The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2022.

This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.

For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).

This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.

Over the past two decades, the average wind speed in the United Kingdom has remained relatively stable. In 2024, the average wind speed in the UK was 8.4 knots. Speeds peaked during this period in 2015 at 9.4 knots, before falling to 8.4 knots the following year. One knot is equivalent to one nautical mile per hour. Overall, wind speeds have mostly remained between eight and nine knots, dropping to a low of 7.8 in 2010. The first and fourth quarters were the windiest Since 2010, the first and fourth quarters of each year generally recorded the highest wind speeds. The highest quarterly wind speed averages occurred in the first quarter of 2020, with speeds of approximately 11.5 knots. Between 2015 and 2023, the most noticeable deviation from the 10-year mean was recorded in February 2020. In this month wind speeds were 4.2 knots higher than normal. Optimal wind conditions for wind energy The United Kingdom has some of the best wind conditions in Europe for wind power, so it is no surprise that it plays an important role in the country's energy mix. As of 2023, there were 39 offshore wind farms operating in the UK, by far the most in Europe. Furthermore, in the same year, offshore wind power additions in the UK reached 1.14 gigawatts.

The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2021.

This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.

For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).

This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.

The Department for Business, Enterprise & Regulatory Reform's wind speed database is available from this website. It contains estimates of the annual mean wind speed throughout the UK. The data is the result of an air flow model that estimates the effect of topography on wind speed. There is no allowance for the effect of local thermally driven winds such as sea breezes or mountain/valley breezes. The model was applied with 1km square resolution and takes no account of topography on a small scale or local surface roughness (such as tall crops, stone walls or trees), both of which may have a considerable effect on the wind speed. The data can only be used as a guide and should be followed by on-site measurements for a proper assessment. Each value stored in the database is the estimated average for a 1km square at either 10m, 25m or 45m above ground level (agl). The database uses the Ordnance Survey grid system for Great Britain and the grid system of the Ordnance Survey of Northern Ireland.

Wind speed averages in the United Kingdom are generally highest in the first and fourth quarters of each calendar year – the winter months. Since 2010, the UK’s highest wind speed average was recorded in the first quarter of 2020, at 11.5 knots. During this period, 2010 was the only year that had the greatest wind speeds outside the winter months, with an average of 8.4 knots in the third quarter. In 2024, wind speeds ranged between a low of 7.9 knots in the third quarter and 9.4 knots in the first quarter. With few exceptions, UK wind speeds generally average at least eight knots annually. 2015 marked the year with the highest average wind speed in the UK (since the beginning of the reporting period in 2001), reaching an average of 9.4 knots. Wind power The UK has some of the best wind conditions in Europe for wind power. By 2023, there were 39 offshore wind farms operating across the UK, by far the most in Europe. Meanwhile, offshore wind power additions in the UK reached 1.14 gigawatts that same year. Quarterly rainfall Another weather phenomenon, UK rainfall also tends to be heaviest in the winter months. The average rainfall in the second quarter of 2024 was 254.5 millimeters, with figures in 2011 spiking to 738.6 millimeters. That year, precipitation levels in some parts of Scotland were the highest in one hundred years, while southern parts of England kept remarkably dry.

Datamarket closure

As Microsoft have announced that they are shutting down their DataMarket service, the API access currently at https://datamarket.azure.com/dataset/datagovuk/metofficeweatheropendata will no longer be available after March 31st 2017.

The interface gives access to three datasets, hourly observations for approximately 150 UK observing stations, daily site specific and 3 hourly site specific forecasts for approximately 5000 UK locations.

Both the 3 hourly and daily forecast datasets provide forecasts out to 5 days with updates issued hourly.

Daily forecasts provide data for day and night using the following data time intervals.

· Weather symbols: Day – Sunrise to sunset, Night Sunset to Sunrise

· Temperature: Max – Maximum during 0600-18:00, Minimum during 18:00-06:00

· All other parameters are calculated for midday or midnight.

Hourly observation reports as recorded in real time by the Met Office UK Monitoring System. It should be noted that sites will only report parameters based on the instrumentation installed at each site and we only make available those parameters published on the Met Office website. Observations are subject to final quality control by the Met Office after publication by data.gov.uk, any changes made will not be retrospectively applied to this dataset.

The Chancellor's Autumn Statement 2011 announced that this release is open (OGL) and unrestricted (bulk download API): https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/61959/Further_detail_on_Open_Data_measures_in_the_Autumn_Statement_2011.pdf which is different to the access provided by the Met Office directly.

What does the data show?

The dataset is derived from projections of seasonal mean wind speeds from UKCP18 which are averaged to produce values for the 1981-2000 baseline and two warming levels: 2.0°C and 4.0°C above the pre-industrial (1850-1900) period. All wind speeds have units of metres per second (m / s). These data enable users to compare future seasonal mean wind speeds to those of the baseline period.

What is a warming level and why are they used?

The wind speeds were calculated from the UKCP18 local climate projections which used a high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g., decades) for this scenario, the dataset is calculated at two levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), so this dataset allows for the exploration of greater levels of warming.

The global warming levels available in this dataset are 2°C and 4°C in line with recommendations in the third UK Climate Risk Assessment. The data at each warming level were calculated using 20 year periods over which the average warming was equal to 2°C and 4°C. The exact time period will be different for different model ensemble members. To calculate the seasonal mean wind speeds, an average is taken across the 20 year period. Therefore, the seasonal wind speeds represent those for a given level of warming.

We cannot provide a precise likelihood for particular emission scenarios being followed in the real world in the future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected under current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate; the warming level reached will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.

What are the naming conventions and how do I explore the data?

The columns (fields) correspond to each global warming level and two baselines. They are named 'windspeed' (Wind Speed), the season, warming level or baseline, and ‘upper’ ‘median’ or ‘lower’ as per the description below. For example, ‘windspeed winter 2.0 median’ is the median winter wind speed for the 2°C projection. Decimal points are included in field aliases but not field names; e.g., ‘windspeed winter 2.0 median’ is ‘ws_winter_20_median’.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, seasonal mean wind speeds were calculated for each ensemble member and then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past.

Data source

The seasonal mean wind speeds were calculated from daily values of wind speeds generated from the UKCP Local climate projections; they are one of the standard UKCP18 products. These projections were created with a 2.2km convection-permitting climate model. To aid comparison with other models and UK-based datasets, the UKCP Local model data were aggregated to a 5km grid on the British National grid; the 5km data were processed to generate the seasonal mean wind speeds.

Useful links

Further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal.

The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2020.

This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2020, historical data recovery has added further data for Eskdalemuir (1914-1944) and Eastbourne (1887-1910).

For details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.

This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data.

This is version v3.4.0.2023f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.

This update (v3.4.0.2023f) to HadISD corrects a long-standing bug which was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html

The quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information.

The data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format "station_code"_HadISD_HadOBS_19310101-20240101_v3.4.1.2023f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.

To keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.

For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/

References: When using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the "citable as" reference) :

Dunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.

Dunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.

Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012

Smith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1

For a homogeneity assessment of HadISD please see this following reference

Dunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. "Pairwise homogeneity assessment of HadISD." Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.

Continuous dataset collection since 2014 through Urban Observatory (UO) sensors. The data covers the geographical area of the North East of England centred on Newcastle upon Tyne (for geographical extent and location of sensors see http://uoweb1.ncl.ac.uk). Data is collected from a variety of sensor platforms with different performance metrics, sampling regimes and sensitivity levels. Information on individual sensors should be consulted before use at http://uoweb1.ncl.ac.uk. Data can be downloaded or accessed via a REST API at http://uoweb1.ncl.ac.uk. Weather metrics include: Rain Int, Solar Radiation, Max Wind Speed, Rain Acc, Humidity, Pressure, Temperature, Wind Direction, Daily Accumulation Rainfall, Visibility, Wind Speed, Wind Gust, Rainfall

In January 2025, the average wind speed was 2.3 knots below the long-term mean (from 2002 to 2021). The largest deviation occurred in February 2020, when winds increased by 4.2 knots compared to the average speed.

Forecast: Offshore Wind Technology (Excl. Low Wind Speed) RD&D in the UK 2024 - 2028 Discover more data with ReportLinker!

The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2018. This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. For details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types. This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data.

ukcp09-Gridded datasets based on surface observations have been generated for a range of climatic variables. The primary purpose of this data resource is to encourage and facilitate research into climate change impacts and adaptation. This data set includes monthly ukcp09-Gridded datasets at 5 x 5 km resolution. A grid for each month covering the whole of the UK, downloadable in 10-year blocks.

The format of the grid text files is the same as that used by ESRI GIS software (e.g. ArcView) to import/export gridded data as plain text. Users of such software can import the files without modification.

The datasets have been created with financial support from the Department for Environment, Food and Rural Affairs (Defra) and they are being promoted by the UK Climate Impacts Programme (UKCIP) as part of the UK Climate Projections (UKCP09). http://ukclimateprojections.defra.gov.uk/content/view/12/689/.

To view this data you will have to register on the Met Office website, here: http://www.metoffice.gov.uk/research/climate/climate-monitoring/UKCP09/register

The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2023.

This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.

For details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.

This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data.

1999-2017 - London SWT Weather data

1. Site: SWT
2. Country\City\Location: UK\London\ Southwark WoodsfordTower SWT
3. Latitude: 51.487760; Longitude: -0.091069
4. Anemometer height: 60 m
5. Weather station owner: Bill Legassick, Southwark Council. Contact: Tel: 020 7525 4253 | Fax: 020 7525 5705
6. Email: Bill.Legassick@southwark.gov.uk

1. Sensor:
2. Sensor type:---- Model -------------: Date Installed
3. Anemometer : CDL Windset (EC8) ......... : 1999
4. Rain gauge : Campbell Scientific ARG-100 : 1999
5. Temperature: T107_C .....................: 1999
6. Humidity : HMP45A .....................: 1999

1. Files: Are Zipped
2. Filenames: Weather_Data_2008.CSV
3. Filetype: comma delimited

4. Header Row:Date and Time,Battery Voltage,CR10 Temperature,Wind Direction 10 Minutes,Wind Speed 10 Minutes,Wind Gust 10 Minutes,Hourly AverageDirection,Hourly Average Speed,Hourly Maximum Gust,Hourly Gust Time,Hourly Gust Direction,Last Minute Average Temperature,Total Hourly Rain,Average RH over previous minute,Maximum Hourly Air Temperature,Minimum Hourly Air Temperature,MaximumHourly Rainfall Rate,Time of Rainfall

5. Data: hourly averages

[THIS DATASET HAS BEEN WITHDRAWN]. Gridded daily meteorological variables over Great Britain for the years 1961-2017 at 1 km resolution. This dataset contains time series of daily mean values of air temperature (K), specific humidity (kg kg-1), wind speed (m s-1), downward longwave radiation (W m-2), downward shortwave radiation (W m-2), precipitation (kg m-2 s-2) and air pressure (Pa), plus daily temperature range (K). These are the variables required to run the JULES land surface model with daily disaggregation. The data are provided in gridded netCDF files. There is one file for each variable for each month of the data set. This data set supersedes the previous version as temporal coverage has been extended to include the years 2016-2017 and the netCDF metadata has been updated and improved. Full details about this dataset can be found at https://doi.org/10.5285/2ab15bf0-ad08-415c-ba64-831168be7293

This is version v3.3.0.2022f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.

The quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information.

The data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format "station_code"_HadISD_HadOBS_19310101-20230101_v3.3.1.2022f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.

To keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.

For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/

References: When using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the "citable as" reference) :

Dunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.

Dunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.

Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012

Smith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1

For a homogeneity assessment of HadISD please see this following reference

Dunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. "Pairwise homogeneity assessment of HadISD." Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.

Snapshot img

Wind Anemometers Market Size 2024-2028

The wind anemometers market size is forecast to increase by USD 110136.5 thousand at a CAGR of 7.4% between 2023 and 2028.

The market is experiencing significant growth due to the increasing demand for accurate weather forecasting sevices. Product innovation, such as the integration of logging functionality and humidity measurement, is driving market expansion. However, calibration issues continue to pose challenges for manufacturers and users. Proper maintenance and regular calibration are essential to ensure the reliability and accuracy of wind anemometer data. The wind profile data obtained from these devices is crucial for various industries, including energy, meteorology, and aviation, to optimize their operations and make informed decisions. Incorporating advanced technologies, such as wireless communication and solar power, can further enhance the functionality and versatility of wind anemometers. The market is expected to continue growing as the need for reliable weather data increases.

What will be the Size of the Market During the Forecast Period?

Request Free Sample

The market is witnessing significant growth due to the increasing demand for accurate wind speed measurements in various industries. Wind anemometers are essential devices used to measure wind pressure and direction, providing valuable data for industries such as meteorology, renewable energy, and aviation. Wind resource assessment plays a crucial role in the wind energy sector. Wind anemometers are used to measure wind speed and direction to evaluate the potential of wind energy sites. The data obtained from wind anemometers is used to determine the wind resource potential, which is a critical factor in wind farm development and wind turbine design.



Climatology is another field where wind anemometers are extensively used. Accurate wind speed measurement is essential for understanding weather patterns and predicting weather conditions. Wind anemometers are used to collect wind data, which is logged and analyzed for climatological studies. Wind energy innovation is driving new wind energy trends in wind energy applications, harnessing air movements more efficiently and promoting wind energy sustainability in the global transition to cleaner, renewable energy sources. The wind energy market is growing, driven by government policies and the increasing demand for renewable energy sources. Wind energy is a sustainable and cost-effective alternative to traditional energy sources. Wind energy solutions are being adopted in various industries, including power generation, marine applications, and engineering. Wind energy economics is a significant factor driving the wind anemometer market.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD thousand' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Type

  Cup anemometers
  Vane anemometers
  Ultrasonic anemometers
  Others


End-user

  Meteorology
  Renewable energy
  Aviation
  Marine and offshore
  Others


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Spain


  APAC

    China
    India
    Japan


  South America

    Brazil


  Middle East and Africa

By Type Insights

The cup anemometers segment is estimated to witness significant growth during the forecast period.

Wind anemometers, which have been utilized for measuring wind speed in the atmosphere for over a century, have gained significant importance, particularly in the construction and wind energy sectors. Initially, these devices were primarily used by meteorologists. However, their application has expanded considerably in the wind energy industry over the past five decades. In this sector, wind anemometers play a vital role in evaluating wind resources and assessing wind turbine performance. The design of wind anemometers, featuring rotating cups mounted on horizontal arms, enables them to capture wind speed effectively. However, studies conducted by meteorologists have revealed a systematic error known as dynamic overspeeding.

Furthermore, this error causes wind anemometers to overestimate wind speed during gusty conditions due to their inertia. Despite this limitation, wind anemometers remain indispensable tools for accurately measuring wind speed in various industries. For construction projects, wind anemometers help determine the wind load on structures, ensuring they are designed to withstand the local wind conditions. In the solar industry, wind anemeters are used to measure wind speed for solar panel efficiency and safety purposes. Pilots and aviation industries also rely on wind anemometers to assess wind conditions for safe flight operations.