A Brief History of Weather Forecasting

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A Brief History of Weather Forecasting
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The Stone Age

• Prior to approximately 1955, forecasting was
  basically a subjective art, and not very
  skillful.
• Observations were sparse, with only a few
  scattered ship reports over the oceans.
• The technology of forecasting was basically
  subjective extrapolation of weather systems 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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1955-1965 The Advent of Modern Forecasting

• During this period, numerical weather
  predictionforecasting future weather with
  digital computers-- became the key tool in the
  meteorologists tool bag.
• The launch of the first weather satellite (1960)
  gave meteorologists a view of the entire planet.
• Weather radars were placed around the U.S.
  explicitly showing areas of precipitation.

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Numerical Weather Prediction

• The advent of digital computers in the late 1940s
  and early 1950s made possible the simulation of
  atmospheric evolution numerically.
• The basic idea is if you understand the current
  state of the atmosphere, you can predict the
  future using the basic physical equations that
  describe the atmosphere.

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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)

This equation is a time machine!
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Numerical Weather Prediction
Using a wide range of weather observations we can
create a three-dimensional description of the
atmosphere known as the initialization
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Numerical Weather Prediction

• This gives the distribution of mass and allows us
  to calculate the various forces.
• Then we can solve for the acceleration using
  Fma
• But this gives us the future. With the
  acceleration we can calculate the velocities in
  the future.
• Similar idea with temperature and humidity.

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Numerical Weather Prediction

• These equations can be solved on a
  three-dimensional grid.
• 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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A Steady Improvement

• Faster computers and better understanding of the
  atmosphere, allowed a better representation of
  important physical processes in the models
• More and more data became available for
  initialization
• As a result there has been a steady increase in
  forecast skill from 1960 to now.

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Forecast Skill Improvement
National Weather Service
Forecast Error
Better
Year
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Satellite and Weather Radars Give Us a More
Comprehensive View of the Atmosphere
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Camano Island Weather Radar
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1995-2003The computers models become capable of
simulating/forecasting local weather.

• As the grid spacing decreased to 15 km and below
  it became apparent that many of the local weather
  features could often be simulated and forecast by
  the models.

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The National Weather Service
Forecaster at the Seattle National Weather
Service Office
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But even with all this improving technology, some
forecasts fail or are inadequate. Why?
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Problems with the Models

• Some forecasts fail due to inadequacies in model
  physics. How the model handles precipitation,
  friction, and other processes.
• Example too much precipitation on mountain
  slopes
• Intensive work at the UW to address this problems.

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Some forecasts fail due to poor initialization,
i.e., a poor starting description of the
atmosphere.

• This is particularly a problem for the Pacific
  Northwest, because we are downstream of a
  relatively data poor regionthe Pacific Ocean.

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3 March 1999 Forecast a snowstorm got a
windstorm instead
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Eta Model Sea Level Pressure 12 UTC 2 March 99
Major Initialization Errors
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Pacific Analysis At 4 PM 18 November 2003
Bad Observation
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The problem of initialization should lessen as
new observation technologies come on line and
mature.New ways of using or assimilating the
data are also being developed.
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Seascan Unmanned Aircraft
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Lack of Coastal Weather Information

• There is a lack of detailed weather information
  immediately off the Northwest Coast.
• Major issue lack of a coastal weather radar.
• The Northwest has the worst coastal weather radar
  coverage in the nation.
• Often cant see the details of weather features
  before they make landfall. Seriously impacts
  short-term forecasts.

NWS Doppler Radar
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Now
With Two New Radars
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A More Fundamental Problem

• In a real sense, the way we have been forecasting
  is essentially flawed.
• 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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A More Fundamental Problem

• Thus, there is fundamental uncertainty in weather
  forecasts that can not be ignored.
• Similarly, uncertainty in our model physics also
  produces uncertainty in the forecasts.
• We should be using probabilities for all our
  forecasts or at least providing the range of
  possibilities.
• There is an approach to handling this issue that
  is being explored by the forecasting
  communityensemble forecasts.

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Ensemble Prediction

• Instead of making one forecastmake manyeach
  with a slightly different initialization
• Possible to do now with the vastly greater
  computation resources that are 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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Forecast Dissemination The Achilles Heal

• Although the technology of weather prediction is
  rapidly improving, our ability to communicate
  what we know to the public is inadequate.
• Although the Internet and wireless communication
  providesfor the first timethe potential to
  distribute large amounts of weather information,
  we have not yet found an effective way to do so.
• The amount of information is massive, how do we
  distill and filter it for a wide variety of
  users?
• We are failing to communicate our degree of
  confidence in the forecasts.