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  • Puede empezar inmediatamente a explorar áreas eólicas,
    haciendo clic en el mapa
  • Dibuje puntos, rectángulos y polígonos cliqueando en los respectivos controles del mapa
  • Seleccione datos sobre recursos eólicos por país y región cliqueando en 'países y regiones'
  • Calcule la producción anual de energía para áreas personalizadas

Frequently Asked Questions

Does the GWA include time series?

There are no time series data in the Global Wind Atlas. GWA primarily provides mean values rather than time series data. However, the mean wind power density obtained from a time series and that using weighted sector-wise Weibull distributions do normally not differ by more than 1 per cent. For more information, please refer to the Global Wind Atlas Method .

The New European Wind Atlas does provide time-series from mesoscale model data for areas in Europe.

What do the three different kinds of wind roses show?

The wind frequency rose shows the percentage of all times that the wind comes from each wind direction sector.

The wind speed rose is calculated by multiplying the mean wind speed for each wind direction sector by the wind frequency of that sector.

The wind power rose is calculated by multiplying the mean wind power density for each wind direction sector by the wind frequency of that sector.

What is mean power density?

The mean wind power density is a measure of the wind resource, and higher mean wind power densities indicate better wind resources. More specifically, the mean wind power density is the average kinetic energy flux per unit area perpendicular to the wind flow, and it is measured in [W/m2].

The mean wind power densities in the Global Wind Atlas are calculated using Weibull distributions, which are statistical models that can be fitted to the frequency distributions of wind speeds. This method accounts for the fact that wind speed isn't constant but varies over time.

To determine the mean wind power density for a specific point, we compute a wind-direction frequency weighted sum of the power densities from the sector-wise Weibull distributions. Then, we can also calculate the mean wind power density by averaging the windiest areas in a region. In the side panel, the areas are sorted by wind power and divided into 2% groups to calculate the average for the selected percentage.

The wind power density formula [0.5×air density×wind speed^3] calculates another measure of the wind resource, based on instantaneous wind speeds, which is not equal to values you see on the Global Wind Atlas.

How is RIX related to GWA uncertainty?

The ruggedness index (RIX) is a measure of the steepness or ruggedness of a terrain. In some areas on Earth, the ruggedness of the terrain has a significant impact on the accuracy and uncertainty of the estimated wind resource. For example, the accuracy is reduced and the uncertainty is increased in mountainous areas.

RIXUncertainty
0% - 5%Low
5% - 10%Medium
> 10%High

Why can I see patterns (tiles) in the wind resource maps in certain regions, especially offshore?

When doing mesoscale weather hindcasting for the whole globe, the computer simulations have to be split into a large number of independent runs due to technical limitations of hardware and software. The 10-year weather simulations are therefore carried out independently in a number of separate, but overlapping geographic »tiles«, each about 300x300 km. Since the GWA3.0 mesoscale modeling covers all land and coastal areas of the globe at 3 km resolution, Vortex created nearly 2500 such tiles. Incoming wind flow patterns differ depending on the location of the tile. Also, Vortex made the mesoscale simulations using their own custom set-up. This directly impacts the wind flow conditions across the entire tile. Due to this constraint, contiguous tiles coming from different simulations can show differences along their borders. This is most visible in areas where the topography is flat and surface roughness is homogenous, particularly in offshore areas with unidirectional wind flows.

Which properties are included in the downloaded csv files?

The 'val' stands for the value of mean wind speed, the 'perc' for the percentage and the 'sel_perc' for the selected percentage which is the 'perc' rounded to the nearest integer.

What is the Generalized Wind Climate file?

The generalized wind climate file, also known as a wind atlas file, contains the sector-wise frequency of occurrence of the wind (the wind rose) as well as the wind speed frequency distributions in the same sectors (as Weibull A- and k-parameters). The wind climates are specified for a number of reference roughness lengths (roughness classes) and heights above ground level. Data are stored in an ASCII (text) file with the default file name extension 'gwc'. The gwc-file is a generalised (site-independent) descriptions of the wind climate. The general format of the file is shown below. Numbers in the same line of the file must be separated by blank space(s) or a comma.

Line Contents
1Global Wind Atlas 2.0 (WRF 9-km) ix: XXX, iy: YYY &ltcoordinates>lat,lon,height</coordinates>
2Number of roughness classes, heights and sectors in data set
Values are: 5, 5 and 12
3Reference roughness lengths [m]
Values are: 0.00, 0.03, 0.10, 0.40, 1.50 m
4Reference heights above ground level [m]
Values are: 10, 50, 100, 150 and 200 m a.g.l.
5Frequencies of occurrence for reference roughness #1 (0 m)
6Weibull A-parameters for reference height #1 (10 m) in [ms-1]
7Weibull k-parameters for reference height #1 (10 m)
8-9Weibull A- and k-parameters for reference height #2 (50 m)
10-11Weibull A- and k-parameters for reference height #3 (100 m)
12-13Weibull A- and k-parameters for reference height #4 (150 m)
14-15Weibull A- and k-parameters for reference height #5 (200 m)
16-26As lines 5-15, but for reference roughness #2 (0.03 m)
27-37As lines 5-15, but for reference roughness #3 (0.10 m)
38-48As lines 5-15, but for reference roughness #4 (0.40 m)
49-59As lines 5-15, but for reference roughness #5 (1.50 m)

What is meant by mesoscale modeling?

Mesoscale modeling is modeling the atmosphere’s complex wind flows and weather features so that weather systems and weather fronts are well described and modeled. However, mesoscale models are too coarse to accurately describe the wind flow over hills and ridges. Typically, mesoscale models have a grid spacing ranging from 1 to 10 km. This means that terrain is often oversimplified by the grid spacing in mesoscale models.

What is meant by microscale modeling?

Microscale modeling is modeling the atmosphere’s complex wind flows, usually limited to wind flow close to the surface and within the lowest few hundred meters. Microscale models can capture the way the wind speeds and directions are modified by terrain features, such as hills and ridges, and different kinds of vegetation. This is important because wind resources are very sensitive to wind speed. However, these models are unable to model and capture larger weather features. Typical grid spacing in microscale models ranges from 5 to 100 m.

What is the difference between resolution and calculation node spacing?

The resolution of a given dataset says something about the scale of features that can be described by the dataset. Often, the resolution is stated as the grid spacing of a gridded dataset, although this is not necessarily the same. In the GWA, calculation node spacing is 0.0025 degree (~250 m), but the wind flow modeling is based on terrain description with grid spacing of 1/3600 degree (~30 m) and 1/2400 degree (~50 m), for terrain elevation and roughness length respectively. The term calculation node spacing is used to describe the sampling of the wind flow characteristics.

What does a country specific wind resource assessment add to the Global Wind Atlas?

Country specific mesoscale modeling can increase the accuracy of the atlas, by tailoring the model set-up to the country’s meteorological and geographical settings, allowing for the model to better capture features such as gap flows, barrier jets, low level jets, and sea breezes. Furthermore, inputs for the mesoscale and microscale modeling can utilize country specific datasets and knowledge.

A country specific wind energy measurement program is extremely valuable for verification and open access to high-quality measurement data; it also adds confidence to the wind sector in a country. Local partner involvement gives a higher-quality atlas, and increases the impact of the atlas. Country partners know best how to engage the right organizations and stakeholders in the energy sector.



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La velocidad media del viento es una medida del recurso eólico. Las velocidades medias del viento más altas normalmente indican recursos eólicos de mejor calidad, pero la densidad media de potencia eólica proporciona una indicación más precisa del recurso eólico disponible.
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