1. The Technology and History of Weather Forecasting or Math and Weather Prediction

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

5. 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

6. 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.

7. The Initialization
Using a wide range of weather observations we can create a three-dimensional description of the atmosphere.

8. 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)

9. This equation is a time machine!

10. 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.

11. 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.

12. 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.

13. Forecast Skill Improvement
National Weather Service
Forecast
Error
Better
Year

14. 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.

15. Satellite and Weather Radars Give Us a More Comprehensive View of the Atmosphere

16. Camano
Island
Weather
Radar

17. 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.

22. But even with all this improving technology, some forecasts fail. Why?

23. 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

24. Some forecasts fail due to poor initialization, i. e
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.

25. Pacific Analysis
At 4 PM
18 November
2003
Bad Observation

26. 3 March 1999: Forecast a snowstorm … got a windstorm instead
Eta 48 hr SLP Forecast valid 00 UTC 3 March 1999
3 March 1999: Forecast a snowstorm … got a windstorm instead

27. The problem of initialization should lessen as new observation technologies come on line and mature.

28. Cloud Track Winds

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 initialization…well 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.
Thus, all forecasts have some uncertainty.

31. This is Ridiculous!

32. Or this…

33. 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

34. 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.

35. The Thanksgiving Forecast 2001 42h forecast (valid Thu 10AM)
Verification
SLP and winds
Reveals high uncertainty in storm track and intensity
Indicates low probability of Puget Sound wind event
1: cent
2: eta
5: ngps
8: eta*
11: ngps*
3: ukmo
6: cmcg
9: ukmo*
12: cmcg*
4: tcwb
7: avn
10: tcwb*
13: avn*

36. 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.

37. 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.

38. PROBCAST: www.probcast.com

39. Ensemble-Based Probabilistic Products

40. Summary
Weather prediction today is fundamentally dependent on the solution of a set of mathematical equations that describe the atmosphere.

41. The National Weather Service
Forecaster at the Seattle National Weather Service Office