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Patterns of planetary boundary layer influence at the Whistler Mountain air chemistry observatory : an observational mountain meteorology study Gallagher, John Patrick

Abstract

An observational study was conducted to characterize atmospheric conditions at an air chemistry monitoring site on the summit of Whistler Mountain, British Columbia, Canada. Discrimination of air samples from the observatory as either representative of the free troposphere (FT) or modified by air from the valley-based planetary boundary layer (PBL) is critical to the proper interpretation of air chemistry datasets. Atmospheric data from a one-year study period were used to evaluate indicators and possible driving forces of PBL influence at the Whistler site. Diurnal cycles in water vapour and aerosol concentration were attributed primarily to convective uplift of PBL air during daytime heating hours. Analysis of these variables found that PBL influence was common in the spring and summer months and relatively rare in late fall through early winter. For the one-year period, 37% of the days had diurnal cycles in aerosol concentration that were considered typical of thermally induced vertical transport processes. Patterns of slope and valley winds were also identified for Whistler, and the presence of these diurnal wind systems was associated with enhanced aerosol concentration at the summit. Synoptic classification methods were used to describe the prevailing conditions on days with well-defined indicators of PBL influence. Strong solar insolation and light synoptic scale winds were found to be common on such days. Case studies of particular days confirmed that a deep convective boundary layer (CBL) of well-mixed air can encompass the mountain summits, even during the winter season. During the summer, a tendency for PBL constituents to remain aloft through the night means that the summit observatory can be unrepresentative of the FT for several days at a time. Separation of air chemistry measurements into periods of FT conditions and times of PBL influence requires careful analysis of a variety of datasets on both local and regional scales.

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