There is an ongoing debate as to whether the UHI intensity (UHII) is enhanced or dampened under heat waves (HWs). Using a comprehensive dataset including continuous surface energy flux data for three summers (2016–18) and automated weather station data for six summers (2013–18) in Shanghai, China, we find synergies between UHIs and HWs when either a coastal or an inland suburban site is used as the reference site. We further find that during HWs, the increase of net radiation at the urban site is larger than that at the suburban site. More importantly, the latent heat flux is slightly reduced at the urban site but is slightly increased at the suburban site, while the increase of the sensible heat flux is larger at the urban site. This change of surface energy partitioning, together with the increased anthropogenic heat flux during HWs, exacerbates the UHII. The change of surface energy partitioning is consistent with the observed decrease of relative humidity ratio between urban and suburban areas. The UHII is stronger when the regional wind speed is reduced and under sea breeze, both of which are found to be associated with HWs in our study region. This study suggests that there are multiple factors controlling the interactions between UHIs and HWs, which may explain why synergies between UHIs and HWs are only found in certain metropolitan regions and/or under certain HW events.

The observed surface energy balance fluxes are essential to improve model forecasting ability but such data are scarce for subtropical cities and urban areas with tall buildings. One year of eddy covariance flux data for an area within Shanghai with a wide range of building heights (8-150 m, mean by direction) are analysed by wind direction. Consideration is given to how to distinguish between local-and micro-scale fluxes. At the local-scale, median daily peaks of sensible heat flux occur in the early afternoon (winter: 87 W m −2 , spring: 205 W m −2 , summer: 292 W m −2 , autumn: 135 W m −2 ). The latent heat flux is small in winter (median daily maxima 21 W m −2 ) and slightly larger in spring, summer and autumn (49, 65, 49 W m −2 , respectively). The monthly mean daytime Bowen ratio under all-sky conditions ranges from 2 to 4.7. At this site, with predominately impervious surface (85% buildings/pavement, 14% vegetation), the enhancement of evaporation following rainfall usually lasts for about 12 h. Consistently larger Bowen ratios at the micro-scale than the local-scale are attributed to roughness effects and the impact of extensive areas of dry walls. The daily median CO 2 flux is dominated by traffic emissions, with two peaks associated with morning and evening rush hours. The data provide insights into urban surface controls on momentum, energy and carbon dynamics, with implications for urban planning strategies in the context of rapid global urbanization and climate change.

Observations of atmospheric conditions and processes in cities are fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality, and climate models, and providing key information for city end users (e.g., decision makers, stakeholders, public). In this paper, Shanghai’s Urban Integrated Meteorological Observation Network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being multipurpose (e.g., forecast, research, service), multifunction (e.g., high-impact weather, city climate, special end users), multiscale (e.g., macro/meso, urban, neighborhood, street canyon), multivariable (e.g., thermal, dynamic, chemical, biometeorological, ecological), and multiplatform (e.g., radar, wind profiler, ground based, satellite based, in situ observation/sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments, to identify data gaps based on science- and user-driven requirements, and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.

The Surface Urban Energy and Water Balance Scheme (SUEWS) is used to investigate the impact of anthropogenic heat flux QF and irrigation on surface energy balance partitioning in a central business district of Shanghai. Diurnal profiles of QF are carefully derived based on city-specific hourly electricity consumption data, hourly traffic data, and dynamic population density. The QF is estimated to be largest in summer (mean daily peak 236 W m−2). When QF is omitted, the SUEWS sensible heat flux QH reproduces the observed diurnal pattern generally well, but the magnitude is underestimated compared to observations for all seasons. When QF is included, the QH estimates are improved in spring, summer, and autumn but are poorer in winter, indicating winter QF is overestimated. Inclusion of QF has little influence on the simulated latent heat flux QE but improves the storage heat flux estimates except in winter. Irrigation, both amount and frequency, has a large impact on QE. When irrigation is not considered, the simulated QE is underestimated for all seasons. The mean summer daytime QE is largely overestimated compared to observations under continuous irrigation conditions. Model results are improved when irrigation occurs with a 3-day frequency, especially in summer. Results are consistent with observed monthly outdoor water use. This study highlights the importance of appropriately including QF and irrigation in urban land surface models—terms not generally considered in many previous studies.