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Explore the transition of weather forecasting from subjective art to precise science, fueled by technology advancements and numerical prediction models. Learn about the challenges, improvements, and the future of probabilistic forecasting.
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The Technology and History of Weather ForecastingorMath 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
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)
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 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 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.
Forecast Skill Improvement National Weather Service Forecast Error Better Year
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
Eta 48 hr SLP Forecast valid 00 UTC 3 March 1999 3 March 1999: Forecast a snowstorm … got a windstorm instead
The problem of initialization should lessen as new observation technologies come on line and mature.
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.
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.
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*
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.
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