The Technology and History of
Weather Forecasting
or
Math and Weather Prediction
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)
Upper
Level
Chart
1955-1965:
The Advent of Modern Numerical
Forecasting
Numerical Weather Prediction
• During this period, numerical weather prediction—
forecasting future weather with digital computers-became meteorologists’ central tool.
• The advent of digital computers in the late 1940s
and early 1950’s made possible the simulation of
atmospheric evolution numerically.
The Eniac
The first
programmable
digital
computer
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.
The Initialization
Using a wide range of weather observations we
can create a three-dimensional description of the
atmosphere.
Numerical Weather Prediction
One of the equations used to predict the weather
is Newton’s 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!
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 F=ma
•With the acceleration we can calculate the
velocities in the future.
•Similar idea with temperature and humidity
but with different equations.
Numerical Weather Prediction
• These equations can be solved on a threedimensional 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.
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.
P
Forecast Skill Improvement
NCEP operational S1 scores at 36 and 72 hr
over North America (500 hPa)
National Weather Service
75
S1 score
65
"useless forecast"
55
36 hr forecast
72 hr forecast
45
Forecast
Error 35
10-20 years
Better
"perfect forecast"
25
15
1950
1960
1970
Year
1980
Year
1990
2000
Modern Weather Prediction
• 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.
Satellite and Weather Radars Give Us a More
Comprehensive View of the Atmosphere
Camano
Island
Weather
Radar
1995-2003+
The 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.
But even with all this improving
technology, some forecasts fail.
Why?
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
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 region…the Pacific
Ocean.
Pacific Analysis
At 4 PM
18 November
2003
Bad Observation
3 March 1999: Forecast a snowstorm
… got a windstorm instead
Eta 48 hr SLP Forecast valid 00 UTC 3
March 1999
The problem of initialization
should lessen as new observation
technologies come on line and
mature.
Cloud Track Winds
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 initialization…well within
observational error… can have
large impacts on the forecasts,
particularly for longer forecasts.
• Not unlike a pinball game….
A More Fundamental Problem
• Similarly, uncertainty in our model physics
also produces uncertainty in the forecasts.
• Thus, all forecasts have some
uncertainty.
This is Ridiculous!
Or this…
Forecast Probabilistically
• 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
community…ensemble forecasts
Ensemble Prediction
• Instead of making one forecast…make
many…each with a slightly different
initialization
• Possible to do now with the vastly greater
computation resources that are available.
The Thanksgiving Forecast 2001
42h forecast (valid Thu 10AM)
SLP and winds
1: cent
Verification
- Reveals high uncertainty in storm track and intensity
- Indicates low probability of Puget Sound wind event
2: eta
5: ngps
8: eta*
11: ngps*
3: ukmo
6: cmcg
9: ukmo*
12: cmcg*
4: tcwb
7: avn
10: tcwb*
13: avn*
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.
Probabilistic Prediction
• So instead of saying the temperature in two
days will be 67F. We might tell you:
50% probability it will be between 64 and 69F
90% probability it will be between 62 and
72F.
PROBCAST: www.probcast.com
Ensemble-Based Probabilistic Products
Summary
Weather prediction today is fundamentally
dependent on the solution of a set of
mathematical equations that describe the
atmosphere.
The National Weather Service
Forecaster at the Seattle National Weather Service Office