Mesoscale Meteorological Model Research Articles

Improved mesoscopic meteorological modelling of the urban climate for building physics applications

A meteorological mesoscale model is used to predict the local urban climate at 250 m resolution. The authors propose a hybrid machine learning approach to improve the prediction accuracy and remove simulation bias. Two case studies are presented to show the improvements of the simulation accuracy. Based on the hybrid model results, using cooling degree hours is proposed as an insightful time-dependent index to map local hotspots and assess the difference of cooling loads between rural and urban environments.

Simulating Microscale Urban Airflow and Pollutant Distributions Based on Computational Fluid Dynamics Model: A Review.

Urban surfaces exert profound influences on local wind patterns, turbulence dynamics, and the dispersion of air pollutants, underscoring the critical need for a thorough understanding of these processes in the realms of urban planning, design, construction, and air quality management. The advent of advanced computational capabilities has propelled the computational fluid dynamics model (CFD) into becoming a mature and widely adopted tool to investigate microscale meteorological phenomena in urban settings. This review provides a comprehensive overview of the current state of CFD-based microscale meteorological simulations, offering insights into their applications, influential factors, and challenges. Significant variables such as the aspect ratio of street canyons, building geometries, ambient wind directions, atmospheric boundary layer stabilities, and street tree configurations play crucial roles in influencing microscale physical processes and the dispersion of air pollutants. The integration of CFD with mesoscale meteorological models and cutting-edge machine learning techniques empowers high-resolution, precise simulations of urban meteorology, establishing a robust scientific basis for sustainable urban development, the mitigation of air pollution, and emergency response planning for hazardous substances. Nonetheless, the broader application of CFD in this domain introduces challenges in grid optimization, enhancing integration with mesoscale models, addressing data limitations, and simulating diverse weather conditions.

Influence of the lowest model level height and vertical grid resolution on mesoscale meteorological modeling

This study employed the Weather Research and Forecasting (WRF) model to investigate the roles of lowest model level height (LMLH) and vertical grid resolution (VGR) in mesoscale meteorological modeling. Statistical analysis suggests that the vertical configuration of the model has a minor impact on meteorological modeling under daytime convective boundary layer conditions. However, modifying the LMLH can have a noticeable effect on the surface meteorology simulation during nighttime, specifically in the simulations of the 2-m temperature and relative humidity. The contribution of the VGR was mainly reflected in the 10-m wind speed simulation. Further analysis showed that the discrepancies in the surface meteorology variables caused by the LMLH configurations were more apparent during pollution episodes than during regular days. The LMLH had a significant impact on surface meteorology, and the VGR primarily influenced vertical distributions. These findings indicate that the effects of the vertical configuration of the model on meteorological simulation are closely associated with the stability of the boundary layer, which will have important implications for subsequent chemical transport modeling. Decreasing the LMLH and refining the VGR both enhanced the stability of the nocturnal boundary layer, with negligible effects on the convective boundary layer prediction. Reducing the LMLH from 58 m to 30 m resulted in a 7.6% reduction in the simulation error of the surface meteorological variables. A further reduction to 12 m resulted in a 10.6% improvement without a significant increase in the computational cost.

NUMERICAL SIMULATION OF GRAVEL NOURISHMENT TO THE SEISHO COASTLINE IN JAPAN

It is feared that as a consequence of the potential future intensification of tropical cyclones due to ongoing climate change the patterns of coastal erosion around the world could change. In this study, the mesoscale meteorological model WRF (Weather Research and Forecasting), the third-generation stand-alone wave model SWAN (Simulating WAves Nearshore), and the coastal deformation model XBeach (eXtreme Beach behavior) are combined to calculate the short-term coastal deformation caused by high waves during the approach of Typhoon No.21 (Paolo) in 2017 to the Seisho Coast and Niigata Coast in Japan (Nishida and Shibayama, 2020). The model is then applied to predict future patterns of coastal erosion. Potential countermeasures to prevent future coastal erosion are then examined. The construction of detached breakwaters, which are currently used as a countermeasure against coastal erosion in many parts of the world, is often opposed by local residents due to the changes they can produce on the fishing environment and landscape. Therefore, it is often desirable to stabilize the beach without constructing structures offshore. Thus, gravel nourishment is proposed as a countermeasure against the short-term erosion that can be caused high waves, and its benefits and impacts were verified through numerical simulations.

On a new one‐dimensional k$$ \boldsymbol{k} $$–ε$$ \boldsymbol{\varepsilon} $$ turbulence closure for building‐induced drag

AbstractVarious urban canopy parameterizations (UCPs) have been developed in the last two decades to take into account the modifications induced by buildings on mean flow and turbulent fields in mesoscale meteorological models, the typical spatial resolution of which cannot resolve urban structures explicitly. In particular, several multilayer UCPs have been proposed, successfully reproducing wind‐flow characteristics in the urban environment. However, they often rely on length scales for the calculation of the eddy viscosity and the dissipation rate, which need to be tuned for various urban configurations. The main objective of this work is to address this shortcoming, by developing a new one‐dimensional turbulence closure that takes building‐induced turbulence into account independently of turbulence length scales. This model directly solves not only the equation for turbulent kinetic energy but also the equation for its dissipation rate (– model). Similar closure schemes have been successfully adopted for vegetated canopies, but their applicability to urban canopies is still unknown. The performance of the new – model, with additional sources and sinks for wind speed, turbulent kinetic energy, and dissipation rate, is tested by means of single‐column simulations in idealized urban areas, using different building packing densities. Results are in good agreement with spatially averaged building‐resolving CFD simulations. In particular, vertical profiles of mean and turbulent variables show better results with respect to simulations using turbulence closures adopting a parameterization of turbulence length scales. The best improvements are obtained for wind speed, reducing errors to half the typical values for standard UCP for high packing densities, and for the dissipation rate. Furthermore, besides the enhancement in the reproduction of the mean flow for urban areas, the proposed turbulence closure does not need additional tuning of coefficients depending on the packing density, resulting in a more general and efficient scheme.

Effects of anthropogenic emissions and meteorological conditions on diurnal variation of formaldehyde (HCHO) in the Yangtze River Delta, China

Formaldehyde (HCHO) plays an important role in the troposphere, as it is a major precursor of ozone and heavily affects the health of lives on the earth. However, to the present, major factors that influence the diurnal variation of HCHO in the Yangtze River Delta (YRD) of China have not been investigated thoroughly. Moreover, sensitivities of the HCHO concentration in cities of YRD to the primary anthropogenic emissions of these cities are also unclear. Thus, we used a mesoscale meteorological model coupled with chemistry, WRF-Chem to capture the variation of HCHO in ten cities of YRD, so that the factors dominating the diurnal change of HCHO in these cities can be identified. We also performed sensitivity tests by varying the primary anthropogenic emission intensity of HCHO, to investigate the sensitivity of HCHO in each city to primary anthropogenic emissions of HCHO. The simulation results showed that the driving factors for the daytime peak of HCHO include photochemical reactions and VOCs＋OH reactions. The change in meteorological conditions causes a deviation of the temporal evolution of HCHO in many cities of YRD from the conventional trend (i.e., peak at noon and low in the rest). The major impact areas of HCHO anthropogenic emissions from the cities of YRD and the contributions to HCHO in these cities were also revealed.

The Influence of Refined Urban Morphological Parameters on Dynamical and Thermal Fields in a Single-Layer Urban Canopy Model

In this study, localised and non-uniform urban morphology (UM) and urban fraction (UF) parameters are implemented in a single-layer urban canopy scheme in the Weather Research and Forecasting (WRF) mesoscale meteorological model. The purpose of this research is to evaluate the effect of the refined parameterisation scheme on the simulation of dynamic and thermal fields in the urban canopy of the Guangzhou metropolitan area. The results showed that, compared with the default urban canopy parameters of the WRF model, using the localised UM parameters resulted in the most significant improvement in the 10 m wind speed simulation. In urban districts, the mean bias between the observed and simulated 10 m wind speed was reduced significantly by 59% from 2.63 m/s to 1.09 m/s during the daytime. For the thermal environment simulation during the daytime, higher UF and UM values resulted in lower surface albedos and generated narrower street canyons compared with the default modelling setting, which caused more heat to be trapped in the urban canopy and ultimately led to an increase in the surface skin temperature (TSK) and a largely increased ground heat flux (GRD). As a result, at night, more heat was transferred from the ground to the surface, producing a higher TSK. The effect of the localised UF on the sensible heat flux (HFX) was closely related to the near-surface temperature gradient. The UM caused the HFX to increase during the daytime, which was related to the near-surface heat exchange coefficient in the lower model layers. As the high-resolution UM significantly altered the urban geometry, the dynamic environment simulation resulted in a large increase in friction velocity and a decrease in wind speed.

メソ気象モデルWRFを用いた堺市の人口減少に対応した緑地配置シナリオの気候分析

This study aimed to understand how different green spaces allocation would moderate higher urban temperatures. Specifically, numerical simulation was performed for understanding air temperature and wind distribution in August 2020, and the Weather Research and Forecasting meso-scale meteorological model was used in Sakai City. Furthermore, we performed climate simulation under three future green spaces allocation scenarios corresponding to population decline. In addition, climate analysis maps were created for each of these scenarios, and a comparison and discussion were conducted on how Sakai City’s green spaces should be arranged to accommodate future population decline. The results showed that conservation of green spaces reduced high temperatures in the city as a whole, but the distribution trends of temperature reduction area differed among the scenarios. These results suggested that while a large area of green spaces was effective in reducing temperatures locally, the green space network can also extend the temperature reduction over a wider area.

Comparison of tropospheric delay correction methods for InSAR analysis using a mesoscale meteorological model: a case study from Japan

A major source of error in interferometric synthetic aperture radar (InSAR), used for mapping ground deformation, is the delay caused by changes in the propagation velocity of radar microwaves in the troposphere. Correcting this tropospheric delay noise using numerical weather models is common because of their global availability. Various correction methods and tools exist; selecting the most appropriate one by considering weather models, delay models, and delay calculation algorithms is essential for specific applications. We compared the performance of two tropospheric delay correction methods applied to Advanced Land Observing Satellite-2 (ALOS-2) data acquired over Japan, where the atmospheric field is complex with significant seasonal variation. We tested: (1) a method of delay integration along the slant radar line-of-sight (LOS) path using the mesoscale model (MSM) provided by the Japan Meteorological Agency and (2) the Generic Atmospheric Correction Online Service (GACOS) for InSAR, which estimates delay using the high-resolution forecast (HRES)-European Centre for Medium-Range Weather Forecasts (ECMWF) products along with an iterative decomposition approach. The results showed that the tropospheric delay correction using the slant-delay integration approach with MSM, which has a finer temporal and spatial resolution, performed slightly better than GACOS. We further found that the differences in the refractivity models would have limited significance, suggesting that the difference in performance mainly originates from differences in the numerical weather models being used. This study highlights the importance of using the best-available numerical weather model data for tropospheric delay calculations.Graphical

Radio-tellurium released into the environment during the complete oxidation of fuel cladding, containment venting and reactor building failure of the Fukushima accident

ABSTRACT An accurate source term estimation of radionuclides released during the Fukushima accident is essential for understanding the accident progression of reactors and the environmental impact assessment. The hypothetical amount emission-regression estimation method was used, in which the deposition distribution is weighted based on the hourly deposition obtained from mesoscale meteorological model calculations assuming hypothetical amount emissions. The weighted emission rate is determined to minimize the difference between the sum of these distributions and a soil contamination map. The preceding study focused on obtaining tentative results for the source terms. Subsequent examination revealed that if any part of the time when a release is thought to have occurred is missing from the estimated release period, the entire calculation will be distorted, leading to the conclusion that a recalculation is necessary. Therefore, present study performed the recalculation by extending the estimation period to cover all major releases. Consequently, unspecified release events were clarified, and their correspondence to in-core events was confirmed. Based on the present study’s results, the possibility of increased iodine and Cs releases in the evening of 11 March 2011, and early mornings of March 13 and 14, 2011, which were not predicted by the WSPEEDI reverse calculation, was highlighted.

Simulated climate effect of the Three Gorges Reservoir after its completion:Within surface and local scope instead of regional

针对以往三峡水库气候效应数值模拟研究中,水库参数化方案简约及模拟时段未涉及成库以来高水位运行阶段等不足,在中尺度气象模式中,通过扩宽水体面积和抬升水位高度的方式对三峡水库引起的陆面参数变化进行描述,进而采用敏感性数值试验及统计分析等手段,评估了三峡水库成库以来高温干旱(2013年)和低温洪涝(2020年)年景下,关键气象要素对水库运行的响应特征。结果表明:两种典型年景下水库运行均会造成近地层气温降低(0.98~1.27℃)、相对湿度增加(3.9%~5.5%)和风速增大(0.43~0.68 m/s),同时响应强度的日变化导致近地层气温和相对湿度的日较差减小、平均风速的日较差增大;尽管上述变量的变化幅度与该地区气候的自然变率相当,但水库运行对气温和相对湿度的影响范围基本限制于水库周边约2 km,垂直方向则大多低于200 m,对风速的影响范围可扩展至水库周边约12 km,垂直方向延伸至200 m左右,且响应强度均随水平距离和垂直高度的增加而显著减小。尽管数值试验放大了三峡水库的气候效应,但作为典型的河道型水库,三峡水库成库以来的不同气候年景下,水库运行产生的气候效应基本限制在近地层、局地范围内,未对区域气候产生明显影响。;In view of the shortcomings of the previous numerical simulation research on the climate effect of the Three Gorges Reservoir (TGR), such as the simplicity of the reservoir parameterization and the fact that the simulation period did not involve the reservoir impoundment period, the changes of land surface parameters induced by the TGR were numerically described by increasing the river width and raising the water level in the mesoscale meteorological model. The variation characteristics of meteorological elements after completion of the TGR were analyzed based on two parallel numerical simulations, control run (no TGR) and sensitive run (TGR), during the drought year with high temperature (2013) and the flood year with low temperature (2020). The results show that the operation of TGR under these two typical years both reduce the surface temperature (0.98-1.27℃), increase the relative humidity (3.9%-5.5%) and the wind speed (0.43-0.68 m/s), the diurnal range of near-surface temperature/relative humidity decreases and the diurnal range of wind speed increases with the diurnal variation of the response; Although the aforementioned responses are equivalent to the natural climate variability, the variations of temperature and relative humidity are basically limited to about 2 km around the reservoir, most of which are lower than 200 m in the vertical direction, and the variation of wind speed change extend to about 12 km near the reservoir with up to 200 m in the vertical direction. All of these responses decrease significantly with the increase of horizontal distance and vertical height. Therefore, although the climate effect of the TGR is amplified in our simulation experiment, as a typical river-type reservoir, the climate effect induced by the operation of TGR is basically limited to the surface and local area, and has no obvious influence on the regional climate.

Preliminary Investigation of the Potentialities of a Mesoscale Meteorological Model to Reproduce Experimental Statistics of Rain Attenuation on Earth-Space Links

Current spatial resolutions achieved by mesoscale weather forecast models allow them to be used to generate the state of the lowest layers of the atmosphere over areas as small as a few square kilometers which corresponds to the typical size of the tropospheric area crossed by Earth-space links. Furthermore, they allow the evolution of the troposphere to be predicted with a time stamp of five minutes instead of every hour with large-scale weather forecast models which makes them attractive for radio propagation predictions for satellite communication applications. This paper aims at studying the capability of the Weather Research and Forecast (WRF) model coupled with an electromagnetic physical model to reproduce rain attenuation statistics for Earth-space paths at Ka-band. To this purpose, one year of propagation measurements collected at 20 GHz in different places at midlatitudes in Toulouse and Salon de Provence (France), Spino d’Adda (Italy), Aveiro (Portugal), and Madrid (Spain), at high latitudes in Svalbard (Norway) and at low latitudes in Kourou are used to make comparisons between simulations and measurements. Comparisons between the simulated and the experimental annual statistics considered in this paper provide encouraging results, with a similar accuracy as Recommendation ITU-R P.618–13 for midlatitude European locations and with better accuracy for a high latitude area in Svalbard and for an equatorial location in French Guiana.

A coupled WRF-PV mesoscale model simulating the near-surface climate of utility-scale photovoltaic plants

To simulate the local or regional climate of utility-scale photovoltaic (PV) plants, a new PV-associated energy balance model was developed for the Weather Research and Forecasting Model (WRF). The resultant tool can be used to improve our understanding of the interaction between utility-scale PV plants and land-surface processes. The effects of PV panels were represented by transferring the solar radiation into electricity and heat flux and imposing an extra drag force on the mean flow in the model domain. The proposed PV model is more advanced than previous models in the following ways: (1) The model is universal based on its analytical expression of the sensible heat of PV panels and the influence of the physical shielding of the panels on the upward longwave radiation. (2) The photoelectric conversion efficiency (ε) in the model is temperature dependent and restrained between seasons. (3) The model includes the soil and latent heat flux parameterizations under observation constraints in a novel way. (4) The model bases the dynamic roughness length (Z0) on the eddy covariance flux observation. This new PV model was then incorporated with the WRF mesoscale meteorological model, and the model evaluation in two utility-scale PV plants demonstrated acceptable performance of the new WRF-PV mesoscale model in simulating the max/mean daily surface temperature, downward shortwave radiation, and wind speed with correlation coefficients of 0.61–0.99, and the hourly sensible/latent heat fluxes, with correlation coefficients of 0.59–0.93 during different seasons. The consistency of the performance of the model across these near-surface meteorological variables confirms the versatility and reliability of the new WRF-PV model as a suitable tool for simulating the climate of utility-scale PV plants.

Temperature and Precipitation Bias Patterns in a Dynamical Downscaling Procedure over Europe during the Period 1951–2010

The Weather Research and Forecasting (WRF) mesoscale meteorological model is used to dynamically downscale data from the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) CMIP5 version (Model E2-R) over Europe at a 0.25° grid size resolution, for the period of 1951 to 2010. The model configuration is single nested with grid resolutions of 0.75° to 0.25°. Two 30-year datasets are produced for the periods of 1951–1980 and 1981–2010, representing the historic and current periods, respectively. Simulated changes in climate normals are estimated and compared against the change derived from the E-OBS gridded dataset at 0.25° spatial analysis. Results indicate that the model consistently underpredicts the temperature fluctuations observed across all subregions, indicative of a colder model climatology. Winter has the strongest bias of all seasons, with the northeastern part of the domain having the highest. This is largely due to the land–atmosphere interactions. Conversely, spring and summer have the lowest regional biases, owing to a combination of low snow cover (relative to winter) and milder radiation effects (as opposed to summer). Precipitation has a negative bias in most cases, regardless of the subregion analyzed, due to the physical mechanism employed and the topographic features of each region. Both the change in the number of days when the temperature exceeds 25 °C and the change in the number of days when precipitation exceeds 5 mm/day are captured by the model reasonably well, exhibiting similar characteristics with their counterpart means.

Urban ventilation assessment with improved vertical wind profile in high-density cities – Comparisons between LiDAR and conventional methods

The vertical wind speed profile is crucial to urban ventilation assessment and urban planning/design. This study uses Light Detection and Ranging (LiDAR) observation as benchmark to evaluate accuracy of wind profiles estimated by conventional methods. The conventional methods include Boundary Layer Wind Tunnel (BLWT), Regional Atmospheric Modeling System (RAMS), Power Law (PL), and Weather Research and Forecasting (WRF). The evaluation involves two typical urban sites with different densities under summer weak-wind conditions. Large Eddie Simulations (LES) are conducted to further investigate the sensitivity of urban ventilation assessment results to the deviations of wind profiles. The results indicate significant deviations in LES caused by conventional methods. The largest deviations of wind velocity ratio are found in mesoscale meteorological models (RAMS and WRF (>65%)). Deviations caused by physical and empirical models are smaller but still significant (BLWT (>25%) and PL (>40%)). Consequently, large deviations (>100%) of wind-relevant criterion for outdoor thermal comfort are observed. Finally, to balance accuracy and data availability, we recommend power law method as the optimal method to provide inflow boundary condition for numerical simulations when LiDAR observation is not available. We provide new and valuable understandings to improve urban ventilation assessment in high-density cities.

Simulated Influence of Mountainous Wind Farms Operations on Local Climate

Renewable energy sources, especially wind power, were believed to be able to slow down global warming; however, evidence in recent years shows that wind farms may also induce climate change. With the rapid development of wind power industry, the number of wind farms installed in mountains has gradually increased. Therefore, it is necessary to study the impact of wind farms in mountainous areas on local climate. The Suizhou and Dawu wind farms in northern Hubei Province were chosen for the present study on the impact of wind farm operations on the local climate in mountainous areas. The mesoscale meteorological numerical model Weather Research and Forecasting Model (WRF) and the Fitch model, together with turbulence correction factor, were used to simulate wind farm operations and study their effects on local climate. The results showed the characteristics of wind speed attenuation in mountainous wind farms: the amplitude and range of wind speed attenuation were stronger in the nighttime than in the daytime, and stronger in summer than in winter. The surface temperature increased and became more significant in summer. However, a cooling variation was observed above the surface warming center. The height of this center was higher in the daytime than it was in the nighttime. The latent heat flux in the wind farms decreased at night, accompanied by an increase in sensible heat flux. However, these changes were not significant. Some differences were observed between the impact of wind farms on the climate in the plains and the mountains. Such differences are more likely to be related to complex terrain conditions, climate conditions, and the density of wind turbines. The present study may provide support for the development and construction of wind farms in mountainous areas.

Measurements on the surface wind pressure characteristics of a thousand-meter scale megatall building by wind tunnel test

This paper investigates the wind pressure distribution of a thousand-meter scale megatall building through a wind tunnel test. One key challenge is that the power-law wind profiles are not applicable due to the height limitation. Therefore, a mesoscale meteorological model WRFv3.4 (Weather Research & Forecasting Model) was used to explore the wind profile covering the height of the thousand-meter scale megatall building. Then the wind profile was reproduced in the wind tunnel representing the actual vertical distribution of wind speed by a passive simulation method, and thereby the wind pressure test was conducted in the wind tunnel. Moreover, to investigate the effect of the inlet wind profile on the wind pressure, a wind tunnel test using the power-law wind profile was carried out for comparison as well. It was revealed that the wind pressure distribution was greatly influenced by the inlet wind profile, which should be investigated with accuracy in the wind tunnel.

A Supercomputer-Based Modeling System for Short-Term Prediction of Urban Surface Air Quality

This paper proposes a mathematical model and an effective supercomputer-based numerical method for short-term prediction of extreme meteorological conditions and atmospheric air quality over limited stretches of land encompassing large population centers. The mathematical model includes a pollutant transport model with a reduced chemical mechanism and a non-hydrostatic mesoscale meteorological model with a modern moisture microphysics parametrization scheme. The numerical method relies on the use of the finite volume method and semi-implicit difference schemes of the second order of approximation, which are solved using the TDMA method with a linear dependence of the number of arithmetic operations on the size of the grid. This property of the numerical method ensures high efficiency when parallelized: not less than 70% when using up to 256 computing cores with a horizontal grid size of 0.5–1.0 km. Development of parallel programs was carried out using the Message Passing Interface parallel programming technology, two-dimensional decomposition of the grid area along horizontal (west to east and south to north) directions, and introduction of additional fictitious grid nodes along the perimeter of the decomposition subdomains.

The Flash Flood Guidance System Implementation Worldwide: A Successful Multidecadal Research-to-Operations Effort

Abstract At the beginning of the twenty-first century a research-to-operations program was initiated to design and develop operational systems to support local forecasters in their challenging task to provide advance warning for flash floods worldwide. Twenty-some years later, the Flash Flood Guidance System with global coverage provides real-time assessment and guidance products to more than 60 countries, serving nearly 3 billion people. The implementation domains cover a wide range of hydroclimatological, geomorphological, and land-use regimes worldwide. This flexible and evolving system combines meteorology and hydrology data and concepts as well as supports product utility for flash flood disaster mitigation on very large scales with high spatial and temporal resolution. Through quality control procedures, it integrates remotely sensed data of land surface precipitation and of land surface properties from geostationary and polar-orbiting satellite platforms, reflectivity data from a variety of weather radar systems, and asynchronous precipitation data from ground-based automated precipitation gauges in order to produce assessments and short-term forecasts that support forecasters and disaster managers in real time. For each region, it also integrates mesoscale meteorological model forecasts with land surface model response to produce longer-term guidance products. It contains components and interfaces that allow real-time forecaster adjustments to products based on local last-minute field information and relevant forecaster experience. Assessments of utility for flash flood warning operations by national forecasting agencies worldwide are positive. The article exemplifies the process of realization and evolution of the Flash Flood Guidance System (FFGS) from research in interdisciplinary fields to operations in diverse environments, and discusses lessons learned.

The relationship between the altitude and the simulations of ozone and NO2 by WRF-Chem for the Tibetan Plateau

Simulations of the spatiotemporal distribution of air constituents such as ozone and NO2 on the Tibetan Plateau (TP) can be affected by many factors such as the altitude of the observational site. In the present study, we used a mesoscale meteorological model coupled with chemistry (WRF-Chem) with two different anthropogenic emission inventories (MEIC and MEIC + EDGAR), to investigate the association of the simulation accuracy of ozone and NO2 on TP with the altitude of the observational sites. Statistical parameters such as the correlation coefficient (r) and the index of agreement (IOA) were also calculated to evaluate the model performance in capturing the concentration change of these two air constituents (i.e., ozone and NO2). The results revealed that when only the MEIC emission inventory is implemented, the deviation between the model simulations and the observations becomes larger with the increase of the altitude of the city. Moreover, it was also found that when the EDGAR emission inventory was added into the model (i.e., MEIC + EDGAR scenario), the negative dependence of the simulation accuracy of ozone on the altitude becomes weaker than that using only MEIC inventory, due to the change in ozone simulations in high-altitude cities. In contrast, simulation results of NO2 using two different emission inventories were found to be similar to each other.