Wind Map Research Articles

A new airborne system for simultaneous high-resolution ocean vector current and wind mapping: first demonstration of the SeaSTAR mission concept in the macrotidal Iroise Sea

Abstract. Coastal seas, shelf seas and marginal ice zones are dominated by small-scale ocean surface dynamic processes that play a vital role in the transport and exchange of climate-relevant properties such as carbon, heat, water and nutrients between land, ocean, ice and atmosphere. Mounting evidence indicates that ocean scales below 10 km have far-ranging impacts on air–sea interactions, lateral ocean dispersion, vertical stratification, ocean carbon cycling and marine productivity – governing exchanges across key interfaces of the Earth system, the global ocean, and atmosphere circulation and climate. Yet, these processes remain poorly observed at the fine spatial and temporal scales necessary to resolve them. The Ocean Surface Current Airborne Radar (OSCAR) is a new airborne instrument with the capacity to inform these questions by mapping vectorial fields of total ocean surface currents and winds at high resolution over a wide swath. Developed for the European Space Agency (ESA), OSCAR is the airborne demonstrator of the satellite mission concept SeaSTAR, which aims to map total surface current and ocean wind vectors with unprecedented accuracy, spatial resolution and temporal revisit across all coastal seas, shelf seas and marginal ice zones. Like SeaSTAR, OSCAR is an active microwave synthetic aperture radar along-track interferometer (SAR-ATI) with optimal three-azimuth sensing enabled by unique highly squinted beams. In May 2022, OSCAR was flown over the Iroise Sea, France, in its first scientific campaign as part of the ESA-funded SEASTARex project. The campaign successfully demonstrated the capabilities of OSCAR to produce high-resolution 2D images of total surface current vectors and near-surface ocean vector winds, simultaneously, in a highly dynamic, macrotidal coastal environment. OSCAR current and wind vectors show excellent agreement with ground-based X-band-radar-derived surface currents, numerical model outputs and NovaSAR-1 satellite SAR imagery, with root mean square differences from the X-band radar better than 0.2 m s−1 for currents at 200 m resolution. These results are the first demonstration of simultaneous retrieval of total current and wind vectors from a high-squint three-look SAR-ATI instrument and the first geophysical validation of the OSCAR and SeaSTAR observing principle. OSCAR presents a remarkable new ocean observing capability to support the study of small-scale ocean dynamics and air–sea interactions across the Earth's coastal, shelf and polar seas.

Improving the wind map using interpolation approach: Case study of a southeastern region of Algeria

Various software programs like Wind Atlas Analysis and Application Program (WAsP) and WindSim use only a single data source, limiting the information generated to a small area, while it is more interesting to look for the contribution that can be added to the local speed generated at a certain distance. To improve accuracy of the prediction, refining wind maps with data from neighboring masts and using new interpolation methods is proposed in this paper. Thus, to make corrections to the local speed generated at a certain distance, we propose to refine the wind maps produced by numerical simulations of WAsP software, taking into account the data from neighboring masts and optimizing the results by new interpolation methods. This technique is applied to a region of southeastern Algeria, where the wind data were collected from three meteorological stations, namely of Biskra, Guemar, Sidi Mahdi, and three neighboring stations of Tunisia namely Gafsa, Kebili and Nefta. The results shown that depending on the characteristics and the surrounding environment of the measuring mast, the simulated wind speed can vary between 5% and 25%.

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

This study aims to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical scheme and to evaluate the model’s performance for wind energy assessment and mapping over the Iranian territory. In this initiative, five PBL and surface layer parameterization schemes were tested, and their performance was evaluated via comparison with observational wind data. The study used two-way nesting domains with spatial resolutions of 15 km and 5 km to represent atmospheric circulation patterns affecting the study area. Additionally, a seventeen-year simulation (2004–2020) was conducted, producing wind datasets for the entire Iranian territory. The accuracy of the WRF model was assessed by comparing its results with observations from multiple sites and with the high-resolution Global Wind Atlas. Statistical parameters and wind power density were calculated from the simulated data and compared with observations to evaluate wind energy potential at specific sites. The model’s performance was sensitive to the horizontal resolution of the terrain data, with weaker simulations for wind speeds below 3 m/s and above 10 m/s. The results confirm that the WRF model provides reliable wind speed data for realistic wind energy assessment studies in Iran. The model-generated wind resource map identifies areas with high wind (wind speed > 5.6 m/s) potential that are currently without wind farms or Aeolic parks for exploitation of the wind energy potential. The Sistan Basin in eastern Iran was identified as the area with the highest wind power density, while areas west of the Zagros Mountains and in southwest Iran showed high aeolian potential during summer. A novelty of this research is the application of the WRF model in an area characterized by high topographical complexities and specific geographical features. The results provide practical solutions and valuable insights for industry stakeholders, facilitating informed decision making, reducing uncertainties, and promoting the effective utilization of wind energy resources in the region.

Wind Mapping of Malaysia Using Ward’s Clustering Method

Malaysian wind maps used in wind analysis and engineering design are dated back to the last 50 years of wind data. Cotemporally, the mean wind speed was used as the basic wind design and due to changes in the weather condition worldwide, wind monitoring assumption and structure design are jeopardized. Therefore, this study aims to map the wind based on the trend of the highest wind speed recorded. The wind speed was analyzed based on a trend basis. The study included 42 Malaysian Metrological Department weather stations and the annual wind speed was acquired based on the monthly highest wind speed (1990–2019). The data were then processed using the 95% confidence interval method to determine the mean of the month, and the annual wind trendline was obtained. The trendline was then clustered using Ward’s method with the assistance of the high-level programming language, PYTHON v3.11.6. The clustering analysis produced two clusters for the Malaysian Peninsula and two for Sabah and Sarawak. The recommendation is to use the highest wind speed recorded on the map as the design wind speed. The recommendation is expected to help experts to compensate for the uncertainties in wind speed during the design stage and avoid incidents in the field.

Leveraging national forestry data repositories to advocate wildfire modeling towards simulation-driven risk assessment

Modeling wildfire dynamics is complex and challenging due to the multiple scales involved in fire propagation, from physical–chemical processes to the interaction with topography and meteorological conditions. To provide reliable indicators of the risk of an ongoing wildfire, models aimed at informing policy-making should quantify the primary sources of uncertainty in their predictions. In this paper, we introduce a novel methodology built on top of Cellular Automata to assess the impact of uncertainty by implementing wildfire ensemble modeling using data from the Spanish National Forestry Data Repositories. Uncertainty is embedded in the model considering the ±2σ deviations from the medians of linear regressions of the canopy stratum with LiDAR metrics as explainable variables. The relevance of dynamic meteorological conditions in contrast to static environment conditions is analyzed. Our results suggest that an accurate account of the fuel model, including time-dependent wind and moisture maps, is mandatory to provide reliable predictions. Using a real case study (Concentaina’s extreme wildfire), we also illustrate the importance of assessing the impact of the firefighters’ mitigation efforts.

METOCEAN SPECIFICATIONS FOR WIND DATA BASE ON THE BLACK SEA

In this paper we present the steps to establish a design of floating wind turbine in offshore area. In order to be able to design a floating wind turbine in the offshore area of the Black Sea, data about the wind potential, the potential of waves and sea currents are needed, as well as wave-wind cross-data and other atmospheric data. It is assumed that the location of the floating turbine is the area of the Galata platform, Varna, Bulgaria, located at 25 km south-east of the city of Varna in the South-West Black Sea area. The wind dataset can downloaded from a server in NetCDF file form. The spatial data are used to generate wind maps showing the distribution of the mean wind speed for the full-time distribution (i.e. total time) and for the four seasons, respectively.

Harnessing of the low energy wind potential

This paper analyzes the wind energy parameters for different areas with low wind energy potential using the data from the global online wind map. The performance characteristics of different types of wind turbines are reviewed. The generated theoretical electric energy within one year for 9 types of wind turbines is presented. Suitable wind turbines for harnessing low wind potential, that can cover the electrical needs of one household are proposed.

ЭФФЕКТИВНОЕ ИСПОЛЬЗОВАНИЕ АЛЬТЕРНАТИВНОЙ ЭНЕРГИИ ДЛЯ ОСНАЩЕНИЯ ВОЙСКОВЫХ ЧАСТЕЙ И ОТДАЛЕННЫХ НАСЕЛЕННЫХ ПУНКТОВ

The energy that is obtained from nature: from wind, sun, water, etc., is by far the cheapest type of resource and environmentally friendly. As the wind map shows, Kazakhstan’s wind potential provides a direction to promote the use of renewable energy sources as an important means to solve the problems of electricity shortage. The scientific article was published as part of the implementation of the scientific project of grant funding for 2022...2024 IRN № АР148039/0222 «Scientific and technical substantiation of the parameters and development of a wind power plant for the electric power supply of the objects of the Armed Forces, other troops and military formations of the Republic of Kazakhstan» (the study is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan). The article is devoted to the study and use of wind turbines with different parameters depending on climatic conditions, such as wind speed, air density, air pressure, air temperature, etc. The result of the research will be widely used in the design and manufacture of wind turbines in remote settlements and military units.

Shadow is related to roughness but MODIS BRDF should not be used to estimate lateral cover

A simple geometric-optical model is used to show that shadow in optical remote sensing imagery contains information about surface roughness. The use of MODIS albedo products for the purpose of estimating surface roughness so that these products may aid in dust emission modeling has been proposed in previous studies (Chappell et al. 2010; Chappell and Webb 2016; Chappell et al. 2018). This approach is evaluated through geometric-optical modeling and by analysis of existing MODIS data. Little support is found for the utility of this approach for dust emission modeling. However, because there is clearly information about surface roughness in optical satellite imagery, some suggestions for the proper use of optical data to estimate surface roughness are made.Chappell, A., Van Pelt, S., Zobeck, T., & Dong, Z. (2010). Estimating aerodynamic resistance of rough surfaces using angular reflectance. Remote Sensing of Environment, 114, 1462–1470.Chappell, A., & Webb, N.P. (2016). Using albedo to reform wind erosion modeling, mapping and monitoring. Aeolian Research, 23, 63–78.Chappell, A., Webb, N.P., Guerschman, J.P., Thomas, D.T., Mata, G., Handcock, R.N., Leys, J.F., & Butler, H.J. (2018). Improving ground cover monitoring for wind erosion assessment using MODIS BRDF parameters. Remote Sensing of Environment, 204, 756–768.

The effect of different area uses and topography on surface temperature and climate parameters.

Global warming and the ecological burden it causes affect people and the environment negatively and make adaptation difficult. For people to adapt to the environment and vice versa, they need to do extensive research and planning. Planning, on the other hand, is taking an easy form with the technology that has recently developed. GIS infrastructures and supporting satellite images along with software help with provincial-scale planning. This study has been handled on a scale covering the provincial borders of Nevsehir. The thermal data of the 10-year-old Landsat 7 satellite was analyzed and mapped in the Arc-GIS 10.2 package program. In the same way, maps of wind, air temperature, topography, and land use were created and the relationship between them was revealed by "Spearman's correlation" method. According to the results obtained, the average surface temperature in the study area was determined as 34.4°C. When evaluated in terms of land use, natural grasslands have the highest surface temperature of 40.6°C, while city structures have the highest average surface temperature of 33.3°C. At the same time, the lowest surface temperature measured in the study area, 13.8°C, is also found in natural grassland areas. A significant positive correlation was measured between the wind speed and the land use pattern, while a significant negative correlation emerged between the wind speed and the air temperature. In addition, there is another significant negative correlation between height and land surface temperature (LST). Furthermore, a high degree of positive significance was determined between altitude and wind speed. Finally, between air temperature and LST, a positive significance was observed.

Accurate Wind Observation and Robust Control for Drones in the Field of Micro-meteorology⋆

Urban logistics has been the primary target for recent drone applications. However, these drones face varying weather conditions in their flight horizon that can limit their performance. From another perspective, this flight horizon is the focus of micro-meteorology data gathering for a city-wide accurate weather prediction system. Hence, these drones can carry out logistics while gathering micro-meteorology data. This paper focuses on the latter and aims to realize the drone capabilities required for forecasting micro-meteorology, especially observing highly accurate wind data and robust control capability against strong wind disturbances. The generation of wind maps using a 2D wind sensor mounted on a drone and wind gust estimation using a nonlinear disturbance observer (NDOB) are proposed as the capability for accurate wind observation. Next, the position and velocity control of the drone using super twisting sliding mode control (STSMC) and NDOB are designed for robust control. Lastly, numerical simulation and real-world experiments verify the effectiveness of the whole system proposed in this paper.

A climatology-based wind speed map for NBR 6123

abstract: Updating the basic wind speed map of NBR 6123 –-Wind loading on buildings – is one of the duties of the committee responsible for the revision of this code. Traditionally such maps are elaborated by means of extreme value wind speed data collected at meteorological stations, use of statistical methods for data characterization, and application of mathematical regression to elaborate the territorial maps. However, the spatial distribution of the atmospheric phenomena responsible for strong winds cannot be disregarded. This work presents a proposal for a new wind speed map for NBR 6123 combining a climatological approach and wind speed data recently compiled from hundreds of meteorological stations. A climatological wind map was first produced considering the phenomena which cause strong winds, and used as a basis to draw the isopleths of the basic wind speed map, considering the measured wind speed data. The resulting map shows basic wind speeds ranging from 30 to 48m/s.

Development of wind-solar maps in Aqaba, Jordan as potential sources for power generation

The potential for free, clean, and limitless energy from renewable sources has long been recognized. However, because of a lack of thorough wind and solar maps, expertise, and public understanding of the significance of these resources in the country, Jordan continues to rely on non-renewable sources for its energy needs. The main objective of this study is to analyze the potential of solar and wind energies as renewable resources for power generation. Weibull distribution function with two parameters and the Angstrom-Prescott model, respectively, are used in this study to offer estimates of the wind and solar energy in the coastal city of Jordan, Aqaba during a five-year period. According to the assessment of wind potential, the annual means of the shape and scale parameters at 10 m for the studied station varied between (1.65 to 1.73) and (4.42 to 4.86), respectively. During the dry season, the wind speed was seen to be stronger, while during the wet season, it was seen to be slower. The maximum power density is found to be in September with values of 622.81 W/m2 and 192.74 W/m2 for the elevations 80 m and 10 m, respectively. According to the forecast for solar potential in this area, the city's global solar radiation is promising for the production of solar energy. The maximum global solar radiation is found to be 8.3 KWh/m2 in June. Results also demonstrated that Aqaba city is suitable for wind and solar power generation.

Wind Energy Potential in Pakistan: A Feasibility Study in Sindh Province

The environment and the economy are negatively impacted by conventional energy sources, such as coal, gasoline, and other fossil fuels. Pakistan’s reliance on these resources has resulted in a catastrophic energy crisis. This has driven the government to make critical decisions such as early retail closures, power outages for the industrial sector, and an increase to two days a week vacations. Wind energy, accessible and affordable, will become a viable option for meeting Pakistan’s present and future energy demands. Approximately 3% of Pakistan’s land can produce nearly 132 GW of power with an installed capacity of 5 MW per km2. In this study, four zones (Karachi, Thatta, Badin, and Jamshoro) in Sindh province are assessed for the feasibility of wind energy generation. The installed capacity, generator types, and detailed specifications are provided for each zone. Moreover, the wind mapping of Pakistan is presented considering the four potential zones. The zones are analyzed using annual wind speed and power output considering wind data measured at 50 m height over one year. The higher mean speed is recorded at Jamshoro compared to other zones. The analysis indicates that all four sites are suitable for large-scale wind power generation due to their energy potential.

Urban Wind Field Mapping Technique for Municipal Environmental Planning: A Case Study of Cheongju-Si, Korea

The integrated management of land and environmental plans (EPs) has been a key direction of sustainable policy in Korea. Although local EPs should be established based on spatial data, much of the pertinent environmental information has not been mapped. Accordingly, we develop a wind field mapping technique for establishing local EPs. This method was developed via a numerical weather prediction model (Weather Research and Forecast—WRF), and a diagnostic meteorological model (California Meteorological model—CALMET), based on weather observation data, as well as terrain and land cover data. The developed method was applied to a case study in Cheongju-si, Korea, for verifying its effectiveness. The created wind field maps of Cheongju-si provided an intuitive visual representation of the spatial distribution of seasonal and daytime/nighttime wind patterns. Such data helped understand the directionality and patterns of winds blowing into a city, or identify stagnant areas of wind circulation. Overlaying the wind field map with maps of air pollutant emissions revealed that pollutants from industrial areas could flow along the prevailing winds into residential areas downtown. These maps also implied that open spaces, such as parks and grasslands, were recommendable for stagnant areas, instead of creating industrial complexes or residential areas.

Analysis of wind energy resources from high rise building for micro wind turbine: A review

Micro wind turbine is a technology that is used to generate electricity in urban areas. The purpose of this review paper is an analysis of micro wind turbines on high-rise buildings. High-rise buildings are used as towers for micro wind turbines. Here is an analysis of the wind map of India for installing wind turbines. With the help of wind maps, the behavior of wind at different heights has been studied. The result of this study is to analyze how much wind power is generated in different states of India. At present nine states of India, wind energy is produced for commercial use and connected to the grid. Tamil Nadu is the largest wind power producer state. The wind flow in nine states is very good for wind power generation. Micro wind turbines have also been installed in these states and wind power generation for domestic use yields good results.

Integrating the Spatial Autocorrelation Structure of Irregularly Distributed Wind Measurement Stations to Model Wind Patterns Using R

Wind behavior in Sri Lanka, mainly exposed to two major monsoon seasons, is complex to model spatially. The acute changes in the topography further make it difficult to map the wind patterns. Irregularly distributed wind measurements are the main source of data available to interpret and model this dynamic geographic phenomenon. Sri Lanka is in need of an accurate and timely wind map in order to support wind energy resource planning and to enable weather prediction systems to be more accurate. Strong and continuous winds in the southern part of the island encourage wind harvesting for energy. Wind energy is arguably the most affordable per megawatt-hour renewable energy source, and it is growing nearly as quickly as conventional energy generation techniques in the country. The objective of this paper is twofold. First is to use the spatial autocorrelation structure of 23 data points using diurnal data measured every 10 minutes on an irregularly distributed grid to construct continuous wind speed fields for the 4 monsoon seasons. This has been done for the year 2015 as a reference year, where a complete set of data was acquired. Secondly, it was intended to provide the reader how R opensource with advanced statistical modelling capabilities and graphics could be utilized conveniently for vague geographic phenomena analysis. The spatial autocorrelation of the wind speed and the direction was determined in the beginning by using the semi-variograms. Candidate semi-variogram models, especially spherical and exponential models, were tested to be more suitable for the observations. Ordinary Kriging, which uses the samples in the local neighborhood to avoid the mean estimation, was used to perform the spatial interpolations Kriging. For each month of the year 2015, four weekly wind maps were generated, both for the direction and speed. These 48 wind maps were further analyzed for the wind patterns. The changes in the morning and evening wind patterns, and the significant wind pattern changes along the coastal areas and the central highlands are extracted and presented in the study. The generated maps could be useful in identifying potential areas for wind farming. By feeding the data in a time series to the presented model, it would be possible to deduce wind pattern changes in Sri Lanka on a yearly basis. As a whole, the paper presents a reasonable model that could be used to model a diverse set of vague phenomena with an understanding of the uncertainties involved.

An overview of the tropical cyclone database at the Central Weather Bureau of Taiwan

Taiwan’s Central Weather Bureau (CWB) has established a new version of tropical cyclone (TC) database to provide users with comprehensive TC data services. As of June 2022, the database includes 1673 TCs originating in the western North Pacific and South China Sea regions since the CWB began TC forecasting operations in 1958. It collects not only the track dataset, satellite imagery, and synoptic weather charts, but also more detailed data and products of TCs that have impacted Taiwan, such as radar reflectivity imagery, high-density surface observations, dropwindsonde data from aircraft observations, and mesoscale analysis maps of rainfall, wind, pressure, and temperature. Such detailed data realistically preserves the TC’s journey across Taiwan and is a feature of the CWB TC database. In addition, the TC database website (https://rdc28.cwb.gov.tw/TDB/) provides tools that allow users to search for TCs of interest based on track, rainfall, and wind. Digital best track data since 1958 is available (https://rdc28.cwb.gov.tw/TDB/manager/obs_data_download/) for users to download and conduct TC research. Also included are technical reports summarizing extensive historical observational research focusing on the mesoscale variations during a TC’s passage over Taiwan. The TC database has been widely used in academic research, disaster prevention, crop revenue insurance, offshore wind power, and other fields. It will continue to develop useful products and integrate more diverse observations to meet the needs of different users.

Sites exploring prioritisation of offshore wind energy potential and mapping for wind farms installation: Iranian islands case studies

Offshore Wind Energy (OWE) can be considered the Renewable Energy Sources (RESs) with a higher potential of newly installed power in marine areas more the following decades. As a primary phase of the Offshore Wind Farms (OWFs) development, focusing on the long-term Offshore Wind (OW) potential assessment and mapping is necessary to highlight the best areas for turbine generators installations. In this case, accurate assessment and mapping of long-term OWs can help pinpoint previously not considered marine areas. In this regard, the Iranian islands located in the Persian Gulf can be called one of these forgotten areas in dire need of energy supply due to their remoteness from the mainland. To these aims, the long-term Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) re-analysis dataset has been used to identify possible locations of the Offshore Wind Turbine Generators (OWTGs) installations. In particular, an OW classification based on the 40 years of monthly data and the last 10-years of hourly data highlighted the best areas for OWTGs potential installations in the 12 Iranian islands of the Persian Sea. The time-series method has been designed, tested, and developed to understand better and manage the OW potential and mapping of the Iranian islands decision-making process. Furthermore, the time-series method has been applied to the generated energy source based on the OW speed used in the Iranian islands. Finally, exploring results show Iranian islands, such as Kharg, Siri and Abu Musa islands, have attractive OWE potentials for OWTGs installations.

Contributors

Contributors