Surface ozone and meteorological predictors on a subregional scale |
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| Institution: | 1. Meteorological Service of the GDR, Main Meteorological Observatory, Telegrafenberg, Potsdam, DDR-1561, Germany;2. Central Weather Office, Michendorfer Chaussee 23, Potsdam, DDR-1561, Germany;1. CEMSE Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia;2. PIMM Laboratory, UMR CNRS 800, Arts et Métiers ParisTech, Paris, France;3. University of Sharjah, Department of Electrical and Computer Engineering, Sharjah, United Arab Emirates;1. University of Washington Bothell, School of Science, Technology, Engineering and Mathematics, 18115 Campus Way NE, Bothell, WA, 98011, USA;2. University of Washington, Department of Atmospheric Sciences, 408 ATG Building, Box 351640, Seattle, WA, 98195-1640, USA;1. School of Mechanical Engineering, VIT University, Vellore, 632014, India;2. School of Information Technology and Engineering, VIT University, Vellore, 632014, India;1. Institute for Space and Nuclear Power Studies, Department of Nuclear Engineering, University of New Mexico, Albuquerque, NM, USA;2. Nuclear Engineering, University of New Mexico, Albuquerque, NM, USA;3. Mechanical Engineering, University of New Mexico, Albuquerque, NM, USA;4. Chemical and Biological Engineering, University of New Mexico, Albuquerque, NM, USA |
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| Abstract: | Meteorological conditions affect the ozone concentration near the surface. To quantify the importance of meteorological parameters for the surface ozone concentration a nonlinear regression analysis between 313 meteorological candidate predictors and surface ozone concentration at five stations in the German Democratic Republic over the period 1972–1987 has been made. The stability and quality of the relationship between ozone and meteorological predictors has been tested by independent samples. Most important predictors for surface ozone are the ozone value of the preceding day (persistence) and solar radiation. They explain 33–46% and 6–21% of the climatological ozone variance, respectively. As all meteorological parameters can be forecasted, the regression method described might be the basis for a short-term prediction of surface ozone. An analysis of long-term changes of surface ozone and solar radiation shows that changes in cloudiness are probably not the main cause of the long-term changes in surface ozone. Therefore, the ozone changes should mainly be due to changes in circulation and/or concentration of ozone precursors (NOx, VOC). |
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