Quantitative climate reconstruction on long timescales can provide important insights for understanding the climate variability and providing valuable data for simulations. Unfortunately, the credibility of some attem...Quantitative climate reconstruction on long timescales can provide important insights for understanding the climate variability and providing valuable data for simulations. Unfortunately, the credibility of some attempts was hampered by incomplete reconstruction procedures. We here establish a comprehensive framework resting on high-quality Chinese modern pollen database, including modern pollen data screening, calibration set selection, major climate factor analysis, appropriate model selection, strict statistical assessment of results and ecological interpretation. The application of this framework to three high-resolution pollen records from the eastern Tibetan Plateau allows accurate quantitative inferences of Holocene temperature changes, which is the major control of regional vegetation. The results show that the mean warmest month temperature(MTwa)during the early Holocene was ca. 10.4℃ and reached the highest value at 8.5–6 ka BP(ca. 11℃). The early and mid-Holocene(11–5 ka BP) warmth was followed by 1.2℃ temperature decrease, culminating in the coolest temperatures of the Holocene during the Neoglacial cooling. Superimposing on the general cooling trend, MTwareveals a significant 500-yr periodicity with varying intensities through time, showing that warm(cold) intervals are in phase with solar maxima(minima) periods. This spectral similarity indicates a possible connection of multi-century scale climate fluctuations with solar forcing.展开更多
基金supported by the National Key Research and Development Program of China (Grant No. 2016YFA0600501)the National Natural Science Foundation of China (Grant Nos. 41690113, 41888101 and 41471169)the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA20070101)。
文摘Quantitative climate reconstruction on long timescales can provide important insights for understanding the climate variability and providing valuable data for simulations. Unfortunately, the credibility of some attempts was hampered by incomplete reconstruction procedures. We here establish a comprehensive framework resting on high-quality Chinese modern pollen database, including modern pollen data screening, calibration set selection, major climate factor analysis, appropriate model selection, strict statistical assessment of results and ecological interpretation. The application of this framework to three high-resolution pollen records from the eastern Tibetan Plateau allows accurate quantitative inferences of Holocene temperature changes, which is the major control of regional vegetation. The results show that the mean warmest month temperature(MTwa)during the early Holocene was ca. 10.4℃ and reached the highest value at 8.5–6 ka BP(ca. 11℃). The early and mid-Holocene(11–5 ka BP) warmth was followed by 1.2℃ temperature decrease, culminating in the coolest temperatures of the Holocene during the Neoglacial cooling. Superimposing on the general cooling trend, MTwareveals a significant 500-yr periodicity with varying intensities through time, showing that warm(cold) intervals are in phase with solar maxima(minima) periods. This spectral similarity indicates a possible connection of multi-century scale climate fluctuations with solar forcing.
