Abstract: Under the background of global warming, the disaster events (drought, heat wave, freezing, cold wave, etc.) caused by extreme temperature changes are also becoming more and more frequent, which pose a serious threat to industrial and agricultural production, human life and property. Therefore, extreme temperature changes have gradu? ally caused widespread concern. Based on the daily temperature (maximum, minimum) data of 404 stations in north? ern China from 1960 to 2017, 16 extreme temperature indices are calculated by RclimDex1.0 of R. Using the meth? ods of linear regression, Mann-Kendal test, sliding t-test, cumulative anomaly and correlation analysis to analyze spatial- temporal variation characteristics of extreme temperature events, and exploring the influencing factors of temperature indices. The results show that: (1) An upward trend in warm extremes and extremal indices, and a down? ward trend in cold extremes as well as diurnal temperature range (DTR); the magnitudes of changes in cold extremes are obviously higher than those of warm extremes，the magnitudes of changes in night extremes are higher than those of day extremes; The warming in the northwest region is the most obvious, and the warming in the northeast re? gion is not obvious; (2) The mutation time of the extreme temperature indices mainly occurred in the 1980s and 1990s. Additionally, the cold extremes and minimum values of daily maximum (minimum) temperature mutated ear? lier than those of the warm extremes and maximum values of daily maximum (minimum) temperature. After the mu? tation, the extreme warm events and extreme value events tended to occur frequently, whereas the occurrence of ex? treme cold events decreased gradually. The extreme temperature indices in the northeast region has the earliest mu? tation time, the northwest region has the latest mutation time; (3) The changes of extreme temperature indices re? sponds to the global warming hiatus during 1988 to 2012; (4) Most extreme temperature indices show close correla? tion with longitude, latitude and altitude; (5) The Arctic Oscillation (AO) index has the strongest impact on extreme temperatures and the most significant impact on the cold index; (6) During the 2007 to 2016, a downward trend in Aerosol Optical thickness (AOD), extreme high temperature events increased and extreme low temperature events decreased. Most cold indices were negatively correlated with AOD, and most warm indexes were positively correlat? ed with AOD. This study analyzes the variation characteristics of extreme temperature in the northern China, aims to understand the trend of extreme temperature change deeply, carry out meteorological disaster prediction, early warning research, reduce the adverse impact of extreme temperature events on local production and life, and ensure the safety of agricultural production.

Key words: extreme temperature, temporal and spatial variation, influencing factors, northern China