Weather regimes and related atmospheric composition at a Pyrenean observatory characterized by hierarchical clustering of a 5-year data set

Atmospheric composition measurements taken at many high-altitude stations around the world, aim to collect data representative of the free troposphere and of an intercontinental scale. However, the high-altitude environment favours vertical mixing and the transportation of air masses at local or regional scales, which has a potential influence on the composition of the sampled air masses. Mixing processes, source-receptor pathways, and atmospheric chemistry may strongly depend on local and regional weather regimes, and these should be characterized specifically for each station. The Pic du Midi (PDM) isa mountaintop observatory (2850 m a.s.l.) on the north side of the Pyrenees. PDM is associated with the Centre de Recherches Atmosph{\'e}riques (CRA), a site in the foothills ar 600 m a.s.l. 28 km north-east of the PDM. The two centers make up the Pyrenean Platform for the Observation of the Atmosphere (P2OA). Data measured at PDM and CRA were combined to form a5-year hourly dataset of 23 meteorological variables notably: temperature, humidity, cloud cover, wind at several altitudes. The dataset was classified using hierarchical clustering, with the aim of grouping together the days which had similar meteorological characteristics. To complete the clustering, we computed several diagnostic tools, in order to provide additional information and study specific phenomena (foehn, precipitation, atmospheric vertical structure, and thermally driven circulations). This classification resulted in six clusters: three highly populated clusters which correspond to the most frequent meteorological conditions (fair weather, mixed weather and disturbed weather, respectively); a small cluster evidencing clear characteristics of winter northwesterly windstorms; and two small clusters characteristic of south foehn (south- to southwesterly large-scaleflow, associated with warm and dry downslope flow on the lee side of the chain). The diagnostic tools applied to the six clusters provided results in line with the conclusions tentatively drawn from 23 meteorological variables. This, to some extent,validates the approach of hierarchical clustering of local data to distinguish weather regimes. Then statistics of atmospheric composition at PDM were analysed and discussed for each cluster. Radon measurements, notably, revealed that the regional background in the lower troposphere dominates the influence of diurnal thermal flows when daily averaged concentrations are considered. Differences between clusters were demonstrated by the anomalies of CO, CO$_2$, CH$_4$, O$_3$ and aerosol number concentration, and interpretations in relation with chemical sinks and sources are proposed.Comment: Atmospheric Chemistry and Physics, In pres

Breakup of nocturnal low-level stratiform clouds during the southern West African monsoon season

Within the framework of the DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa) project and based on a field experiment conducted in June and July 2016, we analyze the daytime breakup of continental low-level stratiform clouds in southern West Africa. We use the observational data gathered during 22 precipitation-free occurrences at Savè, Benin. Our analysis, which starts from the stratiform cloud formation usually at night, focuses on the role played by the coupling between cloud and surface in the transition towards shallow convective clouds during daytime. It is based on several diagnostics, including the Richardson number and various cloud macrophysical properties. The distance between the cloud base height and lifting condensation level is used as a criterion of coupling. We also make an attempt to estimate the most predominant terms of the liquid water path budget in the early morning. When the nocturnal low-level stratiform cloud forms, it is decoupled from the surface except in one case. In the early morning, the cloud is found coupled with the surface in 9 cases and remains decoupled in the 13 other cases. The coupling, which occurs within the 4 h after cloud formation, is accompanied by cloud base lowering and near-neutral thermal stability in the subcloud layer. Further, at the initial stage of the transition, the stratiform cloud base is slightly cooler, wetter and more homogeneous in coupled cases. The moisture jump at the cloud top is usually found to be lower than 2 g kg−1 and the temperature jump within 1–5 K, which is significantly smaller than typical marine stratocumulus and explained by the monsoon flow environment in which the stratiform cloud develops over West Africa. No significant difference in liquid water path budget terms was found between coupled and decoupled cases. In agreement with previous numerical studies, we found that the stratiform cloud maintenance before sunrise results from the interplay between the predominant radiative cooling, entrainment and large-scale subsidence at its top. Three transition scenarios were observed depending on the state of coupling at the initial stage. In coupled cases, the low-level stratiform cloud remains coupled until its breakup. In five of the decoupled cases, the cloud couples with the surface as the lifting condensation level rises. In the eight remaining cases, the stratiform cloud remains hypothetically decoupled from the surface throughout its life cycle since the height of its base remains separated from the condensation level. In cases of coupling during the transition, the stratiform cloud base lifts with the growing convective boundary layer roughly between 06:30 and 08:00 UTC. The cloud deck breakup, occurring at 11:00 UTC or later, leads to the formation of shallow convective clouds. When the decoupling subsists, shallow cumulus clouds form below the stratiform cloud deck between 06:30 and 09:00 UTC. The breakup time in this scenario has a stronger variability and occurs before 11:00 UTC in most cases. Thus, we argue that the coupling with the surface during daytime hours has a crucial role in the low-level stratiform cloud maintenance and its transition towards shallow convective clouds

The BLLAST field experiment: Boundary-Layer late afternoon and sunset turbulence

Due to the major role of the sun in heating the earth's surface, the atmospheric planetary boundary layer over land is inherently marked by a diurnal cycle. The afternoon transition, the period of the day that connects the daytime dry convective boundary layer to the night-time stable boundary layer, still has a number of unanswered scientific questions. This phase of the diurnal cycle is challenging from both modelling and observational perspectives: it is transitory, most of the forcings are small or null and the turbulence regime changes from fully convective, close to homogeneous and isotropic, toward a more heterogeneous and intermittent state. These issues motivated the BLLAST (Boundary-Layer Late Afternoon and Sunset Turbulence) field campaign that was conducted from 14 June to 8 July 2011 in southern France, in an area of complex and heterogeneous terrain. A wide range of instrumented platforms including full-size aircraft, remotely piloted aircraft systems, remote-sensing instruments, radiosoundings, tethered balloons, surface flux stations and various meteorological towers were deployed over different surface types. The boundary layer, from the earth's surface to the free troposphere, was probed during the entire day, with a focus and intense observation periods that were conducted from midday until sunset. The BLLAST field campaign also provided an opportunity to test innovative measurement systems, such as new miniaturized sensors, and a new technique for frequent radiosoundings of the low troposphere. Twelve fair weather days displaying various meteorological conditions were extensively documented during the field experiment. The boundary-layer growth varied from one day to another depending on many contributions including stability, advection, subsidence, the state of the previous day's residual layer, as well as local, meso- or synoptic scale conditions. Ground-based measurements combined with tethered-balloon and airborne observations captured the turbulence decay from the surface throughout the whole boundary layer and documented the evolution of the turbulence characteristic length scales during the transition period. Closely integrated with the field experiment, numerical studies are now underway with a complete hierarchy of models to support the data interpretation and improve the model representations.publishedVersio

Vertical wind velocity measurements using a five-hole probe with remotely piloted aircraft to study aerosol–cloud interactions

International audienceThe importance of 3D winds (in particular updraft) in atmospheric science has motivated the adaptation of airborne wind instruments developed for manned aircraft, to the small size of Remotely Piloted Aircraft Systems (RPAS). Simultaneously, enhancements in RPAS technology have increased their contribution to many fields. In atmospheric research, lightweight RPAS (< 2.5 kg) are now able to accurately measure 3D wind vectors, even in a cloud, which provides new observing tools for understanding aerosol-cloud interactions. The European project BACCHUS (Impact of Biogenic versus Anthropogenic Emissions on Clouds and Climate: towards a Holistic Understanding) focuses on these specific interactions. Vertical wind velocity at cloud base is a key parameter for aerosol-cloud interactions. To measure the three components of wind, one RPAS is equipped with a 5-hole probe and an Inertial Measurement Unit (IMU), synchronized on an acquisition system. The 5-hole probe is calibrated and validated on a multi-axis platform in a wind tunnel, each probe and its associated pressure sensors have specific calibration coefficients. Once mounted on a RPAS, 3D winds and turbulent kinetic energy (TKE) derived from the 5-hole probe are validated with a sonic anemometer on a meteorological mast. During the BACCHUS field campaign at Mace Head (Ireland), a fleet of RPAS has been utilized to profile the atmosphere and complement ground-based and satellite observations. To study aerosol-cloud interactions, the RPAS with the 5-hole probe flew at level legs near cloud base to measure vertical wind speeds. The vertical velocity measurements from RPAS are validated with vertical velocities derived from the Mace Head Doppler cloud radar, and the results illustrate the relationships between the distributions of vertical velocity and the different cloud fields

Validation of Tropospheric Water Vapor as Measured by the 183-GHz HAMSTRAD Radiometer Over the Pyrenees Mountains, France

International audienceThe H2O Antarctica Microwave Stratospheric and Tropospheric Radiometers (HAMSTRAD) 183-GHz radiometer has been developed to measure vertical profiles of tropospheric water vapor above Dome C (Concordia station), Antarctica ( 75?06'S, 123?21'E, 3233 m asml), which is an extremely cold and dry environment, over decades. Prior to its installation at Dome C in January 2009, the instrument was deployed at the Pic du Midi (PdM) station ( 42?56'N, 0?08'E, 2877 m asml) in the Pyrenees Mountains, France, over the period covering February-June 2008. Vertical profiles of absolute humidity and integrated water vapor (IWV) as measured by HAMSTRAD were compared with measurements from radiosondes launched in three different sites: Lannemezan (43?07'N, 0?23'E, 610 m asml), France (~30 km northeast from PdM), Bordeaux-Me?rignac Airport (44?49'N, 0?42'W, 50 m asml), France ( ~ 220 km northwest from PdM), and Zaragoza (41?39'N, 0?53'W, 263 m asml), Spain ( ~170 km southwest from PdM). The validation process also used the vertical profiles of tropospheric H2O as measured by the nadir-viewing infrared atmospheric sounding interferometer (IASI) instrument aboard the MetOp-A space platform. The temporal evolution of the HAMSTRAD H2O measurements above the PdM station is very consistent with IASI, sonde, and in situ measurements, tracking the same atmosphere from a dry period in February to a wet period in June. HAMSTRAD showed unrealistic values in periods of well-established snow tempest. While the sensitivity of the HAMSTRAD measurements tends to be degraded 6 km above the altitude of the instrument, namely, above 8877 m asml, the HAMSTRAD measurements seem reasonable at the uppermost retrieval level (namely, 10 km, 12 877 m asml). In May, the wet periods are systematically showing a good agreement between sonde and HAMSTRAD IWV fields and H2O below 6777 m asml but a dry bias of IASI by more than 4-kg m-2 IWV, where- - as outside of these periods, the three data sets behave consistently. Since the best results (mean, standard deviation, bias, and correlation) are obtained when the HAMSTRAD radiometer operates in the very dry conditions of February, namely, in dryness conditions comparable to Dome C summertime values, we are very confident in the optimal use of the instrument when deployed in Antarctica

HAMSTRAD-Tropo, A 183-GHz Radiometer Dedicated to Sound Tropospheric Water Vapor Over Concordia Station, Antarctica

International audienceThe H2O Antarctica Microwave Stratospheric and Tropospheric Radiometers (HAMSTRAD) program aims to develop two ground-based microwave radiometers to sound tropospheric and stratospheric water vapor (H2O) above Dome C (Concordia Station), Antarctica (75??06' S, 123??21'E, 3233 m asml), an extremely cold and dry environment, over decades. By using state-of-the-art technology, the HAMSTRAD-Tropo radiometer uses spectral information in the domains 51-59 GHz (oxygen line) and 169-197 GHz (water vapor line) to derive accurate tropospheric profiles of temperature (with accuracy ranging from 1 to 2 K) and low absolute humidity (with accuracy ranging from 0.02 to 0.05 g ?? m-3), together with integrated water vapor (with accuracy of about 0.008 kg ?? m-2) and liquid water path. Prior to its installation at Dome C in January 2009, the fully automated radiometer has been deployed at the Pic du Midi (PdM, 42??56'N, 0??08'E, 2877 m asml, France) in February 2008 and was in operation for five months. Preliminary comparisons with radio soundings particularly launched in the vicinity of PdM in February 2008 and the outputs from the mesoscale MESO-NH model show a great consistency to within 0.2-0.3 g ?? m-3 between all absolute humidity data sets whatever the atmosphere considered (extremely dry or wet)

Weather regimes and related atmospheric composition at aPyrenean observatory characterized by hierarchical clustering of a5-year data set

International audienceAtmospheric composition measurements taken at many high-altitude stations around the world, aim to collect datarepresentative of the free troposphere and of an intercontinental scale. However, the high-altitude environment favours verticalmixing and the transportation of air masses at local or regional scales, which has a potential influence on the compositionof the sampled air masses. Mixing processes, source-receptor pathways, and atmospheric chemistry may strongly depend onlocal and regional weather regimes, and these should be characterized specifically for each station. The Pic du Midi (PDM) isa mountaintop observatory (2850 m a.s.l.) on the north side of the Pyrenees. PDM is associated with the Centre de RecherchesAtmosphériques (CRA), a site in the foothills ar 600 m a.s.l. 28 km north-east of the PDM. The two centers make up thePyrenean Platform for the Observation of the Atmosphere (P2OA). Data measured at PDM and CRA were combined to form a5-year hourly dataset of 23 meteorological variables notably: temperature, humidity, cloud cover, wind at several altitudes. Thedataset was classified using hierarchical clustering, with the aim of grouping together the days which had similar meteorologicalcharacteristics. To complete the clustering, we computed several diagnostic tools, in order to provide additional informationand study specific phenomena (foehn, precipitation, atmospheric vertical structure, and thermally driven circulations). Thisclassification resulted in six clusters: three highly populated clusters which correspond to the most frequent meteorologicalconditions (fair weather, mixed weather and disturbed weather, respectively); a small cluster evidencing clear characteristicsof winter northwesterly windstorms; and two small clusters characteristic of south foehn (south- to southwesterly large-scaleflow, associated with warm and dry downslope flow on the lee side of the chain). The diagnostic tools applied to the six clustersprovided results in line with the conclusions tentatively drawn from 23 meteorological variables. This, to some extent,validates the approach of hierarchical clustering of local data to distinguish weather regimes. Then statistics of atmosphericcomposition at PDM were analysed and discussed for each cluster. Radon measurements, notably, revealed that the regionalbackground in the lower troposphere dominates the influence of diurnal thermal flows when daily averaged concentrations areconsidered. Differences between clusters were demonstrated by the anomalies of CO, CO2 , CH4 , O3 and aerosol numberconcentration, and interpretations in relation with chemical sinks and sources are proposed

Weather regimes and the related atmospheric composition at a Pyrenean observatory characterized by hierarchical clustering of a 5-year data set

International audienceAt high-altitude stations worldwide, atmospheric composition measurements aim to represent the free troposphere and intercontinental scale. The high-altitude environment favours local and regional air mass transport, impacting the sampled air composition. Processes like mixing, source–receptor pathways, and chemistry rely on local and regional weather patterns, necessitating station-specific characterization. The Pic du Midi (PDM) is a mountaintop observatory at 2850 m above sea level in the Pyrenees. The PDM and the Centre de Recherches Atmosphériques (CRA) in the foothills form the Pyrenean Platform for the Observation of the Atmosphere (P2OA). This study aimed to identify recurring weather patterns at P2OA and relate them to the PDM's atmospheric composition. We combined 5 years of data from PDM and CRA, including 23 meteorological variables (temperature, humidity, cloud cover, and wind at different altitudes). We used hierarchical clustering to classify the data set into six clusters. Three of the clusters represented common weather conditions (fair, mixed, disturbed weather), one highlighted winter north-westerly windstorms, and the last two denoted south foehn conditions. Additional diagnostic tools allowed us to study specific phenomena such as foehns and thermally driven circulations and to affirm our understanding of the clusters. We then analysed the PDM's atmospheric composition statistics for each cluster. Notably, radon measurements indicated a regional background dominance in the lower troposphere, overshadowing diurnal thermal effects. Cluster differences emerged for the anomalies in CO, CO2, CH4, O3, and aerosol concentrations, and we propose interpretations in relation to chemical sources and sinks

Effects of environmental factors on the monitoring of environmental radioactivity by airborne gamma-ray spectrometry

International audienceThis study describes and discusses the results of a 14 month-long campaign (April 2019 to June 2020) aimed at characterizing and quantifying the influence of environmental factors (cosmic rays, rainfall events, soil moisture and atmospheric radon) on airborne radiometric surveys, which are used for mapping the concentrations of potassium (K), uranium (U) and thorium (Th), or for monitoring the natural radioactivity in the environment. A large NaI(Tl) airborne spectrometer (4 down + 1 up detectors of 4 L) was installed at a height of 50 m on a meteorological tower to simulate an airborne hover at the Pyrenean Platform for Observation of the Atmosphere (P2OA) in Lannemezan. The continuous, high frequency acquisition of gamma-rays was accompanied by measurements of rainfall intensity, soil moisture content, atmospheric radon activity and meteorological parameters. A semi-diurnal cycle of apparent $^{232}$Th and $^{232}$K was observed and explained by atmospheric thermal tides. Both diurnal and seasonal cycles are also evident in the gamma-ray signal, mostly due to variations of soil moisture at these timescales with a maximum during summer when surface soil moisture (0–5 cm depth) is the lowest. An increase of 25% vol. of the soil moisture content, representing the range of variation between the end of summer (18% vol.) and the beginning of spring (43% vol.) leads to a decrease of gamma-rays in the K and Th window by the same amount. Conversely, these results illustrate the potential of using airborne gamma-ray spectrometry to monitor soil moisture at hectometer scales. The washout of radon-222 progeny during rainfall events influences the count of gamma-rays in the U window by adding an atmospheric component to the soil component. The amplitude of the signal increase in the U window varies with the precipitation rate and reaches 30% for an average event. By clear weather, atmospheric radon-222 volumic activity influences the count rate in the U window by about ±3.8% per Bq m$^{-3}$, which translates into an influence of 148%/Bq m$^{-3}$/kg Bq$^{-1}$ (U). This comprehensive, multi-compartment approach is necessary to optimize and improve the processing and analysis of airborne gamma-ray spectrometry data for high sensitivity environmental studies. These results show the importance of environmental factors on the variability of gamma-ray spectrometry and the importance of taking them into account to accurately map radionuclides activitie

ELIFAN, an algorithm for the estimation of cloud cover from sky imagers

International audienceIn the context of a network of sky cameras installed on atmospheric multi-instrumented sites, we present an algorithm named ELIFAN, which aims to estimate the cloud cover amount from full-sky visible daytime images with a common principle and procedure. ELIFAN was initially developed for a self-made full-sky image system presented in this article and adapted to a set of other systems in the network. It is based on red-to-blue ratio thresholding for the distinction of cloudy and cloud-free pixels of the image and on the use of a cloud-free sky library, without taking account of aerosol loading. Both an absolute (without the use of a cloud-free reference image) and a differential (based on a cloud-free reference image) red-to-blue ratio thresholding are used. An evaluation of the algorithm based on a 1-year-long series of images shows that the proposed algorithm is very convincing for most of the images, with about 97 % of relevance in the process, outside the sunrise and sunset transitions. During those latter periods, however, ELIFAN has large difficulties in appropriately processing the image due to a large difference in color composition and potential confusion between cloud-free and cloudy sky at that time. This issue also impacts the library of cloud-free images. Beside this, the library also reveals some limitations during daytime, with the possible presence of very small and/or thin clouds. However, the latter have only a small impact on the cloud cover estimate. The two thresholding methodologies, the absolute and the differential red-to-blue ratio thresholding processes, agree very well, with departure usually below 8 % except in sunrise-sunset periods and in some specific conditions. The use of the cloud-free image library gives generally better results than the absolute process. It particularly better detects thin cirrus clouds. But the absolute thresholding process turns out to be better sometimes, for example in some cases in which the sun is hidden by a cloud