WEATHER FORECASTING

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WEATHER FORECASTING

• A Scientific Look into the Future.

Prepared by Margaret Milligan, July 5, 2005
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HISTORY OF FORECASTING

• Weather forecasting began with early
  civilizations using reoccurring astronomical and
  meteorological events to monitor seasonal changes
  in the weather.
• By 300 BC the Chinese developed a calendar which
  divided the year into 24 festivals, with each
  festival celebrating a different type of weather.
• Aristotle's ideas in the text Meteorologica stuck
  for almost 2000 years even though many claims
  were erroneous.
• The Renaissance brought about the first types of
  instruments used to measure factors affecting
  weather.
• The 19th Century saw a global compilation of
  weather data and the beginning of more accurate
  forecasting.

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HISTORY OF FORECASTINGIN THE UNITED STATES

• National Weather Organization set up in 1870
  under the Secretary of War to forecast storms in
  the Great Lakes and Atlantic Seaboard. Done in
  order to cut down on shipping loses.
• United States Army Signal Service
• continued to grow and spread
• across the country.
• Interested in more history and
• application of weather forecasting?
• Check out Issacs Storm by
• Erik Larson

A Man, a Time, and the Deadliest Hurricane in
History
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FORECASTING METHODS

• Persistance Method Hot today, Hot tomorrow.
• - Basically used for short term forecasting.
• - Works well in areas where there are little
• changes day to day. ie California
• - Can be accurate in long term forecasting.
• A hot and dry month will most likely be
• followed by another hot and dry month.
• Trends Method Math in action!
• - Uses math to make predictions.
• - A storm is 1000 miles away moving at
• 250 mph. The trends method would predict
• stormy weather in 4 days.
• - Works best with systems moving with a
• consistent velocity.

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FORECASTING METHODS

• Climatology
• - Use years of data to predict what type of
  weather will occur on certain days.
• - Works well in areas of predictable weather
  patterns. Not accurate in day to day weather.
• Analog Method
• - Looking at todays weather and comparing it to
  weather in the past.
• - Today is warm, but a cold front is
  approaching. The previous cold front produced
  stormy weather, so storms are forecasted again.
• - Hard to be accurate because of natural
  variations in weather systems.
• Numerical Weather Prediction
• - Use of computer programs to make a forecast.
• - Programs provide predictions of temperature,
  pressure, wind, and rainfall. These features
  used to predict the weather of the day.
• - Flaws include incomplete data or incorrect
  equations in program, which lead to flawed
  forecasts. BEST OF THE FIVE TYPES!

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SURFACE FEATURES

• There are key surface features which need to be
  observed in order to make an accurate forecast.
• Anticyclones (high pressure)
• Cyclones (low pressure)
• Cold, Warm, Stationary, and Occluded Fronts
• Dry Lines
• Clouds
• Temperature
• Moisture/Precipitation

A dry line forming west of Texas. Dry lines are
extremely rare east of the Mississippi.
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SURFACE FEATURES

• ANTICYCLONES (HIGH)
• Brings clam, fair weather
• Air moves away from center of high, sinking air
  replaces it
• Temperature depends on location relative to high
• Northerly winds cooler
• Southerly winds warmer

• CYCLONES (LOWS)
• Brings stormy, unsettled weather
• Air moves towards center of low, causes air to
  rise
• Rising motion may result in clouds and
  precipitation.
• Lows are associated with fronts

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SURFACE FEATURES

• Warm Fronts
• Warm air replacing cool air
• Light intensity precipitation
• seen in front of and behind the front in large
  area

• Cold Fronts
• Cold air replacing
• warm air.
• Warm air lifted and cooled, moisture condenses to
  form clouds and precipitation.

• Stationary Fronts
• Non moving front.
• Separate warm and cool air masses.
• Can be the beginning of cyclone (see Norwegian
  Cyclone Model)

• Occluded Fronts
• Occur when a cold front catches a warm front
• Cuts off supply of
• warm, moist air
• Death of cyclone

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NORWEGIAN CYCLONE MODEL

• 1. Stationary front forms separating warm and
  cool air masses

2. A wave develops on the front and
precipitation begins to form

• 4. Mature low pressure system. Occluded front,
  system dissipates

3. The wave intensifies and cold and warm fronts
organize
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SURFACE FEATURES

• Dry Lines
• Boundary between a moist air mass and a dry air
  mass
• Dry air can cause moist air to rise and clouds
  and precipitation develop similar to cold front

• Clouds
• Day Clear warmer temps predicted
• Day Cloud cooler temps predicted
• Night Clear cooler temps
• Night Cloudy warmer temps

• Temperature
• When forecasting, look at stations upsteam
• Warm air advection warmer temps
• Cold air advection cooler temps

• Moisture
• Even if lifting is occurring, precipitation will
  not occur if dew points are too low.

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REMOTE SENSING

• The science of obtaining information about a
  subject without being in contact with the
  subject.
• Weather forecasting uses devises sensitive to
  electromagnetic energy such as
• Light (satellite)
• Heat (infrared scanning on satellites)
• Radio waves Doppler Radar

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REMOTE SENSING

• Doppler Radar
• Radio antenna turns and sends out radio waves
• with short listening periods between pulses.
• The amount of time needed for wave to return
  tells us distance to object.
• Returns in clear air can tell us a lot also.
• Radar waves hitting bugs can inform us of air
  
• motion and wind direction.
• Most often used to ID precipitation.
• As seen in the image to the left,
  areas of greater precipitation are shown
  in reds and pinks, while blues blue and
  greens represent light precipitation.
  High reflectivity (grey) represents hail.

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REMOTE SENSING

• Doppler Radar
• Most used to determine wind direction and
  possible tornados within severe storms.
• Air moving towards the radar are shaded green
  while air moving away from the radar are shaded
  red.
• Tornados form in areas where the wind is blowing
  in opposite directions over a small distance. A
  tornado developed six minutes after the radar
• image to the right was taken. It formed
• in the area near the bright green patch.

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REMOTE SENSING

• REFLECTIVE IMAGE

• STORM RELATIVE VELOCITY

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REMOTE SENSING

• Satellites
• Polar Orbiting Satellite (POES)
• Close to the earth, detailed images, views of
  polar regions
• Cant see whole surface, orbit changes due to
  Earths rotation, 6 6 to 7 images a day
• Geostationary Orbiting Satellite (GOES)
• Same spot in sky relative to earth, views entire
  surface, fast imaging, view motion on Earth, can
  collect data from stations.
• Far from earth, loss of detail, limited view of
  polar region.

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REMOTE SENSING
Satellites Types of Images

• Visible Imagery
• An image of the Earth in visible light
• Detects reflected sunlight, thick clouds appear
  brighter.
• Excellent for detecting developing thunderstorms

• Infrared Imagery
• An image using Infrared light.
• Senses radiant heat given off by clouds.
• Used for detecting clouds and thunderstorms when
  sunlight is not present.

• Water Vapor Imagery
• Detects water vapor in addition to clouds.
• Only sees top third of Troposphere
• Moist areas are white, dry areas are black

• Derived Satellite Images
• Example Lifted Index
• Shows instability present in the atmosphere.
• Can predict where storms may form.

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REMOTE SENSING
Satellites Types of Images, Tropical Storm
Isidore

• Visible Imagery

• Infrared Imagery

• Water Vapor Imagery

• Derived Satellite Images

Light blue Very Stable Green Stable Yellow
Slightly Unstable Orange Unstable Red Very
Unstable Pink Extremely Unstable Thunderstorms
likely orange and above, Severe if lifting
mechanism present.
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REMOTE SENSING

• Automated Surface Observing Systems (ASOS)
• Works non-stop, 24 hours a day, updating every
  minute
• Reports the following information
• Sky conditions such as cloud height and cloud
  amount up to 12,000 feet,
• Surface visibility up to at least 10 statute
  miles,
• Basic present weather information such as the
  type and intensity for rain, snow, and freezing
  rain,
• Obstructions to vision like fog, haze, and/or
  dust,
• Sea-level pressure and altimeter settings,
• Air and dew point temperatures,
• Wind direction, speed and character (gusts,
  squalls),
• Precipitation accumulation
• Selected significant remarks including- variable
  cloud height, variable visibility, precipitation
  beginning/ending times, rapid pressure changes,
  pressure change tendency, wind shift, peak wind.

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REMOTE SENSING

• Radiosondes
• A small instrument package attached to a balloon.
• The balloon lifts the package as measurements
• are taken.
• Information is sent back to weather station and
• data is recorded.
• The data is used for
• Input for computer-based weather prediction
  models,
• Local severe storm, aviation, and marine
  forecasts
• Weather and climate change research
• Input for air pollution research
• Ground truth for satellite data.

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FORECASTING IN ACTION

• IBMs Deep Thunder is a computer program that can
  make short term weather predictions based on data
  from weather stations.
• Deep thunder created the following 3D images of
  forecasted thunderstorms at 8pm on May 31, 2005
  in New York.
• Deep Thunder Animation

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FORECASTING IN ACTION

• Forecasts predicted a warm and humid day. Deep
  Thunder predicted storms late in the day as a
  cold front approached.
• The following animation shows a shift in winds,
  lifting, and formation of thunderstorms.
• Deep Thunders predictions were only off by 30
  minutes. All other predictions, including area
  of rain, rainfall totals, and wind directions,
  were accurate.
• Rain and wind animation

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THE FUTURE OF FORECASTING

• Scientists are striving to increase warning time
  for severe weather such as tornados and flash
  floods with the help of forecasting technology.
  More accurate forecasting can continue to help
  forecast the path of tropical cyclones.
• In its simplest form, weather forecasting is used
  for day to day living.
• Long term forecasts can predict droughts, rainy
  periods, frost, and other important weather
  affecting agriculture.
• Historical forecasts and data can be used to
• determine changes in climate and its effect
• on an ecosystem.

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WEATHER FORECASTING

• FORECASTING WEBSITES
• The Weather Channel
• Weather Underground
• WeatherBug
• National Weather Service

• LESSON PLANS
• Forecasting Grades 2-6
• Weather Forecasting Grades 6-8
• Weather Patterns Grade 4-8
• Kids as Global Scientists Grade 6-8
• Weather Forecasting Research Grade 6-8

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RESOURCES

• INTERNET RESOURCES
• University of Illinois Online Weather Guides
• USA Today Weather Forecasting
• JetStream An Online Weather School
• The Weather Channel
• National Weather Service
• National Geographic Fire and Rain, Forecasting
  the Chaos of Weather
• Weather Forecasting Through the Ages (NASA)
• Economic History of Weather Forecasting
• TEXT RESOURCES
• National Geographic June 2005
• The Atmosphere, 7th Edition (Lutgens and Tarbuck)
• Isaacs Storm (Larson)
• The Usborne Internet-linked Science Encyclopedia
• Online Weather Studies, 2nd Edition (Moran)