Articles | Volume 22, issue 1
https://doi.org/10.5194/acp-22-319-2022
https://doi.org/10.5194/acp-22-319-2022
Research article
 | 
10 Jan 2022
Research article |  | 10 Jan 2022

Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog

Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié

Related authors

Simulations of idealised 3D atmospheric flows on terrestrial planets using LFRic-Atmosphere
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavčič, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 16, 5601–5626, https://doi.org/10.5194/gmd-16-5601-2023,https://doi.org/10.5194/gmd-16-5601-2023, 2023
Short summary
The second Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL2
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023,https://doi.org/10.5194/gmd-16-1713-2023, 2023
Short summary
A modern-day Mars climate in the Met Office Unified Model: dry simulations
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023,https://doi.org/10.5194/gmd-16-621-2023, 2023
Short summary
The first Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL1
Mike Bush, Tom Allen, Caroline Bain, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Humphrey Lean, Adrian Lock, James Manners, Marion Mittermaier, Cyril Morcrette, Rachel North, Jon Petch, Chris Short, Simon Vosper, David Walters, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 13, 1999–2029, https://doi.org/10.5194/gmd-13-1999-2020,https://doi.org/10.5194/gmd-13-1999-2020, 2020
Short summary
TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI): motivations and protocol version 1.0
Thomas J. Fauchez, Martin Turbet, Eric T. Wolf, Ian Boutle, Michael J. Way, Anthony D. Del Genio, Nathan J. Mayne, Konstantinos Tsigaridis, Ravi K. Kopparapu, Jun Yang, Francois Forget, Avi Mandell, and Shawn D. Domagal Goldman
Geosci. Model Dev., 13, 707–716, https://doi.org/10.5194/gmd-13-707-2020,https://doi.org/10.5194/gmd-13-707-2020, 2020
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Above-cloud concentrations of cloud condensation nuclei help to sustain some Arctic low-level clouds
Lucas J. Sterzinger and Adele L. Igel
Atmos. Chem. Phys., 24, 3529–3540, https://doi.org/10.5194/acp-24-3529-2024,https://doi.org/10.5194/acp-24-3529-2024, 2024
Short summary
Contrail formation on ambient aerosol particles for aircraft with hydrogen combustion: a box model trajectory study
Andreas Bier, Simon Unterstrasser, Josef Zink, Dennis Hillenbrand, Tina Jurkat-Witschas, and Annemarie Lottermoser
Atmos. Chem. Phys., 24, 2319–2344, https://doi.org/10.5194/acp-24-2319-2024,https://doi.org/10.5194/acp-24-2319-2024, 2024
Short summary
Effects of intermittent aerosol forcing on the stratocumulus-to-cumulus transition
Prasanth Prabhakaran, Fabian Hoffmann, and Graham Feingold
Atmos. Chem. Phys., 24, 1919–1937, https://doi.org/10.5194/acp-24-1919-2024,https://doi.org/10.5194/acp-24-1919-2024, 2024
Short summary
Cloud properties and their projected changes in CMIP models with low to high climate sensitivity
Lisa Bock and Axel Lauer
Atmos. Chem. Phys., 24, 1587–1605, https://doi.org/10.5194/acp-24-1587-2024,https://doi.org/10.5194/acp-24-1587-2024, 2024
Short summary
Water isotopic characterisation of the cloud–circulation coupling in the North Atlantic trades – Part 2: The imprint of the atmospheric circulation at different scales
Leonie Villiger and Franziska Aemisegger
Atmos. Chem. Phys., 24, 957–976, https://doi.org/10.5194/acp-24-957-2024,https://doi.org/10.5194/acp-24-957-2024, 2024
Short summary

Cited articles

Ahlgrimm, M. and Forbes, R.: Improving the representation of low clouds and drizzle in the ECMWF model based on ARM observations from the Azores, Mon. Weather Rev., 142, 668–685, 2014. a
Angevine, W. M., Olson, J., Kenyon, J., Gustafson, W. I., Endo, S., Suselj, K., and Turner, D. D.: Shallow Cumulus in WRF Parameterizations Evaluated against LASSO Large-Eddy Simulations, Mon. Weather Rev., 146, 4303–4322, https://doi.org/10.1175/MWR-D-18-0115.1, 2018. a
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, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. a
Bašták Ďurán, I., Köhler, M., Eichhorn-Müller, A., Maurer, V., Schmidli, J., Schomburg, A., Klocke, D., Göcke, T., Schäfer, S., Schlemmer, L., and Dewani, N.: The ICON Single-Column Mode, Atmosphere, 12, 906, https://doi.org/10.3390/atmos12070906, 2021. a
Beare, R. J., MacVean, M. K., Holtslag, A. A. M., Cuxart, J., Esau, I., Golaz, J.-C., Jimenez, M. A., Khairoutdinov, M., Kosovic, B., Lewellen, D., Lund, T. S., Lundquist, J. K., McCabe, A., Moene, A. F., Noh, Y., Raasch, S., and Sullivan, P.: An Intercomparison of Large-Eddy Simulations of the Stable Boundary Layer, Bound.-Lay. Meteorol., 118, 247–272, https://doi.org/10.1007/s10546-004-2820-6, 2006. a, b
Download
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Altmetrics
Final-revised paper
Preprint