Abstract
Anthropogenic emissions are generally lower during holidays than they are on workdays, this pattern is expected to result in temperature variations. Variations in the daily maximum (Tmax), mean (Tmean) and minimum (Tmin) air temperatures and the diurnal temperature range (DTR) during the Chinese New Year holiday are evaluated with two methods using daily meteorological observations collected at 2200 stations in China from 1961 to 2015. These two methods yield nearly equivalent results that reflect strong variations in the defined holiday effects. During the period from 1961 to 1980, Tmean, Tmax, Tmin and the DTR all exhibit cooling holiday effects, this effect as measured by the DTR disappears during the period from 1981 to 2000. However, during the period from 2001 to 2015 warming holiday effects are observed for Tmax and the DTR. The evaluation shows that the holiday effect is neither unique nor statistically significant. These results indicate that the holiday effect is primarily caused by natural atmospheric oscillations, because ΔT oscillates noticeably with periods of approximately 7.1 days, 8.5 days and 16.2 days, and these oscillations can account for approximately 75.6% of the variance in ΔT. The oscillation identified here is consistent with the fundamental theory of Rossby wave in the atmosphere.
Highlights
Whether regional and global climate changes can be attributed to natural and anthropogenic causes is a central issue[1,2]
The effects of holidays and weekends on meteorological and environmental variables represent an important aspect of the detection and attribution of climate change
Researchers have generally focused on anthropogenic impacts while assuming that the weekly cycles of consumption and emissions resulting from human activity could help explain the effects of weekends on the climate[7]
Summary
Whether regional and global climate changes can be attributed to natural and anthropogenic causes is a central issue[1,2]. The effects of holidays and weekends on meteorological and environmental variables (i.e., the differences in aerosol concentrations and air temperatures across days that fall on workdays vs across days that fall on weekends or holidays) represent an important aspect of the detection and attribution of climate change. These effects have been analyzed in several studies using observed meteorological and satellite datasets[3,4,5]. Propagate both within the atmosphere and over the oceans, and display considerable variations in their length and time scales[17,18,19]
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