Impact of Rapid Urban Sprawl on the Local Meteorological Observational Environment Based on Remote Sensing Images and GIS Technology

Abstract

Rapid increases in urban sprawl affect the observational environment around meteorological stations by changing the land use/land cover (LULC) and the anthropogenic heat flux (AHF). Based on remote sensing images and GIS technology, we investigated the impact of changes in both LULC and AHF induced by urbanization on the meteorological observational environment in the Yangtze River Delta (YRD) during 2000–2018. Our results show that the observational environments around meteorological stations were significantly affected by the rapid expansion of built-up areas and the subsequent increase in the AHF, with a clear spatiotemporal variability. A positive correlation was observed between the proportion of built-up areas and the AHF around meteorological stations. The AHF was in the order urban stations > suburban stations > rural stations, but the increases in the AHF were greater around suburban and rural stations than around urban stations. Some meteorological stations need to be relocated to address the adverse effects induced by urbanization. The proportion of built-up areas and AHF around the new stations decreased significantly after relocation, weakening the urban heat island effect on the meteorological observations and substantially improving the observational environment. As a result, the observed daily mean temperature (relative humidity) decreased (increased) around the new stations after relocation. Our study comprehensively shows the impact of rapid urban sprawl on the observational environment around meteorological stations by assessing changes in both LULC and the AHF induced by urbanization. These findings provide scientific insights for the selection and construction of networks of meteorological stations and are therefore helpful in scientifically evaluating and correcting the impact of rapid urban sprawl on meteorological observations.

Influence of Changes in Meteorological Observational Environment on Urbanization Bias in Surface Air Temperature: A Review

“…In addition, anthropogenic heat released from boilers, air conditioners and motor vehicles within the city is transferred via the urban boundary layer (Zhang et al, 2016(Zhang et al, , 2021Yang et al, 2020a). The pollutants emitted exacerbate the urban heat island effect at night through the interaction of aerosols with solar radiation (Zheng et al, 2018).…”

“…The anthropogenic heat flux is closely related to changes in the built-up area around stations (Yang X. et al, 2019;Yang et al, 2020a;Chen G. et al, 2021;Zhang et al, 2021) and can reliably reflect the effects of both anthropogenic emissions and changes in land use related to the latent heat flux and the sensible heat flux. A characterization system of the MOE (the surface thermal environment class and the anthropogenic heat flux) centered on the thermal environment around a station has been developed based on remote sensing images and geographical information systems technology (Shi et al, 2015;Yang X. et al, 2019;Yang et al, 2020a,b;Zhang et al, 2021). This system solves the problem of the quantitative characterization of the influence of anthropogenic heat emissions on the SAT series under the effects of turbulent and horizontal advection.…”

“…Previous studies have shown that the errors caused by MOE changes and destructions are usually greater than the instrumental observation errors, which can completely submerge the signal of climate change (Gallo et al, 1996;Peterson, 2003;Vose and Menne, 2004;Soon et al, 2018;Zhang et al, 2021). For example, Peterson (2003) proposed that the micro-scale and local-scale environments have greater influence on the observation data of stations than the meso-scale environments.…”

“…Therefore, these two biases can occur independently. For example, an urban site with a significant urbanization bias may have a good degree of environmental exposure, while a rural site that is not affected by the urbanization bias may have a siting bias due to insufficient environmental exposure (Davey and Pielke, 2005;Menne et al, 2010;Ren et al, 2015;Zhang et al, 2021). It can be seen that changes in meteorological elements are not only extremely sensitive to local MOE changes around the station but also to urbanization bias.…”

“…Peterson (2003) suggested that the micro-scale and local-scale environments have a greater impact on observations of meteorological elements than meso-scale environments. In eastern China, rapidly increasing urban sprawl impacted on the MOE, showing that the maximum range of influence affecting observational data under advection and turbulence transport conditions does not usually exceed 5 km (Ren and Ren, 2011;Tysa et al, 2019;Yang et al, 2020a;Zhang et al, 2021).…”