Mesoscale Meteorological Model Research Articles

Parallel implementation of a numerical method for solving a three-dimensional transport equation for a mesoscale meteorological model

Abstract A parallel algorithm for numerical solution of a generalized unsteady 3-dimensional advection-diffusion equation for a mesoscale meteorological model is considered. Efficiency of parallel implementations of the solver with Message Passing Interface (MPI), Open Multi-Processing (OpenMP), and NVidia Compute Unified Device Architecture (CUDA) technologies was compared. It was shown that on the mesh of 25625632 nodes the speedup of the program reaches 18 for OpenMP and MPI implementations and 38 for CUDA.

Introduction, evaluation and application of an energy balance model for photovoltaic modules

Here we introduce a new energy balance model that accurately simulates the complete diurnal dynamics of photovoltaic (PV) thermal behavior with routinely available meteorological input. The model is evaluated extensively against observed module surface temperatures (day and nighttime), electrical output, and sensible heat flux measurements. It is demonstrated that different tracking systems have a significant effect on module temperatures and sensible heat fluxes by modulating the total radiation received on the PV surface. A model intercomparison study indicates significant improvements in the representation of module temperatures compared to an earlier study, the commercial software PVsyst and the Python package PVLIB. A sensitivity study demonstrates a considerable effect of the PV conversion efficiency and longwave emissivity on sensible heat fluxes emitted by the module. The model is available as a stand-alone program (UCRC-Solar) written in Python and planned to be implemented in mesoscale meteorological models to study the geophysical impacts of PV arrays at larger spatial and longer temporal scales.

Teaching Atmospheric Modeling at the Graduate Level: 15 Years of Using Mesoscale Models as Educational Tools in an Active Learning Environment

AbstractNumerical weather prediction models have become widespread tools that are accessible to a variety of communities, ranging from academia and the national meteorological services to commercial weather providers, wind and solar energy industries, and air quality modelers. Mesoscale meteorological models that are used to refine relatively coarse global weather forecasts to finer atmospheric scales have become mainstream. The wide use of mesoscale meteorological models also generates new requirements in undergraduate education concerning the knowledge and application of these models. In this paper, we present teaching strategies, course outcomes, student activities, impacts, and reflections on the possible future direction of the graduate-level atmospheric modeling course using the Weather Research and Forecasting (WRF) Model at Wageningen University, the Netherlands. This information is based on 15 years of experience in teaching the course and the continuous implementation of new educational techniques to adapt to students’ needs and improve their chances in their academic careers and the atmospheric sciences job market.

Modeling of mesoscale phenomena using WRF-BEP-BEM-CIM in a complex region

Because of the global warming, urban planning strategies must be investigated to reduce building energy consumption and increase thermal comfort in urban areas. It is thus proposed in this study to use a mesoscale meteorological model to study the impact of multiple urban planning scenarios in the Canton of Vaud. The Weather Research and Forecast (WRF) model is used to conduct simulations. The urban parameterizations, Building Effect Parameterization + Building Energy Model + Canopy Interface Model (BEP-BEM-CIM), developed in previous studies are already integrated in the WRF model. We demonstrate that the models perform well in plateaued regions (<10% difference) but some important deviations (20%-30% difference) are noted in particularly complex regions with complex topography. Two possible improvements will be addressed in the future: there is a need to improve the topography representation in the model itself and other scenarios including the impact of future climate will also be assessed.

Development of turbulent scheme in the FLEXPART-AROME v1.2.1 Lagrangian particle dispersion model

Abstract. The FLEXible PARTicle dispersion model FLEXPART, first released in 1998, is a Lagrangian particle dispersion model developed to simulate atmospheric transport over large and mesoscale distances. Due to FLEXPART's success and its open source nature, different limited area model versions of FLEXPART were released making it possible to run FLEXPART simulations by ingesting WRF (Weather Research Forecasting model), COSMO (Consortium for Small-scale Modeling) or MM5 (mesoscale community model maintained by Penn State university) meteorological fields on top of the ECMWF (European Centre for Medium-Range Weather Forecasts) and GFS (Global Forecast System) meteorological fields. Here, we present a new FLEXPART limited area model that is compatible with the AROME mesoscale meteorological forecast model (the Applications of Research to Operations at Mesoscale model).1 FLEXPART-AROME was originally developed to study mesoscale transport around La Réunion, a small volcanic island in the southwest Indian Ocean with a complex orographic structure, which is not well represented in current global operational models. We present new turbulent modes in FLEXPART-AROME. They differ from each other by dimensionality, mixing length parameterization, turbulent transport constraint interpretation and time step configuration. A novel time step was introduced in FLEXPART-AROME. Performances of new turbulent modes are compared to the ones in FLEXPART-WRF by testing the conservation of well-mixedness by turbulence, the dispersion of a point release at the surface and the marine boundary layer evolution around Réunion. The novel time step configuration proved necessary to conserve the well-mixedness in the new turbulent modes. An adaptive vertical turbulence time step was implemented, allowing the model to adapt on a finer timescale when significant changes in the local turbulent state of the atmosphere occur.

Analysis of Pollutant Dispersion in a Realistic Urban Street Canyon Using Coupled CFD and Chemical Reaction Modeling

Studies in actual urban settings that integrate chemical reaction modeling, radiation, and particular emissions are mandatory to evaluate the effects of traffic-related air pollution on street canyons. In this paper, airflow patterns and reactive pollutant behavior for over 24 h, in a realistic urban canyon in Osaka City, Japan, was conducted using a computational fluid dynamics (CFD) model coupled with a chemical reaction model (CBM-IV). The boundary conditions for the CFD model were obtained from mesoscale meteorological and air quality models. Inherent street canyon processes, such as ground and wall radiation, were evaluated using a surface energy budget model of the ground and a building envelope model, respectively. The CFD-coupled chemical reaction model surpassed the mesoscale models in describing the NO, NO2, and O3 transport process, representing pollutants concentrations more accurately within the street canyon since the latter cannot capture the local phenomena because of coarse grid resolution. This work showed that the concentration of pollutants in the urban canyon is heavily reliant on roadside emissions and airflow patterns, which, in turn, is strongly affected by the heterogeneity of the urban layout. The CFD-coupled chemical reaction model characterized better the complex three-dimensional site and hour-dependent dispersion of contaminants within an urban canyon.

One-way coupling of WRF with a Gaussian dispersion model: a focused fine-scale air pollution assessment on southern Mediterranean.

Numerous uncertainty factors in dispersion models should be taken into account in order to improve the reliability of predictions. The ability of a mesoscale meteorological model to assimilate observational data is an efficient way to improve operational air quality model forecasts. In this study, local weather data assimilation based on a flux-adjusting surface data assimilation system (FASDAS) is introduced to a Gaussian atmospheric dispersion model for a period with reported stable meteorological conditions. After evaluating the vulnerabilities of FASDAS, a combined data assimilation method is proposed to simultaneously improve the model weather prediction and retrieve the representation of accurate concentration distributions for short-range dispersion modeling against a control run. The two main uncertainty parameters considered are the wind speed and direction. A twin experiment demonstrates that the combined technique effectively improves the distribution of simulated concentrations. Comparison between results before and after the implement of data assimilation demonstrates that discrepancies between the reference simulation and the model forecast are mitigated after introducing the combined method, with more than 70 % of the predictions within a factor of two of the measurements. The errors in wind predictions in the FASDAS influenced the dispersion calculations, and the implementation of wind data assimilation in conjunction with the FASDAS has an indirect effect on further alleviating pollutant transport modeling errors.

Assessment of AERMOD modeling system for application in complex terrain in Pakistan

Atmospheric dispersion models based on Gaussian plume formulation are widely used for regulatory purposes in flat terrain. In this paper, the application of an advanced Gaussian plume modeling system, AERMOD, has been investigated over complex terrain setting through a field tracer test conducted in April 2018 near Islamabad, Pakistan. The model was validated through short term (2 h) release from a point elevated non buoyant source of SF6. The hourly averaged concentrations were measured at 47 discrete sampling points. The mesoscale meteorological model, WRF was coupled with AERMOD to provide hourly surface and upper boundary layer meteorological parameters. The statistical evaluation of model was carried out using Fractional Bias (FB) and Normalized Mean Square Error (NMSE). The quantile-quantile (Q-Q) plot was used to assess model's ability to follow the observed concentration distribution. For this field tracer test the model over-predicted ground level concentrations at the receptors close to the source and underestimated at the receptors located in a valley and far away from the source. Moreover, AERMOD overestimated the concentration at receptors which were at the point of direct impaction of plume and ridge. Overall, the model under-predicted the ground level concentration within a factor of two (FB = 0.63) for this field tracer test. It was found that the model better simulated the higher concentrations which are of primary interest for regulatory purposes.

Application of Tropospheric Sulfate Aerosol Emissions to Mitigate Meteorological Phenomena with Extremely High Daily Temperatures

Abstract This research examined whether tropospheric sulfate ion aerosols (SO4 2−) might be applied at a regional scale to mitigate meteorological phenomena with extremely high daily temperatures. The specific objectives of this work were: 1) to model the behaviour of SO4 2−aerosols in the troposphere and their influence on surface temperature and incident solar radiation, at a regional scale, using an appropriate online coupled mesoscale meteorology and chemistry model; 2) to determine the main engineering design parameters using tropospheric SO4 2−aerosols in order to artificially reduce the temperature and incoming radiation at surface during events of extremely high daily temperatures, and 3) to evaluate a preliminary technical proposal for the injection of regionally engineered tropospheric SO4 2−aerosols based on the integral anti-hail system of the Province of Mendoza. In order to accomplish these objectives, we used the Weather Research &amp; Forecasting Model coupled with Chemistry (WRF/Chem) to model and evaluate the behaviour of tropospheric SO4 2−over the Province of Mendoza (Argentina) (PMA) on a clear sky day during a heat wave event occurred in January 2012. In addition, using WRF/Chem, we evaluated the potential reductions on surface temperature and incident shortwave radiation around the metropolitan area of Great Mendoza, PMA, based on an artificially designed aerosol layer and on observed meteorological parameters. The results demonstrated the ability of WRF/Chem to represent the behaviour of tropospheric SO4 2− aerosols at a regional scale and suggested that the inclusion of these aerosols in the atmosphere causes changes in the surface energy balance and, therefore, in the surface temperature and the regional atmospheric circulation. However, it became evident that, given the high rate of injection and the large amount of mass required for its practical implementation by means of the technology currently used by the anti-hail program, it is inefficient and energetically costly.

Investigating sources of variability and error in simulations of carbon dioxide in an urban region

As cities embark upon greenhouse gas (GHG) mitigation efforts, there is an increasing need for accurate quantification of urban emissions. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric carbon dioxide (CO2) from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations).

Multi-scale modeling of the urban meteorology: Integration of a new canopy model in the WRF model

Urban parametrizations have been recently developed and integrated in mesoscale meteorological models for a better reproduction of urban heat islands and to compute building energy consumption. The objective of the present study is to evaluate the value of the use of a module able to produce highly resolved vertical profiles of these variables. For this purpose, the Canopy Interface Model (CIM) was integrated as an additional urban physics option in the Weather Research and Forecasting model. The coupling method is here detailed and its evaluation is done using a reference run based on a fine resolution WRF simulation. In order to keep both the CIM and the mesoscale model coherent, an additional term is added to the calculation of the CIM. Finally, the BUBBLE dataset is used to validate the simulation of the profiles from CIM. It is demonstrated that the proposed coupling improves the simulations of the variables in an urban grid and that the WRF + CIM + BEP-BEM system can provide highly resolved vertical profiles while at the same time improving significantly computational time. The data from these preliminary results are very promising as it provides the foundation for the CIM to act as an interface between mesoscale and microscale models.

Modeling Study of a Summertime Rainstorm Process Over North China Plain with a Meso-scale Meteorological Model

Using meso-scale meteorological model FDDA, this study presented a high-definition modeling of a rainstorm process during July 19-21, 2016 in the North China Plain. The meso-scale meteorological model captured the precipitation distribution of the observed rainstorm over North China Plain, showing that the FDDA model has strong ability to simulate and forecast precipitation. The modeling study also revealed the mechanism of rainfall formation with 3-dimensional structures of atmospheric circulation. The subtropical high pressure peripheral warm and wet air flow and the coexistence of cold shear affect the development of convection in the rainfall area. Due to the vapor transport of low-level jet stream, the rainfall area has sufficient water vapor supply. A convergence of the south-easterly and northerly airstreams triggered a strong convection for the summer rainstorm in North China Plain. The study provided us the valuable information for further development of a high-definition modeling of rainstorm process.

High-definition Modeling of a Springtime Gale Event in Tarim Basin, Northwest China

Tarim Basin in Northwest China is one of the areas with frequent gale. This study investigated a gale event in the Tarim Basin during April 26 - 28, 2015. The gale winds were reproduced by the meso-scale meteorological model. The study revealed the synoptic mechanism of gale process. A well-developed trough in the mid-troposphere crossed eastwards over Northwest China. Accompanied with cold air invasion into the Tarim Basin, strong winds were caused by the strong pressure gradient during the process of this event and the unique basin terrain forcing the wind speed increased sharply for the gale event.

Fine Resolution Simulation of a Cold Vortex in Northeast China by Using a Meso-Scale Meteorological Model

In this paper, a cold vortex of June 16-19, 2016 was simulated with fine resolution model (Climate-FDDA) to investigate the mechanism of precipitation and strong wind induced by a cold vortex in the Northeast Plain. The cold vortex process was reasonably captured by the fine resolution simulation. Due to the severe cyclonic circulation caused by the cold vortex process, water vapor was transported to the Northeast China Plain, providing a wealth of water vapor conditions. As the cold vortex is a deep convective synoptic system, unstable stratification and vigorous mixing action in the vertical direction could promote the occurrence of precipitation events over the region of northeast China. The cold vortex also lead the strong winds in the plain. During this case, the maximum surface wind speed reached 18m/s, which could be beneficial to the utilization of wind energy.

A comparison study of the application of data assimilation in the short-term prediction of radiation and precipitation

Based on the meteorological observation of the DG plants in East China, the assimilation effect of the WRF in the summer of 2016 was studied. The results show that, in the case of using data assimilation, the model correctly predicted the occurrence time of precipitation, as well as the variation of the precipitation along with the time were well consistent with the observations, which gives more accurate downward shortwave radiation. The application of data assimilation techniques can provide reliable information to adapt to the high resolution of meso-scale meteorological model. Therefore, it provides the necessary technical support for the development of the distributed power generation.

Design Wind Speed Evaluation Technique in Wind Turbine Installation Point by Using the Meteorological and CFD Models

It is highly important in Japan to choose a good site for wind turbines, because the spatial distribution of wind speed is quite complicated over steep complex terrain. We have been developing the unsteady numerical model called the RIAM-COMPACT (Research Institute for Applied Mechanics, Kyushu University, Computational Prediction of Airflow over Complex Terrain). The RIAM-COMPACT is based on the LES (Large-Eddy Simulation). The object domain of the RIAM-COMPACT is from several m to several km, and can predict the airflow and gas diffusion over complex terrain with high precision. In the present paper, the design wind speed evaluation technique in wind turbine installation point by using the mesoscale meteorological model and RIAM-COMPACT CFD model was proposed. The design wind speed to be used for designing WTGs can be calculated by multiplying the ratio of the mean wind speed at the hub-height to the mean upper-air wind speed at the inflow boundary, i.e., the fractional increase of the mean hub-height wind speed, by the reduction ratio, R. The fractional increase of the mean hub-height wind speed was evaluated using the CFD simulation results. This method was proposed as Approach 1 in the present paper. A value of 61.9 m/s was obtained for the final design wind speed, Uh, in Approach 1. In the evaluation procedure of the design wind speed in Approach 2, neither the above-mentioned reduction rate, R, nor an upper-air wind speed of 1.7 Vo, where Vo is the reference wind speed, was used. Instead, the value of the maximum wind speed which was obtained from the typhoon simulation for each of the investigated wind directions was adopted. When the design wind speed was evaluated using the 50-year recurrence value, the design wind speed was 48.3 m/s. When a somewhat conservative safety factor was applied, that is, when the 100 year recurrence value was used instead, the design wind speed was 52.9 m/s.

Computational Investigation of the Causes of Wind Turbine Blade Damage at Japan’s Wind Farm in Complex Terrain

During the passage of Typhoon 0918 (Melor) over southern Honshu in Japan on 7 and 8 October 2009, strong winds with extremely high turbulence fluctuations were observed over Shirataki Mountain and the surrounding mountains in Shimonoseki, Yamaguchi Prefecture, Japan. These strong winds caused damage to wind turbine blades at the Shiratakiyama Wind Farm owned by Kinden Corporation. In order to investigate the causes of the blade damage, the airflow characteristics from the time of the incidences are first simulated in detail with the combined use of the WRF-ARW mesoscale meteorological model and the RIAM-COMPACT LES turbulence model (CFD model). Subsequently, in order to evaluate the wind pressure acting on the wind turbine blades, an airflow analysis is separately performed for the vicinity of the blades with the RANS turbulence model. Finally, the stress on the blades is investigated using the FEM with the RANS analysis results as the boundary conditions.

Calculation of precipitation during period of catastrophic flood 21-27 july 2008 in Ukrainian Carpathians

Intense precipitation event happened in Ukraine on 21-27 July 2008 leading to extreme flash floods in the Ukrainian Carpathians which are characterized by the return period of approximately 50 years. Besides favourable synoptic conditions leading to quasi-stationary low situated over Balkans and South-West part of Ukraine precipitation during this event was intensified by mountains. This lead to formation of the specific precipitation patterns in the Ukrainian Carpathians which was not adequately resolved by the existing measurement network.&#x0D; The purpose of this publication is application of the mesoscale meteorological model WRF with high resolution (1 km) for reconstruction of precipitation during flood in July, 2008 in the Ukrainian Carpathians and evaluation of the simulated results against measurements.&#x0D; Calculation of precipitation during the period of catastrophic summer flood in 2008 at the territory of Ukrainian Carpathians had been carried out with the use of meteorological model WRF. The precipitation field was well simulated for the period of maximum floods (July, 25-th) as compared to precipitation data measured at meteorological stations. However the second and lower peak of precipitation which happened during July, 27-th was underestimated by WRF. The reason of such underestimation is possibly the influence of boundary conditions on simulated results. The precipitation field formed during July, 25-th is elongated along the main ridge of the Ukrainian Carpathians and precipitation maximums on that date, reaching up to 70 mm/3 hours are situated above foothills of the Carpathians. On July, 27-th the precipitation maximums are shifted south-eastward, close to the boundary of the computational domain. The vertical crossections of the calculated meteorological fields demonstrate characteristic system of gravitational waves occurring in flow above mountains and sequence of convective cells situated mostly above the windward (north-eastern) hills and coinciding with the precipitation maximums. The depth of some of the convective cells reaches 10 km, which is supported by satellite data. The indirect evaluation of the calculated precipitation field is performed using the measured water discharge data at the watersheds of the rivers in Carpathians. For the period of maximum flood the relative precipitation amount at each watershed (over total precipitation amount at all water-sheds) appears to be approximately equal to relative water discharge of the corresponding watershed.&#x0D; In conclusion we could state that the precipitation field was well simulated by WRF for the period of maximum floods (25 July). High quality of simulated results is supported by comparison of the calculated and measured precipitation as well as with indirect juxtaposition of the calculated integral precipitation at the watersheds of Carpathian rivers and water discharges in the corresponding river outlets. The calculated results demonstratre that existing measurement network is too sparse to capture the details of the orographically enhanced precipitation field. The scarcity of the measurement network makes it difficult to evaluate integral and maximum characteristics of precipitation happening in the Ukrainian Carpathians.&#x0D; Directions for further research should include usage of the coupled mesoscale meteorological-distributed hydrological model chain for calculation and forecasting of meteorological and hydrological characteristics of floods.

Sensitivity analysis of physical parameterizations in WRF for urban climate simulations and heat island mitigation in Montreal

In mesoscale meteorological modeling, physical models (radiation, planetary boundary layer, microphysics, cumulus, and land-surface) are employed to calculate terms of governing equations. We evaluate the sensitivity of near surface air temperature, wind speed, relative humidity and precipitation to different physical models within Weather Research and Forecasting (WRFV3.6.1) model for urban climate simulations and heat island mitigation for Montreal, Canada for period 09–11 Aug-2009. A multi-layer urban canopy model is used to consider the turbulence between buildings in urban areas. The model ensemble with the least error is proposed as an appropriate platform for urban climate simulations to study Urban Heat Island (UHI) mitigation strategies. Increasing surface reflectivity was applied to mitigate the UHI intensity over the domain. The albedo of roofs, walls, and roads increased from 0.2 to 0.65, 0.6, and 0.45, respectively. The results of surface modification are presented. The averaged 2-m air temperature indicates a decrease by 0.2°C. The 10-m wind speed is slightly increased over the domain. The relative humidity decreases as an average of 2.8% and the average precipitation reduced by 0.2mm. An increase of albedo leads to a net decrease of radiative flux into the ground and therefore a decrease of convective cloud formation and precipitation.

A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

Abstract. A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology–hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph.