Utilizing hourly temperature data from 107 regional automatic weather stations and 5 conventional stations in Nanjing from 2018 to 2020, a comprehensive analysis of the variation characteristics of temperature effect intensity in different typical local environments of the main urban area and suburbs of Nanjing was conducted. This analysis was grounded in the local climate zoning system and augmented by remote sensing images from Tianditu and station photos. The findings reveal that the background environment plays a significant role in influencing the temperature effects of local environments. In urban areas, the combined effects of ground hardening and the built environment's thermal characteristics tend to amplify the warming effect or mitigate the cooling effect of local environments. Conversely, in suburban areas, where human modifications to the natural landscape are less pronounced, the temperature patterns of these environments align more closely with traditional understandings. Within the suburban context, specific environmental features exhibit distinct seasonal and diurnal temperature effects. For instance, the built environment consistently exhibits a warming effect throughout the year, while dense tree provides a cooling effect. Water bodies, on the other hand, tend to cool in spring and summer but warm in autumn and winter, exhibiting diurnal temperature variations. The extreme temperature effect intensity in local environments in Nanjing can reach approximately ±8 ℃. The most probable weather condition for such extreme effects is sunny days, followed by local rainfall events. Sunny weather conditions tend to accentuate the temperature effects of local environments, while during local rainfall, the temperature contrast between rainy and non-rainy areas becomes more pronounced, contributing to significant spatial variations in the temperature field.
参考文献
相似文献
引证文献
引用本文
林依宁,曾燕,邱新法.南京市局地环境气温效应.气象科学,2025,45(1):145-154 LIN Yining, ZENG Yan, QIU Xinfa. The effect of local environmental temperature in Nanjing. Journal of the Meteorological Sciences,2025,45(1):145-154