Numerical Meteorological Model Research Articles

ZPD Retrieval Performances of the First Operational Ship-Based Network of GNSS Receivers over the North-West Mediterranean Sea.

This work presents the design and implementation of an operational infrastructure for the monitoring of atmospheric parameters at sea through GNSS meteorology sensors installed on liners operating in the north-west Mediterranean Sea. A measurement system, capable of operationally and continuously providing the values of surface parameters, is implemented together with software procedures based on a float-PPP approach for estimating zenith path delay (ZPD) values. The values continuously registered over a three year period (2020-2022) from this infrastructure are compared with the data from a numerical meteorological reanalysis model (MERRA-2). The results clearly prove the ability of the system to estimate the ZPD from ship-based GNSS-meteo equipment, with the accuracy evaluated in terms of correlation and root mean square error reaching values between 0.94 and 0.65 and between 18.4 and 42.9 mm, these extreme values being from the best and worst performing installations, respectively. This offers a new perspective on the operational exploitation of GNSS signals over sea areas in climate and operational meteorological applications.

Refined Simulation of Strong Convective Winds in Jiangsu and Its Application to Tower Level Disaster Prevention and Forecast of Power Grid

Severe convective gale is one of the main factors affecting power grid security. In order to improve the accuracy of the meteorological numerical model for predicting that and provide a reliable basis for decision-making of disaster prevention, we use CALMET dynamic downscaling technology based on WRF model to simulate the regional wind field in Jiangsu, and diagnose the terrain dynamics, slope flow, terrain blocking effect of the wind module. Linear interpolation and the time downscaling of the spline function method are used to construct the WRF-CALMET coupling model, and the 1km resolution simulation of a strong convective gale weather with different scales, namely, the typhoon "Madum" and the tornado in Yancheng, which affect the power grid security in Jiangsu Province, is realized. The simulation results show that the combination of CALMET downscaling technology and WRF model well simulate the 1km wind field under the background of strong convective weather in Jiangsu Province, and the accuracy of transmission line towers covered by a single grid point increases by 10 times. Compared to traditional meteorological forecasting models, this method has more accurate characterization of gale disasters on small-scale and mesoscale, and meet the needs of the power grid for fine prediction of catastrophic weather.

Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility

The feasibility, safety, and efficiency of a drone mission in an urban environment are heavily influenced by atmospheric conditions. However, numerical meteorological models cannot cope with fine-grained grids capturing urban geometries; they are typically tuned for best resolutions ranging from 1 to 10 km. To enable urban air mobility, new now-casting techniques are being developed based on different techniques, such as data assimilation, variational analysis, machine-learning algorithms, and time series analysis. Most of these methods require generating an urban wind field database using CFD codes coupled with the mesoscale models. The quality and accuracy of that database determines the accuracy of the now-casting techniques. This review describes the latest advances in CFD simulations applied to urban wind and the alternatives that exist for the coupling with the mesoscale model. First, the distinct turbulence models are introduced, analyzing their advantages and limitations. Secondly, a study of the meshing is introduced, exploring how it has to be adapted to the characteristics of the urban environment. Then, the several alternatives for the definition of the boundary conditions and the interpolation methods for the initial conditions are described. As a key step, the available order reduction methods applicable to the models are presented, so the size and operability of the wind database can be reduced as much as possible. Finally, the data assimilation techniques and the model validation are presented.

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.

A convolutional recurrent neural network for strong convective rainfall nowcasting using weather radar data in Southeastern Brazil

Strong convective systems and the associated heavy rainfall events can trig-ger floods and landslides with severe detrimental consequences. These events have a high spatio-temporal variability, being difficult to predict by standard meteorological numerical models. This work proposes the M5Images method for performing the very short-term prediction (nowcasting) of heavy convective rainfall using weather radar data by means of a convolutional recurrent neural network. The recurrent part of it is a Long Short-Term Memory (LSTM) neural network. Prediction tests were performed for the city and surroundings of Campinas, located in the Southeastern Brazil. The convolutional recurrent neural network was trained using time series of rainfall rate images derived from weather radar data for a selected set of heavy rainfall events. The attained pre-diction performance was better than that given by the persistence forecasting method for different prediction times.

Numerical Simulation of Storm Waves during Typhoon Maysak and Haishen in the Korean Peninsula

In this study, we simulated storm waves induced by typhoon Maysak and Haishen in the Korean peninsula by using the third-generation numerical wave model SWAN(Simulating WAves Nearshore). We used the sea-surface wind data of KMA(Korea Meteorological Agency)’s operational meteorological model RDAPS(Regional Data Assimilation Prediction System), and JMA(Japan Meteorological Agency)’s weather forecast model JMA-MSM(Meso-Scale Model) as input forcing of the numerical wave model. In addition, the wind field of the tropical cyclone was established with JTWC(Joint Typhoon Warning Center)’s best track data for the storm wave simulation. We used two different source term options, which consider other physics of energy generation by wind and dissipation by whitecapping. Validation of the simulation result was conducted over statistical analysis with the observation data from KMA and KHOA(Korea Hydrographic and Oceanographic Agency)’s buoys. As a result, the whole scenario tended to overestimate significant wave height. The simulation result by using RDAPS as input forcing outperformed the result by using JMA-MSM. It denoted that the performance of a wave model depends on the accuracy of input forcing wind. The wind field by JTWC’s best track data was not suitable compared with the meteorological numerical model. ST6 simulated the wave height higher than Komen’s source term. However, Komen's source term simulated storm waves better than ST6 in this study, and further researches under various conditions are required to evaluate ST6 for the storm waves simulation. In the simulation of wave period parameters, it was hard to estimate the accuracy of the model, and other approaches are necessary for the evaluation.

Określenie zasobów energii wiatru w Polsce z wykorzystaniem rezultatów numerycznych modeli meteorologicznych = Determination of wind-energy resources in Poland using the results of numerical meteorological models

The article presents a comparison of the results of calculations of wind energy resources based on measurements at meteorological stations and on the basis of the results of the COSMO meteorological model in three basic resolutions in the period of 2011-2019. The aim of the study was to compare the results of calculations of wind energy resources obtained on the basis of measurements at meteorological stations and on the basis of analyzes resulting from the work of meteorological numerical models, operating at various spatial scales. It was found that the use of archived results of analyzes of meteorological models, especially those in high resolution, allows for such an assessment in a climatological sense in the same way as the results of measurements at meteorological stations used for this purpose. For investment purposes, calculations of wind energy resources at higher altitudes were also carried out, so that the results could also be applied to high wind turbines – those of higher power.

Middle-Atmosphere Temperature Monitoring Addressed with a Constellation of CubeSats Dedicated to Climate Issues

AbstractWhile meteorological numerical models extend upward to the mesopause, mesospheric observations are required for leading simulations and numerical weather forecasts and climate projections. This work reviews some of the challenges about temperature observation requirements and the limiting factors of the actual measurements associated with atmospheric tides. A new strategy is described here using a limb-scattering technique that is based on previous experiments in space. Such observations can be used with cube satellites. Technical issues are the large dynamic range (4 orders of magnitude) required for the measurements, the accuracy of the limb pointing, and the level of stray light. The technique described here will expect accuracy of 1–2 K with a vertical resolution of 1–2 km. A constellation of 100 platforms could provide temperature observations with space (100 km) and time (3 h) resolutions recommended by the World Meteorological Organization, and tidal issues could be resolved with a minimum of 3–5 platforms with specific orbit maintained to avoid drifts.

Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm

With the large-scale development of wind energy, wind power forecasting plays a key role in power dispatching in the electric power grid, as well as in the operation and maintenance of wind farms. The most important technology for wind power forecasting is forecasting wind speed. The current mainstream methods for wind speed forecasting involve the combination of mesoscale numerical meteorological models with a post-processing system. Our work uses the WRF model to obtain the numerical weather forecast and the gradient boosting decision tree (GBDT) algorithm to improve the near-surface wind speed post-processing results of the numerical weather model. We calculate the feature importance of GBDT in order to find out which feature most affects the post-processing wind speed results. The results show that, after using about 300 features at different height and pressure layers, the GBDT algorithm can output more accurate wind speed forecasts than the original WRF results and other post-processing models like decision tree regression (DTR) and multi-layer perceptron regression (MLPR). Using GBDT, the root mean square error (RMSE) of wind speed can be reduced from 2.7–3.5 m/s in the original WRF result by 1–1.5 m/s, which is better than DTR and MLPR. While the index of agreement (IA) can be improved by 0.10–0.20, correlation coefficient be improved by 0.10–0.18, Nash–Sutcliffe efficiency coefficient (NSE) be improved by −0.06–0.6. It also can be found that the feature which most affects the GBDT results is the near-surface wind speed. Other variables, such as forecast month, forecast time, and temperature, also affect the GBDT results.

Опыт определения площади городской застройки по космическим снимкам для задач метеорологического моделирования (на примере Москвы)

Detailed weather and climate modeling for urban areas is in demand in various scientific and applied tasks, starting from a numerical weather forecast and ending with an assessment of the bioclimatic conditions of the city and long-term urban planning. The application of modern meteorological models for urban areas requires the determination of a set of parameters characterizing the urban environment and urban canopy features. One of these parameters is the area fraction, occupied by buildings. In this paper, we propose a universal method for determining building area fraction based on the interpretation of high-resolution satellite images from the Sentinel-2 satellites. The methodology was tested on the example of the territory of the city of Moscow, characterized by a variety of forms of urban development. The calculation of the building area fraction was performed for the cells of the computational grid of the COSMO mesoscale numerical meteorological model with 1 km spacing. To verify the developed method, we used an alternative estimate of the building area fraction based on the crowdsourcing cartographic data OpenStreetMap. The data on the building area fraction derived from the satellite images and from OpenStreetMap data have shown a good mutual agreement, which confirms the promise of using the proposed methodology. On the example of territories where the two methods show significant differences, their typical causes are identified, namely the lack of information about buildings in the OpenStreetMap database, or the masking of buildings by trees, which does not allow them to be revealed from satellite images.

Online Nuclear Emergency Response System (ONERS) for consequence assessment and decision support in the early phase of nuclear accidents - Simulations for postulated events and methodology validation

Online Nuclear Emergency Response System (ONERS) is a comprehensive Decision Support System developed using Open source WebGIS (Geographical Information System) technologies for management of Off-Site Nuclear Emergencies for Nuclear Power Plant sites of India. The system is based on numerical meteorological and dispersion models, weather data and source term estimation using environmental radiation monitors. It simulates the pattern of atmospheric dispersion, concentration, radioactivity fallout, and radiation dose profiles in various pathways around the affected site. The system projects the current and future radiological scenario along with geographical and demographic information and simulates the consequences of atmospheric releases on population by spatial analysis. It also computes counter measures using national regulatory guidelines for suggestion of protective actions to decision makers and first responders. This work presents the salient features of the ONERS, its monitoring network and utility. The methodology of dose projections is tested by performing simulations for a postulated accident and the effectiveness of the system for decision making during emergency scenarios is illustrated for a hypothetical scenario.

The eastern-Iran wind-resource assessment through a planetary boundary layer simulation (2011–2015)

Currently, in order to reduce the time and cost of wind measurement masts installation, numerical meteorological models are being utilized to simulate the regional wind climate. In this study, the Weather Research and Forecasting model was applied to assess the wind power potential in the East of Iran. After evaluating the model, the wind mean speed and the power map were prepared based on a 5-year simulation (2011–2015). The results indicated that there were high wind-energy-potential areas bordering Iran and Afghanistan. The model illuminated that Khaf city had a satisfactory wind potential, reasonably corresponding with the observations. The model error was greater for the low wind speeds. With regard to the wind resource map of the area, only 3% of the study area falls within class 3 or higher, and therefore, can be considered conformative to the wind power generation.

Estimation of thermal comfort felt by human exposed to extreme heat wave in a complex urban area using a WRF-MENEX model.

Thermal comfort could indicate human thermal sensation when exposed to a local meteorological condition. Because humans can suffer illness when exposed to heat or even die, it is essential to assess human comfort levels to increased temperature and to provide this information to the public. This study aims to estimate thermal comfort using the human heat balance model combined with a numerical meteorological model in Seoul mega city during the heat wave periods experienced during 2016. The gridded thermal comfort index of physiological subjective temperature (PST) was calculated based on the Man-Environment Heat Exchange (MENEX) model, which used as inputs the meteorological parameters, clothing insulations, and metabolic rates. High-resolution meteorological parameters were obtained by coupling Weather Research and Forecasting (WRF) model with Building Effect Parameterization (BEP) + Building Energy Model (BEM) using detailed urban classification. The modeling results showed that the PST distribution has a clearly heterogeneous spatial distribution during the heat wave period. The high PST values were largely found in the residential area during the day, due to the high temperature and low wind speed associated with high-density buildings, and the daily maximum PST reached a very hot level (44.1-54.0°C). Our study suggested that the human heat balance model combined with the numerical meteorological model could be used to provide more reliable information about thermal comfort to groups that may be vulnerable to the effects of heat waves in complex urban environments.

Improving Cloud Simulation for Air Quality Studies through Assimilation of Geostationary Satellite Observations in Retrospective Meteorological Modeling

Abstract Development of clouds in space and time within numerical meteorological models as observed in nature is essential for producing an accurate representation of the physical atmosphere for input into air quality models. In this study, a new technique was developed to assimilate Geostationary Operational Environmental Satellite (GOES)-derived cloud fields into the Weather Research and Forecasting (WRF) meteorological model to improve the placement of clouds in space and time within the model. The simulations were performed on 36-, 12-, and 4-km grid-size domains covering the contiguous United States, the south-southeastern United States, and eastern Texas, respectively. The technique was tested over the month of August 2006. The results indicate that the assimilation technique significantly improves the agreement between the model-predicted and GOES-derived cloud fields. The daily average percentage increase in the cloud agreement was determined to be 14.02%, 11.29%, and 4.96% for the 36-, 12-, and 4-km domains, respectively. This was accomplished without degrading the model performance with respect to surface wind speed, temperature, and mixing ratio, which are important parameters for air quality applications; in some cases these variables were even slightly improved. The assimilation technique also produced improvements in the model-predicted precipitation and predicted downwelling shortwave radiation reaching the surface.

Code optimization by using GPU applied to a Dataflow numerical simulation model

This work aims to study techniques for parallel computing using GPU (Graphics Processing Unit) in order to optimize the performance of a fragment of computational code, implemented as a Dataflow system, which is part of a meteorological numerical model responsible for calculating the advection transportation phenomena. The possible algorithm limitations for GPU efficiency will also be addressed through an extensive code instrumentation. Considering the difficulties found on the original algorithm which implies a GPU accelerated code dealing with flow dependencies and coarse grain parallelism, the performance gain with GPU may be considered fair.

Wind speed forecast correction models using polynomial neural networks

Accurate short-term wind speed forecasting is important for the planning of a renewable energy power generation and utilization, especially in grid systems. In meteorology it is usual to improve the forecasts by means of some post-processing methods using local measurements and weather prediction model outputs. Neural networks, trained with local real data observations can improve short-term wind speed forecasts with respect to meso-scale numerical meteorological model outcomes of the same data types in the majority of cases. Large-scale forecast models are based on the numerical integration of differential equation systems, which can describe atmospheric circulation processes on account of global meteorological observations. Several layer 3D complex models, which involve a large number of matrix variables, cannot exactly describe conditions near the ground, highly influenced by a landscape relief, coast, structure and other factors. Polynomial neural networks can form and solve general differential equations, which allow to model real complex systems by means of substitution derivative term sum series. The proposed adaptive method forms a correction function according to real observations and consequently applies forecasts to revise a desired prognosis in a selected locality.

Study on the future weather data considering the global and local climate change for building energy simulation

Energy simulations are often used to evaluate the indoor thermal environment and energy consumption of buildings. In such simulations, it is common to use regional weather data that are typically based on current or past weather conditions. However, most buildings have a lifespan of several decades, during which climate can change gradually. Therefore, the design of energy conservation systems and energy simulations should incorporate climate change predictions to ensure that buildings are adaptable to future climatic conditions.The present study aims to construct future (i.e., 2030s) standard weather data for use in architectural design using numerical meteorological models. For this purpose, we adopted a dynamical downscaling method, used global climate model (GCM) data as the initial and boundary conditions for input into a regional climate model (RCM), and physically downscaled the data using the RCM.We constructed a prototype of the future (i.e., 2031–2035) standard weather data based on version 4 of the Model for Interdisciplinary Research on Climate (MIROC) and the Weather Research and Forecasting (WRF) model. The results confirm that the weather data generated via the dynamical downscaling method can predict local climate. Subsequently, we simulated building thermal load consumption using regional climate data. By comparing the results for the present (2007) and future (2034), we estimated the impact of climate change on the energy performance of a detached house. In particular, the sensible heat load for the house was predicted to increase by 15% under the conditions considered.

Influence of orography on precipitation amount and distribution in NW Greece; A case study

In this work the impact of topography on the distribution and the amount of precipitation in Epirus, NW Greece is investigated, during the cold period of the year. A precipitation event with typical wintertime characteristics is considered. In the selected case, extended and heavy precipitation over Epirus is caused by a low pressure system centred northwest of Epirus and moving southeastwards, generating southerly winds over the Ionian Sea. The case is simulated by applying the numerical meteorological model MM5 in a high resolution grid (2×2km). Various sensitivity tests are performed, searching for the model initialization time and the convective parameterization scheme (CPS) leading to the best simulation of the observed event. Then, the model is applied again incorporating modified data of topography, in order to study the differentiations in the fields of the most important meteorological parameters, which are directly related with precipitation. The topography is modified with two ways: either by reducing the height of the mountains (type RT) or by elevating the terrain height (type ET). The results show that in the RT type, the precipitation field appears more homogeneous, with weaker maxima on the windward sides and above the mountain ridges. As a consequence, less rain falls in these areas and humid air passes easier to the lee sides reducing rain shadows. In the ET type, rain increases in the windward coastal zone of Epirus while it is reduced in the inland areas where less humid air is available. Generally, the modification of topography changes the flows near the surface, causing a displacement of the convergence zones and thus a new distribution of vertical velocities, which, combined with the new water vapour field, has a direct impact on precipitation.

福岡都市圏におけるヒートアイランド強度の変動特性

The influences of meteorological factors on the variability of heat-island structure in the Fukuoka metropolitan area are investigated on the basis of observation data and numerical simulation by using a meteorological numerical model, i.e., Weather Research and Forecasting (WRF). The present results show spatial patterns of the heat island to be controlled by local wind systems. The heat-island intensity varies temporally depending on the formations of sea and land breezes, whereas the variation becomes relatively small under background wind dominated condition. The heat-island intensity takes a maximum value in nighttime and the value depends on the amount of the global solar radiation in daytime.

Analysis for Influence upon Local Climate Factors of Reservoir Area of Hydropower Station after Water Storage

An artificial reservoir will be formed at the dam upstream in a large hydropower station after the station put into use, and with water area expanding, the local climate will change. This paper takes mesoscale meteorological numerical model WRF to simulate a certain hydropower station in Sichuan to obtain the impacting situation of the local climate after the water storage. The result indicates as follows: firstly, the wind field has been greatest changed after the water storage. Except in the winter, we can found obvious lake-land breeze in the spring and the summer and the flow field is very evident; secondly, the temperature is rising or falling; except for a little change in the spring, the average temperature falls 1.27°C in the summer but rises at 1.28°C in the winter. In addition, the humidity around the reservoir is changed distinctly; the average humid degree rises mostly at 4.56% in the winter, moderately at 2.25% in the spring but a little change at 0.94% in the summer. It is since the climate factors have been changed that the concentration field of atmospheric pollutants which generated by the industrial and mining enterprises around the reservoir has been changed at all.