New Temperature Reconstruction Shows Asia’s Tianshan Mountains Were 1-2°C Warmer During The 1700s

Yet another region of the globe has not warmed (net) for the last 333 years.

The authors of a new study (Jiao et al., 2019) point out that temperature changes in the Tianshan mountains are “mainly influenced by the solar activity via the mean minimum temperature within approximately 11-year periods.”

Despite some warming since the 1950s, the authors do not maintain CO2 changes were an influencing climate factor in the 1680-2012 reconstruction.

The 1708-1801 period is shown to be about 1-2°C warmer than the the 1950-2012 period.

new temperature reconstruction shows asias tianshan mountains were 1 2c warmer during the 1700s

Jiao et al., 2019

Regional climate change is affected by large-scale climate-forcing factors, such as solar activity and atmospheric–oceanic variability (Fang et al., 2010; Linderholm et al., 2015; Rydval et al., 2017). On the one hand, based on the MTM analysis results, the temperature changes in the study area are mainly influenced by the solar activity via the mean minimum temperature within approximately 11-year periods (Li et al., 2006; Wang et al., 2015). The tree-ring chronology was developed by samples of Schrenk spruce collected from the National Nature Reserve of the Western Tianshan Mountains. The mean minimum temperature in the growing season is the main and stable limiting climate factor. Therefore, the mean minimum temperature series in the growing season during 1680–2012 was reconstructed based on the STD chronology.”
“In the past 333 years, the mean minimum temperature has roughly experienced three relatively cold periods and relatively warm stages (relatively cold periods: 1680–1707, 1802–1911 and 1935–1997; relatively warm periods: 1708–1801, 1912–1934 and 1998–2012). By analyzing similar trends in regional temperature changes in our reconstruction series with drought events, large volcanic eruptions and other reconstruction series around the study regions in Xinjiang and even large-scale regions, we found that the mean minimum temperature of the reconstruction was accurate and reliant. Moreover, the mean minimum temperature was influenced by solar activity (sunspots) and large-scale atmospheric–oceanic fluctuations (NAO, WPO, ENSO, TBO) based on the MTM and spatial correlation analysis.”

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