Meteorology Forecast Applications Aviation Meteorology Wave Forecasting Atmospheric
- Slides: 39
Meteorology Forecast Applications • • Aviation Meteorology Wave Forecasting Atmospheric Dispersion Decision Support Systems The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Aviation Meteorology Weather Conditions Important Element in Safety Take Off/landing and Enroute Weather Cloud Type - Amount and Height of Ceiling Wind Speed and Direction Terminal Forecasts (Tafs), Metars Wind Shear, Clear Air Turbulence (CAT), Thunderstorms, Visibility, Fog, Icing, Cumulonimbus (Cb), Mountain Waves The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Turbulence • Wind shear – usually in vicinity of jet stream • Horizontal > 30 kt deg-1 latitude (60 nm) • Vertical > 09 kt 300 m -1 • • • Near thermal gradients of >2. 5°C deg-1 latitude In anticyclonic curvature with winds of >130 kt Upper air troughs where wind shift > 90 ° In cols where wind direction can reverse rapidly Topography – CAT reported twice as often over land than at sea The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
300 h. Pa Aviation Route Wind Map The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Icing • Occurs in clouds when temperature <0 °C, supercooled droplets build up on an airplane and freeze. • Supercooled Liquid Water (SLW) can exist in clouds at -15 °C, below this ice crystals grow rapidly • Occurs in deep convection scenariios (e. g. Cb) • Occurs where there are strong thermal gradients i. e. near upper air fronts The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Mountain Waves 1. In very stable conditions with light winds, the air will tend to flow around a hill 2. In neutral conditions with strong winds, a turbulent wake develops behind the hill The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Mountain Waves In stable conditions perturbed parcels oscillate at a characteristic frequency For certain windspeeds the air has a natural wavelength When that wavelength matches the height of the hill, a natural resonance occurs The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Mountain Waves CHARACTERISTIC WAVELENGTH The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Mountain Waves WIND DIRECTION IS PERPENDICULAR TO THE RIDGE THE LEE WAVES ARE PARALLEL TO THE RIDGE > 15 kts The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Mountain Waves Conditions: • • Orography A stable layer aloft Wind speed of >15 knots Uniform wind direction to the top of the stable layer Lee Wave Clouds The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Example of Mountain Waves The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Aviation Significant Weather map The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Marine Meteorology – Waves • A wave starts when the wind interacts with the water surface and created a disturbance. • As the wind continues forcing the wave grows and begins to move. • Eventually the wave moves outside of the area of initial wind forcing and propagates across the water. (Swell) The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Waves – Limiting Factors There are three basic components to wave growth: • Wind speed • Fetch or fetch length • Duration Fetch is the distance over which the wind blows from a constant direction and at a constant speed. Duration is how long the wind affects that distance. The Wave Analysis and Forecasting Nomogram quantitatively illustrates the relationship between wind speed, wind duration, fetch length, and wave growth The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
The Wave Analysis and Forecasting Nomogram • Wind speed is charted on the y-axis and fetch length on the x-axis. Contour lines represent wind duration, wave height and wave period The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
The Wave Model - WAM • The nature of waves is chaotic, Numerical methods allow a better approach based on the energy spectrum • The sea surface may be represented as a Fourier series of superimposed waves with different wave lengths and statistically random phases The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
WAM Model Output The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Atmospheric Dispersion Modelling Applications Factors Influencing Dispersion • • • Wind speed and direction Stability (mechanical turbulence, buoyancy) Boundary layer depth The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Stability Effects Neutral conditions Stable conditions Unstable conditions The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Atmospheric Dispersion Models § NWP Models provide wind fields etc. § Lagrangian Particle Dispersion Models • • § Individual particles are tracked (Wind and turbulence needed from NWP Large quantity of release particles to get concentration Gaussian Dispersion Models • • Simple statistical based calculations of concentration Release and sample times large compared to travel time (approximately steady state) Horizontal and vertical dispersion is Gaussian distributed Wind speed and direction constant with height (layer approach The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Gaussian Dispersion Models Instantaneous point source with isotropic diffusion (puff) and transport with wind speed u away from source The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
The Irish Meteorological Service www. met. ie T. Mikkelson et al. : Airborne Spread: Modelling Accuracy and Predictive Value UCD Forecasting Course June 2006
Applications: Airborne Spread of Foot and Mouth Virus Depends on: • Virus emission (pigs have highest 106 , sheep and cattle lowest 103 TICP 50 per min - bovine thyroid tissue culture infections units) • Virus survival (RH>60% several hours) • Virus dispersion • Virus deposition (direct contact through inhalation: cattle large intake, sheep and pigs small intake) The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Foot and Mouth Dispersion uses NWP data: • U 10, RH and rain from the nearest grid point x~15 km • Direct predictions of surface heat flux, friction velocity, stability and boundary layer depth (turbulent flux profiles) The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Output of FMD model The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
G Mc. GRath, RF Hammond, K Towey: GIS Integration and Utilisation The Irish Meteorological Service www. met. ie of the of Foot and Mouth Dispersion Model UCD Forecasting Course June 2006
Applications: Dispersion from Nuclear Accidents The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Applications: Rimpuff Dispersion Model RPII (Radio Protection Institute of Ireland) run a dispersion model with input data from Met Éireann: • Hourly NWP output of fields at 20 levels of • 3 D wind speed and direction, geopotential height • 2 D boundary layer height, rainfall • Surface description: lat/lon, roughness length, land fraction The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
• ARGOS (Accident Reporting Guidelines and Operational Systems interface) • Developed by DEMA (Danish Emergency Management Agency) • Used in Denmark, Norway, Canada, Ireland • Plume trajectory model (<200 km) RIMPUFF (RIso Mesoscale PUFF) • time integrated concentration of 63 radio nuclides The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Decision Support Systems • Need Conceptual Model to describe system which is dependent on weather parameters • Input of relevant weather parameters • Interpretation of result • Examples Potato Blight, Soil Moisture Deficits, Fire Weather Index, Road Ice Prediction The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Potato Blight (May-September) Warm Humid weather favours the spread of fungal diseases: Conceptual Model Irish Blight Rules require: T >10 ºC and RH >90 % for 12 hours if wet and 16 hours if dry, for development of blight. ……but farmers must spray before the onsest of blight conditions Warning are issued 2 days ahead of spell if possible The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
NWP Application of Blight rules The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Road Ice Prediction • Over 50 sites located around the country • Weather data and NWP ouptut fed into Icebreak prediction model • Graphs and maps produced of forecast road surface temperatures and road state. The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Cooling at road surface Non Radiation Energy Balance • Latent Heat • Evaporation(loss) • Condensation (gain) • Convection (Sensible heat) • Loss by day, gain by night • Traffic Flow • Conduction from ground These last two parameters are measurable and will be different for each site. Bridges are prone to low Temperatures Constant Physical parameters for each roadside station are used in the model and are contained in Local Information Files (LIF) The Irish Meteorological Service www. met. ie UCD Forecasting Course June 2006
Input into Icebreak Model Hirlam Model is run every 6 hours. • Model grid size 15 X 15 km. • Direct output in 3 hour steps is used as a first guess. • Data manipulated by forecaster • No manual intervention if expected Troad > 5° Celsius. Icebreak Output • Site specific graphical forecasts • Short and long range text forecasts • Thermal Map Forecasts
UCD Forecasting Course June 2006
UCD Forecasting Course June 2006
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