Articles | Volume 17, issue 14
https://doi.org/10.5194/gmd-17-5511-2024
© Author(s) 2024. 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-17-5511-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
24 Jul 2024
Model evaluation paper |
| 24 Jul 2024
| 24 Jul 2024
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
Gunilla Svensson
Department of Meteorology and Bolin Centre for Climate Change, Stockholm University, Stockholm, Sweden
Barbara Casati
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Canada
Taneil Uttal
NOAA Physical Science Laboratory, Boulder, Colorado, USA
Siri-Jodha Khalsa
National Snow and Ice Data Center, University of Colorado, Boulder, Colorado, USA
Eric Bazile
Météo-France, Toulouse, France
Elena Akish
NOAA Physical Science Laboratory, Boulder, Colorado, USA
Niramson Azouz
Météo-France, Toulouse, France
Lara Ferrighi
Norwegian Meteorological Institute, Oslo, Norway
Helmut Frank
Deutscher Wetterdienst, Offenbach, Germany
Michael Gallagher
NOAA Physical Science Laboratory, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado Boulder, Boulder, Colorado, USA
Øystein Godøy
Norwegian Meteorological Institute, Oslo, Norway
Leslie M. Hartten
NOAA Physical Science Laboratory, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado Boulder, Boulder, Colorado, USA
Laura X. Huang
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Canada
Jareth Holt
Department of Meteorology and Bolin Centre for Climate Change, Stockholm University, Stockholm, Sweden
Massimo Di Stefano
Norwegian Meteorological Institute, Oslo, Norway
Irene Suomi
Finnish Meteorological Institute, Helsinki, Finland
Zen Mariani
Meteorological Research Division, Environment and Climate Change Canada, Dorval, Canada
Sara Morris
NOAA Physical Science Laboratory, Boulder, Colorado, USA
Ewan O'Connor
Finnish Meteorological Institute, Helsinki, Finland
Roberta Pirazzini
Finnish Meteorological Institute, Helsinki, Finland
Teresa Remes
Norwegian Meteorological Institute, Oslo, Norway
Rostislav Fadeev
Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia
Amy Solomon
NOAA Physical Science Laboratory, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado Boulder, Boulder, Colorado, USA
Johanna Tjernström
Swedish Meteorological and Hydrological Institute, Linköping, Sweden
Mikhail Tolstykh
Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia
Hydrometeorological Research Centre of Russia, Moscow, Russia
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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
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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.
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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.
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024, https://doi.org/10.5194/nhess-24-2115-2024, 2024
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The risk posed to ships by Arctic cyclones has seldom been quantified due to the lack of publicly available historical Arctic ship track data. This study investigates historical Arctic ship tracks, cyclone tracks, and shipping incident reports to determine the number of shipping incidents caused by the passage of Arctic cyclones. Results suggest that Arctic cyclones have not been hazardous to ships and that ships are resilient to the rough sea conditions caused by Arctic cyclones.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
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In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
Alexander F. Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Weather Clim. Dynam., 3, 1097–1112, https://doi.org/10.5194/wcd-3-1097-2022, https://doi.org/10.5194/wcd-3-1097-2022, 2022
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Understanding the location and intensity of hazardous weather across the Arctic is important for assessing risks to infrastructure, shipping, and coastal communities. This study describes the typical lifetime and structure of intense winter and summer Arctic cyclones. Results show the composite development and structure of intense summer Arctic cyclones are different from intense winter Arctic and North Atlantic Ocean extra-tropical cyclones and from conceptual models.
Jonathan J. Day, Sarah Keeley, Gabriele Arduini, Linus Magnusson, Kristian Mogensen, Mark Rodwell, Irina Sandu, and Steffen Tietsche
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A recent drive to develop seamless forecasting systems has culminated in the development of weather forecasting systems that include a coupled representation of the atmosphere, ocean and sea ice. Before this, sea ice and sea surface temperature anomalies were typically fixed throughout a given forecast. We show that the dynamic coupling is most beneficial during periods of rapid ice advance, where persistence is a poor forecast of the sea ice and leads to large errors in the uncoupled system.
Paul J. Valdes, Edward Armstrong, Marcus P. S. Badger, Catherine D. Bradshaw, Fran Bragg, Michel Crucifix, Taraka Davies-Barnard, Jonathan J. Day, Alex Farnsworth, Chris Gordon, Peter O. Hopcroft, Alan T. Kennedy, Natalie S. Lord, Dan J. Lunt, Alice Marzocchi, Louise M. Parry, Vicky Pope, William H. G. Roberts, Emma J. Stone, Gregory J. L. Tourte, and Jonny H. T. Williams
Geosci. Model Dev., 10, 3715–3743, https://doi.org/10.5194/gmd-10-3715-2017, https://doi.org/10.5194/gmd-10-3715-2017, 2017
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In this paper we describe the family of climate models used by the BRIDGE research group at the University of Bristol as well as by various other institutions. These models are based on the UK Met Office HadCM3 models and here we describe the various modifications which have been made as well as the key features of a number of configurations in use.
Tom Edinburgh and Jonathan J. Day
The Cryosphere, 10, 2721–2730, https://doi.org/10.5194/tc-10-2721-2016, https://doi.org/10.5194/tc-10-2721-2016, 2016
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Contrary to expectations, Antarctic sea ice cover has been increasing in area during the last three decades. In order to put these trends into a wider context this paper analyses direct observations of sea ice, recorded in ships' logbooks during the Heroic Age of Antarctic Exploration (1887–1917) for the first time. It shows that the sea ice was significantly further north in the Weddell Sea during the period but comparable to the present day in other sectors.
Jonathan J. Day, Steffen Tietsche, Mat Collins, Helge F. Goessling, Virginie Guemas, Anabelle Guillory, William J. Hurlin, Masayoshi Ishii, Sarah P. E. Keeley, Daniela Matei, Rym Msadek, Michael Sigmond, Hiroaki Tatebe, and Ed Hawkins
Geosci. Model Dev., 9, 2255–2270, https://doi.org/10.5194/gmd-9-2255-2016, https://doi.org/10.5194/gmd-9-2255-2016, 2016
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Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable.
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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A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-56, https://doi.org/10.5194/essd-2025-56, 2025
Preprint under review for ESSD
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This article presents the data management strategies of the Nansen Legacy project, developed to handle data from 300+ researchers and 20 expeditions in the northern Barents Sea. Data collection protocols were documented and followed for consistency, and a searchable data overview was available soon after each cruise. The project required early data sharing and publishing in line with FAIR principles where possible. This article details these strategies to guide future projects.
Simo Tukiainen, Tuomas Siipola, Niko Leskinen, and Ewan O'Connor
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-605, https://doi.org/10.5194/essd-2024-605, 2025
Preprint under review for ESSD
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Measurement campaigns are crucial for advancing the understanding of complex cloud–aerosol interactions in the atmosphere. Ground-based remote sensing measurements were conducted in Kenttärova, Finland, during the PaCE 2022 campaign. These measurements were processed using the Cloudnet methodology, and the data are available through the ACTRIS Cloudnet data portal.
Michail Karalis, Gunilla Svensson, Manfred Wendisch, and Michael Tjernström
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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.
Sasu Karttunen, Matthias Sühring, Ewan O'Connor, and Leena Järvi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-235, https://doi.org/10.5194/gmd-2024-235, 2024
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This paper presents PALM-SLUrb, a single-layer urban canopy model for the PALM system, designed to simulate urban-atmosphere interactions without resolving flow around individual buildings. The model is described in detail and evaluated against grid-resolved urban canopy simulations, demonstrating its ability to model urban surfaces accurately. By bridging the gap between computational efficiency and physical detail, PALM-SLUrb broadens PALM's potential for urban climate research.
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
Short summary
Short summary
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.
Jutta Kesti, Ewan J. O'Connor, Anne Hirsikko, John Backman, Maria Filioglou, Anu-Maija Sundström, Juha Tonttila, Heikki Lihavainen, Hannele Korhonen, and Eija Asmi
Atmos. Chem. Phys., 24, 9369–9386, https://doi.org/10.5194/acp-24-9369-2024, https://doi.org/10.5194/acp-24-9369-2024, 2024
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The study combines aerosol particle measurements at the surface and vertical profiling of the atmosphere with a scanning Doppler lidar to investigate how particle transportation together with boundary layer evolution can affect particle and SO2 concentrations at the surface in the Arabian Peninsula region. The instrumentation enabled us to see elevated nucleation mode particle and SO2 concentrations at the surface when air masses transported from polluted areas are mixed in the boundary layer.
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.
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
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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.
Shan Sun and Amy Solomon
The Cryosphere, 18, 3033–3048, https://doi.org/10.5194/tc-18-3033-2024, https://doi.org/10.5194/tc-18-3033-2024, 2024
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The study brings to light the suitability of CICE for seasonal prediction being contingent on several factors, such as initial conditions like sea ice coverage and thickness, as well as atmospheric and oceanic conditions including oceanic currents and sea surface temperature. We show there is potential to improve seasonal forecasting by using a more reliable sea ice thickness initialization. Thus, data assimilation of sea ice thickness is highly relevant for advancing seasonal prediction skills.
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
Short summary
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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.
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024, https://doi.org/10.5194/nhess-24-2115-2024, 2024
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The risk posed to ships by Arctic cyclones has seldom been quantified due to the lack of publicly available historical Arctic ship track data. This study investigates historical Arctic ship tracks, cyclone tracks, and shipping incident reports to determine the number of shipping incidents caused by the passage of Arctic cyclones. Results suggest that Arctic cyclones have not been hazardous to ships and that ships are resilient to the rough sea conditions caused by Arctic cyclones.
Xin Yang, Kimberly Strong, Alison S. Criscitiello, Marta Santos-Garcia, Kristof Bognar, Xiaoyi Zhao, Pierre Fogal, Kaley A. Walker, Sara M. Morris, and Peter Effertz
Atmos. Chem. Phys., 24, 5863–5886, https://doi.org/10.5194/acp-24-5863-2024, https://doi.org/10.5194/acp-24-5863-2024, 2024
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This study uses snow samples collected from a Canadian high Arctic site, Eureka, to demonstrate that surface snow in early spring is a net sink of atmospheric bromine and nitrogen. Surface snow bromide and nitrate are significantly correlated, indicating the oxidation of reactive nitrogen is accelerated by reactive bromine. In addition, we show evidence that snow photochemical release of reactive bromine is very weak, and its emission flux is much smaller than the deposition flux of bromide.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
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This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
Philippe Ricaud, Massimo Del Guasta, Angelo Lupi, Romain Roehrig, Eric Bazile, Pierre Durand, Jean-Luc Attié, Alessia Nicosia, and Paolo Grigioni
Atmos. Chem. Phys., 24, 613–630, https://doi.org/10.5194/acp-24-613-2024, https://doi.org/10.5194/acp-24-613-2024, 2024
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Clouds affect the Earth's climate in ways that depend on the type of cloud (solid/liquid water). From observations at Concordia (Antarctica), we show that in supercooled liquid water (liquid water for temperatures below 0°C) clouds (SLWCs), temperature and SLWC radiative forcing increase with liquid water (up to 70 W m−2). We extrapolated that the maximum SLWC radiative forcing can reach 40 W m−2 over the Antarctic Peninsula, highlighting the importance of SLWCs for global climate prediction.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
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The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Maria Filioglou, Ari Leskinen, Ville Vakkari, Ewan O'Connor, Minttu Tuononen, Pekko Tuominen, Samuli Laukkanen, Linnea Toiviainen, Annika Saarto, Xiaoxia Shang, Petri Tiitta, and Mika Komppula
Atmos. Chem. Phys., 23, 9009–9021, https://doi.org/10.5194/acp-23-9009-2023, https://doi.org/10.5194/acp-23-9009-2023, 2023
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Pollen impacts climate and public health, and it can be detected in the atmosphere by lidars which measure the linear particle depolarization ratio (PDR), a shape-relevant optical parameter. As aerosols also cause depolarization, surface aerosol and pollen observations were combined with measurements from ground-based lidars operating at different wavelengths to determine the optical properties of birch and pine pollen and quantify their relative contribution to the PDR.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
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In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
Pyry Pentikäinen, Ewan J. O'Connor, and Pablo Ortiz-Amezcua
Geosci. Model Dev., 16, 2077–2094, https://doi.org/10.5194/gmd-16-2077-2023, https://doi.org/10.5194/gmd-16-2077-2023, 2023
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We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
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.
Konstantinos Matthaios Doulgeris, Ville Vakkari, Ewan J. O'Connor, Veli-Matti Kerminen, Heikki Lihavainen, and David Brus
Atmos. Chem. Phys., 23, 2483–2498, https://doi.org/10.5194/acp-23-2483-2023, https://doi.org/10.5194/acp-23-2483-2023, 2023
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We investigated how different long-range-transported air masses can affect the microphysical properties of low-level clouds in a clean subarctic environment. A connection was revealed. Higher values of cloud droplet number concentrations were related to continental air masses, whereas the lowest values of number concentrations were related to marine air masses. These were characterized by larger cloud droplets. Clouds in all regions were sensitive to increases in cloud number concentration.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Shan Sun and Amy Solomon
EGUsphere, https://doi.org/10.5194/egusphere-2022-1368, https://doi.org/10.5194/egusphere-2022-1368, 2022
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We evaluate sea ice prediction skill at seasonal time scales using the CICE sea ice model. It confirms the importance of the accuracy in ice thickness initialization for seasonal sea ice prediction. It suggests that there exists a potentially important source of additional skill in seasonal forecasting, namely, a more reliable sea ice thickness initialization. Hence, assimilation of sea ice thickness appears to be highly relevant for advancing seasonal prediction skill.
Zen Mariani, Laura Huang, Robert Crawford, Jean-Pierre Blanchet, Shannon Hicks-Jalali, Eva Mekis, Ludovick Pelletier, Peter Rodriguez, and Kevin Strawbridge
Earth Syst. Sci. Data, 14, 4995–5017, https://doi.org/10.5194/essd-14-4995-2022, https://doi.org/10.5194/essd-14-4995-2022, 2022
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Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
Jenna Ritvanen, Ewan O'Connor, Dmitri Moisseev, Raisa Lehtinen, Jani Tyynelä, and Ludovic Thobois
Atmos. Meas. Tech., 15, 6507–6519, https://doi.org/10.5194/amt-15-6507-2022, https://doi.org/10.5194/amt-15-6507-2022, 2022
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Doppler lidars and weather radars provide accurate wind measurements, with Doppler lidar usually performing better in dry weather conditions and weather radar performing better when there is precipitation. Operating both instruments together should therefore improve the overall performance. We investigate how well a co-located Doppler lidar and X-band radar perform with respect to various weather conditions, including changes in horizontal visibility, cloud altitude, and precipitation.
Andrew Clifton, Sarah Barber, Alexander Stökl, Helmut Frank, and Timo Karlsson
Wind Energ. Sci., 7, 2231–2254, https://doi.org/10.5194/wes-7-2231-2022, https://doi.org/10.5194/wes-7-2231-2022, 2022
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The transition to low-carbon sources of energy means that wind turbines will need to be built in hilly or mountainous regions or in places affected by icing. These locations are called
complexand are hard to develop. This paper sets out the research and development (R&D) needed to make it easier and cheaper to harness wind energy there. This includes collaborative R&D facilities, improved wind and weather models, frameworks for sharing data, and a clear definition of site complexity.
Xin Yang, Kimberly Strong, Alison S. Criscitiello, Marta Santos-Garcia, Kristof Bognar, Xiaoyi Zhao, Pierre Fogal, Kaley A. Walker, Sara M. Morris, and Peter Effertz
EGUsphere, https://doi.org/10.5194/egusphere-2022-696, https://doi.org/10.5194/egusphere-2022-696, 2022
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Snow pack in high Arctic plays a key role in polar atmospheric chemistry, especially in spring when photochemistry becomes active. By sampling surface snow from a Canadian high Arctic location at Eureka, Nunavut (80° N, 86° W), we demonstrate that surface snow is a net sink rather than a source of atmospheric reactive bromine and nitrate. This finding is new and opposite to previous conclusions that snowpack is a large and direct source of reactive bromine in polar spring.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, https://doi.org/10.5194/tc-16-4223-2022, 2022
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Impacts of rain on snow (ROS) on satellite-retrieved sea ice variables remain to be fully understood. This study evaluates the impacts of ROS over sea ice on active and passive microwave data collected during the 2019–20 MOSAiC expedition. Rainfall and subsequent refreezing of the snowpack significantly altered emitted and backscattered radar energy, laying important groundwork for understanding their impacts on operational satellite retrievals of various sea ice geophysical variables.
Alexander F. Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Weather Clim. Dynam., 3, 1097–1112, https://doi.org/10.5194/wcd-3-1097-2022, https://doi.org/10.5194/wcd-3-1097-2022, 2022
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Understanding the location and intensity of hazardous weather across the Arctic is important for assessing risks to infrastructure, shipping, and coastal communities. This study describes the typical lifetime and structure of intense winter and summer Arctic cyclones. Results show the composite development and structure of intense summer Arctic cyclones are different from intense winter Arctic and North Atlantic Ocean extra-tropical cyclones and from conceptual models.
Chih-Chun Chou, Paul J. Kushner, Stéphane Laroche, Zen Mariani, Peter Rodriguez, Stella Melo, and Christopher G. Fletcher
Atmos. Meas. Tech., 15, 4443–4461, https://doi.org/10.5194/amt-15-4443-2022, https://doi.org/10.5194/amt-15-4443-2022, 2022
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Aeolus is the first satellite that provides global wind profile measurements. The mission aims to improve the weather forecasts in the tropics, but also, potentially, in the polar regions. We evaluate the performance of the instrument over the Canadian North and the Arctic by comparing its measured winds in both cloudy and non-cloudy layers to wind data from forecasts, reanalysis, and ground-based instruments. Overall, good agreement was seen, but Aeolus winds have greater dispersion.
Jonathan J. Day, Sarah Keeley, Gabriele Arduini, Linus Magnusson, Kristian Mogensen, Mark Rodwell, Irina Sandu, and Steffen Tietsche
Weather Clim. Dynam., 3, 713–731, https://doi.org/10.5194/wcd-3-713-2022, https://doi.org/10.5194/wcd-3-713-2022, 2022
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A recent drive to develop seamless forecasting systems has culminated in the development of weather forecasting systems that include a coupled representation of the atmosphere, ocean and sea ice. Before this, sea ice and sea surface temperature anomalies were typically fixed throughout a given forecast. We show that the dynamic coupling is most beneficial during periods of rapid ice advance, where persistence is a poor forecast of the sea ice and leads to large errors in the uncoupled system.
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.
Patrick Le Moigne, Eric Bazile, Anning Cheng, Emanuel Dutra, John M. Edwards, William Maurel, Irina Sandu, Olivier Traullé, Etienne Vignon, Ayrton Zadra, and Weizhong Zheng
The Cryosphere, 16, 2183–2202, https://doi.org/10.5194/tc-16-2183-2022, https://doi.org/10.5194/tc-16-2183-2022, 2022
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This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results show that the simplest models are, under certain conditions, able to reproduce the surface temperature just as well as the most complex models. Moreover, the diversity of surface parameters of the models has a strong impact on the temporal variability of the components of the simulated surface energy balance.
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432, https://doi.org/10.5194/amt-15-2417-2022, https://doi.org/10.5194/amt-15-2417-2022, 2022
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To study the complex structure of the lowest tens of metres of atmosphere in urban areas, measurement methods with great spatial and temporal coverage are needed. In our study, we analyse measurements with a promising and relatively new method, distributed temperature sensing, capable of providing detailed information on the near-surface atmosphere. We present multiple ways to utilise these kinds of measurements, as well as important considerations for planning new studies using the method.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
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.
Jutta Kesti, John Backman, Ewan J. O'Connor, Anne Hirsikko, Eija Asmi, Minna Aurela, Ulla Makkonen, Maria Filioglou, Mika Komppula, Hannele Korhonen, and Heikki Lihavainen
Atmos. Chem. Phys., 22, 481–503, https://doi.org/10.5194/acp-22-481-2022, https://doi.org/10.5194/acp-22-481-2022, 2022
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In this study we combined aerosol particle measurements at the surface with a scanning Doppler lidar providing vertical profiles of the atmosphere to study the effect of different boundary layer conditions on aerosol particle properties in the understudied Arabian Peninsula region. The instrumentation used in this study enabled us to identify periods when pollution from remote sources was mixed down to the surface and initiated new particle formation in the growing boundary layer.
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.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
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We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Shan Sun and Amy Solomon
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-353, https://doi.org/10.5194/tc-2021-353, 2021
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We validate the standalone CICE sea ice model for application in the seasonal forecast, before it is used in the coupled atmosphere-ocean-ice model. We found the model did a better job in forecasting Arctic sea ice extent in the warm season than in the cold season at the seasonal time scale. A higher forecast skill is achieved when the model is initialized with ice thickness from satellite observations, indicating the importance of the ice thickness initialization.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
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The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Amy Solomon, Céline Heuzé, Benjamin Rabe, Sheldon Bacon, Laurent Bertino, Patrick Heimbach, Jun Inoue, Doroteaciro Iovino, Ruth Mottram, Xiangdong Zhang, Yevgeny Aksenov, Ronan McAdam, An Nguyen, Roshin P. Raj, and Han Tang
Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, https://doi.org/10.5194/os-17-1081-2021, 2021
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Freshwater in the Arctic Ocean plays a critical role in the global climate system by impacting ocean circulations, stratification, mixing, and emergent regimes. In this review paper we assess how Arctic Ocean freshwater changed in the 2010s relative to the 2000s. Estimates from observations and reanalyses show a qualitative stabilization in the 2010s due to a compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the Amerasian and Eurasian basins.
Chiara Marsigli, Elizabeth Ebert, Raghavendra Ashrit, Barbara Casati, Jing Chen, Caio A. S. Coelho, Manfred Dorninger, Eric Gilleland, Thomas Haiden, Stephanie Landman, and Marion Mittermaier
Nat. Hazards Earth Syst. Sci., 21, 1297–1312, https://doi.org/10.5194/nhess-21-1297-2021, https://doi.org/10.5194/nhess-21-1297-2021, 2021
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This paper reviews new observations for the verification of high-impact weather and provides advice for their usage in objective verification. New observations include remote sensing datasets, products developed for nowcasting, datasets derived from telecommunication systems, data collected from citizens, reports of impacts and reports from insurance companies. This work has been performed in the framework of the Joint Working Group on Forecast Verification Research (JWGFVR) of the WMO.
Ville Vakkari, Holger Baars, Stephanie Bohlmann, Johannes Bühl, Mika Komppula, Rodanthi-Elisavet Mamouri, and Ewan James O'Connor
Atmos. Chem. Phys., 21, 5807–5820, https://doi.org/10.5194/acp-21-5807-2021, https://doi.org/10.5194/acp-21-5807-2021, 2021
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The depolarization ratio is a valuable parameter for aerosol categorization from remote sensing measurements. Here, we introduce particle depolarization ratio measurements at the 1565 nm wavelength, which is substantially longer than previously utilized wavelengths and enhances our capabilities to study the wavelength dependency of the particle depolarization ratio.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
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We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
Julie M. Thériault, Stephen J. Déry, John W. Pomeroy, Hilary M. Smith, Juris Almonte, André Bertoncini, Robert W. Crawford, Aurélie Desroches-Lapointe, Mathieu Lachapelle, Zen Mariani, Selina Mitchell, Jeremy E. Morris, Charlie Hébert-Pinard, Peter Rodriguez, and Hadleigh D. Thompson
Earth Syst. Sci. Data, 13, 1233–1249, https://doi.org/10.5194/essd-13-1233-2021, https://doi.org/10.5194/essd-13-1233-2021, 2021
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This article discusses the data that were collected during the Storms and Precipitation Across the continental Divide (SPADE) field campaign in spring 2019 in the Canadian Rockies, along the Alberta and British Columbia border. Various instruments were installed at five field sites to gather information about atmospheric conditions focussing on precipitation. Details about the field sites, the instrumentation used, the variables collected, and the collection methods and intervals are presented.
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
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The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
Christopher J. Cox, Sara M. Morris, Taneil Uttal, Ross Burgener, Emiel Hall, Mark Kutchenreiter, Allison McComiskey, Charles N. Long, Bryan D. Thomas, and James Wendell
Atmos. Meas. Tech., 14, 1205–1224, https://doi.org/10.5194/amt-14-1205-2021, https://doi.org/10.5194/amt-14-1205-2021, 2021
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Solar and infrared radiation are measured regularly for research, industry, and climate monitoring. In cold climates, icing of sensors is a poorly constrained source of uncertainty. D-ICE was carried out in Alaska to document the effectiveness of ice-mitigation technology and quantify errors associated with ice. Technology was more effective than anticipated, and while instantaneous errors were large, mean biases were small. Attributes of effective ice mitigation design were identified.
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.
Xin Yang, Anne-M. Blechschmidt, Kristof Bognar, Audra McClure-Begley, Sara Morris, Irina Petropavlovskikh, Andreas Richter, Henrik Skov, Kimberly Strong, David W. Tarasick, Taneil Uttal, Mika Vestenius, and Xiaoyi Zhao
Atmos. Chem. Phys., 20, 15937–15967, https://doi.org/10.5194/acp-20-15937-2020, https://doi.org/10.5194/acp-20-15937-2020, 2020
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This is a modelling-based study on Arctic surface ozone, with a particular focus on spring ozone depletion events (i.e. with concentrations < 10 ppbv). Model experiments show that model runs with blowing-snow-sourced sea salt aerosols implemented as a source of reactive bromine can reproduce well large-scale ozone depletion events observed in the Arctic. This study supplies modelling evidence of the proposed mechanism of reactive-bromine release from blowing snow on sea ice (Yang et al., 2008).
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
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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.
Maria Filioglou, Elina Giannakaki, John Backman, Jutta Kesti, Anne Hirsikko, Ronny Engelmann, Ewan O'Connor, Jari T. T. Leskinen, Xiaoxia Shang, Hannele Korhonen, Heikki Lihavainen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 20, 8909–8922, https://doi.org/10.5194/acp-20-8909-2020, https://doi.org/10.5194/acp-20-8909-2020, 2020
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Dust optical properties are region-dependent. Saharan, Asian, and Arabian dusts do not pose similar optical properties in terms of lidar ratios; thus, a universal lidar ratio for dust particles will lead to biases. The present study analyses observations over the United Arab Emirates, quantifying the optical and geometrical extents of the aerosol layers in the area, providing at the same time the Arabian dust properties along with chemical analysis of dust samples collected in the region.
Pyry Pentikäinen, Ewan James O'Connor, Antti Juhani Manninen, and Pablo Ortiz-Amezcua
Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, https://doi.org/10.5194/amt-13-2849-2020, 2020
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We provide a methodology for obtaining a function describing how the Doppler lidar telescope configuration
impacts the measurements. Together with the function itself, we also provide the uncertainties in the function, which propagate through to provide uncertainties in the geophysical quantities obtained from the measurements. The method can be used to determine how stable the instrument is over time and also identify if changes have been made in the instrument setup.
Ghislain Picard, Marie Dumont, Maxim Lamare, François Tuzet, Fanny Larue, Roberta Pirazzini, and Laurent Arnaud
The Cryosphere, 14, 1497–1517, https://doi.org/10.5194/tc-14-1497-2020, https://doi.org/10.5194/tc-14-1497-2020, 2020
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Surface albedo is an essential variable of snow-covered areas. The measurement of this variable over a tilted terrain with levelled sensors is affected by artefacts that need to be corrected. Here we develop a theory of spectral albedo measurement over slopes from which we derive four correction algorithms. The comparison to in situ measurements taken in the Alps shows the adequacy of the theory, and the application of the algorithms shows systematic improvements.
Angela Cheng, Barbara Casati, Adrienne Tivy, Tom Zagon, Jean-François Lemieux, and L. Bruno Tremblay
The Cryosphere, 14, 1289–1310, https://doi.org/10.5194/tc-14-1289-2020, https://doi.org/10.5194/tc-14-1289-2020, 2020
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Sea ice charts by the Canadian Ice Service (CIS) contain visually estimated ice concentration produced by analysts. The accuracy of manually derived ice concentrations is not well understood. The subsequent uncertainty of ice charts results in downstream uncertainties for ice charts users, such as models and climatology studies, and when used as a verification source for automated sea ice classifiers. This study quantifies the level of accuracy and inter-analyst agreement for ice charts by CIS.
Philippe Ricaud, Massimo Del Guasta, Eric Bazile, Niramson Azouz, Angelo Lupi, Pierre Durand, Jean-Luc Attié, Dana Veron, Vincent Guidard, and Paolo Grigioni
Atmos. Chem. Phys., 20, 4167–4191, https://doi.org/10.5194/acp-20-4167-2020, https://doi.org/10.5194/acp-20-4167-2020, 2020
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Thin (~ 100 m) supercooled liquid water (SLW, water staying in liquid phase below 0 °C) clouds have been detected, analysed, and modelled over the Dome C (Concordia, Antarctica) station during the austral summer 2018–2019 using observations and meteorological analyses. The SLW clouds were observed at the top of the planetary boundary layer and the SLW content was always strongly underestimated by the model indicating an incorrect simulation of the surface energy budget of the Antarctic Plateau.
Gijs de Boer, Darielle Dexheimer, Fan Mei, John Hubbe, Casey Longbottom, Peter J. Carroll, Monty Apple, Lexie Goldberger, David Oaks, Justin Lapierre, Michael Crume, Nathan Bernard, Matthew D. Shupe, Amy Solomon, Janet Intrieri, Dale Lawrence, Abhiram Doddi, Donna J. Holdridge, Michael Hubbell, Mark D. Ivey, and Beat Schmid
Earth Syst. Sci. Data, 11, 1349–1362, https://doi.org/10.5194/essd-11-1349-2019, https://doi.org/10.5194/essd-11-1349-2019, 2019
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This paper provides a summary of observations collected at Oliktok Point, Alaska, as part of the Profiling at Oliktok Point to Enhance YOPP Experiments (POPEYE) campaign. The Year of Polar Prediction (YOPP) is a multi-year concentrated effort to improve forecasting capabilities at high latitudes across a variety of timescales. POPEYE observations include atmospheric data collected using unmanned aircraft, tethered balloons, and radiosondes, made in parallel with routine measurements at the site.
Tatiana Nomokonova, Kerstin Ebell, Ulrich Löhnert, Marion Maturilli, Christoph Ritter, and Ewan O'Connor
Atmos. Chem. Phys., 19, 4105–4126, https://doi.org/10.5194/acp-19-4105-2019, https://doi.org/10.5194/acp-19-4105-2019, 2019
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In this study, properties of clouds at the French–German Arctic research station in Ny-Ålesund are related to in-cloud thermodynamic conditions. The dataset used was collected within the Arctic Amplification project with a set of active and passive remote instruments. The results are compared with a model output. Significant divergence in observations and modelling of single-layer ice and mixed-phase clouds was found.
Minttu Tuononen, Ewan J. O'Connor, and Victoria A. Sinclair
Atmos. Chem. Phys., 19, 1985–2000, https://doi.org/10.5194/acp-19-1985-2019, https://doi.org/10.5194/acp-19-1985-2019, 2019
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Many applications require accurate forecasts of the amount of solar radiation reaching the surface, such as solar energy and UV radiation forecasts. This also means that cloud must be correctly forecast. We investigated the skill of these forecasts over Helsinki, Finland, using cloud and solar radiation observations. We found that there were errors in the model radiation forecast even when the clouds were correctly forecast, which we attribute to incorrect representation of the cloud properties.
Timo Vihma, Petteri Uotila, Stein Sandven, Dmitry Pozdnyakov, Alexander Makshtas, Alexander Pelyasov, Roberta Pirazzini, Finn Danielsen, Sergey Chalov, Hanna K. Lappalainen, Vladimir Ivanov, Ivan Frolov, Anna Albin, Bin Cheng, Sergey Dobrolyubov, Viktor Arkhipkin, Stanislav Myslenkov, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 19, 1941–1970, https://doi.org/10.5194/acp-19-1941-2019, https://doi.org/10.5194/acp-19-1941-2019, 2019
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The Arctic marine climate system, ecosystems, and socio-economic systems are changing rapidly. This calls for the establishment of a marine Arctic component of the Pan-Eurasian Experiment (MA-PEEX), for which we present a plan. The program will promote international collaboration; sustainable marine meteorological, sea ice, and oceanographic observations; advanced data management; and multidisciplinary research on the marine Arctic and its interaction with the Eurasian continent.
Ville Vakkari, Antti J. Manninen, Ewan J. O'Connor, Jan H. Schween, Pieter G. van Zyl, and Eleni Marinou
Atmos. Meas. Tech., 12, 839–852, https://doi.org/10.5194/amt-12-839-2019, https://doi.org/10.5194/amt-12-839-2019, 2019
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Commercially available Doppler lidars have been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more.
Xiang-Yu Li, Gunilla Svensson, Axel Brandenburg, and Nils E. L. Haugen
Atmos. Chem. Phys., 19, 639–648, https://doi.org/10.5194/acp-19-639-2019, https://doi.org/10.5194/acp-19-639-2019, 2019
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The broadening of droplet size distributions in stratiform clouds, where the updraft velocity is almost zero, is puzzling. Without turbulence, the classical treatment of condensational growth of cloud droplets fails to explain this
broadening. We investigated the time evolution of droplet size distributions using direct numerical simulations, where turbulence is resolved into the smallest scales. We found that the broadening is due to the turbulence-facilitated supersaturation fluctuations.
Amy Solomon, Gijs de Boer, Jessie M. Creamean, Allison McComiskey, Matthew D. Shupe, Maximilian Maahn, and Christopher Cox
Atmos. Chem. Phys., 18, 17047–17059, https://doi.org/10.5194/acp-18-17047-2018, https://doi.org/10.5194/acp-18-17047-2018, 2018
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The results of this study indicate that perturbations in ice nucleating particles (INPs) dominate over cloud condensation nuclei (CCN) perturbations in Arctic mixed-phase stratocumulus; i.e., an equivalent fractional decrease in CCN and INPs results in an increase in the cloud-top longwave cooling rate, even though the droplet effective radius increases and the cloud emissivity decreases. In addition, cloud-processing causes layering of aerosols with increased concentrations of CCN at cloud top.
Kerstin Hartung, Gunilla Svensson, Hamish Struthers, Anna-Lena Deppenmeier, and Wilco Hazeleger
Geosci. Model Dev., 11, 4117–4137, https://doi.org/10.5194/gmd-11-4117-2018, https://doi.org/10.5194/gmd-11-4117-2018, 2018
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Single-column models have been used to develop weather and climate models for several decades. They decouple small-scale processes from large-scale forcing and allow us to test models in a controlled environment with reduced computational cost. Here, we present a fully coupled atmosphere–ocean single-column model, including sea ice. We demonstrate that it is a valuable tool to advance our understanding in marine and polar boundary layer processes and interactions of their coupled components.
Lauren Schmeisser, John Backman, John A. Ogren, Elisabeth Andrews, Eija Asmi, Sandra Starkweather, Taneil Uttal, Markus Fiebig, Sangeeta Sharma, Kostas Eleftheriadis, Stergios Vratolis, Michael Bergin, Peter Tunved, and Anne Jefferson
Atmos. Chem. Phys., 18, 11599–11622, https://doi.org/10.5194/acp-18-11599-2018, https://doi.org/10.5194/acp-18-11599-2018, 2018
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This paper presents pan-Arctic seasonality of in-situ-measured aerosol optical properties from six surface monitoring sites. The analysis provides insight into aerosol annual variability throughout the region – something that is not possible using only measurements from satellite or temporary aircraft campaigns. This paper shows that the large spatiotemporal variability in aerosol optical properties needs to be taken into account in order to properly represent Arctic climate.
Anna Nikandrova, Ksenia Tabakova, Antti Manninen, Riikka Väänänen, Tuukka Petäjä, Markku Kulmala, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Chem. Phys., 18, 10575–10591, https://doi.org/10.5194/acp-18-10575-2018, https://doi.org/10.5194/acp-18-10575-2018, 2018
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We investigated temporal and vertical aerosol properties in a rural environment during BAECC (Biogenic Aerosols – Effects on Cloud and Climate) campaign. Differences were observed in aerosol number size distribution, variability and mixing in the layers between two case studies: clear-sky and partly cloudy case. We also conclude that care should be taken in selecting appropriate arrival heights of backward trajectories, since the modelled and observed layer heights did not always coincide.
Emma L. Mungall, Jonathan P. D. Abbatt, Jeremy J. B. Wentzell, Gregory R. Wentworth, Jennifer G. Murphy, Daniel Kunkel, Ellen Gute, David W. Tarasick, Sangeeta Sharma, Christopher J. Cox, Taneil Uttal, and John Liggio
Atmos. Chem. Phys., 18, 10237–10254, https://doi.org/10.5194/acp-18-10237-2018, https://doi.org/10.5194/acp-18-10237-2018, 2018
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We measured gas-phase formic and acetic acid at Alert, Nunavut. These acids play an important role in cloud water acidity in remote environments, yet they are not well represented in chemical transport models, particularly in the Arctic. We observed high levels of formic and acetic acid under both cold, wet, and cloudy and warm, sunny, and dry conditions, suggesting that multiple sources significantly contribute to gas-phase concentrations of these species in the summer Arctic.
Leslie M. Hartten, Christopher J. Cox, Paul E. Johnston, Daniel E. Wolfe, Scott Abbott, and H. Alex McColl
Earth Syst. Sci. Data, 10, 1139–1164, https://doi.org/10.5194/essd-10-1139-2018, https://doi.org/10.5194/essd-10-1139-2018, 2018
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In early 2016 the NOAA's El Niño Rapid Response Field Campaign documented the ongoing strong event and its impacts. Observations from the warmed Pacific included 10 weeks of surface meteorology from Kiritimati Island and 4 weeks of surface meteorology and air–sea fluxes from NOAA Ship Ronald H. Brown. We have vetted the data, identifying issues and minimizing their impacts when possible. Measurements include a meter of rain at Kiritimati, and continuous ocean and air conditions from the ship.
Leslie M. Hartten, Christopher J. Cox, Paul E. Johnston, Daniel E. Wolfe, Scott Abbott, H. Alex McColl, Xiao-Wei Quan, and Matthew G. Winterkorn
Earth Syst. Sci. Data, 10, 1165–1183, https://doi.org/10.5194/essd-10-1165-2018, https://doi.org/10.5194/essd-10-1165-2018, 2018
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Radiosonde data collected during NOAA's El Niño Rapid Response Field Campaign in early 2016 have been reprocessed and lightly quality controlled. Temperature, humidity, and wind soundings from Kiritimati and NOAA Ship Ronald H. Brown capture the repeated advance and retreat of the ITCZ at Kiritimati, a variety of marine tropospheric environments encountered by the ship, and lower-stratospheric features of the 2015 2016 QBO (quasi-biennial oscillation).
Piet Termonia, Claude Fischer, Eric Bazile, François Bouyssel, Radmila Brožková, Pierre Bénard, Bogdan Bochenek, Daan Degrauwe, Mariá Derková, Ryad El Khatib, Rafiq Hamdi, Ján Mašek, Patricia Pottier, Neva Pristov, Yann Seity, Petra Smolíková, Oldřich Španiel, Martina Tudor, Yong Wang, Christoph Wittmann, and Alain Joly
Geosci. Model Dev., 11, 257–281, https://doi.org/10.5194/gmd-11-257-2018, https://doi.org/10.5194/gmd-11-257-2018, 2018
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This paper describes the ALADIN System that has been developed by the international ALADIN consortium of 16 European and northern African partners since its creation in 1990. The paper also describes how its model configurations are used by the consortium partners for their operational weather forecasting applications and for weather and climate research.
John Backman, Lauren Schmeisser, Aki Virkkula, John A. Ogren, Eija Asmi, Sandra Starkweather, Sangeeta Sharma, Konstantinos Eleftheriadis, Taneil Uttal, Anne Jefferson, Michael Bergin, Alexander Makshtas, Peter Tunved, and Markus Fiebig
Atmos. Meas. Tech., 10, 5039–5062, https://doi.org/10.5194/amt-10-5039-2017, https://doi.org/10.5194/amt-10-5039-2017, 2017
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Light absorption by aerosol particles is of climatic importance. A widely used means to measure aerosol light absorption is a filter-based measurement technique. In remote areas, such as the Arctic, filter-based instruments operate close to their detection limit. The study presents how a lower detection limit can be achieved for one such instrument, the Aethalometer. Additionally, the Aethalometer is compared to similar instruments, thus improving measurement inter-comparability in the Arctic.
Paul J. Valdes, Edward Armstrong, Marcus P. S. Badger, Catherine D. Bradshaw, Fran Bragg, Michel Crucifix, Taraka Davies-Barnard, Jonathan J. Day, Alex Farnsworth, Chris Gordon, Peter O. Hopcroft, Alan T. Kennedy, Natalie S. Lord, Dan J. Lunt, Alice Marzocchi, Louise M. Parry, Vicky Pope, William H. G. Roberts, Emma J. Stone, Gregory J. L. Tourte, and Jonny H. T. Williams
Geosci. Model Dev., 10, 3715–3743, https://doi.org/10.5194/gmd-10-3715-2017, https://doi.org/10.5194/gmd-10-3715-2017, 2017
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In this paper we describe the family of climate models used by the BRIDGE research group at the University of Bristol as well as by various other institutions. These models are based on the UK Met Office HadCM3 models and here we describe the various modifications which have been made as well as the key features of a number of configurations in use.
Dan Weaver, Kimberly Strong, Matthias Schneider, Penny M. Rowe, Chris Sioris, Kaley A. Walker, Zen Mariani, Taneil Uttal, C. Thomas McElroy, Holger Vömel, Alessio Spassiani, and James R. Drummond
Atmos. Meas. Tech., 10, 2851–2880, https://doi.org/10.5194/amt-10-2851-2017, https://doi.org/10.5194/amt-10-2851-2017, 2017
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We have compared techniques used by several PEARL instruments to measure atmospheric water vapour. No single instrument can comprehensively map the atmosphere. We documented how well these techniques perform and quantified the agreement and biases between them. This work showed that new FTIR datasets at PEARL capture accurate measurements of High Arctic water vapour.
Lena Frey, Frida A.-M. Bender, and Gunilla Svensson
Atmos. Chem. Phys., 17, 9145–9162, https://doi.org/10.5194/acp-17-9145-2017, https://doi.org/10.5194/acp-17-9145-2017, 2017
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In this study, the cloud albedo effect in climate models is investigated, separating the influence of anthropogenic sulfate and non-sulfate aerosols. Cloud albedo changes induced by added anthropogenic aerosols are found to be determined by changes in the cloud water content rather than model sensitivity to monthly aerosol variations. The results also indicate that the background aerosol is the main driver for a cloud brightening effect on the month-to-month scale.
Philippe Ricaud, Eric Bazile, Massimo del Guasta, Christian Lanconelli, Paolo Grigioni, and Achraf Mahjoub
Atmos. Chem. Phys., 17, 5221–5237, https://doi.org/10.5194/acp-17-5221-2017, https://doi.org/10.5194/acp-17-5221-2017, 2017
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The novelty of the paper is to combine a large set of measurements and meteorological models to study the genesis of thick cloud and diamond dust/ice fog (ice crystals) episodes above Dome C, Antarctica. The originality of the work is to attribute the presence of thick cloud and diamond dust/ice fog to advection and microphysical processes with oceanic and continental origin of air masses, respectively. Thick cloud episodes are reproduced by the models but not diamond dust/ice fog episode.
Tom Edinburgh and Jonathan J. Day
The Cryosphere, 10, 2721–2730, https://doi.org/10.5194/tc-10-2721-2016, https://doi.org/10.5194/tc-10-2721-2016, 2016
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Contrary to expectations, Antarctic sea ice cover has been increasing in area during the last three decades. In order to put these trends into a wider context this paper analyses direct observations of sea ice, recorded in ships' logbooks during the Heroic Age of Antarctic Exploration (1887–1917) for the first time. It shows that the sea ice was significantly further north in the Weddell Sea during the period but comparable to the present day in other sectors.
Simone Kotthaus, Ewan O'Connor, Christoph Münkel, Cristina Charlton-Perez, Martial Haeffelin, Andrew M. Gabey, and C. Sue B. Grimmond
Atmos. Meas. Tech., 9, 3769–3791, https://doi.org/10.5194/amt-9-3769-2016, https://doi.org/10.5194/amt-9-3769-2016, 2016
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Ceilometers lidars are useful to study clouds, aerosol layers and atmospheric boundary layer structures. As sensor optics and acquisition algorithms can strongly influence the observations, sensor specifics need to be incorporated into the physical interpretation. Here, recommendations are made for the operation and processing of profile observations from the widely deployed Vaisala CL31 ceilometer. Proposed corrections are shown to increase data quality and even data availability at times.
Fleur Couvreux, Eric Bazile, Guylaine Canut, Yann Seity, Marie Lothon, Fabienne Lohou, Françoise Guichard, and Erik Nilsson
Atmos. Chem. Phys., 16, 8983–9002, https://doi.org/10.5194/acp-16-8983-2016, https://doi.org/10.5194/acp-16-8983-2016, 2016
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This study evaluates the ability of operational models to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence field campaign. The models succeed in reproducing the variability from one day to another in terms of cloud cover, temperature and boundary-layer depth. However, they exhibit some systematic biases. The high-resolution model reproduces the vertical structures better.
Moa K. Sporre, Ewan J. O'Connor, Nina Håkansson, Anke Thoss, Erik Swietlicki, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 3193–3203, https://doi.org/10.5194/amt-9-3193-2016, https://doi.org/10.5194/amt-9-3193-2016, 2016
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Satellite measurements of cloud top height and liquid water path are compared to ground-based remote sensing to evaluate the satellite retrievals. The overall performance of the satellite retrievals of cloud top height are good, but they become more problematic when several layers of clouds are present. The liquid water path retrievals also agree well, and the average differences are within the estimated measurement uncertainties.
Riikka Väänänen, Radovan Krejci, Hanna E. Manninen, Antti Manninen, Janne Lampilahti, Stephany Buenrostro Mazon, Tuomo Nieminen, Taina Yli-Juuti, Jenni Kontkanen, Ari Asmi, Pasi P. Aalto, Petri Keronen, Toivo Pohja, Ewan O'Connor, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-556, https://doi.org/10.5194/acp-2016-556, 2016
Revised manuscript has not been submitted
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A light aircraft was used as a platform to explore the horizontal and vertical variability of the aerosol particles over a boreal forest in Central Finland. This information is needed when data measured at ground level station is extrapolated and parameterized to represent the
conditions of the larger scale. The measurements showed that despite local fluctuations there was a good agreement between the on-ground and airborne measurements inside the planetary boundary layer.
Jonathan J. Day, Steffen Tietsche, Mat Collins, Helge F. Goessling, Virginie Guemas, Anabelle Guillory, William J. Hurlin, Masayoshi Ishii, Sarah P. E. Keeley, Daniela Matei, Rym Msadek, Michael Sigmond, Hiroaki Tatebe, and Ed Hawkins
Geosci. Model Dev., 9, 2255–2270, https://doi.org/10.5194/gmd-9-2255-2016, https://doi.org/10.5194/gmd-9-2255-2016, 2016
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Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable.
N. Evangeliou, Y. Balkanski, W. M. Hao, A. Petkov, R. P. Silverstein, R. Corley, B. L. Nordgren, S. P. Urbanski, S. Eckhardt, A. Stohl, P. Tunved, S. Crepinsek, A. Jefferson, S. Sharma, J. K. Nøjgaard, and H. Skov
Atmos. Chem. Phys., 16, 7587–7604, https://doi.org/10.5194/acp-16-7587-2016, https://doi.org/10.5194/acp-16-7587-2016, 2016
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In this study, we focused on how vegetation fires that occurred in northern Eurasia during the period 2002–2013 influenced the budget of BC in the Arctic. An average area of 250 000 km2 yr−1 was burned in northern Eurasia and the global emissions of BC ranged between 8.0 and 9.5 Tg yr−1, while 102 ± 29 kt yr−1 BC from biomass burning was deposited on the Arctic. About 46 % of the Arctic BC from vegetation fires originated from Siberia, 6 % from Kazakhstan, 5 % from Europe, and about 1 % from Mon
Antti J. Manninen, Ewan J. O'Connor, Ville Vakkari, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 817–827, https://doi.org/10.5194/amt-9-817-2016, https://doi.org/10.5194/amt-9-817-2016, 2016
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Current commercially available Doppler lidars provide a cost-effective solution for measuring vertical and horizontal wind velocities, and the co- and cross-polarised backscatter profiles. However, the background noise behaviour becomes a limiting factor for the instrument sensitivity in low aerosol load regions. In this paper we present a correction method which can improve the data availability up to 50 % and greatly improves the calculation of turbulent properties in weak signal regimes.
E. Asmi, V. Kondratyev, D. Brus, T. Laurila, H. Lihavainen, J. Backman, V. Vakkari, M. Aurela, J. Hatakka, Y. Viisanen, T. Uttal, V. Ivakhov, and A. Makshtas
Atmos. Chem. Phys., 16, 1271–1287, https://doi.org/10.5194/acp-16-1271-2016, https://doi.org/10.5194/acp-16-1271-2016, 2016
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Aerosol number size distributions were measured in Arctic Russia continuously during 4 years. The particles' seasonal characteristics and sources were identified based on these data. In early spring, elevated concentrations were detected during episodes of Arctic haze and during days of secondary particle formation. In summer, Siberian forests biogenic emissions had a significant impact on particle number and mass. These are the first such results obtained from the region.
R. Pirazzini, P. Räisänen, T. Vihma, M. Johansson, and E.-M. Tastula
The Cryosphere, 9, 2357–2381, https://doi.org/10.5194/tc-9-2357-2015, https://doi.org/10.5194/tc-9-2357-2015, 2015
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We illustrate a method to measure the size distribution of a snow particle metric from macro photos of snow particles. This snow particle metric corresponds well to the optically equivalent effective radius. Our results evidence the impact of grain shape on albedo, indicate that more than just one particle metric distribution is needed to characterize the snow scattering properties at all optical wavelengths, and suggest an impact of surface roughness on the shortwave infrared albedo.
A. Solomon, G. Feingold, and M. D. Shupe
Atmos. Chem. Phys., 15, 10631–10643, https://doi.org/10.5194/acp-15-10631-2015, https://doi.org/10.5194/acp-15-10631-2015, 2015
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The maintenance of cloud ice production in Arctic mixed-phase stratocumulus is investigated in large eddy simulations that include a prognostic ice nuclei (IN) formulation and a diurnal cycle. It is demonstrated that IN recycling through subcloud sublimation prolongs ice production. Competing feedbacks between dynamical mixing and recycling are found to slow the rate of ice lost. The results of this study have important implications for the maintenance of phase partitioning in Arctic clouds.
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
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The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
M. D. Fielding, J. C. Chiu, R. J. Hogan, G. Feingold, E. Eloranta, E. J. O'Connor, and M. P. Cadeddu
Atmos. Meas. Tech., 8, 2663–2683, https://doi.org/10.5194/amt-8-2663-2015, https://doi.org/10.5194/amt-8-2663-2015, 2015
F. Besson, E. Bazile, C. Soci, J.-M. Soubeyroux, G. Ouzeau, and M. Perrin
Adv. Sci. Res., 12, 137–140, https://doi.org/10.5194/asr-12-137-2015, https://doi.org/10.5194/asr-12-137-2015, 2015
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Due to the evolution of the observation network, hourly 2m temperature analysis performed by reanalysis systems shows temporal inhomogeneities. In this study, the diurnal temperature cycle has been reconstructed for stations which only record extreme temperatures to produce new “pseudo” hourly temperature observations. Then they are provided to analysis systems; the results have shown that it enables reducing the bias in temperature analysis.
J. Tonttila, E. J. O'Connor, A. Hellsten, A. Hirsikko, C. O'Dowd, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 5873–5885, https://doi.org/10.5194/acp-15-5873-2015, https://doi.org/10.5194/acp-15-5873-2015, 2015
M. Lothon, F. Lohou, D. Pino, F. Couvreux, E. R. Pardyjak, J. Reuder, J. Vilà-Guerau de Arellano, P Durand, O. Hartogensis, D. Legain, P. Augustin, B. Gioli, D. H. Lenschow, I. Faloona, C. Yagüe, D. C. Alexander, W. M. Angevine, E Bargain, J. Barrié, E. Bazile, Y. Bezombes, E. Blay-Carreras, A. van de Boer, J. L. Boichard, A. Bourdon, A. Butet, B. Campistron, O. de Coster, J. Cuxart, A. Dabas, C. Darbieu, K. Deboudt, H. Delbarre, S. Derrien, P. Flament, M. Fourmentin, A. Garai, F. Gibert, A. Graf, J. Groebner, F. Guichard, M. A. Jiménez, M. Jonassen, A. van den Kroonenberg, V. Magliulo, S. Martin, D. Martinez, L. Mastrorillo, A. F. Moene, F. Molinos, E. Moulin, H. P. Pietersen, B. Piguet, E. Pique, C. Román-Cascón, C. Rufin-Soler, F. Saïd, M. Sastre-Marugán, Y. Seity, G. J. Steeneveld, P. Toscano, O. Traullé, D. Tzanos, S. Wacker, N. Wildmann, and A. Zaldei
Atmos. Chem. Phys., 14, 10931–10960, https://doi.org/10.5194/acp-14-10931-2014, https://doi.org/10.5194/acp-14-10931-2014, 2014
T. Vihma, R. Pirazzini, I. Fer, I. A. Renfrew, J. Sedlar, M. Tjernström, C. Lüpkes, T. Nygård, D. Notz, J. Weiss, D. Marsan, B. Cheng, G. Birnbaum, S. Gerland, D. Chechin, and J. C. Gascard
Atmos. Chem. Phys., 14, 9403–9450, https://doi.org/10.5194/acp-14-9403-2014, https://doi.org/10.5194/acp-14-9403-2014, 2014
W. M. Angevine, E. Bazile, D. Legain, and D. Pino
Atmos. Chem. Phys., 14, 8165–8172, https://doi.org/10.5194/acp-14-8165-2014, https://doi.org/10.5194/acp-14-8165-2014, 2014
A. Hirsikko, E. J. O'Connor, M. Komppula, K. Korhonen, A. Pfüller, E. Giannakaki, C. R. Wood, M. Bauer-Pfundstein, A. Poikonen, T. Karppinen, H. Lonka, M. Kurri, J. Heinonen, D. Moisseev, E. Asmi, V. Aaltonen, A. Nordbo, E. Rodriguez, H. Lihavainen, A. Laaksonen, K. E. J. Lehtinen, T. Laurila, T. Petäjä, M. Kulmala, and Y. Viisanen
Atmos. Meas. Tech., 7, 1351–1375, https://doi.org/10.5194/amt-7-1351-2014, https://doi.org/10.5194/amt-7-1351-2014, 2014
B. Brecht and H. Frank
Adv. Sci. Res., 11, 1–6, https://doi.org/10.5194/asr-11-1-2014, https://doi.org/10.5194/asr-11-1-2014, 2014
Related subject area
Atmospheric sciences
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
Atmospheric moisture tracking with WAM2layers v3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
EGUsphere, https://doi.org/10.5194/egusphere-2024-3401, https://doi.org/10.5194/egusphere-2024-3401, 2024
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We introduce a new version of WAM2layers, a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data became a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent and reliable, and easier to maintain.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Cited articles
Akish, E. and Morris, S.: MODF for Eureka, Canada, during YOPP SOP1 and SOP2, Norwegian Meteorological Institute, https://doi.org/10.21343/R85J-TC61, 2023a.
Akish, E. and Morris, S.: MODF for Tiksi, Russia, during YOPP SOP1 and SOP2, Norwegian Meteorological Institute, https://doi.org/10.21343/5BWN-W881, 2023b.
Akish, E. and Morris, S.: MODF for Utqiagvik, Alaska, during YOPP SOP1 and SOP2, Norwegian Meteorological Institute, https://doi.org/10.21343/A2DX-NQ55, 2023c.
Arduini, G., Balsamo, G., Dutra, E., Day, J. J., Sandu, I., Boussetta, S., and Haiden, T.: Impact of a multi-layer snow scheme on near-surface weather forecasts, J. Adv. Model. Earth Sy., 11, 4687–4710, https://doi.org/10.1029/2019MS001725, 2019.
Atlaskin, E. and Vihma, T.: Evaluation of NWP results for wintertime nocturnal boundary-layer temperatures over Europe and Finland, Q. J. Roy. Meteor. Soc., 138, 1440–1451, https://doi.org/10.1002/qj.1885, 2012.
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities, Mon. Weather Rev., 139, 3887–3905, 2011.
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A revised hydrology for the ECMWF model: verification from field site to terrestrial water storage and impact in the integrated forecast system, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009.
Batrak, Y. and Müller, M.: On the warm bias in atmospheric reanalyses induced by the missing snow over Arctic sea-ice, Nat. Commun., 10, 4170, https://doi.org/10.1038/s41467-019-11975-3, 2019.
Bauer, P., Magnusson, L., Thépaut, J.-N., and Hamill, T. M.: Aspects of ECMWF model performance in polar areas, Q. J. Roy. Meteor. Soc., 142, 583–596, https://doi.org/10.1002/qj.2449, 2016.
Bazile, E. and Azouz, N.: Merged model data files (MMDFs) for the Météo-France ARPEGE global forecast model for various polar sites, Norwegian Meteorological Institute [data set], https://doi.org/10.21343/T31Z-J391, 2023a.
Bazile, E. and Azouz, N.: MMDFs for the Météo-France AROME regional forecast model for various Arctic sites, Norwegian Meteorological Institute [data set], https://doi.org/10.21343/JZH3-2470, 2023b.
Bazile, E., Marquet, P., Bouteloup, Y., and Bouyssel, F.: The Turbulent Kinetic Energy (TKE) scheme in the NWP models at Météo-France, ECMWF GABLS Workshop on Diurnal Cycles and the Stable Boundary Layer, Reading, 7–10 November, 127–136, 2011.
Bazile, E., Azouz, N., Napoly, A., and Loo, C.: Impact of the 1D sea-ice model GELATO in the global model ARPEGE, France, 6–03, http://bluebook.meteoinfo.ru/index.php?year=2020&ch_=2 (last access: 11 July 2024), 2020.
Bechtold, P., Bazile, E., Guichard, F., Mascart, P., and Richard, E.: A mass flux convection scheme for regional and global models, Q. J. Roy. Meteor. Soc., 127, 869–886, 2001.
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell, M. J., Vitart, F., and Balsamo, G.: Advances in simulating atmospheric variability with the ECMWF model: from synoptic to decadal time-scales, Q. J. Roy. Meteor. Soc., 134, 1337–1351, https://doi.org/10.1002/qj.289, 2008.
Bélair, S., Brown, R., Mailhot, J., Bilodeau, B., and Crevier, L.: Operational implementation of the ISBA land surface scheme in the Canadian regional weather forecast model. Part II: Cold season results, J. Hydrometeorol., 4, 371–386, 2003.
Bélair, S., Mailhot, J., Girard, C., and Vaillancourt, P.: Boundary layer and shallow cumulus clouds in a medium-range forecast of a large-scale weather system, Mon. Weather Rev., 133, 1938–1960, https://doi.org/10.1175/MWR2958.1, 2005.
Beljaars, A. C. M. and Holtslag, A. A. M.: Flux parameterization over land surfaces for atmospheric models, J. Appl. Meteorol., 30, 327–341, https://doi.org/10.1175/1520-0450(1991)030<0327:FPOLSF>2.0.CO;2, 1991.
Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J., de Rooy, W., Gleeson, E., Hansen-Sass, B., Homleid, M., Hortal, M., Ivarsson, K.-I., Lenderink, G., Niemelä, S., Nielsen, K. P., Onvlee, J., Rontu, L., Samuelsson, P., Muñoz, D. S., Subias, A., Tijm, S., Toll, V., Yang, X., and Køltzow, M. Ø.: The HARMONIE–AROME model configuration in the ALADIN–HIRLAM NWP system, Mon. Weather Rev., 145, 1919–1935, https://doi.org/10.1175/MWR-D-16-0417.1, 2017.
Bougeault, P.: Cloud ensemble relations for use in higher order models of the planetary boundary layer, J. Atmos. Sci., 39, 2691–2700, 1982.
Bougeault, P.: A simple parameterisation of the large scale effects of cumulus convection, Mon. Weather Rev., 113, 2108–2121, https://doi.org/10.1175/1520-0493(1985)113<2108:ASPOTL>2.0.CO;2, 1985.
Bromwich, D. H., Werner, K., Casati, B., Powers, J. G., Gorodetskaya, I. V., Massonnet, F., Vitale, V., Heinrich, V. J., Liggett, D., Arndt, S., Barja, B., Bazile, E., Carpentier, S., Carrasco, J. F., Choi, T., Choi, Y., Colwell, S. R., Cordero, R. R., Gervasi, M., Haiden, T., Hirasawa, N., Inoue, J., Jung, T., Kalesse, H., Kim, S.-J., Lazzara, M. A., Manning, K. W., Norris, K., Park, S.-J., Reid, P., Rigor, I., Rowe, P. M., Schmithüsen, H., Seifert, P., Sun, Q., Uttal, T., Zannoni, M., and Zou, X.: The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH), B. Am. Meteorol. Soc., 101, E1653–E1676, https://doi.org/10.1175/BAMS-D-19-0255.1, 2020.
Buizza, R., Bidlot, J.-R., Janousek, M., Keeley, S., Mogensen, K., and Richardson, D.: New IFS cycle brings sea-ice coupling and higher ocean resolution, ECMWF Newsl., 150, 14–17, https://doi.org/10.21957/xbov3ybily, 2017.
Casati, B.: MMDFs for the Environment and Climate Change Canada-CAPS regional forecast model for various Arctic sites, Norwegian Meteorological Institute [data set], https://doi.org/10.21343/2BX6-6027, 2023.
Casati, B., Robinson, T., Lemay, F., Køltzow, M., Haiden, T., Mekis, E., Lespinas, F., Fortin, V., Gascon, G., Milbrandt, J., and Smith, G.: Performance of the Canadian Arctic Prediction System during the YOPP Special Observing Periods, Atmosphere-Ocean, 61, 246–272, https://doi.org/10.1080/07055900.2023.2191831, 2023.
Catry, B., Geleyn, J. F., Bouyssel, F., Cedilnik, J., Brožková, R., and Derková, M.: A new sub-grid scale lift formulation in a mountain drag parameterisation scheme, Meteorol. Z., 17, 193–208, https://doi.org/10.1127/0941-2948/2008/0272, 2008.
Cheng, Y., Canuto, V. M., and Howard, A. M.: An Improved Model for the Turbulent PBL, J. Atmos. Sci., 59, 1550–1565, https://doi.org/10.1175/1520-0469(2002)059<1550:AIMFTT>2.0.CO;2, 2002.
Coté, J., Gravel, S., Méthot, A., Patoine, A., Roch, M., and Staniforth, A.: The operational CMC–MRD Global Environmental Multiscale (GEM) model. Part I: Design considerations and formulation, Mon. Weather Rev., 126, 1373–1395, https://doi.org/10.1175/1520-0493(1998)126<1373:TOCMGE>2.0.CO;2, 1998.
Cuxart, J., Bougeault, P., and Redelsperger, J.-L.: A turbulence scheme allowing for mesoscale and large-eddy simulations, Q. J. Roy. Meteor. Soc., 126, 1–30, https://doi.org/10.1002/qj.49712656202, 2000.
Cuxart, J., Holtslag, A. A. M., Beare, R. J., Bazile, E., Beljaars, A., Cheng, A., Conangla, L., Ek, M., Freedman, F., Hamdi, R., Kerstein, A., Kitagawa, H., Lenderink, G., Lewellen, D., Mailhot, J., Mauritsen, T., Perov, V., Schayes, G., Steeneveld, G.-J., Svensson, G., Taylor, P., Weng, W., Wunsch, S., and Xu, K.-M.: Single-Column Model Intercomparison for a Stably Stratified Atmospheric Boundary Layer, Bound.-Lay. Meteorol., 118, 273–303, https://doi.org/10.1007/s10546-005-3780-1, 2006.
Day, J.: MMDFs for the ECMWF-IFS global forecast model for various Polar sites, Norwegian Meteorological Institute [data set], https://doi.org/10.21343/A6KA-7142, 2023.
Day, J. J., Arduini, G., Sandu, I., Magnusson, L., Beljaars, A., Balsamo, G., Rodwell, M., and Richardson, D.: Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships, J. Adv. Model. Earth Sy., 12, e2020MS002144, https://doi.org/10.1029/2020MS002144, 2020.
Day, J. J., Keeley, S., Arduini, G., Magnusson, L., Mogensen, K., Rodwell, M., Sandu, I., and Tietsche, S.: Benefits and challenges of dynamic sea ice for weather forecasts, Weather Clim. Dynam., 3, 713–731, https://doi.org/10.5194/wcd-3-713-2022, 2022.
Delage, Y.: Parametrizing sub-grid scale vertical transport in atmospheric models under statically stable conditions, Bound.-Lay. Meteorol., 82, 23–48, https://doi.org/10.1023/A:1000132524077, 1997.
Delage, Y. and Girard, C.: Stability functions correct at the free convection limit and consistent for both the surface and Ekman layers, Bound.-Lay. Meteorol., 58, 19–31, https://doi.org/10.1007/BF00120749, 1992.
Donlon, C. J., Martin, M., Stark, J., Roberts-Jones, J., Fiedler, E., and Wimmer, W.: The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system, Remote Sens. Environ., 116, 140–158, https://doi.org/10.1016/j.rse.2010.10.017, 2012.
Ďurán, I. B., Geleyn, J., and Váňa, F.: A compact model for the stability dependency of TKE production–destruction–conversion terms valid for the whole range of Richardson numbers, J. Atmos. Sci., 71, 3004–3026, 2014.
Dyer, A. J. and Hicks, B. B.: Flux-Gradient Relationships in the Constant Flux Layer, Q. J. Roy. Meteor. Soc. 96, 715–721, 1970.
Emmerson, C. and Lahn, G.: Arctic opening: Opportunity and risk in the high north, Lloyds Rep., 59 pp., https://www.lloyds.com/news-and-insights/risk-reports/library/arctic-opening-opportunity-and-risk-in-the-high-north (last access: 11 July 2024), 2012.
Forbes, R. M. and Ahlgrimm, M.: On the Representation of High-Latitude Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model, Mon. Weather Rev., 142, 3425–3445, https://doi.org/10.1175/MWR-D-13-00325.1, 2014.
Frank, H.: MMDFs for the DWD-ICON global forecast model for various Arctic sites, Norwegian Meteorological Institute [data set], https://doi.org/10.21343/09KM-BJ07, 2023.
Gerard, L. and Geleyn, J.-F.: Evolution of a subgrid deep convection parametrization in a limited-area model with increasing resolution, Q. J. Roy. Meteor. Soc., 131, 2293–2312, https://doi.org/10.1256/qj.04.72, 2005.
Gerard, L., Piriou, J., Brožková, R., Geleyn, J., and Banciu, D.: Cloud and Precipitation Parameterization in a Meso-Gamma-Scale Operational Weather Prediction Model, Mon. Weather Rev., 137, 3960–3977, https://doi.org/10.1175/2009MWR2750.1, 2009.
Girard, C., Plante, A., Desgagné, M., McTaggart-Cowan, R., Côté, J., Charron, M., Gravel, S., Lee, V., Patoine, A., Qaddouri, A., Roch, M., Spacek, L., Tanguay, M., Vaillancourt, P. A., and Zadra, A.: Staggered vertical discretization of the Canadian Environmental Multiscale (GEM) model using a coordinate of the log-hydrostatic-pressure type, Mon. Weather Rev., 142, 1183–1196, https://doi.org/10.1175/MWR-D-13-00255.1, 2014.
Goessling, H. F., Jung, T., Klebe, S., Baeseman, J., Bauer, P., Chen, P., Chevallier, M., Dole, R., Gordon, N., Ruti, P., Bradley, A., Bromwich, D. H., Casati, B., Chechin, D., Day, J. J., Massonnet, F., Mills, B., Renfrew, I., Smith, G., and Tatusko, R.: Paving the way for the Year of Polar Prediction, B. Am. Meteorol. Soc., 97, ES85–ES88, https://doi.org/10.1175/BAMS-D-15-00270.1, 2016.
Haiden, T., Sandu, I., Balsamo, G., Arduini, G., and Beljaars, A.: Addressing biases in near-surface forecasts, ECMWF Newsletter, 157, 20–25, https://doi.org/10.21957/eng71d53th, 2018.
Hartten, L. M. and Khalsa, S. J. S.: The H-K Variable SchemaTable developed for the YOPPsiteMIP, https://doi.org/10.5281/zenodo.6463464, 2022.
Heise, E., Ritter, B., and Schrodin, R.: Operational implementation of the multilayer soil model, COSMO Technical Reports no. 9, Consortium for Small-Scale Modelling, Offenbach am Main, Germany, https://doi.org/10.5676/DWD_pub/nwv/cosmo-tr_9, 2006.
Hogan, R. J. and Bozzo, A.: A Flexible and Efficient Radiation Scheme for the ECMWF Model, J. Adv. Model. Earth Sy., 10, 1990–2008, https://doi.org/10.1029/2018MS001364, 2018.
Holt, J.: Merged Observatory Data File (MODF) for Ny Alesund, Norwegian Meteorological Institute, https://doi.org/10.21343/Y89M-6393, 2023.
Holtslag, A. A. M. and De Bruin, H. A. R.: Applied Modeling of the Nighttime Surface Energy Balance over Land, J. Appl. Meteorol. Clim., 27, 689–704, 1988.
Holtslag, A. A. M., Svensson, G., Baas, P., Basu, S., Beare, B., Beljaars, A. C. M., Bosveld, F. C., Cuxart, J., Lindvall, J., Steeneveld, G. J., Tjernström, M., and Van De Wiel, B. J. H.: Stable Atmospheric Boundary Layers and Diurnal Cycles: Challenges for Weather and Climate Models, B. Am. Meteorol. Soc., 94, 1691–1706, 2013.
Huang, L., Mariani, Z., and Crawford, R.: MODF for Erik Nielsen Airport, Whitehorse, Canada during YOPP SOP1 and SOP2, Norwegian Meteorological Institute, https://doi.org/10.21343/A33E-J150, 2023a.
Huang, L., Mariani, Z., and Crawford, R.: MODF for Iqaluit Airport, Iqaluit, Nunavut, Canada during YOPP SOP1 and SOP2, Norwegian Meteorological Institute, https://doi.org/10.21343/YRNF-CK57, 2023b.
Iacono, M., Delamere, J., Mlawer, E., Shephard, M., Clough, S., and Collins, W.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res., 113D, 13103, https://doi.org/10.1029/2008JD009944, 2008.
Jung, T. and Matsueda, M.: Verification of global numerical weather forecasting systems in polar regions using TIGGE data, Q. J. Roy. Meteor. Soc., 142, 574–582, https://doi.org/10.1002/qj.2437, 2016.
Jung, T., Gordon, N. D., Bauer, P., Bromwich, D. H., Chevallier, M., Day, J. J., Dawson, J., Doblas-Reyes, F., Fairall, C., Goessling, H. F., Holland, M., Inoue, J., Iversen, T., Klebe, S., Lemke, P., Losch, M., Makshtas, A., Mills, B., Nurmi, P., Perovich, D., Reid, P., Renfrew, I. A., Smith, G., Svensson, G., Tolstykh, M., and Yang, Q.: Advancing Polar Prediction Capabilities on Daily to Seasonal Time Scales, B. Am. Meteorol. Soc., 97, 1631–1647, https://doi.org/10.1175/BAMS-D-14-00246.1, 2016.
Kähnert, M., Sodemann, H., and Remes, T. M., Fortelius, C., Bazile, E., and Esau, I.: Spatial Variability of Nocturnal Stability Regimes in an Operational Weather Prediction Model, Bound.-Lay. Meteorol., 186, 373–397, https://doi.org/10.1007/s10546-022-00762-1, 2023.
Kain, J. S. and Fritsch, J. M.: A One-Dimensional Entraining/Detraining Plume Model and Its Application in Convective Parameterization, J. Atmos. Sci., 47, 2784–2802, https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2, 1990.
Karlsson, J. and Svensson, G.: Consequences of poor representation of Arctic sea-ice albedo and cloud-radiation interactions in the CMIP5 model ensemble, Geophys. Res. Lett., 40, 4374–4379, https://doi.org/10.1002/grl.50768, 2013.
Köhler, M., Ahlgrimm, M., and Beljaars, A.: Unified treatment of dry convective and stratocumulus topped boundary layers in the ECMWF model, Q. J. Roy. Meteor. Soc., 137, 43–57, 2011.
Køltzow, M., Casati, B., Bazile, E., Haiden, T., and Valkonen, T.: An NWP Model Intercomparison of Surface Weather Parameters in the European Arctic during the Year of Polar Prediction Special Observing Period Northern Hemisphere 1, Weather Forecast., 34, 959–983, https://doi.org/10.1175/WAF-D-19-0003.1, 2019.
Lawrence, H., Bormann, N., Sandu, I., Day, J., Farnan, J., and Bauer, P.: Use and impact of Arctic observations in the ECMWF Numerical Weather Prediction system, Q. J. Roy. Meteor. Soc., 145, 3432–3454, https://doi.org/10.1002/qj.3628, 2019.
Lenderink, G. and Holtslag, A. A. M.: An updated length-scale formulation for turbulent mixing in clear and cloudy boundary layers, Q. J. Roy. Meteor. Soc., 130, 3405–3427, https://doi.org/10.1256/qj.03.117, 2004.
Li, J. and Barker, H. W.: A radiation algorithm with correlated-k distribution. Part I: Local thermal equilibrium, J. Atmos. Sci., 62, 286–309, 2005.
Lott, F. and Miller, M. J.: A new subgrid-scale orographic drag parametrization: Its formulation and testing, Q. J. Roy. Meteor. Soc., 123, 101–127, 1997.
Louis, J. F.: A parametric model of vertical eddy fluxes in the atmosphere, Bound.-Lay. Meteorol., 17, 187–202, 1979.
Mariani, Z., Morris, S. M., Uttal, T., Akish, E., Crawford, R., Huang, L., Day, J., Tjernström, J., Godøy, Ø., Ferrighi, L., Hartten, L. M., Holt, J., Cox, C. J., O'Connor, E., Pirazzini, R., Maturilli, M., Prakash, G., Mather, J., Strong, K., Fogal, P., Kustov, V., Svensson, G., Gallagher, M., and Vasel, B.: Special Observing Period (SOP) data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP), Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, 2024.
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013.
Milbrandt, J. A. and Morrison, H.: Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part III: Introduction of Multiple Free Categories, J. Atmos. Sci., 73, 975–995, https://doi.org/10.1175/JAS-D-15-0204.1, 2016.
Milbrandt, J. A., Bélair, S., Faucher, M., Vallée, M., Carrera, M. L., and Glazer, A.: The Pan-Canadian High Resolution (2.5 km) Deterministic Prediction System, Weather Forecast., 31, 1791–1816, https://doi.org/10.1175/WAF-D-16-0035.1, 2016.
Miller, N. B., Shupe, M. D., Lenaerts, J. T. M., Kay, J. E., de Boer, G., and Bennartz, R.: Process-based model evaluation using surface energy budget observations in central Greenland, J. Geophys. Res.-Atmos., 123, 4777–4796, https://doi.org/10.1029/2017JD027377, 2018.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102D, 16663–16682, 1997.
Morrison, H. and Milbrandt, J. A.: Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests, J. Atmos. Sci., 72, 287–311, https://doi.org/10.1175/JAS-D-14-0065.1, 2015.
Morrison, H., Milbrandt, J. A., Bryan, G. H., Ikeda, K., Tessendorf, S. A., and Thompson, G.: Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part II: Case Study Comparisons with Observations and Other Schemes, J. Atmos. Sci., 72, 312–339, https://doi.org/10.1175/JAS-D-14-0066.1, 2015.
Müller, M., Homleid, M., Ivarsson, K.-I., Køltzow, M. A. Ø., Lindskog, M., Midtbø, K. H., Andrae, U., Aspelien, T., Berggren, L., Bjørge, D., Dahlgren, P., Kristiansen, J., Randriamampianina, R., Ridal, M., and Vignes, O.: AROME-MetCoOp: A Nordic Convective-Scale Operational Weather Prediction Model, Weather Forecast., 32, 609–627, https://doi.org/10.1175/WAF-D-16-0099.1, 2017.
Noilhan, J. and Planton, S.: A Simple Parameterization of Land Surface Processes for Meteorological Models, Mon. Weather Rev., 117, 536–549, 1989.
O'Connor, E.: Merged observation data file for Sodankyla, Norwegian Meteorological Institute, https://doi.org/10.21343/M16P-PQ17, 2023.
Pailleux, J., Geleyn, J.-F., Hamrud, M., Courtier, P., Thépaut, J.-N., Rabier, F., Andersson, E., Burridge, D., Simmons, A., Salmond, D., Khatib, E., and Fischer, C.: Twenty-five years of IFS/ARPEGE, ECMWF Newsletter, 141, 22–30, https://doi.org/10.21957/FTU6MFVY, 2014.
Pergaud, J., Masson, V., Malardel, S., and Couvreux, F.: A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction, Bound.-Lay. Meteorol., 132, 83–106, https://doi.org/10.1007/s10546-009-9388-0, 2009.
Pinty, J.-P. and Jabouille, P.: A mixed-phase cloud parameterization for use in a mesoscale non-hydrostatic model: Simulations of a squall line and of orographic precipitation, in: Proc. Conf. on Cloud Physics, Everett, WA, August 1998, 217–220, 1998.
Pithan, F., Medeiros, B., and Mauritsen, T.: Mixed-phase clouds cause climate model biases in Arctic wintertime temperature inversions, Clim. Dynam., 43, 289–303, https://doi.org/10.1007/s00382-013-1964-9, 2014.
Pithan, F., Ackerman, A., Angevine, W. M., Hartung, K., Ickes, L., Kelley, M., Medeiros, B., Sandu, I., Steeneveld, G.-J., Sterk, H. A. M., Svensson, G., Vaillancourt, P. A., and Zadra, A.: Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison, J. Adv. Model. Earth Sy., 8, 1345–1357, https://doi.org/10.1002/2016MS000630, 2016.
Prill, F, Reinert, D., Rieger, D., and Zängl, G.: ICON Tutorial – Working with the ICON model, https://doi.org/10.5676/dwd_pub/nwv/icon_tutorial2020, 2020.
Raschendorfer, M.: The new turbulence parameterization of LM, COSMO Newsl., 1, 89–97, 2001.
Remes, T.: MMDFs for the MetNorway AROME regional forecast model for various Arctic sites, Norwegian Meteorological Institute [data set], https://doi.org/10.21343/47AX-MY36, 2023.
Rodwell, M. J. and Palmer, T. N.: Using numerical weather prediction to assess climate models, Q. J. Roy. Meteor. Soc., 133, 129–146, https://doi.org/10.1002/qj.23, 2007.
Sandu, I., Beljars, A., Bechtold, P., Mauritsen, T., and Balsamo, G.: Why is it so difficult to represent stably stratified conditions in numerical weather prediction (NWP) models?, J. Adv. Model. Earth Sy., 5, 117–133, https://doi.org/10.1002/jame.20013, 2013.
Sedlar, J., Tjernström, M., Rinke, A., Orr, A., Cassano, J., and Fettweis, X.: Confronting Arctic troposphere, clouds, and surface energy budget representations in regional climate models with observations, J. Geophys. Res.-Atmos., 125, e2019JD031783, https://doi.org/10.1029/2019JD031783, 2020.
Seifert, A.: A revised cloud microphysical parameterization for COSMO-LME, COSMO News Letter no. 7, http://www.cosmo-model.org (last access: 11 July 2024), 2008.
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier, F., Lac, C., and Masson, V.: The AROME-France Convective-Scale Operational Model, Mon. Weather Rev., 139, 976–991, https://doi.org/10.1175/2010MWR3425.1, 2011.
Seity, Y., Lac, C., Bouyssel, F., Riette, S., and Bouteloup, Y.: Cloud and microphysical schemes in ARPEGE and AROME models, in: Proceedings of the Workshop on Parametrization of Clouds and Precipitation (ECMWF), Reading, UK, 5–8 November 2012, https://www.ecmwf.int/en/elibrary/ (last access: 16 July 2024), 2012.
Siebesma, A. P., Soares, P. M., and Teixeira, J.: A combined eddy diffusivity mass-flux approach for the convective boundary layer, J. Atmos. Sci., 64, 1230–1248, https://doi.org/10.1175/JAS3888.1, 2007.
Soares, P., Miranda, P., Siebesma, A., and Teixeira, J.: An eddy-diffusivity/mass-flux parametrization for dry and shallow cumulus convection, Q. J. Roy. Meteor. Soc., 130, 3365–3383, https://doi.org/10.1256/qj.03.223, 2004.
Solomon, A., Shupe, M. D., Svensson, G., Barton, N. P., Batrak, Y., Bazile, E., Day, J. J., Doyle, J. D., Frank, H. P., Keeley, S., Remes, T., and Tolstykh, M.: The winter central Arctic surface energy budget: A model evaluation using observations from the MOSAiC campaign, Elem. Sci. Anthr., 11, 00104, https://doi.org/10.1525/elementa.2022.00104, 2023.
Svensson, G. and Karlsson, J.: On the Arctic Wintertime Climate in Global Climate Models, J. Climate, 24, 5757–5771, https://doi.org/10.1175/2011JCLI4012.1, 2011.
Tarasova, T. A. and Fomin, B. A.: The Use of New Parameterizations for Gaseous Absorption in the CLIRAD-SW Solar Radiation Code for Models, J. Atmos. Ocean. Tech., 24, 1157–1162, https://doi.org/10.1175/JTECH2023.1, 2007.
Tiedtke, M.: Representation of Clouds in Large-Scale Models, Mon. Weather Rev., 121, 3040–3061, 1993.
Tjernström, M., Žagar, M., Svensson, G., Cassano, J. J., Pfeifer, S., Rinke, A., Wyser, K., Dethloff, K., Jones, C., Semmler, T., and Shaw, M.: Modelling the Arctic Boundary Layer: An Evaluation of Six Arcmip Regional-Scale Models using Data from the Sheba Project, Bound.-Lay. Meteorol., 117, 337–381, https://doi.org/10.1007/s10546-004-7954-z, 2005.
Tjernström, M., Svensson, G., Magnusson, L., Brooks, I. M., Prytherch, J., Vüllers, J., and Young, G.: Central Arctic weather forecasting: Confronting the ECMWF IFS with observations from the Arctic Ocean 2018 expedition, Q. J. Roy. Meteor. Soc., 147, 1278–1299, https://doi.org/10.1002/qj.3971, 2021.
Tolstykh, M.: MMDFs for the Roshydromet-SLAV global forecast model for various Arctic sites, Nor. Meteorol. Inst. [data set], https://doi.org/10.21343/J4SJ-4N61, 2023.
Tolstykh, M., Shashkin, V., Fadeev, R., and Goyman, G.: Vorticity-divergence semi-Lagrangian global atmospheric model SL-AV20: dynamical core, Geosci. Model Dev., 10, 1961–1983, https://doi.org/10.5194/gmd-10-1961-2017, 2017.
Tolstykh, M. A., Fadeev, R. Yu., Shashkin, V. V., Goyman, G. S., Zaripov, R. B., Kiktev, D. B., Makhnorylova, S. V., Mizyak, V. G., and Rogutov, V. S.: Multiscale Global Atmosphere Model SLAV: the Results of Medium-range Weather Forecasts, Russ. Meteorol. Hydro+., 43, 773–779, https://doi.org/10.3103/S1068373918110080, 2018.
Uttal, T., Starkweather, S., Drummond, J. R., Vihma, T., Makshtas, A. P., Darby, L. S., Burkhart, J. F., Cox, C. J., Schmeisser, L. N., Haiden, T., Maturilli, M., Shupe, M. D., De Boer, G., Saha, A., Grachev, A. A., Crepinsek, S. M., Bruhwiler, L., Goodison, B., McArthur, B., Walden, V. P., Dlugokencky, E. J., Persson, P. O. G., Lesins, G., Laurila, T., Ogren, J. A., Stone, R., Long, C. N., Sharma, S., Massling, A., Turner, D. D., Stanitski, D. M., Asmi, E., Aurela, M., Skov, H., Eleftheriadis, K., Virkkula, A., Platt, A., Førland, E. J., Iijima, Y., Nielsen, I. E., Bergin, M. H., Candlish, L., Zimov, N. S., Zimov, S. A., O'Neill, N. T., Fogal, P. F., Kivi, R., Konopleva-Akish, E. A., Verlinde, J., Kustov, V. Y., Vasel, B., Ivakhov, V. M., Viisanen, Y., and Intrieri, J. M.: International Arctic Systems for Observing the Atmosphere: An International Polar Year Legacy Consortium, B. Am. Meteorol. Soc., 97, 1033–1056, https://doi.org/10.1175/BAMS-D-14-00145.1, 2015.
Uttal, T., Hartten, L. M., Khalsa, S. J., Casati, B., Svensson, G., Day, J., Holt, J., Akish, E., Morris, S., O'Connor, E., Pirazzini, R., Huang, L. X., Crawford, R., Mariani, Z., Godøy, Ø., Tjernström, J. A. K., Prakash, G., Hickmon, N., Maturilli, M., and Cox, C. J.: Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics, Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, 2024.
Van de Wiel, B. J. H., Vignon, E., Baas, P., van Hooijdonk, I. G. S., van der Linden, S. J. A., van Hooft, J. A., Bosveld, F. C., de Roode, S. R., Moene, A. F., and Genthon, C.: Regime Transitions in Near-Surface Temperature Inversions: A Conceptual Model, J. Atmos. Sci., 74, 1057–1073, https://doi.org/10.1175/JAS-D-16-0180.1, 2017.
van Hooijdonk, I. G. S., Donda, J. M. M., Clercx, H. J. H., Bosveld, F. C., and van de Wiel, B. J. H.: Shear Capacity as Prognostic for Nocturnal Boundary Layer Regimes, J. Atmos. Sci., 72, 1518–1532, https://doi.org/10.1175/JAS-D-14-0140.1, 2015.
van Meijgaard, E., van Ulft, L., Lenderink, G., De Roode, S., Wipfler, E. L., Boers, R., and van Timmermans, R.: Refinement and application of a regional atmospheric model for climate scenario calculations of Western Europe, KVR Research Rep. 054/12, 44 pp., http://library.wur.nl/WebQuery/wurpubs/fulltext/312258 (last access: 11 July 2024), 2012.
Vignon, E., van de Wiel, B. J. H., van Hooijdonk, I. G. S., Genthon, C., van der Linden, S. J. A., van Hooft, J. A., Baas, P., Maurel, W., Traullé, O., and Casasanta, G.: Stable boundary-layer regimes at Dome C, Antarctica: observation and analysis, Q. J. Roy. Meteor. Soc., 143, 1241–1253, https://doi.org/10.1002/qj.2998, 2017.
Wallace, J. M., Tibaldi, S., and Simmons, A. J.: Reduction of systematic forecast errors in the ECMWF model through the introduction of an envelope orography, Q. J. Roy. Meteor. Soc., 109, 683–717, https://doi.org/10.1002/qj.49710946202, 1983.
Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., Gonzalez-Beltran, A., Gray, A. J. G., Groth, P., Goble, C., Grethe, J. S., Heringa, J., ’t Hoen, P. A. C., Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S. J., Martone, M. E., Mons, A., Packer, A. L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M. A., Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J., Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B.: The FAIR Guiding Principles for scientific data management and stewardship, Sci. Data, 3, 160018, https://doi.org/10.1038/sdata.2016.18, 2016.
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015.
Short summary
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.
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate...
