Articles | Volume 16, issue 7
https://doi.org/10.5194/gmd-16-1857-2023
© 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/gmd-16-1857-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
04 Apr 2023
Methods for assessment of models |
| 04 Apr 2023
| 04 Apr 2023
Nudging allows direct evaluation of coupled climate models with in situ observations: a case study from the MOSAiC expedition
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven/Potsdam, Germany
Marylou Athanase
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven/Potsdam, Germany
Sandro Dahlke
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven/Potsdam, Germany
Antonio Sánchez-Benítez
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven/Potsdam, Germany
Matthew D. Shupe
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
National Oceanic and Atmospheric Administration Physical Science Laboratory, Boulder, Colorado
Anne Sledd
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
National Oceanic and Atmospheric Administration Physical Science Laboratory, Boulder, Colorado
Jan Streffing
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven/Potsdam, Germany
Department of Mathematics and Logistics, Jacobs University Bremen, Bremen, Germany
Gunilla Svensson
Department of Meteorology and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Thomas Jung
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven/Potsdam, Germany
Institute of Environmental Physics, University of Bremen, Bremen, Germany
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Representing the exchange of air masses between the Arctic and mid-latitudes and the associated cloud formation is difficult for climate models. We compare climate model output to temperature and humidity measurements from weather balloons to provide suggestions for model improvements. Cold biases mostly occur in air that is exported from the Arctic. Models that compute the number of ice particles in a cloud better represent humidity than models that assume a fixed number of ice particles.
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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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.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
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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, Monica Navarro Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-566, https://doi.org/10.5194/essd-2024-566, 2025
Revised manuscript accepted for ESSD
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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.
Tatiana Klimiuk, Patrick Ludwig, Antonio Sanchez-Benitez, Helge F. Goessling, Peter Braesicke, and Joaquim G. Pinto
Earth Syst. Dynam., 16, 239–255, https://doi.org/10.5194/esd-16-239-2025, https://doi.org/10.5194/esd-16-239-2025, 2025
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Our study examines potential changes in heatwaves in central Europe due to global warming, using the 2019 summer heatwave as an example. By producing high-resolution storylines, we provide insights into how future heatwaves might spread, how they might persist for longer, and where stronger or weaker temperature increases may occur. This research helps us understand regional thermodynamic responses and highlights the importance of local strategies to protect communities from future heat events.
Michail Karalis, Gunilla Svensson, Manfred Wendisch, and Michael Tjernström
EGUsphere, https://doi.org/10.5194/egusphere-2024-3709, https://doi.org/10.5194/egusphere-2024-3709, 2025
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During the spring Arctic warm-air intrusion captured by HALO-(𝒜𝒞)3, the airmass demonstrated a column-like structure. We built a Lagrangian modeling framework using a single-column model (AOSCM) to simulate the airmass transformation. Comparing to observations, reanalysis and forecast data, we found that the AOSCM can successfully reproduce the main features of the transformation. The framework can be used for future model development to improve Arctic weather and climate prediction.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
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.
Shreya Trivedi, Imke Sievers, Marylou Athanase, Antonio Sánchez Benítez, and Tido Semmler
EGUsphere, https://doi.org/10.5194/egusphere-2024-2214, https://doi.org/10.5194/egusphere-2024-2214, 2024
Preprint archived
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Our study introduces a new method to compare CMIP6 models' sea ice and snow simulations with in-situ (MOSAiC) measurements. We assessed models for their accuracy in replicating Arctic sea ice and snow thicknesses, using two sea-ice and atmosphere-based methods to select "proxy years." We show that the models often overestimate snow thickness and mistime sea ice cycles. Despite limitations, this approach provides a valuable tool for evaluating climate models in localized time and space.
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.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
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During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
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.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
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.
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.
Shijie Peng, Qinghua Yang, Matthew D. Shupe, Xingya Xi, Bo Han, Dake Chen, Sandro Dahlke, and Changwei Liu
Atmos. Chem. Phys., 23, 8683–8703, https://doi.org/10.5194/acp-23-8683-2023, https://doi.org/10.5194/acp-23-8683-2023, 2023
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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.
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.
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.
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
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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.
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.
Sara Pasqualetto, Luisa Cristini, and Thomas Jung
Geosci. Commun., 5, 87–100, https://doi.org/10.5194/gc-5-87-2022, https://doi.org/10.5194/gc-5-87-2022, 2022
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Many projects in their reporting phase are required to provide a clear plan for evaluating the results of those efforts aimed at translating scientific results to a broader audience. This paper illustrates methodologies and strategies used in the framework of a European research project to assess the impact of knowledge transfer activities, both quantitatively and qualitatively, and provides recommendations and hints for developing a useful impact plan for scientific projects.
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.
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
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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.
Sonja Murto, Rodrigo Caballero, Gunilla Svensson, and Lukas Papritz
Weather Clim. Dynam., 3, 21–44, https://doi.org/10.5194/wcd-3-21-2022, https://doi.org/10.5194/wcd-3-21-2022, 2022
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This study uses reanalysis data to investigate the role of atmospheric blocking, prevailing high-pressure systems and mid-latitude cyclones in driving high-Arctic wintertime warm extreme events. These events are mainly preceded by Ural and Scandinavian blocks, which are shown to be significantly influenced and amplified by cyclones in the North Atlantic. It also highlights processes that need to be well captured in climate models for improving their representation of Arctic wintertime climate.
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.
Lena Frey, Frida A.-M. Bender, and Gunilla Svensson
Atmos. Chem. Phys., 21, 577–595, https://doi.org/10.5194/acp-21-577-2021, https://doi.org/10.5194/acp-21-577-2021, 2021
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We investigate the vertical distribution of aerosol in the climate model NorESM1-M in five regions of marine stratocumulus clouds. We thereby analyze the total aerosol extinction to facilitate a comparison with satellite data. We find that the model underestimates aerosol extinction throughout the troposphere, especially elevated aerosol layers. Further, we perform sensitivity experiments to identify the processes most important for vertical aerosol distribution in our model.
Peggy Achtert, Ewan J. O'Connor, Ian M. Brooks, Georgia Sotiropoulou, Matthew D. Shupe, Bernhard Pospichal, Barbara J. Brooks, and Michael Tjernström
Atmos. Chem. Phys., 20, 14983–15002, https://doi.org/10.5194/acp-20-14983-2020, https://doi.org/10.5194/acp-20-14983-2020, 2020
Short summary
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We present observations of precipitating and non-precipitating Arctic liquid and mixed-phase clouds during a research cruise along the Russian shelf in summer and autumn of 2014. Active remote-sensing observations, radiosondes, and auxiliary measurements are combined in the synergistic Cloudnet retrieval. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. About 8 % of all liquid clouds show a liquid water path below the infrared black body limit.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
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Short summary
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.
Evaluating climate models usually requires long observational time series, but we present a...
