Transcript Weather Forecasting - Michigan State University

WEATHER FORECASTING
A Scientific Look into the Future.
Prepared by: Margaret Milligan, July 5, 2005
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.
HISTORY OF FORECASTING
IN 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: Issac’s Storm by
Erik Larson
“A Man, a Time, and the Deadliest Hurricane in History”
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.
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 today’s 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!
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.
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
SURFACE FEATURES
• 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)
• Warm Fronts
Warm air replacing cool air
Light intensity precipitation
seen in front of and behind the
front in large area
• Occluded Fronts
Occur when a cold front “catches”
a warm front
Cuts off supply of
warm, moist air
Death of cyclone
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
3. The wave intensifies and cold
and warm fronts organize
4. Mature low pressure system.
Occluded front, system dissipates
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.
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
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.
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.
REMOTE SENSING
REFLECTIVE IMAGE
STORM RELATIVE VELOCITY
REMOTE SENSING
• Satellites
– Polar Orbiting Satellite (POES)
• Close to the earth, detailed images, views of polar regions
• Can’t see whole surface, orbit changes due to Earth’s 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.
REMOTE SENSING
Satellites: Types of Images
• Visible Imagery
• Infrared Imagery
An image of the Earth in visible light
Detects reflected sunlight, thick clouds
appear brighter.
Excellent for detecting developing
thunderstorms
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
• Derived Satellite Images
Detects water vapor in addition to
clouds.
Only “sees” top third of Troposphere
Example: Lifted Index
Shows instability present in the
atmosphere.
Can predict where storms may
form.
Moist areas are white, dry areas are
black
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.
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.
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.
FORECASTING IN ACTION
• IBM’s 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
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 Thunder’s 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
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.
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
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)
Isaac’s Storm (Larson)
The Usborne Internet-linked Science Encyclopedia
Online Weather Studies, 2nd Edition (Moran)