Long‐range persistence in global Aerosol Index dynamics

Abstract

Abstract Detrended fluctuation analysis (DFA) was applied to zonal mean daily Aerosol Index (AI) values derived from satellite observations during 1979–2003 to search for self‐similarity properties. The results show that the detrended and deseasonalized AI fluctuations in both hemispheres and globally obey persistent long‐range power‐law correlations for time scales longer than about 4 days and shorter than about 2 years. This suggests that the AI fluctuations in small time intervals are related to the AI fluctuations in longer time intervals in a power‐law fashion (when the time intervals vary from about 4 days to about 2 years). In other words, an anomaly in AI in one time frame continues into the next, exhibiting a power‐law evolution. The influence of the annual and semiannual cycles on the scaling behaviour of the AI time series in both hemispheres is discussed. A plausible mechanism for the time scale of about 2 years in AI time series could be the modulation of the Brewer–Dobson cell by the quasi‐biennial oscillation at the equatorial stratosphere in the zonal wind. The synoptic‐scale meteorological systems probably give rise to the time scale of about 4 days. These findings could prove useful in testing the results of existing models, which should be examined to determine if they demonstrate the scaling behaviour mentioned above.