scholarly journals Dynamical modes associated with the Antarctic ozone hole

2009 ◽  
Vol 9 (15) ◽  
pp. 5403-5416 ◽  
Author(s):  
B. C. Weare

Abstract. Generalized Maximum Covariance Analysis (GMCA) has been developed and applied to diagnosing the dynamical modes associated with variations in the Antarctic spring ozone hole. GMCA is used to identify the most important patterns of co-variability between interannual ozone mixing ratio variations in the Antarctic region and temperature, zonal, meridional and vertical velocities between 100 and 10 hPa in the same region. The most important two pairs of GMCA time coefficients show large year-to-year variations and trends, which are connected with the growth of the Antarctic Ozone Hole and the increase of ozone depleting substances. The associated spatial patterns of ozone variations may be characterized as being quasi-symmetric and asymmetric about the pole. These patterns of ozone variations are associated with comparable patterns of variations of temperature and winds through most of the vertical domain. The year 2000 is shown to be dominated by the asymmetric mode, whereas the adjacent year 2001 is dominated by the quasi-symmetric mode. A case study, focusing on the asymmetric differences between these two years, shows the magnitude of the ozone mixing ratio, temperature and zonal wind differences to be in the range of 2 e–6 kg/kg, 10°C and 10 m/s, respectively. Budget calculations show that transport processes contribute substantially to the ozone and temperature changes in the middle stratosphere over the Antarctic continent. However, both radiative and chemical processes also play important roles in the changes.

2009 ◽  
Vol 9 (1) ◽  
pp. 5055-5086
Author(s):  
B. C. Weare

Abstract. Generalized Maximum Covariance Analysis (GMCA) has been developed and applied to diagnosing the dynamical modes associated with variations in the Antarctic spring ozone hole. GMCA is used to identify the most important patterns of co-variability between interannual ozone mixing ratio variations in the Antarctic region and temperature, zonal, meridional and vertical velocities between 100 and 10 hPa in the same region. The most important two pairs of GMCA time coefficients show large year-to-year variations and trends, which are connected with the growth of the Antarctic Ozone Hole and the increase of ozone depleting substances. The associated spatial patterns of ozone variations may be characterized as being quasi-symmetric and asymmetric about the pole. These patterns of ozone variations are associated with comparable patterns of variations of temperature and winds through most of the vertical domain. The year 2000 is shown to be dominated by the asymmetric mode, whereas the adjacent year 2001 is dominated by the quasi-symmetric mode. A case study, focusing on the asymmetric differences between these two years, shows the magnitude of the ozone mixing ratio, temperature and zonal wind differences to be in the range of 2 e-6, 10°C and 10 m/s, respectively. Budget calculations show that transport processes contribute substantially to the ozone and temperature changes in the middle stratosphere over the Antarctic continent. However, both radiative and chemical processes also play important roles in the changes.


2021 ◽  
pp. 5-15
Author(s):  
I. P. Gabis ◽  

The Antarctic ozone hole is observed annually in spring due to the complex influence of photochemical and dynamical processes. The increased concentration of ozone-depleting substances in the atmosphere causes a long-term negative trend in total ozone (TO). Intense interannual fluctuations in TO against a background of the long-term trend associated with dynamic atmospheric processes do not allow assessing definitely the direction of the trend (growth/decline) in the recent years. Studying the dependence of interannual fluctuations in the ozone hole intensity on the equatorial quasi-biennial oscillation (QBO) allows identifying natural causes of variations and assessing the trend due to anthropogenic factors. The long-term QBO forecast allows predicting different phenomena that depend on the QBO.


Nature ◽  
2019 ◽  
Vol 575 (7781) ◽  
pp. 46-47 ◽  
Author(s):  
Susan Solomon

2004 ◽  
Vol 31 (21) ◽  
pp. n/a-n/a ◽  
Author(s):  
Paul A. Newman ◽  
S. Randolph Kawa ◽  
Eric R. Nash

Science ◽  
2011 ◽  
Vol 332 (6032) ◽  
pp. 925-926 ◽  
Author(s):  
S. B. Feldstein

1996 ◽  
Vol 23 (2) ◽  
pp. 153-156 ◽  
Author(s):  
Michael Y. Danilin ◽  
Nien-Dak Sze ◽  
Malcolm K. W. Ko ◽  
Jose M. Rodriguez ◽  
Michael J. Prather

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