Urban Heat Island Simulations in Guangzhou, China, Using the Coupled WRF/UCM Model with a Land Use Map Extracted from Remote Sensing Data

Guang Chen, Lihua Zhao, Akashi Mochida
2016 Sustainability  
The Weather Research and Forecasting (WRF) model coupled with an Urban Canopy Model (UCM) was used for studying urban environmental issues. Because land use data employed in the WRF model do not agree with the current situation around Guangzhou, China, the performance of WRF/UCM with new land-use data extracted from Remote Sensing (RS) data was evaluated in early August 2012. Results from simulations reveal that experiments with the extracted data are capable of reasonable reproductions of the
more » ... ajority of the observed temporal characteristics of the 2-m temperature, and can capture the characteristics of Urban Heat Island (UHI). The "UCM_12" simulation, which employed the extracted land-use data with the WRF/UCM model, provided the best reproduction of the 2-m temperature data evolution and the smallest minimum absolute average error when compared with the other two experiments without coupled UCM. The contributions of various factors to the UHI effect were analyzed by comparing the energy equilibrium processes of "UCM_12" in urban and suburban areas. Analysis revealed that energy equilibrium processes with new land use data can explain the diurnal character of the UHI intensity variation. Furthermore, land use data extracted from RS can be used to simulate the UHI. Many studies have performed simulations using land use data from different years with the single-layer urban canopy model in the Noah land surface model to demonstrate that urban development and the accompanying land use changes can make a significant contribution to extreme heat events [9] [10] [11] [12] . However, the default data (U.S. Geological Survey (USGS) land use) employed in the WRF model are based on the NationalOceanic and Atmospheric Administration (NOAA) 1-km Advanced Very High Resolution Radiometer (AVHRR) data obtained from 1992 to 1993. Owing to the rapid urban expansion in the past decade in China, the USGS data are considered outdated. Numerical simulations in Guangzhou [9] and Chengdu [13] with the new land use data reproduced better 2-m temperature evolution data with a smaller minimum absolute average error compared with results obtained using the default USGS land use data in the WRF model. Versions of the WRF model after version 3.1 provide an alternative land use dataset based on the Moderate Resolution Imaging Spectroradiometer (MODIS) 2001 satellite products. Implementation of MODIS data results in better performance of the coupled WRF/UCM modeling system, although the urban area in MODIS also falls short of reality because of fast urbanization [14] . The diurnal variations of UHI intensity and the spatial distribution of the UHI effect in Beijing have been reproduced well by the WRF/UCM with MODIS data [15] . The simulation results with MODIS data improved predictions of the accumulated rainfall when compared with the simulation performed using USGS data [16] . Numerical simulations of Taiwan showed that results obtained using MODIS land use data are in better agreement with the observed data than those obtained using USGS data, although MODIS land use data overestimated the urban area [17] . When compared with observational data, numerical simulations in Guangzhou [18] showed improved accuracy using MODIS data compared with USGS data, but poorer accuracy than that obtained using land use data extracted from the Landsat-7 remote sensing dataset. The effect of urbanization on the weather and climate in Hangzhou were investigated using the coupled WRF/UCM model with updated land use data, and the research showed that updated land use data can reproduce the local climate accurately, and that urban land use has a significant impact on the simulated UHI effect [19] . In this study, the land-use data were extracted from the remote sensing dataset of Landsat-7 using a previous research [20] method and then up-to-date extracted land-use data classified as urban land cover were divided into three urban subcategories by satellite-measured night time light data and the normalized difference vegetation index dataset. The mesoscale coupled WRF/UCM model with different land-use data are used to simulate the formation of high-temperature synoptic conditions in the area of Guangzhou in early August 2012. The aim of this research is to demonstrate that, when using the extracted and up-to-date urban land use data from a remote sensing dataset, the WRF/UCM modeling system provides a more accurate simulation of urban temperatures and the UHI effect in Guangzhou. Furthermore, the study aims to simulate the formation of high-temperature synoptic conditions in the area of Guangzhou, and to investigate the properties of coupled WRF/UCM model and their effects on the UHI simulations.
doi:10.3390/su8070628 fatcat:guohp4i725bh7p7dnvglsnxqpm