Weather Forecasting - PowerPoint PPT Presentation


PPT – Weather Forecasting PowerPoint presentation | free to view - id: 43c2b4-MTk0Y


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation

Weather Forecasting


Weather Forecasting Forecasting Goal: With Respect to Severe Weather is to Minimize Impact Reduce Loss of Life and Limit Property Damage General Forecasting Notes ... – PowerPoint PPT presentation

Number of Views:182
Avg rating:3.0/5.0
Slides: 18
Provided by: JanN70


Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Weather Forecasting

Weather Forecasting
Forecasting Goal With Respect to Severe Weather
is to Minimize ImpactReduce Loss of Life and
Limit Property Damage
General Forecasting Notes
  • Four day forecasts today are about as accurate as
    two day forecasts in the 1970s
  • Improved measurement systems are part of the
  • Improvements in numerical modeling techniques are
    part of the reason
  • Speed and memory increases in computers are part
    of the reason

Forecast Methods
  • Persistence (what happened today will continue
  • Trend (temperature lowered 5 degrees in last 24
    hours, will continue tomorrow)
  • Climatology (never rains in July, wont tomorrow)
  • Interpolation (60 F at SFO, 80 at SJC so 70 at
    SQL (San Carlos))
  • Analogue
  • Weather Types (jet stream pattern looks like
    storm of Dec 95)
  • 30-90 Day Outlooks
  • Numerical Weather Prediction (NWP) Models

Numerical Weather Prediction
  • Initial Conditions
  • Surface Observations
  • Airports
  • Auto Remote Sites
  • Buoys
  • Ships
  • Upper Air
  • Radiosondes
  • Satellite Sounders
  • Parameters
  • Temperature
  • Moisture
  • Wind
  • Pressure

Numerical Weather Prediction
  • Grids
  • Horizontal
  • Vertical
  • Other Inputs
  • Topography
  • Date/Season
  • Ground Cover
  • Numerical Models
  • Time Step Forward
  • 3, 6, 12, 24, 36, 48384hrs

Scales of Weather Phenomenon
Initializing and Running a Model
  • Atmosphere is three dimensional, so both vertical
    and horizontal grids are needed
  • Vertical grids are developed on constant pressure
    surfaces (Fig 4.5)
  • Notice how grid lines are not equally spaced in
    the verticalWhy? Answer pressure does not
    decrease with height in equal proportionsgeometri
    c decrease not arithmetic
  • Horizontal grids are typically equally spaced
  • NAM (formerly called ETA) model has 60 vertical
    layers and a grid spacing of 12 km (_at_ 8 miles)
  • Can severe weather phenomena be resolved using
    such a grid? See exercise 4.1 (Noteweather
    phenomena smaller than the grid spacing can not
    be resolvedfor examplea 12 km grid can not
    resolve a 1 km tornado

How Do Models Work
  • Initialization Process
  • Measured data are interpolated to gridpoints
  • First guess (prior 12 hour forecast) data are put
    on gridpoints
  • Observations are used to adjust first guess to
  • Final mathematical adjustments are made to insure
    that data on the model grid satisfy the equations
    that govern the atmosphere

After Initialization Computational Work Begins
  • Rates of change of variables (T,WS,P) are
    evaluated from the equations and calculated over
    a period of time (dx/dt)
  • Timesteps are usually five minutes
  • Change in quantity of each variable is added to
    the initial conditions, and equations are run
  • At the end of an output timestep, say 12 hours,
    gridpoint solutions are filed and a mapping
    process is initiated

Examples of Model Development DifficultiesSnowco
  • Snow ability to radiate energy (albedo) affects
    nighttime temperaturesclear skies and snow cover
    will result in lower minimums
  • Model must be initialized with proper snow cover
    area and depth, and changes in snow cover must be
  • In reality, snow cover is derived from
    satellites, snow depth is estimated (guessed)

  • Percent of sunlight reflected from clouds and
    earth surfaces
  • Earth average albedo 30

Snow fresh Snow old Ice Water high sun Water low sun Bare earth Forest Green Crops Cities Clouds opaque Clouds - thin 75-95 40-60 70 3-5 10-50 15 5-10 15-25 14-18 50-85 5-50
General rule the lighter the surface the lower
the albedo
High albedo more sunlight reflected Low albedo
more sunlight absorbed
Examples of Model Development DifficultiesTopogr
  • Mountains have a tremendous effect on weather
    patterns, and coarse grid spacing is not
  • Gridding makes terrain features look like lego
  • Even with refined resolution, local weather for
    mountains and valleys can not be resolved

Examples of Model Development DifficultiesTopogr

Forecast Model Limitations
  • Errors in Initial Conditions
  • Measurements not made at exact gridpoints
  • Satellite derived temperatures have errors no
    RAOBS near the poles
  • Small errors grow over time and contaminate

Forecast Model Limitations
  • Inadequate Resolution
  • Narrow topographical features will be
    overlookedlocal rainfall forecasts are affected
  • Thunderstorms lake effect snowfalls and local sea
    breeze conditions may be missed

Watches and Warnings
  • Advisories
  • Less Severe
  • Dense Fog, Wind, Urban Flooding
  • Watches
  • Possible Severe Weather (could happen)
  • Tornadoes, Severe Thunderstorms, Flash Flooding
  • Warnings
  • Probable Severe Weather (are happening)
  • Tornadoes, Severe Thunderstorms, Flash Flooding