A Brief History of Weather Forecasting - PowerPoint PPT Presentation

1 / 38
About This Presentation
Title:

A Brief History of Weather Forecasting

Description:

Prior to approximately 1960, forecasting was basically a subjective art, and not ... first weather satellite (1960) gave meteorologists a view of the entire planet. ... – PowerPoint PPT presentation

Number of Views:101
Avg rating:3.0/5.0
Slides: 39
Provided by: Cliff51
Category:

less

Transcript and Presenter's Notes

Title: A Brief History of Weather Forecasting


1
A Brief History of Weather Forecasting
2
The Stone Age
  • Prior to approximately 1960, 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)

3
Upper Level Chart
4
1955-1965 The Advent of Modern Numerical
Forecasting
  • 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.

5
Satellite and Weather Radars Give Us a More
Comprehensive View of the Atmosphere
6
Camano Island Weather Radar
7
Numerical Weather Prediction
  • During this period, numerical weather
    predictionforecasting future weather with
    digital computers-- became meteorologists
    central tool.
  • The advent of digital computers in the late 1940s
    and early 1950s made possible the simulation of
    atmospheric evolution numerically.

The Eniac The first programmable digital computer
8
Numerical Weather Prediction
  • The basic idea is if you can describe the
    current state of the atmosphere (known as the
    initialization) , you can predict the future
    using the equations that describe the physics of
    the atmosphere.

9
The Initialization
Using a wide range of weather observations we can
create a three-dimensional description of the
atmosphere
10
Numerical Weather Prediction
  • One of the equations used to predict the weather
    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)

11
This equation is a time machine!
12
F ma
  • The initialization gives the distribution of mass
    (how much air there is and where) and allows us
    to calculate the various forces.
  • Then we can solve for the acceleration using
    Fma
  • With the acceleration we can calculate the
    velocities in the future.
  • Similar idea with temperature and humidity but
    with different equations.

13
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.

14
A Steady Improvement over the Past 50 years
  • 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.

15
Forecast Skill Improvement
National Weather Service
Forecast Error
Better
Year
16
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.

17
(No Transcript)
18
(No Transcript)
19
(No Transcript)
20
(No Transcript)
21
But even with all this improving technology, some
forecasts fail. Why?
22
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

23
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.

24
Pacific Analysis At 4 PM 18 November 2003
Bad Observation
25
3 March 1999 Forecast a snowstorm got a
windstorm instead
26
The problem of initialization should lessen as
new observation technologies come on line and
mature.New ways of using or assimilating
weather data are also being developed.
27
(No Transcript)
28
Seascan Unmanned Aircraft
29
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.

30
A More Fundamental Problem
  • 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.

31
This is Ridiculous!
32
Does this make sense?
33
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.

34
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
35
Ensemble Prediction
  • Can use ensembles to 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.

36
Ensemble-Based Probabilistic Products
37
Summary
  • Weather prediction today is fundamentally
    dependent on the solution of a collection of
    mathematical equations that describe the
    atmosphere.

38
The National Weather Service
Forecaster at the Seattle National Weather
Service Office
Write a Comment
User Comments (0)
About PowerShow.com