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

Abstract

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