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The drag coefficient ( 𝐴𝐴 𝐴𝐴𝑑𝑑 ) is an important parameter of the land surface layer that represents the efficiency of momentum exchange between the Earth's surface and is thus important in numerical models for the climate simulation and weather forecasting, such as the prediction of typhoons (Emanuel, 1995) and sandstorms (Okin, 2005). Previous studies documented that 𝐴𝐴 𝐴𝐴𝑑𝑑 levels off over land (Raupach & Thom, 1981;Wieringa, 1993

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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In order to meet the demand of more refined urban weather forecast, it is of great practical significance to improve and optimize the single-layer urban canopy model (SLUCM) suitable for the megacity of Shanghai. In this paper, based on the offline SLUCM model driven by a whole-year surface flux observation data in the Shanghai central business district, a series of parameter sensitivity tests are carried out by using the one at a time (OAT) method, the relative importance and a set of optimized parameters of the SLUCM suitable for high-density urban area are established, and the improvement of simulation is evaluated. The results show that SLUCM well reproduces the seasonal mean diurnal patterns of the net all-wave radiation flux ( Q ∗ ) and sensible heat flux (QH) but underestimates their magnitudes. Both Q ∗ and QH are linearly sensitive to the albedo, and most sensitive to the roof albedo, the second to the wall albedo, but relatively insensitive to the road albedo. The sensitivity of Q ∗ and QH to emissivity is not as strong as that of albedo, and the variation trend is also linear. Similar to albedo, Q ∗ and QH are most sensitive to roof emissivity. The effect of thermal parameters (heat capacity and conductivity) on fluxes is logarithmic. The sensitivity of surface fluxes to geometric parameters has no specific variation pattern. After parameter optimization, RMSE of Q ∗ decreases by about 3.4–18.7 Wm−2 in four seasons. RMSE of the longwave radiation (L↑) decreases by about 1.2–7.87 Wm−2. RMSE of QH decreases by about 2–5 Wm−2. This study provides guidance for future development of the urban canopy model parameterizations and urban climate risk response.