Spatiotemporal Characteristics of Altitudinal Lapse Rate of Temperature in Mainland China

Abstract:

Quantitative evaluation of how mountain ecosystems respond to climate change requires accurate estimates of temperature at high altitudes. One approach to estimating highland temperature is by extrapolating temperatures from low altitudes, based on previous observations of the actual altitudinal lapse rate of temperature (γ_local). However, our understanding of γ_local is still very limited. Here, we use daily mean, maximum and minimum temperature (T_mean, T_max, T_min) data from 523 meteorological stations in mainland China to estimate the spatiotemporal patterns of γ_local. The mean γ_local across the whole country is 5.4 K km^-1, with a daytime average of 5.0 K km^-1 and a nighttime average of 5.6 K km^-1. The patterns of γ_local for T_mean (γ_local(T_mean)) display: 1) a significant spatial difference between southern China and northern China (including the Qinghai-Tibet Plateau, p<0.05); 2) a distinct seasonal variation, with higher γ_local occurring in summer and lower occurring in winter in most regions. Interestingly, the seasonal variation for the Qinghai-Tibet Plateau is reversed, with γ_local being lower in summer and higher in winter. In addition, the spatial difference and seasonal variation of γ_local for T_max and T_min (γ_local(T_max) and γ_local(T­_min)) show similar patterns to γ_local(T_mean), but slightly diverge from each other. Our results demonstrate that the magnitude of γ_local obviously differs in regional distributions and seasonal variations, and may be a result of the interactions among temperature, atmospheric moisture content and solar radiation. To improve the accuracy of the extrapolation method requires spatial patterns of γ_local rather than just a constant universal value.