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WEATHER FORECASTING. Prepared by: Margaret Milligan, July 5, 2005. A Scientific Look into the Future. HISTORY OF FORECASTING. Weather forecasting began with early civilizations using reoccurring astronomical and meteorological events to monitor seasonal changes in the weather.
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WEATHER FORECASTING Prepared by: Margaret Milligan, July 5, 2005 A Scientific Look into the Future.
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 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: 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.
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
SURFACE FEATURES • Warm Fronts Warm air replacing cool air Light intensity precipitation seen in front of and behind the front in large area • 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 • Cold Fronts Cold air replacing warm air. Warm air lifted and cooled, moisture condenses to form clouds and precipitation.
NORWEGIAN CYCLONE MODEL 1. Stationary front forms separating warm and cool air masses 4. Mature low pressure system. Occluded front, system dissipates 2. A wave develops on the front and precipitation begins to form 3. The wave intensifies and cold and warm fronts organize
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 • 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. Satellites: Types of Images
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)