scholarly journals Changes in daily and cumulative volumetric rainfall at various intensity levels due to urban surface expansion over China

2020 ◽  
Vol 72 (1) ◽  
pp. 1-21
Author(s):  
Deming Zhao ◽  
Jinlin Zha ◽  
Jian Wu
Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 48
Author(s):  
Deming Zhao ◽  
Jian Wu

The impacts of urban surface expansion, based on satellite-derived data displaying urban surface expansion in China at different spatial scales from 1980 to 2016, were investigated using nested dynamical downscaling methods with the Weather Research and Forecasting (WRF) regional climate model at a 3.3-km resolution over a city and city cluster scale. Urban-related warming, based on daily mean surface air temperature at 2 m (SAT), calculated from the averages of four time records each day (00, 06, 12, and 18 h UTC, T4) and averages of SAT maximum (Tmax) and minimum (Tmin) (Txn), was evaluated. Differences in urban-related warming contributions calculated using T4 and Txn were small, whereas annual mean SAT and trends calculated using Txn were respectively and significantly larger and smaller than those calculated using T4 over Guangzhou and Shenzhen, excluding the trends over middle-northern Shenzhen. The differences in annual mean SAT calculated using T4 and Txn are attributed to nonlinear or asymmetric variations with time for the diurnal cycle of SAT. Meanwhile, differences in trends between T4 and Txn are interpreted as a strong trend for Tmin and a weak one for Tmax, which mitigated the trend for Txn. The impacts on the evaluations of urban-related warming contributions calculated from different methods were the largest over the areas classified as urban surfaces in both time periods (U2U), especially during intense urban-surface-expansion periods between 2000 and 2016. The subregional performances in the changes in annual mean SAT, trends, and urban-related warming are attributed to urban-surface-expansion, which induced varied changes in the diurnal cycle due to asymmetric warming during the daytime and nighttime over different subregions.


2017 ◽  
Vol 56 (6) ◽  
pp. 1551-1559 ◽  
Author(s):  
Deming Zhao ◽  
Jian Wu

AbstractThe contribution of urban surface expansion to regional warming as detected from meteorological observational station data may vary with considerable uncertainty because of the spatial heterogeneity of such data—a situation that promotes a requirement for numerical model-based investigations. Satellite-based images from 1980 to 2016 that have fine resolution over three city clusters and that display the urban surface expansion in China from rapid economic development and anthropogenic activity were used to perform 37-yr nested dynamical downscaling using the Weather Research and Forecasting (WRF) Model. The urban surface areas in Beijing, China, expressed marked expansion in the last 37 years. The contribution of urban surface expansion to regional warming was approximately 22% of the overall warming in Beijing and was stronger in the plains areas of Beijing (42%). The contributions to land-use grids that changed from nonurban (in 1980) to urban (in 2016; N2U) were much stronger than those to grids that were classified as urban in both time periods (U2U), which were closer to the values of urban areas (including N2U and U2U) because of the intense increase in urban surface areas. Urban-related warming expressed marked annual variation and was greater in the warm seasons and smaller in the cold seasons. The greater increase in surface air temperature (SAT) minimum and the weaker SAT maximum accounted for the decreased diurnal temperature range.


2017 ◽  
Vol 30 (3) ◽  
pp. 1061-1080 ◽  
Author(s):  
Deming Zhao ◽  
Jian Wu

Abstract Incorporating satellite-based urban surface data for the 1980s, 1990s, 2000s, and 2010s in China, contributions to regional warming, and changes in the precipitation due to urban surface expansion were explored using the nested Fifth-generation Pennsylvania State University–NCAR Mesoscale Model version 3.7 (MM5V3.7) with urban effects considered. The impact on surface air temperature at 2 m (SAT) due to urban surface expansion between the 1980s and the 2010s revealed that annual urban-related warming was lower over East Asia (0.031°C) and China (0.075°C) but higher in eastern China (0.14°C), which experienced dramatic urbanization. Greater warming could be detected over urban surface areas in the three city clusters [Beijing–Tianjin–Hebei (BTH) and the Yangtze and Pearl River deltas (YRD and PRD, respectively)], which reached 1.06°, 0.84°, and 0.92°C, respectively. Urban-related warming was not limited to a single city or city clusters but extended over a SAT-increased belt that covered the eastern coast of China. Further analysis showed that urban-surface-expansion-induced changes in albedo and the total cloud amount contributed to the changes in the radiation budget, which resulted in strong surface radiative forcings in the urban surface (14.5, 11.2, and 11.7 W m−2 for BTH, YRD, and PRD, respectively). However, significant differences could be detected for the transition from nonurban to urban land use compared to those that were classified as urban in both time periods because of the varied albedo changes. The urbanization-related warming, especially in the city cluster areas, also had a further effect on the large-scale circulation and precipitation. The precipitation was weakened in northeastern and northern China but intensified in eastern and southern China, which resulted in the strengthened precipitation over China (0.016 mm day−1, 0.65%) and East Asia (0.011 mm day−1, 0.28%). Therefore, subregional characteristics with marked seasonal, interannual, and decadal variations were detected for the influence of the urban surface expansion.


1986 ◽  
Vol 47 (C4) ◽  
pp. C4-289-C4-303
Author(s):  
R. LACEY ◽  
N. N. AJITANAND ◽  
J. M. ALEXANDER ◽  
D.M. DE CASTRO RIZZO ◽  
G. F. PEASLEE ◽  
...  

2021 ◽  
Vol 194 ◽  
pp. 110730
Author(s):  
Olivia Ginn ◽  
Dennis Nichols ◽  
Lucas Rocha-Melogno ◽  
Aaron Bivins ◽  
David Berendes ◽  
...  

Author(s):  
Qing Ding ◽  
Zhenfeng Shao ◽  
Xiao Huang ◽  
Orhan Altan ◽  
Qingwei Zhuang ◽  
...  

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