气候变化领域集成服务门户(CCPortal): Multivariate statistical air mass classification for the high-alpine observatory at the Zugspitze Mountain; Germany

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DOI	10.5194/acp-19-12477-2019
	Multivariate statistical air mass classification for the high-alpine observatory at the Zugspitze Mountain; Germany
	Sigmund A.; Freier K.; Rehm T.; Ries L.; Schunk C.; Menzel A.; Thomas C.K.
发表日期	2019
ISSN	16807316
起始页码	12477
结束页码	12494
卷号	19 期号:19
英文摘要	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 Schneefernerhaus site at Zugspitze Mountain, 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 principal components, nine air mass regimes were defined. These regimes were interpreted with respect to vertical transport and assigned to the BL (recent contact with the boundary layer), UFT/SIN (undisturbed free troposphere or stratospheric intrusion), and HYBRID (influences of both the boundary layer and the free troposphere or ambiguous) air mass classes. The input data were available for 78% of the investigated year. BL accounted for 31% of the cases with similar frequencies in all seasons. UFT/SIN comprised 14% of the cases but was not found from April to July. HYBRID (55%) mostly exhibited intermediate characteristics, whereby 17% of the HYBRID class suggested an influence from 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. Due to data gaps, only 25% of the cases could be classified using 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 classification of air masses. Future work is necessary to assess the uncertainty arising from the standardization of real-time data. © 2019 Author(s). This work is distributed under the Creative Commons Attribution 4.0 License.
语种	英语
scopus关键词	air mass; alpine environment; boundary layer; classification; multivariate analysis; principal component analysis; real time; Alps; Bavaria; Bavarian Alps; Central Alps; Wetterstein Mountains; Zugspitze
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/144107
作者单位	Micrometeorology Group, University of Bayreuth, Bayreuth, Germany; Bavarian Environment Agency, Augsburg, Germany; Research Unit Sustainability and Global Change, Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany; Environmental Research Station Schneefernerhaus, Zugspitze, Germany; German Environment Agency, GAW Global Observatory, Zugspitze/Hohenpeissenberg, Germany; Ecoclimatology, Technical University of Munich, Freising, Germany; Institute for Advanced Study, Technical University of Munich, Garching, Germany; School of Architecture, Civil and Environmental Engineering, Swiss Federal Institute of Technology, Lausanne, Switzerland; Safety and Radiation Protection, Technical University of Munich, Garching, Germany
推荐引用方式 GB/T 7714	Sigmund A.,Freier K.,Rehm T.,et al. Multivariate statistical air mass classification for the high-alpine observatory at the Zugspitze Mountain; Germany[J],2019,19(19).
APA	Sigmund A..,Freier K..,Rehm T..,Ries L..,Schunk C..,...&Thomas C.K..(2019).Multivariate statistical air mass classification for the high-alpine observatory at the Zugspitze Mountain; Germany.Atmospheric Chemistry and Physics,19(19).
MLA	Sigmund A.,et al."Multivariate statistical air mass classification for the high-alpine observatory at the Zugspitze Mountain; Germany".Atmospheric Chemistry and Physics 19.19(2019).