Articles | Volume 15, issue 18
https://doi.org/10.5194/amt-15-5415-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-5415-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Sep 2022
Research article |
| 26 Sep 2022
| 26 Sep 2022
An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties
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
Direction des opérations pour la prévision, Météo-France, Toulouse, France
Frédéric Burnet
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Julien Delanoë
Laboratoire Atmosphères, Milieux, Observations Spatiales/UVSQ/CNRS/UPMC, Guyancourt, France
Susana Jorquera
Laboratoire Atmosphères, Milieux, Observations Spatiales/UVSQ/CNRS/UPMC, Guyancourt, France
Yann Seity
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Vinciane Unger
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Related authors
Alistair Bell, Axel Murk, and Gunter Stober
EGUsphere, https://doi.org/10.5194/egusphere-2025-1396, https://doi.org/10.5194/egusphere-2025-1396, 2025
Short summary
Short summary
Increases in middle atmospheric water vapour from the 2022 Hunga eruption have been measured worldwide. This study uses remote sensing measurements at two latitudes and accurate radiative transfer modeling to show significant long-wave heating effects. Though minimal at the surface, the water vapour enhancement can alter middle-atmospheric dynamics, potentially affecting ozone chemistry and weather patterns.
Alistair Bell, Eric Sauvageat, Gunter Stober, Klemens Hocke, and Axel Murk
Atmos. Meas. Tech., 18, 555–567, https://doi.org/10.5194/amt-18-555-2025, https://doi.org/10.5194/amt-18-555-2025, 2025
Short summary
Short summary
Hardware and software developments have been made on a 22 GHz microwave radiometer for the measurement of middle-atmospheric water vapour near Bern, Switzerland. Previous measurements dating back to 2010 have been re-calibrated and an improved optimal estimation retrieval performed on these measurements, giving a 13-year dataset. Measurements made with new and improved instrumental hardware are used to correct previous measurements, which show better agreement than the non-corrected dataset.
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
Short summary
Short summary
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, 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
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Théophane Costabloz, Frédéric Burnet, Christine Lac, Pauline Martinet, Julien Delanoë, Susana Jorquera, and Maroua Fathalli
Atmos. Chem. Phys., 25, 6539–6573, https://doi.org/10.5194/acp-25-6539-2025, https://doi.org/10.5194/acp-25-6539-2025, 2025
Short summary
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.
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
Short summary
Short summary
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.
Alistair Bell, Axel Murk, and Gunter Stober
EGUsphere, https://doi.org/10.5194/egusphere-2025-1396, https://doi.org/10.5194/egusphere-2025-1396, 2025
Short summary
Short summary
Increases in middle atmospheric water vapour from the 2022 Hunga eruption have been measured worldwide. This study uses remote sensing measurements at two latitudes and accurate radiative transfer modeling to show significant long-wave heating effects. Though minimal at the surface, the water vapour enhancement can alter middle-atmospheric dynamics, potentially affecting ozone chemistry and weather patterns.
Danaé Préaux, Ingrid Dombrowski-Etchevers, Isabelle Gouttevin, and Yann Seity
EGUsphere, https://doi.org/10.5194/egusphere-2025-708, https://doi.org/10.5194/egusphere-2025-708, 2025
Short summary
Short summary
Structural inhomogeneities of the valleys and mountains observational network contribute to the misrepresentation of near-surface air temperature and should be considered both when evaluating the model performances and in assimilation.
Alistair Bell, Eric Sauvageat, Gunter Stober, Klemens Hocke, and Axel Murk
Atmos. Meas. Tech., 18, 555–567, https://doi.org/10.5194/amt-18-555-2025, https://doi.org/10.5194/amt-18-555-2025, 2025
Short summary
Short summary
Hardware and software developments have been made on a 22 GHz microwave radiometer for the measurement of middle-atmospheric water vapour near Bern, Switzerland. Previous measurements dating back to 2010 have been re-calibrated and an improved optimal estimation retrieval performed on these measurements, giving a 13-year dataset. Measurements made with new and improved instrumental hardware are used to correct previous measurements, which show better agreement than the non-corrected dataset.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 25, 429–449, https://doi.org/10.5194/nhess-25-429-2025, https://doi.org/10.5194/nhess-25-429-2025, 2025
Short summary
Short summary
The use of numerical weather prediction models enables the forecasting of hazardous weather situations. The incorporation of new temperature and relative humidity observations from personal weather stations into the French limited-area model is evaluated in this study. This leads to the improvement of the associated near-surface variables of the model during the first hours of the forecast. Examples are provided for a sea breeze case during a heatwave and a fog episode.
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
Short summary
Short summary
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.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloé David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
Atmos. Meas. Tech., 17, 6707–6734, https://doi.org/10.5194/amt-17-6707-2024, https://doi.org/10.5194/amt-17-6707-2024, 2024
Short summary
Short summary
This study demonstrates the potential of enhancing severe-hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe-hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, https://doi.org/10.5194/nhess-24-907-2024, 2024
Short summary
Short summary
Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Felix Erdmann, Olivier Caumont, and Eric Defer
Nat. Hazards Earth Syst. Sci., 23, 2821–2840, https://doi.org/10.5194/nhess-23-2821-2023, https://doi.org/10.5194/nhess-23-2821-2023, 2023
Short summary
Short summary
This work develops a novel lightning data assimilation (LDA) technique to make use of Meteosat Third Generation (MTG) Lightning Imager (LI) data in a regional, convection-permitting numerical weather prediction model. The approach combines statistical Bayesian and 3-dimensional variational methods. Our LDA can promote missing convection and suppress spurious convection in the initial state of the model, and it has similar skill to the operational radar data assimilation for rainfall forecasts.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Pauline Combarnous, Felix Erdmann, Olivier Caumont, Éric Defer, and Maud Martet
Nat. Hazards Earth Syst. Sci., 22, 2943–2962, https://doi.org/10.5194/nhess-22-2943-2022, https://doi.org/10.5194/nhess-22-2943-2022, 2022
Short summary
Short summary
The objective of this study is to prepare the assimilation of satellite lightning data in the French regional numerical weather prediction system. The assimilation of lightning data requires an observation operator, based on empirical relationships between the lightning observations and a set of proxies derived from the numerical weather prediction system variables. We fit machine learning regression models to our data to yield those relationships and to investigate the best proxy for lightning.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. II: Modelling the forecast error covariance statistics, Q. J. Roy. Meteor. Soc., 134, 1971–1996, 2008. a
Bauer, P., Lopez, P., Benedetti, A., Salmond, D., and Moreau, E.:
Implementation of 1D + 4D-Var assimilation of precipitation-affected microwave radiances at ECMWF. I: 1D-Var, Q. J. Roy. Meteorol. Soc., 132, 2277–2306, 2006. a
Bell, A., Martinet, P., Caumont, O., Vié, B., Delanoë, J., Dupont, J.-C., and Borderies, M.: W-band radar observations for fog forecast improvement: an analysis of model and forward operator errors, Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, 2021. a, b, c, d, e, f, g, h, i
Borderies, M., Caumont, O., Augros, C., Bresson, É., Delanoë, J.,
Ducrocq, V., Fourrié, N., Bastard, T. L., and Nuret, M.: Simulation of
W-band radar reflectivity for model validation and data assimilation, Q. J. Roy. Meteorol. Soc., 144, 391–403, 2018. a
Brousseau, P., Berre, L., Bouttier, F., and Desroziers, G.: Background-error
covariances for a convective-scale data-assimilation system: AROME–France
3D-Var, Q. J. Royal Meteorol. Soc., 137, 409–422, 2011. a
Burnet, F.: SOFOG3D_CHARBONNIERE_CNRM_VISI-TEMPS-PRESENT-3M-15SEC_L1, Aeris [data set], https://doi.org/10.25326/110, 2020a. a
Burnet, F.: SOFOG3D_CHARBONNIERE_CNRM_Vaisala-RS_L2, Aeris [data set], https://doi.org/10.25326/106, 2020b. a
Burnet, F.: SOFOG3D_NOAILLAN_CNRM_CEILOMETER-CL31-30SEC_L1, Aeris [data set], https://doi.org/10.25326/240, 2021. 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
Che, Y., Ma, S., Xing, F., Li, S., and Dai, Y.: Research on Retrieval of Atmospheric Temperature and Humidity Profiles from combined Ground-based Microwave Radiometer and Cloud Radar Observations, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2016-286, 2016. a
Cimini, D., Westwater, E. R., and Gasiewski, A. J.: Temperature and humidity
profiling in the Arctic using ground-based millimeter-wave radiometry and
1DVAR, IEEE T. Geosci. Remote, 48, 1381–1388, 2009. a
Cimini, D., Rosenkranz, P. W., Tretyakov, M. Y., Koshelev, M. A., and Romano, F.: Uncertainty of atmospheric microwave absorption model: impact on ground-based radiometer simulations and retrievals, Atmos. Chem. Phys., 18, 15231–15259, https://doi.org/10.5194/acp-18-15231-2018, 2018. a
Cimini, D., Hocking, J., De Angelis, F., Cersosimo, A., Di Paola, F., Gallucci, D., Gentile, S., Geraldi, E., Larosa, S., Nilo, S., Romano, F., Ricciardelli, E., Ripepi, E., Viggiano, M., Luini, L., Riva, C., Marzano, F. S., Martinet, P., Song, Y. Y., Ahn, M. H., and Rosenkranz, P. W.: RTTOV-gb v1.0 – updates on sensors, absorption models, uncertainty, and availability, Geosci. Model Dev., 12, 1833–1845, https://doi.org/10.5194/gmd-12-1833-2019, 2019. a
Courtier, P., Andersson, E., Heckley, W., Vasiljevic, D., Hamrud, M.,
Hollingsworth, A., Rabier, F., Fisher, M., and Pailleux, J.: The ECMWF
implementation of three-dimensional variational assimilation (3D-Var). I: Formulation, Q. J. Roy. Meteorol. Soc., 124, 1783–1807, 1998. a
Crewell, S., Ebell, K., Löhnert, U., and Turner, D.: Can liquid water
profiles be retrieved from passive microwave zenith observations?, Geophys. Res. Lett., 36, 1–5, https://doi.org/10.1029/2008GL036934, 2009. a
De Angelis, F., Cimini, D., Hocking, J., Martinet, P., and Kneifel, S.: RTTOV-gb – adapting the fast radiative transfer model RTTOV for the assimilation of ground-based microwave radiometer observations, Geosci. Model Dev., 9, 2721–2739, https://doi.org/10.5194/gmd-9-2721-2016, 2016. a, b, c
Delanoë, J.: SOFOG3D_BASTA-CHAMP_LATMOS_BASTA-vertical_L2a, Aeris [data set], https://doi.org/10.25326/133, 2020. a
Delanoë, J. and Jorquera, S.: L2 BASTA Processing, https://owncloud.latmos.ipsl.fr/index.php/s/N7O3hkfPUMaTTeB (last access: 8 September 2022), 2021. a
Derber, J. and Bouttier, F.: A reformulation of the background error covariance in the ECMWF global data assimilation system, Tellus A, 51, 195–221, 1999. a
Descombes, G., Auligné, T., Vandenberghe, F., Barker, D. M., and Barré, J.: Generalized background error covariance matrix model (GEN_BE v2.0), Geosci. Model Dev., 8, 669–696, https://doi.org/10.5194/gmd-8-669-2015, 2015. a
Ebell, K., Löhnert, U., Crewell, S., and Turner, D. D.: On characterizing
the error in a remotely sensed liquid water content profile, Atmos. Res., 98, 57–68, 2010. a
Faber, S., French, J. R., and Jackson, R.: Laboratory and in-flight evaluation of measurement uncertainties from a commercial Cloud Droplet Probe (CDP), Atmos. Meas. Tech., 11, 3645–3659, https://doi.org/10.5194/amt-11-3645-2018, 2018. a
Fisher, M.: Background error covariance modelling, in: Seminar on Recent
Development in Data Assimilation for Atmosphere and Ocean, 8–12 September 2003, Shinfield Park, Reading, 45–63, https://www.ecmwf.int/sites/default/files/elibrary/2003/9404-background-error-covariance-modelling.pdf (last access: 8 September 2022), 2003. a, b
Fox, N. I. and Illingworth, A. J.: The retrieval of stratocumulus cloud
properties by ground-based cloud radar, J. Appl. Meteorol., 36, 485–492, 1997. a
Gultepe, I., Tardif, R., Michaelides, S., 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, 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
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R.,
Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant,
T. E.: Array programming with NumPy, Nature, 585, 357–362,
https://doi.org/10.1038/s41586-020-2649-2, 2020. 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
Jorquera, S. and Delanoë, J.: SOFOG-3D: Overview of the Radar Data,
https://www.umr-cnrm.fr/IMG/pdf/latmos_sofog3d-15052020.pdf (last access: 8 September 2022), 2020. a
Löhnert, U. and Maier, O.: Operational profiling of temperature using ground-based microwave radiometry at Payerne: prospects and challenges, Atmos. Meas. Tech., 5, 1121–1134, https://doi.org/10.5194/amt-5-1121-2012, 2012. a
Löhnert, U., van Meijgaard, E., Baltink, H. K., Groß, S., and Boers,
R.: Accuracy assessment of an integrated profiling technique for operationally deriving profiles of temperature, humidity, and cloud liquid
water, J. Geophys. Res.-Atmos., 112, 1–17, https://doi.org/10.1029/2006JD007379, 2007. a
Löhnert, U., Crewell, S., Krasnov, O., O'Connor, E., and Russchenberg,
H.: Advances in continuously profiling the thermodynamic state of the
boundary layer: Integration of measurements and methods, J. Atmos. Ocean. Tech., 25, 1251–1266, 2008. a
Martinet, P.: SOFOG3D_CHARBONNIERE_CNRM_MWR-HATPRO-TB_L1, Aeris [data set], https://doi.org/10.25326/148, 2021. a
Martinet, P., Fourrié, N., Guidard, V., Rabier, F., Montmerle, T., and
Brunel, P.: Towards the use of microphysical variables for the assimilation
of cloud-affected infrared radiances, Q. J. Roy. Meteorol. Soc., 139, 1402–1416, 2013. 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
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, b
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, b, c, d, e, f, g, h
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 new database of temperature, humidity and liquid water path retrievals from a fog dedicated network of ground-based microwave radiometers, B. Atmos. Sci. Tech., in press, 2022. a
Maschwitz, G., Löhnert, U., Crewell, S., Rose, T., and Turner, D. D.: Investigation of ground-based microwave radiometer calibration techniques at 530 hPa, Atmos. Meas. Tech., 6, 2641–2658, https://doi.org/10.5194/amt-6-2641-2013, 2013. a
Matrosov, S., Uttal, T., Snider, J., and Kropfli, R.: Estimation of ice cloud
parameters from ground-based infrared radiometer and radar measurements, J. Geophys. Res.-Atmos., 97, 11567–11574, 1992. 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
McCartney, E. J.: Optics of the atmosphere: scattering by molecules and
particles, Wiley, Hoboken, NJ, USA, ISBN-13: 9780471015260, 1976. a
Ménétrier, B. and Montmerle, T.: Heterogeneous background-error
covariances for the analysis and forecast of fog events, Q. J. Roy. Meteorol. Soc., 137, 2004–2013, 2011. a
Morss, R. and Emanuel, K.: Influence of added observations on analysis and
forecast errors: Results from idealized systems, Q. J. Roy. Meteorol. Soc., 128, 285–321, 2002. a
Pavelin E. G. and Collard A.: NWP SAF Met Office 1D-Var User Manual, NWPSAF-MO-UD-006, 2009. a
Philip, A., Bergot, T., Bouteloup, Y., and Bouyssel, F.: The impact of vertical resolution on fog forecasting in the kilometric-scale model arome: a case study and statistics, Weather Forecast., 31, 1655–1671, 2016. a
Pospichal, B., Kilian, P., and Seifert, P.: Performance of cloud liquid water
retrievals from ground-based remote sensing observations over Leipzig, in:
Proceedings of the 9th International Symposium on Tropospheric Profiling (ISTP), L'Aquila, Italy , 5 September 2012,
http://meteorema.aquila.infn.it/istp/proceedings/Session_C_Aerosols_clouds_and_precipitation/Session_C_Wednesday_5_September_2012/SC_04_Pospichal.pdf (last access: 8 September 2022), 2012. a
Russchenberg, H., Crewell, S., Loehnert, U., Quante, M., Meywerk, J., Baltink, H. K., and Krasnov, O.: Radar observations of stratocumulus compared with in situ aircraft data and simulations, in: Proc. ERAD, Visby, Island of Gotland, Sweden, 6–10 September 2004, 296–300, 2004. a
Saunders, R., Hocking, J., Turner, E., Rayer, P., Rundle, D., Brunel, P., Vidot, J., Roquet, P., Matricardi, M., Geer, A., Bormann, N., and Lupu, C.: An update on the RTTOV fast radiative transfer model (currently at version 12), Geosci. Model Dev., 11, 2717–2737, https://doi.org/10.5194/gmd-11-2717-2018, 2018. 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
Thomas, G., Mahfouf, J.-F., and Montmerle, T.: Toward a variational assimilation of polarimetric radar observations in a convective-scale numerical weather prediction (NWP) model, Atmos. Meas. Tech., 13, 2279–2298, https://doi.org/10.5194/amt-13-2279-2020, 2020. a, b
Tinel, C., Testud, J., Pelon, J., Hogan, R. J., Protat, A., Delanoë, J.,
and Bouniol, D.: The retrieval of ice-cloud properties from cloud radar and
lidar synergy, J. Appl. Meteorol., 44, 860–875, 2005. 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, b, c
Toledo, F., Haeffelin, M., Wærsted, E., and Dupont, J.-C.: A new conceptual model for adiabatic fog, Atmos. Chem. Phys., 21, 13099–13117, https://doi.org/10.5194/acp-21-13099-2021, 2021. a
Turner, D. D. and Löhnert, U.: Ground-based temperature and humidity profiling: combining active and passive remote sensors, Atmos. Meas. Tech., 14, 3033–3048, https://doi.org/10.5194/amt-14-3033-2021, 2021. a, b
Wattrelot, E., Caumont, O., and Mahfouf, J.-F.: Operational implementation of
the 1D + 3D-Var assimilation method of radar reflectivity data in the AROME
model, Mon. Weather Rev., 142, 1852–1873, 2014. a
Wendisch, M., Keil, A., and Korolev, A.: FSSP characterization with
monodisperse water droplets, J. Atmos. Ocean. Tech., 13, 1152–1165, 1996. a
Short summary
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.
Cloud radars and microwave radiometers offer the potential to improve fog forecasts when...
