11.5 Atmospheric turbulence scales
8 min read•august 21, 2024
Atmospheric turbulence scales shape weather patterns, air quality, and climate dynamics. From lasting seconds to synoptic-scale systems persisting for weeks, these scales play crucial roles in mixing heat, moisture, and pollutants throughout the atmosphere.
Understanding turbulence scales is vital for accurate weather forecasting and climate modeling. The energy cascade process, measurement techniques, and parameterization methods help scientists analyze and predict atmospheric behavior across different environments, from urban areas to marine settings.
Atmospheric turbulence scales
- Atmospheric turbulence scales describe the various sizes of turbulent eddies in the atmosphere
- Understanding these scales helps atmospheric physicists analyze and predict weather patterns, air quality, and climate dynamics
Microscale turbulence
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- Occurs at scales smaller than 2 km, typically lasting seconds to minutes
- Characterized by rapid fluctuations in wind speed, temperature, and humidity
- Influenced by surface roughness, heat fluxes, and local topography
- Plays a crucial role in the vertical mixing of heat, moisture, and pollutants near the Earth's surface
- Examples include:
- Thermal plumes rising from heated surfaces
- Wake turbulence behind buildings or trees
Mesoscale turbulence
- Spans scales from 2 km to 200 km, with durations of hours to a day
- Associated with phenomena such as thunderstorms, sea breezes, and mountain waves
- Driven by temperature gradients, pressure systems, and terrain features
- Affects regional weather patterns and air quality
- Examples include:
- Convective cells in thunderstorms
- Turbulence generated by frontal systems
Synoptic scale turbulence
- Encompasses scales larger than 200 km, lasting days to weeks
- Linked to large-scale weather systems and planetary waves
- Influenced by global circulation patterns and the Earth's rotation
- Shapes long-term weather patterns and climate variability
- Examples include:
- Turbulence associated with jet streams
- Eddies in the polar vortex
Energy cascade process
- Describes the transfer of energy from larger to smaller scales in turbulent flows
- Fundamental concept in understanding atmospheric energy distribution and dissipation
Kolmogorov's theory
- Developed by Andrey Kolmogorov in 1941, provides a statistical description of turbulence
- Assumes isotropic turbulence and a constant energy transfer rate between scales
- Predicts a -5/3 power law for the energy spectrum in the inertial subrange
- Key concepts include:
- Universal equilibrium range where energy transfer depends only on dissipation rate
- Kolmogorov microscale, the smallest scale of turbulent motion
Inertial subrange
- Range of scales where energy transfer occurs without significant dissipation
- Lies between the energy-containing range and the dissipation range
- Characterized by a constant energy flux and self-similar turbulent structures
- Important for understanding energy distribution in atmospheric turbulence
- Typically spans scales from meters to kilometers in the atmosphere
Energy dissipation rate
- Measures the rate at which turbulent kinetic energy converts to heat
- Crucial parameter in determining the intensity of turbulence
- Varies with atmospheric conditions and height above the surface
- Can be estimated using:
- Direct measurements of velocity fluctuations
- Indirect methods based on temperature or humidity profiles
Turbulence measurement techniques
- Essential for quantifying and understanding atmospheric turbulence
- Provide data for model validation and improvement of weather forecasts
Sonic anemometers
- Measure 3D wind components and temperature at high frequencies (10-100 Hz)
- Use ultrasonic pulses to determine wind speed and direction
- Provide direct measurements of turbulent fluxes and energy spectra
- Advantages include:
- No moving parts, reducing maintenance needs
- High precision and temporal resolution
- Limitations involve:
- Sensitivity to precipitation and extreme temperatures
- Potential flow distortion in certain mounting configurations
Doppler lidar
- Uses laser technology to measure wind speed and direction remotely
- Can profile the atmospheric boundary layer up to several kilometers
- Provides spatial and temporal information on turbulent structures
- Applications include:
- Studying and turbulence in wind energy
- Monitoring urban air quality and pollutant dispersion
- Limitations include:
- Reduced performance in very clean air or heavy precipitation
- Higher cost compared to in-situ instruments
Aircraft-based measurements
- Allow for spatial sampling of turbulence over large areas
- Utilize fast-response instruments mounted on research aircraft
- Provide data on turbulence at various altitudes and in remote locations
- Measurements include:
- Eddy covariance fluxes of heat, moisture, and momentum
- and spectral characteristics
- Challenges involve:
- High operational costs
- Potential aircraft-induced flow distortions
Turbulence in boundary layer
- Focuses on turbulent processes in the lowest part of the atmosphere
- Critical for understanding surface-atmosphere interactions and pollutant dispersion
Surface layer turbulence
- Occurs in the lowest 10% of the atmospheric boundary layer
- Characterized by strong vertical gradients of wind speed and temperature
- Influenced by surface roughness, heat fluxes, and friction
- Key features include:
- Logarithmic wind profile in neutral conditions
- Monin-Obukhov similarity theory for flux-profile relationships
- Important for:
- Calculating surface fluxes of heat, moisture, and momentum
- Determining pollutant deposition rates
Mixed layer turbulence
- Extends from the surface layer to the top of the convective boundary layer
- Characterized by well-mixed properties due to strong turbulent mixing
- Driven primarily by surface heating and wind shear
- Features include:
- Nearly constant potential temperature and humidity with height
- Large-scale convective eddies (thermals)
- Crucial for:
- Vertical transport of heat, moisture, and pollutants
- Development of cumulus clouds
Entrainment zone turbulence
- Occurs at the top of the boundary layer, where it interfaces with the free atmosphere
- Characterized by intermittent turbulence and strong gradients
- Driven by processes such as:
- Wind shear at the top of the boundary layer
- Radiative cooling of cloud tops
- Important for:
- Growth of the boundary layer
- Mixing of free-tropospheric air into the boundary layer
Turbulence vs stability
- Examines the relationship between atmospheric stability and turbulence intensity
- Crucial for understanding and predicting turbulent mixing in different conditions
Richardson number
- Dimensionless parameter relating buoyancy to shear production of turbulence
- Defined as the ratio of buoyancy forces to inertial forces
- Calculated using vertical gradients of temperature and wind speed
- Critical values include:
- Ri < 0: unstable conditions, enhancing turbulence
- 0 < Ri < 0.25: neutral to weakly stable, turbulence can persist
- Ri > 0.25: strongly stable, turbulence tends to be suppressed
- Used in:
- Determining the onset of turbulence in stable layers
- Parameterizing turbulent mixing in numerical models
Monin-Obukhov similarity theory
- Describes the structure of turbulence in the atmospheric surface layer
- Based on dimensional analysis and the concept of similarity
- Key parameters include:
- Monin-Obukhov length (L), representing the height where buoyancy and shear production of turbulence are equal
- Stability parameter (z/L), indicating the relative importance of mechanical and thermal forcing
- Provides universal functions for:
- Vertical profiles of wind speed, temperature, and humidity
- Turbulent fluxes of momentum, heat, and moisture
- Limitations include:
- Assumes horizontal homogeneity and stationarity
- May break down in strongly stable or convective conditions
Turbulence parameterization
- Represents turbulent processes in numerical weather and climate models
- Essential for accurate simulations of atmospheric dynamics and transport
Eddy diffusivity approach
- Simplifies turbulent transport using a gradient-diffusion approximation
- Assumes turbulent fluxes are proportional to mean gradients
- Eddy diffusivity (K) represents the efficiency of turbulent mixing
- Advantages include:
- Computational efficiency
- Simplicity in implementation
- Limitations involve:
- Inability to capture non-local transport in convective conditions
- Difficulty in determining appropriate K values for all conditions
K-epsilon model
- Two-equation turbulence closure model widely used in engineering and atmospheric applications
- Solves transport equations for turbulent kinetic energy (k) and dissipation rate (ε)
- Calculates eddy viscosity using k and ε
- Advantages include:
- Accounts for history effects on turbulence
- Suitable for complex flows with separation and recirculation
- Challenges involve:
- Tuning of model constants for atmospheric applications
- Potential numerical instabilities in strongly stratified conditions
Large eddy simulation
- Resolves large-scale turbulent motions explicitly while parameterizing smaller scales
- Uses a spatial filter to separate resolved and subgrid-scale motions
- Requires high spatial and temporal resolution
- Advantages include:
- More realistic representation of turbulent structures
- Improved predictions of extreme events and non-local transport
- Limitations include:
- High computational cost
- Sensitivity to subgrid-scale model formulation
Turbulence effects
- Examines the impacts of turbulence on various atmospheric processes
- Critical for understanding weather, climate, and air quality
Heat and moisture transport
- Turbulence facilitates vertical mixing of heat and moisture in the atmosphere
- Affects the development of the atmospheric boundary layer
- Influences processes such as:
- Evaporation from land and water surfaces
- Formation of fog and low-level clouds
- Impacts energy balance and water cycle on local to global scales
- Key in determining surface temperature and humidity distributions
Pollutant dispersion
- Turbulence plays a crucial role in the transport and dilution of air pollutants
- Affects the concentration and spatial distribution of pollutants
- Influences processes such as:
- Plume rise from industrial stacks
- Urban air quality and street canyon ventilation
- Important for:
- Assessing health impacts of air pollution
- Designing effective emission control strategies
- Challenges include modeling dispersion in complex urban environments
Cloud formation and precipitation
- Turbulence affects cloud microphysics and dynamics
- Influences processes such as:
- Droplet formation and growth through collision-coalescence
- Entrainment and mixing at cloud edges
- Impacts precipitation efficiency and distribution
- Key in understanding:
- Convective cloud development
- Stratocumulus cloud persistence
- Challenges involve representing subgrid-scale turbulence effects in climate models
Turbulence in different environments
- Examines how turbulence characteristics vary across different atmospheric settings
- Important for understanding local weather patterns and air quality
Urban turbulence
- Characterized by complex flow patterns due to building structures
- Features include:
- Enhanced mechanical turbulence from increased surface roughness
- Thermal effects from urban heat island
- Impacts:
- Pollutant dispersion and air quality in cities
- Urban microclimate and pedestrian comfort
- Challenges in modeling due to heterogeneous urban landscapes
Mountain turbulence
- Generated by interaction of airflow with complex terrain
- Phenomena include:
- Mountain waves and rotors
- Foehn winds and valley circulations
- Affects:
- Aviation safety in mountainous regions
- Orographic precipitation patterns
- Requires high-resolution modeling to capture small-scale terrain effects
Marine boundary layer turbulence
- Influenced by air-sea interactions and surface wave states
- Characteristics include:
- Generally weaker turbulence intensity compared to land
- Strong dependence on sea surface temperature gradients
- Important for:
- Understanding and predicting tropical cyclone intensity
- Modeling air-sea gas exchange (CO2, water vapor)
- Challenges in measurements due to remote oceanic locations
Turbulence and climate
- Explores the role of turbulence in climate systems and its representation in models
- Critical for improving climate predictions and understanding climate change impacts
Turbulence in climate models
- Represents subgrid-scale turbulent processes in global climate simulations
- Challenges include:
- Parameterizing turbulence across a wide range of scales
- Balancing computational efficiency with accuracy
- Impacts predictions of:
- Cloud cover and precipitation patterns
- Surface temperature and humidity distributions
- Ongoing research focuses on:
- Improving turbulence schemes for different atmospheric conditions
- Developing scale-aware parameterizations for variable resolution models
Turbulence and climate change
- Examines how changing climate conditions may affect turbulence patterns
- Potential impacts include:
- Changes in boundary layer height and stability
- Alterations in convective intensity and frequency
- Implications for:
- Severe weather events (thunderstorms, tornadoes)
- Aviation safety and efficiency
- Research areas involve:
- Assessing turbulence trends in long-term climate data
- Projecting future changes in turbulence using climate models
Key Terms to Review (19)
Anemometer: An anemometer is a device used to measure wind speed and direction, essential for understanding atmospheric conditions. By providing accurate data on wind patterns, it plays a crucial role in various fields, including meteorology, aviation, and environmental science. The measurements obtained from an anemometer can inform us about storm systems, influence weather forecasting, and contribute to studies related to atmospheric turbulence.
Bernoulli's Principle: Bernoulli's Principle states that an increase in the speed of a fluid occurs simultaneously with a decrease in pressure or potential energy of that fluid. This concept helps explain various atmospheric phenomena, including how air movement impacts temperature profiles, cloud formation, and motion in the atmosphere. Understanding this principle allows us to connect fluid dynamics with meteorological processes and atmospheric stability.
Clear-air turbulence: Clear-air turbulence refers to sudden and unexpected changes in wind speed and direction that occur in the atmosphere, typically at high altitudes and away from thunderstorms. It is often invisible to pilots and radar, making it particularly hazardous during flight. Understanding this phenomenon is crucial for aviation safety, as it can lead to uncomfortable conditions for passengers and crew.
Convective processes: Convective processes refer to the movement of heat and moisture within the atmosphere through the vertical transport of air. This occurs when warmer, less dense air rises and cooler, denser air sinks, leading to the formation of clouds, precipitation, and various weather phenomena. Understanding convective processes is crucial for grasping how energy is redistributed in the atmosphere, influencing weather patterns and turbulence on different scales.
Eddies: Eddies are small-scale, swirling motions of fluid that occur within a larger flow field, often caused by turbulence. These phenomena can significantly influence atmospheric processes by redistributing momentum, heat, and moisture within the atmosphere, which in turn affects weather patterns and climate dynamics.
Frictional drag: Frictional drag refers to the resistance experienced by air as it moves over a surface, such as the Earth's surface or objects in the atmosphere. This drag plays a significant role in atmospheric turbulence by affecting wind patterns and the transfer of momentum and energy within the atmosphere. Understanding frictional drag helps explain how it influences weather phenomena, boundary layer dynamics, and overall atmospheric stability.
Macroscale: Macroscale refers to large-scale atmospheric processes that occur over extensive distances and timeframes, typically involving phenomena that can affect weather patterns and climate on a regional or global scale. It encompasses a range of atmospheric dynamics, including high-pressure systems, low-pressure systems, and the movement of air masses, which collectively influence broader weather systems and climatic trends.
Mesoscale: Mesoscale refers to atmospheric phenomena that occur at a scale of 2 to 200 kilometers, bridging the gap between microscale events, like turbulence, and large-scale features, such as cyclones. It encompasses various weather patterns and processes, including thunderstorms, sea breezes, and mountain-valley breezes, which can significantly impact local weather and climate. Understanding mesoscale dynamics is crucial for predicting short-term weather events and the behavior of atmospheric systems.
Microscale: Microscale refers to the smallest scale of atmospheric turbulence, typically involving processes that occur over short distances, usually less than a few hundred meters. This scale is critical in understanding small-scale wind patterns, turbulence generated by buildings, and the effects of local topography on airflow. At this level, phenomena such as eddies and gusts play a significant role in shaping the immediate atmospheric conditions experienced in various environments.
Navier-Stokes Equations: The Navier-Stokes equations are a set of nonlinear partial differential equations that describe the motion of fluid substances, taking into account the effects of viscosity. These equations are fundamental in fluid dynamics, providing a mathematical framework for understanding how fluids behave under various conditions, including turbulence, pressure changes, and other forces acting on them.
Sodar: Sodar, short for sonic detection and ranging, is a remote sensing technology used to measure atmospheric wind profiles in the lower part of the atmosphere, typically within the planetary boundary layer. This instrument emits sound waves and analyzes the backscattered signals to determine wind speed and direction at various heights. Sodar plays a vital role in understanding atmospheric dynamics, particularly in urban areas and turbulent conditions.
Stable layer: A stable layer refers to a segment of the atmosphere where temperature increases with altitude or where the temperature lapse rate is low, inhibiting vertical mixing of air. This condition generally leads to a calm atmosphere, reducing turbulence and preventing the vertical movement of air parcels, which is crucial for understanding atmospheric stability and its effects on weather patterns.
Stratification: Stratification refers to the layering of different physical properties within a fluid, like the atmosphere or ocean, often driven by variations in temperature, salinity, or density. This concept is crucial in understanding how these layers interact with each other and influence various atmospheric and oceanic phenomena, including energy transfer, wave formation, and turbulence.
Thermal mixing: Thermal mixing refers to the process by which warmer and cooler air masses interact, leading to the homogenization of temperature within a volume of air. This phenomenon is crucial in understanding how energy is distributed in the atmosphere and how it influences local weather patterns and turbulence. It plays a significant role in the development of atmospheric turbulence scales, impacting everything from convection to the vertical motion of air parcels.
Turbulence intensity: Turbulence intensity is a measure of the fluctuations in wind speed and direction within a turbulent flow, often expressed as the ratio of the standard deviation of the turbulent velocity components to the mean wind speed. This concept is essential in understanding atmospheric turbulence scales, as it reflects the strength and effects of turbulence on various atmospheric phenomena. Higher turbulence intensity indicates more chaotic and fluctuating airflow, which can significantly impact weather patterns, aircraft performance, and pollutant dispersion.
Turbulence kinetic energy: Turbulence kinetic energy (TKE) refers to the energy associated with the turbulent motion of fluid, representing the intensity of turbulence in a given volume of air. It is a crucial parameter in atmospheric physics, as it helps to describe how energy is transferred and dissipated within turbulent flows, influencing various atmospheric processes such as mixing, dispersion, and cloud formation.
Turbulization: Turbulization refers to the process through which flow in the atmosphere becomes turbulent, characterized by chaotic and irregular fluctuations in velocity and pressure. This phenomenon is critical in understanding atmospheric dynamics, as it plays a vital role in heat transfer, mixing, and energy dissipation within different layers of the atmosphere.
Unstable boundary layer: An unstable boundary layer is a region of the atmosphere characterized by strong vertical mixing and turbulence, typically occurring when the surface heating causes warm air to rise rapidly through cooler air above. This instability leads to enhanced convective activity and the development of turbulence, which plays a crucial role in atmospheric processes such as cloud formation and precipitation.
Wind Shear: Wind shear refers to the change in wind speed or direction with height in the atmosphere, which can have significant impacts on weather phenomena and atmospheric processes. This change can occur both horizontally and vertically, influencing pressure and density variations, the formation and behavior of cyclones and anticyclones, and the development of turbulence and mountain waves. Understanding wind shear is crucial for predicting weather patterns and assessing atmospheric stability.