Accounting for local meteorological effects in the ozone time-series of Lovozero (Kola Peninsula)

International audience The relationship between local meteorological conditions and the surface ozone variability was studied by means of statistical modeling, using ozone and meteorological parameters measured at Lovozero (250 m a.s.l., 68.5°N, 35.0°E, Kola Peninsula) for the period of 1999-2000. T...

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Bibliographic Details
Main Authors: Tarasova, O. A., Karpetchko, A. Yu.
Other Authors: Atmosphere Physics Department Moscow, Faculty of Physics MSU, Moscow, Lomonosov Moscow State University (MSU)-Lomonosov Moscow State University (MSU), Polar Geophysical Institute of Russian Academy of Sciences (PGI), Russian Academy of Sciences Moscow (RAS)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2003
Subjects:
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
Kola Peninsula
Lovozero
kola peninsula
Online Access:https://hal.science/hal-00295291
https://hal.science/hal-00295291/document
https://hal.science/hal-00295291/file/acp-3-941-2003.pdf
Description
Summary:International audience The relationship between local meteorological conditions and the surface ozone variability was studied by means of statistical modeling, using ozone and meteorological parameters measured at Lovozero (250 m a.s.l., 68.5°N, 35.0°E, Kola Peninsula) for the period of 1999-2000. The regression model of daily mean ozone concentrations on such meteorological parameters as temperature, relative humidity and wind speed explains up to 70% of day-to-day ozone variability in terms of meteorological condition changes, if the seasonal cycle is also considered. A regression model was created for separated time scales of the variables. Short-term, synoptical and seasonal components are separated by means of Kolmogorov-Zurbenko filtering. The synoptical scale variations were chosen as the most informative from the point of their mutual relation with meteorological parameters. Almost 40% of surface ozone variations in time periods of 11-60 days can be explained by the regression model on separated scales that is 30% more efficient than ozone residuals usage. Quantitative and qualitative estimations of the relations between surface ozone and meteorological predictors let us preliminarily conclude that at the Lovozero site surface ozone variability is governed mainly by dynamical processes of various time scale rather than photochemistry, especially during the cold season.

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