The Technology and Future of Weather Forecasting ATMS 490

2012: Hurricane Sandy 125 dead, 60+ billion dollars damage in an area with a population of tens of millions.

Well predicted, more than a week ahead ECMWF 6-day Forecast of Sea Level Pressure

1938 Hurricane: Similar in Strength to Sandy Nearly a thousand died

Not forecast the day before

1962 Columbus Day Storm

Not forecast the day before either Seattle Times

Jan 1993: Inauguration Day Storm: Near Perfect Forecast

Something Has Changed Before 1990 the National Weather Service got virtually every major storm wrong, even the day before. After 1990, they gave good warnings for nearly all.

Forecast Skill Improvement National Weather Service Forecast Error Better Year

Skill Improvements (ECMWF) Major improvements, mainly due to satellite data and improved models

Weatherman Jokes Are No Longer Appropriate

The Key Technology of Modern Weather Forecasting is Numerical Weather Prediction

The First Numerical Weather Prediction The first successful numerical prediction of weather was made in April 1950, using the ENIAC computer at Maryland's Aberdeen Proving Ground

Numerical Weather Prediction The basic idea is that if you can determine 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. These equations can be solved on a three-dimensional grid.

Observation Collection Needed to Create the Initialization

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.

The “Primitive” Equations

Numerical Weather Prediction Numerical weather prediction is limited by the available computer resources. As computer speed increases, the number of grid points can be increased. More (and thus) closer grid points means we can simulate (forecast) smaller scale features. National Weather Service Weather Prediction Computer

NGM, 80 km, 1995

1995

2007-2008 4-km UW MM5 System

1.33 km resolution available on the UW web site

But just as important as the computer revolution has been the weather data revolution, with satellites giving us three dimension data over the entire planet

Example: The Pacific Data Void No Longer Exists

Cloud Track Winds

Better than Star Trek!

NOAA Polar Orbiter Weather Satellite

Satellite Sensors Provide Thousands of High Quality Vertical Soundings Daily over the Pacific

Impacts The addition of massive amounts of new observations is causing a steady improvement in weather prediction We are now starting to see frequent examples of forecast skill past one week: Hurricane Sandy is only one example

Observed 180 hr (7.5 days)

Forecast Skill Will Continue to Extend Further in Time…with limits (about 2 weeks) More satellite assets will provide a far better description of the atmosphere. Better models and higher resolution Better data assimilation: how we use the observations to produce an initialization for our models.

Increasing Resolution and Better Models Will Not Be Enough The Next Major Revolution in Numerical Weather Prediction Will Come Elsewhere

The Transition from Deterministic to Probabilistic Prediction

A Fundamental Problem The way we have been forecasting has been 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 Fundamental Problem Similarly, uncertainty in processes, like the development of clouds and precipitation, also produces uncertainty in forecasts. Thus, all forecasts have some uncertainty. The uncertainty generally increases in time.

This is Ridiculous!

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 or different model physics. Possible to do this now with the vastly greater computation resources that are available.

Ensemble Prediction Can use ensembles to give the probabilities that some weather feature will occur. The ensemble mean is more accurate than any individual member. Can also predict forecast skill! When forecasts are similar, forecast skill is generally higher. When forecasts differ greatly, forecast skill is less.

The Nowcasting Revolution

AMS Nowcasting Definition A description of current weather and a short-term forecast varying from minutes to a few hours; typically shorter than most operational short-range forecasts. American Meteorological Society’s Glossary of Weather and Climate

Huge amounts of local data has come online during the past several decades

Pacific Northwest Surface Observations 3000-4000 observations per hour over WA and OR

New High Resolution Models Run Each Hour

Traditional Approaches of Weather Information Dissemination Are Incapable of Delivering the Specificity and Detail Meteorologists Can Now Provide Typical TV weathercasters have only 2.5 minutes!

The Solution? Smartphones are Ideal for Weather Data Delivery. Lots of bandwidth They know where they are, so forecast information can be tailored to the user Substantial computational capacity.

There are now thousands of weather apps for smartphones…and the best are yet to come!

The End