenneth C. Aikin, David D. Parrish, John S. Holloway, Thomas B. Ryerson, Ilana B. Pollack, Eric J. Williams, Brian M. Lerner, Andrew J. Weinheimer, Teresa Campos, Frank M. Flocke, J. Ryan Spackman, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Ralf M. Staebler, Amir A. Aliabadi, Wanmin Gong, Roeland Van Malderen, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Juan Carlos Gómez Martin, Masatomo Fujiwara, Katie Read, Matthew Rowlinson, Keiichi Sato, Junichi Kurokawa, Yoko Iwamoto, Fumikazu Taketani, Hisahiro Takashima, Mónica Navarro-Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data, 17, 4901–4932, https://doi.org/10.5194/essd-17-4901-2025, https://doi.org/10.5194/essd-17-4901-2025, 2025
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The first comprehensive dataset of tropospheric ozone over oceans/polar regions is presented, including 77 ship/buoy and 48 aircraft campaign observations (1977–2022, 0–5000 m altitude), supplemented by ozonesonde and surface data. Air masses isolated from land for 72+ hours are systematically selected as essentially oceanic. Among the 11 global regions, they show daytime decreases of 11–16 % in the tropics, while near-zero depletions are rare, unlike in the Arctic, implying different mechanisms.
Peggy Achtert, Torsten Seelig, Gabriella Wallentin, Luisa Ickes, Matthew D. Shupe, Corinna Hoose, and Matthias Tesche
EGUsphere, https://doi.org/10.5194/egusphere-2025-3529, https://doi.org/10.5194/egusphere-2025-3529, 2025
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We quantify the occurrence of single- and multi-layer clouds in the Arctic based on combining soundings with cloud-radar observations. We also assess the rate of ice-crystal seeding in multi-layer cloud systems as this is an important initiator of glaciation in super-cooled liquid cloud layers. We find an abundance of multi-layer clouds in the Arctic with seeding in about half to two thirds of cases in which the gap between upper and lower layers ranges between 100 and 1000 m.
Jean Lac, Hélène Chepfer, Matthew D. Shupe, and Hannes Griesche
EGUsphere, https://doi.org/10.5194/egusphere-2025-3549, https://doi.org/10.5194/egusphere-2025-3549, 2025
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Satellite observations show that Arctic spring experiences a rapid increase in liquid-containing clouds over sea ice. Our study shows that this transition is mostly driven by warmer temperatures in early spring than in late spring, favoring more liquid clouds formation, rather than a limited moisture source in early spring. It suggests that, in the future, this transition is likely to occur earlier in spring considering the rapid Arctic warming.
Hu Yang, Xiaoxu Shi, Xulong Wang, Qingsong Liu, Yi Zhong, Xiaodong Liu, Youbin Sun, Yanjun Cai, Fei Liu, Gerrit Lohmann, Martin Werner, Zhimin Jian, Tainã M. L. Pinho, Hai Cheng, Lijuan Lu, Jiping Liu, Chao-Yuan Yang, Qinghua Yang, Yongyun Hu, Xing Cheng, Jingyu Zhang, and Dake Chen
Clim. Past, 21, 1263–1279, https://doi.org/10.5194/cp-21-1263-2025, https://doi.org/10.5194/cp-21-1263-2025, 2025
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For 1 century, the hemispheric summer insolation is proposed as a key pacemaker of astronomical climate change. However, an increasing number of geologic records reveal that the low-latitude hydrological cycle shows asynchronous precessional evolutions that are very often out of phase with the summer insolation. Here, we propose that the astronomically driven low-latitude hydrological cycle is not paced by summer insolation but by shifting perihelion.
Kerstin Ebell, Christian Buhren, Rosa Gierens, Giovanni Chellini, Melanie Lauer, Andreas Walbröl, Sandro Dahlke, Pavel Krobot, and Mario Mech
Atmos. Chem. Phys., 25, 7315–7342, https://doi.org/10.5194/acp-25-7315-2025, https://doi.org/10.5194/acp-25-7315-2025, 2025
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Ground-based observations of precipitation are rare in the Arctic. Since 2017, additional temporally highly resolved precipitation measurements have been carried out by a precipitation gauge and an optical precipitation sensor at Ny-Ålesund, Svalbard. These new data facilitate the distinction between liquid and solid precipitation. Using reanalysis data, we also find that water vapor transport contributes strongly to precipitation and especially to extreme precipitation events.
Albert Ansmann, Cristofer Jimenez, Johanna Roschke, Johannes Bühl, Kevin Ohneiser, Ronny Engelmann, Martin Radenz, Hannes Griesche, Julian Hofer, Dietrich Althausen, Daniel A. Knopf, Sandro Dahlke, Tom Gaudek, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 25, 4847–4866, https://doi.org/10.5194/acp-25-4847-2025, https://doi.org/10.5194/acp-25-4847-2025, 2025
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In this study, we focus on the potential impact of wildfire smoke on cirrus formation. For the first time, state-of-the-art aerosol and cirrus observations with lidar and radar, presented in this paper (Part 1 of a series of two articles), are closely linked to the comprehensive modeling of gravity-wave-induced ice nucleation in cirrus evolution processes, presented in a companion paper (Part 2). We found a clear impact of wildfire smoke on cirrus evolution.
Christopher J. Cox, Janet M. Intrieri, Brian J. Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data, 17, 1481–1499, https://doi.org/10.5194/essd-17-1481-2025, https://doi.org/10.5194/essd-17-1481-2025, 2025
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Snow is an essential water resource in the intermountain western United States, and predictions are made using models. We made observations to validate, constrain, and develop the models. The data are from the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign in Colorado's East River valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
Carola Barrientos-Velasco, Christopher J. Cox, Hartwig Deneke, J. Brant Dodson, Anja Hünerbein, Matthew D. Shupe, Patrick C. Taylor, and Andreas Macke
Atmos. Chem. Phys., 25, 3929–3960, https://doi.org/10.5194/acp-25-3929-2025, https://doi.org/10.5194/acp-25-3929-2025, 2025
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Understanding how clouds affect the climate, especially in the Arctic, is crucial. This study used data from the largest polar expedition in history, MOSAiC, and the CERES satellite to analyse the impact of clouds on radiation. Simulations showed accurate results, aligning with observations. Over the year, clouds caused the atmospheric surface system to lose 5.2 W m−² of radiative energy to space, while the surface gained 25 W m−² and the atmosphere cooled by 30.2 W m−².
Benjamin Heutte, Nora Bergner, Hélène Angot, Jakob B. Pernov, Lubna Dada, Jessica A. Mirrielees, Ivo Beck, Andrea Baccarini, Matthew Boyer, Jessie M. Creamean, Kaspar R. Daellenbach, Imad El Haddad, Markus M. Frey, Silvia Henning, Tiia Laurila, Vaios Moschos, Tuukka Petäjä, Kerri A. Pratt, Lauriane L. J. Quéléver, Matthew D. Shupe, Paul Zieger, Tuija Jokinen, and Julia Schmale
Atmos. Chem. Phys., 25, 2207–2241, https://doi.org/10.5194/acp-25-2207-2025, https://doi.org/10.5194/acp-25-2207-2025, 2025
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Limited aerosol measurements in the central Arctic hinder our understanding of aerosol–climate interactions in the region. Our year-long observations of aerosol physicochemical properties during the MOSAiC expedition reveal strong seasonal variations in aerosol chemical composition, where the short-term variability is heavily affected by storms in the Arctic. Local wind-generated particles are shown to be an important source of cloud seeds, especially in autumn.
Madison M. Smith, Niels Fuchs, Evgenii Salganik, Donald K. Perovich, Ian Raphael, Mats A. Granskog, Kirstin Schulz, Matthew D. Shupe, and Melinda Webster
The Cryosphere, 19, 619–644, https://doi.org/10.5194/tc-19-619-2025, https://doi.org/10.5194/tc-19-619-2025, 2025
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The fate of freshwater from Arctic sea ice and snowmelt impacts interactions of the atmosphere, sea ice, and ocean. We complete a comprehensive analysis of datasets from a 2020 central Arctic field campaign to understand the drivers of the sea ice freshwater budget and the fate of this water. Over half of the freshwater comes from surface melt, and a majority fraction is incorporated into the ocean. Results suggest that the representation of melt ponds is a key area for future development.
Han Zhang, Dake Chen, Tongya Liu, Di Tian, Min He, Qi Li, Guofei Wei, and Jian Liu
Earth Syst. Sci. Data, 16, 5665–5679, https://doi.org/10.5194/essd-16-5665-2024, https://doi.org/10.5194/essd-16-5665-2024, 2024
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This paper provides a cross-shaped moored array dataset (MASCS 1.0) of observations that consist of five buoys and four moorings in the northern South China Sea from 2014 to 2015. The moored array is influenced by atmospheric forcings such as tropical cyclones and monsoon as well as oceanic tides and flows. The data reveal variations of the air–sea interface and the ocean itself, which are valuable for studies of air–sea interactions and ocean dynamics in the northern South China Sea.
Johanna Tjernström, Michael Gallagher, Jareth Holt, Gunilla Svensson, Matthew D. Shupe, Jonathan J. Day, Lara Ferrighi, Siri Jodha Khalsa, Leslie M. Hartten, Ewan O'Connor, Zen Mariani, and Øystein Godøy
EGUsphere, https://doi.org/10.5194/egusphere-2024-2088, https://doi.org/10.5194/egusphere-2024-2088, 2024
Preprint archived
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The value of numerical weather predictions can be enhanced in several ways, one is to improve the representations of small-scale processes in models. To understand what needs to be improved, the model results need to be evaluated. Following standardized principles, a file format has been defined to be as similar as possible for both observational and model data. Python packages and toolkits are presented as a community resource in the production of the files and evaluation analysis.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
The Cryosphere, 18, 1215–1239, https://doi.org/10.5194/tc-18-1215-2024, https://doi.org/10.5194/tc-18-1215-2024, 2024
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We present a new atmosphere–ocean–wave–sea ice coupled model to study the influences of ocean waves on Arctic sea ice simulation. Our results show (1) smaller ice-floe size with wave breaking increases ice melt, (2) the responses in the atmosphere and ocean to smaller floe size partially reduce the effect of the enhanced ice melt, (3) the limited oceanic energy is a strong constraint for ice melt enhancement, and (4) ocean waves can indirectly affect sea ice through the atmosphere and the ocean.
Michael Lonardi, Elisa F. Akansu, André Ehrlich, Mauro Mazzola, Christian Pilz, Matthew D. Shupe, Holger Siebert, and Manfred Wendisch
Atmos. Chem. Phys., 24, 1961–1978, https://doi.org/10.5194/acp-24-1961-2024, https://doi.org/10.5194/acp-24-1961-2024, 2024
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Profiles of thermal-infrared irradiance were measured at two Arctic sites. The presence or lack of clouds influences the vertical structure of these observations. In particular, the cloud top region is a source of radiative energy that can promote cooling and mixing in the cloud layer. Simulations are used to further characterize how the amount of water in the cloud modifies this forcing. A case study additionally showcases the evolution of the radiation profiles in a dynamic atmosphere.
Maximilian Maahn, Dmitri Moisseev, Isabelle Steinke, Nina Maherndl, and Matthew D. Shupe
Atmos. Meas. Tech., 17, 899–919, https://doi.org/10.5194/amt-17-899-2024, https://doi.org/10.5194/amt-17-899-2024, 2024
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The open-source Video In Situ Snowfall Sensor (VISSS) is a novel instrument for characterizing particle shape, size, and sedimentation velocity in snowfall. It combines a large observation volume with relatively high resolution and a design that limits wind perturbations. The open-source nature of the VISSS hardware and software invites the community to contribute to the development of the instrument, which has many potential applications in atmospheric science and beyond.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 24, 1429–1450, https://doi.org/10.5194/acp-24-1429-2024, https://doi.org/10.5194/acp-24-1429-2024, 2024
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Observations collected during MOSAiC were used to identify the range in vertical structure and stability of the central Arctic lower atmosphere through a self-organizing map analysis. Characteristics of wind features (such as low-level jets) and atmospheric moisture features (such as clouds) were analyzed in the context of the varying vertical structure and stability. Thus, the results of this paper give an overview of the thermodynamic and kinematic features of the central Arctic atmosphere.
Elisa F. Akansu, Sandro Dahlke, Holger Siebert, and Manfred Wendisch
Atmos. Chem. Phys., 23, 15473–15489, https://doi.org/10.5194/acp-23-15473-2023, https://doi.org/10.5194/acp-23-15473-2023, 2023
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The height of the mixing layer is an important measure of the surface-level distribution of energy or other substances. The experimental determination of this height is associated with large uncertainties, particularly under stable conditions that we often find during the polar night or in the presence of clouds. We present a reference method using turbulence measurements on a tethered balloon, which allows us to evaluate approaches based on radiosondes or surface observations.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
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Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Shaohui Zhou, Chloe Yuchao Gao, Zexia Duan, Xingya Xi, and Yubin Li
Geosci. Model Dev., 16, 6247–6266, https://doi.org/10.5194/gmd-16-6247-2023, https://doi.org/10.5194/gmd-16-6247-2023, 2023
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The proposed wind speed correction model (VMD-PCA-RF) demonstrates the highest prediction accuracy and stability in the five southern provinces in nearly a year and at different heights. VMD-PCA-RF evaluation indices for 13 months remain relatively stable: the forecasting accuracy rate FA is above 85 %. In future research, the proposed VMD-PCA-RF algorithm can be extrapolated to the 3 km grid points of the five southern provinces to generate a 3 km grid-corrected wind speed product.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 23, 13087–13106, https://doi.org/10.5194/acp-23-13087-2023, https://doi.org/10.5194/acp-23-13087-2023, 2023
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Observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) were used to determine the frequency of occurrence of various central Arctic lower atmospheric stability regimes and how the stability regimes transition between each other. Wind and radiation observations were analyzed in the context of stability regime and season to reveal the relationships between Arctic atmospheric stability and mechanically and radiatively driven turbulent forcings.
Albert Ansmann, Kevin Ohneiser, Ronny Engelmann, Martin Radenz, Hannes Griesche, Julian Hofer, Dietrich Althausen, Jessie M. Creamean, Matthew C. Boyer, Daniel A. Knopf, Sandro Dahlke, Marion Maturilli, Henriette Gebauer, Johannes Bühl, Cristofer Jimenez, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 23, 12821–12849, https://doi.org/10.5194/acp-23-12821-2023, https://doi.org/10.5194/acp-23-12821-2023, 2023
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The 1-year MOSAiC (2019–2020) expedition with the German ice breaker Polarstern was the largest polar field campaign ever conducted. The Polarstern, with our lidar aboard, drifted with the pack ice north of 85° N for more than 7 months (October 2019 to mid-May 2020). We measured the full annual cycle of aerosol conditions in terms of aerosol optical and cloud-process-relevant properties. We observed a strong contrast between polluted winter and clean summer aerosol conditions.
Olivia Linke, Johannes Quaas, Finja Baumer, Sebastian Becker, Jan Chylik, Sandro Dahlke, André Ehrlich, Dörthe Handorf, Christoph Jacobi, Heike Kalesse-Los, Luca Lelli, Sina Mehrdad, Roel A. J. Neggers, Johannes Riebold, Pablo Saavedra Garfias, Niklas Schnierstein, Matthew D. Shupe, Chris Smith, Gunnar Spreen, Baptiste Verneuil, Kameswara S. Vinjamuri, Marco Vountas, and Manfred Wendisch
Atmos. Chem. Phys., 23, 9963–9992, https://doi.org/10.5194/acp-23-9963-2023, https://doi.org/10.5194/acp-23-9963-2023, 2023
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Lapse rate feedback (LRF) is a major driver of the Arctic amplification (AA) of climate change. It arises because the warming is stronger at the surface than aloft. Several processes can affect the LRF in the Arctic, such as the omnipresent temperature inversion. Here, we compare multimodel climate simulations to Arctic-based observations from a large research consortium to broaden our understanding of these processes, find synergy among them, and constrain the Arctic LRF and AA.
Manfred Wendisch, Johannes Stapf, Sebastian Becker, André Ehrlich, Evelyn Jäkel, Marcus Klingebiel, Christof Lüpkes, Michael Schäfer, and Matthew D. Shupe
Atmos. Chem. Phys., 23, 9647–9667, https://doi.org/10.5194/acp-23-9647-2023, https://doi.org/10.5194/acp-23-9647-2023, 2023
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Atmospheric radiation measurements have been conducted during two field campaigns using research aircraft. The data are analyzed to see if the near-surface air in the Arctic is warmed or cooled if warm–humid air masses from the south enter the Arctic or cold–dry air moves from the north from the Arctic to mid-latitude areas. It is important to study these processes and to check if climate models represent them well. Otherwise it is not possible to reliably forecast the future Arctic climate.
Kameswara S. Vinjamuri, Marco Vountas, Luca Lelli, Martin Stengel, Matthew D. Shupe, Kerstin Ebell, and John P. Burrows
Atmos. Meas. Tech., 16, 2903–2918, https://doi.org/10.5194/amt-16-2903-2023, https://doi.org/10.5194/amt-16-2903-2023, 2023
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Clouds play an important role in Arctic amplification. Cloud data from ground-based sites are valuable but cannot represent the whole Arctic. Therefore the use of satellite products is a measure to cover the entire Arctic. However, the quality of such cloud measurements from space is not well known. The paper discusses the differences and commonalities between satellite and ground-based measurements. We conclude that the satellite dataset, with a few exceptions, can be used in the Arctic.
Ulrike Egerer, John J. Cassano, Matthew D. Shupe, Gijs de Boer, Dale Lawrence, Abhiram Doddi, Holger Siebert, Gina Jozef, Radiance Calmer, Jonathan Hamilton, Christian Pilz, and Michael Lonardi
Atmos. Meas. Tech., 16, 2297–2317, https://doi.org/10.5194/amt-16-2297-2023, https://doi.org/10.5194/amt-16-2297-2023, 2023
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This paper describes how measurements from a small uncrewed aircraft system can be used to estimate the vertical turbulent heat energy exchange between different layers in the atmosphere. This is particularly important for the atmosphere in the Arctic, as turbulent exchange in this region is often suppressed but is still important to understand how the atmosphere interacts with sea ice. We present three case studies from the MOSAiC field campaign in Arctic sea ice in 2020.
Felix Pithan, Marylou Athanase, Sandro Dahlke, Antonio Sánchez-Benítez, Matthew D. Shupe, Anne Sledd, Jan Streffing, Gunilla Svensson, and Thomas Jung
Geosci. Model Dev., 16, 1857–1873, https://doi.org/10.5194/gmd-16-1857-2023, https://doi.org/10.5194/gmd-16-1857-2023, 2023
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Evaluating climate models usually requires long observational time series, but we present a method that also works for short field campaigns. We compare climate model output to observations from the MOSAiC expedition in the central Arctic Ocean. All models show how the arrival of a warm air mass warms the Arctic in April 2020, but two models do not show the response of snow temperature to the diurnal cycle. One model has too little liquid water and too much ice in clouds during cold days.
Jinfei Wang, Chao Min, Robert Ricker, Qian Shi, Bo Han, Stefan Hendricks, Renhao Wu, and Qinghua Yang
The Cryosphere, 16, 4473–4490, https://doi.org/10.5194/tc-16-4473-2022, https://doi.org/10.5194/tc-16-4473-2022, 2022
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The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
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This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Gina Jozef, John Cassano, Sandro Dahlke, and Gijs de Boer
Atmos. Meas. Tech., 15, 4001–4022, https://doi.org/10.5194/amt-15-4001-2022, https://doi.org/10.5194/amt-15-4001-2022, 2022
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During the MOSAiC expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 uncrewed aircraft system. These data were used to identify the best method for atmospheric boundary layer height detection by comparing visually identified subjective boundary layer height to that identified by several objective automated detection methods. The results show a bulk Richardson number-based approach gives the best estimate of boundary layer height.
Assia Arouf, Hélène Chepfer, Thibault Vaillant de Guélis, Marjolaine Chiriaco, Matthew D. Shupe, Rodrigo Guzman, Artem Feofilov, Patrick Raberanto, Tristan S. L'Ecuyer, Seiji Kato, and Michael R. Gallagher
Atmos. Meas. Tech., 15, 3893–3923, https://doi.org/10.5194/amt-15-3893-2022, https://doi.org/10.5194/amt-15-3893-2022, 2022
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We proposed new estimates of the surface longwave (LW) cloud radiative effect (CRE) derived from observations collected by a space-based lidar on board the CALIPSO satellite and radiative transfer computations. Our estimate appropriately captures the surface LW CRE annual variability over bright polar surfaces, and it provides a dataset more than 13 years long.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Fengguan Gu, Qinghua Yang, Frank Kauker, Changwei Liu, Guanghua Hao, Chao-Yuan Yang, Jiping Liu, Petra Heil, Xuewei Li, and Bo Han
The Cryosphere, 16, 1873–1887, https://doi.org/10.5194/tc-16-1873-2022, https://doi.org/10.5194/tc-16-1873-2022, 2022
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The sea ice thickness was simulated by a single-column model and compared with in situ observations obtained off Zhongshan Station in the Antarctic. It is shown that the unrealistic precipitation in the atmospheric forcing data leads to the largest bias in sea ice thickness and snow depth modeling. In addition, the increasing snow depth gradually inhibits the growth of sea ice associated with thermal blanketing by the snow.
Sutao Liao, Hao Luo, Jinfei Wang, Qian Shi, Jinlun Zhang, and Qinghua Yang
The Cryosphere, 16, 1807–1819, https://doi.org/10.5194/tc-16-1807-2022, https://doi.org/10.5194/tc-16-1807-2022, 2022
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The Global Ice-Ocean Modeling and Assimilation System (GIOMAS) can basically reproduce the observed variability in Antarctic sea-ice volume and its changes in the trend before and after 2013, and it underestimates Antarctic sea-ice thickness (SIT) especially in deformed ice zones. Assimilating additional sea-ice observations with advanced assimilation methods may result in a more accurate estimation of Antarctic SIT.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
Geosci. Model Dev., 15, 1155–1176, https://doi.org/10.5194/gmd-15-1155-2022, https://doi.org/10.5194/gmd-15-1155-2022, 2022
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We present an improved coupled modeling system for Arctic sea ice prediction. We perform Arctic sea ice prediction experiments with improved/updated physical parameterizations, which show better skill in predicting sea ice state as well as atmospheric and oceanic state in the Arctic compared with its predecessor. The improved model also shows extended predictive skill of Arctic sea ice after the summer season. This provides an added value of this prediction system for decision-making.
Michael R. Gallagher, Matthew D. Shupe, Hélène Chepfer, and Tristan L'Ecuyer
The Cryosphere, 16, 435–450, https://doi.org/10.5194/tc-16-435-2022, https://doi.org/10.5194/tc-16-435-2022, 2022
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By using direct observations of snowfall and mass changes, the variability of daily snowfall mass input to the Greenland ice sheet is quantified for the first time. With new methods we conclude that cyclones west of Greenland in summer contribute the most snowfall, with 1.66 Gt per occurrence. These cyclones are contextualized in the broader Greenland climate, and snowfall is validated against mass changes to verify the results. Snowfall and mass change observations are shown to agree well.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
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We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Ronny Engelmann, Albert Ansmann, Kevin Ohneiser, Hannes Griesche, Martin Radenz, Julian Hofer, Dietrich Althausen, Sandro Dahlke, Marion Maturilli, Igor Veselovskii, Cristofer Jimenez, Robert Wiesen, Holger Baars, Johannes Bühl, Henriette Gebauer, Moritz Haarig, Patric Seifert, Ulla Wandinger, and Andreas Macke
Atmos. Chem. Phys., 21, 13397–13423, https://doi.org/10.5194/acp-21-13397-2021, https://doi.org/10.5194/acp-21-13397-2021, 2021
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A Raman lidar was operated aboard the icebreaker Polarstern during MOSAiC and monitored aerosol and cloud layers in the central Arctic up to 30 km height. The article provides an overview of the spectrum of aerosol profiling observations and shows aerosol–cloud interaction studies for liquid-water and ice clouds. A highlight was the detection of a 10 km deep wildfire smoke layer over the North Pole up to 17 km height from the fire season of 2019, which persisted over the whole winter period.
Benjamin Männel, Florian Zus, Galina Dick, Susanne Glaser, Maximilian Semmling, Kyriakos Balidakis, Jens Wickert, Marion Maturilli, Sandro Dahlke, and Harald Schuh
Atmos. Meas. Tech., 14, 5127–5138, https://doi.org/10.5194/amt-14-5127-2021, https://doi.org/10.5194/amt-14-5127-2021, 2021
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Within the MOSAiC expedition, GNSS was used to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked data, coordinates and hourly zenith total delays (ZTDs) were determined using kinematic precise point positioning. The derived ZTD values agree within few millimeters with ERA5 and terrestrial GNSS and VLBI stations. The derived integrated water vapor corresponds to the frequently launched radiosondes (0.08 ± 0.04 kg m−2, rms of the differences of 1.47 kg m−2).
Jessie M. Creamean, Gijs de Boer, Hagen Telg, Fan Mei, Darielle Dexheimer, Matthew D. Shupe, Amy Solomon, and Allison McComiskey
Atmos. Chem. Phys., 21, 1737–1757, https://doi.org/10.5194/acp-21-1737-2021, https://doi.org/10.5194/acp-21-1737-2021, 2021
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Arctic clouds play a role in modulating sea ice extent. Importantly, aerosols facilitate cloud formation, and thus it is crucial to understand the interactions between aerosols and clouds. Vertical measurements of aerosols and clouds are needed to tackle this issue. We present results from balloon-borne measurements of aerosols and clouds over the course of 2 years in northern Alaska. These data shed light onto the vertical distributions of aerosols relative to clouds spanning multiple seasons.
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Short summary
Due to a lack of observations, the structure of the Arctic atmospheric boundary layer (ABL) remains to be further explored. By analyzing a year-round radiosonde dataset collected over the Arctic sea-ice surface, we found the annual cycle of the ABL height (ABLH) is primarily controlled by the evolution of ABL thermal structure, and the surface conditions also show a high correlation with ABLH variation. In addition, the Arctic ABLH is found to be decreased in summer compared with 20 years ago.
Due to a lack of observations, the structure of the Arctic atmospheric boundary layer (ABL)...
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