The contribution of atmospheric proxies to the vertical distribution of ozone over Summit Station, Greenland
Abstract
The current trend and future concentrations of atmospheric ozone are active areas of research as the effect of the Montreal Protocol is realized. The trend of ozone is due to various chemical and dynamical parameters that create, destroy, and transport atmospheric ozone. These important parameters can be represented by different proxies, but their effects on ozone concentration are not completely understood. Previous studies show that proxies related to ozone have different contributions depending on latitude and altitude. In this study, we use vertical profiles of ozone derived from ozonesondes launched by the NOAA Global Monitoring Division at Summit Station, Greenland from 2005 to 2016. The effects of different proxies on ozone are investigated. Summit Station is located at 3,200 meters above sea level on the Greenland Ice Sheet and is a unique place in the Arctic. We use a stepwise multiple regression (MLR) technique to remove the seasonal cycle of ozone and investigate how the different proxies [solar flux (SF), the Quasi-Biennial Oscillation (QBO), the El Nino-Southern Oscillation index (ENSO), the Arctic Oscillation (AO), eddy heat flux (EHF), the volume of polar stratospheric clouds (VPSC), equivalent latitude (EL), and the tropopause pressure (TP)] affect the vertical distribution of ozone over Summit. The MLR is applied separately to total column ozone (TCO) as well as partial ozone columns (PCO) in the troposphere and the lower, middle, and upper stratosphere. Our results show that dynamical processes are important contributors to ozone concentrations over Summit Station. Tropospheric pressure and the QBO are effective predictors of ozone in the troposphere, lower and middle stratosphere, and to the TCO. The VPSC is an important contributor to changes in ozone in the middle stratosphere. AO explains part of low/mid stratospheric and TCO ozone cycle. A simulation model of ozone over Summit built from the MLR results explains the seasonal cycle and the trends in TCO over Summit with a correlation coefficient (R2) of 82% for TCO. Simulations of PCO in the lower and middle stratosphere range from R2 = 62% to 85%.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.A21I2281B
- Keywords:
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- 0340 Middle atmosphere: composition and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0341 Middle atmosphere: constituent transport and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 3311 Clouds and aerosols;
- ATMOSPHERIC PROCESSES;
- 3375 Tropopause dynamics;
- ATMOSPHERIC PROCESSES