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Wind gust
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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]- ^ a b "Gust". Glossary. American Meteorological Society. Archived from the original on June 2, 2023. Retrieved November 15, 2018.
- ^ "What causes wind gusts?". wxguys.ssec.wisc.edu. Archived from the original on 2023-12-10. Retrieved 2021-11-28.
- ^ World Meteorological Organization. "Gust amplitude". Eumetcal. Archived from the original on 2016-03-03. Retrieved November 15, 2018.
- ^ a b "Rafale". Glossaire météorologique (in French). Météo-France. Archived from the original on October 30, 2020. Retrieved November 15, 2018.
Wind gust
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Fundamentals
Definition
A wind gust is defined by the World Meteorological Organization (WMO) as the maximum value, over the observing cycle, of the 3-second running average wind speed, measured in meters per second.[1] This represents a short-duration peak in horizontal wind speed within a longer sampling period, typically 10 minutes, distinguishing it from sustained wind, 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 wind speed by at least 5 m/s (10 knots), beyond which it is reported in standard meteorological observations.[8] These criteria differentiate gusts from steady winds or longer-duration events like squalls, emphasizing their transient nature associated with atmospheric turbulence.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 meters 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 boundary layer, influencing small-scale transport of momentum, heat, and moisture without affecting broader circulation patterns. Field observations confirm that gust propagation distances rarely exceed 500 meters, 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 planetary boundary layer due to frictional effects and turbulence dissipation. The logarithmic wind law, which describes the mean wind profile as $ 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 surface roughness enhances shear. Gust speeds demonstrate statistical variability often following a log-normal distribution, 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 mean 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 mean 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 wind gusts through the creation of vertical and horizontal wind shear. 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 thermal wind 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 momentum 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 condensation and the formation of precipitation; as rain or hail falls, evaporative cooling increases air density, 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:
where is the material acceleration of horizontal velocity , is the Coriolis parameter ( Earth's rotation rate, latitude), the vertical unit vector, air density, and the pressure gradient. Gusts arise from transient imbalances: a steepened pressure gradient accelerates flow, while the Coriolis force 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 Eastern Air Lines Flight 66, a Boeing 727 approaching John F. Kennedy International Airport. The aircraft encountered severe wind shear from a thunderstorm's downdraft, with increasing headwinds transitioning to tailwinds, causing a high descent rate and collision with approach lights; the National Transportation Safety Board 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.[9] Similarly, chinook winds on the leeward side of the Rocky Mountains 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.[10] Surface friction from land use variations generates mechanical turbulence that alters gust profiles, with urban environments contrasting sharply against rural ones. In rural landscapes, open fields and low roughness allow smoother airflow, resulting in less intense but more sustained gusts; however, urban areas introduce high friction through buildings and infrastructure, creating chaotic eddies and shear layers. Urban canyons, formed by tall structures aligned with prevailing winds, can funnel and accelerate air, producing localized gusts higher than ambient rural speeds due to the Venturi effect and enhanced turbulence production. This mechanical turbulence 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.[11] 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 terrain and surface influences amplifying gusts occurred during the 1999 Sydney hailstorm, 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 turbulence and contribute to widespread structural damage, including shattered windows and roof failures across 20,000 homes.[12] The urban density amplified the storm's impact, as confined spaces limited dissipation, leading to higher effective gust forces on infrastructure compared to what might have occurred in more open terrain.[12]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.[4][13] Ultrasonic anemometers provide advanced 3D vector measurements of wind gusts by emitting acoustic pulses between transducers and calculating velocity from transit time differences along multiple paths, offering simultaneous horizontal and vertical components without moving parts. 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 turbulence that cup anemometers may underrepresent. These sensors are particularly effective in harsh environments due to their durability and low starting threshold near 0 m/s.[4][14] Remote sensing techniques complement direct measurements by enabling non-contact profiling of wind gusts over vertical extents. Doppler LIDAR systems use laser 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 severe weather, where they can track gust propagation and provide early warnings by resolving fluctuations as low as 4.5 m/s at low altitudes.[15] Similarly, SODAR (Sonic Detection and Ranging) employs phased-array acoustic beams to measure wind profiles through Doppler-shifted echoes from refractive index fluctuations, reaching up to 1 km in the boundary layer with resolutions down to 5-20 m. SODAR 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 precipitation.[16][17] 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 20th century, 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 Automated Surface Observing System (ASOS) since the 1990s, now predominantly employ ultrasonic anemometers (such as the Vaisala WS425, introduced in 2005) that sample at high frequencies to determine 3-second gust averages, enhancing real-time aviation and weather reporting over earlier magneto-type systems.[13][18] Calibration and placement adhere to World Meteorological Organization (WMO) guidelines to minimize errors in gust readings, specifying a standard height of 10 m above ground level in open, homogeneous terrain with roughness length 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 data integrity.[19][17]Gust Metrics
The gust factor (GF) is a key metric used to quantify the intensity of wind gusts relative to sustained winds, defined as the ratio of the maximum gust speed $ V_{\max} $ to the mean wind speed $ V_{\mean} $ over a reference period, typically 10 minutes:
This ratio helps assess turbulence and peak loads in meteorological and engineering contexts. [4] [20] In open terrain, such as flat rural areas or over water, typical GF values range from 1.3 to 1.7, reflecting lower surface friction and more uniform flow compared to urban environments where values can exceed 2.0. [6]
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. [21] This Type I extreme value distribution assumes gust speeds follow an exponential tail for rare events, enabling extrapolation to long-term risks. [22] For a 50-year return period in temperate zones, such as much of the United States or central Europe, 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 climate patterns but represent a benchmark for non-hurricane-prone areas. [23]
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. [24] 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. [25] 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 $ K_d $ (typically 0.85 for rigid buildings), to adjust for wind approach angles and reduce loads from non-perpendicular directions. [26] These provisions ensure conservative estimates for a 700-year mean recurrence interval, adaptable to 50-year risks by scaling. [27]
In data analysis, 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. [6] NOAA datasets, such as those from the Automated Surface Observing System (ASOS), report gusts as the highest 3-second average within a 10-minute window, enabling consistent analysis 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 averages up to 15-20 m/s during winter storms, informing probabilistic models. [28]