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Modeling domains with elevation, location of Osaka meteorological observatory, and southwest to northeast cross-section line (a) and with dominant land use (b).
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This study utilized the Weather Research and Forecasting (WRF) model version 3.5.1 to evaluate the impact of urbanization on summertime precipitation in Osaka, Japan. The evaluation was conducted by comparing the WRF simulations with the present land use and no-urban land use (replacing “Urban” with “Paddy”) for August from 2006 to 2010. The urbani...
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... Most of them emphasize an obvious influence of the UHI, which can intensify convective activity during the day (Bornstein & Lin, 2000;Shem & Shepherd, 2009). Some others pointed out that the change in boundary-layer height over urban areas due to an increase in sensible heat flux can enhance turbulence and instability over the city (Chen et al., 2011;Guo et al., 2006;Shimadera et al., 2015;Zhong & Yang, 2015). At the same time, the expansion of built-up areas strengthens surface roughness, commonly referred to as the building barrier effect (Bornstein & Lin, 2000), and often leads to a decrease in upwind and an increase in downwind surface winds (Guo et al., 2006;Niyogi et al., 2006). ...
The purpose of this study is to investigate the influence of the urban environment of the Paris region on an isolated convective cell that formed downwind of the city on May 7, 2022, using the Meso‐NH research atmospheric model at a horizontal scale of 300 m. To account for all sources of forecast uncertainty, the initial and lateral boundary conditions of the simulations are provided by an ensemble prediction system. A multi‐layer urban scheme is used to represent the influence of buildings on the airflow accurately. Two sets of ensemble simulations are performed: the first set (URB) uses a fine‐scale surface description of the city, while the second set (NOURB) replaces urban surfaces with vegetation. This sensitivity test shows that, despite the high variability of simulated precipitation within the ensemble, the city of Paris plays a statistically significant role in the initiation of convection in this case. Convective cells are initiated over the city for several members of the URB ensemble, while almost no precipitation is simulated for the same members of the NOURB ensemble. The mean 6‐h rainfall accumulation of the URB ensemble is increased by 70% over Paris (compared with the NOURB ensemble) and no statistically significant trend is found around the city. The analysis reveals that the capital experiences a higher sensible heat flux due to drier and warmer air, resulting in enhanced vertical velocities and an increase in boundary‐layer height in the URB ensemble. Additionally, the total water content and cloud fraction over Paris are intensified, leading to more precipitation. These findings suggest that urbanisation has a notable impact on convection and precipitation processes in this case.
... A summary of results on urban influence on rainfall was given by Liu and Niyogi (2019), noting that urban-induced precipitation increases range from 11% (14%) to 21% (22%) over the urban (downstream) area. Numerical modeling also shows that AH released over mega-cities can strongly enhance the extreme rainfall over coastal urban areas such as Tokyo and South China (SC), by intensifying the local convection, land-sea circulation, and strengthening the local moisture flux convergence Holst et al., 2016;Hu et al., 2021;Kusaka et al., 2014;Shimadera et al., 2015;Z. Xiao et al., 2020), whereas this impact is relatively weaker for inland cities (Benson-Lira et al., 2016). ...
How urbanization affects tropical cyclone (TC) rainfall is inferred from station observations over the Great Bay Area (GBA, located on the South China coast) and numerical model experiments. Observations from 41 TCs indicate that surface wind is noticeably weaker in urban compared to rural stations during TC passages, while the urban heat island effect is considerably suppressed. Extreme (99th percentile of) hourly rainfall for these TC events during 2008–2017 is more intense over urban compared to rural stations. For eight selected TC cases, dynamical downscaling was carried out using the convection‐resolving Weather Research and Forecasting model, each with three parallel experiments: “Nourban” in which the urban area was replaced by cropland; “AH0” (“AH300”) in which the diurnal maximum anthropogenic heat (AH) was set to 0 (300 W/m²) in city locations. Both AH0 and AH300 show a significant increase in urban hourly rainfall intensity and probability in all ranges (most obvious for heavy rainfall >40 mm/hr), over the GBA mega‐city. Further diagnosis indicates increased moisture flux convergence in urban areas over a 2‐day period during the landfall, contributes to increased rainfall, likely induced by the surface roughness. The influence of AH, however, is found to be insignificant. The increase in accumulated rainfall due to urbanization is proportional to the storm residence time over the city, implying greater rainfall exacerbation for slower or larger TCs. Overall, urbanization intensifies extreme TC rainfall over the coastal GBA mega‐city mainly due to surface frictional convergence, with stronger intensification for storms residing longer over the city.
... For the differences in maxima, the similar shift in timing is also evident in the ERA5 ensemble as the maximum rainfall initiates later and lasts longer over the provincial borders in NOURBAN ERA5 (also visually seen in Fig. 3). Additionally, when the rainfall amounts across the urban grids are aggregated throughout the six consecutive hours that our analysis focuses on, we note that the URBAN ERA5 simulation increases the rainfall totals by more than 6%, in parallel with the literature (Shimadera et al., 2015). ...
... Cities can influence wind speed and the direction of the atmospheric circulation, and sometimes modulate local atmospheric circulations (Childs and Raman, 2005;Lemonsu et al., 2009;Bauer, 2020). They may increase the persistence of cloud cover by advecting moisture (Theeuwes et al., 2019), and enhance the development of convective clouds (Shimadera et al., 2015). Studies have also shown a change in the frequency and intensity of thunderstorms (Kingfield et al., 2018;Ashley et al., 2011), and an increase of precipitation over urban areas during summer (Liu and Niyogi, 2019;Le Roy et al., 2020). ...
... A similar result has also been reported in other megacity regions in East Asia. By conducting numerical model experiments with and without urban surfaces in Osaka, Japan, Shimadera et al. (2015) showed that a strengthened sensible heat flux from the urban surface results in an enhanced local convection that increases afternoon rainfall in urban areas. Zhang et al. (2017) obtained a similar result in Beijing from the model experiments under the weak and strong UHI conditions. ...
This study evaluates the impact of the urban heat island (UHI) on the daily and sub-daily monsoon rainfall variabilities in East Asian megacities using the high-resolution ground- and satellite-based observations for the period of 1998–2015. The three representative megacity regions, i.e., Guangdong in China, Seoul/Gyeonggi in Korea, and Tokyo in Japan, are particularly considered. A strong UHI day, defined as a summer day with UHI index greater than one standard deviation, is typically drier than normal especially in the urban area. However, when rainy, a distinct rainfall peak appears in the early afternoon, contrasting to the climatological rainfall distribution with a maximum rainfall in the early morning and a secondary maximum in the late afternoon. A stronger early-afternoon rainfall in the urban area than in the rural area becomes more pronounced as UHI intensity increases beyond a certain threshold value. The UHI-induced extreme rainfall in the afternoon, which is larger than climatology, is also robustly found in all three megacity regions. The impact of the UHI on extreme rainfall is the largest in Tokyo (55–75%), followed by Seoul/Gyeonggi (35–65%) and Guangdong (25–50%). Such regional difference can be partly explained by the difference in the geographical location and urbanization progress. This result suggests that East Asian megacities are likely prone to more extreme UHI-induced rainfall with accelerated urbanization.
... Apart from thermodynamic effects, the increase in urbanization can also dynamically change the microclimate around the urban area (Li et al., 2020;Niyogi et al., 2020). Wind directed towards urban areas can change direction, promote upward movement of the air, or even affect the characteristics of precipitation systems, relocating the precipitation center to the downwind or upwind of the urbanized area depending on the city geometry, topography, and characteristics of weather systems (Shimadera et al., 2015). Also, the thermodynamic and dynamic impacts of urbanization may act in harmony. ...
This study examines the temperature variability over urban and rural sites of Istanbul and Ankara, two strategic metropoles in Turkiye, using multiple data sources, including satellite, ground observations, and a reanalysis product for the period of 2011-2018. The practice of this study is twi-formed. Firstly, we introduce a location-based analysis, in which we identify the differences in annual, seasonal, and monthly temperature characteristics of urban and rural stations using hourly 2-meter mean temperature provided from station observation data. Secondly, in the grid-based analysis, we utilize the GHS Settlement Model grid classification dataset with a resolution of 1 km to determine urban-rural grids and employ the MODIS-Terra daily land surface temperature data to reveal the long-term dissimilarity of the urban and rural grids. Also included in the grid-based analysis is the CHIRTS-daily temperature product at high resolution, which we use to compare the number of days where the daily maximum temperature exceeds a specified threshold at urban and rural grids in each city. Results reveal the variability of the temperature difference between the corresponding urban and rural grids, which we refer to as the urban heat island (UHI) effect. However, this variability is higher for Istanbul, where urban land use constitutes approximately 20% of the grids, compared to Ankara, where the percentage of the grids represented by urbanization is less than 4%. When we consider the urban land use in Istanbul, there is a clear signal of a shift in the location parameter of observed temperature values to the warmer side of the probability distribution function (PDF), as revealed by the kernel density estimation analysis. Yet, for Ankara, we do not see a notable change in the corresponding PDF. Long-term UHI analyses also support these, as the difference in annual, seasonal, and monthly temperature between urban and rural locations of Istanbul is more pronounced than in Ankara. This study communicates the importance of avoiding a broad generalization of the urban impact in different cities.
... Several studies quantitatively addressed the impact of this urban expansion in modifying the amount, intensity, location, and timing of rainfall in different cities across the world either by conceptualizing simulations with different land cover configurations or utilizing observational approaches (Li et al., 2020;Niyogi et al., 2020;Su et al., 2021). Further, a bulk of them focused on the precipitation changes over the sub-regions of upwind and downwind of the city center, taking into account the potential for urbanization-induced local circulation over and around the urban center (Shimadera et al., 2015). Not surprisingly, the simulated or observed changes over these sub-regions were shown to alternate when rainfall characteristics, urban extension, and UHI strength were factored in (Yang et al., 2014;Chang et al., 2021). ...
... Recent studies demonstrate that the simulation strategy, where the urban land use is included in one simulation and discarded in the other, can provide a descriptive measure of urban impact on atmospheric and hydrological variables (Shimadera et al., 2015;Su et al., 2021). In other words, designing simulations that only include modifying a land-cover class over a city of interest will likely expose changes induced exclusively by the land-cover change. ...
Urbanization has been demonstrated to alter precipitation characteristics. However, there is a lack of modeling-based examination of the interaction between urbanization and precipitation in Turkey. Here, we analyze the urban impacts on two precipitation events with different synoptic backgrounds in Ankara using the Weather Research and Forecasting model. The rainfall occurrences were selected considering the urban heat island (UHI) intensity over the urbanized area. We conceptualize urban and nourban configurations using the CORINE land cover data and create ensemble simulations. Our findings underline the dissimilarity in the urban impacts on the precipitation pattern of the selected events. The urban scenario suppressed the rainfall over the downwind and upwind of the urban center by more than 10 mm for the summertime event, reshaping the rainfall pattern to be more spatially distributed and protracting the rainfall duration. By contrast, the urban impact on the springtime event is less discernible, with less than 1% change in the rainfall amounts over the urban center. Strong synoptic forcing and significantly less UHI magnitude for the springtime event are responsible for the masked urban impacts on precipitation. Regardless, the urban land use changed the surface energy balance, reducing the moisture content over the highly urbanized area.
... Focus on the urban area, global warming and urbanization are the two major drivers of the warming environment in the city (Yang et al. 2011;Sun et al. 2014Sun et al. , 2021Bassett et al. 2020;Kong et al. 2020;Wang et al. 2020Wang et al. , 2021. Urbanization, one form of human-induced LULC change, plays an important role in human-induced weather and climate change (temperature and precipitation) on the regional/local and global scales through altering land-atmosphere interactions because of its impacts on atmospheric dynamics, thermodynamics, energy exchanges, cloud microphysics, and atmospheric composition (Oke 1982;Shepherd 2005;Miao et al. 2009;Zhang et al. 2010;Chen et al. 2011;Gao et al. 2011Gao et al. , 2012Gao et al. , 2021Feng et al. 2012Feng et al. , 2013Feng et al. , 2014Wang et al. 2012Wang et al. , 2013Wang et al. , 2015Yang et al. 2012Yang et al. , 2021Mahmood et al. 2014;Shimadera et al. 2015;Chen and Frauenfeld 2016;Perugini et al. 2017;Kong et al. 2020;Han et al. 2020;Liu et al. 2021;Sun et al. 2021). Climate change and LULC change also could alter the groundwater recharge areas and the surface and subsurface flows in the river basin Shakya 2019a, 2019b). ...
... Although many previous studies have indicated that urbanization has significant impacts on weather, climate and environment in the different spatial-temporal scales (Shepherd 2005;Zhang et al. 2010;Chen et al. 2011;Gao et al. 2011Gao et al. , 2012Gao et al. . 2021Yang et al. 2011Yang et al. , 2012Feng et al. 2012Feng et al. , 2013Feng et al. , 2014Wang et al. 2012Wang et al. , 2016Wang et al. , 2021Argüeso et al. 2014;Sun et al. 2014;Shimadera et al. 2015;Liao et al. 2018;Ye et al. 2018;Lamichhane and Shakya 2019a, 2019bBassett et al. 2020;Shi et al. 2021;Yang et al. 2021), projections of future weather, climate and environment have rarely been investigated in the Greater Bay Area under the increasing urban land areas and different GHGs concentration scenarios, especially the extreme high and low temperature. Although the LULC change forcing has been included in many climate models, as shown in Coupled Model Intercomparison Project Phase 5 (CMIP5), the urban fraction usually still remains constant over time (Di Vittorio et al. 2014). ...
Relative contributions of greenhouse gases (GHGs) concentration and land use/cover (LULC) change induced by urbanization on future temperature over the Guangdong-Hong Kong-Macao Greater Bay Area in China under different climate scenarios are investigated in this study. The Weather Research and Forecasting model is used to downscale the future mean and extreme temperature using the Representative Concentration Pathways (RCP) 4.5&8.5 simulations from the Community Earth System Model. Results show that GHGs concentration is the key dominate factor for future mean and extreme temperature over the Greater Bay Area in the next 10–30 years, LULC change (urbanization) has relative slight effect on the future regional temperature. On the urban local scale, the LULC change in urban area has an obvious warming effect on urban local temperature under future different GHGs concentration scenarios. The regional-averaged annual mean surface air temperature (SAT) of urban area will increase 0.51 °C (0.73 °C), 0.83 °C (1.17 °C) and 1.26 °C (1.74 °C) resulting from the combined contributions of urbanization and GHGs forcing for the year of 2030, 2040, and 2050 under RCP4.5(RCP8.5) scenario, respectively. The contributions of the GHGs forcing are 0.33 °C (0.53 °C), 0.66 °C (1.00 °C) and 1.12 °C (1.58 °C), the urbanization forcing are 0.18 °C (0.20 °C), 0.17 °C (0.17 °C) and 0.14 °C (0.16 °C). Same as regional-averaged annual mean SAT, for the extreme high- and low-temperature, the contribution of GHGs forcing is more important than that of the urbanization forcing. The extreme temperatures are more sensitively to GHGs concentration under RCP8.5 scenario than that under RCP4.5, especially for the extreme low-temperature. GHGs are the most important factor for dominating the future mean and extreme temperature of the Greater Bay Area.
... In coastal urban areas, extreme rainfall is due to extensive heat flux, atmospheric instability, strong vertical convection and water vapour from the sea [34,35]. Studies focused on the coastal Pearl River Delta (PRD) megacity region in China [36] showed an increase in the total rainfall by 6.3% and 7.4% due to AH and urban land-use change (ULUC). ...
The current study addresses the role of heat and moisture emitted from anthropogenic sources on the local weather with the aid of numerical weather prediction (NWP). The heat and moisture emitted by industries to the atmosphere are considered main sources in this study. In order to understand the effect of heat and moisture on local weather, the study is conducted to capture the impact of heat with no moisture change. The results are compared against a control run case without perturbation and also against the case where both heat and moisture are perturbed with temperature as a single parameter. The Angul district in Odisha that houses over 4000 industries is considered our study region. The numerical simulations are performed using the mesoscale Weather Research and Forecasting (WRF) model for two rain events, namely a light rain case and a heavy rain case, with different physics options available in the WRF model. The WRF simulated maximum rainfall rate using various microphysics schemes are compared with the Tropical rainfall measuring mission (TRMM) observations for validation purposes. Our study shows that the WDM6 double moment microphysics scheme is better in capturing rain events. The TRMM-validated WRF simulation is considered a reference state of the atmosphere against which comparisons for the perturbed case are made. The surface temperature is perturbed by increasing it by 10 K near the industrial site and exponentially decreasing it with height up to the atmospheric boundary layer. A numerical experiment represents heating without addition of moisture by recalculating the relative humidity (RH) corresponding to the perturbed temperature. The perturbed temperature affects sensible heat (SH) and latent heat (LH) parameters in the numerical experiment. From the results of the numerical investigation, it is found that the near-surface rainfall rate increases locally in a reasonable manner with the addition of sensible heat to the atmosphere. A comparison against the case where moisture is added shows that enhanced rainfall is more sensitive to sensible and latent heat than sensible heat alone.
... Over the past few decades, many regions of the world have experienced significant GHGs emission and LULC change since industrialization and urbanization have rapidly increased around the world. Human-induced LULC change exerts a significant impact on weather and climate on regional/local and global scales by modifying the energy, momentum and water exchanges between the land surface and atmosphere (Oke 1982;Shepherd 2005;Miao et al. 2009;Zhang et al., 2010;Chen et al. 2011;Gao et al. 2011Gao et al. , 2012Feng et al. 2012Feng et al. , 2013Feng et al. , 2014Wang et al. 2012Wang et al. , 2013Wang et al. , 2015Yang et al. 2012;Mahmood et al. 2014;Shimadera et al. 2015;Chen and Frauenfeld 2016;Sun et al. 2021). Climate change and LULC change also have great impact on hydrology, which could alter the groundwater recharge areas and the surface and subsurface flows in the river basin (Lamichhane and Shakya 2019a, b). ...
... Many previous studies have indicated that urbanization has significant impacts on weather, climate, environment and human being health on the local and regional scales (Shepherd 2005;Zhang et al. 2010;Chen et al. 2011;Gao et al. 2011Gao et al. , 2012Gong et al. 2012;Yang et al. 2012;Feng et al. 2012Feng et al. , 2013Feng et al. , 2014Wang et al. 2012Wang et al. , 2016Argüeso et al. 2014;Shimadera et al. 2015;Shakya 2019a, b, 2020), but projections of future weather, climate and environment have rarely been investigated under the increasing urban land areas and different GHGs concentration scenarios. As shown in Coupled Model Intercomparison Project Phase 5 (CMIP5), although the LULC change forcing has been included in some climate models, the urban fraction usually still remains constant over time (Di Vittorio et al. 2014). ...
In this study, the effects of land use/cover (LULC) change induced by urbanization and greenhouse gases (GHGs) concentration on future climate over the Beijing–Tianjin–Hebei region in China under Representative Concentration Pathways 4.5 (RCP4.5) scenario are investigated. The Weather Research and Forecasting model is used to downscale and predict the future climate state using the RCP4.5 simulations from the Community Earth System Model. Results show that large-scale general atmospheric circulation and GHGs are the two dominate factors for the future climate over the Beijing–Tianjin–Hebei region in the next 10–20 years under the RCP4.5 scenario. Urbanization over a small-scale region and scattered areas has a slight effect on the regional future climate. On the urban local scale, the LULC change in the urban area has a relatively obvious impact on the local climate of the city through altering the land–atmosphere interaction within the urban region accompanied with seasonal dependence. The annual mean surface air temperature (SAT) of urban area is projected to be 0.44 °C (2020), 0.87 °C (2030), and 1.48 °C (2040) higher than the climatology under different climate scenarios in the future resulting from integrated urbanization and GHGs forcing effects. The annual mean SAT of urban area changed by the GHGs forcing will increase by 0.35 °C (2020), 1.00 °C (2030), and 1.66 °C (2040), and the urbanization forcing will increase the annual mean SAT by 0.09 °C (2020), − 0.13 °C (2030), and − 0.18 °C (2040) in the urban area, respectively. The effects of urban expansion on the seasonal mean SAT are different during different the warm and cold periods of a year. The expanded urban area will increase the SAT during the warm period of a year (from March to September), and will decrease the SAT during the cold period of a year (from October to February of next year). The effects of scattered urbanization process and large-scale urban agglomeration on regional and local climate have strong spatial and temporal scale dependence. GHGs are the most important factor for dominating the future climate of this region. Meanwhile, due to the important impact of urbanization on the urban local scale, we strongly suggest that urbanization process should be considered in climate modeling system since it can provide a more realistic and reliable scenario of the future climate in the urban area.
