Change features and regional distribution of temperature trend and variability joint mode in mainland China

Abstract

Adaption for temperature should be suitable to local conditions for regional differences in temperature change features. This paper proposed to utilize nine temperature modes that joint the trend (increasing/decreasing/unchanged) with variability (intensifying/weakening/unchanged) to investigate features of temperature change in mainland China. Monthly temperature data over the period 1960–2013 were obtained from 522 national basic and reference meteorological stations. Here, temperature trend (TT) was reflected by the trend of mean annual temperature (MAT) and the uptrend (downtrend) of inter-monthly sliding standard deviation (SSD) series with a sliding length of 29 years (348 months) was used for representing the intensification (weakening) of temperature variability (TV). The Mann-Kendall method and the least squares method were applied to assess the significance and quantify the magnitude of trend in MAT and SSD time series, respectively. The results show that there is a consistent warming trend throughout the country except for only three stations in which a cooling trend is identified. Moreover, the overall increasing rate in the north of 35° N is the highest, over 0.4 °C/decade for most stations. TV is weakened for almost 98% of the stations, indicating the low instability of temperature at a national scale. Finally, temperature mode (TM), for more than 90% of the stations, is the combination of an increasing TT with a weakened TV (mode 8). So, it is more important for people to adapt to the increasing temperature in these regions. Compared to using annual temperature data to calculate SSD, monthly data can accurately reflect the inter-monthly change of temperature and reserve more initial characteristics of temperature.