No Thumbnail Available
Multivariate statistical air mass discrimination for the high-alpine observatory at the Zugspitze mountain, Germany
Multivariate statistical air mass discrimination for the high-alpine observatory at the Zugspitze mountain, Germany
Authors
Editor
Containing Item
Atmospheric Chemistry and Physics Discussions
19 (2019), Heft 19
19 (2019), Heft 19
Keywords
Citation
SIGMUND, Armin, Korbinian FREIER, Till REHM und Ludwig RIES, 2019. Multivariate statistical air mass discrimination for the high-alpine observatory at the Zugspitze mountain, Germany. Atmospheric Chemistry and Physics Discussions [online]. 2019. Bd. 19 (2019), Heft 19. DOI 10.60810/openumwelt-258. Verfügbar unter: https://openumwelt.de/handle/123456789/4823
Abstract english
To assist atmospheric monitoring at high-alpine sites, a statistical approach for distinguishing between the dominant air masses was developed. This approach was based on a principal component analysis using five gas-phase and two meteorological variables. The analysis focused on the site Schneefernerhaus at Mt. Zugspitze, Germany. The investigated year was divided into 2-month periods, for which the analysis was repeated. Using the 33.3 % and 66.6 % percentiles of the first two 5 principal components, nine air mass regimes were defined. These regimes were interpreted with respect to vertical transport and assigned to the air mass classes ML (recent contact with the mixing layer), UFT/SIN (undisturbed free troposphere or stratospheric intrusion), and HYBRID (influences of both the mixing layer and the free troposphere or ambiguous). 78 % of the investigated year were classifiable. ML accounted for 31 % of the cases with similar frequencies in all seasons. UFT/SIN comprised 14 % of the cases but were not found from April to July. HYBRID (55 %) mostly exhibited intermediate charac10 teristics, whereby 17 % of HYBRID suggested an influence of the marine boundary layer or the lower free troposphere. The statistical approach was compared to a mechanistic approach using the ceilometer-based mixing layer height from a nearby valley site and a detection scheme for thermally induced mountain winds. Only 25 % of the cases were classifiable with the mechanistic approach. Both approaches agreed well, except in the rare cases of thermally induced uplift. The statistical approach is a promising step towards a real-time discrimination of air masses. Future work is necessary to assess the uncertainty 15 arising from the standardization of real-time data.Copyright: Author(s) 2019. CC BY 4.0 License