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A distinct feature of Wuhan is that almost a quarter of the total area of this city is covered with water, leading to its unique hot and humid climate characteristics in summer. However, according to records, water area in built-up zone of Wuhan has been reduced by 130.5 km2 from 1965 to 2008, while the annual average air temperature has been incre...
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... is located in the geographic centre of China and is the capital city of Hubei province. The Yangtze River ( Figure 5) is the longest river in Asia and runs through Wuhan. The central region of Wuhan includes the entire built-up zone within a radius of 30 km, which consists of many rivers and lakes. Water areas inside the built-up zone of Wuhan have been reduced due to urban development from 1965 to 2008 by 130.5 km 2 . The water area maps of the built-up zone from 1965 and 2008 8 are shown in Figure 5(a) and (b), respectively, and are used to calculate the domains shown in Figure 6. Domain 3 includes the entire built-up zone of Wuhan and is centred at 114.30 E, 30.50 N. Resolution of the horizontal grid of domain 3 is 0.5 km. The coarse grid values at the boundaries of the nested area have provided boundary conditions for the nested grid. The vertical direction was divided into 35 layers from the ground surface up to an altitude of approximately 20 km in the model. Further details of computational domains and grid arrangements are listed in Table ...
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... is located in the geographic centre of China and is the capital city of Hubei province. The Yangtze River ( Figure 5) is the longest river in Asia and runs through Wuhan. The central region of Wuhan includes the entire built-up zone within a radius of 30 km, which consists of many rivers and lakes. Water areas inside the built-up zone of Wuhan have been reduced due to urban development from 1965 to 2008 by 130.5 km 2 . The water area maps of the built-up zone from 1965 and 2008 8 are shown in Figure 5(a) and (b), respectively, and are used to calculate the domains shown in Figure 6. Domain 3 includes the entire built-up zone of Wuhan and is centred at 114.30 E, 30.50 N. Resolution of the horizontal grid of domain 3 is 0.5 km. The coarse grid values at the boundaries of the nested area have provided boundary conditions for the nested grid. The vertical direction was divided into 35 layers from the ground surface up to an altitude of approximately 20 km in the model. Further details of computational domains and grid arrangements are listed in Table ...
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... this section, estimates are given of the impact of land-use alterations for scenarios '1965', '2008' and 'No-water' on local wind systems. To clarify the effects of urbanization and land-use alteration, the same meteorological dataset was applied in the three scen- arios. Furthermore, only water areas were changed among scenarios. Wind velocity at 10 m AGL for the built-up zone at 1400 LST for scenarios '1965', '2008' and'No-water' is shown in Figure 14 Wind velocity increased significantly when the water areas were reduced in scenarios of '1965' ' to '2008. The higher wind velocity might be caused by the higher air temperatures. The areas with signifi- cant differences are highlighted inside the contour lines. The areas are in the downwind direction of 1400 LST. As mentioned earlier, the decrease of water area would cause the air temperature to rise. Cool air coming from rural area, passes through the built-up area, would become heated up, and would gain more kinetic energy. Therefore, wind velocity is higher in the cases of less water area and significant velocity differences are located in the downwind direction. In addition, the wind direction has slightly changed towards the east because of the reduction of water area. Altered wind velocity and direction are caused by the alteration of air temperature and its distribution. The areas with significant differences in wind velocity and direction are distributed among the downwind zones, which also show differences in air temperature and distribution. Figure 15 shows the average wind velocity and dir- ection over the course of a day for the entire area of the built-up zone for the three scenarios. During the period from 1400 LST to 1700 LST, wind velocity increased with a reduction in water area. Conversely, during the period from 0000 LST to 0600 LST, the wind velocity decreased along with water area. Within the hottest period of the day, the T2 would be highest in scenario with 'No-water' and would cause the largest local pres- sure differences. Hence, the wind velocity was also the highest in 'No-water' area. During the predawn hours, the wind velocity is primarily determined by roughness length because of small temperature differences Figure 11. Q2 and UMF differences between '1965' ('1965-2008, 'No-water' and'2008' ('NW-2008') '1965' and '2008' ('1965-2008') and 'No-water' and'2008' ('NW-2008') for the entire grids averaged for the built-up zone in domain 3 (area without land-use and land-cover change). The abscissa is local solar time. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] ...
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There is a consensus that Urban Heat Island phenomenon - UHI occurs in every large city. This effect is characterized by higher air temperatures in cities than in the neighboring countryside at night. However, to date, there has been no systematic study on the Fortaleza case, the Brazil's 5th largest city. By the comparison between screen-level air...
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... However, rapid urban growth is replacing green spaces and lakes with new residential areas and production plants, leading to fragmentation of ecological spatial patterns and subsequently posing a risk to the local microclimate. From 1965 to 2008, the water area within the built-up area of Wuhan decreased by 130.5 km 2 due to urban development (Zhou et al., 2014). ...
... From the very beginning of the use of the lake, its area began to be constantly transformed into agricultural land and land for construction. Excessive development has led to a reduction of the water body area of Nan Lake, the disappearance of several of its water system tributaries, and the gradual weakening of its connection with the Yangtze River [38], which has further led to the occurrence of urban flooding and the deterioration of the microclimate of the surrounding area [39]. As shown in Figure 2, due to the rapid development of urban construction, the area of Nan Lake has been gradually reduced, resulting in a corresponding reduction in the area of the waterfront. ...
As China’s urbanization progresses, thermal environmental problems such as the overheating effect experienced by cities are becoming more and more obvious in the daily lives of residents. Urban waterfront spaces not only create pleasant landscape environments and regulate microclimates, but also help to maintain ecological diversity. However, the current high-density urban construction model has led to poor air mobility and weakened water regulation functions in cities. Therefore, the rationalization of the spatial form of settlements has become particularly important in recent times. In this study, the Nan Lake area of Wuhan City was taken as the research object, and it was simulated using ENVI-met (5.5.1) software. Further, the orthogonal experimental design method was combined with the extremum difference analysis method. This study focused on the effects of the layout form (LF), floor area ratio (FAR), green form (GF), and offshore distance (OD) on the temperature (T), relative humidity (RH), and thermal comfort in waterfront settlements in summer. This study found that (1) among the various factors, the effect of the GFs and LFs on the overall microclimate of the study region was the most significant, while the volume ratio had the least significant effect on each indicator. (2) The parallel layout form was found to have better ventilation effects compared to the other three layout forms, with its cooling and humidifying effects being superior. (3) Among the four types of greening combinations, the combination of “grass + shrubs” had the best cooling effect at the height of pedestrians, while trees were able to reduce the heat transfer of solar radiation to the ground due to the shading and evaporation effects provided by their canopies. (4) The cooling and humidifying effects provided by the water body of Nan Lake gradually diminished as the distance from its shore increased; therefore, waterfront settlements maintaining a reasonable proximity to their water bodies will help bring into play the microclimate adjustment effect of such bodies. This study provides a valuable reference for the construction and renewal of urban waterfront settlements in the hot summer and cold winter zones of China (HSCW).
... In the rural area, the albedo of the forests and savannas is 0.14 and 0.2, respectively. The WRF model coupled with Noah-LSM has been demonstrated to give satisfactory predictions of UHI effects (Li et al., 2018a;Giannaros et al., 2013;Bhati and Mohan, 2016;Zhou and Marshall Shepherd, 2010;Chemel and Sokhi, 2012;Jr et al., 2013;Li et al., 2015b;Zhou et al., 2016;Sequera et al., 2016;Jänicke et al., 2017;Kawamoto, 2017;Dimitrova et al., 2019). ...
The impact of heatwaves (HWs) on urban heat island (UHI) is a contentious topic with contradictory research findings. A comprehensive understanding of the response of urban and rural areas to HWs, considering the underlying cause of surface energy budget changes, remains elusive. This study attempts to address this gap by investigating a 2020 HW event in the Greater Sydney Area using the Advanced Weather Research and Forecasting (WRF) model with 250-m high resolution. Findings indicate that the HW intensifies the nighttime surface UHI by approximately 4 °C. An analysis of surface energy budgets reveals that urban areas store more heat during the HW due to receiving more solar radiation and less evapotranspiration compared to rural areas. The maximum heat storage flux in urban during the HW can be around 200 W/m2 higher than that during post-HW. The stored heat is released at nightime, raising the air temperature in the urban areas. Forests and savannas have relatively lower storage heat fluxes due to high transpiration and albedo, and the maximum heat storage flux is only around 50 W/m2 higher than that during post-HW. In contrast, a negative synergistic effect is detected between the 2-m UHI and HW. This may be because other meteorological conditions including wind have substantial impacts on the air temperature pattern. The strong hot and dry winds coming from the west resulted in a higher air temperature in the western urban district, and intra-city disparities are higher. The difference Meanwhile, the western forest area also experiences higher temperatures due to the westward winds. In addition, changes in wind direction alter the temperature distribution in the northern rural region. The findings of the present study may provide some insights into urban heat mitigation during HW.
... The majority of the water bodies are proximal to parklands (Figure 2), which may have led to a spatial confound in the detected pattern. Additionally, simulations of cities with no urban water bodies have demonstrated increased wind speeds, which could allow particulate matter to remain suspended in the air column [69], while urban areas with natural or artificial water bodies may experience decreased wind speeds [69], facilitating particle deposition [51,70,71]. ...
... The majority of the water bodies are proximal to parklands (Figure 2), which may have led to a spatial confound in the detected pattern. Additionally, simulations of cities with no urban water bodies have demonstrated increased wind speeds, which could allow particulate matter to remain suspended in the air column [69], while urban areas with natural or artificial water bodies may experience decreased wind speeds [69], facilitating particle deposition [51,70,71]. ...
Globally, rapid urbanisation is one of the major drivers for land-use changes, many of which have a marked impact on urban air quality. Urban forestry has been increasingly proposed as a means of reducing airborne pollutants; however, limited studies have comparatively assessed land-use types, including urban forestry, for their relationship with air pollution on a city scale. We, thus, investigated the spatial relationships between three air pollutant concentrations, NO2, SO2, and PM10, and different land uses and land covers across a major city, by constructing a yearly average model combining these variables. Additionally, relationships between different vegetation types and air pollutant concentrations were investigated to determine whether different types of vegetation are associated with different air pollutants. Parklands, water bodies, and more specifically, broadleaf evergreen forest and mangrove vegetation were associated with lower pollutant concentrations. These findings support urban forestry’s capabilities to mitigate air pollution across a city-wide scale.
... The presence of water bodies may reduce daytime temperature but raise nighttime temperature, which is called the thermostatic effect (Oke, 1987;Theeuwes et al., 2013). Although previous mesoscale studies highlighted the importance of water bodies in modifying urban climate, these studies were either focused on urban expansion near or around a lake (e.g., Sharma et al., 2016;Su et al., 2021;Xing et al., 2019), or focused merely on lake changes within an indicated urban area (e.g., Theeuwes et al., 2013;Zhou et al., 2016). That is, the coupling relationship between urban expansion and lake changes in a complex physiographic background (i.e., land-water mosaics), and the combined impacts of urban expansion and lake changes on regional climate remained understudied. ...
Wuhan has witnessed unprecedented urban expansion that encroached upon sizable inland lakes. However, the impacts of urban expansion on climate and heat stress for such a city with complex physiographic background (land‐water mosaics) remain understudied. Using a coupled urban‐lake‐atmospheric model, we first examined summer climate responses to urban expansion and lake shrinkage in Wuhan during 2000–2020. Second, multiple heat stress indicators were used to evaluate human thermal comfort in different contexts of interest. Results showed that the presence of water bodies reduced daytime maximum temperature, raised nighttime minimum temperature, and increased moisture content in urban and built‐up areas. Urban expansion alone led to summer warming of 0.9°C and drying of 0.9 g/kg, with local peak warming and drying up to 2°C and 1.4 g/kg. In comparison, urban expansion with lake shrinkage showed a reduced magnitude of warming of 0.8°C and increased magnitude of drying of 1.6 g/kg, with the maximum changes up to 1.4°C and 2.0 g/kg. The presence of water bodies reduced while urban expansion increased the frequency of occurrence of yellow and orange heat alert days; however, both increased the number of days exerting high thermal risks on outdoor workers and those days that were dangerous for outdoor pedestrians. Our study underlined that both urban expansion and water body existence exerted a strong influence on summer climate and heat stress in Wuhan, and highlighted that mitigation measures should be taken to alleviate the deleterious impacts of high temperature and humidity on human health.
... However, though the spatial and temporal distribution in air and surface temperatures may be similar and correlated, there are marked discrepancies between the two, especially during daytime. The land surface temperature rises and falls at a faster rate and is more sensitive to changes in radiation and urban canopy parameters, giving rise to generally higher land surface temperatures, a larger diurnal range, and a greater surface UHI intensity around noon (Miao et al., 2009;Cui and de Foy, 2012;Li et al., 2015;Zhou et al., 2016;Nemunaitis-Berry et al., 2017;Li et al., 2018). Different mitigation strategies are also required to target the reduction of urban air and surface temperatures (Rosenzweig et al., 2009, Chen and; more in Section 5.3). ...
Researchers have made immense progress in understanding the urban-induced microclimate by numerical modelling. It has been around two decades since urban canopy models now commonly employed in mesoscale atmospheric models for operational and applied research purposes have emerged. To drive further advancement, it is timely to conduct a review of the state-of-the-art and lessons learnt from the relevant literature. In this paper, 102 urban climate real case modelling studies published in 2000-2019 are reviewed. Patterns and preferences in their study locations, periods, model choices, land cover databases, topics discussed, and scenarios investigated are holistically examined. There is an evident improvement in model complexity and urban surface data precision during the period reviewed. Most studies focus on the urban thermal climate and effects of urbanization. Based on the research gaps identified, more work is needed on the currently underrepresented but vulnerable cities in developing countries with tropical, arid, and cold climates. Collaborative field campaigns, initiatives to characterize cities in a consistent manner, and multi-scale modelling approaches have proven to benefit the progress in urban climate studies and should therefore be encouraged. More importantly, efforts should be invested in translating the science into information relevant to human well-being, urban planning, and policymaking.
... Despite this, IMV has yet to be fully investigated by the RCM community (Giorgi, 2019;Laprise et al., 2012). Moreover, RCM studies often draw conclusions without exploring model uncertainty (e.g., El Afandi et al., 2013;Sertel et al., 2011;Tse et al., 2018;Zhang et al., 2011;Zhou et al., 2016). Considering that IMV is reflected in RCM output (Giorgi & Bi, 2000), results from such single-run studies should at best be seen as contingent. ...
The Weather Research and Forecasting (WRF) community model is widely used to explore cross‐scale atmospheric features. Although WRF uncertainty studies exist, these usually involve ensembles where different physics options are selected (e.g., the boundary layer scheme) or adjusting individual parameters. Uncertainty from perturbing initial conditions, which generates internal model variability (IMV), has rarely been considered. Moreover, many off‐line WRF research studies generate conclusions based on a single model run without addressing any form of uncertainty. To demonstrate the importance of IMV, or noise, we present a 4‐month case study of summer 2018 over London, UK, using a 244‐member initial condition ensemble. Simply by changing the model start time, a median 2‐m temperature range or IMV of 1.2 °C was found (occasionally exceeding 8 °C). During our analysis, episodes of high and low IMV were found for all variables explored, explained by a relationship with the boundary condition data. Periods of slower wind speed input contained increased IMV, and vice versa, which we hypothesis is related to how strongly the boundary conditions influence the nested region. We also show the importance of IMV effects for the uncertainty of derived variables like the urban heat island, whose median variation in magnitude is 1 °C. Finally, a realistic ensemble size to capture the majority of WRF IMV is also estimated, essential considering the high computational overheads (244 members equaled 140,000 CPU hours). We envisage that highlighting considerable IMV in this repeatable manner will help advance best practices for the WRF and wider regional climate modeling community.
... In the late 1970s, Rao (1972) for the first time used thermal infrared remote sensing to study urban heat island. Halstead (1979) simulated the urban microclimate by computer; in 2000, Massachusetts Institute of Technology adopted CFD technology to simulate indoor and outdoor wind environment (Chen and Srebric 2000); Dr. Chen et al. (2009) from University of Tokyo employed the computer simulation method to study the thermal environment of two regions with different densities; Dr. Zhou et al. (2014) from Huazhong University of Science and Technology utilized WRF simulation technology to explore the impact of inland lake area change on urban climate; Pan and Li (2012) carried out a research about the impacts of underlying surface changes on climate precision by WRF in Heihe River basin region; Li et al. 2014 carried out WRF simulation to study the impact of increased urban plot ratio on urban thermal environment. This paper will discuss impacts of urban land sprawl extension on urban climate by the couple technology of UCM (urban canopy model) and WRF (weather research and forecasting). ...
... In 2001, Kusaka et al. (2001) compared the results measured in Vancouver, British Columbia and the results measured in Nagahama of Japan and found that the two results agreed well with each other. Dr. Zhou Xuefan from Huazhong University of Science and Technology compared the air temperature value measured at a certain point in Wuhan city from August 13 to August 16, 2011, with the simulated air temperature at a 2-m height, and the two results were consistent with each other (Zhou et al. 2014). The reliability of method was verified in this study. ...
In the twenty-first century, Wuhan has become one of the most rapidly developing cities in the world, accompanied by the changes of urban climate and environment. In order to explore the relationship between land extension and urban thermal environment in a quantitative way, the expansion of construction land in the southeast of Wuhan city was simulated using mesoscale weather forecasting model (WRF) of urban canopy model (UCM), based on Wuhan’s geographical information, climate characteristics, urban function layout, regional development planning goals, and the equivalent of artificial energy consumption indicators. By summarizing and processing the calculated data, a series of meteorological values at key time points and during time periods were derived. Through quantitative analysis and comparison, conclusions about the effect of land spread in southeast of the city on urban microclimate in summer were obtained, which provides the theoretical basis for making the expansion strategy of construction land in Wuhan.
... Proximity to open water could affect wind patterns and air temperatures, hence altering the UHII (Zhou et al. 2016). The small river Cerezuelo proved to be of great influence in Mediterranean Cazorla, reaching > 4°C cooling in summer TN compared to the centre, but this phenomenon is substantially less important in temperate Geisenheim and boreal Haparanda. ...
Although urban heat islands (UHIs) have been found in many cities throughout the world, work on smaller settlements is still limited, especially concerning variations connected to climate zones. Meteorological stations are often regarded as rural when located in a village or small town, and any temperature bias is assumed negligible. In this paper, we therefore present air temperature variations and their connection to land cover in 3 European villages, boreal Haparanda, temperate Geisenheim, and Mediterranean Cazorla, all of them hosting long temperature records that might be biased. The villages were equipped with temperature sensors, and the surrounding areas were digitized to compare UHI effects and to evaluate the contribution of land cover on local cooling and warming. This sensor network reveals significant village UHIs in all 3 climate zones, with seasonal maximum intensities decreasing from north (1.4°C) to south (0.9°C). During summer, urban warming is most emphasized in minimum temperatures in boreal Haparanda and temperate Geisenheim but weakest in Mediterranean Cazorla, presumably because of limited plant transpiration due to high insolation and drought stress. Urban warming is correlated with building density in all 3 settlements and shows little seasonal variation. Even though the mountain river passing Cazorla substantially cools ambient temperatures at distances <100 m, mitigation of warming through water bodies is limited in the Central and Northern European sites. Our results suggest to treat rural instrumental station data with care and to avoid using data recorded in villages as unbiased reference records to adjust measurements from larger cities.
