Numerical study of the impact of urbanization on the precipitation over Taiwan

Lin, Chih-Hong; Chen, W. C.; Liu, Shaw C.; Liou, Yuei-An; Liu, G. R.; Lin, Tang-Huang

doi:10.1016/j.atmosenv.2007.12.054

Cited by 88 publications

(51 citation statements)

References 32 publications

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“…Because of the mountains along the east, most of the population is concentrated on the western coastal plain of Taiwan where periurbanization is leading to increased pressure on the environment (Huang et al, 2009). Intensive urban and industrial development with high population density has turned the western plain of Taiwan into a "mega-city" since the 1970s (Lin et al, 2008). Nearly 80% of Taiwan's population currently lives in urban areas, making it a highly urbanized nation.…”

Section: Peri-urban Land Use Change In Western Taiwanmentioning

confidence: 99%

Ecosystem services in peri-urban landscapes: The effects of agricultural landscape change on ecosystem services in Taiwan's western coastal plain

Lee

Ahern

Yeh

2015

Landscape and Urban Planning

110

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Section: Peri-urban Land Use Change In Western Taiwanmentioning

confidence: 99%

Ecosystem services in peri-urban landscapes: The effects of agricultural landscape change on ecosystem services in Taiwan's western coastal plain

Lee

Ahern

Yeh

2015

Landscape and Urban Planning

110

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“…High heat capacity and impermeable surfaces in urban land lead to more heat storage and air warmth because these raise heat absorption and lower heat consumption. In addition, tall buildings increase surface roughness, thus reducing the rate of ventilation in urban areas (Lin et al, 2008). Preferential heating in the city compared to the surrounding area also increases convection over the city that traps heat (as well as pollutants) inside the urban area (Oke, 1982;Arnfield, 2003).…”

Section: The Relationship Between Population Density and Anthropogenimentioning

confidence: 99%

“…The changes in LUCC widen the temperature difference between urban and rural areas. Lin et al (2008) pointed out that Taichung and two other smaller nearby cities in Taiwan clearly show higher temperatures than those over mountains and farmlands. The temperature at the centre of Taichung is about 5°C higher than that over the forested mountain area to the east and the rice paddies to the west.…”

Section: Introductionmentioning

confidence: 99%

Climate change and its human dimensions based on GIS and meteorological statistics in Pearl River Delta, Southern China

Dou

Zhao

2010

Meteorological Applications

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Climate change in the Pearl River Delta (PRD) has attracted growing attention along with rapid urbanization in Southern China. Annual mean temperatures in this area have increased more rapidly than the average level, which can be attributed to population expansion and land use changes in this region.In this study, temperature records from 31 weather stations in the PRD in Guangdong, China and the global dataset from the National Centres for Environmental Prediction (NCEP) Reanalysis (R-2) are analysed. Data from NCEP R-2 and temperature soundings taken at 850 hPa are used to define the background temperature. Anthropogenic temperature is then calculated according to the observed temperature and background temperature. The relationships of anthropogenic temperature to population density and area ratio of land-use types are analysed by univariate and multiple regression analysis techniques.Spatial distribution of anthropogenic temperature in the daytime is different from that at night. Model results indicate that relationships between population and anthropogenic temperature in the daytime are logarithmic or inverse but tend to be linearly related at night. Multiple regression analysis conducted on the area ratios of land-use types and anthropogenic temperature shows that a strong relationship exists between the two in spring and autumn. Positive correlations with anthropogenic temperature from arid land, water bodies and urban land, as well as a negative correlation from woodland, are detected regardless of time of day. Contrary to the paddy field, grassland and sea show a negative correlation with anthropogenic temperature in the daytime and a positive correlation at night.

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“…The important impact of changes in land use and land cover (LULC) on precipitation and climate has also been much emphasized (e.g., Kalnay and Cai, 2003;Koster et al, 2004;Feddema et al, 2005;Lin et al, 2008aLin et al, , 2011IPCC, 2007IPCC, , 2013Wang et al, 2014). It is estimated that the world's population will rise to 9.3 billion in 2050 (http://esa.un.org/ unpd/wup/index.htm).…”

Section: Introductionmentioning

confidence: 99%

Impact of an improved WRF urban canopy model on diurnal air temperature simulation over northern Taiwan

Lin

Kusaka

et al. 2016

Atmos. Chem. Phys.

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Abstract. This study evaluates the impact of urbanization over northern Taiwan using the Weather Research and Forecasting (WRF) Model coupled with the Noah land-surface model and a modified urban canopy model (WRF-UCM2D). In the original UCM coupled to WRF (WRF-UCM), when the land use in the model grid is identified as "urban", the urban fraction value is fixed. Similarly, the UCM assumes the distribution of anthropogenic heat (AH) to be constant. This may not only lead to over-or underestimation of urban fraction and AH in urban and non-urban areas, but spatial variation also affects the model-estimated temperature. To overcome the abovementioned limitations and to improve the performance of the original UCM model, WRF-UCM is modified to consider the 2-D urban fraction and AH (WRF-UCM2D).The two models were found to have comparable temperature simulation performance for urban areas, but large differences in simulated results were observed for non-urban areas, especially at nighttime. WRF-UCM2D yielded a higher correlation coefficient (R 2 ) than WRF-UCM (0.72 vs. 0.48, respectively), while bias and RMSE achieved by WRF-UCM2D were both significantly smaller than those attained by WRF-UCM (0.27 and 1.27 vs. 1.12 and 1.89, respectively). In other words, the improved model not only enhanced correlation but also reduced bias and RMSE for the nighttime data of non-urban areas. WRF-UCM2D performed much better than WRF-UCM at non-urban stations with a low urban fraction during nighttime. The improved simulation performance of WRF-UCM2D in non-urban areas is attributed to the energy exchange which enables efficient turbulence mixing at a low urban fraction. The result of this study has a crucial implication for assessing the impacts of urbanization on air quality and regional climate.

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Numerical study of the impact of urbanization on the precipitation over Taiwan

Cited by 88 publications

References 32 publications

Ecosystem services in peri-urban landscapes: The effects of agricultural landscape change on ecosystem services in Taiwan's western coastal plain

Ecosystem services in peri-urban landscapes: The effects of agricultural landscape change on ecosystem services in Taiwan's western coastal plain

Climate change and its human dimensions based on GIS and meteorological statistics in Pearl River Delta, Southern China

Impact of an improved WRF urban canopy model on diurnal air temperature simulation over northern Taiwan

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