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A Brief History of Weather Forecasting. The Beginning: Weather Sayings. "Red Sky at night, sailor\'s delight. Red sky in the morning, sailor take warning." "Mare\'s tails and mackerel scales make tall ships take in their sails." "Clear moon, frost soon." .

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the beginning weather sayings
The Beginning: Weather Sayings
  • "Red Sky at night, sailor\'s delight. Red sky in the morning, sailor take warning."
  • "Mare\'s tails and mackerel scales make tall ships take in their sails."
  • "Clear moon, frost soon."
  • .
  • "Halo around the sun or moon, rain or snow soon."
  • "Rainbow in the morning gives you fair warning."
  • "When the stars begin to huddle, the earth will soon become a puddle."
the problem no way to rapidly communicate weather observations
The problem: no way to rapidly communicate weather observations
  • This changed around 1845 with the invention of the telegraph
weather prediction began
Weather Prediction Began
  • The main approach to weather prediction during the late 1800s and early 1900s…simple extrapolation using simple schematic “models”
slide10

L

L

L

ol probs
“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.

Professor Cleveland Abbe, who issued the first public

“Weather Synopsis and Probabilities” on February 19, 1871

slide12
On May 7, 1869, Abbe proposed to the Cincinnati Chamber of Commerce "to inaugurate such a system, by publishing in the daily papers, a weather bulletin, which shall give the probable state of the weather and river for Cincinnati and vicinity one or two days in advance”.

Cleveland Abbe released the first public weather forecast on September 1, 1869.

Following the signing by President Ulysses S. Grant of an authorization to establish a system of weather observations and warnings of approaching storms, on February 19, 1871, Abbe issued the first “official” public Weather Synopsis and Probabilities based on observations taken at 7:35 a.m.

slide13
An early example of a report:

"Synopsis for past twenty-four hours; the barometric pressure had diminished in the southern and Gulf states this morning; it has remained nearly stationary on the Lakes. A decided diminution has appeared unannounced in Missouri accompanied with a rapid rise in the thermometer which is felt as far east as Cincinnati; the barometer in Missouri is about four-tenths of an inch lower than on Erie and on the Gulf. Fresh north and west winds are prevailing in the north; southerly winds in the south. Probabilities [emphasis added]; it is probable that the low pressure in Missouri will make itself felt decidedly tomorrow with northerly winds and clouds on the Lakes, and brisk southerly winds on the Gulf."

the next major advance
The Next Major Advance
  • The Norwegian Cyclone Model around 1920
slide15
Next Major Advance: Upper Air Observations Became Available from Radiosonde in the 1920’s, 30s, and 40s
1940s upper air charts using the new data
1940s: Upper Air Charts Using the New Data
  • Gave a 3D picture of what was happening
  • Learned how the upper flow steered storms, and thus provided a tool for forecasting cyclone movement.
slide17

Upper

Level

Chart

the development of numerical weather prediction nwp
The Development of Numerical Weather Prediction (NWP)
  • Vilhelm Bjerknes in his landmark paper of 1904 suggested that NWP was possible.
    • A set of equations existed that could predict the future atmosphere (primitive equations)
    • But it wasn’t practical then because there was no reasonable way to do the computations and sufficient data for initialization did not exist.
numerical weather prediction
Numerical Weather Prediction
  • The advent of digital computers in the late 1940s and early 1950’s 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.
numerical weather prediction22
Numerical Weather Prediction

One such equation 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!

slide23

Numerical Weather Prediction

Using a wide range of weather observations we can create a three-dimensional description of the atmosphere… known as the initialization

slide24

Numerical Weather Prediction

  • Observations give the distribution of mass and allows us to calculate the various forces.
  • Then… we can solve for the acceleration using F=ma
  • This gives us the future since the acceleration can be used to calculate the velocities in the future.
  • Similar idea with temperature and humidity.
numerical weather prediction25
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.
a steady improvement
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.
forecast skill improvement
Forecast Skill Improvement

National Weather Service

Forecast

Error

Better

Year

before satellites we had a very poor knowledge of what was happening over the oceans
Before Satellites We Had a VERY Poor Knowledge of What Was Happening Over the Oceans!
  • As a result, forecasts were often very poor, particularly in coastal locations.

The 1938 Hurricane was basically unforecast

weather satellites give us much more than pretty pictures
Weather Satellites Give Us Much More than Pretty Pictures
  • We start with imagery in several wavelengths:
    • Visible
    • Infrared
    • Water vapor (wavelengths where we see the water vapor distribution)
  • Plus many new capabilities
slide32

Each wavelength

gives us information

slide33

Cloud and

Water Vapor

Track Winds

Based on Geostationary Weather Satellites

slide35

Camano

Island

Weather

Radar

1995 2003 the computers models become capable of simulating forecasting local weather
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.

slide42

The National Weather Service

Forecaster at the Seattle National Weather Service Office

problems with the models
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.
some forecasts fail due to poor initialization i e a poor starting description of the atmosphere
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.

slide46

Pacific Analysis

At 4 PM

18 November

2003

Bad Observation

slide47

Eta 48 hr SLP Forecast valid 00 UTC 3 March 1999

3 March 1999: Forecast a snowstorm … got a windstorm instead

slide48

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.

a more fundamental problem
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 problem51
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 community…ensemble forecasts.
ensemble prediction
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.
slide53

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

5: ngps

11: ngps*

8: eta*

2: eta

3: ukmo

6: cmcg

9: ukmo*

12: cmcg*

4: tcwb

7: avn

13: avn*

10: tcwb*

slide55

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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