A dataset of 282 meteorological stations including all of the ordinary and national basic/reference surface stations of north China is used to analyze the urbanization effect on surface air temperature trends. These stations are classified into rural, small city, medium city, large city, and metropolis based on the updated information of total population and specific station locations. The significance of urban warming effects on regional average temperature trends is estimated using monthly mean temperature series of the station group datasets, which undergo inhomogeneity adjustment. The authors found that the largest effect of urbanization on annual mean surface air temperature trends occurs for the large-city station group, with the urban warming being 0.16°C (10 yr)−1, and the effect is the smallest for the small-city station group with urban warming being only 0.07°C (10 yr)−1. A similar assessment is made for the dataset of national basic/reference stations, which has been widely used in regional climate change analyses in China. The results indicate that the regional average annual mean temperature series, as calculated using the data from the national basic/reference stations, is significantly impacted by urban warming, and the trend of urban warming is estimated to be 0.11°C (10 yr)−1. The contribution of urban warming to total annual mean surface air temperature change as estimated with the national basic/reference station dataset reaches 37.9%. It is therefore obvious that, in the current regional average surface air temperature series in north China, or probably in the country as a whole, there still remain large effects from urban warming. The urban warming bias for the regional average temperature anomaly series is corrected. After that, the increasing rate of the regional annual mean temperature is brought down from 0.29°C (10 yr)−1 to 0.18°C (10 yr)−1, and the total change in temperature approaches 0.72°C for the period analyzed.

Historically, the climate of the HKH has experienced significant changes that are closely related to the rise and fall of regional cultures and civilizations. Studies show well-established evidence that climate drivers of tropical and extra-tropical origin—such as the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), the Madden-Julian Oscillation (MJO), and the Arctic Oscillation—influence the region’s weather and climate on multiple spatio-temporal scales.

Climate change has a distinct impact on agriculture in China, particularly in the northeast, a key agriculture area sensitive to extreme hydroclimate events. Using monthly climate and agriculture data, the influence of drought on maize and soybean yields—two of the main crops in the region—in northeast China since 1961 to 2017 were investigated. The results showed that the temperature in the growing season increased by 1.0 °C from the period 1998–2017 to the period 1961–1980, while the annual precipitation decreased slightly. However, precipitation trends varied throughout the growing season (May–September), increasing slightly in May and June, but decreasing in July, August and September, associated with the weakening of the East Asian summer monsoon. Consequently, the annual and growing season drought frequency increased by 15%, and 25%, respectively, in the period 1998–2017 relative to the period 1961–1980. The highest drought frequency (55%) was observed in September. At the same time, the drought intensity during the growing season increased by 7.8%. The increasing frequency and intensity of drought had negative influences on the two crops. During moderate drought years in the period 1961–2017, 3.2% and 10.4% of the provincial maize and soybean yields were lost, respectively. However, during more severe drought years, losses doubled for soybean (21.8%), but increased more than four-fold for maize (14.0%). Moreover, in comparison to the period 1961–1980, a higher proportion of the yields were lost in the period 1998–2017, particularly for maize, which increased by 15% (increase for soybean was 2.4%). This change largely depends on increasing droughts in August and September, when both crops are in their filling stages. The impact of drought on maize and soybean production was different during different growth stages, where a strong relationship was noted between drought and yield loss of soybean in its filling stage. Given the sensitivity of maize and soybean yields in northeast China to drought, and the observed production trends, climate change will likely have significant negative impacts on productivity in the future.

Heavy PM_2.5 (particulate matter with aerodynamic diameter equal to or less than 2.5 μm) pollution and urban heat island (UHI) pose increasing threats to human health and living environment in populated cities. However, how PM_2.5 pollution affects the UHI intensity (UHII) has not been fully understood. The impacts of PM_2.5 on the wintertime UHII in the Beijing‐Tianjin‐Hebei megalopolis of China are explored during 2013–2017. The results show that the UHII at the time of daily maximum/minimum temperature (UHII_max/UHII_min) exhibits a decreasing/increasing tendency as PM_2.5 concentration increases, causing a continuous decrease in the diurnal temperature range. These effects are mediated via aerosol‐radiation interaction (aerosol‐cloud interaction) under clear‐sky (cloudy) condition. The changes in PM_2.5 concentration further cause different relative trends of UHII_max/UHII_min/diurnal temperature range across different cities in the Beijing‐Tianjin‐Hebei region, which are likely related to the differences in both the PM_2.5 composition and city size. This study provides insights on how air pollution affects urban climate and would help to design effective mitigation strategies.