Introduction to Weather Forecasting

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Introduction to Weather Forecasting
Cliff Mass Department of Atmospheric
Sciences University of Washington
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The Stone Age

• Prior to approximately 1955, weather forecasting
  was basically a subjective art, and not very
  skillful.
• The technology of forecasting was basically
  subjective extrapolation of weather systems, in
  the latter years using the upper level flow (the
  jet stream).
• Local weather detailswhich really werent
  understood-- were added subjectively.

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Upper Level Chart
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The Development of Numerical Weather Prediction
(NWP)

• Vilhelm Bjerknes in his landmark paper of 1904
  suggested that NWP--objective weather
  prediction-- was possible.
• A closed set of equations existed that could
  predict the future atmosphere
• But it wasnt practical then because there was no
  reasonable way to do the computations and a
  sufficient 3-D description of the atmosphere did
  not exist.

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Numerical Weather Prediction

• One such equation is Newtons Second Law
• F ma
• Force mass x acceleration
• Mass is the amount of matter
• Acceleration is how velocity changes with time
• Force is a push or pull on some object (e.g.,
  gravitational force, pressure forces, friction)

Using observations we can determine the mass and
forces, and thus can calculate the
acceleration--giving the future
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NWP Becomes Possible

• By the 1940s an extensive upper air network was
  in place, plus many more surface observations.
  Thus, a reasonable 3-D description of the
  atmosphere was possible.
• By the mid to late 1940s, digital programmable
  computers were becoming availablethe first..the
  ENIAC

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The Eniac
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1955-1965 The Advent of Modern Forecasting

• Numerical weather prediction became the
  cornerstone.
• New observing technologies also had a huge
  impact
• Weather satellites
• Weather radar

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Satellite and Weather Radars Provides a More
Comprehensive View of the Atmosphere
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Camano Island Weather Radar
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Weather Prediction Steps

• Data collection and quality control
• Data assimilation creating a physically
  realistic 3-D description of the atmosphere
  called the initialization.
• Model integration. Solving the equations to
  produce future 3D descriptions of the atmosphere
• Model output post-processing using statistical
  methods
• Dissemination and communication

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Initialization
Using a wide range of weather observations we can
create a three-dimensional description of the
atmosphere
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Numerical Weather Prediction

• The observations are interpolated to a 3-D grid
  where they are integrated into the future using a
  computer model--the collection of equations and a
  method for solving them.
• As computer speed increased, the number of grid
  points could be increased.
• More (and thus) closer grid points means we can
  simulate (forecast) smaller and smaller scale
  features. We call this improved resolution.

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Model Postprocessing in the U.S. Model Output
Statistics (MOS)

• Main post-processing approach used by the
  National Weather Service
• Based on linear regression Ya0 a1X1 a2X2
  a3X3
• MOS is available for many parameters and time and
  greatly improves the quality of most model
  predictions.

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Prob. Of Precip. Cool Season(0000/1200 UTC
Cycles Combined)
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Major Improvement

• Weather forecasting skill has substantially
  improved over the last 50 years. Really.

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Forecast Skill Improvement
National Weather Service
Forecast Error
Better
Year
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Why Large Improvement in Weather Forecast Skill?

• As computers became faster, were able to solve
  the equations at higher resolution
• Improved physics
• New observational assets allowed a better
  initialization

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A More Basic Problem

• There is fundamental uncertainty in weather
  forecasts that can not be ignored.
• This uncertainty has a number of causes
• Uncertainty in initialization
• Uncertainty in model physics
• Uncertainties in how we solve the equations
• Insufficient resolution to properly model
  atmospheric features.

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The Atmospheric is Chaotic

• The work of Lorenz (1963, 1965, 1968)
  demonstrated that the atmosphere is a chaotic
  system, in which small differences in the
  initializationwell within observational error
  can have large impacts on the forecasts,
  particularly for longer forecasts.
• Not unlike a pinball game.

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Probabilistic Prediction

• Thus, forecasts must be provided in a
  probabilistic framework, not the deterministic
  single answer approach that has dominated weather
  prediction during the last century.
• Interestinglythe first public forecasts were
  probabilistic

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Ol Probs
Cleveland Abbe (Ol Probabilities), who led the
establishment of a weather forecasting division
within the U.S. Army Signal Corps. Produced the
first known communication of a weather
probability to users and the public in 1869.
Professor Cleveland Abbe, who issued the first
public Weather Synopsis and Probabilities on
February 19, 1871
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Ensemble Prediction

• The most prevalent approach for producing
  probabilistic forecasts and uncertainty
  informationensemble prediction.
• Instead of making one forecastmake manyeach
  with a slightly different initialization or
  varied model physics.
• Possible to do now with the vastly greater
  computation resources that are now available.

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Verification
The Thanksgiving Forecast 2001 42h forecast
(valid Thu 10AM)
SLP and winds

• Reveals high uncertainty in storm track and
  intensity
• Indicates low probability of Puget Sound wind
  event

1 cent
11 ngps
5 ngps
8 eta
2 eta
3 ukmo
12 cmcg
9 ukmo
6 cmcg
4 tcwb
13 avn
10 tcwb
7 avn
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Ensemble Prediction

• Can use ensembles to provide a new generation of
  products that give the probabilities that some
  weather feature will occur.
• Can also predict forecast skill.
• It appears that when forecasts are similar,
  forecast skill is higher.
• When forecasts differ greatly, forecast skill is
  less.

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Ensemble-Based Probabilistic Products
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Ensemble Post-Processing

• To get the maximum benefits from ensembles,
  post-processing is needed, such as
• Correction for systematic bias
• Optimal weighting of the various ensemble
  members--e.g., Bayesian Model Averaging

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The UW-MURI Project

• Possibility the most advanced ensemble/postprocess
  ing system in the world has been developed at the
  UW
• Includes UW Atmospheric Sciences, Statistics,
  Psychology, and Applied Physics Lab
• Remaining talks will describe some of the
  research and development completed by this effort.

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Providing forecast uncertainty information is
good.
But you can have too much of a good thing
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The END