Hubbry Logo
Wind gustWind gustMain
Open search
Wind gust
Community hub
Wind gust
logo
8 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
Wind gust
Wind gust
Wind gust
View on Wikipedia
from Wikipedia
Wind gust speeds during Storm Abigail in November 2015
Sound of wind blowing in a pine forest at around 25 m/sec, with gust alterations

A wind gust or just gust is a brief, sudden increase in the wind speed. It usually lasts for less than 20 seconds, briefer than a squall, which lasts minutes. A gust is followed by a lull (or slackening) in the wind speed.[1] Generally, winds are least gusty over large water surfaces and most gusty over rough land and near high buildings.[2]

Definition

[edit]

The wind is measured using an anemometer or estimated with a windsock. The average value of wind speed is generally measured over a period of 2 minutes before the meteorological observation according to the World Meteorological Organization. Any significant variation at this mean wind during the ten minutes preceding the observation are noted as gusts in messages such as METAR.[3]

It is generally reported in METAR when the peak wind speed reaches at least 16 knots (30 km/h; 18 mph) and the variation in wind speed between the peaks and average wind is at least 9 to 10 knots (17 to 19 km/h; 10 to 12 mph).[1][4] In marine meteorology, the top speed of a burst is expressed in meters per second (m/s) or in knots, while the Beaufort scale is used for reporting the mean speed. When the maximum speed exceeds the average speed by 10 to 15 knots (19 to 28 km/h; 12 to 17 mph), the term gusts is used while strong gusts is used for departure of 15 to 25 knots (28 to 46 km/h; 17 to 29 mph), and violent gusts when it exceeds 25 knots (46 km/h; 29 mph).[4]

References

[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Wind gust

View on Grokipedia
from Grokipedia
A wind gust is a brief, sudden increase in above the prevailing mean, typically lasting less than 20 seconds and defined by the as the maximum value, over the observing cycle, of the 3-second running average . In standard meteorological observations, a gust is recorded when the peak exceeds the 10-minute mean by at least 5 m/s (10 knots). These short-lived events are measured at a height of 10 above the surface using high-resolution anemometers, such as cup or sonic types, which capture the 3-second maximum within a longer sampling period like 10 minutes. Wind gusts primarily result from atmospheric , where large eddies or intermittent fluctuations transport high-momentum air downward, often amplified by convective processes in storms, frontal passages, or interactions with and surface friction. In thunderstorms, downdrafts can generate intense gust fronts—leading edges of cool air that propagate outward, producing sudden wind shifts and very strong winds. Gust factors, the of gust speed to sustained , typically range from 1.3 to 1.5 but can exceed 2 in extreme conditions, varying with height, stability, and geography. The impacts of wind gusts are significant, contributing to structural , aviation hazards, and disruptions in sectors like and shipping; for instance, storms involving strong wind gusts accounted for about 32% of total natural hazard losses in from 1980 to 2009, amounting to around 132 billion euros in total damages (of which about 71 billion were insured). Forecasting gusts remains challenging due to their localized nature, relying on models like the High-Resolution Rapid Refresh (HRRR) that incorporate parameterization, though biases persist in predicting extremes. Understanding gusts is crucial for engineering standards, such as building codes that use peak 3-second gusts for load calculations, and for issuing warnings in events.

Fundamentals

Definition

A wind gust is defined by the (WMO) as the maximum value, over the observing cycle, of the 3-second running average , measured in meters per second. This represents a short-duration peak in horizontal within a longer sampling period, typically 10 minutes, distinguishing it from sustained , which is averaged over that full interval. Key thresholds for classifying a fluctuation as a gust include a minimum duration of 3 seconds for the peak average and an amplitude exceeding the 10-minute mean by at least 5 m/s (10 knots), beyond which it is reported in standard meteorological observations. These criteria differentiate gusts from steady winds or longer-duration events like squalls, emphasizing their transient nature associated with atmospheric .

Characteristics

Wind gusts are characterized by their brief and intense nature, typically lasting less than 20 seconds, with rapid onset and decay phases that distinguish them from sustained winds. This short duration arises from transient atmospheric perturbations, allowing gusts to fluctuate significantly over short time intervals, often exhibiting frequencies of 0.1 to 1 Hz in turbulent conditions. In gusty weather, such as during thunderstorms or frontal passages, gusts can occur at intervals of seconds to minutes, contributing to the overall variability in near-surface wind fields. Spatially, wind gusts operate on microscale dimensions, typically spanning tens to hundreds of horizontally, in contrast to the synoptic-scale patterns of larger wind systems that extend over kilometers. This localized scale enables gusts to form discrete plumes or eddies within the atmospheric , influencing small-scale transport of , , and without affecting broader circulation patterns. Field observations confirm that gust propagation distances rarely exceed 500 , emphasizing their role as fine-scale features in turbulent flows. In terms of vertical structure, wind gusts exhibit pronounced shear, with speeds generally decreasing with height in the due to frictional effects and dissipation. The logarithmic wind law, which describes the mean wind profile as u(z)=u∗κln⁡(zz0)u(z) = \frac{u_*}{\kappa} \ln\left(\frac{z}{z_0}\right), applies to gusts by modulating their intensity; for instance, near-surface gust speeds can reach 1.5 to 2 times the mean wind at 10 meters, but this ratio diminishes aloft, dropping to near unity above 100 meters in neutral stability conditions. Measurements from tower-based anemometers over flat terrain illustrate this profile, showing gust maxima concentrated within the lowest 20-50 meters where enhances shear. Gust speeds demonstrate statistical variability often following a , reflecting the multiplicative nature of turbulent processes in the atmosphere. Empirical studies from diverse environments, including open plains and coastal sites, indicate that gust factors (ratio of peak to wind) typically range from 1.3 to 1.8, with higher values in unstable conditions; this distribution implies a skewed tail of extreme events, where gusts exceeding 1.5 times the occur with probabilities around 10-20% in moderately turbulent flows. Such patterns have been validated through long-term datasets, underscoring the non-Gaussian behavior of gust magnitudes.

Causes

Atmospheric Processes

Synoptic-scale atmospheric features play a crucial role in generating gusts through the creation of vertical and horizontal . Cold fronts, marking the leading edge of denser cold air displacing warmer air, often produce significant gusts due to strong temperature gradients that induce vertical shear via balance. These gradients can lead to turbulent mixing and sudden wind accelerations, with gusts behind cold fronts commonly reaching 20-30 m/s in severe cases, particularly in mid-latitude cyclones. Low-pressure systems amplify this effect through intensified pressure gradients that accelerate airflow toward the center, fostering cyclonic shear and episodic bursts of high winds exceeding mean speeds. Jet streams, especially low-level jets, contribute by transporting downward, creating low-level shear that manifests as gusty surface winds during nocturnal or frontal passages. Convective processes within thunderstorms and cumulonimbus clouds drive some of the most abrupt wind gusts through the interplay of updrafts and downdrafts. In mature thunderstorms, strong updrafts lift moist air, leading to and the formation of ; as rain or falls, evaporative cooling increases , promoting rapid downdrafts that accelerate toward the surface. Upon impacting the ground, this sinking air diverges outward as a gust front, producing sudden horizontal wind accelerations. Microbursts, a specific convective phenomenon, are localized downdrafts less than 4 km in diameter, often triggered by mid-level dry air enhancing evaporative cooling; they uniquely generate divergent outflow winds up to 45 m/s (100 mph) over short durations of 2-5 minutes, posing hazards distinct from broader synoptic gusts due to their intensity and rapid onset. The initiation of wind gusts can be understood through the fundamental dynamics of atmospheric flow, governed by the momentum equation—a simplified form of the Navier-Stokes equations for geophysical fluids. In the horizontal plane, neglecting friction for large-scale flows, the equation approximates as: DuDt+fk×u=−1ρ∇p,\frac{D\mathbf{u}}{Dt} + f \mathbf{k} \times \mathbf{u} = -\frac{1}{\rho} \nabla p, where DuDt\frac{D\mathbf{u}}{Dt} is the material acceleration of horizontal velocity u\mathbf{u}, f=2Ωsin⁡ϕf = 2 \Omega \sin \phi is the Coriolis parameter (Ω\Omega rate, ϕ\phi ), k\mathbf{k} the vertical , ρ\rho air , and ∇p\nabla p the . Gusts arise from transient imbalances: a steepened accelerates flow, while the deflects it, leading to ageostrophic perturbations and shear that manifest as turbulent gusts. A notable historical example illustrating convective gust hazards is the 1975 crash of , a approaching . The aircraft encountered severe from a thunderstorm's downdraft, with increasing headwinds transitioning to tailwinds, causing a high descent rate and collision with approach lights; the attributed the accident to these thunderstorm-induced gusts, resulting in 113 fatalities and underscoring the dangers of microburst-like outflows.

Terrain and Surface Influences

Terrain and surface features play a crucial role in modifying wind gusts by channeling, accelerating, or dissipating airflow through mechanical and frictional interactions. Topographical elements, such as hills and escarpments, can significantly amplify gust intensities via downslope acceleration, where descending air warms and speeds up, leading to strong, turbulent bursts. For instance, foehn winds in alpine regions often produce gusts exceeding 50 m/s due to this compression and reduced friction over elevated terrain. Similarly, chinook winds on the leeward side of the exhibit comparable effects, with reported surface gusts reaching up to 40 m/s in extreme cases, driven by the interaction of stable air flows with mountainous barriers. Surface from variations generates mechanical that alters gust profiles, with urban environments contrasting sharply against rural ones. In rural landscapes, open fields and low roughness allow smoother , resulting in less intense but more sustained gusts; however, urban areas introduce high through buildings and , creating chaotic eddies and shear layers. Urban canyons, formed by tall structures aligned with , can funnel and accelerate air, producing localized gusts higher than ambient rural speeds due to the and enhanced production. This mechanical in cities often elevates gust factors compared to open rural settings. Vegetation and oceanic surfaces further influence gust propagation by either dampening or enhancing turbulence through drag and wave interactions. Dense forests act as natural barriers, reducing wind speeds and gust amplitudes within and downwind of the canopy via frictional drag on leaves and branches, which dissipates kinetic energy into heat and sound. In contrast, oceanic influences like sea breeze fronts can sharpen gust fronts, where the convergence of cool marine air with warmer land outflows generates sharp pressure gradients and turbulent bursts, often intensifying inland gusts by 5-10 m/s along coastal zones. Surface waves over water may also modulate gusts by creating roughness that promotes small-scale eddies, though this effect is generally less pronounced than terrestrial features. A notable example of and surface influences amplifying gusts occurred during the , where urban topography in the city's eastern and inner suburbs exacerbated wind effects. Gusts reached 85 km/h (approximately 24 m/s) as the storm propagated over densely built areas, with building alignments and reduced open spaces channeling airflow to intensify localized and contribute to widespread structural damage, including shattered windows and roof failures across 20,000 homes. The amplified the storm's impact, as confined spaces limited dissipation, leading to higher effective gust forces on compared to what might have occurred in more open .

Measurement

Instruments and Methods

The measurement of wind gusts relies on a variety of instruments designed to capture rapid fluctuations in wind speed and direction, with primary focus on in-situ sensors and remote profiling systems. Cup anemometers, the traditional standard for surface wind speed measurement, consist of three or four hemispherical cups mounted on horizontal arms attached to a vertical shaft, where rotation speed is proportional to wind velocity. These instruments typically sample at intervals of 0.1 to 1 second, enabling detection of gusts with response times around 0.2 seconds at 10 m/s wind speeds, though mechanical inertia can lead to overspeeding during acceleration. Ultrasonic anemometers provide advanced 3D vector measurements of wind gusts by emitting acoustic pulses between transducers and calculating from transit time differences along multiple paths, offering simultaneous horizontal and vertical components without . With sampling rates of 10 to 20 Hz or higher, they achieve response times on the order of milliseconds, making them ideal for resolving fine-scale gust structures and that cup anemometers may underrepresent. These sensors are particularly effective in harsh environments due to their and low starting threshold near 0 m/s. Remote sensing techniques complement direct measurements by enabling non-contact profiling of wind gusts over vertical extents. systems use pulses to detect backscattered light from atmospheric aerosols, deriving wind velocities via Doppler shift, with profiling capabilities up to 10 km altitude in clear conditions. Their advantages include operation in hazardous or inaccessible areas, such as during , where they can track gust propagation and provide early warnings by resolving fluctuations as low as 4.5 m/s at low altitudes. Similarly, (Sonic Detection and Ranging) employs phased-array acoustic beams to measure wind profiles through Doppler-shifted echoes from fluctuations, reaching up to 1 km in the boundary layer with resolutions down to 5-20 m. excels in low-altitude gust detection under varied weather, offering robust performance without physical exposure to extreme conditions, though signal attenuation limits range in high winds or . The historical evolution of these instruments traces from 19th-century mechanical gauges, such as Robinson's four-cup anemometer introduced in 1846, which revolutionized continuous wind recording but suffered from calibration inconsistencies. By the early , the U.S. Weather Bureau standardized cup anemometers, transitioning from four-cup to three-cup designs in 1928 for improved response, with corrections applied from 1932 to ensure accuracy in gust data. Modern digital sensors, integrated into automated networks like the NOAA since the , now predominantly employ ultrasonic anemometers (such as the WS425, introduced in 2005) that sample at high frequencies to determine 3-second gust averages, enhancing real-time and reporting over earlier magneto-type systems. Calibration and placement adhere to (WMO) guidelines to minimize errors in gust readings, specifying a standard height of 10 m above ground level in open, homogeneous terrain with around 0.03 m. This elevation ensures representative exposure, avoiding distortions from nearby obstacles like trees or buildings, which must be at least 10 times their height distant to prevent false accelerations or sheltering effects. In complex terrains, such as urban or forested areas, adjustments above the canopy or to taller structures are required, with site-specific validation to maintain .

Gust Metrics

The gust factor (GF) is a key metric used to quantify the intensity of gusts relative to sustained winds, defined as the of the maximum gust speed Vmax⁡V_{\max} to the wind speed V\meanV_{\mean} over a reference period, typically 10 minutes:
\GF=Vmax⁡V\mean\GF = \frac{V_{\max}}{V_{\mean}}
This helps assess and peak loads in meteorological and contexts. In open , such as flat rural areas or over , typical GF values range from 1.3 to 1.7, reflecting lower surface and more uniform flow compared to urban environments where values can exceed 2.0. Return periods provide a statistical framework for estimating the probability and magnitude of extreme gusts, often modeled using the Gumbel extreme value distribution fitted to annual maximum wind data. This Type I extreme value distribution assumes gust speeds follow an exponential tail for rare events, enabling extrapolation to long-term risks. For a 50-year in temperate zones, such as much of the or , design gust speeds typically range from 25 to 30 m/s at 10 m height, based on historical records from land stations; these values vary by location due to regional patterns but represent a benchmark for non-hurricane-prone areas. Engineering standards incorporate gust metrics to ensure structural resilience, with ISO 4354:2009 specifying methods for wind actions on structures using peak velocity pressures that account for gust effects through conversion factors between mean and peak speeds. The standard assumes a gust factor of approximately 1.46 for 3-second peaks relative to 10-minute means in exposure categories, applied to calculate design loads for buildings and bridges. Similarly, ASCE 7 guidelines define design gust speeds via mapped ultimate wind speeds (e.g., 3-second gusts at 10 m height) and include directional gust factors, such as the directionality factor KdK_d (typically 0.85 for rigid buildings), to adjust for approach angles and reduce loads from non-perpendicular directions. These provisions ensure conservative estimates for a 700-year mean recurrence interval, adaptable to 50-year risks by scaling. In , peak gusts are commonly derived using 3-second averaging intervals to capture short-duration maxima, as this duration balances resolution and instrument response without excessive noise. NOAA datasets, such as those from the , report gusts as the highest 3-second within a 10-minute , enabling consistent of hourly or daily extremes. For example, in NOAA's Local Climatological Data archives, 3-second peaks from U.S. stations illustrate seasonal gust variability, with mid-latitude sites showing up to 15-20 m/s during winter storms, informing probabilistic models.

Impacts

Environmental and Weather Effects

Wind gusts play a significant role in modifying weather patterns by enhancing through interactions with in convective storms. In thunderstorms, gusts associated with downdrafts and shear can intensify updrafts, leading to greater convergence and heavier rainfall rates, as observed in studies of severe convective systems where stronger winds correlate with increased precipitation efficiency. Additionally, gusts facilitate the dispersion of atmospheric by promoting turbulent mixing, which dilutes concentrations and alters plume trajectories, particularly in urban environments where intermittent gusts enhance vertical and horizontal pollutant transport. Ecologically, wind gusts influence pollination by aiding in dispersal for anemophilous , where sudden bursts trigger aeroelastic responses in plant structures, releasing more effectively during turbulent conditions. In coastal areas, gusts drive aeolian sand transport, contributing to rates that can reach up to ~1 kg m⁻¹ s⁻¹ under high-velocity events, reshaping dunes and altering budgets. Gusts also disrupt migration, particularly for birds, by increasing energy expenditure and causing deviations in flight paths during storms, as evidenced by reduced rates linked to frequent high-wind episodes on migratory routes. In climate interactions, gusts are central to extreme events like derechos, which are widespread convective wind storms producing sustained gusts exceeding 58 mph over paths longer than 240 miles, amplifying regional cooling or heating effects through enhanced mixing. These gusts contribute to calculations by accelerating heat loss from surfaces, making apparent temperatures much lower than air temperatures alone in cold conditions. Observational studies in arid regions demonstrate that gusts can increase soil evaporation rates compared to steady winds, exacerbating water loss and influencing local moisture balances.

Human and Infrastructure Effects

Wind gusts impose dynamic loads on structures, particularly buildings, where peak s are often estimated using quasi-steady theory, which relates fluctuating wind speeds to corresponding pressure variations on building surfaces. This approach assumes that the wind flow behaves similarly to steady flow but scaled by instantaneous gust velocities, aiding in the design of structural elements to withstand sudden force increases. In extreme cases, such as in 1992, gusts exceeding 175 mph (78 m/s) contributed to widespread structural failures, including the destruction of over 63,500 homes and commercial buildings in due to inadequate resistance to these peak loads. In transportation, wind gusts pose significant risks to through low-level , sudden changes in wind speed and direction near the ground that can lead to loss of control during . These events have been a factor in numerous accidents, historically contributing to a substantial portion of weather-related incidents, with studies indicating involvement in up to 25-30% of such crashes in and air carrier operations prior to advanced detection systems. Maritime operations face similar threats, as gusts can destabilize vessels by generating uneven aerodynamic forces on superstructures, reducing steering effectiveness and increasing the risk of or grounding, particularly for ships with high windage areas like container vessels. Human safety is compromised by wind gusts during outdoor activities, where sudden high winds can cause direct injuries from flying or structural collapses, as well as indirect harm through disrupted balance or equipment failure. For instance, nonconvective high-wind events, often featuring intense gusts, resulted in 616 fatalities across the from 1980 to 2005, many occurring outdoors during recreational or occupational exposure. A notable example is the 2013 , EF5 tornado, where gusts associated with winds up to 210 mph led to 24 fatalities, including several children caught outdoors or in inadequate , alongside hundreds of injuries from debris impacts. The economic impacts of wind gusts are substantial, with global annual damages from wind-related events estimated in the tens of billions of dollars, encompassing destruction and interruptions primarily from severe storms. alone, wind disasters cause average annual economic losses exceeding $6 billion, representing over 50% of total weather-related , much of which stems from gust-induced structural failures covered by claims. data highlights this burden, with global insured losses from and severe convective events reaching $80 billion in the first half of 2025, driven by frequent gust-heavy occurrences like thunderstorms and hurricanes. These costs underscore the need for gust metrics, such as peak gust velocities, in designs to minimize financial repercussions.

Prediction and Mitigation

Forecasting Techniques

models, such as the Weather Research and Forecasting (WRF) model, employ high-resolution simulations to forecast gusts through dedicated parameterization schemes that account for and mixing in the (PBL). These schemes, including the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) options, simulate near-surface variability by resolving PBL processes like vertical mixing and shear-driven , which are critical for gust formation during convective or synoptic events. Gust-specific parameterizations, such as those by Gutiérrez-Fovell (2018) and Nakamura et al. (1996), further refine WRF outputs by estimating peak gusts from mean profiles and convective activity indicators, like vertically integrated rainwater mixing ratios exceeding thresholds verified against . Combining these parameterizations in WRF simulations at resolutions around 3 km has demonstrated superior skill in predicting gusts at heights up to 100 m, particularly for energy applications in regions like . Probabilistic forecasting of wind gusts relies on prediction systems, such as the COSMO-DE-EPS and ECMWF-ENS, which generate multiple scenarios to quantify uncertainty in gust occurrences. Postprocessing techniques, including model output statistics (EMOS) and logistic regressions, calibrate raw outputs using historical data from weather stations to produce reliable probability forecasts for gust thresholds ranging from 12.9 m/s to 38.6 m/s. These methods reduce biases like overforecasting in raw ensembles and achieve skill comparable to human forecasters for severe gust warnings, with continuous ranked probability score (CRPS) improvements of 26–29% over baseline approaches and positive Brier Skill Scores for gusts up to 30 m/s. For instance, incorporating additional predictors like and enhances probabilistic reliability, enabling automated warning systems such as Germany's AutoWARN. Nowcasting techniques for gusts focus on short-term predictions (0–2 hours) by leveraging and observations to identify and track gust fronts—leading edges of convective outflows that produce sudden increases. detects these fronts through signatures like convergence and reflectivity gradients, allowing of gust propagation based on storm motion vectors. data from instruments like GOES complements by monitoring cloud development and outflow boundaries, facilitating real-time alerts for gusts associated with thunderstorms or breezes. Advanced nowcasting models, such as the deep learning-based CGsNet, integrate reflectivity fields to provide quantitative gust forecasts at minute-scale resolutions and kilometer spatial scales, outperforming traditional methods in convective scenarios. Recent advancements in the 2020s have integrated (ML) with numerical models to enhance wind gust prediction, particularly through postprocessing of ensemble outputs. Neural network-based methods, like distributional regression networks (DRN) and quantile networks (BQN), applied to WRF or COSMO ensembles, improve calibration and sharpness by learning complex relationships from predictors such as , , and convective indices, yielding CRPS reductions of up to 29% compared to statistical baselines. As of 2025, further progress includes post-processing methods applied to models like Pangu-Weather for improved forecasts of convective storm wind gusts up to three days ahead. These ML approaches extend effective lead times for reliable gust forecasts, with studies reporting relative improvements in probabilistic metrics like CRPS by 10–30% over the first 7 days, enabling better integration of atmospheric processes as model inputs. For storm-scale events, ML-augmented WRF simulations have shown enhanced accuracy in predicting peak gusts, supporting applications in alerting.

Safety Measures

Engineering designs for gust resistance incorporate building codes that account for peak wind loads to ensure structural integrity during sudden gusts. Eurocode 1 (EN 1991-1-4) specifies wind actions based on a 10-minute mean wind velocity combined with gust factors to derive peak velocity pressures, enabling designs that account for short-term wind fluctuations. These codes promote features such as tuned mass dampers, which absorb vibrational energy from gust-induced oscillations, and aerodynamic shaping like tapered forms or slotted facades to minimize and reduce overall wind forces by up to 30% in high-rise structures. Warning systems play a crucial role in public preparedness by issuing alerts for gust-prone conditions. The (NWS) issues high wind warnings when sustained winds reach 40 mph (18 m/s) or gusts exceed 58 mph (26 m/s), triggering advisories to limit outdoor activities and secure property. These thresholds help mitigate risks from gusts that can amplify hazards in non-convective , with alerts disseminated via broadcasts and apps to reach affected populations promptly. Operational protocols in high-risk sectors emphasize real-time monitoring and response. In , the Low Level Wind Shear Alert System (LLWAS) detects gust-related near runways by measuring wind speed changes exceeding 15 knots, issuing radio alerts to pilots for or diversion procedures, thereby addressing impacts like sudden losses during . Emergency evacuations in gust-prone areas, such as coastal or mountainous regions, follow protocols that include pre-storm relocation orders and designations to protect residents from flying debris and structural failures. Research initiatives since the have enhanced coastal defenses against gust-amplified storm surges through nature-based and engineered solutions. Post-hurricane assessments led to widespread adoption of wetland restoration and barrier enhancements, which reduce surge heights and associated wind-driven flooding; for instance, a 1% loss in coastal coverage is associated with a 0.6% increase in from tropical cyclones. Global analyses indicate that improved defenses and early warning systems have contributed to a decline in storm surge fatalities since the .

References

  1. https://space.oscar.wmo.int/variables/view/wind_gust
  2. http://www.moratech.com/aviation/metar-class/metar-pg6.html
  3. https://digital.weather.gov/staticpages/definitions.php
  4. https://pmc.ncbi.nlm.nih.gov/articles/PMC5948875/
  5. https://www.nesdis.noaa.gov/about/k-12-education/severe-weather/what-gust-front
  6. https://journals.ametsoc.org/view/journals/apme/56/12/jamc-d-17-0133.1.xml
  7. https://repository.library.noaa.gov/view/noaa/67853
  8. https://codes.wmo.int/common/quantity-kind/_aerodromeMaximumWindGustSpeed
  9. https://ams.confex.com/ams/pdfpapers/141372.pdf
  10. http://www.nwcg.gov/publications/pms425-1/6-general-winds
  11. http://www.nwcg.gov/publications/pms437/weather/critical-fire-weather
  12. https://hal.science/hal-00299245/document
  13. https://library.oarcloud.noaa.gov/noaa_documents.lib/NOAA_historic_documents/WB/Key_Meteorological_Records_Doc/KMRD_3.151.pdf
  14. https://www.vaisala.com/en/products/weather-environmental-sensors/windcap-ultrasonic-wind-sensor-wmt700
  15. https://ntrs.nasa.gov/api/citations/20080013367/downloads/20080013367.pdf
  16. https://www.scintec.com/catalogs/sodar-wind-profilers/
  17. https://library.wmo.int/records/item/68695-guide-to-instruments-and-methods-of-observation
  18. https://www.weather.gov/media/asos/ASOS%20Implementation/IFWS_BelfordWS_comparison.pdf
  19. https://www.epa.gov/sites/default/files/2020-10/documents/mmgrma_0.pdf
  20. https://www.vos.noaa.gov/MWL/fall_02/Gust.pdf
  21. https://help.emd.dk/knowledgebase/content/ReferenceManual/ExtremeWinds.pdf
  22. https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1017/S1350482799001103
  23. https://meetingorganizer.copernicus.org/ECSS2019/ECSS2019-218-3.pdf
  24. https://www.iso.org/standard/38882.html
  25. https://rmets.onlinelibrary.wiley.com/doi/10.1002/met.2094
  26. https://ascelibrary.org/doi/book/10.1061/9780784414248
  27. https://www.sciencedirect.com/science/article/pii/S0167610598001822
  28. https://www.ncei.noaa.gov/pub/data/cdo/documentation/LCD_documentation.pdf
  29. https://www.nsf.gov/news/why-are-big-storms-bringing-so-much-more-rain
  30. https://acp.copernicus.org/articles/19/3797/2019/acp-19-3797-2019.pdf
  31. https://www.researchgate.net/publication/24430918_Wind_gusts_and_plant_aeroelasticity_effects_on_the_aerodynamics_of_pollen_shedding_A_hypothetical_turbulence-initiated_wind-pollination_mechanism
  32. https://www.sciencedirect.com/science/article/abs/pii/S0169555X04002922
  33. https://bmcecol.biomedcentral.com/articles/10.1186/s12898-017-0139-7
  34. https://www.weather.gov/safety/wind-thunderstorms-derecho
  35. https://www.weather.gov/safety/cold-wind-chill-chart
  36. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013WR013952
  37. https://www.engr.colostate.edu/~meroney/PapersPDF/cep99-00-7.pdf
  38. https://www.aoml.noaa.gov/hrd/flyers/HurricaneAndrewHandoutCat5b.pdf
  39. https://ams.confex.com/ams/30Hurricane/webprogram/Manuscript/Paper206042/andrew-V4.pdf
  40. https://ntrs.nasa.gov/api/citations/19830013440/downloads/19830013440.pdf
  41. https://www.marineinsight.com/marine-navigation/effects-of-wind-on-ship-handling/
  42. https://journals.ametsoc.org/view/journals/bams/103/10/BAMS-D-21-0160.1.xml
  43. https://huskiecommons.lib.niu.edu/cgi/viewcontent.cgi?article=1878&context=allfaculty-peerpub
  44. https://www.weather.gov/oun/events-20130520
  45. https://www.ncei.noaa.gov/access/billions/
  46. https://pmc.ncbi.nlm.nih.gov/articles/PMC3743338/
  47. https://www.insurancejournal.com/news/international/2025/08/06/834711.htm
  48. https://journals.ametsoc.org/downloadpdf/journals/wefo/30/3/waf-d-14-00105_1.pdf
  49. https://www.sciencedirect.com/science/article/abs/pii/S0167610520300283
  50. https://npg.copernicus.org/articles/27/473/2020/npg-27-473-2020.pdf
  51. https://arxiv.org/pdf/2106.09512
  52. https://www.mdpi.com/1424-8220/18/4/1300
  53. https://gmd.copernicus.org/articles/16/3611/2023/
  54. https://www.nature.com/articles/s44304-025-00142-y
  55. https://www.science.org/doi/10.1126/sciadv.adu2854
  56. https://journals.ametsoc.org/view/journals/aies/3/3/AIES-D-23-0047.1.xml
  57. https://www.phd.eng.br/wp-content/uploads/2015/12/en.1991.1.4.2005.pdf
  58. https://www.sciencedirect.com/science/article/abs/pii/S2352710217305569
  59. https://onlinelibrary.wiley.com/doi/10.1155/2017/2031248
  60. https://www.weather.gov/box/criteria
  61. https://www.weather.gov/lwx/warningsdefined
  62. https://www.faa.gov/air_traffic/weather/wsds
  63. https://safetyfirst.airbus.com/wind-shear-an-invisible-enemy-to-pilots/
  64. https://www.weather.gov/mlb/seasonal_wind_rules
  65. https://www.pnas.org/doi/10.1073/pnas.1915169117
  66. https://iopscience.iop.org/article/10.1088/1748-9326/aa98a3
Add your contribution
Related Hubs
User Avatar
No comments yet.