WEATHER FORECASTING Acquisition of Weather Information WFO Regions Weather Forecasting Tools Weather Forecasting Tools Weather Forecasting Methods

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Gertrude Reed
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1 WEATHER FORECASTING Chapter 13 Acquisition of Weather Information 10,000 land-based stations, hundreds of ships and buoys; four times a day, airports hourly Upper level: radiosonde, aircraft, satellites United Nations World Meteorological Organization, 175 countries NCEP collects and distributes data US NWS- Silver Spring, MD 122 local weather forecast offices ASOS: 900 stations at airports in US Some TV and radio stations hire meteorologists, others just use the NWS forecasts. WFO Regions Weather Forecasting Tools NWS uses high speed data modeling systems Advance Weather Interactive Processing System AWIPS Communication, storage, processing, and display Doppler radar Satellite imagery Forecast charts Soundings Wind profiles Weather Forecasting Tools Topic: Watches, Warnings, and Advisories Advisories: potential hazardous conditions; wind, wind chill, heat, urban and small stream, snow, dense fog Watch: atmospheric conditions favoring hazardous weather over a region in time, actual location and time not known; flash flood, severe thunderstorm, tornado, hurricane Warning: imminent or occurring hazardous weather over a region in time; high wind, heat, flash flood, severe storm, tornado, hurricane, winter storm, blizzard, gale, storm 1

2 tornado, hurricane, winter storm, blizzard, gale, storm 1950s: maps, charts plotted by hand Numerical weather prediction Solves equations using gridded data Final chart called prognostic charts or progs 24 hr forecast for the N Hemisphere requires millions of calculations Resolution Guidance/ rules of thumb Topic: Thickness Charts Difference in height between two constant pressure surfaces (100mb-500mb) Higher thickness equals warmer air 5400 m thickness separates rain from snow. Why Forecast Go Awry Assumptions: Progs idealize the atmosphere Models not global Regions with few observations Cannot model small-scale features Grid point spacing: 100 km down to 0.5 km More grid points take more calculations Half the grid spacing yields 8 times as many computations, 16 times as long. All factors cannot be modeled E.g. interactions of water, ice, surface friction, local terrain Chaos: sensitivity to initial conditions The Butterfly Effect Edward Lorenz, 1963: "One meteorologist remarked that if the theory were correct, one flap of a seagull's wings could change the course of weather forever." 2

3 Other Forecasting Techniques Persistence: How long will things stay the same? Steady-State (Trend): Constant motion Analogue: What have current conditions produced in the past? Statistical: Computers make statistically-weighted analogue predictions Sixty percent chance of rain Weather types: Groups of weather patterns generate analogue predictions Climatological: Relies on knowledge of the area s climate. It s not going to rain in Los Angeles on July 4 th. Observation: Weathercasters Chroma key or color separation Types of Forecasts: Now cast <6 hrs Short range hrs Medium range days Long Range >8.5 days Accuracy and Skill hrs most accurate, 2-5 days good Skill = more accurate than a forecast utilizing persistence of climatology Forecasting Temperature Advection by Watching the Clouds Winds that back with height (change ccw) indicate cold advection, rain to snow. Winds that veer with height (change cw) indicate warm advection, snow to rain. Weather Forecasting Using Surface Charts Movement of Weather Systems 3

4 Movement of Weather Systems 1. Mid-lat cyclones move in same direction and speed as previous 6 hrs 2. Lows move in direction parallel the isobars in the warm air ahead of the cold front 3. Lows move toward region of greatest pressure drop Weather Forecasting Using Surface Charts Forecast August GA, p. 359 Washington DC Chicago Memphis Dallas Denver Chart Commentary A complete picture of surface weather systems is given on the chart. By comparing this chart with the prediction we can summarize why our forecasts did not turn out exactly as we had predicted. For one thing, the storm center near the Great Lakes moved slower than expected. This slow movement allowed a southeasterly flow of mild Atlantic air to overrun cooler surface air ahead of the sotrm while, behind the low, cities remained in the snow area for a longer time. The weak wave that developed along the trailing cold front over Texas brought cloudiness and precipitation to Texas and prevented the really cold air from penetrating deep into the south. Farther west, the high-pressure area originally over Montana moved more southerly than southeasterly, which set up a pressure gradient that brought westerly downslope winds to eastern Colorado. 4

5 eastern Colorado. Going Deep: A Meteorologist Makes a Prediction for San Francisco 500mb chart 5640m height Blocking high Gradient and advection Computer Model Valid Forecast Satellite Day of Rain and Wind Homework for Chapter 13 Chapter 13 Questions for Review, p. 368 #1, 2, 4-7, 12, 13, 18 Chapter 13 Questions for Thought, p. 368 #1, 4 Chapter 13 Problems and Exercises, p. 368 None Project for Chapter 13 Use Appendix E to make weather predictions for Seward every day for one week, April (make first prediction 4/17. Use weather data at 4:00 pm. Use data from the CUNE weather station. Track your predictions with a table that includes: Pressure Pressure Tendency Surface Wind Direction Sky Condition Forecast Actual Conditions 5

6 Actual Conditions Project is due Wednesday, April 27,

Weather Forecasting. March 26, 2009

Weather Forecasting. March 26, 2009 Weather Forecasting Chapter 13 March 26, 2009 Forecasting The process of inferring weather from a blend of data, understanding, climatology, and solutions of the governing equations Requires an analysis