Urban heat islands (UHIs) are one of the most typical changes to surface climate induced by human activities, which manifest as higher temperatures in urban areas than in their surroundings. In this study, we synthetically analyzed spatiotemporal features of daytime surface UHI intensity in east China over the period from 2009 to 2018 carried out with several offline simulations coupled with four land‐use data sets, and identified the causes of UHIs with two attribution methods. The results indicate that spatial variations of summer daytime UHI intensity in east China are dominated by variations in the efficiency of evaporating water (∼3°C) between urban and rural areas. Geographic variations of winter UHI intensity mainly depend on the urban‐rural contrast of heat storage capacity (∼1°C). Additionally, we found that forest‐covered rural areas have an extremely higher convection efficiency than urban areas and nonforest rural landscapes, resulting in a remarkable contribution to summer daytime UHI intensity (∼6°C). However, rural areas largely comprising croplands and grasslands evaporate water more efficiently, expanding summer daytime UHI intensity by approximately 3°C. The prominent capacity of heat storage in nonforest vegetation rural areas accounts for 1°C warming of winter daytime UHI intensity. The major discrepancy between the two attribution methods lies in the evapotranspiration performances of forest‐covered rural lands. Furthermore, the inter‐comparison of several modeling experiments for land‐use data sets suggests that the disparity in UHI intensity could increase by up to 0.4°C, which may exceed 1°C at the local scale.

The urban expansion‐induced heat can exacerbate heat stress for urban dwellers, especially during heat waves. With a focus on the intra‐urban variability of urban heat islands (UHIs) and thermal comfort, the urban parameterization within the Community Land Model version 5 (CLM5) was modified incorporating the local climate zones (LCZs) framework, named CLM5‐LCZs, to simulate the urban climate during a heat wave (HW) event in the summer of 2013. The evaluation of model performance demonstrated that it did a reasonable job of simulating surface energy balance and thermal regimes in cities against observational fluxes from a flux tower measurement site and temperatures from automatic meteorological stations in Nanjing, China. Then we investigated the characteristics and causes of UHIs associated with local background climate, intra‐urban inhomogeneity and HW intensity in East China. The results exhibited that daytime and nighttime canopy urban heat island intensity (CUHII) were highest in the Compact Low Rise (LCZ3) and the Compact High Rise (LCZ1) areas respectively, while surface urban heat island intensity (SUHII) peaked in the Large Low Rise (LCZ8) and the Compact High Rise (LCZ1) areas during daytime and nighttime respectively. Urban dwellers were easier exposed to serious heat environment in LCZ3 and LCZ1 areas over the north subtropical climate zone. Contrasts of CUHII and SUHII among different urban classes could exceed 1.7 °C and 5.4°C. The intra‐urban heterogeneity may alter the dominant factors controlling SUHII, which were also modulated by local climate and HW intensity. Unlike other controlling factors, the impact of local climate on the contribution from the urban‐rural contrast of convection efficiency was larger than urban features. Overall, CLM5‐LCZs displayed potential of implementing detailed simulations for inter‐ and intra‐city UHIs at a larger scale, and enhancing the capabilities in modelling urban climate and exploring the causes and controls of UHIs.

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