Search

Atmospheric boundary layer (ABL) dynamics severely impact the horizontal transport of pollutants as well as their vertical dilution. Despite this, observations of vertical wind profiles and the ABL height are still rare, particularly in cities. Thanks to recent technological advances compact ground-based remote sensing instruments are now available to monitor the heterogeneous urban atmosphere across dense sensor networks. In urban settings, Doppler wind lidars (DWL) and automatic lidars and ceilometers (ALC) are particularly useful as they operate continuously and automatically with very low maintenance under all weather conditions. Thanks to those novel profiling instruments, high-resolution (time and vertical) wind information as well as aerosol backscatter profiles can be recorded.Based on the RI-URBANS (and ICOS-cities) pilot city of Paris, France, we demonstrate what advanced products can be derived using different detailed algorithms, including vertical profiles of horizontal wind and turbulence, boundary layer heights based on aerosol or turbulence indicators, as well as low-level jet characteristics. In Paris, RI-URBANS is embedded in the PANAME initiative that coordinates the synergy between numerous projects that are investigating the urban atmosphere. Clear measurement standards, careful quality control and advanced processing algorithms are required to ensure harmonised products are obtained from the diverse sensor networks that involve instruments of different models from various manufacturers with respective capabilities and limitations.Using the synergy of the different ABL products obtained in the Paris region, it is investigated how the urban boundary layer interacts with the synoptic scale flow, the underlying topography and the urban surface. A combination of wind direction, atmospheric stability and terrain clearly affect shallow boundary layer heights and the low-level jet characteristics. But also spatial variations across the region are registered during deep convective boundary layer development.

In the context of climate change with increasingly pronounced impacts, year 2022 in France has been the warmest year ever observed. It has been the case more specifically during July, when a severe heatwave occurred across North-Western Europe. Sea-level temperature anomalies jumped over +12°C, especially in the Western half of France, pushing back all-time records. Associated to extreme temperature occurred a severe drought, with long-lasting precipitation deficit throughout the year, which was amplified during July. With around 80% deficit, July 2022 in France has also been the driest ever recorded. These singular meteorological conditions were therefore a fertile ground for forest fires. Around 70 000 ha of forest have burned in France during 2022. The South-West region has been particularly impacted during July 2022, as well as other areas which are not usually subject to this kind of events (Brittany, Center, Paris region). During July 2022 occurred the ACROSS field campaign within the Paris region, where several sites following a South-West to North-East transect provided comprehensive characterization of atmospheric composition. Namely Rambouillet station (forest, SW of Paris), SIRTA (peri-urban, SW of Paris), PRG (urban, Paris center) and Chatelet Les Halles (urban, Paris center). These sites were equiped with state-of-the-art instrumentations to characterize aerosols and reactive gases. On July 19th, an intense biomass burning plume went through the Paris region, with PM10 concentrations reaching more than 150µg/m3. The experimental effort during that period is therefore a unique asset in order to characterize the composition of this episode. Most of the sites, during that episode, record high concentrations of carbonaceous aerosols (organic matter and black carbon) and Volatile Organic Compounds tracers of biomass burning (eg acetonitrile, benzene, toluene). Temporality of the episode, atmospheric dynamics and air mass pathways, suggest the transport of a biomass burning plume from South-Western France, more than 600km away from Paris. However, aerosol size distribution surpringly reveals the influence of local fires occuring near some of the sites, at almost the same time. This work is therefore focusing on the different properties of different plumes mixing at the same time over a densely urbanized region. These differences can be highlighted by source apportionment, combined with size distribution, as well as oxydation state of organic aerosols.

Clouds have a strong influence on the amount of solar irradiance reaching the ground. However, they have large spatio-temporal variations and are difficult to model. The 1D irradiance model of code_saturne is used to estimate the global and direct solar irradiances at the ground, taking into account the impact of atmospheric gas, clouds and aerosols. Simulations are conducted and compared to measurements at the French SIRTA observatory (instrumental site for atmospheric remote sensing research), located in Palaiseau, Ile-de-France in August 2009 and in the year 2014. Although irradiance is very well modelled during clear-sky days, it is over-estimated during cloud-sky days. The estimation of irradiance during cloudy-sky days is improved by coupling the model to on-site measurements of cloud parameters from the SIRTA. RMSEs around 59 W m−2 and 50 W m−2 and MBEs around +17 W m−2 and -18 W m−2 are obtained, respectively, for global and direct irradiances during cloudy-sky days using pyranometer measurements for cloud fraction and microwave radiometric measurements for liquid water path. A sensitivity analysis on the cloud parameters that may lead to the best improvement of simulated irradiance is performed. The cloud optical depth is the most important one, followed by the cloud fraction. The different instruments used for the determination of these parameters are examined. Moreover, hourly values of solar fluxes are analysed to determine and physically understand persistent errors between model and measurements when measured cloud parameters are used.

An improved version of the near-real-time decision tool PARAFOG (PFG2) is presented to retrieve pre-fog alert levels and to discriminate between radiation (RAD) and stratus lowering (STL) fog situations. PFG2 has two distinct modules to monitor the physical processes involved in RAD and STL fog formation and is evaluated at European sites. The modules are based on innovative fuzzy logic algorithms to retrieve fog alert levels (low, moderate, high) specific to RAD/STL conditions, minutes to hours prior to fog onset. The PFG2-RAD module assesses also the thickness of the fog. Both the PFG2-RAD and PFG2-STL modules rely on the combination of visibility observations and automatic lidar and ceilometer (ALC) measurements. The overall performance of the PFG2-RAD and PFG2-STL modules is evaluated based on 9 years of measurements at the SIRTA (Instrumented Site for Atmospheric Remote Sensing Research) observatory near Paris and up to two fog seasons at the Paris-Roissy, Vienna, Munich, and Zurich airports. At all sites, pre-fog alert levels retrieved by PFG2 are found to be consistent with the local weather analysis. The advanced PFG2 algorithm performs with a hit rate of about 100 % for both considered fog types and presents a false alarm ratio on the order of 10 % (30 %) for RAD (STL) fog situations. Finally, the first high alerts that result in a subsequent fog event are found to occur for periods of time ranging from −120 min to fog onset, with the first high alerts occurring earlier for RAD than STL cases.

A detailed understanding of atmospheric boundary layer (ABL) processes is key to improve forecasting of pollution dispersion and cloud dynamics in the context of future climate scenarios. International networks of automatic lidars and ceilometers (ALC) are gathering valuable data that allow for ABL layers to be derived in near real time. A new generation of advanced methods to automatically detect the ABL heights now exist. However, diversity in ALC models means these algorithms need to be tailored to instrument-specific capabilities. Initial evaluation of the advanced algorithms STRATfinder (for application to high signal-to-noise ratio (SNR) ALC observations) and CABAM (low-SNR measurements) to automatically derive ABL heights indicates promising performances (Kotthaus et al. 2020).In the framework of the ABL testbed project (funded by ICOS, ACTRIS and E-PROFILE) the two algorithms are now being assessed for application in an operational network setting, such as EUMETNET E-PROFILE. A subset of 11 E-PROFILE sites in a range of geographical and land cover settings across Europe are selected where data from low-SNR and/or high-SNR ALC are available for multiple years. Automatic layer detection is implemented, including instrument-specific corrections and calibrations. Algorithm performance for layer height detection is being evaluated via comparison of results from different ALC and by including reference data from thermodynamic- and turbulence derived layer heights from radiosondes and other ground-based profiling sensors where available. Recommendations are formulated for implementation of automatic ABL height retrievals across a diverse sensor network. A prime example of collaborations within the EU COST action PROBE on profiling the atmospheric boundary layer, the ABL testbed is a crucial step towards harmonised ABL height products at the European scale.ReferencesKotthaus, S, M Haeffelin, MA Drouin, JC Dupont, S Grimmond, A Haefele, M Hervo, Y Poltera, M Wiegner, 2020: Tailored Algorithms for the Detection of the Atmospheric Boundary Layer Height from Common Automatic Lidars and Ceilometers (ALC). Remote Sens, 12, 3259, DOI: 10.3390/rs12193259.

Since early 2020, the COVID-19 pandemic has led to lockdowns at national scales. These lockdowns resulted in large cuts of atmospheric pollutant emissions, notably related to the vehicular traffic source where daily commuting of light-duty vehicles was almost completely stopped in numerous urban areas worldwide, especially during Spring 2020. As a result, air quality changed in manners that are still currently under investigation. Long-term in-situ monitoring of atmospheric composition provides, to this perspective, essential information. However, a robust quantitative assessment of the impact of lockdown measures on ambient concentrations is hindered by weather variability. Basic comparisons with previous years may thus be flawed, especially regarding secondary pollutants, whose concentrations strongly depends on meteorological conditions. In order to circumvent this difficulty, an innovative methodology has been developed. The Analog Application for Air Quality (A3Q) method is based on the comparison of each day of lockdown to a group of analog days having similar meteorological conditions. The A3Q method has been successfully evaluated and applied to a comprehensive in-situ dataset of primary and secondary pollutants obtained at the SIRTA observatory, a suburban background site of the Paris megacity (France). The overall slight decrease of PM1 concentrations (−14 %) compared to business-as-usual conditions conceals contrasting behaviours. Primary traffic tracers (NOx and traffic-related carbonaceous aerosols) dropped by 42–66 % during the lockdown period. Further, the A3Q method enabled us to characterize of changes triggered by NOx decreases. Particulate nitrate and secondary organic aerosols (SOA), two of the main springtime aerosol components in North-Western Europe, decreased by −45 % and −25 %, respectively. A NOx-relationship emphasizes the interest of NOx mitigation policies at the regional (i.e. city) scale, although long-range pollution advection sporadically overcompensated regional decreases. Variations of the oxidation state of SOA suggests discrepancies in SOA formation processes. At the same time, the expected ozone increase (+20 %) underlines the negative feedback of NO titration. These results provide a quasi-comprehensive observation-based insight on mitigation policies regarding air quality in future low-carbon urban areas.

Comprehensive field campaigns dedicated to fog life cycle observation were conducted during the winters of 2010–2013 at the Instrumented Site for Atmospheric Remote Sensing Research (SIRTA) observatory in a suburb of Paris. In order to document their properties, in situ microphysical measurements collected during 23 fog events induced by both radiative cooling and stratus lowering are examined here. They reveal large variability in number, concentration and size of both aerosol background before the fog onset and fog droplets according to the different cases. The objective of this paper is to evaluate the impact of aerosol particles on the fog microphysics. To derive an accurate estimation of the actual activated fog droplet number concentration Nact, we determine the hygroscopicity parameter κ, the dry and the wet critical diameter and the critical supersaturation for each case by using an iterative procedure based on the κ-Köhler theory that combines cloud condensation nuclei (CCN), dry particle and droplet size distribution measurements. Our study reveals low values of the derived critical supersaturation occurring in fog with a median of 0.043 %. Consequently, the median dry and wet activation diameters are 0.39 and 3.79 µm, respectively, leading to a minor fraction of the aerosol population activated into droplets. The corresponding Nact values are low, with median concentrations of 53.5 and 111 cm−3 within the 75th percentile. The activated fraction of aerosols exhibits remarkably low correlation with κ values, which reflects the chemical composition of the aerosols. On the contrary, the activated fraction exhibits a strong correlation with the inferred critical diameter throughout the field campaigns. This suggests that the variability in the activated fraction is mostly driven by particle size, while variations in aerosol composition are of secondary importance. Moreover, our analysis suggests that the supersaturation reached in fog could be lowered by the aerosol number concentration, which could contribute to the sink term of water vapor during the radiative cooling. Although radiative fogs are usually associated with higher aerosol loading than stratus-lowering events, our analysis also reveals that the activated fraction at the beginning of the event is similar for both types of fog. However, the evolution of the droplet concentration during the fog life cycle shows significant differences between both types of fog. This work demonstrates that an accurate calculation of supersaturation is required to provide a realistic representation of fog microphysical properties in numerical models.

An improved version of the near-real time decision tool PARAFOG (PFG2) is presented to retrieve pre-fog alert levels and to discriminate between radiation (RAD) and stratus lowering (STL) fog situations. PFG2 has two distinct modules to monitor the physical processes involved in RAD and STL fog formation and is evaluated at European sites. The modules are based on innovative fuzzy logic algorithms to retrieve fog alert levels (low, moderate, high) specific to RAD/STL conditions, minutes to hours prior to fog onset. The PFG2-RAD module assesses also the thickness of the fog. Both the PFG2-RAD and PFG2-STL modules rely on the combination of visibility observations and automatic lidar and ceilometer (ALC) measurements. The overall performance of the PFG2-RAD and -STL modules is evaluated based on 9 years of measurements at the SIRTA observatory near Paris and up to two fog seasons at the Paris-Roissy, Vienna, Munich and Zurich airports. At all sites, pre-fog alert levels retrieved by PFG2 are found to be consistent with the local weather analysis. The advanced PFG2 algorithm performs with a hit rate of about 100 % for both considered fog types, and presents a false alarm ratio on the order of 10 % (30 %) for RAD (STL) fog situations. Finally, the first high alerts that result in a subsequent fog event are found to occur for periods of time ranging from −120 minutes to fog onset, with first high alerts occurring earlier for RAD than STL cases.

Volatile Organic Compounds (VOCs) have direct influences on air quality and climate. They also play a key role in atmospheric chemistry, as they are precursors of secondary pollutants, such as ozone (O3) and secondary organic aerosols (SOA).Long-term datasets of in-situ atmospheric measurements are crucial to characterize the variability of atmospheric chemical composition. Online and continuous measurements of O3, NOx and aerosols have been achieved at the SIRTA-ACTRIS facility (Paris region, France), since 2012. Regarding VOCs, they have been measured there for several years thanks to bi-weekly samplings followed by offline Gas Chromatography analysis. However, this method doesn’t provide a good representation of the temporal variability of VOC concentrations. To tackle this issue, online VOC measurements using a Proton-Transfer-Reaction Quadrupole Mass-Spectrometer (PTR-Q-MS) have been started in January 2020.The dataset acquired during the first year of online VOC measurements is analyzed, which gives insights on VOC seasonal variability. The additional long-term datasets obtained from co-located measurements (O3, NOx, aerosol physical and chemical properties, meteorological parameters) are also used for the sake of this study.Due to Covid-19 pandemic, the year 2020 notably comprised a total lockdown in France in Spring, and a lighter one in Autumn. Therefore, a focus can be made on the impact of these lockdowns on the VOC variability and sources. To this end, the diurnal cycles of VOCs considered markers for anthropogenic sources are carefully investigated. Results notably indicate that markers for traffic and wood burning sources behave quite differently during the Spring lockdown in comparison to the other periods. A source apportionment analysis using positive matrix factorization allows to further document the seasonal variability of VOC sources and the impacts on air quality associated with the lockdown measures.

Transportation especially aviation sector all around the world is severely hindered due to Fog and hence observations and specific research for fog is necessary. The SOFOG3D (SOuth west FOGs 3D) experiment took place in South-West of France which is particularly prone to fog occurrence, during the period between November 2019 to March 2020 with primary objective to advance our understanding of fog processes and to improve fog forecast. Simultaneous measurements from various remote sensing instruments like BASTA: a 95 GHz cloud radar with scanning capability, HATPRO Microwave radiometer (MWR), doppler lidar, and balloon-borne in-situ measurements were collected to characterize the spatio-temporal evolution of Fog. On the supersite, detailed measurements of meteorological conditions, aerosol properties, fog microphysics, water deposition, radiation budget, heat, and momentum fluxes are collected to provide 3D structure of the boundary layer during fog events. The improvement in the retrieval of fog parameters and understanding of fog dynamics based on cloud radar and microwave (MWR) synergy will be addressed. We will present our work on the retrieval of key fog parameters like dynamics and microphysics using a combination of cloud radar and MWR observations. The retrievals will be validated with the tethered-balloon and radio-sounding observations. In-situ measurements and remote-sensing retrievals of fog microphysical properties will be compared. We will show a detailed analysis of retrieved LWP derived from BASTA radar only with LWP derived from HATPRO microwave radiometer, considering instrumental uncertainty and sensitivity. A closer analysis of the in-situ data (measured by granulometer) will be presented in order to assess and improve the retrieval derived with cloud radar in vertically pointing mode. Radar attenuation will be quantified by measuring the backscattered radar signal on well-known calibrated reflectivity metallic targets installed at the top of 20 m mast. The integrated attenuation along the radar beam path will be measured by the cloud radar and used as a new constraint to improve the microphysical properties.

The worldwide COVID-19 pandemic has led to lockdowns at national scales in the Spring of 2020. Large cuts in emissions occurred, but the quantitative assessment of their role from observations is hindered by weather variability. In order to circumvent this difficulty, we developed here an innovative analog methodology and applied it to a comprehensive in-situ dataset of primary and secondary pollutants obtained at the SIRTA observatory, a suburban background site of the Paris megacity (France). We find that concentrations of primary traffic dropped by 69-76% during the lockdown period. Further, the decrease of NOx triggered a decrease of particulate nitrate (-41%), one of the main springtime aerosol components in North-Western Europe. We reveal a threshold effect highlighting the need of substantial NOx decrease to affect particulate nitrate. At the same time, the expected ozone increase (+21%) underlines the negative feedback of NO titration. Finally, an increase of residential wood burning sporadically compensated primary traffic, and influenced the oxidation state of secondary organic aerosols. Our results provide a quasi-comprehensive observation-based insight on mitigation policies regarding air quality in future low-carbon urban areas.

The development of ground-based cloud radars offers a new capability to continuously monitor fog structure. Retrievals of fog microphysics are key for future process studies, data assimilation, or model evaluation and can be performed using a variational method. Both the one-dimensional variational retrieval method (1D-Var) or direct 3D/4D-Var data assimilation techniques rely on the combination of cloud radar measurements and a background profile weighted by their corresponding uncertainties to obtain the optimal solution for the atmospheric state. In order to prepare for the use of ground-based cloud radar measurements for future applications based on variational approaches, the different sources of uncertainty due to instrumental, background, and forward operator errors need to be properly treated and accounted for. This paper aims at preparing 1D-Var retrievals by analysing the errors associated with a background profile and a forward operator during fog conditions. For this, the background was provided by a high-resolution numerical weather prediction model and the forward operator by a radar simulator. Firstly, an instrumental dataset was taken from the SIRTA observatory near Paris, France, for winter 2018–2019 during which 31 fog events were observed. Statistics were calculated comparing cloud radar observations to those simulated. It was found that the accuracy of simulations could be drastically improved by correcting for significant spatio-temporal background errors. This was achieved by implementing a most resembling profile method in which an optimal model background profile is selected from a domain and time window around the observation location and time. After selecting the background profiles with the best agreement with the observations, the standard deviation of innovations (observations–simulations) was found to decrease significantly. Moreover, innovation statistics were found to satisfy the conditions needed for future 1D-Var retrievals (un-biased and normally distributed).

International audience

Fog strongly perturbs the aviation, marine and land transportation, leading to human losses and high financial costs. The primary objective of SOFOG3D is to advance our understanding of fog processes at the smallest scale to improve forecasts of fog events by numerical weather prediction (NWP) models.Specifically, SOFOG3D conducts process studies on very well documented situations, using synergy between 3D high-resolution Large Eddy Simulation (LES) and unprecedented 3D detailed observations. SOFOG3D will particularly focus on the impact of surface heterogeneities (types of vegetation, rivers, orography) on the fog life cycle, on fog microphysics properties, on entrainment at fog top, on the surface energy budget, and on the impact of aerosols. SOFOG3D will also investigate how improving the initial conditions of NWP models can improve fog forecasts. To that end, data from a ground-based MWR network will be assimilated using an innovative ensemble-based variational data assimilation scheme.A 6 months field experiment took place during wintertime 2019/2020 in the South-West of France to provide 3D mapping of the boundary layer during fog events. The observation strategy is to combine vertical profiles derived from new remote sensing instruments (microwave radiometer (MWR), Doppler cloud radar and Doppler lidars) and balloon-borne in-situ measurements, with local observations provided by a network of surface stations, and a fleet of Unmanned Aerial Vehicles (UAV) to explore fog spatial heterogeneities. Three nested domains has been instrumented with increasing density to provide observations from regional scale (300x200 km) down to local scale on the super-site (10x10 km), thanks to Meteo France and U.K. Meteorological Office sensors. On the super site, meteorological conditions, visibility, aerosol optical, microphysical and hygroscopic properties, fog microphysics and liquid water content, water deposition, radiation budget, heat and momentum fluxes on flux-masts has been performed on different areas to investigate the impacts of surface heterogeneities on fog processes, as well as turbulence anisotropy. Combination of cloud radar and MWR measurements will allow optimal retrieval of temperature, humidity and liquid water content profiles.We will present the instrumental set-up that has been deployed during this campaign and discuss the main objectives of the project. An overview of fog events that occurred during the 6 months experiment will be given, and preliminary analysis of data collected during IOPs with a tethered balloon and UAVs will be presented.

This article presents a new Cloud Radar calibration methodology using solid reference reflectors mounted on masts, developed during two field experiments held in 2018 and 2019 at the SIRTA atmospheric observatory, located in Palaiseau, France, in the framework of the ACTRIS-2 research and innovation program. The experimental setup includes 10 cm and 20 cm triangular trihedral targets installed at the top of 10 m and 20 m masts, respectively. The 10 cm target is mounted on a pan-tilt motor at the top of the 10 m mast to precisely align its boresight with the radar beam. Sources of calibration bias and uncertainty are identified and quantified. Specifically, this work assesses the impact of receiver compression, incomplete antenna overlap, temperature variations inside the radar, clutter and experimental setup misalignment. Setup misalignment is a source of bias previously undocumented in the literature, that can have an impact on the order of tenths of dB in calibration retrievals of W band Radars. A detailed analysis enabled the design of a calibration methodology which can reach a cloud radar calibration uncertainty of 0.3 dB based on the equipment used in the experiment. Among different sources of uncertainty, the two largest terms are due to signal-to-clutter ratio and radar-to-target alignment. The analysis revealed that our 20 m mast setup with an approximate alignment approach is preferred to the 10 m mast setup with the motor-driven alignment system. The calibration uncertainty associated with signal-to-clutter ratio of the former is ten times smaller than for the latter. Cloud radar calibration results are found to be repeatable when comparing results from a total of 18 independent tests. Once calibrated the cloud radar provides valid reflectivity values when sampling mid-tropospheric clouds. Thus we conclude that the method is repeatable and robust, and that the uncertainties are precisely characterized. The method can be implemented under different configurations as long as the proposed principles are respected. It could be extended to reference reflectors held by other lifting devices such as tethered balloons or unmanned aerial vehicles.

In the last two decades, technological progress has not only seen improvements to the quality of atmospheric upper-air observations but also provided the opportunity to design and implement automated systems able to replace measurement procedures typically performed manually. Radiosoundings, which remain one of the primary data sources for weather and climate applications, are still largely performed around the world manually, although increasingly fully automated upper-air observations are used, from urban areas to the remotest locations, which minimize operating costs and challenges in performing radiosounding launches. This analysis presents a first step to demonstrating the reliability of the automatic radiosonde launchers (ARLs) provided by Vaisala, Meteomodem and Meisei. The metadata and datasets collected by a few existing ARLs operated by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) certified or candidate sites (Sodankylä, Payerne, Trappes, Potenza) have been investigated and a comparative analysis of the technical performance (i.e. manual versus ARL) is reported. The performance of ARLs is evaluated as being similar or superior to those achieved with the traditional manual launches in terms of percentage of successful launches, balloon burst and ascent speed. For both temperature and relative humidity, the ground-check comparisons showed a negative bias of a few tenths of a degree and % RH, respectively. Two datasets of parallel soundings between manual and ARL-based measurements, using identical sonde models, provided by Sodankylä and Faa'a stations, showed mean differences between the ARL and manual launches smaller than ±0.2 K up to 10 hPa for the temperature profiles. For relative humidity, differences were smaller than 1 % RH for the Sodankylä dataset up to 300 hPa, while they were smaller than 0.7 % RH for Faa'a station. Finally, the observation-minus-background (O–B) mean and root mean square (rms) statistics for German RS92 and RS41 stations, which operate a mix of manual and ARL launch protocols, calculated using the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model, are very similar, although RS41 shows larger rms(O–B) differences for ARL stations, in particular for temperature and wind. A discussion of the potential next steps proposed by GRUAN community and other parties is provided, with the aim to lay the basis for the elaboration of a strategy to fully demonstrate the value of ARLs and guarantee that the provided products are traceable and suitable for the creation of GRUAN data products.

International audience; A detailed understanding of atmospheric boundary layer (ABL) processes is key to improve forecasting of pollution dispersion and cloud dynamics in the context of future climate scenarios. International networks of automatic lidars and ceilometers (ALC) are gathering valuable data that allow for the height of the ABL and its sublayers to be derived in near real time. A new generation of advanced methods to automatically detect the ABL heights now exist. However, diversity in ALC models means these algorithms need to be tailored to instrument-specific capabilities. Here, the advanced algorithm STRATfinder is presented for application to high signal-to-noise ratio (SNR) ALC observations, and results are compared to an automatic algorithm designed for low-SNR measurements (CABAM). The two algorithms are evaluated for application in an operational network setting. Results indicate that the ABL heights derived from low-SNR ALC have increased uncertainty during daytime deep convection, while high-SNR observations can have slightly reduced capabilities in detecting shallow nocturnal layers. Agreement between the ALC-based methods is similar when either is compared to the ABL heights derived from temperature profile data. The two independent methods describe very similar average diurnal and seasonal variations. Hence, high-quality products of ABL heights may soon become possible at national and continental scales.

Measurement of water vapor or humidity in the atmosphere is fundamental for many applications. Relative humidity measurements with a capacitive sensor in radiosondes are affected by several factors that need to be assessed and corrected. This work aims to address corrections for the main effects for the Meteomodem M10 radiosonde as a step to meet the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) requirements. The considered corrections are 1) the calibration correction; 2) a slow regime due to the slow diffusion of molecules through the sensor, especially at very high and very low relative humidity conditions; 3) the relative humidity sensor dependence on the gradient of temperature; and 4) the time lag at cold temperatures, which affects measurements in regions of strong relative humidity gradients. These corrections were tested for 26 nighttime and 25 daytime radiosondes in two midlatitude locations for which both Meteomodem M10 and Vaisala RS92 measurements were available. The results show that, after correcting for the four effects, M10 relative humidity measurements are, on average, consistent with the Vaisala RS92 relative humidity values within 2% RH at all altitudes for the nighttime launches (against 6% RH before the correction) and within 5% RH at all altitudes for the daytime launches (against 9% RH before the correction).

An innovative set of six observed predictors of fog formation by radiative cooling is proposed, which describes: 1) one of the main processes of fog formation that is the water uptake by aerosols at surface level; 2) the fog development along the vertical up to 30 meters, as well as the cloud cover; and 3) the temporal evolution of the parameters describing the water uptake by aerosols and the cloud cover. The visibility is used as a signal of atmospheric and surface processes affecting the water uptake by aerosols. The vertical fog development is described by the vertical thermal gradient along a 30-m meteorological mast. The cloud cover is described using a ceilometer for low and middle clouds above the instrument, and satellite data for clouds in a pixel and in a larger 9 × 9-pixel region around the site. The set of predictors can be observed in operational conditions, such as on airport fields. Data acquired at the SIRTA platform (Paris, France) during two autumns and two winters were analysed, and the cloud cover classification derived from the SEVIRI instrument on the METEOSAT Second Generation satellite by the EUMETSAT/NWCSAF program was also utilized. The training data set was acquired in November 2011 while the validation data set extended over 12 months. All situations were discriminated between favourable and unfavourable scenarii of radiative cooling fog formation, with a factor of 10 in probability. 246 moderate visibility events (with visibility between 5 and 10 km) were observed under a clear sky in 12 months at SIRTA. While developed fog formed according to one scenario, thin fog formed according to six scenarii. On the contrary to thin fog, developed fog did not form when cirrus clouds were observed above moderate visibility situations. The fog formation probability varied from 12 to 43%, and even reached 100% for one thin fog. As the training data set was acquired in autumn, the predictor set seems more appropriate to nowcast fog in humid autumn conditions, when the fog formation probability was multiplied by ~2. The predictive set could be enriched by predictors proposed in literature, and tests suggest that relative humidity would improve the fog formation probability in winter. Five predictors identify 65 of the 217 no-fog events counted in 12 months, with ~3 h anticipation time. If visibility decreased below 5 km, 88 additional no-fog events were identified. In this case, the formation probability was 35% for developed fog, and 24–60% for thin fog, but with an anticipation time reduced to ~1.5 h. Only one fog, which represents 3% of the fog events, would be missed with such a predictive scheme.

Ground-based microwave radiometers (MWRs) offer the capability to provide continuous, high-temporal-resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL) with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP) models through data assimilation. State-of-the-art data assimilation systems (e.g. variational schemes) require an accurate representation of the differences between model (background) and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O–B). Monitoring of O–B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O–B analysis for MWR observations in clear-sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB) measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective-scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O–B monitoring can effectively detect instrument malfunctions. O–B statistics (bias, standard deviation, and root mean square) for water vapour channels (22.24–30.0 GHz) are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line centre ( ∼ 2–2.5 K) towards the high-frequency wing ( ∼ 0.8–1.3 K). Statistics for zenith and lower-elevation observations show a similar trend, though values increase with increasing air mass. O–B statistics for temperature channels show different behaviour for relatively transparent (51–53 GHz) and opaque channels (54–58 GHz). Opaque channels show lower uncertainties (

Radiative cooling and heating impact the liquid water balance of fog and therefore play an important role in determining their persistence or dissipation. We demonstrate that a quantitative analysis of the radiation-driven condensation and evaporation is possible in real time using ground-based remote sensing observations (cloud radar, ceilometer, microwave radiometer). Seven continental fog events in midlatitude winter are studied, and the radiative processes are further explored through sensitivity studies. The longwave (LW) radiative cooling of the fog is able to produce 40–70 g m−2 h−1 of liquid water by condensation when the fog liquid water path exceeds 30 g m−2 and there are no clouds above the fog, which corresponds to renewing the fog water in 0.5–2 h. The variability is related to fog temperature and atmospheric humidity, with warmer fog below a drier atmosphere producing more liquid water. The appearance of a cloud layer above the fog strongly reduces the LW cooling relative to a situation with no cloud above; the effect is strongest for a low cloud, when the reduction can reach 100 %. Consequently, the appearance of clouds above will perturb the liquid water balance in the fog and may therefore induce fog dissipation. Shortwave (SW) radiative heating by absorption by fog droplets is smaller than the LW cooling, but it can contribute significantly, inducing 10–15 g m−2 h−1 of evaporation in thick fog at (winter) midday. The absorption of SW radiation by unactivated aerosols inside the fog is likely less than 30 % of the SW absorption by the water droplets, in most cases. However, the aerosols may contribute more significantly if the air mass contains a high concentration of absorbing aerosols. The absorbed radiation at the surface can reach 40–120 W m−2 during the daytime depending on the fog thickness. As in situ measurements indicate that 20–40 % of this energy is transferred to the fog as sensible heat, this surface absorption can contribute significantly to heating and evaporation of the fog, up to 30 g m−2 h−1 for thin fog, even without correcting for the typical underestimation of turbulent heat fluxes by the eddy covariance method. Since the radiative processes depend mainly on the profiles of temperature, humidity and clouds, the results of this paper are not site specific and can be generalised to fog under different dynamic conditions and formation mechanisms, and the methodology should be applicable to warmer and moister climates as well. The retrieval of approximate emissivity of clouds above fog from cloud radar should be further developed.

Comprehensive field campaigns dedicated to fog life cycle observation were conducted during the winters of 2010–2013 at the SIRTA observatory in the suburb of Paris. In order to document their properties, in situ microphysical measurements collected during 23 fog events are examined here. They reveal large variability in number, concentration and size of both aerosol background before the fog onset and fog droplets according to the different cases. The objective of this paper is to evaluate the impact of aerosol particles on the fog microphysics. To derive an accurate estimation of the actual activated fog droplet number concentration Nact we determine the hygro-scopicity parameter κ, the dry and the wet critical diameter and the critical supersaturation for each case by using an iterative procedure based on the κ-Köhler theory that combines cloud condensation nuclei (CCN), dry particle and droplet size distribution measurements. Resulting values of κ = 0.17 ± 0.05 were found typical of continental aerosols. Our study reveals low values of the derived critical supersaturation with a median of 0.043 % and large values for both wet and dry activation diameters. Consequently, the corresponding Nact values are low with median concentrations of 53.5 cm−3 and 111 cm−3 within the percentile 75th. No detectable trend between the concentration of aerosol particles with diameter > 200 nm and Nact was observed. In contrast the CCN data at 0.1 % supersaturation exhibits a strong correlation with these aerosol concentrations. We therefore conclude that the actual supersaturations reached during these fog episodes are too low and no simultaneous increase of aerosols > 200 nm and droplet concentrations can be observed. Moreover our analysis suggests that a high aerosol loading limits the supersaturation values. It is also found that the activated fraction mainly depends on the aerosol size while the hygroscopicity appears to be of a secondary importance. Although radiative fogs are usually associated with higher aerosol loading rather than to stratus lowering events, our analysis reveals that the activated particle concentrations at the beginning of the event are similar for both types of fog. However the evolution of the droplet concentration during the fog life cycle shows significant differences between both types of fog.

International audience; In the companion (Part I) paper, we have described and evaluated a new versatile optical particle counter/sizer named LOAC (Light Optical Aerosol Counter), based on scattering measurements at angles of 12 and 60 •. That allows for some typology identification of particles (droplets, carbonaceous, salts, and mineral dust) in addition to size-segregated counting in a large diameter range from 0.2 µm up to possibly more than 100 µm depending on sampling conditions (Renard et al., 2016). Its capabilities overpass those of preceding optical particle counters (OPCs) allowing the characterization of all kind of aerosols from submicronic-sized absorbing carbonaceous particles in polluted air to very coarse particles (> 10–20 µm in diameter) in desert dust plumes or fog and clouds. LOAC's light and compact design allows measurements under all kinds of balloons , on-board unmanned aerial vehicles (UAVs) and at Published by Copernicus Publications on behalf of the European Geosciences Union. 3674 J.-B. Renard et al.: LOAC: a counter/sizer for ground-based and balloon measurements – Part 2 ground level. We illustrate here the first LOAC airborne results obtained from a UAV and a variety of scientific balloons. The UAV was deployed in a peri-urban environment near Bordeaux in France. Balloon operations include (i) tethered balloons deployed in urban environments in Vi-enna (Austria) and Paris (France), (ii) pressurized balloons drifting in the lower troposphere over the western Mediter-ranean (during the Chemistry-Aerosol Mediterranean Experiment – ChArMEx campaigns), (iii) meteorological sounding balloons launched in the western Mediterranean region (ChArMEx) and from Aire-sur-l'Adour in southwestern France (VOLTAIRE-LOAC campaign). More focus is put on measurements performed in the Mediterranean during (ChArMEx) and especially during African dust transport events to illustrate the original capability of balloon-borne LOAC to monitor in situ coarse mineral dust particles. In particular, LOAC has detected unexpected large particles in desert sand plumes.

Doppler cloud radars are amazing tools to characterize cloud and fog properties and to improve their representation in models. However, commercially available cloud radars (35 and 95 GHz) are still very expensive, which hinders their widespread deployment. This study presents the development of a lower-cost semioperational 95-GHz Doppler cloud radar called the Bistatic Radar System for Atmospheric Studies (BASTA). To drastically reduce the cost of the instrument, a different approach is used compared to traditional pulsed radars: instead of transmitting a large amount of energy for a very short time period (as a pulse), a lower amount of energy is transmitted continuously. By using a specific signal processing technique, the radar can challenge expensive radars and provide high-quality measurements of cloud and fog. The latest version of the instrument has a sensitivity of about −50 dBZ at 1 km for 3-s integration and a vertical resolution of 25 m. The BASTA radar currently uses four successive modes for specific applications: the 12.5-m vertical resolution mode is dedicated to fog and low clouds, the 25-m mode is for liquid and ice midtropospheric clouds, and the 100- and 200-m modes are ideal for optically thin high-level ice clouds. The advantages of such a radar for calibration procedures and field operations are also highlighted. The radar comes with a set of products dedicated to cloud and fog studies. For instance, cloud mask, corrected Doppler velocity, and multimode products combining the high-sensitivity mode and high-resolution modes are provided.

Physical processes relevant for the dissipation of thick, continental fog after sunrise are studied through observations from the SIRTA observatory and idealized sensitivity studies with the large-eddy simulation model DALES. Observations of 250 fog events over 7 years show that more than half of the fog dissipations after sunrise are transitions to stratus lasting 2 hr or more. From the simulations, we quantify the contribution of each process to the liquid water path (LWP) budget of the fog. Radiative cooling is the main source of LWP, while surface turbulent heat fluxes are the most important process contributing to loss of LWP, followed by the absorption of solar radiation, the mixing with unsaturated air at the fog top and the deposition of cloud droplets. The loss of LWP by surface heat fluxes is very sensitive to the Bowen ratio, which is importantly affected by the availability of liquid water on the surface; in a run without liquid on the surface, fog dissipation occurred 85 min earlier than in the Baseline simulation. The variability of stratification and humidity above fog top is documented by 47 radiosondes and cloud radar. Using DALES, we find that the variability in stratification has an important impact on the entrainment velocity; a three times more rapid fog-top entrainment enables the cloud base to lift from the ground 90 min earlier in weak stratification than in strong stratification in the model. With relatively dry overlying air, the fog evaporates faster than if the air is near saturation, leading to 70 min earlier dissipation in our simulations. Continuous observations of the temperature and humidity profiles of the layer overlying the fog could therefore be useful for understanding and anticipating fog dissipation.

A scientific approach is presented to aggregate and harmonize a set of 60 geophysical variables at hourly timescale over a decade, and to allow multiannual and multi-variable studies combining atmospheric dynamics and thermodynamics, radiation, clouds and aerosols from ground-based observations. Many datasets from ground-based observations are currently in use worldwide. They are very valuable because they contain complete and precise information due to their spatio-temporal co-localization over more than a decade. These datasets, in particular the synergy between different type of observations, are under-used because of their complexity and diversity due to calibration, quality control, treatment, format, temporal averaging, metadata, etc. Two main results are presented in this article: (1) a set of methods available for the community to robustly and reliably process ground-based data at an hourly timescale over a decade is described and (2) a single netCDF file is provided based on the SIRTA supersite observations. This file contains approximately 60 geophysical variables (atmospheric and in ground) hourly averaged over a decade for the longest variables. The netCDF file is available and easy to use for the community. In this article, observations are re-analyzed. The prefix re refers to six main steps: calibration, quality control, treatment, hourly averaging, homogenization of the formats and associated metadata, as well as expertise on more than a decade of observations. In contrast, previous studies (i) took only some of these six steps into account for each variable, (ii) did not aggregate all variables together in a single file and (iii) did not offer an hourly resolution for about 60 variables over a decade (for the longest variables). The approach described in this article can be applied to different supersites and to additional variables. The main implication of this work is that complex atmospheric observations are made readily available for scientists who are non-experts in measurements. The dataset from SIRTA observations can be downloaded at http://sirta.ipsl.fr/reobs.html (last access: April 2017) (Downloads tab, no password required) under https://doi.org/10.14768/4F63BAD4-E6AF-4101-AD5A-61D4A34620DE.

Le mini-compteur d'aérosols LOAC permet d'obtenir la concentration et la typologie principale des aérosols entre 0,2 et 100 micromètres. Son faible poids permet de l'embarquer sur tous types de ballons atmosphériques (ballons captifs, ballons météorologiques, ballons dérivants, ballons stratosphériques) et à bord de drones. Depuis 2013, LOAC a permis d'obtenir des mesures inédites sur le contenu en aérosols, là où les instruments classiques ne peuvent accéder. Plus d'une centaine de vols a été effectués sous ballons libres. Au-dessus de la Méditerranée, LOAC a mis en évidence la présence de particules supérieurs à 20 micromètres dans des panaches de poussières sahariennes soulevés plusieurs jours auparavant. En Islande, il a effectué des mesures dans un panache volcanique dans la zone de condensation des gaz et lors d'un re-soulèvement de cendres volcanique. LOAC participe aussi aux études d'évènements de pollution urbaine jusqu'à 300 m d'altitude dans Paris et Angers. Enfin, il peut effectuer des mesures précises à bord de drones, comme l'a montré une campagne de mesures au-dessus des pins dans les Landes., The light aerosols counter LOAC allows us to obtain the concentration and the main typology of the aerosols between 0,2 and 100 micrometers. Because of its low weight, LOAC can be used under all kinds of atmospheric balloons (tethered balloons, weather balloons, drifting balloons, stratospheric balloons) and onboard drones. LOAC has obtained original measurements of the aerosol content where traditional instrument cannot be operated. Since 2013, more than one hundred of flights have been conducted under free balloons. Above the Mediterranean Sea, LOAC has detected dust particles greater than 20 micrometers in Saharan plume lifted several days ago. In Iceland, LOAC has performed measurements inside a volcanic plume in the gas-liquid transition zone from, and during an episode of lifted ashes by winds. LOAC is involved in the study of urban pollution up to an altitude of 300 m in Paris and Angers. Finally, LOAC can provide accurate measurement from a drone, as shown above a pine forest.

High uncertainties affect black carbon (BC) emissions, and, despite its important impact on air pollution and climate, very few BC emissions evaluations are found in the literature. This paper presents a novel approach, based on airborne measurements across the Paris, France, plume, developed in order to evaluate BC and NOx emissions at the scale of a whole agglomeration. The methodology consists in integrating, for each transect, across the plume observed and simulated concentrations above background. This allows for several error sources (e.g., representativeness, chemistry, plume lateral dispersion) to be minimized in the model used. The procedure is applied with the CHIMERE chemistry-transport model to three inventories – the EMEP inventory and the so-called TNO and TNO-MP inventories – over the month of July 2009. Various systematic uncertainty sources both in the model (e.g., boundary layer height, vertical mixing, deposition) and in observations (e.g., BC nature) are discussed and quantified, notably through sensitivity tests. Large uncertainty values are determined in our results, which limits the usefulness of the method to rather strongly erroneous emission inventories. A statistically significant (but moderate) overestimation is obtained for the TNO BC emissions and the EMEP and TNO-MP NOx emissions, as well as for the BC / NOx emission ratio in TNO-MP. The benefit of the airborne approach is discussed through a comparison with the BC / NOx ratio at a ground site in Paris, which additionally suggests a spatially heterogeneous error in BC emissions over the agglomeration.

International audience; Despite the knowledge gained on the physical processes dominating the formation, development and dissipation of radiation fog events, uncertainties still exist about the role of the microphysical processes related to aerosol characteristics. The objective of this work is to analyze the sensitivity of fog to aerosols through their impacts on the fog droplets. A radiation fog event that formed on 15/11/2011 at the SIRTA Observatory near Paris in the context of the 2011-2012 ParisFog field campaign is the basis of this study. The selected case is one that initially forms a few hundred meters above the surface and within half an hour lowers down to the surface. A combination of SIRTA's sophisticated observations and 1D numerical simulations is employed with the aim of better understanding the influence of thermodynamics and microphysics on the life-cycle of the fog event and the degree to which aerosol characteristics such as concentration of potentially activated aerosols, size and solubility affect its characteristics. It results that the model simulates fairly well the fog life cycle, with only one half hour advance in the onset and one hour in the dissipation at the surface. The quality of the reference simulation is evaluated against several in-situ and remote sensing measurements. A numerical sensitivity analysis shows that the fog characteristics are strongly influenced by the aerosols. Doubling (halving) the cloud condensation nuclei (CCN) number translates into a 160% increase (65% decrease) in the production of fog droplets, and a 60% increase (40% decrease) of the liquid water path (LWP). The aerosols influence up to 10% the fog geometrical thickness. The necessity for more detailed local forcings that will produce better thermohygrometric conditions in the upper levels above the formed fog layer is underlined, as well as the addition of microphysical measurements in the vertical that will allow to improve two-moment microphysics schemes.

Ground-based microwave radiometers (MWRs) offer the capability to provide continuous, high-temporal resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL) with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP) models through data assimilation. State-of-the-art data assimilation systems (e.g., variational schemes) require an accurate representation of the differences between model (background) and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O-B). Monitoring of O-B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O-B analysis for MWR observations in clear sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB) measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O-B monitoring can effectively detect instrument malfunctions. O-B statistics (bias, standard deviation and root-mean-square) for water vapor channels (22.24–30.0 GHz) are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line center (~ 2–2.5 K) towards the high-frequency wing (~ 0.8–1.3 K). Statistics for zenith and lower elevation observations show a similar trend, though values increase with increasing air mass. O-B statistics for temperature channels show different behaviour for relatively transparent (51–53 GHz) and opaque channels (54-58 GHz). Opaque channels show lower uncertainties (

July 2006 was particularly warm in Europe. The consistency of this kind of anomaly with large-scale circulation conditions or local processes is a key issue for regional climate evolution. Using observations from space and ground-based observatory, together with simulations from regional model, shows that two concomitant but disconnected drivers explain this heatwave. The first driver corresponds to large-scale conditions (specific atmospheric condition with advection of continental air favoring clear sky). The second condition relates to local processes (dry soil, amplifying surface temperature in heatwave for first 5 days, and making this event warm enough to induce a monthly mean anomaly). This large-scale event is studied at a site in northern France, where comprehensive observation data carefully reanalyzed are available. A regional model is able to produce the amplitude of the event, for both temperature and cloud large-scale anomalies. Coupling model and observations allow discriminating the surface contribution to the temperature anomaly.

Nitrous acid measurements were carried out during the MEGAPOLI summer and winter field campaigns at SIRTA observatory in Paris surroundings. Highly variable HONO levels were observed during the campaigns, ranging from 10 ppt to 500 ppt in summer and from 10 ppt to 1.7 ppb in winter. Significant HONO mixing ratios have also been measured during daytime hours, comprised between some tenth of ppt and 200 ppt for the summer campaign and between few ppt and 1 ppb for the winter campaign. Ancillary measurements, such as NOx, O3, photolysis frequencies, meteorological parameters (pressure, temperature, relative humidity, wind speed and wind direction), black carbon concentration, total aerosol surface area, boundary layer height and soil moisture, were conducted during both campaigns. In addition, for the summer period, OH radical measurements were made with a CIMS (Chemical Ionisation Mass Spectrometer). This large dataset has been used to investigate the HONO budget in a suburban environment. To do so, calculations of HONO concentrations using PhotoStationary State (PSS) approach have been performed, for daytime hours. The comparison of these calculations with measured HONO concentrations revealed an underestimation of the calculations making evident a missing source term for both campaigns. This unknown HONO source exhibits a bell-shaped like average diurnal profile with a maximum around noon of approximately 0.7 ppb h−1 and 0.25 ppb h−1, during summer and winter respectively. This source is the main HONO source during daytime hours for both campaigns. In both cases, this source shows a slight positive correlation with J(NO2) and the product between J(NO2) and soil moisture. This original approach had, thus, indicated that this missing source is photolytic and might be heterogeneous occurring at ground surface and involving water content available on the ground., Atmospheric Chemistry and Physics, 14 (6), ISSN:1680-7375, ISSN:1680-7367

Nowadays, more than 50% of the global population leave in urban centers which activities generate large anthropogenic emissions of CO2 (more than 70% of fossil fuel CO2 comes from urbanized/industrialized areas) and reactive gases that endanger our climate, the health of human beings and surrounding ecosystems. The worst situations are encountered during urban pollution events that usually form under anticyclonic conditions. Analyzing the contribution of the local and regional sources of urban CO2 and co-emitted species vs the remote ones, as well as the nature of these sources and the dynamical processes that lead to the building of such events can provide interesting knowledge for helping urban policy makers to better identify the role of anthropogenic/biogenic sources on the urban air composition and to take proper decisions in matter of CO2 and pollutants sources mitigation. With 12 million of people, Paris (France) is the second megacity in Europe. In 2016, two pollution events occured in the Paris region during which the instrumental platform OCAPI (http://observations.ipsl.fr/composition-atmospherique-en-idf.html) from IPSL (Institut Pierre Simon Laplace) was mobilized in collaboration with air quality governing actors (AIRPARIF, INERIS) to collect a bunch of observations. Five sites located in the urban, peri-urban and rural areas of Paris were equiped with in-situ analyzers (CO2, CO, black carbon, 13CO2, COS) ; Fourier transform spectrometers for column measurements (XCO2, XCO, XCOS), particle filters (for aerosols size and content analysis) ; air samples (levoglucosan, 14CO2, VOCs) ; and Lidar profilers (boundary layer height ; wind profiles). These data, combined with a backtrajectories analysis, give information about the dynamical processes that lead to the formation of the pollution events and on the contribution of local, regional and remote sources. The analysis of the correlations between the trace species and of the isotopic content of carbon in CO2 provides further clues on the nature of the anthropogenic and biogenic sources involved in the urban pollution events. Especially, the role of agricultural spreading through the observation of ammonium nitrate particles and the contribution of biomass burning through levoglucosan and black carbon measurements will be discussed.

International audience; Within the framework of a French nationally funded project (CO2-MEGAPARIS) for quantifying the CO2 emissions of the Paris area, a lidar-based experimental investigation of the variability of the atmospheric boundary layer (ABL) depths was performed over four days in March 2011 under clear sky conditions. The prevailing synoptic settings were mainly characterized by anti-cyclonic situations with low wind. The key aim of this paper is to assess the impact of the urban heat island intensity (UHII) on the spatio-temporal variability of the ABL depths over the Paris megacity. A network of fixed aerosol lidars was deployed inside the city and in the vicinity of sub-urban and rural areas. Additionally, the spatial heterogeneity of the nocturnal boundary layer (NBL) depths over greater Paris area is addressed, thanks in particular, to the deployment of a 355-nm elastic lidar in a mobile van to measure the aerosol distributions. Radiosonde-derived profiles (twice a day) of thermodynamic variables over the sub-urban site helped investigate the temperature inversion above ground and hence to compare the lidar-derived ABL depths. Comparing these two results, an excellent concordance was found with a correlation coefficient of 0.994. Five important factors closely related to the ABL circulation, namely, spatio-temporal variability of the ABL depths, growth rate of the ABL depths, entrainment zone thickness, and near-surface temperature fields including resultant UHII were considered to infer the urban-rural contrasts. The mean NBL depth over the urban area was on average 63 m (45%) higher than its adjacent sub-urban area which was, on occasion, as much as (74 m) 58% higher mainly due to the effect of UHII. Daytime well-mixed convective boundary layer and associated strong turbulent mixing near its top over the urban area showed higher entrainment zone thickness (326 m) than over sub-urban (234 m) and rural (200 m) areas. Temperature growth rates during sunrise increased up to more than 3 °C h−1 over the sub-urban area while over the urban region it was 2.5 °C h−1 or even less. The ABL depths over the urban site decayed more slowly (500 m h−1) than over the sub-urban area (600 m h−1) during the late afternoon transition period suggesting an impact of the UHII on the ABL dynamics over the urban area.

The study of aerosols in the troposphere and in the stratosphere is of major importance both for climate and air quality studies. Among the numerous instruments available, optical aerosol particles counters (OPCs) provide the size distribution in diameter range from about 100 nm to a few tens of µm. Most of them are very sensitive to the nature of aerosols, and this can result in significant biases in the retrieved size distribution. We describe here a new versatile optical particle/sizer counter named LOAC (Light Optical Aerosol Counter), which is light and compact enough to perform measurements not only at the surface but under all kinds of balloons in the troposphere and in the stratosphere. LOAC is an original OPC performing observations at two scattering angles. The first one is around 12°, and is almost insensitive to the refractive index of the particles; the second one is around 60° and is strongly sensitive to the refractive index of the particles. By combining measurement at the two angles, it is possible to retrieve the size distribution between 0.2 and 100 µm and to estimate the nature of the dominant particles (droplets, carbonaceous, salts and mineral particles) when the aerosol is relatively homogeneous. This typology is based on calibration charts obtained in the laboratory. The uncertainty for total concentrations measurements is ±20 % when concentrations are higher than 1 particle cm−3 (for a 10 min integration time). For lower concentrations, the uncertainty is up to about ±60 % for concentrations smaller than 10−2 particle cm−3. Also, the uncertainties in size calibration are ±0.025 µm for particles smaller than 0.6 µm, 5 % for particles in the 0.7–2 µm range, and 10 % for particles greater than 2 µm. The measurement accuracy of submicronic particles could be reduced in a strongly turbid case when concentration of particles > 3 µm exceeds a few particles cm−3. Several campaigns of cross-comparison of LOAC with other particle counting instruments and remote sensing photometers have been conducted to validate both the size distribution derived by LOAC and the retrieved particle number density. The typology of the aerosols has been validated in well-defined conditions including urban pollution, desert dust episodes, sea spray, fog, and cloud. Comparison with reference aerosol mass monitoring instruments also shows that the LOAC measurements can be successfully converted to mass concentrations.

International audience; The physical and chemical aerosol properties are explored here based on ground-based observations in the Paris region to better understand the role of clouds, radiative fluxes and dynamics on aerosol loading during a heavy regional air pollution that occurred in March 2014 over North-Western Europe. This event is primarily characterized by a fine particle mass (PM2.5) increase from 10 to more than 120 μg m−3 and a simultaneous decrease of the horizontal visibility from 40 to 1 km, mainly due to significant formation of ammonium nitrate particles. The aerosol optical depth (AOD) at 550 nm increased steadily from about 0.06 on March 6 to more than 0.9 five days later. The scattering of the solar radiation by polluted particles induced, at the peak of the heavy pollution event, an instantaneous shortwave flux decrease of about 300 W m−2 for direct irradiance and an increase of about 150 W m−2 for diffuse irradiance (only scattering). The mean surface aerosol effect efficiency (effect per unit optical depth) is of about −80 W m−2 with a mean aerosol direct radiative effect of −23 W m−2. The dynamical and radiative processes that can be responsible for the diurnal cycle of PM2.5 in terms of amplitude and timing are investigated. A comparative analysis is performed for 4 consecutive days (between March 11 and 14), showing that the PM2.5 diurnal cycle can be modulated in time and amplitude by local processes such as the boundary layer depth development (ranging from 100 m to 1350 m), surface relative humidity (100%–35%), thermal structure (10 °C–16 °C for day/night amplitude), dynamics (wind speed ranging from 4 m s−1 to 1.5 m s−1) and turbulence (turbulent kinetic energy reaching 2 m2 s−2) near the surface and wind shear along the vertical. Finally, modeled and measured surface PM2.5 loadings are also compared here, notably illustrating the need of accurate boundary layer depth data for efficient air quality forecasts.

International audience; The data from suite of in situ sensors, passive and active remote sensing instruments dedicated to document simultaneously radiative and thermo-dynamical processes driving the fog life cycle at the SIRTA Observatory (instrumented site for atmospheric remote sensing research) near Paris during two periods of 6 months are analysed. The study focuses on the analysis of the relative role of key physical processes and their interactions during fog formation, development and dissipation phases. This work presents, from analysis of detailed observations, the range of values that critical parameters have to take for fog and quasi-fog formation. In our study, we consider fog (horizontal visibility lower than 1 km, a dataset of 300 h) and quasi-fog (horizontal visibility ranging from 1 to 2 km, a dataset of 400 h) events induced by radiative cooling (53 events) and stratus lowering (64 events). For the radiative fog events, (with radiative cooling during prefog conditions), we note that the longwave net radiative flux (around -60 ± 5 W/m2) induces a cooling of the surface layer. The vertical structure of this cooling is controlled by dynamics, that is, wind shear and horizontal and vertical velocities. In case of very low mixing (wind speed below 0.6 m/s), the thermal stability is very strong with a temperature inversion around 3.5 °C for 10 m and a humidity gradient reaching 10 % preventing vertical development of the fog layer. For stratus-lowering fog events, the altitude of the stratus layer, the vertical mixing and the absolute value of humidity are driving parameters of the fog formation. Our statistical analysis shows that a stratus cloud with a cloud base around 170 m and with a small cloud-base subsidence rate of 50 m/h leads to fog, whereas a stratus cloud with a base around 800 m agl, with a larger cloud-base subsidence rate of 190 m/h conducts to quasi-fog situations with an important increase of the stratus liquid water path.

International audience; We compare in this study two simple optical setups to measure the atmospheric turbulence characterized by the refractive index structure parameter [View the MathML source] Cn2. The corresponding heat flux values sensed by the laser beam propagation are calculated leading to the plant evapotranspiration. The results are discussed and compared to measurements obtained with a well-known and calibrated eddy-covariant instrument. A fine analysis gives a good insight of the accuracy of the optical devices proposed here to measure the crop evapotranspiration. Additional evapotranspiration values calculated with meteorological sensor data and the use of different models are also compared in parallel.

The EURODELTA III exercise has facilitated a comprehensive intercomparison and evaluation of chemistry transport model performances. Participating models performed calculations for four 1-month periods in different seasons in the years 2006 to 2009, allowing the influence of different meteorological conditions on model performances to be evaluated. The exercise was performed with strict requirements for the input data, with few exceptions. As a consequence, most of differences in the outputs will be attributed to the differences in model formulations of chemical and physical processes. The models were evaluated mainly for background rural stations in Europe. The performance was assessed in terms of bias, root mean square error and correlation with respect to the concentrations of air pollutants (NO2, O3, SO2, PM10 and PM2.5), as well as key meteorological variables. Though most of meteorological parameters were prescribed, some variables like the planetary boundary layer (PBL) height and the vertical diffusion coefficient were derived in the model preprocessors and can partly explain the spread in model results. In general, the daytime PBL height is underestimated by all models. The largest variability of predicted PBL is observed over the ocean and seas. For ozone, this study shows the importance of proper boundary conditions for accurate model calculations and then on the regime of the gas and particle chemistry. The models show similar and quite good performance for nitrogen dioxide, whereas they struggle to accurately reproduce measured sulfur dioxide concentrations (for which the agreement with observations is the poorest). In general, the models provide a close-to-observations map of particulate matter (PM2.5 and PM10) concentrations over Europe rather with correlations in the range 0.4–0.7 and a systematic underestimation reaching −10 µg m−3 for PM10. The highest concentrations are much more underestimated, particularly in wintertime. Further evaluation of the mean diurnal cycles of PM reveals a general model tendency to overestimate the effect of the PBL height rise on PM levels in the morning, while the intensity of afternoon chemistry leads formation of secondary species to be underestimated. This results in larger modelled PM diurnal variations than the observations for all seasons. The models tend to be too sensitive to the daily variation of the PBL. All in all, in most cases model performances are more influenced by the model setup than the season. The good representation of temporal evolution of wind speed is the most responsible for models' skillfulness in reproducing the daily variability of pollutant concentrations (e.g. the development of peak episodes), while the reconstruction of the PBL diurnal cycle seems to play a larger role in driving the corresponding pollutant diurnal cycle and hence determines the presence of systematic positive and negative biases detectable on daily basis.

The study assesses the contribution of aerosols to the extinction of visible radiation in the mist–fog–mist cycle. Relative humidity is large in the mist–fog–mist cycle, and aerosols most efficient in interacting with visible radiation are hydrated and compose the accumulation mode. Measurements of the microphysical and optical properties of these hydrated aerosols with diameters larger than 0.4 μm were carried out near Paris, during November 2011, under ambient conditions. Eleven mist–fog–mist cycles were observed, with a cumulated fog duration of 96 h, and a cumulated mist–fog–mist cycle duration of 240 h. In mist, aerosols grew by taking up water at relative humidities larger than 93%, causing a visibility decrease below 5 km. While visibility decreased down from 5 to a few kilometres, the mean size of the hydrated aerosols increased, and their number concentration (Nha) increased from approximately 160 to approximately 600 cm−3. When fog formed, droplets became the strongest contributors to visible radiation extinction, and liquid water content (LWC) increased beyond 7 mg m−3. Hydrated aerosols of the accumulation mode co-existed with droplets, as interstitial non-activated aerosols. Their size continued to increase, and some aerosols achieved diameters larger than 2.5 μm. The mean transition diameter between the aerosol accumulation mode and the small droplet mode was 4.0 ± 1.1 μm. Nha also increased on average by 60 % after fog formation. Consequently, the mean contribution to extinction in fog was 20 ± 15% from hydrated aerosols smaller than 2.5 μm and 6 ± 7% from larger aerosols. The standard deviation was large because of the large variability of Nha in fog, which could be smaller than in mist or 3 times larger. The particle extinction coefficient in fog can be computed as the sum of a droplet component and an aerosol component, which can be approximated by 3.5 Nha (Nha in cm−3 and particle extinction coefficient in Mm−1. We observed an influence of the main formation process on Nha, but not on the contribution to fog extinction by aerosols. Indeed, in fogs formed by stratus lowering (STL), the mean Nha was 360 ± 140 cm−3, close to the value observed in mist, while in fogs formed by nocturnal radiative cooling (RAD) under cloud-free sky, the mean Nha was 600 ± 350 cm−3. But because visibility (extinction) in fog was also lower (larger) in RAD than in STL fogs, the contribution by aerosols to extinction depended little on the fog formation process. Similarly, the proportion of hydrated aerosols over all aerosols (dry and hydrated) did not depend on the fog formation process. Measurements showed that visibility in RAD fogs was smaller than in STL fogs due to three factors: (1) LWC was larger in RAD than in STL fogs, (2) droplets were smaller, (3) hydrated aerosols composing the accumulation mode were more numerous.