Articles | Volume 14, issue 7
https://doi.org/10.5194/amt-14-4929-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-14-4929-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jul 2021
Research article |
| 14 Jul 2021
| 14 Jul 2021
W-band radar observations for fog forecast improvement: an analysis of model and forward operator errors
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Pauline Martinet
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Olivier Caumont
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Benoît Vié
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Julien Delanoë
Laboratoire Atmosphères, Milieux, Observations Spatiales/UVSQ/CNRS/UPMC, Guyancourt, France
Jean-Charles Dupont
Institut Pierre Simon Laplace (IPSL), École Polytechnique, UVSQ, Université Paris-Saclay, 91128 Palaiseau Cedex, France
Mary Borderies
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
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The COVID-19 outbreak led to lockdowns at national scales in spring 2020. Large cuts in emissions occurred, but the quantitative assessment of their role from observations is hindered by weather and interannual variability. That is why we developed an innovative methodology in order to best characterize the impact of lockdown on atmospheric chemistry. We find that a local decrease in traffic-related pollutants triggered a decrease of secondary aerosols and an increase in ozone.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
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Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
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.
Felipe Toledo, Martial Haeffelin, Eivind Wærsted, and Jean-Charles Dupont
Atmos. Chem. Phys., 21, 13099–13117, https://doi.org/10.5194/acp-21-13099-2021, https://doi.org/10.5194/acp-21-13099-2021, 2021
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The article presents a new conceptual model to describe the temporal evolution of continental fog layers, developed based on 7 years of fog measurements performed at the SIRTA observatory, France. This new paradigm relates the visibility reduction caused by fog to its vertical thickness and liquid water path and provides diagnostic variables that could substantially improve the reliability of fog dissipation nowcasting at a local scale, based on real-time profiling observation.
Marc Mandement and Olivier Caumont
Weather Clim. Dynam., 2, 795–818, https://doi.org/10.5194/wcd-2-795-2021, https://doi.org/10.5194/wcd-2-795-2021, 2021
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On 14–15 October 2018, in the Aude department (France), a heavy-precipitation event produced up to about 300 mm of rain in 11 h. Simulations carried out show that the former Hurricane Leslie, while involved, was not the first supplier of moisture over the entire event. The location of the highest rainfall was primarily driven by the location of a quasi-stationary front and secondarily by the location of precipitation bands downwind of mountains bordering the Mediterranean Sea.
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.
Rebecca D. Kutzner, Juan Cuesta, Pascale Chelin, Jean-Eudes Petit, Mokhtar Ray, Xavier Landsheere, Benoît Tournadre, Jean-Charles Dupont, Amandine Rosso, Frank Hase, Johannes Orphal, and Matthias Beekmann
Atmos. Chem. Phys., 21, 12091–12111, https://doi.org/10.5194/acp-21-12091-2021, https://doi.org/10.5194/acp-21-12091-2021, 2021
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Our work investigates the diurnal evolution of atmospheric ammonia concentrations during a major pollution event. It analyses it in regard of both chemical (gas–particle conversion) and physical (vertical mixing, meteorology) processes in the atmosphere. These mechanisms are key for understanding the evolution of the physicochemical state of the atmosphere; therefore, it clearly fits into the scope of Atmospheric Chemistry and Physics.
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.
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.
Olivier Caumont, Marc Mandement, François Bouttier, Judith Eeckman, Cindy Lebeaupin Brossier, Alexane Lovat, Olivier Nuissier, and Olivier Laurantin
Nat. Hazards Earth Syst. Sci., 21, 1135–1157, https://doi.org/10.5194/nhess-21-1135-2021, https://doi.org/10.5194/nhess-21-1135-2021, 2021
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This study focuses on the heavy precipitation event of 14 and 15 October 2018, which caused deadly flash floods in the Aude basin in south-western France.
The case is studied from a meteorological point of view using various operational numerical weather prediction systems, as well as a unique combination of observations from both standard and personal weather stations. The peculiarities of this case compared to other cases of Mediterranean heavy precipitation events 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.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 21, 463–480, https://doi.org/10.5194/nhess-21-463-2021, https://doi.org/10.5194/nhess-21-463-2021, 2021
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The assimilation impact of four observation data sets on forecasts is studied in a mesoscale weather model. The ground-based Global Navigation Satellite System (GNSS) zenithal total delay data set with information on humidity has the largest impact on analyses and forecasts, representing an evenly spread and frequent data set for each analysis time over the model domain. Moreover, the reprocessing of these data also improves the forecast quality, but this impact is not statistically significant.
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.
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
American Meteorological Society: Fog. Glossary of Meteorology, available at: http://glossary.ametsoc.org/wiki/fog, last access: 5 July 2021. a
Atlas, D.: The estimation of cloud parameters by radar, J. Meteorol.,
11, 309–317, 1954. a
Bauer, P., Moreau, E., Chevallier, F., and O'keeffe, U.: Multiple-scattering
microwave radiative transfer for data assimilation applications, Q.
J. Roy. Meteor. Soc., 132, 1259–1281,
2006. a
Bohren, C. F. and Huffman, D. R.: Absorption and scattering of light by small
particles, WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim, 2008. a
Bouttier, F. and Courtier, P.: Data assimilation concepts and methods. Presented at the Meteorological Training Course Lecture Series, European Centre for Medium-Range Weather Forecasts, Reading, England, 1–58pp., 2002. a
Bulmer, M. G.: Principles of Statistics, Dover Publications, New York, NY, 1979. a
Crewell, S. and Löhnert, U.: Accuracy of cloud liquid water path from
ground-based microwave radiometry 2. Sensor accuracy and synergy, Radio
Sci., 38, 8042, https://doi.org/10.1029/2002RS002634, 2003. a
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, 2000. a
De Angelis, F., Cimini, D., Löhnert, U., Caumont, O., Haefele, A., Pospichal, B., Martinet, P., Navas-Guzmán, F., Klein-Baltink, H., Dupont, J.-C., and Hocking, J.: Long-term observations minus background monitoring of ground-based brightness temperatures from a microwave radiometer network, Atmos. Meas. Tech., 10, 3947–3961, https://doi.org/10.5194/amt-10-3947-2017, 2017. a
Dombrowski-Etchevers, I., Seity, Y., Mestre, O., and Willemet, J.-M.: New
algorithms for two forecasted products of weather: visibilities and 2
precipitation types, to be submitted, 2021. a
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. Meteor. Soc., 146, 2522–2546, https://doi.org/10.1002/qj.3783, 2019. a
Dupont, J., 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,
2016. a
Dupont, J.-C., Haeffelin, M., Protat, A., Bouniol, D., Boyouk, N., and Morille,
Y.: Stratus–fog formation and dissipation: a 6-day case study,
Bound.-Lay. Meteorol., 143, 207–225, 2012. a
Ebell, K., Löhnert, U., Päschke, E., Orlandi, E., Schween, J. H., and
Crewell, S.: A 1-D variational retrieval of temperature, humidity, and liquid
cloud properties: Performance under idealized and real conditions, J.
Geophys. Res.-Atmos., 122, 1746–1766, https://doi.org/10.1002/2016JD025945, 2017. a
Fielding, M. and Janiskova, M.: Direct 4D-Var assimilation of space-borne cloud
radar reflectivity and lidar backscatter. Part I: Observation operator and
implementation, Q. J. Roy. Meteor. Soc., 146, 3877–3899, https://doi.org/10.1002/qj.3878, 2020. a
Fouquart, Y. and Bonnel, B.: Computations of solar heating of the Earth's atmosphere: A
new parameterization, Beiträge zur Physik der Atmosphäre, 53, 35–62, 1980. a
Geoffroy, O., Brenguier, J.-L., and Burnet, F.: Parametric representation of the cloud droplet spectra for LES warm bulk microphysical schemes, Atmos. Chem. Phys., 10, 4835–4848, https://doi.org/10.5194/acp-10-4835-2010, 2010. a, b
Gultepe, I., Tardif, R., Michaelides, S. C., Cermak, J., Bott, A., Bendix, J.,
Müller, M. D., Pagowski, M., Hansen, B., Ellrod, G., and Jacobs, W.: Fog
research: A review of past achievements and future perspectives, Pure
Appl. Geophys., 164, 1121–1159, 2007. a
Haeffelin, M., Barthès, L., Bock, O., Boitel, C., Bony, S., Bouniol, D., Chepfer, H., Chiriaco, M., Cuesta, J., Delanoë, J., Drobinski, P., Dufresne, J.-L., Flamant, C., Grall, M., Hodzic, A., Hourdin, F., Lapouge, F., Lemaître, Y., Mathieu, A., Morille, Y., Naud, C., Noël, V., O'Hirok, W., Pelon, J., Pietras, C., Protat, A., Romand, B., Scialom, G., and Vautard, R.: SIRTA, a ground-based atmospheric observatory for cloud and aerosol research, Ann. Geophys., 23, 253–275, https://doi.org/10.5194/angeo-23-253-2005, 2005. a, b
Haeffelin, M., Laffineur, Q., Bravo-Aranda, J.-A., Drouin, M.-A., Casquero-Vera, J.-A., Dupont, J.-C., and De Backer, H.: Radiation fog formation alerts using attenuated backscatter power from automatic lidars and ceilometers, Atmos. Meas. Tech., 9, 5347–5365, https://doi.org/10.5194/amt-9-5347-2016, 2016. a
Hu, J., Yussouf, N., Turner, D. D., Jones, T. A., and Wang, X.: Impact of
ground-based remote sensing boundary layer observations on short-term
probabilistic forecasts of a tornadic supercell event, Weather
Forecast., 34, 1453–1476, 2019. a
Janisková, M.: Assimilation of cloud information from space-borne radar and
lidar: experimental study using a 1D+ 4D-Var technique, Q. J.
Roy. Meteorol. Soc., 141, 2708–2725, 2015. a
Kollias, P., Clothiaux, E. E., Miller, M., Albrecht, B. A., Stephens, G., and
Ackerman, T.: Millimeter-wavelength radars: New frontier in atmospheric cloud
and precipitation research, B. Am. Meteorol. Soc.,
88, 1608–1624, 2007. a
Lac, C., Chaboureau, J.-P., Masson, V., Pinty, J.-P., Tulet, P., Escobar, J., Leriche, M., Barthe, C., Aouizerats, B., Augros, C., Aumond, P., Auguste, F., Bechtold, P., Berthet, S., Bielli, S., Bosseur, F., Caumont, O., Cohard, J.-M., Colin, J., Couvreux, F., Cuxart, J., Delautier, G., Dauhut, T., Ducrocq, V., Filippi, J.-B., Gazen, D., Geoffroy, O., Gheusi, F., Honnert, R., Lafore, J.-P., Lebeaupin Brossier, C., Libois, Q., Lunet, T., Mari, C., Maric, T., Mascart, P., Mogé, M., Molinié, G., Nuissier, O., Pantillon, F., Peyrillé, P., Pergaud, J., Perraud, E., Pianezze, J., Redelsperger, J.-L., Ricard, D., Richard, E., Riette, S., Rodier, Q., Schoetter, R., Seyfried, L., Stein, J., Suhre, K., Taufour, M., Thouron, O., Turner, S., Verrelle, A., Vié, B., Visentin, F., Vionnet, V., and Wautelet, P.: Overview of the Meso-NH model version 5.4 and its applications, Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, 2018. a
Lafore, J. P., Stein, J., Asencio, N., Bougeault, P., Ducrocq, V., Duron, J., Fischer, C., Héreil, P., Mascart, P., Masson, V., Pinty, J. P., Redelsperger, J. L., Richard, E., and Vilà-Guerau de Arellano, J.: The Meso-NH Atmospheric Simulation System. Part I: adiabatic formulation and control simulations, Ann. Geophys., 16, 90–109, https://doi.org/10.1007/s00585-997-0090-6, 1998. a
Le Bastard, T., Caumont, O., Gaussiat, N., and Karbou, F.: Combined use of volume radar observations and high-resolution numerical weather predictions to estimate precipitation at the ground: methodology and proof of concept, Atmos. Meas. Tech., 12, 5669–5684, https://doi.org/10.5194/amt-12-5669-2019, 2019. a
Li, Y.: Detection, Imaging and Characterisation of FogFields by Radar, PhD
thesis, Delft University of Technology, Delft, the Netherlands, 2015. a
Liebe, H. J.: An updated model for millimeter wave propagation in moist air,
Radio Sci., 20, 1069–1089, 1985. a
Liu, L., Ruan, Z., Zheng, J., and Gao, W.: Comparing and merging observation
data from Ka-band cloud radar, C-band frequency-modulated continuous wave
radar and ceilometer systems, Remote Sensing, 9, 1282, https://doi.org/10.3390/rs9121282, 2017. a
Liu, Y. and Daum, P. H.: Spectral dispersion of cloud droplet size
distributions and the parameterization of cloud droplet effective radius,
Geophys. Res. Lett., 27, 1903–1906, 2000. a
Maahn, M., Turner, D. D., Löhnert, U., Posselt, D. J., Ebell, K., Mace, G. G., and Comstock, J. M.: Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know, B. Am. Meteorol. Soc., 101, E1512–E1523, https://doi.org/10.1175/BAMS-D-19-0027.1, 2020. a
Maier, F., Bendix, J., and Thies, B.: Simulating Z–LWC relations in natural
fogs with radiative transfer calculations for future application to a cloud
radar profiler, Pure Appl. Geophys., 169, 793–807, 2012. a
Martinet, P., Dabas, A., Donier, J.-M., Douffet, T., Garrouste, O., and
Guillot, R.: 1D-Var temperature retrievals from microwave radiometer and
convective scale model, Tellus A, 67,
27925, https://doi.org/10.3402/tellusa.v67.27925, 2015. a, b
Martinet, P., Cimini, D., De Angelis, F., Canut, G., Unger, V., Guillot, R., Tzanos, D., and Paci, A.: Combining ground-based microwave radiometer and the AROME convective scale model through 1DVAR retrievals in complex terrain: an Alpine valley case study, Atmos. Meas. Tech., 10, 3385–3402, https://doi.org/10.5194/amt-10-3385-2017, 2017. a
Martinet, P., Cimini, D., Burnet, F., Ménétrier, B., Michel, Y., and Unger, V.: Improvement of numerical weather prediction model analysis during fog conditions through the assimilation of ground-based microwave radiometer observations: a 1D-Var study, Atmos. Meas. Tech., 13, 6593–6611, https://doi.org/10.5194/amt-13-6593-2020, 2020. a
Martucci, G., Milroy, C., and O'Dowd, C. D.: Detection of cloud-base height
using Jenoptik CHM15K and Vaisala CL31 ceilometers, J. Atmo.
Ocean. Tech., 27, 305–318, 2010. a
Masson, V.: A physically-based scheme for the urban energy budget in
atmospheric models, Bound.-Lay. Meteorol., 94, 357–397, 2000. a
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. a
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
Météo France: Homepage, available at: https://donneespubliques.meteofrance.fr/, last access: 2021. a
Miles, N. L., Verlinde, J., and Clothiaux, E. E.: Cloud droplet size
distributions in low-level stratiform clouds, J. Atmos.
Sci., 57, 295–311, 2000. a
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.-Atmos., 102, 16663–16682, 1997. a
Müller, M., 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
NRC: Observing weather and climate from the ground up: A nationwide network of
networks, National Academies Press, Washington D. C., 2009. a
Podzimek, J.: Droplet concentration and size distribution in haze and fog,
Stud. Geophys. Geod., 41, 277–296, 1997. a
Román-Cascón, C., Yagüe, C., Steeneveld, G.-J., Morales, G.,
Arrillaga, J. A., Sastre, M., and Maqueda, G.: Radiation and cloud-base
lowering fog events: Observational analysis and evaluation of WRF and
HARMONIE, Atmos. Res., 229, 190–207, 2019. a
Rose, T., Crewell, S., Löhnert, U., and Simmer, C.: A network suitable
microwave radiometer for operational monitoring of the cloudy atmosphere,
Atmos. Res., 75, 183–200, 2005. a
Schaefer, J. T.: The critical success index as an indicator of warning skill,
Weather Forecast., 5, 570–575, 1990. a
Seifert, A. and Beheng, K. D.: A double-moment parameterization for simulating
autoconversion, accretion and selfcollection, Atmos. Res., 59,
265–281, 2001. a
Site Instrumental de Recherche par Télédétection Atmosphérique: Homepage, available at: http://sirta.ipsl.fr/, last access: 2021. a
Steeneveld, G., Ronda, R., and Holtslag, A.: The challenge of forecasting the
onset and development of radiation fog using mesoscale atmospheric models,
Bound.-Lay. Meteorol., 154, 265–289, 2015. a
Tardif, R. and Rasmussen, R. M.: Event-based climatology and typology of fog in
the New York City region, J. Appl. Meteorol. Clim., 46,
1141–1168, 2007. a
Thies, B., Müller, K., Maier, F., and Bendix, J.: Fog monitoring using a
new 94 GHz FMCW cloud radar, in: 5th International Conference on Fog, Fog
Collection and Dew, Münster, Germany, 25–30 July 2010, available at: https://meetingorganizer.copernicus.org/FOGDEW2010/FOGDEW2010-103.pdf (last access: 8 June 2021), FOGDEW2010-103, 2010.
a
Toledo, F., Delanoë, J., Haeffelin, M., Dupont, J.-C., Jorquera, S., and Le Gac, C.: Absolute calibration method for frequency-modulated continuous wave (FMCW) cloud radars based on corner reflectors, Atmos. Meas. Tech., 13, 6853–6875, https://doi.org/10.5194/amt-13-6853-2020, 2020. a
Vié, B., Pinty, J.-P., Berthet, S., and Leriche, M.: LIMA (v1.0): A quasi two-moment microphysical scheme driven by a multimodal population of cloud condensation and ice freezing nuclei, Geosci. Model Dev., 9, 567–586, https://doi.org/10.5194/gmd-9-567-2016, 2016. a
Wærsted, E.: Description of physical processes driving the life cycle of
radiation fog and fog – stratus transitions based on conceptual models, PhD
thesis, Paris Saclay, Paris, 2018. a
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
Wilczak, J., Finley, C., Freedman, J., Cline, J., Bianco, L., Olson, J.,
Djalalova, I., Sheridan, L., Ahlstrom, M., Manobianco, J., and Zack, J.: The Wind
Forecast Improvement Project (WFIP): A public–private partnership addressing
wind energy forecast needs, B. Am. Meteorol. Soc.,
96, 1699–1718, 2015. a
Wriedt, T.: Mie theory: a review, in: The Mie Theory, Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-28738-1_2, pp. 53–71,
2012. a
Yuter, S. E. and Houze, Jr., R. A.: Three-dimensional kinematic and
microphysical evolution of Florida cumulonimbus. Part II: Frequency
distributions of vertical velocity, reflectivity, and differential
reflectivity, Mon. Weather Rev., 123, 1941–1963, 1995. a
Zhao, C., Zhao, L., and Dong, X.: A case study of stratus cloud properties
using in situ aircraft observations over Huanghua, China, Atmosphere, 10, 19, https://doi.org/10.3390/atmos10010019,
2019. a
Short summary
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.
This paper presents work towards making retrievals on the liquid water content in fog and low...
