Studying the characteristics of temperature differences on bridge decks and their prediction models can provide decision-making basis for traffic management departments to predict severe weather and reduce traffic accidents. Based on observation data from three traffic meteorological stations on the Tianxingzhou Bridge section in Wuhan over the past three years, including the minimum temperature, air temperature, wind speed, precipitation, etc., for every five minutes, the daily differences in the minimum temperature between the bridge deck and the road surface, the hourly variation characteristics of typical weather cases, and the temperature change patterns under different weather conditions are analyzed. The prediction models for the minimum temperature of the bridge deck are established by using multiple linear regression and BP (Back Propagation) neural network methods, and the models are driven and tested using intelligent grid minimum temperature prediction products. The results indicate that due to differences in engineering structure, pavement material, geographical environment, and environmental meteorological factors, the temperature of the bridge deck is usually lower than that of the pavement, and the temperature difference between the two is the largest under sunny conditions. The speed at which the temperature on the bridge deck drops below freezing point is faster, and the duration of low temperature maintenance is longer. Both multiple linear regression and BP neural network methods can achieve good prediction results. Among them, BP method is more suitable for scenarios that require high prediction accuracy, while multiple linear regression method is suitable for applications that require high prediction accuracy.

Based on winter mean temperature observation data in Xinjiang and Arctic Oscillation (AO) index and atmospheric circulation data, the relation and variation between mean temperature in Xinjiang and AO in winter were studied, the conceptual model of winter mean temperature prediction in Xinjiang due to AO influence under the climate warming background was established. The results show that in the process of climate warming, the relation between mean temperature in Xinjiang and AO in winter not only came from global warming, but also depended on AO change in the same period. Overall, the positive (negative) anomaly of temperature in Xinjiang in winter corresponded to AO positive (negative) anomaly. Since the global climate warming, the impact of AO on mean temperature in Xinjiang in winter was asymmetric. When the winter AO index was in positive phase, the corresponding air temperature in Xinjiang was higher than normal, the anomalous change of temperature in Xinjiang matched to AO anomaly in winter. However, when the winter AO index was in negative phase, the positive and negative anomaly of winter air temperature in Xinjiang depended on the intensity of the Polar vortex in northeastern Hemisphere and geopotential height anomaly in the east of 70°E longitude and middle latitude.

Based on dynamic downscaling simulation data of temperature and precipitation by the regional climate model version 4 (RegCM4) from National Climate Center under the representative concentration pathways 4.5 (RCP4.5) and RCP8.5 scenarios, the simulation ability of RegCM4 was tested in baseline period (1986-2005). And on this basis, the climate change was analyzed in North China in future of the 21st century. The results show that RegCM4 had a better performance in simulating air temperature and precipitation in North China in baseline period. The change of surface air temperature, precipitation, consecutive dry days (CDD) and strong precipitation (R95p) under RCP4.5 and RCP8.5 scenarios will increase gradually in North China in future of the 21st century, but their changes under RCP4.5 scenario will be obviously less than those under RCP8.5 scenario. Under the higher emission scenario of RCP8.5, the annual mean air temperature will rise 1.77, 3.44 and 5.82 ℃ in near term (2021-2035), medium term (2046-2065) and long term (2080-2098) of the 21st century, the annual mean precipitation will increase 8.1%, 14% and 19.3%, CDD will reduce 3, 3 and 12 d, and R95p will increase 30.8%, 41.9% and 69.8%, respectively. In space, the mean air temperature in the whole year, winter and summer in North China will rise consistently in future of the 21st century, and the warming in summer will be the most, while the mean precipitation in the whole year, winter and summer will increase in most regions, and the increase of precipitation in winter will be the most. Meanwhile, CDD will decrease except in Shanxi and Beijing-Tianjin-Hebei areas in near term and medium term, while R95p will increase, which indicated that the drought events will reduce and the extreme precipitation will increase in the 21st century.