Search

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The continuous expansion of impervious artificial surfaces in cities has significantly influenced the urban thermal environment. This paper examines the spatiotemporal variation of the diurnal surface urban heat island (SUHI) in Shanghai from 1989 to 2013, a period during which the city has experienced drastic development changes. A remote sensing approach was taken to derive the spatial patterns of Shanghai’s land surface temperature (LST) from Landsat Thematic Mapper (TM) images and Operational Land Imager (OLI) data. The LST pattern was further classified into five LST classes to look at the relative SUHI intensity level across the whole city. Spatial analyses, namely, spatial association and centroid movement analysis, were conducted to reveal the trends of LST changes at both local and holistic scales. To understand the potential drivers for the present spatiotemporal variation of SUHI, different indicators including land use change, population density, night light data, and vegetation were analyzed and compared with LST changes. Based on the quantitative analysis and the socioeconomic context of Shanghai, “heating up” regions were identified, possible reasons for such SUHI variation were summarized, and districts that are most vulnerable to extreme heat conditions were projected. In terms of implication for urban development, planning and design recommendations were suggested to improve the urban thermal environment in Shanghai. [ABSTRACT FROM AUTHOR]