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Existing CO2 emissions reported by city inventories usually lag real-time by a year or more and are prone to large uncertainties. This study responds to the growing need for timely and precise estimation of urban CO2 emissions to support the present and future mitigation measures and policies. We focus on the Paris metropolitan area, the largest urban region in the European Union and the city with the densest atmospheric CO2 observation network in Europe. We performed long-term atmospheric inversions to quantify the citywide CO2 emissions, both fossil fuel and biogenic sources and sinks, over six years (2016–2021) using a Bayesian inverse modeling system. Our inversion framework benefits from a novel near-real-time hourly fossil fuel CO2 emission inventory (Origins.earth) at 1 km spatial resolution. In addition to the mid-afternoon observations, we attempt to assimilate morning CO2 concentrations based on the ability of the WRF-Chem transport model to simulate atmospheric boundary layer dynamics constrained by observed layer heights. Our results show a long-term decreasing trend by around 2 % per year in annual CO2 emissions over the Paris region. The impact of COVID-19 pandemic led to a 13 %±1 % reduction in annual fossil fuel CO2 emissions in 2020 with respect to 2019. Then, annual emissions increased by 5.2 % from 32.6±2.2 MtCO2 in 2020 to 34.3±2.3 MtCO2 in 2021. Based on a combination of up-to-date inventories, high-resolution atmospheric modeling, and high-precision observations, our current capacity could deliver near real-time CO2 emission estimates at city scale in less than a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.

The atmospheric boundary layer (ABL) defines the volume of air adjacent to the Earth’s surface for the dilution of heat, moisture, and trace substances. Quantitative knowledge on the temporal and spatial variations in the heights of the ABL and its sub-layers is still scarce, despite their importance for a series of applications (including, for example, air quality, numerical weather prediction, greenhouse gas assessment, and renewable energy production). Thanks to recent advances in ground-based remote-sensing measurement technology and algorithm development, continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution is increasingly possible. Dense measurement networks of autonomous ground-based remote-sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers are hence emerging across Europe and other parts of the world. This review summarises the capabilities and limitations of various instrument types for ABL monitoring and provides an overview on the vast number of retrieval methods developed for the detection of ABL sublayer heights from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, pointing out where instrumental or methodological synergy are considered particularly promising. The review highlights the fact that harmonised data acquisition across carefully designed sensor networks as well as tailored data processing are key to obtaining high-quality products that are again essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe., European Cooperation in Science and Technology (COST) PTDC/CTAMET/29678/2017 European Commission, French National Research Agency (ANR) Region Ile-de-France, Spanish Government, Junta de Andalucia, University of Granada, Programa Operativo FEDER Andalucia 2014-2020, Earth System Excellence Units Program, Marie Sklodowska-Curie Action Cofund 2016 EU project - Athenea3i national Portuguese funds through FCT - Fundacao para a Ciencia e Tecnologia, I.P. CA18235 871115 101036245 ANR-20-CE22-0013 PID2020-120015RB-I00 PID2020.117825GB.C21 P18-RT-3820 P20-00136 A-RNM-430-UGR20 754446 UIDB/04683/2020

The atmospheric boundary layer (ABL) is the layer closest to the Earth’s surface within which most human activities take place. The vertical profile of atmospheric thermodynamic parameters in the ABL impact weather, air quality and climate. However, surface sensor networks and satellite observations do not provide sufficient information on the high temporal variability and strong vertical gradients that occur in the ABL. Thus, the ABL represents an important but rather under-sampled part of the atmosphere. This observational gap currently hampers progress in numerical weather prediction, air quality forecasting and climate assessment. Due to recent technological and methodological advances, ground-based remote sensing instruments are now able to provide high-quality profiles of ABL parameters such as temperature, humidity, wind, aerosol and cloud properties. However, even though state-of-the-art ABL profilers are deployed at numerous sites in Europe, efficient science and technology networking and coordination is still required to exploit this rich dataset effectively. The current lack of data and procedure harmonization often diminishes the potential societal benefits of the existing ABL profiling data. This paper introduces PROBE, a new initiative funded by the European Cooperation in Science and Technology (COST), that aims to broaden the bridge between a wide range of user needs and the science and technology expertise residing in industry and academia, while strengthening and harmonizing methods and procedures to yield higher quality ABL observational data. Here, the challenges, objectives and implementation plan for PROBE are described, highlighting some preliminary results that will be further developed into operational applications during the 4-year duration (2019–2023) of this collaborative project.

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.

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.

Observations of profiles of winds, aerosol, clouds, winds, temperature and humidity in the lowest few km of the atmosphere from networks of ceilometers, Doppler wind lidars and microwave radiometers are starting to flow in real time to forecasting centers in Europe.\ud \ud To realise the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few km are hardly accessible by satellite, especially in dynamically-active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real-time to forecast centers. The three classes of instruments are: (i) Automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog and volcanic ash, the last two being especially important for air traffic control; (ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind-gusts and low-level jets; and (iii) Microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. Twenty-two European countries and fifteen European National Weather Services are collaborating in the project, that involves the implementation of common operating procedures, instrument calibrations, data formats and retrieval algorithms. Currently, data from 220 ceilometers in 17 countries are being distributed in near real-time to national weather forecast centers; this should soon rise to many hundreds. The wind lidars should start delivering real time data in late 2018, and the plan is to incorporate the microwave radiometers in 2019. Initial data assimilation tests indicate a positive impact of the new data.

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.

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.

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.

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.

Air quality in cities is influenced not only by emissions and chemical transformations but also by the physical state of the atmosphere which varies both temporally and spatially. Increasingly, tall buildings (TB) are common features of the urban landscape, yet their impact on urban air flow and dispersion is not well understood, and their effects are not appropriately captured in parameterisation schemes. Here, hardware models of areas within two global mega-cities (London and Beijing) are used to analyse the impact of TB on flow and transport in isolated and cluster settings. Results show that TB generate strong updrafts and downdrafts that affect street-level flow fields. Velocity differences do not decay monotonically with distance from the TB, especially in the near-wake region where the flow is characterised by recirculating winds and jets. Lateral distance from an isolated TB centreline is crucial, and flow is still strongly impacted at longitudinal distances of several TB heights. Evaluation of a wake-flow scheme (ADMS-Build) in the isolated TB case indicates important characteristics are not captured. There is better agreement for a slender, shorter TB than a taller non-cuboidal TB. Better prediction of flow occurs horizontally further away and vertically further from the surface. TB clusters modify the shape of pollutant plumes. Strong updrafts generated by the overlapping wakes of TB clusters lift pollutants out of the canopy, causing a much deeper tracer plume in the lee of the cluster, and an elevated plume centreline with maximum concentrations around the TB mean height. Enhanced vertical spread of the pollutants in the near-wake of the cluster results in overall lower maximum concentrations, but higher concentrations above the mean TB height. These results have important implications for interpreting observations in areas with TB. Using real world ceilometer observations in two mega-cities (Beijing and Paris), we assess the diurnal seasonal variability of the urban boundary layer and evaluate a mixed layer height (MLH) empirical model with parameters derived from a third mega-city (London). The MLH model works well in central Beijing but less well in suburban Paris. The variability of the physical meteorology across different vertical scales discussed in this paper provides additional context for interpreting air quality observations.

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.

International audience

The worldwide growing development of PV capacity requires an accurate forecast for a safer and cheaper PV grid penetration. Solar energy variability mainly depends on cloud cover evolution. Thus, relationships between weather variables and forecast uncertainties may be quantified to optimize forecast use. An intraday solar energy forecast algorithm using satellite images is fully described and validated over three years in the Paris (France) area. For all tested horizons (up to 6 h), the method shows a positive forecast skill score compared to persistence (up to 15%) and numerical weather predictions (between 20% and 40%). Different variables, such as the clear-sky index (Kc), solar zenith angle (SZA), surrounding cloud pattern observed by satellites and northern Atlantic weather regimes have been tested as predictors for this forecast method. Results highlighted an increasing absolute error with a decreasing SZA and Kc. Root mean square error (RMSE) is significantly affected by the mean and the standard deviation of the observed Kc in a 10 km surrounding area. The highest (respectively, lowest) errors occur at the Atlantic Ridge (respectively, Scandinavian Blocking) regime. The differences of relative RMSE between these two regimes are from 8% to 10% in summer and from 18% to 30% depending on the time horizon. These results can help solar energy users to anticipate—at the forecast start time and up to several days in advance—the uncertainties of the intraday forecast. The results can be used as inputs for other solar energy forecast methods.

Air pollution, in particular high concentrations of particulate matter smaller than 1 µm in diameter (PM1), continues to be a major health problem, and meteorology is known to substantially influence atmospheric PM concentrations. However, the scientific understanding of the ways in which complex interactions of meteorological factors lead to high-pollution episodes is inconclusive. In this study, a novel, data-driven approach based on empirical relationships is used to characterize and better understand the meteorology-driven component of PM1 variability. A tree-based machine learning model is set up to reproduce concentrations of speciated PM1 at a suburban site southwest of Paris, France, using meteorological variables as input features. The model is able to capture the majority of occurring variance of mean afternoon total PM1 concentrations (coefficient of determination (R2) of 0.58), with model performance depending on the individual PM1 species predicted. Based on the models, an isolation and quantification of individual, season-specific meteorological influences for process understanding at the measurement site is achieved using SHapley Additive exPlanation (SHAP) regression values. Model results suggest that winter pollution episodes are often driven by a combination of shallow mixed layer heights (MLHs), low temperatures, low wind speeds, or inflow from northeastern wind directions. Contributions of MLHs to the winter pollution episodes are quantified to be on average ∼5 µg/m3 for MLHs below m a.g.l. Temperatures below freezing initiate formation processes and increase local emissions related to residential heating, amounting to a contribution to predicted PM1 concentrations of as much as ∼9 µg/m3. Northeasterly winds are found to contribute ∼5 µg/m3 to predicted PM1 concentrations (combined effects of u- and v-wind components), by advecting particles from source regions, e.g. central Europe or the Paris region. Meteorological drivers of unusually high PM1 concentrations in summer are temperatures above ∼25 ∘C (contributions of up to ∼2.5 µg/m3), dry spells of several days (maximum contributions of ∼1.5 µg/m3), and wind speeds below ∼2 m/s (maximum contributions of ∼3 µg/m3), which cause a lack of dispersion. High-resolution case studies are conducted showing a large variability of processes that can lead to high-pollution episodes. The identification of these meteorological conditions that increase air pollution could help policy makers to adapt policy measures, issue warnings to the public, or assess the effectiveness of air pollution measures.

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.

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.

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).

Six months of stratospheric aerosol observations with the European Aerosol Research Lidar Network (EARLINET) from August 2017 to January 2018 are presented. The decay phase of an unprecedented, record-breaking stratospheric perturbation caused by wildfire smoke is reported and discussed in terms of geometrical, optical, and microphysical aerosol properties. Enormous amounts of smoke were injected into the upper troposphere and lower stratosphere over fire areas in western Canada on 12 August 2017 during strong thunderstorm–pyrocumulonimbus activity. The stratospheric fire plumes spread over the entire Northern Hemisphere in the following weeks and months. Twenty-eight European lidar stations from northern Norway to southern Portugal and the eastern Mediterranean monitored the strong stratospheric perturbation on a continental scale. The main smoke layer (over central, western, southern, and eastern Europe) was found at heights between 15 and 20 km since September 2017 (about 2 weeks after entering the stratosphere). Thin layers of smoke were detected at heights of up to 22–23 km. The stratospheric aerosol optical thickness at 532 nm decreased from values > 0.25 on 21–23 August 2017 to 0.005–0.03 until 5–10 September and was mainly 0.003–0.004 from October to December 2017 and thus was still significantly above the stratospheric background (0.001–0.002). Stratospheric particle extinction coefficients (532 nm) were as high as 50–200 Mm−1 until the beginning of September and on the order of 1 Mm−1 (0.5– 5 Mm−1 ) from October 2017 until the end of January 2018. The corresponding layer mean particle mass concentration was on the order of 0.05–0.5 µg m−3 over these months. Soot particles (light-absorbing carbonaceous particles) are efficient ice-nucleating particles (INPs) at upper tropospheric (cirrus) temperatures and available to influence cirrus formation when entering the tropopause from above. We estimated INP concentrations of 50–500 L−1 until the first days in September and afterwards 5–50 L−1 until the end of the year 2017 in the lower stratosphere for typical cirrus formation temperatures of −55 ◦C and an ice supersaturation level of 1.15. The measured profiles of the particle linear depolarization ratio indicated a predominance of nonspherical smoke particles. The 532 nm depolarization ratio decreased slowly with time in the main smoke layer from values of 0.15–0.25 (August–September) to values of 0.05–0.10 (October–November) and < 0.05 (December–January). The decrease of the depolarization ratio is consistent with aging of the smoke particles, growing of a coating around the solid black carbon core (aggregates), and thus change of the shape towards a spherical form. We found ascending aerosol layer features over the most southern European stations, especially over the eastern Mediterranean at 32–35◦ N, that ascended from heights of about 18–19 to 22–23 km from the beginning of October to the beginning of December 2017 (about 2 km per month). We discuss several transport and lifting mechanisms that may have had an impact on the found aerosol layering structures.

Wood burning is widely used for domestic heating and has been identified as a ubiquitous pollution source in urban areas, especially during cold months. The present study is based on a three and a half winter months field campaign in the Paris region measuring Volatile Organic Compounds (VOCs) by Proton Transfer Reaction Mass Spectrometry (PTR-MS) in addition to Black Carbon (BC). Several VOCs were identified as strongly wood burning-influenced (e.g., acetic acid, furfural), or traffic-influenced (e.g., toluene, C8-aromatics). Methylbutenone, benzenediol and butandione were identified for the first time as wood burning-related in ambient air. A Positive Matrix Factorization (PMF) analysis highlighted that wood burning is the most important source of VOCs during the winter season. (47%). Traffic was found to account for about 22% of the measured VOCs during the same period, whereas solvent use plus background accounted altogether for the remaining fraction. The comparison with the regional emission inventory showed good consistency for benzene and xylenes but revisions of the inventory should be considered for several VOCs such as acetic acid, C9-aromatics and methanol. Finally, complementary measurements acquired simultaneously at other sites in Île-de-France (the Paris region) enabled evaluation of spatial variabilities. The influence of traffic emissions on investigated pollutants displayed a clear negative gradient from roadside to suburban stations, whereas wood burning pollution was found to be fairly homogeneous over the region.

International audience; Six months of stratospheric aerosol observations with the European Aerosol Research Lidar Network (EARLINET) from August 2017 to January 2018 are presented. The decay phase of an unprecedented, record-breaking stratospheric perturbation caused by wildfire smoke is reported and discussed in terms of geometrical, optical, and microphysical aerosol properties. Enormous amounts of smoke were injected into the upper troposphere and lower stratosphere over fire areas in western Canada on 12 August 2017 during strong thunderstorm-pyrocumulonimbus activity. The stratospheric fire plumes spread over the entire Northern Hemisphere in the following weeks and months. Twenty-eight European lidar stations from northern Norway to southern Portugal and the eastern Mediterranean monitored the strong stratospheric perturbation on a continental scale. The main smoke layer (over central, western, southern, and eastern Europe) was found at heights between 15 and 20 km since September 2017 (about 2 weeks after entering the stratosphere). Thin layers of smoke were detected at heights of up to 22-23 km. The stratospheric aerosol optical thickness at 532 nm decreased from values > 0.25 on 21-23 August 2017 to 0.005-0.03 until 5-10 September and was mainly 0.003-0.004 from October to December 2017 and thus was still significantly above the stratospheric background (0.001-0.002). Stratospheric particle extinction coefficients (532 nm) were as high as 50-200 Mm-1 until the beginning of September and on the order of 1 Mm-1 (0.5-5 Mm-1) from October 2017 until the end of January 2018. The corresponding layer mean particle mass concentration was on the order of 0.05-0.5 µg m-3 over these months. Soot particles (light-absorbing carbonaceous particles) are efficient ice-nucleating particles (INPs) at upper tropospheric (cirrus) temperatures and available to influence cirrus formation when entering the tropopause from above. We estimated INP concentrations of 50-500 L-1 until the first days in September and afterwards 5-50 L-1 until the end of the year 2017 in the lower stratosphere for typical cirrus formation temperatures of -55 ∘C and an ice supersaturation level of 1.15. The measured profiles of the particle linear depolarization ratio indicated a predominance of nonspherical smoke particles. The 532 nm depolarization ratio decreased slowly with time in the main smoke layer from values of 0.15-0.25 (August-September) to values of 0.05-0.10 (October-November) and < 0.05 (December-January). The decrease of the depolarization ratio is consistent with aging of the smoke particles, growing of a coating around the solid black carbon core (aggregates), and thus change of the shape towards a spherical form. We found ascending aerosol layer features over the most southern European stations, especially over the eastern Mediterranean at 32-35∘ N, that ascended from heights of about 18-19 to 22-23 km from the beginning of October to the beginning of December 2017 (about 2 km per month). We discuss several transport and lifting mechanisms that may have had an impact on the found aerosol layering structures.

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.

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.

The ultraviolet index (UVI) is an important tool to raise public awareness of the risks of solar radiation overexposure. However, solar ultraviolet radiation instruments are relatively expensive, and the deployment and maintenance of a large-scale network proved impractical. In this paper, we describe a simple method for UVI and daily erythemal dose retrieval from photosynthetically active radiation (PAR – 0.40–0.70 μm) measurements. These latter are generally performed by cheaper instruments and commonly found in any ordinary meteorological station. Despite the different interactions involving UV and PAR radiation with the atmospheric components, our method is based on the solar position and cloud modification factor (CMF) that exert a quite similar influence on these electromagnetic radiation bands. We also show that this method is not suitable for shortwave radiation sensors (0.25–4.00 μm). A large dataset was used to test this method and the comparisons between UVI measurements and inferences are comparable to the instrumental errors. Thus, in this paper we show a 2nd degree regression equation for obtaining erythemal UV from PAR measurements.

Long-range transported smoke aerosols in the UTLS (Upper Troposphere/Lower Stratosphere) over Europe were detected in Summer 2017. The measurements of ground-based instruments and satellite sensors indicate that the UTLS aerosol layers were originated from Canadian wildfires and were transported to Europe by UTLS advection. In this study, the observations of two multi-wavelength Raman Lidar systems in northern France (Lille and Palaiseau) are used to derive aerosol properties, such as optical depth of the UTLS layer, Lidar ratios at 355 and 532 nm and particle linear depolarization ratios at 355, 532 and 1064 nm. The optical depth of the UTLS layers at 532 nm varies from 0.05 to above 0.20, with very weak spectral dependence between 355 and 532 nm. Lidar ratios at 355 nm are in 31 ± 15 sr to 45 ± 9 sr range and at 532 nm, the Lidar ratios are in the range of 54 ± 12 sr to 58 ± 9 sr. Such spectral dependence of Lidar ratio is known to be a characteristic feature of aged smoke. The typical particle depolarization ratios in the UTLS smoke layer are 25 ± 4 % at 355 nm, 19 ± 3 % at 532 nm and 4.5 ± 0.8 % at 1064 nm. The relatively high depolarization ratios and such spectral dependence are an indication of a complicated morphology of aged smoke particles. We found an increase of depolarization ratio versus transport time. The depolarization ratio at 532 nm increases from below 2–5 % for fresh smoke to over 20 % for smoke aged more than 20 days. The 3 β + 2 α observations of two cases at Palaiseau and Lille sites were inverted to the aerosol microphysical properties using regularization algorithm. The particles distribute in the 0.1–1.0 μm range with effective radius of 0.33 ± 0.10 μm for both cases. The derived complex refractive indices are 1.52 (± 0.05) + i 0.021 (± 0.010) and 1.55 (± 0.05) + i 0.028 (± 0.014) for Palaiseau and Lille data. The retrieved aerosol properties were used to calculate the direct radiative forcing (DRF) effect specific to the UTLS aerosol layers. The simulations derive daily net DRF efficiency of −79.6 W m −2 τ −1 at the bottom of the atmosphere for Lille observations. At the top of the atmosphere, the net DRF efficiency is −7.9 W m −2 τ −1 . The results indicate that the UTLS aerosols strongly reduce the radiation reaching the terrestrial surface by absorption. The heating rate of the UTLS layers is estimated to be 3.7 K day −1 . The inversion of Palaiseau data leads to similar results. The heating rate predicts a temperature increase within the UTLS aerosol layer, which has been observed by the radiosonde temperature measurements.

The fast development of solar radiation and energy applications, such as photovoltaic and solar thermodynamic systems, has increased the need for solar radiation measurement and monitoring, not only for the global component but also for the diffuse and direct. End users look for the best compromise between getting close to state-of-the-art measurements and keeping low capital, maintenance and operating costs. Among the existing commercial options, SPN1 is a relatively low cost solar radiometer that estimates global and diffuse solar irradiances from seven thermopile sensors under a shading mask and without moving parts. This work presents a comprehensive study of SPN1 accuracy and sources of uncertainty, which results from laboratory experiments, numerical modeling and comparison studies between measurements from this sensor and state-of-the art instruments for six diverse sites. Several clues are provided for improving the SPN1 accuracy and agreement with state-of-the art measurements.

Small changes in the radiation budget at the earth’s surface can lead to large climatological responses when persistent over time. With the increasing debate on anthropogenic influences on climatic processes during the 1980s the need for accurate radiometric measurements with higher temporal resolution was identified, and it was determined that the existing measurement networks did not have the resolution or accuracy required to meet this need. In 1988 the WMO therefore proposed the establishment of a new international Baseline Surface Radiation Network (BSRN), which should collect and centrally archive high quality ground-based radiation measurements in 1-minute resolution. BSRN began its work in 1992 with 9 stations, currently (status 2018-01-01), the network comprises 59 stations (with data) and 9 candidates (stations recently accepted into the network with data forthcoming to the archive) distributed over all continents. The BSRN database is the World Radiation Monitoring Center. It is hosted at the Alfred Wegener Institute in Bremerhaven, Germany and now offers more than 10 300 months of data from the years 1992 to 2017. All data are available at https://doi.pangaea.de/10.1594/PANGAEA.880000 free of charge.

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.

International audience; The present study aimed at performing PM10 source apportionment, using positive matrix factorization (PMF), based on filter samples collected every 4 h at a sub-urban station in the Paris region (France) during a PM pollution event in March 2015 (PM10 > 50 μg m−3 for several consecutive days). The PMF model allowed to deconvolve 11 source factors. The use of specific primary and secondary organic molecular markers favoured the determination of common sources such as biomass burning and primary traffic emissions, as well as 2 specific biogenic SOA (marine + isoprene) and 3 anthropogenic SOA (nitro-PAHs + oxy-PAHs + phenolic compounds oxidation) factors. This study is probably the first one to report the use of methylnitrocatechol isomers as well as 1-nitropyrene to apportion secondary OA linked to biomass burning emissions and primary traffic emissions, respectively. Secondary organic carbon (SOC) fractions were found to account for 47% of the total OC. The use of organic molecular markers allowed the identification of 41% of the total SOC composed of anthropogenic SOA (namely, oxy-PAHs, nitro-PAHs and phenolic compounds oxidation, representing 15%, 9%, 11% of the total OC, respectively) and biogenic SOA (marine + isoprene) (6% in total). Results obtained also showed that 35% of the total SOC originated from anthropogenic sources and especially PAH SOA (oxy-PAHs + nitro-PAHs), accounting for 24% of the total SOC, highlighting its significant contribution in urban influenced environments. Anthropogenic SOA related to nitro-PAHs and phenolic compounds exhibited a clear diurnal pattern with high concentrations during the night indicating the prominent role of night-time chemistry but with different chemical processes involved.

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.

A Met Office/Natural Environment Research Council Joint Weather and Climate Research Programme workshop brought together 50 key international scientists from the UK and international community to formulate the key requirements for an Urban Meteorological Research strategy. The workshop was jointly organised by University of Reading and the Met Office.

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

[1] A new objective method for the determination of the atmospheric boundary layer (ABL) depth using routine vertically pointing aerosol lidar measurements is presented. A geophysical process-based analysis is introduced to improve the attribution of the lidar-derived aerosol gradients, which is so far the most challenging part in any gradient-based technique. Using micrometeorological measurements of Obukhov length scale, both early morning and evening transition periods are determined which help separate the turbulence regimes during well-mixed convective ABL and nocturnal/stable ABL. The lidar-derived aerosol backscatter signal intensity is used to determine the hourly-averaged vertical profiles of variance of the fluctuations of particle backscatter signal providing the location of maximum turbulent mixing within the ABL; thus, obtained mean ABL depth guides the attribution by searching for the appropriate minimum of the gradients. An empirical classification of the ABL stratification patterns into three different types is proposed by determining the changes in the near-surface stability scenarios. First results using the lidar observations obtained between March and July in 2011 at SIRTA atmospheric observatory near Palaiseau (Paris suburb) in France demonstrate that the new attribution technique makes the lidar estimations of ABL depth more physically reliable under a wide spectrum of meteorological conditions. While comparing lidar and nearby radiosonde measurements of ABL depths, an excellent concordance was found with a correlation coefficient of 0.968 and 0.927 for daytime and nighttime measurements, respectively. A brief climatology of the characteristics of the ABL depth, its diurnal cycle, a detailed discussion of the morning and evening transitions are presented.

Lidar depolarization measurements distinguish between spherical and non-spherical aerosol particles based on the change of the polarization state between the emitted and received signal. The particle shape information in combination with other aerosol optical properties allows the characterization of different aerosol types and the retrieval of aerosol particle microphysical properties. Regarding the microphysical inversions, the lidar depolarization technique is becoming a key method since particle shape information can be used by algorithms based on spheres and spheroids, optimizing the retrieval procedure. Thus, the identification of the depolarization error sources and the quantification of their effects are crucial. This work presents a new tool to assess the systematic error of the volume linear depolarization ratio (δ), combining the Stokes–Müller formalism and the complete sampling of the error space using the lidar model presented in Freudenthaler (2016a). This tool is applied to a synthetic lidar system and to several EARLINET lidars with depolarization capabilities at 355 or 532 nm. The lidar systems show relative errors of δ larger than 100 % for δ values around molecular linear depolarization ratios (∼ 0.004 and up to ∼ 10 % for δ = 0.45). However, one system shows only relative errors of 25 and 0.22 % for δ = 0.004 and δ = 0.45, respectively, and gives an example of how a proper identification and reduction of the main error sources can drastically reduce the systematic errors of δ. In this regard, we provide some indications of how to reduce the systematic errors.

The climate research community aims to better characterize climate forcings such as aerosols, reactive gases, and greenhouse gases, and to better understand the responses of the climate system to these forcings. Such investigations rely in part on monitoring, studying, and understanding essential climate variables such as temperature, water vapor, clouds, radiation, and perturbations of aerosols and reactive gases. According to Dufresne and Bony (2008), the parameters that play a predominant role in radiative feedbacks of the climate system are atmospheric humidity, adiabatic thermal gradients, clouds, and surface albedo. Interactions between humidity, clouds, aerosols, and radiation make climate predictions more complex. The climate research community has long recognized the link between climate prediction uncertainty and atmospheric process complexity. For more than 20 years, it has demonstrated the necessity to perform collocated long-term observations of thermodynamic parameters (temperature, humidity, wind) and atmospheric constituents (gases, aerosols, clouds) distributed along the entire atmospheric column (surface to stratosphere) and associated radiative components. As a result, the U.S. Department of Energy (DOE) launched the Atmospheric Radiation Measurement (ARM) Program in the 1990s (Ackerman and Stokes 2003; Stokes 2016, chapter 2). Four atmospheric profiling observation facilities were developed to gather in situ and remote sensing instruments to monitor physical processes in the atmospheric column. A large research community of observation experts and climate modelers was funded to exploit the observation data. Similar atmospheric profiling observation facilities associated with large scientific communities emerged in Europe at the end of the 1990s. Several European initiatives were triggered or encouraged through bilateral collaborations between U.S. and European Union (EU) scientists or through participation of EU scientists in ARM projects (e.g., Cabauw observatory in the Netherlands; Palaiseau observatory in France; Jülich observatory in Germany). Atmospheric profiling observatories provide scientists with the most resolved description of the atmospheric column. In Europe, as in the United States, these observatories have been collecting data every minute daily for more than a decade, allowing links to be established between processes occurring at diurnal or finer temporal scales and phenomenon occurring at climate scales. The limitation of an atmospheric profiling observatory is that it can only document one location of the globe with its specific atmospheric properties. The aerosol distributions, meteorological anomalies, and cloud properties observed at that location are representative of a limited spatial domain. Hence, atmospheric profiling observatories are needed at many locations around the globe to cover climatically diverse areas: near coasts, in continental plains, mountains, and urban environments. The U.S. ARM Program was designed initially to cover three distinct climatic regions (Cress and Sisterson 2016, chapter 5): the Arctic (Alaska), midlatitudes [U.S. southern Great Plains (SGP)], and the tropics [tropical western Pacific (TWP) Ocean]. Atmospheric profiling observatories in Europe were developed primarily over the European continent, extending from locations around the Mediterranean Basin to the Arctic, and including coastal, continental, urban, and mountain sites. The European Commission established several funding mechanisms to develop collaborations between researchers in Europe, to promote development of harmonized research infrastructures, and to reduce fragmentation in European research investments. As a result, in the past 10 years Europe was able to build an infrastructure essential to a large community of users by harmonizing aerosol, cloud, and trace gas observations across Europe. As infrastructures, measurement techniques, data interpretation algorithms, and scientific expertise developed on both sides of the Atlantic, scientists became interested in the added benefits of collaboration and cross-fertilization between the U.S. ARM Program and EU atmospheric profiling research observatories. To expand investigations beyond existing atmospheric observatories, U.S. ARM scientists and ARM Mobile Facility (AMF) infrastructures participated in field experiments initiated by EU programs. EU and U.S. ARM scientists developed collaborations to harmonize data interpretation algorithms and to exploit jointly U.S. and EU observation datasets. Further development of formal collaboration between U.S. ARM and EU programs would enhance the ability of scientists worldwide to take on science challenges about climate change. This chapter presents several European atmospheric profiling research observatories, development of European networking, and the current European research infrastructure (section 2). Section 3 presents EU program initiatives of interest for future collaboration with the ARM Program. Section 4 highlights collaborations that were developed subsequently between the U.S. ARM Program and its European counterparts. In section 5, we present an outlook toward future U.S.-EU collaborations around climate change challenges and observations.

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 characterization of high clouds as performed from selected spaceborne observations is assessed in this article by employing a number of worldwide ground-based lidar multiyear datasets as reference. Among the latter, the ground lidar observations conducted at Lannion, Bretagne (48.7°N, 3.5°W), and Palaiseau, near Paris [the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) observatory: 48.7°N, 2.2°E], both in France, are discussed in detail. High-cloud altitude statistics at these two sites were found to be similar. Optical thicknesses disagree, and possible reasons were analyzed. Despite the variety of instruments, observation strategies, and methods of analysis employed by different lidar groups, high-cloud optical thicknesses from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud and land Elevation Satellite (ICESat) were found to be consistent on the latitude band 40°–60°N. Respective high-cloud altitudes agree within 1 km with respect to those from ground lidars at Lannion and Palaiseau; such a finding remains to be verified under other synoptic regimes. Mean altitudes of high clouds from Lannion and Palaiseau ground lidars were compared with altitudes of thin cirrus from the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Path-B 8-yr climatology for a common range of optical thicknesses (0.1–1.4). Over both sites, the annual altitude distribution of thin high clouds from TOVS Path-B is asymmetric, with a peak around 8–9.5 km, whereas the distribution of high clouds retrieved from ground lidars seems symmetric with a peak around 9.5–11.5 km. Additional efforts in standardizing ground lidar observation and processing methods, and in merging high-cloud statistics from complementary measuring platforms, are recommended.

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.

The Cloudnet project aims to provide a systematic evaluation of clouds in forecast and climate models by comparing the model output with continuous ground-based observations of the vertical profiles of cloud properties. In the models, the properties of clouds are simplified and expressed in terms of the fraction of the model grid box, which is filled with cloud, together with the liquid and ice water content of the clouds. These models must get the clouds right if they are to correctly represent both their radiative properties and their key role in the production of precipitation, but there are few observations of the vertical profiles of the cloud properties that show whether or not they are successful. Cloud profiles derived from cloud radars, ceilometers, and dual-frequency microwave radiometers operated at three sites in France, Netherlands, and the United Kingdom for several years have been compared with the clouds in seven European models. The advantage of this continuous appraisal is that the feedback on how new versions of models are performing is provided in quasi-real time, as opposed to the much longer time scale needed for in-depth analysis of complex field studies. Here, two occasions are identified when the introduction of new versions of the ECMWF and Météo-France models leads to an immediate improvement in the representation of the clouds and also provides statistics on the performance of the seven models. The Cloudnet analysis scheme is currently being expanded to include sites outside Europe and further operational forecasting and climate models.

The Laboratoire de Météorologie Dynamique atmospheric general circulation model with zooming capability (LMDZ) has been used in a nudged mode to enable comparison of model outputs with routine observations and evaluate the model physical parameterizations. Simulations have been conducted with a stretched grid refined over the vicinity of Paris, France, where observations, collected at the Trappes station (Météo-France) and at the Site Instrumental de Recherche par Télédétection Atmosphérique observatory, are available. For the purpose of evaluation of physical parameterizations, the large-scale component of the modeled circulation is adjusted toward ECMWF analyses outside the zoomed area only, whereas the inside region can evolve freely. A series of sensitivity experiments have been performed with different parameterizations of land surface and boundary layer processes. Compared with previous versions of the LMDZ model, a “thermal plume model,” in association with a constant resistance to evaporation improves agreement with observations. The new parameterization significantly improves the representation of seasonal and diurnal cycles of near-surface meteorology, the day-to-day variability of planetary boundary layer height, and the cloud radiative forcing. This study emphasizes the potential of using a climate model with a nudging and zooming capability to assess model physical parameterizations.

International audience; The atmospheric boundary layer (ABL) depth, zi, is a fundamental variable of ABL and a climatologically important quantity. The exchange of energy between the Earth's surface and the atmosphere is governed by turbulent mixing processes in the daytime ABL, and thus, zi is important for scaling turbulence and diffusion in both meteorological and air quality models. A long-term data set of zi was derived at the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) observatory near Paris, using measurements obtained from a ground-based vertically pointing aerosol lidar and an autonomous algorithm STRAT+. Using multiparameter observational data sets covering a 5 year period (October 2008 to September 2013), this study aims to explore two interconnected ABL research topics: brief climatology involving multiscale temporal zi variability (diurnal, seasonal, annual, and interannual) and the relationship between zi and near-surface thermodynamic parameters to determine meteorological processes governing zi variability. Both the zi and the growth rate over SIRTA showed large seasonal variability with higher mean values in spring (1633 m and 225 m h-1) and summer (1947 m and 247 m h-1) than in autumn (1439 m and 196 m h-1) and winter (1033 m and 149 m h-1). Seasonal variability of daytime maximum zi is found to be strongly and linearly correlated with downwelling solar radiation at the surface (r = 0.92), while the dependence between daytime maximum zi and sensible heat flux (SHF) at seasonal scales is not fully linear, in particular, for summer months. Interannual variability is studied using deseasonalized monthly-mean anomalies of each variable. Conditional sampling and linear regression analyses between the anomalies of deseasonalized SHF and daytime maximum zi, show (1) stronger correlation between the two parameters for the soil conditions compared to the wet soil conditions, (2) that zi anomalies were more dependent on SHF anomalies for negative than for positive boundary layer wind speed anomalies, and (3) in the summer season, zi anomalies varied more consistently with SHF anomalies for conditions with negative cloud cover anomalies than in conditions with positive cloud cover anomalies.