Urbanization Effect in Regional Temperature Series Based on a Remote Sensing Classification Scheme of Stations

Abstract

Quantifying the urbanization effect on station and regional surface air temperature (SAT) trends is a prerequisite for monitoring and detecting long‐term climate change. Based on the data set of satellite visible spectral remote sensing, a new method is developed to determine the urbanization level around observational sites on varied spatial scales and to classify the sites into different categories of stations (U1, U2, …, U6) with U1 the least and U6 the largest affected by urbanization. Urbanization effect on SAT anomaly series of urban and national stations are then evaluated for the periods of 1980–2015 and 1960–2015. Results show that the percentage of built‐up area in different circumferences of the observational sites can be considered as a good indicator of comprehensive urbanization level of station and can be used to classify stations and to determine reference stations; the largest increase in annual mean SAT (Tmean) during 1980–2015 occurred at U6 stations, and U1 stations registered the weakest annual mean warming. The urbanization level is significantly positively correlated to the linear trends of annual mean Tmean and minimum SAT (Tmin) and significantly negatively correlated to the diurnal temperature range (DTR) change. The data sets of the national reference climate station network and basic meteorological station network show large urbanization effect and contribution, with the annual mean urbanization contributions reaching 28.7% and 25.8% for the periods 1960–2015 and 1980–2015, respectively. For all the national stations (2,286 in total), the urbanization contributions are 17.1% and 14.6% for the two same periods, respectively.

A New Evaluation of the Role of Urbanization to Warming at Various Spatial Scales: Evidence From the Guangdong‐Hong Kong‐Macau Region, China

“…Wang et al, 2015;K. C. Wang et al, 2017), due to the use of different data sources and processing methods, such as the use of model data to assess the impact of urbanization on site records (Koopmans et al, 2015;Van Weverberg et al, 2008), as well as different aspects of urbanization, such as the classification of urbanization level (Oke et al, 2017;Tysa et al, 2019). Therefore, accurate detection and extraction of the contribution of urbanization to the climate warming remain an important subject of study.…”

“…For the global average surface air temperature (SAT) change, studies indicated that the impact of urbanization on the contribution to the large‐scale warming is of secondary importance and is an order of magnitude smaller than the climate warming itself (Intergovernmental Panel on Climate Change, Trenberth et al, 2007; Hartmann et al, 2013; Jones et al, 1990; Q. X. Li, Sun, et al, 2020; Parker, 2004). However, there are significant differences (from less than 5% to more than 40% of the total warming in China), and these lead to uncertainties in the urbanization contribution to national and regional warming over China (Jones et al, 2008; Q. X. Li et al, 2004; Ren et al, 2008; Yan et al, 2009; X. Yang et al, 2011, 2013; Ye et al, 2018; F. Wang et al, 2015; K. C. Wang et al, 2017), due to the use of different data sources and processing methods, such as the use of model data to assess the impact of urbanization on site records (Koopmans et al, 2015; Van Weverberg et al, 2008), as well as different aspects of urbanization, such as the classification of urbanization level (Oke et al, 2017; Tysa et al, 2019). Therefore, accurate detection and extraction of the contribution of urbanization to the climate warming remain an important subject of study.…”

Characteristics and main influence factors of heat waves in Beijing–Tianjin–Shijiazhuang cities of northern China in recent 50 years

“…As shown in Figure 5, the average annual temperature in Beijing is positively related with the annual maximum temperature and the number of high temperature days, with the correlation coefficients of 0.540 and 0.579, respectively, indicating the important influence of climate warming on local heat wave events. Moreover, heat wave events are found to be associated with atmospheric circulation anomalies (Luo and Lau, 2017 Furthermore, urbanization can lead to changes in the increase of surface temperature (Tysa et al, 2019). There is a positive feedback relationship between urbanization warming effect and high temperature weather (Liu et al, 2018;He et al, 2019).…”

“…Moreover, heat wave events are found to be associated with atmospheric circulation anomalies (Luo and Lau, 2017, 2018; Chen et al ., 2019; Xu et al ., 2019). Furthermore, urbanization can lead to changes in the increase of surface temperature (Tysa et al ., 2019). There is a positive feedback relationship between urbanization warming effect and high temperature weather (Liu et al ., 2018; He et al ., 2019).…”

Urbanization Significantly Affects Pan-Evaporation Trends in Large River Basins of China Mainland

“…Due to the rapid urbanization process and urban expansion of the world (especially in China) over the past decades, many weather stations which were originally located in rural environments are gradually getting closer and closer to the urban, and even surrounded by urban areas. The research of Tysa et al (2019) [18] showed that nearly 90% of the 2286 observation stations in China were surrounded by built-up areas. As a result, the wind speed and solar radiation of the stations affected by urbanization might have been decreased, which might have caused the pan-evaporation to decrease.…”