Articles | Volume 25, issue 12
https://doi.org/10.5194/acp-25-6539-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-6539-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Vertical profiles of liquid water content in fog layers during the SOFOG3D experiment
Théophane Costabloz
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Frédéric Burnet
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Christine Lac
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Pauline Martinet
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Julien Delanoë
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, Guyancourt, France
Susana Jorquera
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, Guyancourt, France
Maroua Fathalli
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
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Guillaume Feger, Jean-Pierre Chaboureau, Thibaut Dauhut, Julien Delanoë, and Pierre Coutris
Atmos. Chem. Phys., 25, 7447–7465, https://doi.org/10.5194/acp-25-7447-2025, https://doi.org/10.5194/acp-25-7447-2025, 2025
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Saharan air at the trade wind layer, cold pools, and dry upper troposphere has these three main factors inhibiting the cyclogenesis of the Pierre Henri mesoscale convective system. The findings were obtained through observations made during two flights of the Clouds-Atmospheric Dynamics-Dust Interactions in West Africa (CADDIWA) campaign and a convection-permitting simulation run with the Meso-NH model. They provide new insights into the complex dynamics of cyclogenesis in the Cabo Verde region and challenge the existing model of the Saharan Air Layer (SAL).
Aymeric Dziduch, Guillaume Mioche, Quentin Coopman, Clément Bazantay, Julien Delanoë, and Olivier Jourdan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2698, https://doi.org/10.5194/egusphere-2025-2698, 2025
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Low-level clouds play a central role in the Arctic climate, modulating the surface energy budget with competing warming and cooling effects. In this study, radar-lidar satellite products are used to investigate the geographical and seasonal variations of different cloud types observed over eight years. Oceanic regions are characterized by high occurrences of low-level mixed-phase clouds, which are influenced by atmospheric stability conditions, surface temperatures and cold air outbreaks.
Sandrine Bony, Basile Poujol, Brett McKim, Nicolas Rochetin, Marie Lothon, Julia Windmiller, Nicolas Maury, Clarisse Dufaux, Louis Jaffeux, Patrick Chazette, and Julien Delanoë
EGUsphere, https://doi.org/10.5194/egusphere-2025-2839, https://doi.org/10.5194/egusphere-2025-2839, 2025
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Space photographs of the Earth show that clouds form diverse, common but poorly understood cloud patterns. The analysis of observations gathered from research aircraft over the tropical ocean shows that the merging of thermals and clouds in the first kilometer of the atmosphere plays a key role in controlling the size, depth and spacing of clouds. This reveals a fundamental process through which clouds interact with each other and with their environment.
Adrien Marcel, Sébastien Riette, Didier Ricard, and Christine Lac
EGUsphere, https://doi.org/10.5194/egusphere-2025-2504, https://doi.org/10.5194/egusphere-2025-2504, 2025
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This paper provides substantial consistent updates to the atmospheric boundary layer schemes of the AROME model, yet they can be used for both forecasting and climate modelling. The study employs a single-column model versus large eddy simulations comparison and uses a machine learning tool to calibrate parameterizations. The model's ability to simulate shallow clouds has been enhanced, especially for shallow precipitating cumulus and stratocumulus clouds.
Chiara Giorio, Anne Monod, Valerio Di Marco, Pierre Herckes, Denise Napolitano, Amy Sullivan, Gautier Landrot, Daniel Warnes, Marika Nasti, Sara D'Aronco, Agathe Gérardin, Nicolas Brun, Karine Desboeufs, Sylvain Triquet, Servanne Chevaillier, Claudia Di Biagio, Francesco Battaglia, Frédéric Burnet, Stuart J. Piketh, Andreas Namwoonde, Jean-François Doussin, and Paola Formenti
EGUsphere, https://doi.org/10.5194/egusphere-2024-4140, https://doi.org/10.5194/egusphere-2024-4140, 2025
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A comparison between the solubility of trace metals in pairs of total suspended particulate (TSP) and fog water samples collected in Henties Bay, Namibia, during the AEROCLO-sA field campaign is presented. We found enhanced solubility of metals in fog samples which we attributed to metal-ligand complexes formation in the early stages of particle activation into droplets which can then remain in a kinetically stable form in fog or lead to the formation of colloidal nanoparticles.
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.
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024, https://doi.org/10.5194/amt-17-3863-2024, 2024
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Radar–lidar synergy is used to retrieve ice, supercooled water and mixed-phase cloud properties, making the most of the radar sensitivity to ice crystals and the lidar sensitivity to supercooled droplets. A first analysis of the output of the algorithm run on the satellite data is compared with in situ data during an airborne Arctic field campaign, giving a mean percent error of 49 % for liquid water content and 75 % for ice water content.
Karina McCusker, Anthony J. Baran, Chris Westbrook, Stuart Fox, Patrick Eriksson, Richard Cotton, Julien Delanoë, and Florian Ewald
Atmos. Meas. Tech., 17, 3533–3552, https://doi.org/10.5194/amt-17-3533-2024, https://doi.org/10.5194/amt-17-3533-2024, 2024
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Polarised radiative transfer simulations are performed using an atmospheric model based on in situ measurements. These are compared to large polarisation measurements to explore whether such measurements can provide information on cloud ice, e.g. particle shape and orientation. We find that using oriented particle models with shapes based on imagery generally allows for accurate simulations. However, results are sensitive to shape assumptions such as the choice of single crystals or aggregates.
Lucas Pailler, Laurent Deguillaume, Hélène Lavanant, Isabelle Schmitz, Marie Hubert, Edith Nicol, Mickaël Ribeiro, Jean-Marc Pichon, Mickaël Vaïtilingom, Pamela Dominutti, Frédéric Burnet, Pierre Tulet, Maud Leriche, and Angelica Bianco
Atmos. Chem. Phys., 24, 5567–5584, https://doi.org/10.5194/acp-24-5567-2024, https://doi.org/10.5194/acp-24-5567-2024, 2024
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The composition of dissolved organic matter of cloud water has been investigated through non-targeted high-resolution mass spectrometry on only a few samples collected in the Northern Hemisphere. In this work, the chemical composition of samples collected at Réunion Island (SH) is investigated and compared to samples collected at Puy de Dôme (NH). Sampling, analysis and data treatment with the same methodology produced a unique dataset for investigating the molecular composition of clouds.
Maud Leriche, Pierre Tulet, Laurent Deguillaume, Frédéric Burnet, Aurélie Colomb, Agnès Borbon, Corinne Jambert, Valentin Duflot, Stéphan Houdier, Jean-Luc Jaffrezo, Mickaël Vaïtilingom, Pamela Dominutti, Manon Rocco, Camille Mouchel-Vallon, Samira El Gdachi, Maxence Brissy, Maroua Fathalli, Nicolas Maury, Bert Verreyken, Crist Amelynck, Niels Schoon, Valérie Gros, Jean-Marc Pichon, Mickael Ribeiro, Eric Pique, Emmanuel Leclerc, Thierry Bourrianne, Axel Roy, Eric Moulin, Joël Barrie, Jean-Marc Metzger, Guillaume Péris, Christian Guadagno, Chatrapatty Bhugwant, Jean-Mathieu Tibere, Arnaud Tournigand, Evelyn Freney, Karine Sellegri, Anne-Marie Delort, Pierre Amato, Muriel Joly, Jean-Luc Baray, Pascal Renard, Angelica Bianco, Anne Réchou, and Guillaume Payen
Atmos. Chem. Phys., 24, 4129–4155, https://doi.org/10.5194/acp-24-4129-2024, https://doi.org/10.5194/acp-24-4129-2024, 2024
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Aerosol particles in the atmosphere play a key role in climate change and air pollution. A large number of aerosol particles are formed from the oxidation of volatile organic compounds (VOCs and secondary organic aerosols – SOA). An important field campaign was organized on Réunion in March–April 2019 to understand the formation of SOA in a tropical atmosphere mostly influenced by VOCs emitted by forest and in the presence of clouds. This work synthesizes the results of this campaign.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Cheikh Dione, Martial Haeffelin, Frédéric Burnet, Christine Lac, Guylaine Canut, Julien Delanoë, Jean-Charles Dupont, Susana Jorquera, Pauline Martinet, Jean-François Ribaud, and Felipe Toledo
Atmos. Chem. Phys., 23, 15711–15731, https://doi.org/10.5194/acp-23-15711-2023, https://doi.org/10.5194/acp-23-15711-2023, 2023
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This paper documents the role of thermodynamics and turbulence in the fog life cycle over southwestern France. It is based on a unique dataset collected during the SOFOG3D field campaign in autumn and winter 2019–2020. The paper gives a threshold for turbulence driving the different phases of the fog life cycle and the role of advection in the night-time dissipation of fog. The results can be operationalised to nowcast fog and improve short-range forecasts in numerical weather prediction models.
Leonie Villiger, Marina Dütsch, Sandrine Bony, Marie Lothon, Stephan Pfahl, Heini Wernli, Pierre-Etienne Brilouet, Patrick Chazette, Pierre Coutris, Julien Delanoë, Cyrille Flamant, Alfons Schwarzenboeck, Martin Werner, and Franziska Aemisegger
Atmos. Chem. Phys., 23, 14643–14672, https://doi.org/10.5194/acp-23-14643-2023, https://doi.org/10.5194/acp-23-14643-2023, 2023
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This study evaluates three numerical simulations performed with an isotope-enabled weather forecast model and investigates the coupling between shallow trade-wind cumulus clouds and atmospheric circulations on different scales. We show that the simulations reproduce key characteristics of shallow trade-wind clouds as observed during the field experiment EUREC4A and that the spatial distribution of stable-water-vapour isotopes is shaped by the overturning circulation associated with these clouds.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
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Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
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Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Marie Mazoyer, Frédéric Burnet, and Cyrielle Denjean
Atmos. Chem. Phys., 22, 11305–11321, https://doi.org/10.5194/acp-22-11305-2022, https://doi.org/10.5194/acp-22-11305-2022, 2022
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The evolution of the droplet size distribution during the fog life cycle remains poorly understood and progress is required to reduce the uncertainty of fog forecasts. To gain insights into the physical processes driving the microphysics, intensive field campaigns were conducted during three winters at the SIRTA site in the south of Paris. This study analyzed the variations in fog microphysical properties and their potential interactions at the different evolutionary stages of the fog events.
Michael John Weston, Stuart John Piketh, Frédéric Burnet, Stephen Broccardo, Cyrielle Denjean, Thierry Bourrianne, and Paola Formenti
Atmos. Chem. Phys., 22, 10221–10245, https://doi.org/10.5194/acp-22-10221-2022, https://doi.org/10.5194/acp-22-10221-2022, 2022
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An aerosol-aware microphysics scheme is evaluated for fog cases in Namibia. AEROCLO-sA campaign observations are used to access and parameterise the model. The model cloud condensation nuclei activation is lower than the observations. The scheme is designed for clouds with updrafts, while fog typically forms in stable conditions. A pseudo updraft speed assigned to the lowest model levels helps achieve more realistic cloud droplet number concentration and size distribution in the model.
Meryl Wimmer, Gwendal Rivière, Philippe Arbogast, Jean-Marcel Piriou, Julien Delanoë, Carole Labadie, Quitterie Cazenave, and Jacques Pelon
Weather Clim. Dynam., 3, 863–882, https://doi.org/10.5194/wcd-3-863-2022, https://doi.org/10.5194/wcd-3-863-2022, 2022
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The effect of deep convection representation on the jet stream above the cold front of an extratropical cyclone is investigated in the global numerical weather prediction model ARPEGE. Two simulations using different deep convection schemes are compared with (re)analysis datasets and NAWDEX airborne observations. A deeper jet stream is observed with the less active scheme. The diabatic origin of this difference is interpreted by backward Lagrangian trajectories and potential vorticity budgets.
Sandrine Bony, Marie Lothon, Julien Delanoë, Pierre Coutris, Jean-Claude Etienne, Franziska Aemisegger, Anna Lea Albright, Thierry André, Hubert Bellec, Alexandre Baron, Jean-François Bourdinot, Pierre-Etienne Brilouet, Aurélien Bourdon, Jean-Christophe Canonici, Christophe Caudoux, Patrick Chazette, Michel Cluzeau, Céline Cornet, Jean-Philippe Desbios, Dominique Duchanoy, Cyrille Flamant, Benjamin Fildier, Christophe Gourbeyre, Laurent Guiraud, Tetyana Jiang, Claude Lainard, Christophe Le Gac, Christian Lendroit, Julien Lernould, Thierry Perrin, Frédéric Pouvesle, Pascal Richard, Nicolas Rochetin, Kevin Salaün, Alfons Schwarzenboeck, Guillaume Seurat, Bjorn Stevens, Julien Totems, Ludovic Touzé-Peiffer, Gilles Vergez, Jessica Vial, Leonie Villiger, and Raphaela Vogel
Earth Syst. Sci. Data, 14, 2021–2064, https://doi.org/10.5194/essd-14-2021-2022, https://doi.org/10.5194/essd-14-2021-2022, 2022
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The French ATR42 research aircraft participated in the EUREC4A international field campaign that took place in 2020 over the tropical Atlantic, east of Barbados. We present the extensive instrumentation of the aircraft, the research flights and the different measurements. We show that the ATR measurements of humidity, wind, aerosols and cloudiness in the lower atmosphere are robust and consistent with each other. They will make it possible to advance understanding of cloud–climate interactions.
Pascal Marquet, Pauline Martinet, Jean-François Mahfouf, Alina Lavinia Barbu, and Benjamin Ménétrier
Atmos. Meas. Tech., 15, 2021–2035, https://doi.org/10.5194/amt-15-2021-2022, https://doi.org/10.5194/amt-15-2021-2022, 2022
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Two conservative thermodynamic variables (moist-air entropy potential temperature and total water content) are introduced into a one-dimensional EnVar data assimilation system to demonstrate their benefit for future operational assimilation schemes, with the use of microwave brightness temperatures from a ground-based radiometer installed during the field campaign SOFGO3D. Results show that the brightness temperatures analysed with the new variables are improved, including the liquid water.
Pamela A. Dominutti, Pascal Renard, Mickaël Vaïtilingom, Angelica Bianco, Jean-Luc Baray, Agnès Borbon, Thierry Bourianne, Frédéric Burnet, Aurélie Colomb, Anne-Marie Delort, Valentin Duflot, Stephan Houdier, Jean-Luc Jaffrezo, Muriel Joly, Martin Leremboure, Jean-Marc Metzger, Jean-Marc Pichon, Mickaël Ribeiro, Manon Rocco, Pierre Tulet, Anthony Vella, Maud Leriche, and Laurent Deguillaume
Atmos. Chem. Phys., 22, 505–533, https://doi.org/10.5194/acp-22-505-2022, https://doi.org/10.5194/acp-22-505-2022, 2022
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We present here the results obtained during an intensive field campaign conducted in March to April 2019 in Reunion. Our study integrates a comprehensive chemical and microphysical characterization of cloud water. Our investigations reveal that air mass history and cloud microphysical properties do not fully explain the variability observed in their chemical composition. This highlights the complexity of emission sources, multiphasic exchanges, and transformations in clouds.
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
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
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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.
Gwendal Rivière, Meryl Wimmer, Philippe Arbogast, Jean-Marcel Piriou, Julien Delanoë, Carole Labadie, Quitterie Cazenave, and Jacques Pelon
Weather Clim. Dynam., 2, 1011–1031, https://doi.org/10.5194/wcd-2-1011-2021, https://doi.org/10.5194/wcd-2-1011-2021, 2021
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Inacurracies in representing processes occurring at spatial scales smaller than the grid scales of the weather forecast models are important sources of forecast errors. This is the case of deep convection representation in models with 10 km grid spacing. We performed simulations of a real extratropical cyclone using a model with different representations of deep convection. These forecasts lead to different behaviors in the ascending air masses of the cyclone and the jet stream aloft.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Florian Ewald, Silke Groß, Martin Wirth, Julien Delanoë, Stuart Fox, and Bernhard Mayer
Atmos. Meas. Tech., 14, 5029–5047, https://doi.org/10.5194/amt-14-5029-2021, https://doi.org/10.5194/amt-14-5029-2021, 2021
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In this study, we show how solar radiance observations can be used to validate and further constrain ice cloud microphysics retrieved from the synergy of radar–lidar measurements. Since most radar–lidar retrievals rely on a global assumption about the ice particle shape, ice water content and particle size biases are to be expected in individual cloud regimes. In this work, we identify and correct these biases by reconciling simulated and measured solar radiation reflected from these clouds.
Alistair Bell, Pauline Martinet, Olivier Caumont, Benoît Vié, Julien Delanoë, Jean-Charles Dupont, and Mary Borderies
Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, https://doi.org/10.5194/amt-14-4929-2021, 2021
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This paper presents work towards making retrievals on the liquid water content in fog and low clouds. Future retrievals will rely on a radar simulator and high-resolution forecast. In this work, real observations are used to assess the errors associated with the simulator and forecast. A selection method to reduce errors associated with the forecast is proposed. It is concluded that the distribution of errors matches the requirements for future retrievals.
Pierre-Etienne Brilouet, Marie Lothon, Jean-Claude Etienne, Pascal Richard, Sandrine Bony, Julien Lernoult, Hubert Bellec, Gilles Vergez, Thierry Perrin, Julien Delanoë, Tetyana Jiang, Frédéric Pouvesle, Claude Lainard, Michel Cluzeau, Laurent Guiraud, Patrice Medina, and Theotime Charoy
Earth Syst. Sci. Data, 13, 3379–3398, https://doi.org/10.5194/essd-13-3379-2021, https://doi.org/10.5194/essd-13-3379-2021, 2021
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During the EUREC4A field experiment that took place over the tropical Atlantic Ocean east of Barbados, the French ATR 42 environment research aircraft of SAFIRE aimed to characterize the shallow cloud properties near cloud base and the turbulent structure of the subcloud layer. The high-frequency measurements of wind, temperature and humidity as well as their translation in terms of turbulent fluctuations, turbulent moments and characteristic length scales of turbulence are presented.
David L. A. Flack, Gwendal Rivière, Ionela Musat, Romain Roehrig, Sandrine Bony, Julien Delanoë, Quitterie Cazenave, and Jacques Pelon
Weather Clim. Dynam., 2, 233–253, https://doi.org/10.5194/wcd-2-233-2021, https://doi.org/10.5194/wcd-2-233-2021, 2021
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The representation of an extratropical cyclone in simulations of two climate models is studied by comparing them to observations of the international field campaign NAWDEX. We show that the current resolution used to run climate model projections (more than 100 km) is not enough to represent the life cycle accurately, but the use of 50 km resolution is good enough. Despite these encouraging results, cloud properties (partitioning liquid and solid) are found to be far from the observations.
Nicolas Blanchard, Florian Pantillon, Jean-Pierre Chaboureau, and Julien Delanoë
Weather Clim. Dynam., 2, 37–53, https://doi.org/10.5194/wcd-2-37-2021, https://doi.org/10.5194/wcd-2-37-2021, 2021
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Rare aircraft observations in the warm conveyor belt outflow associated with an extratropical cyclone are complemented with convection-permitting simulations. They reveal a complex tropopause structure with two jet stream cores, from which one is reinforced by bands of negative potential vorticity. They show that negative potential vorticity takes its origin in mid-level convection, which indirectly accelerates the jet stream and, thus, may influence the downstream large-scale circulation.
Frédéric Szczap, Alaa Alkasem, Guillaume Mioche, Valery Shcherbakov, Céline Cornet, Julien Delanoë, Yahya Gour, Olivier Jourdan, Sandra Banson, and Edouard Bray
Atmos. Meas. Tech., 14, 199–221, https://doi.org/10.5194/amt-14-199-2021, https://doi.org/10.5194/amt-14-199-2021, 2021
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Spaceborne lidar and radar are suitable tools to investigate cloud vertical properties on a global scale. This paper presents the McRALI code that provides simulations of lidar and radar signals from the EarthCARE mission. Regarding radar signals, cloud heterogeneity induces a severe bias in velocity estimates. Regarding lidar signals, multiple scattering is not negligible. Our results also give some insight into the reliability of lidar signal modeling using independent column approximation.
Felipe Toledo, Julien Delanoë, Martial Haeffelin, Jean-Charles Dupont, Susana Jorquera, and Christophe Le Gac
Atmos. Meas. Tech., 13, 6853–6875, https://doi.org/10.5194/amt-13-6853-2020, https://doi.org/10.5194/amt-13-6853-2020, 2020
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Cloud observations are essential to rainfall, fog and climate change forecasts. One key instrument for these observations is cloud radar. Yet, discrepancies are found when comparing radars from different ground stations or satellites. Our work presents a calibration methodology for cloud radars based on reference targets, including an analysis of the uncertainty sources. The method enables the calibration of reference instruments to improve the quality and value of the cloud radar network data.
Pauline Martinet, Domenico Cimini, Frédéric Burnet, Benjamin Ménétrier, Yann Michel, and Vinciane Unger
Atmos. Meas. Tech., 13, 6593–6611, https://doi.org/10.5194/amt-13-6593-2020, https://doi.org/10.5194/amt-13-6593-2020, 2020
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Each year large human and economical losses are due to fog episodes. However, fog forecasts remain quite inaccurate, partly due to a lack of observations in the atmospheric boundary layer. The benefit of ground-based microwave radiometers has been investigated and has demonstrated their capability of significantly improving the initial state of temperature and liquid water content profiles in current numerical weather prediction models, paving the way for improved fog forecasts in the future.
Olivier Nuissier, Fanny Duffourg, Maxime Martinet, Véronique Ducrocq, and Christine Lac
Atmos. Chem. Phys., 20, 14649–14667, https://doi.org/10.5194/acp-20-14649-2020, https://doi.org/10.5194/acp-20-14649-2020, 2020
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This present article demonstrates how numerical simulations with very high horizontal resolution (150 m) can contribute to better understanding the key physical processes (turbulence and microphysics) that lead to Mediterranean heavy precipitation.
Nicolas Blanchard, Florian Pantillon, Jean-Pierre Chaboureau, and Julien Delanoë
Weather Clim. Dynam., 1, 617–634, https://doi.org/10.5194/wcd-1-617-2020, https://doi.org/10.5194/wcd-1-617-2020, 2020
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The study presents the first results from the airborne RASTA observations measured during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX). Our combined Eulerian–Lagrangian analysis found three types of organized convection (frontal, banded and mid-level) in the warm conveyor belt (WCB) of the Stalactite cyclone. The results emphasize that convection embedded in WCBs occurs in a coherent and organized manner rather than as isolated cells.
Cited articles
Albrecht, B. A., Fairall, C. W., Thomson, D. W., White, A. B., Snider, J. B., and Schubert, W. H.: Surface-based remote sensing of the observed and the Adiabatic liquid water content of stratocumulus clouds, Geophys. Res. Lett., 17, 89–92, https://doi.org/10.1029/GL017i001p00089, 1990. a, b, c
Antoine, S., Honnert, R., Seity, Y., Vié, B., Burnet, F., and Martinet, P.: Evaluation of an Improved AROME Configuration for Fog Forecasts during the SOFOG3D Campaign, Weather Forecast., 38, 1605–1620, https://doi.org/10.1175/WAF-D-22-0215.1, 2023. a
Beare, R. J. and Macvean, M. K.: Resolution Sensitivity and Scaling of Large-Eddy Simulations of the Stable Boundary Layer, Bound.-Lay. Meteorol., 112, 257–281, https://doi.org/10.1023/B:BOUN.0000027910.57913.4d, 2004. a
Bell, A., Martinet, P., Caumont, O., Burnet, F., Delanoë, J., Jorquera, S., Seity, Y., and Unger, V.: An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties, Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, 2022. a, b
Bergot, T. and Guedalia, D.: Numerical Forecasting of Radiation Fog. Part I: Numerical Model and Sensitivity Tests, Mon. Weather Rev., 122, 1218–1230, https://doi.org/10.1175/1520-0493(1994)122<1218:NFORFP>2.0.CO;2, 1994. a
Bergot, T., Escobar, J., and Masson, V.: Effect of small-scale surface heterogeneities and buildings on radiation fog: Large-eddy simulation study at Paris–Charles de Gaulle airport, Q. J. Roy. Meteorol. Soc., 141, 285–298, https://doi.org/10.1002/qj.2358, 2015. a
Betts, A. K.: Cloud Thermodynamic Models in Saturation Point Coordinates, J. Atmos. Sci., 39, 2182–2191, https://doi.org/10.1175/1520-0469(1982)039<2182:CTMISP>2.0.CO;2, 1982. a, b, c
Bott, A.: On the influence of the physico-chemical properties of aerosols on the life cycle of radiation fogs, Bound.-Lay. Meteorol., 56, 1–31, https://doi.org/10.1007/BF00119960, 1991. a
Boutle, I., Price, J., Kudzotsa, I., Kokkola, H., and Romakkaniemi, S.: Aerosol–fog interaction and the transition to well-mixed radiation fog, Atmos. Chem. Phys., 18, 7827–7840, https://doi.org/10.5194/acp-18-7827-2018, 2018. a, b, c, d
Boutle, I., Angevine, W., Bao, J.-W., Bergot, T., Bhattacharya, R., Bott, A., Ducongé, L., Forbes, R., Goecke, T., Grell, E., Hill, A., Igel, A. L., Kudzotsa, I., Lac, C., Maronga, B., Romakkaniemi, S., Schmidli, J., Schwenkel, J., Steeneveld, G.-J., and Vié, B.: Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog, Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, 2022. a, b
Boutle, I. A., Finnenkoetter, A., Lock, A. P., and Wells, H.: The London Model: forecasting fog at 333 m resolution, Q. J. Roy.l Meteorol. Soc., 142, 360–371, https://doi.org/10.1002/qj.2656, 2016. a
Braun, R. A., Dadashazar, H., MacDonald, A. B., Crosbie, E., Jonsson, H. H., Woods, R. K., Flagan, R. C., Seinfeld, J. H., and Sorooshian, A.: Cloud Adiabaticity and Its Relationship to Marine Stratocumulus Characteristics Over the Northeast Pacific Ocean, J. Geophys. Res.-Atmos., 123, 13790–13806, https://doi.org/10.1029/2018JD029287, 2018. a, b, c
Brenguier, J. L.: Parameterization of the Condensation Process: A Theoretical Approach, J. Atmos. Sci., 48, 264–282, https://doi.org/10.1175/1520-0469(1991)048<0264:POTCPA>2.0.CO;2, 1991. a
Brenguier, J.-L., Burnet, F., and Geoffroy, O.: Cloud optical thickness and liquid water path – does the k coefficient vary with droplet concentration?, Atmos. Chem. Phys., 11, 9771–9786, https://doi.org/10.5194/acp-11-9771-2011, 2011. a, b, c
Burnet, F.: SOFOG3D_CHARBONNIERE_CNRM_TETHERED-BALLOON-CDP-10S_L2, Aeris [data set], https://doi.org/10.25326/689, 2024. a
Burnet, F., Lac, C., Martinet, P., Fourrié, N., Haeffelin, M., Delanoë, J., Price, J., Barrau, S., Canut, G., Cayez, G., Dabas, A., Denjean, C., Dupont, J.-C., Honnert, R., Mahfouf, J.-F., Montmerle, T., Roberts, G., Seity, Y., and Vié, B.: The SOuth west FOGs 3D experiment for processes study (SOFOG3D) project, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17836, https://doi.org/10.5194/egusphere-egu2020-17836, 2020 a, b
Canut, G.: SOFOG3D_CHARBONNIERE_CNRM_TETHERED-BALLOON-MTO-10S_L2, Aeris [data set], https://doi.org/10.25326/89, 2020. a
Canut, G., Couvreux, F., Lothon, M., Legain, D., Piguet, B., Lampert, A., Maurel, W., and Moulin, E.: Turbulence fluxes and variances measured with a sonic anemometer mounted on a tethered balloon, Atmos. Meas. Tech., 9, 4375–4386, https://doi.org/10.5194/amt-9-4375-2016, 2016. a
Cermak, J. and Bendix, J.: Detecting ground fog from space–a microphysics-based approach, International Journal of Remote Sensing Bendix J. Int. J. Remote Sens., 00, 3345–3371, https://doi.org/10.1080/01431161003747505, 2011. a, b, c
Choularton, T. W., Fullarton, G., Latham, J., Mill, C. S., Smith, M. H., and Stromberg, I. M.: A field study of radiation fog in meppen, West Germany, Q. J. Roy. Meteorol. Soc., 107, 381–394, https://doi.org/10.1002/qj.49710745209, 1981. a
Cuxart, J. and Jiménez, M. A.: Deep Radiation Fog in a Wide Closed Valley: Study by Numerical Modeling and Remote Sensing, Pure Appl. Geophys., 169, 911–926, https://doi.org/10.1007/s00024-011-0365-4, 2012. a
Delanoë, J.: SOFOG3D_CHARBONNIERE_LATMOS_BASTA-vertical_L2a, Aeris [data set], https://doi.org/10.25326/134, 2020. a, b
Delanoë, J., Protat, A., Vinson, J.-P., Brett, W., Caudoux, C., Bertrand, F., du Chatelet, J. P., Hallali, R., Barthes, L., Haeffelin, M., and Dupont, J.-C.: BASTA: A 95-GHz FMCW Doppler Radar for Cloud and Fog Studies, J. Atmos. Ocean. Technol., 33, 1023–1038, https://doi.org/10.1175/JTECH-D-15-0104.1, 2016. a, b
Dhangar, N. G., Lal, D. M., Ghude, S. D., Kulkarni, R., Parde, A. N., Pithani, P., Niranjan, K., Prasad, D. S. V. V. D., Jena, C., Sajjan, V. S., Prabhakaran, T., Karipot, A. K., Jenamani, R. K., Singh, S., and Rajeevan, M.: On the Conditions for Onset and Development of Fog Over New Delhi: An Observational Study from the WiFEX, Pure Appl. Geophys., 178, 3727–3746, https://doi.org/10.1007/s00024-021-02800-4, 2021. a, b, c
Dione, C., Haeffelin, M., Burnet, F., Lac, C., Canut, G., Delanoë, J., Dupont, J.-C., Jorquera, S., Martinet, P., Ribaud, J.-F., and Toledo, F.: Role of thermodynamic and turbulence processes on the fog life cycle during SOFOG3D experiment, Atmos. Chem. Phys., 23, 15711–15731, https://doi.org/10.5194/acp-23-15711-2023, 2023. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z, aa, ab, ac, ad, ae, af, ag
Ducongé, L., Lac, C., Vié, B., Bergot, T., and Price, J. D.: Fog in heterogeneous environments: the relative importance of local and non-local processes on radiative-advective fog formation, Q. J. Roy. Meteorol. Soc., 146, 2522–2546, https://doi.org/10.1002/qj.3783, 2020. a, b
Dupont, J. C., Haeffelin, M., Stolaki, S., and Elias, T.: Analysis of Dynamical and Thermal Processes Driving Fog and Quasi-Fog Life Cycles Using the 2010–2013 ParisFog Dataset, Pure Appl. Geophys., 173, 1337–1358, https://doi.org/10.1007/s00024-015-1159-x, 2016. a, b, c
Duynkerke, P. G.: Turbulence, Radiation and fog in Dutch Stable Boundary Layers, Bound.-Lay. Meteorol., 90, 447–477, https://doi.org/10.1023/A:1026441904734, 1999. a, b
Edwards, J. M.: Radiative Processes in the Stable Boundary Layer: Part II. The Development of the Nocturnal Boundary Layer, Bound.-Lay. Meteorol., 131, 127–146, https://doi.org/10.1007/s10546-009-9363-9, 2009. a
Egli, S., Maier, F., Bendix, J., and Thies, B.: Vertical distribution of microphysical properties in radiation fogs – A case study, Atmos. Res., 151, 130–145, https://doi.org/10.1016/j.atmosres.2014.05.027, 2015. a, b
Fathalli, M., Lac, C., Burnet, F., and Vié, B.: Formation of fog due to stratus lowering: An observational and modelling case study, Q. J. Roy. Meteorol. Soc., 148, 2299–2324, https://doi.org/10.1002/qj.4304, 2022. a, b, c
Formenti, P., D’Anna, B., Flamant, C., Mallet, M., Piketh, S. J., Schepanski, K., Waquet, F., Auriol, F., Brogniez, G., Burnet, F., Chaboureau, J.-P., Chauvigné, A., Chazette, P., Denjean, C., Desboeufs, K., Doussin, J.-F., Elguindi, N., Feuerstein, S., Gaetani, M., Giorio, C., Klopper, D., Mallet, M. D., Nabat, P., Monod, A., Solmon, F., Namwoonde, A., Chikwililwa, C., Mushi, R., Welton, E. J., and Holben, B.: The Aerosols, Radiation and Clouds in Southern Africa Field Campaign in Namibia: Overview, Illustrative Observations, and Way Forward, B. Am. Meteorol. Soc., 100, 1277–1298, https://doi.org/10.1175/BAMS-D-17-0278.1, 2019. a
Fuzzi, S., Castillo, R. A., Jiusto, J. E., and Lala, G. G.: Chemical composition of radiation fog water at Albany, New York, and its relationship to fog microphysics, J. Geophys. Res.-Atmos., 89, 7159–7164, https://doi.org/10.1029/JD089iD05p07159, 1984. a
Gerber, H.: Microphysics of Marine Stratocumulus Clouds with Two Drizzle Modes, J. Atmos. Sci., 53, 1649–1662, https://doi.org/10.1175/1520-0469(1996)053<1649:MOMSCW>2.0.CO;2, 1996. a
Gerber, H. E.: Microstructure of a Radiation Fog, J. Atmos. Sci., 38, 454–458, https://doi.org/10.1175/1520-0469(1981)038<0454:MOARF>2.0.CO;2, 1981. a
Gultepe, I., Tardif, R., Michaelides, S. C., Cermak, J., Bott, A., Bendix, J., Müller, M. D., Pagowski, M., Hansen, B., Ellrod, G., Jacobs, W., Toth, G., and Cober, S. G.: Fog Research: A Review of Past Achievements and Future Perspectives, Pure Appl. Geophys., 164, 1121–1159, https://doi.org/10.1007/s00024-007-0211-x, 2007. a, b
Gultepe, I., Pearson, G., Milbrandt, J. A., Hansen, B., Platnick, S., Taylor, P., Gordon, M., Oakley, J. P., and Cober, S. G.: The Fog Remote Sensing and Modeling Field Project, B. Am. Meteorol. Soc., 90, 341–360, https://doi.org/10.1175/2008BAMS2354.1, 2009. a, b
Guy, H., Brooks, I. M., Turner, D. D., Cox, C. J., Rowe, P. M., Shupe, M. D., Walden, V. P., and Neely III, R. R.: Observations of Fog-Aerosol Interactions Over Central Greenland, J. Geophys. Res.-Atmos., 128, e2023JD038718, https://doi.org/10.1029/2023JD038718, 2023. a
Hummel, J. R. and Kuhn, W. R.: Comparison of radiative-convective models with constant and pressure-dependent lapse rates, Tellus, 33, 254–261, https://doi.org/10.1111/j.2153-3490.1981.tb01749.x, 1981. a
Koračin, D., Lewis, J., Thompson, W. T., Dorman, C. E., and Businger, J. A.: Transition of Stratus into Fog along the California Coast: Observations and Modeling, J. Atmos. Sci., 58, 1714–1731, https://doi.org/10.1175/1520-0469(2001)058<1714:TOSIFA>2.0.CO;2, 2001. a
Kunkel, B. A.: Parameterization of Droplet Terminal Velocity and Extinction Coefficient in Fog Models, J. Appl. Meteorol. Climatol., 23, 34–41, https://doi.org/10.1175/1520-0450(1984)023<0034:PODTVA>2.0.CO;2, 1984. a
Lance, S., Brock, C. A., Rogers, D., and Gordon, J. A.: Water droplet calibration of the Cloud Droplet Probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC, Atmos. Meas. Tech., 3, 1683–1706, https://doi.org/10.5194/amt-3-1683-2010, 2010. a, b
Maalick, Z., Kühn, T., Korhonen, H., Kokkola, H., Laaksonen, A., and Romakkaniemi, S.: Effect of aerosol concentration and absorbing aerosol on the radiation fog life cycle, Atmos. Environ., 133, 26–33, https://doi.org/10.1016/j.atmosenv.2016.03.018, 2016. a
Martinet, P.: SOFOG3D_CHARBONNIERE_CNRM_MWR-HATPRO-LWP_L2, Aeris [data set], https://doi.org/10.25326/207, 2021. a
Martinet, P., Unger, V., Burnet, F., Georgis, J.-F., Hervo, M., Huet, T., Löhnert, U., Miller, E., Orlandi, E., Price, J., Schröder, M., and Thomas, G.: A dataset of temperature, humidity, and liquid water path retrievals from a network of ground-based microwave radiometers dedicated to fog investigation, B. Atmos. Sci. Technol., 3, 6, https://doi.org/10.1007/s42865-022-00049-w, 2022. a, b
Mason, J.: The Physics of Radiation Fog, J. Meteorol. Soc. JPN II, 60, 486–499, https://doi.org/10.2151/jmsj1965.60.1_486, 1982. a
Mazoyer, M., Lac, C., Thouron, O., Bergot, T., Masson, V., and Musson-Genon, L.: Large eddy simulation of radiation fog: impact of dynamics on the fog life cycle, Atmos. Chem. Phys., 17, 13017–13035, https://doi.org/10.5194/acp-17-13017-2017, 2017. a, b, c
Mazoyer, M., Burnet, F., Denjean, C., Roberts, G. C., Haeffelin, M., Dupont, J.-C., and Elias, T.: Experimental study of the aerosol impact on fog microphysics, Atmos. Chem. Phys., 19, 4323–4344, https://doi.org/10.5194/acp-19-4323-2019, 2019. a
Mazoyer, M., Burnet, F., and Denjean, C.: Experimental study on the evolution of droplet size distribution during the fog life cycle, Atmos. Chem. Phys., 22, 11305–11321, https://doi.org/10.5194/acp-22-11305-2022, 2022. a, b, c, d
Musson-Genon, L.: Numerical Simulation of a Fog Event with a One-Dimensional Boundary Layer Model, Mon. Weather Rev., 115, 592–607, https://doi.org/10.1175/1520-0493(1987)115<0592:NSOAFE>2.0.CO;2, 1987. a
Müller, M. D., Masbou, M., and Bott, A.: Three-dimensional fog forecasting in complex terrain, Q. J. Roy. Meteorol. Soc., 136, 2189–2202, https://doi.org/10.1002/qj.705, 2010. a, b
Nakanishi, M.: Large-Eddy Simulation Of Radiation Fog, Bound.-Lay. Meteorol., 94, 461–493, https://doi.org/10.1023/A:1002490423389, 2000. a, b
Niu, S. J., Liu, D. Y., Zhao, L. J., Lu, C. S., Lü, J. J., and Yang, J.: Summary of a 4-Year Fog Field Study in Northern Nanjing, Part 2: Fog Microphysics, Pure Appl. Geophys., 169, 1137–1155, https://doi.org/10.1007/s00024-011-0344-9, 2011. a, b
Okita, T.: Observations of the vertical structure of a stratus cloud and radiation fogs in relation to the mechanism of drizzle formation, Tellus, 14, 310–322, https://doi.org/10.3402/tellusa.v14i3.9556, 1962. a, b, c
Okuda, T., Tomine, K., and Sugawara, H.: Mechanisms of Temporary Improvement and Rapid Changes in Visibility in Fogs, J. Meteorol. Soc. Jpn, 88, 243–261, https://doi.org/10.2151/jmsj.2010-301, 2010. a
Oliver, D. A., Lewellen, W. S., and Williamson, G. G.: The Interaction between Turbulent and Radiative Transport in the Development of Fog and Low-Level Stratus, J. Atmos. Sci., 35, 301–316, https://doi.org/10.1175/1520-0469(1978)035<0301:TIBTAR>2.0.CO;2, 1978. a
Pagowski, M., Gultepe, I., and King, P.: Analysis and Modeling of an Extremely Dense Fog Event in Southern Ontario, J. Appl. Meteorol., 43, 3–16, https://doi.org/10.1175/1520-0450(2004)043<0003:AAMOAE>2.0.CO;2, 2004. a
Pinnick, R. G., Hoihjelle, D. L., Fernandez, G., Stenmark, E. B., Lindberg, J. D., Hoidale, G. B., and Jennings, S. G.: Vertical Structure in Atmospheric Fog and Haze and Its Effects on Visible and Infrared Extinction, J. Atmos. Sci., 35, 2020–2032, https://doi.org/10.1175/1520-0469(1978)035<2020:VSIAFA>2.0.CO;2, 1978. a, b
Poku, C., Ross, A. N., Hill, A. A., Blyth, A. M., and Shipway, B.: Is a more physical representation of aerosol activation needed for simulations of fog?, Atmos. Chem. Phys., 21, 7271–7292, https://doi.org/10.5194/acp-21-7271-2021, 2021. a
Price, J., Porson, A., and Lock, A.: An Observational Case Study of Persistent Fog and Comparison with an Ensemble Forecast Model, Bound.-Lay. Meteorol., 155, 301–327, https://doi.org/10.1007/s10546-014-9995-2, 2015. a, b
Price, J. D.: On the Formation and Development of Radiation Fog: An Observational Study, Bound.-Lay. Meteorol., 172, 167–197, https://doi.org/10.1007/s10546-019-00444-5, 2019. a, b
Price, J. D., Lane, S., Boutle, I. A., Smith, D. K. E., Bergot, T., Lac, C., Duconge, L., McGregor, J., Kerr-Munslow, A., Pickering, M., and Clark, R.: LANFEX: A Field and Modeling Study to Improve Our Understanding and Forecasting of Radiation Fog, B. Am. Meteorol. Soc., 99, 2061–2077, https://doi.org/10.1175/BAMS-D-16-0299.1, 2018. a
Rémy, S. and Bergot, T.: Assessing the impact of observations on a local numerical fog prediction system, Q. J. Roy. Meteorol. Soc., 135, 1248–1265, https://doi.org/10.1002/qj.448, 2009. a
Roach, W. T., Brown, R., Caughey, S. J., Garland, J. A., and Readings, C. J.: The physics of radiation fog: I – a field study, Q. J. Roy. Meteorol. Soc., 102, 313–333, https://doi.org/10.1002/qj.49710243204, 1976. a, b, c
Ryznar, E.: Advection-radiation fog near lake Michigan, Atmos. Environ. (1967), 11, 427–430, https://doi.org/10.1016/0004-6981(77)90004-X, 1977. a
Schwenkel, J. and Maronga, B.: Large-eddy simulation of radiation fog with comprehensive two-moment bulk microphysics: impact of different aerosol activation and condensation parameterizations, Atmos. Chem. Phys., 19, 7165–7181, https://doi.org/10.5194/acp-19-7165-2019, 2019. a
Steeneveld, G. J., Ronda, R. J., and Holtslag, A. A. M.: The Challenge of Forecasting the Onset and Development of Radiation Fog Using Mesoscale Atmospheric Models, Bound.-Lay. Meteorol., 154, 265–289, https://doi.org/10.1007/s10546-014-9973-8, 2015. a
Stolaki, S., Haeffelin, M., Lac, C., Dupont, J.-C., Elias, T., and Masson, V.: Influence of aerosols on the life cycle of a radiation fog event. A numerical and observational study, Atmos. Res., 151, 146–161, https://doi.org/10.1016/j.atmosres.2014.04.013, 2015. a
Tardif, R.: The Impact of Vertical Resolution in the Explicit Numerical Forecasting of Radiation Fog: A Case Study, Pure Appl. Geophys., 164, 1221–1240, https://doi.org/10.1007/s00024-007-0216-5, 2007. a
Tardif, R. and Rasmussen, R. M.: Event-Based Climatology and Typology of Fog in the New York City Region, J. Appl. Meteorol. Climatol., 46, 1141–1168, https://doi.org/10.1175/JAM2516.1, 2007. a, b, c
Teixeira, J.: Simulation of fog with the ECMWF prognostic cloud scheme, Q. J. Roy. Meteorol. Soc., 125, 529–552, https://doi.org/10.1002/qj.49712555409, 1999. a
Thornton, J., Price, J. D., Burnet, F., and Lac, C.: Contrasting the evolution of radiation fog over a heterogeneous region in southwest France during the SOFOG3D campaign, Q. J. Roy. Meteorol. Soc., 149, 3323–3341, https://doi.org/10.1002/qj.4558, 2023. a, b
Turton, J. D. and Brown, R.: A comparison of a numerical model of radiation fog with detailed observations, Q. J. Roy. Meteorol. Soc., 113, 37–54, https://doi.org/10.1002/qj.49711347504, 1987. a
Vehil, R., Monerris, J., Guedalia, D., and Sarthou, P.: Study of the radiative effects (long-wave and short-wave) within a fog layer, Atmos. Res., 23, 179–194, https://doi.org/10.1016/0169-8095(89)90006-9, 1989. a, b
Vishwakarma, P., Delanoë, J., Jorquera, S., Martinet, P., Burnet, F., Bell, A., and Dupont, J.-C.: Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy, Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, 2023. a, b, c
Wærsted, E. G., Haeffelin, M., Dupont, J.-C., Delanoë, J., and Dubuisson, P.: Radiation in fog: quantification of the impact on fog liquid water based on ground-based remote sensing, Atmos. Chem. Phys., 17, 10811–10835, https://doi.org/10.5194/acp-17-10811-2017, 2017. a, b, c, d, e, f, g, h, i, j, k
Wagh, S., Kulkarni, R., Lonkar, P., Parde, A. N., Dhangar, N. G., Govardhan, G., Sajjan, V., Debnath, S., Gultepe, I., Rajeevan, M., and Ghude, S. D.: Development of visibility equation based on fog microphysical observations and its verification using the WRF model, Model. Earth Syst. Environ., 9, 195–211, https://doi.org/10.1007/s40808-022-01492-6, 2023. a
Westerhuis, S., Fuhrer, O., Cermak, J., and Eugster, W.: Identifying the key challenges for fog and low stratus forecasting in complex terrain, Q. J. Roy. Meteorol. Soc., 146, 3347–3367, https://doi.org/10.1002/qj.3849, 2020. a
Wood, R.: Drizzle in Stratiform Boundary Layer Clouds. Part I: Vertical and Horizontal Structure, J. Atmos. Sci., 62, 3011–3033, https://doi.org/10.1175/JAS3529.1, 2005. a
Wood, R.: Stratocumulus Clouds, Mon. Weather Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012. a
World Meteorological Organization: International Cloud Atlas, no. vol. 1 in International Cloud Atlas, Secretariat of the World Meteorological Organization, https://cloudatlas.wmo.int/docs/ICA_1956-Vol_I_low_res.pdf (last access: 6 June 2025), 1956. a
Yang, L., Liu, J.-W., Ren, Z.-P., Xie, S.-P., Zhang, S.-P., and Gao, S.-H.: Atmospheric Conditions for Advection-Radiation Fog Over the Western Yellow Sea, J. Geophys. Res.-Atmos., 123, 5455–5468, https://doi.org/10.1029/2017JD028088, 2018. a
Zhang, X., Musson-Genon, L., Dupont, E., Milliez, M., and Carissimo, B.: On the Influence of a Simple Microphysics Parametrization on Radiation Fog Modelling: A Case Study During ParisFog, Bound.-Lay. Meteorol., 151, 293–315, https://doi.org/10.1007/s10546-013-9894-y, 2014. a
Short summary
This study documents vertical profiles of liquid water content (LWC) in fogs from in situ measurements collected during the SOFOG3D field campaign in 2019–2020. The analysis of 140 vertical profiles reveals a reverse trend in LWC, maximum values at ground decreasing with height, during stable conditions in optically thin fogs, evolving towards quasi-adiabatic characteristics when fogs become thick. These results offer new perspectives for better constraining fog numerical simulations.
This study documents vertical profiles of liquid water content (LWC) in fogs from in situ...
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