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Comparisons of modeled and observed (a) net all-wave radiation, (b) net shortwave radiation, (c) net longwave radiation, (d) sensible heat flux, and (e) storage heat flux. The equation for the linear fit to the points is given in each panel as well as the coefficient of destination R 2 .
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An offline single-layer urban canopy model (SLUCM) was driven by the surface energy balance observations in winter in Nanjing, China, to evaluate the capability of the model to simulate the urban surface energy balance. The results of the evaluation suggest that the simulated daytime net radiation is approximately 20% lower than the observed and di...
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... Fig. 3, the time series and diurnal mean of the ob- served and simulated SEB fluxes are shown. The linear fitting results for the observed and simulated SEB fluxes are presented in Fig. 4. Table 2 lists the definition of the statistical parameters used for the model evaluation (Willmott 1982), and Table 3 lists the respective values. According to the features of the observed SEB (Fig. 3), the canopy heat storage term is much larger than the turbulent sensible heat flux. This is possibly caused by the deep and narrow ...
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... further analyzing the longwave net radiation (LNET) and the shortwave net radiation (SNET) (Figs. 4b,c; Table 3), we found that both the simulated LNET and SNET are lower than the observed values and dis- play greater systematic error. However, the error in Q* comes mainly from the LNET, whereas the model per- forms well in simulating the SNET [ Fig. 4b; index of agreement (IOA) and coefficient of determination (R 2 ) in Table 3]. For the sensible heat flux (Q H ), the simu- lated values during the daytime and the transition period are slightly higher (approximately 7%) than the ob- served values. The discrete degree of the simulated and observed values is large. The model error is ...
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... (IOA) and coefficient of determination (R 2 ) in Table 3]. For the sensible heat flux (Q H ), the simu- lated values during the daytime and the transition period are slightly higher (approximately 7%) than the ob- served values. The discrete degree of the simulated and observed values is large. The model error is mainly un- systematic (Table 3; Fig. 4d). These results indicate that the simulation error in the estimation of the sensible heat flux is mainly caused by the incorrect specification of the initial and/or bottom-lateral boundary conditions. Because the simulated storage heat flux (DQ S ) depends on Q* and Q H and its real value is hard to measure in field experiments, it is ...
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... For these reasons, the preparation of TCN CHE by the hydrothermal process was a favorable strategy. In terms of electronic mobility improvement in the covalently bonded structure, mechanisms such as an extended ³-conjugated covalent organic framework 49,50) and orbital reconstruction of metal oxide/sulfide surfaces [51][52][53][54][55] were investigated. For g-C 3 N 4 in the heterojunction sample, the ³-conjugated structure could contribute unpaired electrons in the 2p z orbital from N=C-N 2 and C-N=C bonds. ...
Two types of TiO2/g-C3N4 heterojunctions, physically and chemically contacted samples, were synthesized to investigate the effect of their contact modes on the photocatalytic activity for dye degradation. The physically contacted TiO2/g-C3N4 heterojunction (TCNPHY) was prepared by an electrostatic assembly process. In addition, the chemically connected heterojunction (TCNCHE) was synthesized by a hydrothermal method accompanied by the formation of Ti–O–C covalent bonds. Fourier-transform infrared and X-ray photoelectron spectroscopies confirmed the formation of Ti–O–C covalent bonds in TCNCHE. Subsequently, their photocatalytic activity for dye degradation was evaluated as a model reaction. The results showed that TCNCHE exhibited higher degradation efficiency than TCNPHY because of its higher UV light absorbance and lower recombination rate than those of the physically contacted sample. These results indicate that the hydrothermal method gives unique advantages in chemically contacted heterojunction construction, which can lead to the improvement of photocatalytic activity.
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... Urbanization has been rapid in China over the past 30 years, bringing about environmental problems such as the urban heat island (UHI) and urban air pollution (Oke 1982, Ryu et al 2013. Many researchers have looked into the influence of urbanization on meteorology, air quality, human thermal comfort, and so forth (e.g., Zhao et al 2014, Georgescu et al 2014, Huszar et al 2018, Li et al 2019, Wang et al 2020. However, there have been few researches investigating the impact of urbanization on wind gust. ...
Urbanization has promoted economic growth but it can increase gust wind speed, which may lead to serious damage to infrastructures. This study uses the Weather Research and Forecasting model and a gust parametrization scheme to evaluate the mitigation impact of white roofs and green roofs on wind gust over the Pearl River Delta, an urban agglomeration in Southern China in June, July, and August of 2014. The results show that both white and green roofs decrease the gust wind speed by decreasing the mean wind speed, suppressing the turbulent motion and weakening the convection. The impacts of white roofs are stronger than those of green roofs. The daily mean reductions of gust wind speed are approximately 1.2-1.3 m s-1 (12-16%) and 0.4-0.6 m s-1 (6-10%) by white and green roofs, respectively. In general, the contribution of turbulence (60-85%) to the gust wind speed is the largest, and the contribution of mean wind speed is approximately 10-30%, however, the effect of deep convection is not obvious (0-15%) on the decrease of gust wind speed. The effect of cooling roofs on reducing the gust wind speed is stronger during daytime than during nighttime, and the effect is more significant in city areas that have higher building densities. Based on the findings, this study is potentially beneficial for policy-makings in developing urban disaster mitigation methods.
... Previous studies have analyzed the controlling factors of spatial variations of SUHII Zhao, Zhang, et al., 2014) across different cities or local climates. Nevertheless, the impact of intra-urban heterogeneity (i.e., various urban features, including morphology, fabric, etc.) on SUHII remains largely unclear, and the role of HW intensity in regulating the quantitative contributions from intra-urban inhomogeneity needs to be further investigated. ...
... The materials of most of the buildings are reinforced concrete, and 6 of 24 the street canyon constructed with asphalt concrete road is deep and narrow. The location of the source area, with a contribution rate of 90% to the flux signal, has an artificial underlying surface coverage of over 90% ( Figure 1a) (Zhao, Zhang, et al., 2014), which is larger than the percentage of artificial surface used in our experiments. ...
... Recent works devoted to identifying the causes of surface UHIs were conducted by the attribution method including the IBM method (Zhao, Zhang, et al., 2014) and the two-resistance mechanism (TRM) method . These two methods were based on the first-order Taylor series expansion of a linearized surface energy balance equation. ...
The urban expansion‐induced heat can exacerbate heat stress for urban dwellers, especially during heat waves. With a focus on the intra‐urban variability of urban heat islands (UHIs) and thermal comfort, the urban parameterization within the Community Land Model version 5 (CLM5) was modified incorporating the local climate zones (LCZs) framework, named CLM5‐LCZs, to simulate the urban climate during a heat wave (HW) event in the summer of 2013. The evaluation of model performance demonstrated that it did a reasonable job of simulating surface energy balance and thermal regimes in cities against observational fluxes from a flux tower measurement site and temperatures from automatic meteorological stations in Nanjing, China. Then we investigated the characteristics and causes of UHIs associated with local background climate, intra‐urban inhomogeneity and HW intensity in East China. The results exhibited that daytime and nighttime canopy urban heat island intensity (CUHII) were highest in the Compact Low Rise (LCZ3) and the Compact High Rise (LCZ1) areas, respectively, while surface urban heat island intensity (SUHII) peaked in the Large Low Rise (LCZ8) and the Compact High Rise (LCZ1) areas during daytime and nighttime, respectively. Urban dwellers were easier exposed to serious heat environment in LCZ3 and LCZ1 areas over the north subtropical climate zone. Contrasts of CUHII and SUHII among different urban classes could exceed 1.7°C and 5.4°C. The intra‐urban heterogeneity may alter the dominant factors controlling SUHII, which were also modulated by local climate and HW intensity. Unlike other controlling factors, the impact of local climate on the contribution from the urban‐rural contrast of convection efficiency was larger than urban features. Overall, CLM5‐LCZs displayed potential of implementing detailed simulations for inter‐ and intra‐city UHIs at a larger scale, and enhancing the capabilities in modeling urban climate and exploring the causes and controls of UHIs.
... Ryu et al 2013, Wang et al 2014, Tao et al 2017, Huszar et al 2018, Li et al 2019. Some key climatic effects of urbanization have been widely investigated, such as the urban heat islands (UHI) effect (Oke 1982, Zhao et al 2013, the slow-down of near-surface wind by enhanced drag force and greater roughness length (Liao et al 2015, Wang et al 2019, the thermally-driven local atmospheric circulation (Lin et al 2008, Chen et al 2009, and the possible precipitation changes (Miao et al 2011, Georgescu et al 2014, Holst et al 2016. Urbanization can also modify the characteristics/ structures of the planetary boundary layer (PBL) including the boundary layer height in urban areas (Ryu et al 2013), decrease the surface evaporation (Wienert and Kuttler 2005) and relative humidity (Zhao et al 2013), and increase the friction velocity because of the enhanced surface frictional dynamic effect , Ao et al 2022. ...
... Some key climatic effects of urbanization have been widely investigated, such as the urban heat islands (UHI) effect (Oke 1982, Zhao et al 2013, the slow-down of near-surface wind by enhanced drag force and greater roughness length (Liao et al 2015, Wang et al 2019, the thermally-driven local atmospheric circulation (Lin et al 2008, Chen et al 2009, and the possible precipitation changes (Miao et al 2011, Georgescu et al 2014, Holst et al 2016. Urbanization can also modify the characteristics/ structures of the planetary boundary layer (PBL) including the boundary layer height in urban areas (Ryu et al 2013), decrease the surface evaporation (Wienert and Kuttler 2005) and relative humidity (Zhao et al 2013), and increase the friction velocity because of the enhanced surface frictional dynamic effect , Ao et al 2022. ...
... In this study, the effect of urbanization on the wind gust in the Nanjing megacity is analyzed. As an important central city in eastern China, Nanjing has experienced significant urbanization (Zhao et al 2013), which has led to obvious expansion of the urban areas and changed the urban climate. In this study, we use the simulation results from the Weather Research and Forecasting (WRF) model as the input for a parameterization scheme of the wind gust to estimate the gust wind speed. ...
Previous studies have extensively examined effects of urbanization on mean wind speed, but few studies were aimed at gust wind speed, while large wind gust could cause safety and economic hazard to a variety of activities. In this study, the effect of urbanization on the gust wind speed in Nanjing, China is assessed using the Weather Research and Forecasting model (WRF) with a parameterization of the gust wind speed. The WRF simulations are run for the summer period of 2013 with the underlying surface before and after the urbanization. The results indicate that although the mean wind speed is reduced, the gust wind speed in the urban areas is increased significantly due to the enhanced friction velocity and less atmospheric stability induced by the urbanization, while the contribution of deep convection is relatively small. The gust wind speed increases more in the nighttime (0.6-0.9m s-1) than in the daytime (less than 0.3m s-1), since the turbulence is enhanced more in the nighttime than in the daytime after the urbanization. The probability distribution shows that the increase of gust wind speed is mainly between 0.0-0.5m s-1 in the urban areas. In different urban land categories, the increase of the gust wind speed is larger in the commercial or industrial areas than in high-intensity and low-intensity residential urban areas. Averagely, the gust wind speed in the entire city after the urbanization increases by 0.02, 0.36 and 0.19m s-1 for the daytime, nighttime and daily mean, respectively.
... The building height for high-intensity residential is half of the commercial/industrial category as a simple approximation. All the other urban canopy parameters such as the heat capacity, thermal conductivity, anthropogenic heat, roof, and road width are using default values except that the surface albedo for urban facets has been changed from default 0.2 to 0.13 mainly based on radiation observations (Ao et al. 2016; as it is recognized as a key parameter in SLUCM (Loridan et al. 2010;Wang et al. 2015;Zhao et al. 2014). The third experiment (hereafter NOURB-hi) is the same as the URB-hi simulation, but replaces all urban land cover within Shanghai with cropland ( Fig. 2c), which is the dominant surface cover type in rural Shanghai. ...
Urbanization effects on rainfall induced by landfalling tropical cyclones have rarely been studied. Here high-resolution numerical simulations with the Weather Research and Forecasting/Noah/single-layer urban canopy model system (WRF/SLUCM) are conducted to investigate impacts of urban land cover and building heights on heavy rainfall induced by landfalling Typhoon Lekima (2019) over the megacity Shanghai. The default single urban category in WRF was updated to a new land cover data with three urban categories. Results indicate that WRF/SLUCM captures the typhoon intensity , track, and total rainfall amount quite well. Urbanization has a small positive effect on rainfall amount for this event. However, urbanization has a significant impact on the spatial distribution of the accumulated rainfall with enhancement not confined over the urban area but mainly to the southwest of Shanghai possibly due to the changes of the typhoon tracks. With the impact of Typhoon Lekima, the urban heat island disappears, indicating that the thermal effect of urbanization has limited influence on the rainfall processes. The model performance is very sensitive to the building height. More realistic building height values can noticeably improve simulations of the diurnal patterns of rainfall, urban heat island, and the urban wind speed stilling effect. With the rising of building heights, the surface frictional dynamic effect and vertical uplift is enhanced, but seems not enough to evidently intensify the rainfall. The simulated lower-level large moisture flux convergence corresponds well to rainfall peaks. This study has important scientific significance for the accuracy of rainfall forecasts of landfalling typhoons and disaster mitigation in cities.
... erefore, the parameter sensitivity analysis of urban land surface models to determine the reasonable range of parameter values and the relative importance of each parameter is very important before coupling into mesoscale and even global numerical models. Previous scholars have carried out simulation and parameter sensitivity tests for the SLUCM using observational data of Vancouver, Princeton, Marseille, and Nanjing [11,[28][29][30]. Due to the heterogeneity and complexity of urban surfaces, the interaction between urban underlying surface and atmosphere is unique in each city. ...
... T s and q s are the surface temperature and specific humidity, respectively. e calculation of surface dynamic roughness and zero plane displacement height of the urban canyon and roof has been changed from the earliest version as input parameters to the later geometric morphology method [30], which reduces the number of input parameters required by the model and is more scientific. ...
... e SLUCM underestimates the average daily variation of Q H for each season, especially in summer. e magnitudes of RMSE for Q H in winter, spring, and autumn are similar to previous studies [28][29][30], which may indicate systematic errors of SLUCM. However, the magnitude of RMSE for Q H in summer in this study is larger than that for previous studies. ...
In order to meet the demand of more refined urban weather forecast, it is of great practical significance to improve and optimize the single-layer urban canopy model (SLUCM) suitable for the megacity of Shanghai. In this paper, based on the offline SLUCM model driven by a whole-year surface flux observation data in the Shanghai central business district, a series of parameter sensitivity tests are carried out by using the one at a time (OAT) method, the relative importance and a set of optimized parameters of the SLUCM suitable for high-density urban area are established, and the improvement of simulation is evaluated. The results show that SLUCM well reproduces the seasonal mean diurnal patterns of the net all-wave radiation flux ( Q ∗ ) and sensible heat flux (QH) but underestimates their magnitudes. Both Q ∗ and QH are linearly sensitive to the albedo, and most sensitive to the roof albedo, the second to the wall albedo, but relatively insensitive to the road albedo. The sensitivity of Q ∗ and QH to emissivity is not as strong as that of albedo, and the variation trend is also linear. Similar to albedo, Q ∗ and QH are most sensitive to roof emissivity. The effect of thermal parameters (heat capacity and conductivity) on fluxes is logarithmic. The sensitivity of surface fluxes to geometric parameters has no specific variation pattern. After parameter optimization, RMSE of Q ∗ decreases by about 3.4–18.7 Wm−2 in four seasons. RMSE of the longwave radiation (L↑) decreases by about 1.2–7.87 Wm−2. RMSE of QH decreases by about 2–5 Wm−2. This study provides guidance for future development of the urban canopy model parameterizations and urban climate risk response.
... The UCMs vary in complexity, assumptions, computing time, and model parameters from the relatively simple with minimal data requirements or computer needs (e.g., slab) to more complex assumptions about the processes but with greater demands on surface parameters and computer resources (e.g., multilayer; Chen et al. 2011a). The accuracy of modeled SEB fluxes requires the urban surface parameters to be correct (Loridan et al. 2010;Wang et al. 2011;Grimmond et al. 2010Grimmond et al. , 2011Zhao et al. 2014b) but assigning these required parameters remains challenging (Tsiringakis et al. 2019). Additionally, the correct prescription of these properties may be as important as the complexity of the UCMs used to parameterize the physical processes (Grimmond et al. 2011;Best and Grimmond 2015). ...
... Each parameter (Table 3) is varied between literature-based minima and maxima (Chen and Dudhia 2001;Loridan et al. 2010) using 100 equal classes. With permutation and combination methods (Zhao et al. 2014b), optimized albedo, thermal conductivity, emissivity, and heat capacity values (Table 3) for three facets (roof, road, and wall) are determined to minimize the root-mean-square error (RMSE) of modeled outgoing shortwave radiation flux. ...
... W m 22 for different seasons, net all wave radiation (7-14 W m 22 ), and the sensible heat flux (2-7 W m 22 ). The optimized albedo, 10 m AGL wind speed WD 10 10 m AGL wind direction emissivity, and heat capacity for roof, wall, and road in Shanghai (Table 3) are similar, or a bit larger, than those derived using the same optimized method for Nanjing (32.038N, 118.798E; Zhao et al. 2014b). The fraction of impervious area (buildings 1 road, Table 3) or urban built, mean building height and roof width are calculated based on the geographic information system (GIS) information for XJH site (Ao et al. 2016a(Ao et al. , 2018. ...
Urban heat island (UHI) and sea–land-breeze systems are well-known and important characteristics of the climate of coastal cities. To model these, the accurate estimation of the surface energy balance (SEB) is a key factor needed to improve local-scale simulations of thermodynamic and dynamic boundary circulations. The Weather Research and Forecasting Model with a single-layer urban canopy model (WRF/SLUCM), with parameters derived from MODIS and local GIS information, is used to investigate the UHI and sea-breeze circulations (SBC) in the megacity of Shanghai. The WRF/SLUCM can reproduce observed urban radiation and SEB fluxes, near-surface meteorological variables, and the evolution of the UHI and SBC. Simulations for an August period show the maximum UHI tends to drift northwest in the afternoon, driven by the prevailing southeast wind. The sea breeze lasts for about 4 h and is strongest between 1200 and 1400 local time (UTC + 8 h). The interaction between UHI and SBC is evident with low-level convergence, upward motion, and moisture transport from the sea and urban breezes simulated. An urban circulation (horizontal/vertical/time scales: ∼20 km/∼1.5 km/∼3 h) with thermal vertical motions (∼1.5 m s ⁻¹ ) above the urban area and an SBC (horizontal/vertical/time scales: 6–7 km/∼1 km/2–3-h) above the northern coastal suburb occur. Combined the sea breeze and southerly winds form a low-level wind shear (convergence zone) ∼5 km from the coast that penetrates ∼20 km inland to the urban center. Using the WRF/SLUCM simulations we improve understanding of the complex spatial dynamics of summertime urban heating in coastal megacities, such as Shanghai.
... There are two main approaches to studying UHIs: numerical simulation and observation. Numerical simulation can reduce the need for a large number of observations and reveal mechanistic insights by investigating the impacts of cities on meteorological variables (Chun and Guldmann, 2014;Zou et al., 2014;Zhang et al., 2015;Taleghani et al., 2016;. For instance, Zhang et al. (2015) investigated the influence of land use/land cover (LULC) and anthropogenic heat flux (AHF) on the structure of the urban boundary layer in the Pearl River Delta region, China, through a series of numerical experiments. ...
Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high-spatial-resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. Firstly, the observed environmental parameters, e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF), around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 ∘C. Then, the spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the decreasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high spatial and temporal resolution (30 m and 1 h) CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.
... The key parameters required by UCM and the values used in our model are shown in Table 2. The values for each parameter were identical for the three land uses, as cited by Zhao et al. [26] and Xie et al. [27]. ...
Increasingly, Chinese cities are proposing city-scale ventilation corridors (VCs) to strengthen wind velocities and decrease pollution concentrations, although their influences are ambiguous. To assess VC impacts, an effort has been made to predict the impact of VC solutions in the high density and diverse land use of the coastal city of Shanghai, China, in this paper. One base scenario and three VC scenarios, with various VC widths, locations, and densities, were first created. Then, the combination of the Weather Research and Forecasting/Single-Layer Urban Canopy Model (WRFv.3.4/UCM) and Community Multiscale Air Quality (CMAQv.5.0.1) numerical simulation models were employed to comprehensively evaluate the impacts of urban spatial form and VC plans on PM2.5 concentrations. The modeling results indicated that concentrations increased within the VCs in both summer and winter, and the upwind concentration decreased in winter. These counter-intuitive results could be explained by decreased planetary boundary layer (PBL), roughness height, deposition rate, and wind speeds induced by land use and urban height modifications. PM2.5 deposition flux decreased by 15–20% in the VCs, which was attributed to the roughness height decrease for it weakens aerodynamic resistance (Ra). PBL heights within the VCs decreased 15–100 m, and the entire Shanghai’s PBL heights also decreased in general. The modeling results suggest that VCs may not be as functional as certain urban planners have presumed.
... These fluxes play a key role in regulating the energy balance of the atmosphere, which in turn drives atmospheric circulation (Chehbouni et al. 1999;Lee 2015). The eddy covariance (EC) approach is commonly used in studies to estimate in-situ H, as well as for the numerical modeling of land-atmosphere heat flux exchanges (Ingwersen et al. 2011;Zhao et al. 2014;Imukova et al. 2015;Liu et al. 2017;Sun et al. 2017). The large-aperture scintillometer (LAS) is an alternative for collecting H data that has the advantage of aggregating larger spatial scales than the EC approach, which can then be compared to satellite images and numerical models (Klessl et al. 2009;Al-Gaadi et al. 2016;Valayamkunnath et al. 2018). ...
Obtaining accurate estimates of surface-atmosphere energy exchanges and improved comprehension of the mechanisms generating turbulent fluxes over non-uniform landscapes are both challenging goals and essential for validating numerical weather forecasting modeling. In this work, a large-aperture scintillometer (LAS) was deployed to evaluate the effect of mesoscale sea and valley breezes with respect to diurnal sensible heat flux (H) variability over an urban area close to a coastal bay near the metropolitan area of Rio de Janeiro (MARJ) during the austral summer of 2017–2018 time span. The region is characterized by a densely urbanized environment, surrounded by mountainous relief and bounded by a large ocean bay. The transmitter and the receiver of the LAS system were installed 1955 m apart. Diurnal cycle was divided into four periods according to the local time: dawn (00 a.m. to 6 a.m.), morning (6 a.m. to 12 a.m.), afternoon (12 a.m. to 6 p.m.), and night (6 p.m. to 00 a.m.). The results demonstrated the sensitivity of the LAS to record variations in H over the course of the day, taking into account the corresponding sea and valley breezes and the relative humidity variability. During the morning, when valley breezes are predominant, footprint area shrinks to its smallest size, encompassing an area of approximately 2 km2. On the other side, during afternoon and night time periods, during afternoon and night time periods, the presence of sea breeze jointly with a densely urbanized continental area contribute to promote significant changes in the footprint area ranging from 2.05 to 5.38 km2. The effects of topography are also well captured in the diurnal H cycle once sunset and corresponding shading in the late afternoon abruptly reduces heat-sensible flux. Diurnal variations in footprint shape and area lead to modifications in terms of the mode each type of urban surface will contribute to H, increasing the influence of anthropogenic elements in afternoon and early evening. Complementarily, it is noteworthy to mention that a sensitivity test was performed to assess uncertainties in H estimates for the free convection method, which requires the estimation of an empirical constant b. Variations in this constant introduce larger dispersion in H estimates than potential errors in LAS effective height (Zeff) estimations or temperature measurements. These last results highlight the importance of conducting further evaluations as the one pursued in this study to more rigorously validate the outputs of numerical mesoscale and local hydrometeorological models and remotely sensed products.
