Reconstruction of July temperature based on tree-rings during 1845–2002 in North China

The reconstruction of climate factor fields is essential for understanding large-scale climate change. We collected 30 tree-ring width chronologies and 29 meteorological stations data, conducted spatial correlation analysis between tree-ring width chronologies and temperature of meteorological stations, selected the timelines with high correlation ( r > 0.6), and conducted correlation analysis between these tree-ring width chronologies and climate data in North China. The correlation results showed that there was a significant correlation between the chronologies and the maximum temperature in July ( p < 0.05). Based on this, the summer temperature series was reconstructed by Point-by-Point Regression (PPR). The results show that there are two warm periods (1856-1970, 1883-1952) and two cold periods (1871-1882, 1953-1996) in North China from 1845 to 2002. Morlet wavelet analysis shows that the reconstructed sequences have four periodic changes: 1-3a, 2-6a, 7-11a and 13-18a. Cross wavelet analysis shows that he El Niño-Southern Oscillation (ENSO), Sunspot, and the Pacific Decadal Oscillation (PDO) are the factors affecting the temperature change in the study area. In addition, we also analyzed the spatial distribution pattern of the maximum temperature in North China in July by Empirical Orthogonal Function (EOF) and Rotational Empirical Orthogonal Function (REOF). The results show that there are four distribution patterns of the maximum temperature in North China in July: the west, the east, the south and the north, and the west is the main distribution pattern.