Canopy Model Research Articles

Assessing Green Strategies for Urban Cooling in the Development of Nusantara Capital City, Indonesia

The relocation of Indonesia’s capital to Nusantara in East Kalimantan has raised concerns about microclimatic impacts resulting from proposed land use and land cover (LULC) changes. This study explored strategies to mitigate these impacts by using dynamical downscaling with the Weather Research and Forecasting model integrated with the urban canopy model (WRF-UCM). Numerical experiments at a 1 km spatial resolution were used to evaluate the impacts of green and mitigation strategies on the proposed master plan. In this process, five scenarios were analyzed, incorporating varying proportions of blue–green spaces and modifications to building walls and roof albedos. Among them, scenario 5, with 65% blue‒green spaces, exhibited the highest cooling potential, reducing average urban surface temperatures by approximately 2 °C. In contrast, scenario 4, which allocated equal shares of built-up areas and mixed forests (50% each), achieved a more modest reduction of approximately 1 °C. The adoption of nature-based solutions and sustainable urban planning in Nusantara underscores the feasibility of climate-resilient urban development. This framework could inspire other cities worldwide, showcasing how urban growth can align with environmental sustainability.

Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation

Abstract. The urban canopy model Town Energy Balance (TEB) is coupled with the radiation model SPARTACUS-Urban to improve the urban geometry simplification and the radiative transfer calculation. SPARTACUS-Urban assumes that the probability density function of wall-to-wall and ground-to-wall distances follows a decreasing exponential. This better matches the distributions in real cities than in the infinitely long street canyon employed by the classical TEB. SPARTACUS-Urban solves the radiative transfer equation using the discrete ordinate method. This allows us to take into account physical processes such as the interaction of radiation with the air in the urban canopy layer and the spectral dependence of urban material reflectivities or specular reflections. Such processes would be more difficult to account for with the radiosity method used by the classical TEB. With SPARTACUS-Urban, the mean radiant temperature, a crucial parameter for outdoor human thermal comfort, can be calculated from the radiative fluxes in the vertical and horizontal directions incident on the human body in an urban environment. TEB–SPARTACUS is validated by comparing the solar and terrestrial urban radiation budget observables with those simulated by the Monte-Carlo-based HTRDR-Urban reference model for procedurally generated urban districts that mimic the local climate zones. Improvement is found for almost all radiative observables and urban morphologies for direct solar, diffuse solar, and terrestrial infrared radiation. The TEB mean radiant temperature diagnostic for a person in the urban environment is also improved with TEB–SPARTACUS compared with the classical TEB. Based on these results, TEB–SPARTACUS could lead to more realistic results for building energy consumption, outdoor human thermal comfort, or the urban heat island effect.

Impact of high-resolution land use data on numerical simulations of Colombo’s thermal environment during heatwaves

Land Use and Land Cover (LULC) play a crucial role in the regional climate models, as they influence various physical processes interconnected with energy, mass, and atmospheric interactions. This study has examined the impact of high-resolution LULC data on the accuracy of the Weather Research and Forecasting (WRF) model with the Urban Canopy Model in capturing the thermal environment of the Colombo Metropolitan Region (CMR) during heatwaves (HWs). In the performed simulations we used four LULC datasets: USGS, MODIS30, MODIS15, and Esri (Sentinel2). Our investigation is the first application of the WRF model to study the thermal environment in a tropical city such as Colombo. This is also the first research investigation of HWs in the Sri Lanka context from the mesoscale viewpoint. Additionally, this is the first time high-resolution Esri land-use data have been used in a numerical model to examine the thermal environment. By evaluating the three HW cases, we compared the simulation outcomes with observational data from three meteorological stations in CMR. The results from numerical simulations revealed that the LU4 dataset provided the closest agreement with observed Land Surface Temperatures (LST). Daytime LSTs in urban areas peaked above 45 °C, while nighttime temperatures reached 30 °C in commercial zones. Coastal regions consistently exhibited lower temperatures, with daytime LSTs ranging from 40 to 45 °C and nighttime LSTs from 25 to 30 °C, compared to the urban cores. LU4 showed the closest alignment with Himawari satellite data, ensuring superior accuracy. Temperature anomaly analysis indicated that LU4 reduced daytime temperature anomalies by up to 2.5 °C and nighttime anomalies by 1.0 °C compared to other datasets. Statistical evaluations (R = 0.94 in Colombo) further highlight the importance of high-resolution LULC data for enhancing the accuracy of the WRF model in representing urban thermal environments.

Thermal Environmental Impact of Urban Development Scenarios from a Low Carbon Perspective: A Case Study of Wuhan

Amidst the increasingly escalating global concern regarding climate change, adopting a low-carbon approach has become crucial for charting the future developmental trajectory of urban areas. It also offers a novel angle for cities to avoid high-temperature risks. This paper estimates carbon emissions in Wuhan City from both direct and indirect aspects. Then, the ANN (artificial neural network)–CA (Cellular Automata) model is employed to establish three distinct development scenarios (Ecological Priority, Tight Growth, and Natural Growth) to predict future urban expansion. Additionally, the WRF (Weather Research and Forecasting Model)—UCM (Urban Canopy Model) model is used to investigate the thermal environmental impacts of varying urban development scenarios. This study uses a low-carbon perspective to explore how cities can develop scientifically sound urban strategies to meet climate change challenges and achieve sustainable development goals. The conclusions are as follows: (1) The net carbon emission for Wuhan in 2022 is estimated to be approximately 20.8353 million tonnes. Should the city maintain an average annual emission reduction rate of 10%, the carbon sink capacity of Wuhan would need to be enhanced by 382,200 tonnes by 2060. (2) In the absence of anthropogenic influence, there is a propensity for the urban construction zone of Wuhan to expand primarily towards the southeast and western sectors. (3) The Ecological Priority (EP) and Tight Growth (TG) scenarios are effective in alleviating the urban thermal environment, achieving a reduction of 0.88% and 2.48%, respectively, in the urban heat island index during afternoon hours. In contrast, the Natural Growth (NG) scenario results in a degradation of the urban thermal environment, with a significant increase of over 4% in the urban heat island index during the morning and evening periods. (4) An overabundance of urban green spaces and water bodies could exacerbate the urban heat island effect during the early morning and at night. The findings of this study enhance the comprehension of the climatic implications associated with various urban development paradigms and are instrumental in delineating future trajectories for low-carbon sustainable urban development models.

Variation in relaxation of non‐photochemical quenching between the founder genotypes of the soybean (Glycine max) nested association mapping population

SUMMARYImproving the efficiency of crop photosynthesis has the potential to increase yields. Genetic manipulation showed photosynthesis can be improved by speeding up the relaxation of photoprotective mechanisms during sun‐to‐shade transitions. However, it is unclear if natural variation in the relaxation of non‐photochemical quenching (NPQ) can be exploited in crop breeding programs. To address this issue, we measured six NPQ parameters in the 40 founder lines and common parent of a Soybean Nested Association Mapping (SoyNAM) panel over two field seasons in Illinois. Leaf disks were sampled from plants grown in the field, and induction and relaxation of NPQ were measured under controlled conditions. NPQ parameters did not show consistently variable trends throughout development, and variation between sampling days suggests environmental impacts on NPQ dynamics. Seventeen genotypes were found to show small but consistent differences in NPQ relaxation kinetics relative to a reference line, providing a basis for future mapping studies. Finally, a soybean canopy model predicted available phenotypic variation could result in a 1.6% difference in carbon assimilation when comparing the fastest and slowest relaxing NPQ values. No correlation could be found between yield and rates of NPQ relaxation, but a full test will require an analysis of isogenic lines.

A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests

AbstractDry deposition is the second largest tropospheric ozone (O3) sink and occurs through stomatal and nonstomatal pathways. Current O3 uptake predictions are limited by the simplistic big‐leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O3 fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface‐atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi‐Layer Canopy CHemistry and Exchange Model, MLC‐CHEM) to the GEOS‐Chem CTM and use this new framework to simulate O3 fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC‐CHEM runs to test current knowledge of O3 deposition and its drivers. We show that GEOS‐Chem overpredicts observed O3 fluxes across all four studies by up to 2×, whereas the resolved‐canopy models capture observed diel profiles of O3 deposition and in‐canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O3 flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O3 deposition on average; (b) in‐canopy chemistry makes only a small contribution to total O3 fluxes; and (c) the CTM big‐leaf treatment overestimates O3‐driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O3 predictions.

SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)

Abstract. We propose a simple dynamic anthropogenic heat (QF) parameterisation for the Weather Research and Forecasting (WRF) single-layer urban canopy model (SLUCM). The SLUCM is a remarkable physically based urban canopy model that is widely used. However, a limitation of SLUCM is that it considers a statistically based diurnal pattern of QF. Consequently, QF is not affected by outdoor temperature changes, and the diurnal pattern of QF is constant throughout the simulation period. To address these limitations, based on the concept of a building-energy model (BEM), which has been officially introduced in WRF, we propose a parameterisation to dynamically and simply simulate QF from buildings (QFB) through a physically based calculation of the indoor heat load and input parameters for BEM and SLUCM. This method allows users to simulate the dynamic QF and the electricity consumption (EC) as the outdoor temperature, building insulation, and heating and air conditioning (HAC) performance change. This is achieved via the simple selection of certain QF options among the urban parameters of WRF. The new parameterisation, SLUCM+BEM, was shown to simulate temporal variations in QFB and EC for HAC (ECHAC) and broadly reproduce the ECHAC estimates of more sophisticated BEM and ECHAC observations in the world's largest metropolis, Tokyo.

Estimating Grassland Biophysical Parameters in the Cantabrian Mountains Using Radiative Transfer Models in Combination with Multiple Endmember Spectral Mixture Analysis

Grasslands are one of the most abundant and biodiverse ecosystems in the world. However, in southern European countries, the abandonment of traditional management activities, such as extensive grazing, has caused many semi-natural grasslands to be invaded by shrubs. Therefore, there is a need to characterize semi-natural grasslands to determine their aboveground primary production and livestock-carrying capacity. Nevertheless, current methods lack a realistic identification of vegetation assemblages where grassland biophysical parameters can be accurately retrieved by the inversion of turbid-medium radiative transfer models (RTMs) in fine-grained landscapes. To this end, in this study we proposed a novel framework in which multiple endmember spectral mixture analysis (MESMA) was implemented to realistically identify grassland-dominated pixels from Sentinel-2 imagery in heterogeneous mountain landscapes. Then, the inversion of PROSAIL RTM (coupled PROSPECT and SAIL leaf and canopy models) was implemented separately for retrieving grassland biophysical parameters, including the leaf area index (LAI), fractional vegetation cover (FCOVER), and aboveground biomass (AGB), from grassland-dominated Sentinel-2 pixels while accounting for non-vegetated areas at the subpixel level. The study region was the southern slope of the Cantabrian Mountains (Spain), with a high spatial variability of fine-grained land covers. The MESMA grassland fraction image had a high accuracy based on validation results using centimetric resolution aerial orthophotographs (R2 = 0.74, and RMSE = 0.18). The validation with field reference data from several mountain passes of the southern slope of the Cantabrian Mountains featured a high accuracy for LAI (R2 = 0.74, and RMSE = 0.56 m2·m−2), FCOVER (R2 = 0.78 and RMSE = 0.07), and AGB (R2 = 0.67, and RMSE = 43.44 g·m−2). This study provides a reliable method to accurately identify and estimate grassland biophysical variables in highly diverse landscapes at a regional scale, with important implications for the management and conservation of threatened semi-natural grasslands. Future studies should investigate the PROSAIL inversion over the endmember signatures and subpixel fractions depicted by MESMA to adequately address the parametrization of the underlying background reflectance by using prior information and should also explore the scalability of this approach to other heterogeneous landscapes.

An In-depth Analysis of Quiet-Sun IRIS Brightenings

Small-scale brightenings are ubiquitous, dynamic, and energetic phenomena found in the chromosphere. An advanced filter-detection algorithm applied to high-resolution observations from the Interface Region Imaging Spectrograph enables the detection of these brightenings close to the noise level. This algorithm also tracks the movement of these brightenings and extracts their characteristics. This work outlines the results of an in-depth analysis of a quiet-Sun data set including a comparison of a brighter domain—associated with a supergranular boundary—to the quiescent internetwork domains. Several characteristics of brightenings from both domains are extracted and analysed, providing a range of sizes, durations, brightness values, travel distances, and speeds. The “active” quiet-Sun events tend to travel shorter distances and at slower speeds across the plane of the sky than their “true” quiet-Sun counterparts. These results are consistent with the magnetic field model of supergranular photospheric structures and the magnetic canopy model of the chromosphere above. Spectroscopic analyses reveal that bright points demonstrate blueshift (as well as some bidirectionality) and that they may rise from the chromosphere into the transition region. We believe that these bright points are magnetic in nature, are likely the result of magnetic reconnection, and follow current sheets between magnetic field gradients, rather than travel along magnetic field lines themselves.

Sensitivity of Fine‐Resolution Urban Heat Island Simulations to Soil Moisture Parameterization

ABSTRACTUrban areas experience the impact of natural disasters, such as heatwaves and flash floods, disparately in different neighbourhoods across a city. The demand for precise urban hydrometeorological and hydroclimatological modelling to examine this disparity, and the interacting challenges posed by climate change and urbanisation, has thus surged. The Weather Research and Forecasting (WRF) model has served such operational and research purposes for decades. Recent advancements in WRF, including enhanced numerical schemes and sophisticated urban atmospheric‐hydrological parameterizations, have empowered the simulation of urban geophysical processes at high resolution (~1 km), but even this resolution misses significant urban microclimate variability. This study applies the large‐eddy simulations (LES) mode within WRF, coupled with single‐layer urban canopy models (SLUCM), to enable even finer‐scale modelling (150 m) of the Urban Heat Island (UHI) effect in the Baltimore metropolitan area. We run nine scenarios to evaluate various methods of initializing soil moisture and various spinup lead times, and to assess the impact of WRF's Mosaic approach in depicting subgrid‐scale processes. We evaluate the scenarios by comparing the WRF simulated land surface temperature (LST) against Landsat LST and the WRF simulated hourly 2‐m air temperatures (AT) with observations from eight weather stations across the domain. Results underscore the paramount influence of the lead spinup time on the spatiotemporal distribution of simulated soil moisture, consequently shaping WRF's efficacy in predicting the UHI. Furthermore, interpolating soil moisture‐related parameters from the parent for child domain initialization yields a notable reduction in mean and root‐mean‐squared errors. This improvement was particularly evident in simulations with the longest spinup time, affirming the importance of carefully designing the initialization of soil moisture for improved urban temperature predictions.

Terrain analysis in forested areas: consequences of using DSM instead of DTM

Abstract. Relief mapping through dense tropical forest is a challenge, which can be met by processing radar images. Various global digital elevation models (DEMs) are available, either free or paid, the most widely used methods for producing them at global scale being photogrammetry and short wavelength radar interferometry. However, the resulting DEMs do not directly represent the ground surface but rather the canopy or something in between. Since most users need terrain models for a variety of applications in geoscience, water management etc. but use such canopy models for lack of anything better, it was relevant to assess the consequences of this inappropriate but unavoidable choice. This paper presents a study carried out in the Brazilian Amazon, where an airborne P-band radar interferometric DEM was used as a reference based on its accuracy assessed in previous studies. A well-established DEM (SRTM) and newer ones (Copernicus and Fabdem), as well as a DEM obtained from aerial X-bands radar data, were compared to the reference according to different criteria related to elevation (accuracy and a typical application, i.e., dam filling simulation) and to slope at different scales (accuracy and a typical application, i.e., terrain classification). The results highlighted the risks of using short wavelengths to represent the terrain and emphasized the importance of slope in different resolution scales.

Local temperature impact of urban heat mitigation strategy based on WRF integrating urban canopy parameters and local climate zones

Urbanization has led to significant alterations in surface properties, contributing to surging urban heatwave events. The detrimental impact of urban heatwaves on public health highlights the urgency for proactive evaluations of diverse heat mitigation strategies. This study assesses the impacts of cool roof (CR), green roof (GR) and rooftop photovoltaic panel (PV) strategies on urban air temperatures within Guangzhou and Foshan agglomeration, utilizing the Weather Research and Forecasting with Urban Canopy Model (WRF-UCM). A comparative analysis of heat exchanges is conducted between two types of urban morphology datasets: local climate zone maps with categorized urban canopy parameters (LCZ-UCPs) and gridded urban canopy parameters from real building databases (gridded-UCPs). The results indicate that the discrepancies in the average temperature between LCZ-UCP and gridded-UCP is almost negligible, whereas increase to 0.39 °C and 0.54 °C for the daily maximum and minimum temperature, respectively. CR provides the most substantial cooling at an average of 0.44 °C, followed by GR and PV. Scenarios with the two types of morphology datasets reveal varying mitigation efficiencies. CRs with LCZ-UCPs show more pronounced temperature reductions, whereas GRs and PVs with gridded-UCPs in central urban regions demonstrate stronger cooling effects. CRs and PVs cool temperature by decreasing sensible heat flux, whereas GR is largely influenced by enhanced evapotranspiration especially with grass plantation. These findings elucidate the differing efficiencies of the three mitigation strategies and highlight the representation discrepancies in climatic simulations brought by the two urban canopy datasets. This emphasizes the importance of accurate urban morphological datasets in evaluating mitigation strategies in WRF-UCM, thus providing practicable insights for urban planning and climate policy-making.

Study of the Future Evolution of the Urban Climate of Paris by Statistical–Dynamical Downscaling of the EURO-CORDEX Ensemble

Abstract High-resolution urban climate projections are needed for local decision-making on climate change adaptation. Regional climate models have resolutions that are too coarse to simulate the urban climate at such resolutions. A novel statistical–dynamical downscaling (SDD) approach is used here to downscale the EURO-CORDEX ensemble to a resolution of 1 km while adding the effect of the city of Paris (France) on air temperature. The downscaled atmospheric fields are then used to drive the Town Energy Balance urban canopy model to produce high-resolution temperature maps over the period 1970–2099, while maintaining the city’s land cover in its present state. The different steps of the SDD are evaluated for the summer season. The regional climate models simulate minimum (maximum) temperatures (TN/TX) that are too high (low). After correction and downscaling, the urban simulations inherit some of these biases but give satisfactory results for summer urban heat islands (UHIs), with average biases of −0.6 K at night and +0.3 K during the day. Changes in future summer temperatures are then studied for two greenhouse gas emission scenarios, RCP4.5 and RCP8.5. Outside the city, the simulations project average increases of 4.1 and 4.8 K for TN and TX for RCP8.5, respectively. In the city, warming is lower, resulting in a decrease in UHIs of −0.19 K at night (from 2.1 to 1.9 K) and −0.16 K during the day. The changes in UHIs are explained by higher rates of warming in rural temperatures due to lower summer precipitation and soil water content and are partially offset by increased ground heat storage in the city.

Highly inhomogeneous interactions between background climate and urban warming across typical local climate zones in heatwave and non-heatwave days

Abstract Urban heat island (UHI) in conjunction with heatwave (HW) leads to exacerbation of thermal stress in urban areas. Prior research on UHI and HW has predominantly concentrated on examining the thermal conditions at the surface and near-surface, with few investigations extending to the radiative and dynamical interactions of UHI and HW, particularly with a focus on the inhomogeneities across local climate zones (LCZs). Here, we analyse the temperature disparity between HW and non-HW conditions across LCZs in the Sydney area by quantifying the contributions of individual radiative and dynamical processes using the coupled surface-atmosphere climate feedback-response analysis method (CFRAM). Three moist HW events in 2017, 2019, and 2020 are simulated using the Weather Research and Forecasting (WRF) model coupled with the single-layer urban canopy model (SLUCM). It is found that the maximum surface and 900 hPa temperature difference between HW and non-HW days may reach up to 10 K, with the increased net solar radiation during HWs being comparable to the typical level of anthropogenic heat flux in urban areas. It is also found that the reduction of clouds, the presence of vapour, and the increase of sensible heat contribute to the warming effect to various degrees, with the contribution of clouds being the most dominant. Conversely, the generation of dry convection and the increase of latent heat flux lead to cooling effects, with the latter being more dominant and capable of causing up to 10 K surface temperature difference between LCZ1 (compact high-rise) and LCZ9 (sparsely built). The differences in the contributions of climate feedback processes across different LCZs become more evident during more severe and humid HWs. These findings underscore the necessity of implementing LCZ-tailored heat mitigation strategies.

Assessment of Regulatory Ecosystem Services of Amasya University Hakimiyet Campus

Background: Population growth, increasing vehicle numbers, unplanned urbanization and rural-urban migration are reducing green spaces and exacerbating environmental problems such as air, water and noise pollution. In this context, university campuses serve as important small-scale urban models that play a crucial role in maintaining environmental and social well-being within urban ecosystems. Objectives: To evaluate the regulating ecosystem services provided by the tree canopy at Amasya University Hâkimiyet Campus (AUHC), such as air quality, energy savings, and carbon storage. Method: In this study, the land cover and ecosystem services of the AUHC were assessed using the i-Tree Canopy model. Six land cover classes defined for the study area (tree/shrub, grass/herbaceous vegetation, soil/bare ground, impervious buildings, impervious roads, other impervious surfaces) were assessed using 4000 random points and ecosystem services such as air quality were calculated. Results: The tree and shrub canopy covering 31.30% of the AUHC removes 261.53 kg of gaseous and particulate pollutants from the air annually, sequesters 36.57 tons of carbon, and stores a total of 918.42 tons of carbon. The economic value of these ecosystem services was calculated as $758 for air pollution removal and $44420 for carbon storage. The land cover distribution of the campus shows that 57.35% consists of impervious surfaces (buildings, roads) and 42.05% is green space. Conclusion: The tree canopy at the AUHC makes a significant contribution to ecosystem services such as improved air quality, carbon sequestration and storage, and these contributions and economic benefits could be further enhanced by increasing tree cover.

A WRF-UCM-SOLWEIG framework for mapping thermal comfort and quantifying urban climate drivers: Advancing spatial and temporal resolutions at city scale

The capability to evaluate city-scale outdoor thermal comfort is crucial for understanding the public's experience of heat stress, especially during heat waves. Nevertheless, there remains a methodological gap in accurately mapping thermal comfort with high spatial and temporal resolutions in complex urban environment and in quantifying the contributions of various urban climate drivers, such as sky view factors and tree canopy fraction. To bridge this gap, we propose an innovative WRF-UCM-SOLWEIG framework that couples a mesoscale model with an urban microclimate model. Specifically, it integrates the Weather Research and Forecasting model coupled with the urban canopy model (WRF-UCM) and the Solar and Longwave Environmental Irradiance Geometry model (SOLWEIG). This framework is then applied to a densely populated tropical city in China, to quantify the impact of urban climate drivers on the Universal Thermal Climate Index (UTCI). The results reveal a significant diurnal variation in the impact of urban morphology. Notably, the most significant drivers affecting daytime UTCI are the impervious surface fraction and the tree canopy fraction, with maximum Pearson's correlation coefficients of 0.80 and -0.70, respectively. These findings suggest that urban heat mitigation strategies should prioritize on reducing impervious surfaces and enhancing shade management, alongside expanding urban forestry measures.

Structural Uncertainty in the Sensitivity of Urban Temperatures to Anthropogenic Heat Flux

AbstractOne key source of uncertainty for weather and climate models is structural uncertainty arising from the fact that these models must simplify or approximate complex physical, chemical, and biological processes that occur in the real world. However, structural uncertainty is rarely examined in the context of simulated effects of anthropogenic heat flux in cities. Using the Weather Research and Forecasting (WRF) model coupled with a single‐layer urban canopy model, it is found that the sensitivity of urban canopy air temperature to anthropogenic heat flux can differ by an order of magnitude depending on how anthropogenic heat flux is released to the urban environment. Moreover, varying model structures through changing the treatment of roof‐air interaction and the parameterization of convective heat transfer between the canopy air and the atmosphere can affect the sensitivity of urban canopy air temperature by a factor of 4. Urban surface temperature and 2‐m air temperature are less sensitive to the methods of anthropogenic heat flux release and the examined model structural variants than urban canopy air temperature, but their sensitivities to anthropogenic heat flux can still vary by as much as a factor of 4 for surface temperature and 2 for 2‐m air temperature. Our study recommends using temperature sensitivity instead of temperature response to understand how various physical processes (and their representations in numerical models) modulate the simulated effects of anthropogenic heat flux.

Combined impacts of aerosols and urbanization on a highly threatened extreme precipitation event in Beijing, China

On July 21, 2012, a catastrophic precipitation event occurred in Beijing, highlighting the serious threat of extreme precipitation on socio-economic development and human health under climate change. Nevertheless, whether, how and to what extent aerosols and urbanization, as the two main influencing factors of urban extreme precipitation, have affected this highly damaging extreme event remains largely unexplored. Here, we employed the weather research and forecasting model coupled with chemistry (WRF-Chem) and a single-layer urban canopy model to investigate the influences of urbanization, aerosols and their interactions on this extreme precipitation event. We found that the joint intensification effects of urbanization and aerosols on extreme precipitation events greatly enhance its negative influence on megacities. The results indicate that aerosols are enhanced by increasing cloud droplet numbers, thereby intensifying the feedback between precipitation and latent heating. Consequently, the total precipitation increased by 22.6%, raising the precipitation in the Beijing area increase by at least 50 mm. By stimulating atmospheric instability and strengthening vertical air motion (over 0.25 m s−1), the urban heat island effect considerably influences the temporal and spatial distributions of extreme precipitation events, resulting in an increase in warm cloud precipitation (80%) and a decrease (30%) in frontal precipitation. Consequently, joint intensification effects resulted in more concentrated precipitation in the southwest of Beijing, leading to a substantial increase (more than 40%, ∼80 mm). This condition may be an important reason for the most severe disasters in the southwest of Beijing.

Inversion Modeling of Chlorophyll Fluorescence Parameters in Cotton Canopy via Moisture Data and Spectral Analysis

The study of chlorophyll fluorescence parameters is very important for understanding plant photosynthesis. Monitoring cotton chlorophyll fluorescence parameters via spectral technology can aid in understanding the photosynthesis, growth, and stress of cotton fields in real time and provide support for cotton growth regulation and planting management. In this study, cotton plot experiments with different water treatments were set up to obtain the spectral reflectance of the cotton canopy, the maximum photochemical quantum yield (Fv/Fm), and the photochemical quenching coefficient (qP) of leaves at different growth stages. Support vector machine regression (SVR), random forest regression (RFR), and artificial neural network regression (ANNR) were used to establish a fluorescence parameter inversion model of the cotton canopy leaves. The results show that the original spectrum was transformed by multivariate scattering correction (MSC), the standard normal variable (SNV), and continuous wavelet transform (CWT), and the model constructed with Fv/Fm passed accuracy verification. The SNV-SVR model at the budding stage, the MSC-SVR model at the early flowering stage, the SNV-SVR model at the full flowering stage, the MSC-SVR model at the flowering stage, and the CWT-SVR model at the full boll stage had the highest estimation accuracy. The accuracies of the three spectral preprocessing and qP models were verified, and the MSC-SVR model at the budding stage, SNV-SVR model at the early flowering stage, MSC-SVR model at the full flowering stage, SNV-SVR model at the flowering stage, and CWT-SVR model at the full boll stage presented the highest estimation accuracies.

Flow Field Characteristics at the Spanwise Edge of a Vegetative Canopy Model

This study investigates the complex flow field across a spanwise vegetative model canopy edge focusing on turbulent transport processes. Utilizing stereoscopic particle image velocimetry, the three velocity components were measured in wall-parallel planes at various elevations within canopy across the spanwise canopy edge. Conventional ensemble averaged results were contrasted with those obtained by conditionally averaged flow properties across instantaneous internal interfaces in the flow to understand their contribution to the ensemble average. The conditional average captured the strong gradients in mean velocities, Reynolds stresses, vorticity, swirling strength, and turbulent kinetic energy production across the dynamically changing instantaneous interface. In contrast, the conventional ensemble average smeared out the strong gradients. Small magnitudes of advective terms in the turbulent kinetic energy transport equation suggested weak secondary transverse flows in the present model canopy. The turbulent flow structure across the spanwise canopy edge was further investigated using Quadrant-Hole analysis for both averaging approaches. Conventional ensemble averaged results indicated a shift from sweep to ejection dominance when moving from canopy into the open patch, while the conditional average showed only sweep dominated transport. In contrast to a homogeneous canopy layout, below canopy height at the canopy edge, sweeps and ejections lose their dominance in vertical turbulent transport. The present results show that the dynamics of internal interfaces govern the ensemble averaged results and a possible implementation into existing models is proposed. The present results are expected to increase understanding of spanwise turbulent transport and aid in developing strategies to mitigate desertification.