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6. The Paris Low-Level Jet During PANAME 2022 and its Impact on the Summertime Urban Heat Island.

Author

Céspedes, Jonnathan, Kotthaus, Simone, Preissler, Jana, Toupoint, Clément, Thobois, Ludovic, Drouin, Marc-Antoine, Dupont, Jean-Charles, Faucheux, Aurélien, and Haeffelin, Martial

Subjects
URBAN heat islands, WIND speed, ATMOSPHERIC boundary layer, WIND speed measurement, ATMOSPHERIC temperature, CITIES & towns
Abstract

The Low-Level Jet (LLJ) and the Urban Heat Island (UHI) are common nocturnal phenomena in the atmospheric boundary layer. While the canopy layer UHI has been studied extensively, interactions of the LLJ and the urban atmosphere in general (and the UHI in particular) have received less attention. In the framework of the PANAME initiative in the Paris region, continuous measurements of wind speed and vertical velocity profiles were recorded with two Doppler Wind Lidars (DWL) – for the first time allowing for a detailed investigation of the summertime LLJ characteristics in the region. Jets are detected for 70 % of the examined nights, often simultaneously at an urban and a suburban site highlighting the LLJ regional spatial extent. Emerging at around sunset, the mean LLJ duration is ∼10 h, the mean wind speed is ∼9 ms−1, and the average core height is 400 m above the city. For many jets, results show signatures in the temporal evolution that indicate the inertial oscillation mechanism plays a role in the jet development: a clockwise veering of the wind direction and a rapid acceleration followed by a slower deceleration. The LLJ core induces variance in the vertical velocity (σ2w) above the urban canopy layer. It is shown that σ2w is a powerful indicator for the air temperature spatial contrasts as UHI intensity decreases exponentially with increasing σ2w and strong values only occur when σ2w is very weak. This study demonstrates how DWL observations in cities provide valuable insights into near-surface processes relevant to human and environmental health. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Pico-Light H2O: Intercomparison of in situ water vapour measurements during the AsA 2022 campaign.

Author

Ghysels, Mélanie, Durry, Georges, Amarouche, Nadir, Hurst, Dale, Hall, Emrys, Kensy Xiong, Dupont, Jean-Charles, Samake, Jean-Christophe, Frérot, Fabien, Bejjani, Raghed, and Riviere, Emmanuel D.

Subjects
WATER vapor, ATMOSPHERIC water vapor measurement, HUMIDITY, HYGROMETERS, RESEARCH teams, TROPOSPHERE, STRATOSPHERE
Abstract

The mid-infrared lightweight stratospheric hygrometer, "Pico-Light H2O", the successor of Pico-SDLA H2O, is presented and its performances are evaluated during the AsA 2022 balloon-borne intercomparison campaign conducted at CNES Aire-sur-l'Adour (AsA) balloon launch facility and the Aeroclub d'Aire-sur-l'Adour. The Pico-Light instrument primarily been developed for sounding of the upper troposphere and stratosphere. Though, during the AsA 2022 campaign we expand the range of comparison including the lower troposphere additionally. Three different types of hygrometers and two models of radiosonde were flown, operated by the French Space Agency (CNES) and the NOAA Global Monitoring Laboratory (GML) scientific teams: Pico-Light H2O, the NOAA Frost Point Hygrometer (FPH), the micro hygrometer (in an early phase of development), M20 and iMet-4 sondes. In this frame, we intend to validate measurements of Pico-Light H2O through a first intercomparison with the NOAA FPH instrument. The in situ monitoring of water vapour in the UT-LS keeps being very challenging from an instrumental point of view because of the very small amounts of water vapour to be measured in these regions of the atmosphere. Between the lapse rate tropopause (11 to 12.3 km) and 20 km, the mean relative difference between water vapour mixing ratio measurements by Pico-Light H2O and NOAA FPH was (4.2 ± 7.7) %, mean tropospheric difference is was (3.84 ± 23.64)%, with differences depending on the altitude range considered. In the troposphere, relative humidity over water (RH) comparisons leads to an agreement between both Pico-Light and NOAA FPH of -0.2% on average, with excursions of about 30% RH due to moisture variability. Expanding the comparison to meteorological sondes, the iMet-4 sondes agree well with both Pico-Light and FPH between ground and 7.5 km (within ± 3% RH) and so does for M20 sondes, up to 13 km, which are wet biased by 3% RH and dry biased by 20% in case of saturation. [ABSTRACT FROM AUTHOR]

Published
2023
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8. Role of thermodynamic and turbulence processes on the fog life cycle during SOFOF3D experiment

Author

Dione, Cheikh, Haeffelin, Martial, Burnet, Frédéric, Lac, Christine, Canut, Guylaine, Delanoë, Julien, Dupont, Jean-Charles, Jorquera, Susana, Martinet, Pauline, Ribaud, Jean-François, and Toledo, Felipe

Abstract

In this study, we use a synergy of in-situ and remote sensing measurements collected during the Southwest FOGs 3D experiment for processes study (SOFOG3D) field campaign in autumn 2019 and winter 2020, to analyze the thermodynamic and turbulence processes related to fog formation, evolution, and dissipation across southwestern France. Based on a unique dataset with a very high resolution and a fog conceptual model, an analysis of the four heaviest fog episodes (two radiation fogs and two advection-radiation fogs) is conducted. The results show that radiation and advection-radiation fogs form under deep and thin temperature inversion, respectively. For both fog categories, the transition period from stable to adiabatic fog and the fog adiabatic phase are driven by vertical mixing associated with an increase in turbulence in the fog layer due to mechanical production (turbulence kinetic energy (TKE) up to 0.4 m2 s-2 and vertical velocity variance (σw2) up to 0.04 m2 s-2) generated by brisk wind at the supersite (advection). The dissipation time is observed at night for the advection-radiation fog case studies and during the day for the radiation fog case studies. Night-time dissipation is driven by horizontal advection generating mechanical turbulence (TKE at least 0.3 m2 s-2 and σw2 larger than 0.04 m2 s-2). Daytime dissipation is linked to the combination of thermal and mechanical turbulence related respectively to solar heating (near surface sensible heat flux larger than 10 W m-2) and advection. Through a deficit of the fog reservoir of liquid water path, the fog conceptual model estimates the dissipation time at least one hour before the observed dissipation for radiation fog cases. It gives a better estimate of the fog dissipation time for advection-radiation cases. This study also demonstrates the importance of using instrumental synergy (with microwave radiometer, wind lidar, weather station, and cloud radar) and a fog conceptual model to better predict fog characteristics and dissipation time at nowcasting ranges.

Published
2023

9. PANAME – Project synergy of atmospheric research in the Paris region

Author

Haeffelin, Martial, Kotthaus, Simone, Bastin, Sophie, Bouffies-Cloché, Sophie, Cantrell, Chris, Christen, Andreas, Dupont, Jean-Charles, Foret, Gilles, Gros, Valérie, Lemonsu, Aude, Leymarie, Juliette, Lohou, Fabienne, Madelin, Malika, Masson, Valéry, Michoud, Vincent, Price, Jeremy, Ramonet, Michel, Ribaud, Jean-Francois, Sartelet, Karine, Wurtz, Jean, Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Albert-Ludwigs-Universität Freiburg, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Laboratoire d'aérologie (LAERO), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Pôle de recherche pour l'organisation et la diffusion de l'information géographique (PRODIG (UMR_8586 / UMR_D_215 / UM_115)), Université Paris 1 Panthéon-Sorbonne (UP1)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), United Kingdom Met Office [Exeter], Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Centre d'Enseignement et de Recherche en Environnement Atmosphérique (CEREA), École des Ponts ParisTech (ENPC)-EDF R&D (EDF R&D), and EDF (EDF)-EDF (EDF)

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]
Abstract

International audience; The Paris region (France) is increasingly the focus of urban atmospheric research. Numerous national and international research projects have chosen Europe’s largest metropolitan region as their study area to better understand and predict critical hazards (incl. heat, air pollution, thunderstorms) in the context of a changing climate. Located on rather flat terrain in continental, mid-latitude climates, the densely populated Paris region is very suitable for the evaluation of urban processes in numerical simulations at different scales. The European research infrastructures ACTRIS and ICOS are developing strategies for the improved operational monitoring of air pollution and greenhouse gas budgets, respectively. Various research projects are conducting fundamental process studies and model developments to investigate the dynamics and chemistry of the urban atmosphere and its interactions with the rural surroundings and regional-scale flow to better quantify associated health risks and inform sustainable planning.In addition to numerous modelling activities (chemistry-transport, numerical weather prediction, climate projections), diverse atmospheric observations are collected. These include dense surface station networks, turbulent flux towers, and ground-based atmospheric remote sensing to monitor the atmospheric boundary layer. This multi-project context motivates the pooling of resources.To facilitate efficient project synergy and to optimise the coordination of the individual experimental campaigns, the PANAME initiative (https://paname.aeris-data.fr/) was established. PANAME provides a framework to optimise the design of the Paris region measurement network and helps to standardise the operations. A professional, multi-disciplinary data portal is developed at the French AERIS atmospheric data centre to host the PANAME observations and model results. Here, data are collected and formatted, standardised advanced products are derived from the diverse sensor networks and high-quality visualisations are generated in near real-time. The presentation will provide an overview on the scientific objectives of the on-going projects, the deployment of measurements and simulation tools, and the data portal design.

Published
2023

11. Forest fire plumes in the Paris region (France) during summer 2022, the spoor of a schorching summer

Author

Petit, Jean-Eudes, primary, Gros, Valérie, additional, Favez, Olivier, additional, Simon, Leila, additional, Kalalian, Carmen, additional, Brugère, Etienne, additional, Borbon, Agnès, additional, Dupont, Jean-Charles, additional, Abbou, Grégory, additional, Ghersi, Véronique, additional, Michoud, Vincent, additional, Di Biagio, Claudia, additional, Formenti, Paola, additional, Cantrell, Christopher, additional, Gration, Aline, additional, Brito, Joêl, additional, Dusanter, Sebastien, additional, Jamar, Marina, additional, and Haeffelin, Martial, additional

Published
2023
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13. Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy.

Author

Vishwakarma, Pragya, Delanoë, Julien, Jorquera, Susana, Martinet, Pauline, Burnet, Frederic, Bell, Alistair, and Dupont, Jean-Charles

Subjects
CLIMATOLOGY, MICROWAVE radiometers, RADIOMETERS, CLOUD droplets, LIQUIDS, ICE clouds, FOG
Abstract

Cloud radars are capable of providing continuous high-resolution observations of clouds and now offer new capabilities within fog layers thanks to the development of frequency-modulated continuous-wave 95 GHz cloud radars. These observations are related to the microphysical properties of clouds. Power law relations in the form of Z=a⋅LWCb are generally used to estimate liquid water content (LWC) profiles. The constants a and b from the power law relation vary with the cloud type and cloud characteristics. Due to the variety of such parameterizations, selecting the most appropriate Z –LWC relation for a continuous cloud system is complicated. Additional information such as liquid water path (LWP) from a co-located microwave radiometer (MWR) is used to scale the LWC of the cloud profile. An algorithm for estimating the LWC of fog and warm clouds using 95 GHz cloud radar–microwave radiometer synergy in a variational framework is presented. This paper also aims to propose an algorithm configuration that retrieves the LWC of clouds and fog using radar reflectivity and a climatology of the power law parameters. To do so, variations in the scaling factor ln⁡a (the logarithm of pre-factor a from power law relation) when MWR observations are available are allowed in each cloud profile to build a climatology of the scaling factor ln⁡a that can be used when MWR observations are not available. The algorithm also accounts for attenuation due to cloud droplets. In this algorithm formulation, the measure of uncertainty in the observations, the forward model, and the a priori information of desired variables acts as weights in the retrieved quantities. These uncertainties in the retrieval are analyzed in the sensitivity analysis of the algorithm. The retrieval algorithm is first tested on a synthetic profile for different perturbations in sensitivity parameters. The sensitivity study has shown that this method is susceptible to LWP information because LWP is point information for the whole cloud column. By further investigating the sensitivity analysis of various biases in LWP information, it was found that it is beneficial to incorporate LWP, even if it is biased, rather than not assimilate any LWP. The algorithm is then implemented in various cloud and fog cases at the SIRTA observatory to estimate LWC and the scaling factor. The scaling factor (ln⁡a) changes for each cloud profile, and the range of ln⁡a is consistent with suggested values in the literature. The validation of such an algorithm is challenging, as we need reference measurements of LWC co-located with the retrieved values. During the SOFOG-3D campaign (southwest of France, October 2019 to March 2020), in situ measurements of LWC were collected in the vicinity of a cloud radar and a microwave radiometer, allowing comparison of retrieved and measured LWC. The comparison demonstrated that the cloud–fog heterogeneity played a key role in the assessment. The proposed synergistic retrieval algorithm is applied to 39 cloud and fog cases at SIRTA, and the behavior of the scaling factor is studied. This statistical analysis of scaling is carried out to develop a radar-only retrieval method. The climatology revealed that the scaling factor can be linked to the maximum reflectivity of the profile. From climatology, the statistical relations for the scaling factor are proposed for fog and clouds. Thanks to the variational framework, a stand-alone radar version of the algorithm is adapted from the synergistic retrieval algorithm, which incorporates the climatology of the scaling factor as a priori information to estimate the LWC of warm clouds. This method allows the LWC estimation using only radar reflectivity and climatology of the scaling factor. [ABSTRACT FROM AUTHOR]

Published
2023
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15. L'institut Pierre-Simon Laplace

Author

Claveau, Tiphaine, primary, Vautard, Robert, additional, Sabouraud, Valérie, additional, Haeffelin, Martial, additional, Boucher, Olivier, additional, Dupont, Jean-Charles, additional, and Braconnot, Pascale, additional

Published
2022
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17. Response of atmospheric composition to COVID-19 lockdown measures during spring in the Paris region (France)

Author

Petit, Jean-Eudes, primary, Dupont, Jean-Charles, additional, Favez, Olivier, additional, Gros, Valérie, additional, Zhang, Yunjiang, additional, Sciare, Jean, additional, Simon, Leila, additional, Truong, François, additional, Bonnaire, Nicolas, additional, Amodeo, Tanguy, additional, Vautard, Robert, additional, and Haeffelin, Martial, additional

Published
2021
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20. Fog dissipation through ground warming monitored by satellite image : an approach to support regional forecasting

Author

Badosa Jordi, Felipe Toledo, Martial Haeffelin, Dupont Jean-Charles, and Sylvain Cros

Subjects
Meteorology, Satellite image, Environmental science, Dissipation
Abstract

By reducing the atmospheric visibility, fog events have strong impacts on several humans activities. Transport security, military operations, air quality forecast and solar energy production are critical activities considering fog dissipation time as a high valuable information.Fog dissipation occurs through these two following processes. (1) An adiabatic cloud elevation converts the fog into a low stratus, increasing the visibility at ground level while keeping an overcast sky. (2) A radiative warming can break through a large continuous fog deck. Then, the cleared area increases progressively by heating the ground of the neighboured fog covered area.These two events are particularly difficult to forecast using NWP models as many non-linear local processes at short-time scale are involved. Moreover, current network of fog presence sensors is too scarce to analyse and/or anticipate the phenomena. Subsequent images of geostationary meteorological satellite offer a high temporal resolution that enables to monitor large fog decks and detect punctual clear areas that induce dissipation (case 2). However, fog detection using satellite images suffers from a lack of distinction between fog and very low stratus.In this work, we explored the potential of MSG SEVIRI radiometer through radiance observations and more advanced cloud products to analyse fog events effectively observed at the SIRTA atmospheric observatory (Palaiseau, France). We assumed that, during these events, pixels classified as “very low cloud” according to SAF-NWC algorithm were covered by fog. We monitored the evolution of these pixels using a cloud index derived from HRV channels, providing a more detailed spatial distribution of cloud cover during day time. We analysed the evolution of brightness temperature spatial gradient from the SEVIRI infrared window channel (IR 10.8µm). We isolated cases where ground warming situation could anticipate an irreversible fog dissipation. Then we deduced some fog dissipation forecasting principles.This approach has the potential to provide to users information on morning fog sustainability with a higher accuracy and finer temporal resolution than NWP. Ongoing work focuses on characterizing favourable situations for accurate forecasts, while further predictors are investigated using recent products providing a smart distinction between fog and low stratus using SEVIRI images.

Published
2021

22. Diurnal evolution of total column and surface atmospheric ammonia in the megacity of Paris, France, during an intense springtime pollution episode

Author

Kutzner, Rebecca D., primary, Cuesta, Juan, additional, Chelin, Pascale, additional, Petit, Jean-Eudes, additional, Ray, Mokhtar, additional, Landsheere, Xavier, additional, Tournadre, Benoît, additional, Dupont, Jean-Charles, additional, Rosso, Amandine, additional, Hase, Frank, additional, Orphal, Johannes, additional, and Beekmann, Matthias, additional

Published
2021
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24. Supplementary material to "Response of atmospheric composition to COVID-19 lockdown measures during Spring in the Paris region (France)"

Author

Petit, Jean-Eudes, primary, Dupont, Jean-Charles, additional, Favez, Olivier, additional, Gros, Valérie, additional, Zhang, Yunjiang, additional, Sciare, Jean, additional, Simon, Leïla, additional, Truong, François, additional, Bonnaire, Nicolas, additional, Amodeo, Tanguy, additional, Vautard, Robert, additional, and Haeffelin, Martial, additional

Published
2021
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26. Modélisation de la composition chimique de la troposphère avec CHIMERE

Author

Dupont, Jean-Charles, Haeffelin, Martial, Gros, Valérie, Petit, Jean-Eudes, Favez, Olivier, Menut, Laurent, Bessagnet, Bertrand, Khvorostyanov, Dmitry, Turquety, Solène, MONGE, Jean-Louis, VALARI, Myrto, Vautard, Robert, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Chimie Atmosphérique Expérimentale (CAE), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract

International audience; 91128 Palaiseau Cedex (2) Institut national de l'environnement industriel et des risques (INERIS), Division des risques chroniques-Verneuil-en-Halatte, France.

Published
2020

27. First year of real-time VOC measurements at the SIRTA facility (Paris region, France): diurnal and seasonal variabilities, impact of lockdowns on air quality

Author

Simon, Leïla, primary, Gros, Valérie, additional, Petit, Jean-Eudes, additional, Truong, François, additional, Sarda-Esteve, Roland, additional, Baisnee, Dominique, additional, Bonnaire, Nicolas, additional, Dupont, Jean-Charles, additional, Haeffelin, Martial, additional, Marchand, Caroline, additional, and Favez, Olivier, additional

Published
2021
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28. Fog Analysis during SOFOG3D Experiment

Author

Vishwakarma, Pragya, primary, Delanoë, Julien, additional, Le Gac, Christophe, additional, Bertrand, Fabrice, additional, Dupont, Jean-Charles, additional, Haeffelin, Martial, additional, Martinet, Pauline, additional, Burnet, Frédéric, additional, Lac, Christine, additional, Bell, Alistair, additional, Vignelles, Damien, additional, Toledo, Felipe, additional, Jorquera, Susana, additional, and Vinson, Jean-Paul, additional

Published
2021
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32. Diurnal evolution of total column and surface atmospheric ammonia in the megacity of Paris, France, during an intense springtime pollution episode

Author

Kutzner, Rebecca D., primary, Cuesta, Juan, additional, Chelin, Pascale, additional, Petit, Jean-Eudes, additional, Ray, Mokhtar, additional, Landsheere, Xavier, additional, Tournadre, Benoît, additional, Dupont, Jean-Charles, additional, Rosso, Amandine, additional, Hase, Frank, additional, Orphal, Johannes, additional, and Beekmann, Matthias, additional

Published
2020
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33. Supplementary material to "Diurnal evolution of total column and surface atmospheric ammonia in the megacity of Paris, France, during an intense springtime pollution episode"

Author

Kutzner, Rebecca D., primary, Cuesta, Juan, additional, Chelin, Pascale, additional, Petit, Jean-Eudes, additional, Ray, Mokhtar, additional, Landsheere, Xavier, additional, Tournadre, Benoît, additional, Dupont, Jean-Charles, additional, Rosso, Amandine, additional, Hase, Frank, additional, Orphal, Johannes, additional, and Beekmann, Matthias, additional

Published
2020
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35. Use of automatic radiosonde launchers to measure temperature and humidity profiles from the GRUAN perspective

Author

Madonna, Fabio, primary, Kivi, Rigel, additional, Dupont, Jean-Charles, additional, Ingleby, Bruce, additional, Fujiwara, Masatomo, additional, Romanens, Gonzague, additional, Hernandez, Miguel, additional, Calbet, Xavier, additional, Rosoldi, Marco, additional, Giunta, Aldo, additional, Karppinen, Tomi, additional, Iwabuchi, Masami, additional, Hoshino, Shunsuke, additional, von Rohden, Christoph, additional, and Thorne, Peter William, additional

Published
2020
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37. The SOuth west FOGs 3D experiment for processes study (SOFOG3D) project

Author

Burnet, Frédéric, primary, Lac, Christine, additional, Martinet, Pauline, additional, Fourrié, Nadia, additional, Haeffelin, Martial, additional, Delanoë, Julien, additional, Price, Jeremy, additional, Barrau, Sébastien, additional, Canut, Guylaine, additional, Cayez, Grégoire, additional, Dabas, Alain, additional, Denjean, Cyrielle, additional, Dupont, Jean-Charles, additional, Honnert, Rachel, additional, Mahfouf, Jean-François, additional, Montmerle, Thibault, additional, Roberts, Greg, additional, Seity, Yann, additional, and Vié, Benoit, additional

Published
2020
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41. ELIFAN, an algorithm for the estimation of cloud cover from sky imagers

Author

Lothon, Marie, primary, Barnéoud, Paul, additional, Gabella, Omar, additional, Lohou, Fabienne, additional, Derrien, Solène, additional, Rondi, Sylvain, additional, Chiriaco, Marjolaine, additional, Bastin, Sophie, additional, Dupont, Jean-Charles, additional, Haeffelin, Martial, additional, Badosa, Jordi, additional, Pascal, Nicolas, additional, and Montoux, Nadège, additional

Published
2019
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42. Evaluation of Fog and Low Stratus Cloud Microphysical Properties Derived from In Situ Sensor, Cloud Radar and SYRSOC Algorithm

Author

Dupont, Jean-Charles, Haeffelin, Martial, Wærsted, Eivind, Delanoe, Julien, Renard, Jean-Baptiste, Preissler, Jana, O’Dowd, Colin, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES), and National University of Ireland [Galway] (NUI Galway)

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], model, microphysical properties, cloud radar, atmospheric particles, lcsh:QC851-999, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, fog, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, size distribution, reflectivity, impact, lcsh:Meteorology. Climatology, balloon measurements, retrieval, aerosol optical counter/sizer, liquid water, radiation fog
Abstract

The microphysical properties of low stratus and fog are analyzed here based on simultaneous measurement of an in situ sensor installed on board a tethered balloon and active remote-sensing instruments deployed at the Instrumented Site for Atmospheric Remote Sensing Research (SIRTA) observatory (south of Paris, France). The study focuses on the analysis of 3 case studies where the tethered balloon is deployed for several hours in order to derive the relationship between liquid water content (LWC), effective radius (Re) and cloud droplet number concentration (CDNC) measured by a light optical aerosol counter (LOAC) in situ granulometer and Bistatic Radar System for Atmospheric Studies (BASTA) cloud radar reflectivity. The well-known relationship Z = α × (LWC)β has been optimized with α ϵ [0.02, 0.097] and β ϵ [1.91, 2.51]. Similar analysis is done to optimize the relationship Re = f(Z) and CDNC = f(Z). Two methodologies have been applied to normalize the particle-size distribution measured by the LOAC granulometer with a visible extinction closure (R² ϵ [0.73, 0.93]) and to validate the LWC profile with a liquid water closure using the Humidity and Temperature Profiler (HATPRO) microwave radiometer (R² ϵ [0.83, 0.91]). In a second step, these relationships are used to derive spatial and temporal variability of the vertical profile of LWC, Re and CDNC starting from BASTA measurement. Finally, the synergistic remote sensing of clouds (SYRSOC) algorithm has been tested on three tethered balloon flights. Generally, SYRSOC CDNC and Re profiles agreed well with LOAC in situ and BASTA profiles for the studied fog layers. A systematic overestimation of LWC by SYRSOC in the top half of the fog layer was found due to fog processes that are not accounted for in the cloud algorithm SYRSOC.

Published
2018

43. Impact des nuages sur la production photovoltaïque

Author

Nicole, LINDSAY, Quentin, LIBOIS, Christine, LAC, Badosa, Jordi, Migan-Dubois, Anne, Dupont, Jean-Charles, Bourdin, Vincent, Migan, Anne, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire Génie électrique et électronique de Paris (GeePs), Université Paris-Sud - Paris 11 (UP11)-Université Pierre et Marie Curie - Paris 6 (UPMC)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris Saclay (COmUE)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université - UFR d'Ingénierie (UFR 919), and Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Université Paris-Sud - Paris 11 (UP11)

Subjects
[SPI.NRJ]Engineering Sciences [physics]/Electric power, [PHYS.COND.CM-MS]Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], ComputingMilieux_MISCELLANEOUS, [PHYS.COND.CM-MS] Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], [SPI.TRON] Engineering Sciences [physics]/Electronics, [SPI.TRON]Engineering Sciences [physics]/Electronics, [SPI.NRJ] Engineering Sciences [physics]/Electric power
Abstract

National audience

Published
2018

47. Diurnal evolution of total column and surface atmospheric ammonia in the megacity of Paris, France, during an intense springtime pollution episode.

Author

Kutzner, Rebecca D., Cuesta, Juan, Chelin, Pascale, Petit, Jean-Eudes, Ray, Mokhtar, Landsheere, Xavier, Tournadre, Benoît, Dupont, Jean-Charles, Rosso, Amandine, Hase, Frank, Orphal, Johannes, and Beekmann, Matthias

Abstract

Ammonia (NH3) is a key precursor for the formation of atmospheric secondary inorganic particles, such as ammonium nitrate and sulfate. Although the chemical processes associated with the gas-to-particle conversion are well known, atmospheric concentrations of gaseous ammonia are still scarcely characterized. This information is however critical especially for processes concerning the equilibrium between ammonia and ammonium nitrate, due to the semi-volatile character of the latter one. This study presents an analysis of the diurnal cycle of atmospheric ammonia during a pollution event over the Paris megacity region in spring 2012 (five days in late March 2012). Our objective is to analyze the link between the diurnal evolution of surface NH3 concentrations and its integrated column abundance, meteorological variables and relevant chemical species involved in gas/particle partitioning. For this, we implement an original approach based on the combined use of surface and total column ammonia measurements. These last ones are derived from ground-based remote-sensing measurements performed by the Observations of the Atmosphere by Solar Infrared Spectroscopy (OASIS) Fourier transform infrared observatory at an urban site over the southeastern suburbs of the Paris megacity. This analysis considers the following meteorological variables relevant to the ammonia pollution event: temperature, relative humidity, wind speed and direction and vertical dilution in the atmospheric boundary layer. Moreover, we study the partitioning between ammonia and ammonium particles from concomitant measurements of total particulate matter (PM) and ammonium (NH4+) concentrations at the surface. We identify the origin of the pollution event as local emissions at the beginning of the analyzed period and advection of pollution from the Benelux and west Germany region by the end. Our results show a clearly different diurnal behavior of atmospheric ammonia concentrations at the surface and those vertically integrated over the total atmospheric column. Surface concentrations remain relatively stable during the day, while total column abundances show a minimum value in the morning and rise steadily to reach a relative maximum in the late afternoon during the spring pollution event. These differences are mainly explained by vertical mixing within the boundary layer, as suggested by ground-based measurements of vertical profiles of aerosol backscatter, used as tracer of the vertical distribution of pollutants in the atmospheric boundary layer. Indeed, the afternoon enhancement of ammonia clearly seen by OASIS for the whole atmospheric column is barely depicted by surface concentrations, as the latter are strongly affected by vertical dilution within the rising boundary layer. Moreover, the concomitant occurrence of a decrease of ammonium particle concentrations and an increase of gaseous ammonia abundance suggests the volatilization of particles for forming ammonia. Furthermore, surface observations may also suggest night-time formation of ammonium particles from gas-to-particle conversion, for relative humidity levels higher than the deliquescence point of ammonium nitrate. [ABSTRACT FROM AUTHOR]

Published
2020
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48. Thermal inversion influence on the mixing layer height during a record pollutant event at Paris megacity

Author

Bravo Aranda, Juan Antonio, Haeffelin, Martial, Foret, Gilles, Gross, Valérie, Gratien, Aline, Dupont, Jean-Charles, Michaud, Vincent, Favez, Olivier, Drouin, Marc-Antoine, Institut National de l'Environnement Industriel et des Risques (INERIS), and Civs, Gestionnaire

Subjects
[SDE] Environmental Sciences, SIRTA, COURBE DE MÉLANGE, [SDE]Environmental Sciences, POLLUTION ATMOSPHERIQUE, INVERSION THERMIQUE, PARTICULES
Abstract

A network composed of three CL31 ceilometers was deployed along a 40-km South-West to North-East transect across the Paris megacity (France). This network together with information obtained from the SIRTA observatory (Doppler lidar, microwave radiometer and radiosondes) is used to monitor the atmospheric column during a recordhigh pollution event that occurred from 29th November to 7th December 2016 in Paris. The AIRPARIF network (in charge of the air quality monitoring of the Paris region) reported peak daily mean PM10 concentrations close to 150 µg/m3 at several stations in Paris city center during this event, which is the largest value observed in the past decade. At SIRTA, located 20 km away from Paris center, hourly PM10 concentrations rose up to 80 µg/m3 .This event presented among the largest PM10 concentrations in the center of Paris in the last decade. Microwave radiometer measurements allowed us to study atmospheric stability based on the high temporal resolved temperature profile. To this aim, we developed a new methodology which quantifies the thermal inversion strength through two parameters explained below. Assuming a thermal inversion, we define Tmax as the local maximum of the temperature profile below 2 km at height R(Tmax). According to the parcel’s method, to allow a surface air mass of temperature Tsurf to rise to R(Tmax), its temperature must be raised to the adiabatic temperature of Tmax, named θmax. The parameter we define to evaluate the atmospheric stability, called inhibitor parameter, is the difference between θmax and Tsurf . We observe that the thermal inversions prevented mixing layer development confining the aerosol load near the surface. This fact together with low wind speed due to high pressure caused the large PM concentration at surface level in the Paris megacity. The spatial distribution of the ceilometer network allows us to extrapolate the analysis performed at SIRTA to the Paris regional dimension. This study highlights the relevance of the synergetic combination of backscatter and Doppler lidars and microwave radiometer measurements, providing a deeper understanding of the relationship between the dynamical processes and the PM concentration at surface level.

Published
2017

49. Étude de la variabilité spatiale du flux d'évapotranspiration. Applications au SIRTA

Author

Ramier, David, Douar, Abdelhak, Ameni, Youssef, Dupont, Jean-Charles, Faucheux, Aurélien, Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement - Equipe-projet TEAM (Cerema Equipe-projet TEAM), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)

Subjects
[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2017

50. GT Précipitation (SIRTA)

Author

Banson, Sandra, Baray, Jean-Luc, Barthès, Laurent, Bastin, Sophie, Chazottes, Aymeric, Delanoë, Julien, Dilmi, Djallel, Dupont, Jean-Charles, Gires, Auguste, Hallali, Ruben, Jahangir, Emad, Lemaître, Yvon, Martini, Audrey, Mallet, Cécile, Molinié, Gilles, Parent Du Châtelet, Jacques, Paz, Igor, Schertzer, D, Tchiguirinskaia, Ioulia, Van Baelen, Joël, Viltard, Nicolas, Laboratoire de Météorologie Physique - Clermont Auvergne (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), SPACE - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Hydrologie, Météorologie et Complexité (HM&Co), École des Ponts ParisTech (ENPC), Centre de Géosciences (GEOSCIENCES), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Centre national de recherches météorologiques (CNRM), Météo France-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Mines Paris - PSL (École nationale supérieure des mines de Paris), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), MINES ParisTech - École nationale supérieure des mines de Paris, Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology
Abstract

International audience; Le rôle du GT est de coordonner les activités d'observation et d'étude des précipitations qui exploiteront l’infrastructure et les moyens mis en œuvre sur le SIRTA, de s’insérer dans action de structuration au niveau national des activités en radar météorologie, d'être en relation avec la structuration des moyens d’observations atmosphériques français (SOERE ATMOS, IR-ATMO / ACTRIS-FR ), dêtre une des briques du réseau d’observations national (plateformes d’observations existantes en France)

Published
2017

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