Articles | Volume 13, issue 1
https://doi.org/10.5194/acp-13-269-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-13-269-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Jan 2013
Research article |
| 11 Jan 2013
Assimilation of ground versus lidar observations for PM10 forecasting
Y. Wang
LSCE, joint laboratory CEA-CNRS, UMR8212, 91191 Gif-sur-Yvette, France
CEREA, joint laboratory Ecole des Ponts ParisTech - EDF R&D, Université Paris-Est, 77455 Champs sur Marne, France
K. N. Sartelet
CEREA, joint laboratory Ecole des Ponts ParisTech - EDF R&D, Université Paris-Est, 77455 Champs sur Marne, France
M. Bocquet
INRIA, Paris-Rocquencourt Research Center, Le Chesnay, France
CEREA, joint laboratory Ecole des Ponts ParisTech - EDF R&D, Université Paris-Est, 77455 Champs sur Marne, France
P. Chazette
LSCE, joint laboratory CEA-CNRS, UMR8212, 91191 Gif-sur-Yvette, France
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Atmos. Meas. Tech., 19, 5223–5242, https://doi.org/10.5194/amt-19-5223-2026, https://doi.org/10.5194/amt-19-5223-2026, 2026
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Between October 2022 and January 2023, the Water Vapour Lidar Network Assimilation (WaLiNeAs) campaign was conducted on the western Mediterranean by four European countries. To improve the forecasting of heavy precipitation events, eight ground-based stations equipped with water vapour Raman lidars were strategically deployed. They offered a valuable chance to verify the consistency of the water vapour products of both the Infrared Atmospheric Sounding Interferometer (IASI) and ERA5 reanalysis.
Marc Bocquet, Tobias Sebastian Finn, Sibo Cheng, and Alban Farchi
Nonlin. Processes Geophys., 33, 401–424, https://doi.org/10.5194/npg-33-401-2026, https://doi.org/10.5194/npg-33-401-2026, 2026
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Dominique Gantois, Alexandre Baron, Michaël Sicard, Valentin Duflot, Niels Groenen, Nelson Bègue, Sabine Eckhardt, Nikolaos Evangeliou, Martine De Mazière, Corinne Vigouroux, Guillaume Payen, Nicolas Marquestaut, Jean-Marc Metzger, Patrick Chazette, and Cyrille Flamant
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Aurélien Le Bayon, Aliisa Ojala, Siddharth Iyer, Zhizhao Wang, Victor Lannuque, Florian Couvidat, Raluca Ciuraru, and Karine Sartelet
EGUsphere, https://doi.org/10.5194/egusphere-2026-3391, https://doi.org/10.5194/egusphere-2026-3391, 2026
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Patrick Chazette
Atmos. Meas. Tech., 19, 4293–4311, https://doi.org/10.5194/amt-19-4293-2026, https://doi.org/10.5194/amt-19-4293-2026, 2026
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Wenbo Yu, Anirbit Ghosh, Tobias Sebastian Finn, Rossella Arcucci, Marc Bocquet, and Sibo Cheng
Geosci. Model Dev., 19, 1027–1054, https://doi.org/10.5194/gmd-19-1027-2026, https://doi.org/10.5194/gmd-19-1027-2026, 2026
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Karine Sartelet, Zhizhao Wang, Youngseob Kim, Victor Lannuque, and Florian Couvidat
Geosci. Model Dev., 19, 389–421, https://doi.org/10.5194/gmd-19-389-2026, https://doi.org/10.5194/gmd-19-389-2026, 2026
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The model simulates the evolution of primary and secondary pollutants via gas-phase chemistry, aerosol dynamics (including ultrafine particles), and intra-particle reactions. It uses a sectional approach for size and composition, includes a wall-loss module, and links gas-phase mechanisms of different complexity to secondary organic aerosol formation. Representation of particle phase composition allows viscosity and non-ideality to be taken into account.
Frédéric Laly, Patrick Chazette, Julien Totems, Vincent Crenn, David Ledur, and Alexandre Marpillat
Atmos. Meas. Tech., 18, 7629–7649, https://doi.org/10.5194/amt-18-7629-2025, https://doi.org/10.5194/amt-18-7629-2025, 2025
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This article presents the evolution of aerosol optical properties as derived from a Raman lidar in relation to relative humidity over the Paris area. It examines the influence of aerosol chemical compounds linked to air mass origins, as well as their relationship with the efficiency of aerosol growth. Such a study provides a better understanding of the interactions between aerosols and water vapour, which is important for reducing the uncertainties surrounding the Earth's radiative balance.
Sandrine Bony, Basile Poujol, Brett McKim, Nicolas Rochetin, Marie Lothon, Julia Windmiller, Nicolas Maury, Clarisse Dufaux, Louis Jaffeux, Patrick Chazette, and Julien Delanoë
Atmos. Chem. Phys., 25, 17331–17362, https://doi.org/10.5194/acp-25-17331-2025, https://doi.org/10.5194/acp-25-17331-2025, 2025
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Space photographs of the Earth show that clouds form diverse, common but poorly understood cloud patterns. The analysis of observations gathered from research aircraft over the tropical ocean shows that the merging of thermals and clouds in the first kilometer of the atmosphere plays a key role in controlling the size, depth and spacing of clouds. This reveals a fundamental process through which clouds interact with each other and with their environment.
Daphné Ladet, Yelva Roustan, Karine Sartelet, and Olivier Duclaux
EGUsphere, https://doi.org/10.5194/egusphere-2025-4472, https://doi.org/10.5194/egusphere-2025-4472, 2025
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Amines used as solvents for CO2 capture can lead to the formation of secondary pollutants once they enter the atmosphere. We studied the degradation of 2-amino-2-methyl-1-propanol to understand the processes that can lead to the formation of secondary particles. Relying on an atmospheric chamber experiment, we developed a model with low-volatility compounds and reproduce the results with nucleation and condensation processes.
Charlotte Durand, Tobias Sebastian Finn, Alban Farchi, Marc Bocquet, Julien Brajard, and Laurent Bertino
The Cryosphere, 19, 5613–5637, https://doi.org/10.5194/tc-19-5613-2025, https://doi.org/10.5194/tc-19-5613-2025, 2025
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This paper presents a four-dimensional variational data assimilation system based on a neural network emulator for sea-ice thickness, learned from neXtSIM (neXt generation Sea Ice Model) simulation outputs. Testing with simulated and real observation retrievals, the system improves forecasts and bias error, performing comparably to operational methods, demonstrating the promise of sea-ice data-driven data assimilation systems.
Daniele Zannoni, Hans Christian Steen-Larsen, Harald Sodemann, Iris Thurnherr, Cyrille Flamant, Patrick Chazette, Julien Totems, Martin Werner, and Myriam Raybaut
Atmos. Chem. Phys., 25, 9471–9495, https://doi.org/10.5194/acp-25-9471-2025, https://doi.org/10.5194/acp-25-9471-2025, 2025
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High-resolution airborne observations reveal that mixing between the free troposphere and surface evapotranspiration flux primarily modulates the water vapor isotopic composition in the lower troposphere. Water vapor isotope structure variations occur on the scale of hundreds of meters, underlining the utility of stable isotopes for studying microscale atmospheric dynamics. This study also provides the basis for better validation of water vapor isotope remote sensing retrievals with surface observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Patrick Chazette, Julien Totems, and Frédéric Laly
Atmos. Meas. Tech., 18, 2681–2699, https://doi.org/10.5194/amt-18-2681-2025, https://doi.org/10.5194/amt-18-2681-2025, 2025
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The use of active remote sensing instruments to sample the atmospheric environment requires accurate calibration that is stable over time so that measurements are reproducible. This is the case for measurements of atmospheric water vapour using Raman lidar, which are of growing interest in the context of climate risks such as extreme precipitation. This study addresses this issue. It is based on six campaigns spread over a period of 7 years between 2016 and 2022.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Soo-Jin Park, Lya Lugon, Oscar Jacquot, Youngseob Kim, Alexia Baudic, Barbara D'Anna, Ludovico Di Antonio, Claudia Di Biagio, Fabrice Dugay, Olivier Favez, Véronique Ghersi, Aline Gratien, Julien Kammer, Jean-Eudes Petit, Olivier Sanchez, Myrto Valari, Jérémy Vigneron, and Karine Sartelet
Atmos. Chem. Phys., 25, 3363–3387, https://doi.org/10.5194/acp-25-3363-2025, https://doi.org/10.5194/acp-25-3363-2025, 2025
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To accurately represent the population exposure to outdoor concentrations of pollutants of interest to health (NO2, PM2.5, black carbon, and ultrafine particles), multi-scale modelling down to the street scale is set up and evaluated using measurements from field campaigns. An exposure scaling factor is defined, allowing regional-scale simulations to be corrected to evaluate population exposure. Urban heterogeneities strongly influence NO2, black carbon, and ultrafine particles but less strongly PM2.5.
Alexis Squarcioni, Yelva Roustan, Myrto Valari, Youngseob Kim, Karine Sartelet, Lya Lugon, Fabrice Dugay, and Robin Voitot
Atmos. Chem. Phys., 25, 93–117, https://doi.org/10.5194/acp-25-93-2025, https://doi.org/10.5194/acp-25-93-2025, 2025
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This study highlights the interest of using a street-network model to estimate pollutant concentrations of NOx, NO2, and PM2.5 in heterogeneous urban areas, particularly those adjacent to highways, compared with the subgrid-scale approach embedded in the 3D Eulerian model CHIMERE. However, the study also reveals comparable performances between the two approaches for the aforementioned pollutants in areas near the city center, where urban characteristics are more uniform.
Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant
Earth Syst. Sci. Data, 16, 5579–5602, https://doi.org/10.5194/essd-16-5579-2024, https://doi.org/10.5194/essd-16-5579-2024, 2024
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We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
Simon Driscoll, Alberto Carrassi, Julien Brajard, Laurent Bertino, Einar Ólason, Marc Bocquet, and Amos Lawless
EGUsphere, https://doi.org/10.5194/egusphere-2024-2476, https://doi.org/10.5194/egusphere-2024-2476, 2024
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The formation and evolution of sea ice melt ponds (ponds of melted water) are complex, insufficiently understood and represented in models with considerable uncertainty. These uncertain representations are not traditionally included in climate models potentially causing the known underestimation of sea ice loss in climate models. Our work creates the first observationally based machine learning model of melt ponds that is also a ready and viable candidate to be included in climate models.
Tobias Sebastian Finn, Lucas Disson, Alban Farchi, Marc Bocquet, and Charlotte Durand
Nonlin. Processes Geophys., 31, 409–431, https://doi.org/10.5194/npg-31-409-2024, https://doi.org/10.5194/npg-31-409-2024, 2024
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We train neural networks as denoising diffusion models for state generation in the Lorenz 1963 system and demonstrate that they learn an internal representation of the system. We make use of this learned representation and the pre-trained model in two downstream tasks: surrogate modelling and ensemble generation. For both tasks, the diffusion model can outperform other more common approaches. Thus, we see a potential of representation learning with diffusion models for dynamical systems.
Victor Lannuque and Karine Sartelet
Atmos. Chem. Phys., 24, 8589–8606, https://doi.org/10.5194/acp-24-8589-2024, https://doi.org/10.5194/acp-24-8589-2024, 2024
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Large uncertainties remain in understanding secondary organic aerosol (SOA) formation and speciation from naphthalene oxidation. This study details the development of the first near-explicit chemical scheme for naphthalene oxidation by OH, which includes kinetic and mechanistic data, and is able to reproduce most of the experimentally identified products in both gas and particle phases.
Maëlie Chazette, Patrick Chazette, Ilja M. Reiter, Xiaoxia Shang, Julien Totems, Jean-Philippe Orts, Irène Xueref-Remy, and Nicolas Montes
Biogeosciences, 21, 3289–3303, https://doi.org/10.5194/bg-21-3289-2024, https://doi.org/10.5194/bg-21-3289-2024, 2024
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The approach presented is original in its coupling between field observations and airborne lidar observations. It has been applied to an instrumented reference forest site in the south of France, which is heavily impacted by climate change. It leads to the evaluation of tree heights and ends with assessments of aerial and root carbon stocks. A detailed assessment of uncertainties is presented to add a level of reliability to the scientific products delivered.
Marc Bocquet, Pierre J. Vanderbecken, Alban Farchi, Joffrey Dumont Le Brazidec, and Yelva Roustan
Nonlin. Processes Geophys., 31, 335–357, https://doi.org/10.5194/npg-31-335-2024, https://doi.org/10.5194/npg-31-335-2024, 2024
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A novel approach, optimal transport data assimilation (OTDA), is introduced to merge DA and OT concepts. By leveraging OT's displacement interpolation in space, it minimises mislocation errors within DA applied to physical fields, such as water vapour, hydrometeors, and chemical species. Its richness and flexibility are showcased through one- and two-dimensional illustrations.
Alice Maison, Lya Lugon, Soo-Jin Park, Alexia Baudic, Christopher Cantrell, Florian Couvidat, Barbara D'Anna, Claudia Di Biagio, Aline Gratien, Valérie Gros, Carmen Kalalian, Julien Kammer, Vincent Michoud, Jean-Eudes Petit, Marwa Shahin, Leila Simon, Myrto Valari, Jérémy Vigneron, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 24, 6011–6046, https://doi.org/10.5194/acp-24-6011-2024, https://doi.org/10.5194/acp-24-6011-2024, 2024
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This study presents the development of a bottom-up inventory of urban tree biogenic emissions. Emissions are computed for each tree based on their location and characteristics and are integrated in the regional air quality model WRF-CHIMERE. The impact of these biogenic emissions on air quality is quantified for June–July 2022. Over Paris city, urban trees increase the concentrations of particulate organic matter by 4.6 %, of PM2.5 by 0.6 %, and of ozone by 1.0 % on average over 2 months.
Yumeng Chen, Polly Smith, Alberto Carrassi, Ivo Pasmans, Laurent Bertino, Marc Bocquet, Tobias Sebastian Finn, Pierre Rampal, and Véronique Dansereau
The Cryosphere, 18, 2381–2406, https://doi.org/10.5194/tc-18-2381-2024, https://doi.org/10.5194/tc-18-2381-2024, 2024
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We explore multivariate state and parameter estimation using a data assimilation approach through idealised simulations in a dynamics-only sea-ice model based on novel rheology. We identify various potential issues that can arise in complex operational sea-ice models when model parameters are estimated. Even though further investigation will be needed for such complex sea-ice models, we show possibilities of improving the observed and the unobserved model state forecast and parameter accuracy.
Charlotte Durand, Tobias Sebastian Finn, Alban Farchi, Marc Bocquet, Guillaume Boutin, and Einar Ólason
The Cryosphere, 18, 1791–1815, https://doi.org/10.5194/tc-18-1791-2024, https://doi.org/10.5194/tc-18-1791-2024, 2024
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This paper focuses on predicting Arctic-wide sea-ice thickness using surrogate modeling with deep learning. The model has a predictive power of 12 h up to 6 months. For this forecast horizon, persistence and daily climatology are systematically outperformed, a result of learned thermodynamics and advection. Consequently, surrogate modeling with deep learning proves to be effective at capturing the complex behavior of sea ice.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Evangelia Kostenidou, Baptiste Marques, Brice Temime-Roussel, Yao Liu, Boris Vansevenant, Karine Sartelet, and Barbara D'Anna
Atmos. Chem. Phys., 24, 2705–2729, https://doi.org/10.5194/acp-24-2705-2024, https://doi.org/10.5194/acp-24-2705-2024, 2024
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Secondary organic aerosol (SOA) from gasoline vehicles can be a significant source of particulate matter in urban areas. Here the chemical composition of secondary volatile organic compounds and SOA produced by photo-oxidation of Euro 5 gasoline vehicle emissions was studied. The volatility of the SOA formed was calculated. Except for the temperature and the concentration of the aerosol, additional parameters may play a role in the gas-to-particle partitioning.
Victor Lannuque, Barbara D'Anna, Evangelia Kostenidou, Florian Couvidat, Alvaro Martinez-Valiente, Philipp Eichler, Armin Wisthaler, Markus Müller, Brice Temime-Roussel, Richard Valorso, and Karine Sartelet
Atmos. Chem. Phys., 23, 15537–15560, https://doi.org/10.5194/acp-23-15537-2023, https://doi.org/10.5194/acp-23-15537-2023, 2023
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Large uncertainties remain in understanding secondary organic aerosol (SOA) formation from toluene oxidation. In this study, speciation measurements in gaseous and particulate phases were carried out, providing partitioning and volatility data on individual toluene SOA components at different temperatures. A new detailed oxidation mechanism was developed to improve modeled speciation, and effects of different processes involved in gas–particle partitioning at the molecular scale are explored.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Leonie Villiger, Marina Dütsch, Sandrine Bony, Marie Lothon, Stephan Pfahl, Heini Wernli, Pierre-Etienne Brilouet, Patrick Chazette, Pierre Coutris, Julien Delanoë, Cyrille Flamant, Alfons Schwarzenboeck, Martin Werner, and Franziska Aemisegger
Atmos. Chem. Phys., 23, 14643–14672, https://doi.org/10.5194/acp-23-14643-2023, https://doi.org/10.5194/acp-23-14643-2023, 2023
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This study evaluates three numerical simulations performed with an isotope-enabled weather forecast model and investigates the coupling between shallow trade-wind cumulus clouds and atmospheric circulations on different scales. We show that the simulations reproduce key characteristics of shallow trade-wind clouds as observed during the field experiment EUREC4A and that the spatial distribution of stable-water-vapour isotopes is shaped by the overturning circulation associated with these clouds.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev., 16, 5281–5303, https://doi.org/10.5194/gmd-16-5281-2023, https://doi.org/10.5194/gmd-16-5281-2023, 2023
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A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Tobias Sebastian Finn, Charlotte Durand, Alban Farchi, Marc Bocquet, Yumeng Chen, Alberto Carrassi, and Véronique Dansereau
The Cryosphere, 17, 2965–2991, https://doi.org/10.5194/tc-17-2965-2023, https://doi.org/10.5194/tc-17-2965-2023, 2023
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We combine deep learning with a regional sea-ice model to correct model errors in the sea-ice dynamics of low-resolution forecasts towards high-resolution simulations. The combined model improves the forecast by up to 75 % and thereby surpasses the performance of persistence. As the error connection can additionally be used to analyse the shortcomings of the forecasts, this study highlights the potential of combined modelling for short-term sea-ice forecasting.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
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Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
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Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
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When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi.
Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Chao Lin, Yunyi Wang, Ryozo Ooka, Cédric Flageul, Youngseob Kim, Hideki Kikumoto, Zhizhao Wang, and Karine Sartelet
Atmos. Chem. Phys., 23, 1421–1436, https://doi.org/10.5194/acp-23-1421-2023, https://doi.org/10.5194/acp-23-1421-2023, 2023
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In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary, and secondary aerosols, is coupled with the computational fluid dynamics (CFD) software, OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon of Greater Paris is simulated. The coupled model achieved better agreement in NO2 and PM10 with measurement data than the conventional CFD simulation which regards pollutants as passive scalars.
Zhizhao Wang, Florian Couvidat, and Karine Sartelet
Geosci. Model Dev., 15, 8957–8982, https://doi.org/10.5194/gmd-15-8957-2022, https://doi.org/10.5194/gmd-15-8957-2022, 2022
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Air quality models need to reliably predict secondary organic aerosols (SOAs) at a reasonable computational cost. Thus, we developed GENOA v1.0, a mechanism reduction algorithm that preserves the accuracy of detailed gas-phase chemical mechanisms for SOA formation, thereby improving the practical use of actual chemistry in SOA models. With GENOA, a near-explicit chemical scheme was reduced to 2 % of its original size and computational time, with an average error of less than 3 %.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Alice Maison, Cédric Flageul, Bertrand Carissimo, Yunyi Wang, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 22, 9369–9388, https://doi.org/10.5194/acp-22-9369-2022, https://doi.org/10.5194/acp-22-9369-2022, 2022
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This paper presents a parameterization of the tree crown effect on air flow and pollutant dispersion in a street network model used to simulate air quality at the street level. The new parameterization is built using a finer-scale model (computational fluid dynamics). The tree effect increases with the leaf area index and the crown volume fraction of the trees; the street horizontal velocity is reduced by up to 68 % and the vertical transfer into or out of the street by up to 23 %.
Karine Sartelet, Youngseob Kim, Florian Couvidat, Maik Merkel, Tuukka Petäjä, Jean Sciare, and Alfred Wiedensohler
Atmos. Chem. Phys., 22, 8579–8596, https://doi.org/10.5194/acp-22-8579-2022, https://doi.org/10.5194/acp-22-8579-2022, 2022
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A methodology is defined to estimate number emissions from an inventory providing mass emissions. Number concentrations are simulated over Greater Paris using different nucleation parameterisations (binary, ternary involving sulfuric acid and ammonia, and heteromolecular involving sulfuric acid and extremely low-volatility organics, ELVOCs). The comparisons show that ternary nucleation may not be a dominant process for new particle formation in cities, but they stress the role of ELVOCs.
Cyrille Flamant, Marco Gaetani, Jean-Pierre Chaboureau, Patrick Chazette, Juan Cuesta, Stuart John Piketh, and Paola Formenti
Atmos. Chem. Phys., 22, 5701–5724, https://doi.org/10.5194/acp-22-5701-2022, https://doi.org/10.5194/acp-22-5701-2022, 2022
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Rivers of smoke extend from tropical southern Africa towards the Indian Ocean during the winter fire season, controlled by the interaction of tropical easterly waves, and westerly waves at mid latitudes. During the AEROCLO-sA field campaign in 2017, a river of smoke was directly observed over Namibia. In this paper, the evolution and atmospheric drivers of the river of smoke are described, and the role of a mid-latitude cut-off low in lifting the smoke to the upper troposphere is highlighted.
Sandrine Bony, Marie Lothon, Julien Delanoë, Pierre Coutris, Jean-Claude Etienne, Franziska Aemisegger, Anna Lea Albright, Thierry André, Hubert Bellec, Alexandre Baron, Jean-François Bourdinot, Pierre-Etienne Brilouet, Aurélien Bourdon, Jean-Christophe Canonici, Christophe Caudoux, Patrick Chazette, Michel Cluzeau, Céline Cornet, Jean-Philippe Desbios, Dominique Duchanoy, Cyrille Flamant, Benjamin Fildier, Christophe Gourbeyre, Laurent Guiraud, Tetyana Jiang, Claude Lainard, Christophe Le Gac, Christian Lendroit, Julien Lernould, Thierry Perrin, Frédéric Pouvesle, Pascal Richard, Nicolas Rochetin, Kevin Salaün, Alfons Schwarzenboeck, Guillaume Seurat, Bjorn Stevens, Julien Totems, Ludovic Touzé-Peiffer, Gilles Vergez, Jessica Vial, Leonie Villiger, and Raphaela Vogel
Earth Syst. Sci. Data, 14, 2021–2064, https://doi.org/10.5194/essd-14-2021-2022, https://doi.org/10.5194/essd-14-2021-2022, 2022
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The French ATR42 research aircraft participated in the EUREC4A international field campaign that took place in 2020 over the tropical Atlantic, east of Barbados. We present the extensive instrumentation of the aircraft, the research flights and the different measurements. We show that the ATR measurements of humidity, wind, aerosols and cloudiness in the lower atmosphere are robust and consistent with each other. They will make it possible to advance understanding of cloud–climate interactions.
Karine Desboeufs, Franck Fu, Matthieu Bressac, Antonio Tovar-Sánchez, Sylvain Triquet, Jean-François Doussin, Chiara Giorio, Patrick Chazette, Julie Disnaquet, Anaïs Feron, Paola Formenti, Franck Maisonneuve, Araceli Rodríguez-Romero, Pascal Zapf, François Dulac, and Cécile Guieu
Atmos. Chem. Phys., 22, 2309–2332, https://doi.org/10.5194/acp-22-2309-2022, https://doi.org/10.5194/acp-22-2309-2022, 2022
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This article reports the first concurrent sampling of wet deposition samples and surface seawater and was performed during the PEACETIME cruise in the remote Mediterranean (May–June 2017). Through the chemical composition of trace metals (TMs) in these samples, it emphasizes the decrease of atmospheric metal pollution in this area during the last few decades and the critical role of wet deposition as source of TMs for Mediterranean surface seawater, especially for intense dust deposition events.
Patrick Chazette, Alexandre Baron, and Cyrille Flamant
Atmos. Chem. Phys., 22, 1271–1292, https://doi.org/10.5194/acp-22-1271-2022, https://doi.org/10.5194/acp-22-1271-2022, 2022
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Within the framework of the international EUREC4A project, horizontal lidar measurements were carried out over Barbados from the French research aircraft ATR-42. These measurements highlighted the strong heterogeneity of the aerosol field (mainly dust and biomass burning aerosols) and therefore of the associated optical properties. This heterogeneity varies according to meteorological conditions and could significantly modulate the climatic impact of aerosols trapped over the tropical Atlantic.
Boris Vansevenant, Cédric Louis, Corinne Ferronato, Ludovic Fine, Patrick Tassel, Pascal Perret, Evangelia Kostenidou, Brice Temime-Roussel, Barbara D'Anna, Karine Sartelet, Véronique Cerezo, and Yao Liu
Atmos. Meas. Tech., 14, 7627–7655, https://doi.org/10.5194/amt-14-7627-2021, https://doi.org/10.5194/amt-14-7627-2021, 2021
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A new method was developed to correct wall losses of particles on Teflon walls using a new environmental chamber. It was applied to experiments with six diesel vehicles (Euro 3 to 6), tested on a chassis dynamometer. Emissions of particles and precursors were obtained under urban and motorway conditions. The chamber experiments help understand the role of physical processes in diesel particle evolutions in the dark. These results can be applied to situations such as tunnels or winter rush hours.
Julien Totems, Patrick Chazette, and Alexandre Baron
Atmos. Meas. Tech., 14, 7525–7544, https://doi.org/10.5194/amt-14-7525-2021, https://doi.org/10.5194/amt-14-7525-2021, 2021
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We describe in detail the design and calibration of the new Raman channels for the WALI system, going over the important sources of bias and uncertainty on retrieved temperature profiles. For the first time, their impact is investigated using horizontal shots in a homogenous atmosphere: the magnitude of the highlighted biases can be much larger than the targeted absolute accuracy of 1° C. Actual measurement errors are quantified using radiosoundings launched close to the lidar site.
Lya Lugon, Jérémy Vigneron, Christophe Debert, Olivier Chrétien, and Karine Sartelet
Geosci. Model Dev., 14, 7001–7019, https://doi.org/10.5194/gmd-14-7001-2021, https://doi.org/10.5194/gmd-14-7001-2021, 2021
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The multiscale Street-in-Grid model is used to simulate black carbon (BC) concentrations in streets. To respect street-surface mass balance, particle resuspension is estimated with a new approach based on deposited mass. The contribution of resuspension is low, but non-exhaust emissions from tyre wear may largely contribute to BC concentrations. The impact of the two-way dynamic coupling between scales on BC concentrations varies depending on the street geometry and traffic emission intensity.
Jonas Hamperl, Clément Capitaine, Jean-Baptiste Dherbecourt, Myriam Raybaut, Patrick Chazette, Julien Totems, Bruno Grouiez, Laurence Régalia, Rosa Santagata, Corinne Evesque, Jean-Michel Melkonian, Antoine Godard, Andrew Seidl, Harald Sodemann, and Cyrille Flamant
Atmos. Meas. Tech., 14, 6675–6693, https://doi.org/10.5194/amt-14-6675-2021, https://doi.org/10.5194/amt-14-6675-2021, 2021
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Laser active remote sensing of tropospheric water vapor is a promising technology for enhancing our understanding of processes governing the global hydrological cycle. We investigate the potential of a ground-based lidar to monitor the main water vapor isotopes at high spatio-temporal resolutions in the lower troposphere. Using a realistic end-to-end simulator, we show that high-precision measurements can be achieved within a range of 1.5 km, in mid-latitude or tropical environments.
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