Hurricanes, Climate Models, and Wild Guesses

Hurricane season is upon us. Harvey last week and Irma this week. Both monster storms are long overdue if one looks at the pattern of hurricanes throughout history. After a hurricane drought, Harvey was the first major hurricane, meaning Category 3 or higher, to make U.S. landfall since 2005 when Hurricane Wilma hit Florida.

Despite myriad predictions of monster storms after Hurricane Katrina flooded New Orleans, there were not a plethora of superstorms to follow. Why not? These mega storms were predicted based on the “settled science” of global warming, climate change, severe weather, and the like.

Such predictions are based on computer models, factoring in tons of data including ocean temperatures and currents, wind patterns, moisture levels and other factors. Many models exist, their accuracy based on their ability to predict the severity and track of hurricanes and tropical storms. As these storms are frequent and short lived, there is ample opportunity to run the models and compare predictions to reality. The models can also be modified based on how accurate their predictions turned out, hopefully improving their reliability with each iteration. Otherwise, the predictions are nothing but guesses.

That’s the scientific method. Develop a hypothesis, test it, then modify it until it predicts with a high degree of reliability. Exactly what climate models do. Or are supposed to do.

Hurricane predictions are all over the place. Wild guesses. Spaghetti models with lines going every which way. Hurricane Irma heading into the Gulf of Mexico, hitting Florida, making landfall as far north as Canada, or veering harmlessly out to sea. Which is it? Each spaghetti line is based on some computer model, aggregating data, plugging numbers into equations, and spitting out a particular storm track. Only one of the below lines, maybe even none, will be the actual track Hurricane Irma follows.

Climate models are similar, factoring in measurements of temperatures on land, air and sea, ocean currents, wind patterns, geological activity and a host of other variables. All in an effort to predict future climate.

Yes, I know that weather is not climate. But the commonality is that predicting both rests on computer models. Collecting data and feeding the data into equations. Then, interpreting the results in such a way as to predict future events. Whether a hurricane over the next five days or the climate over the next five decades. The commonality is the predictive model.

It all sounds simple and straightforward. But it’s not. Weather and climate are incredibly complex, and as a result, not easily predictable. You can predict tomorrow’s weather by saying it will be the same as today’s weather and be correct much of the time. Hurricanes in the next few days or climate in a century are not as easy to forecast.

Which is why Al Gore and others have failed spectacularly in their doomsday prognostications. Melting polar ice caps, rising sea levels flooding cities, superstorms, and droughts. All based on what? Some computer model that has no track record of correctly predicting future events?

The reality is that weather and climate cannot be predicted with accuracy, at least given our current knowledge. The Intergovernmental Panel on Climate Change agrees, “The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.”

The idea of chaos theory is that complex systems, such as weather, cloud patterns, financial markets, bird migrations, and so on, while appearing random, actually follow a set of rules. Small changes in any of the numerous variables affecting such a system can change the outcome. The problem is that we can’t measure each and every one of these variables or their seemingly inconsequential effects on the model. Think of a butterfly flapping its wings in Nepal, influencing a hurricane in the Caribbean. Heady stuff but this explains why hurricane trackers can’t know in advance where Irma will make landfall. They can only guess.

Then how does Al Gore know what the temperature will be in 2050? Or the sea level? Or the mass of Antarctic ice, which, as an amusing aside, is increasing according to NASA.

With dozens of hurricanes each year, each model, every one of those spaghetti lines, can be tested. And refined. The lousy ones get tossed and the good ones are tweaked and retested as their accuracy improves. Knowing that none of the models will be right every time as hurricanes are nonlinear chaotic systems and therefore unpredictable.

Newsweek writer Kurt Eichenwald claims to have “predicted Irma intensity growth and timing. 100% correct.” This was a few days ago before Irma hit the U.S. mainland. He cites a fancy math formula of differential equations as the basis of his prediction. Pretty impressive for a political science major. I was a math major and I don’t understand the equation.

He should go on record stating where Irma will hit U.S. mainland, the wind speed, size of the storm surge, and track after landfall. If everything happens as predicted, his formula may be the winning ticket. If not, back to the Newsweek drawing board. Since there are three storms currently in the Atlantic, he should predict the future for all three and see if his model is “100% correct” as he claims.

How about climate? Rather than turning it into a political issue, calling anyone who disagrees a “denier”, meaning a Luddite, a rube, a Trump supporter, where’s the science? The hypotheses subject to scrutiny and testing?

If the predictive models are correct, then prove it. So far, all the apocalyptic forecasts have fizzled out. Past measurements should be able to be placed into a climate model with an accurate prediction of future climate. Easy to test, just as with a stock market predictive model, using old data to accurately predict current conditions.

Recall the last presidential election, another example of predictions based on computer models and data. In previous years fairly accurate, but not last year when almost everyone, from Nate Silver to the New York Times to the Huffington Post all predicted a Hillary Clinton landslide, holding to their predictions even on election day until evening when their prognostications blew up in grand fashion.

The point is that computer models provide nothing but educated guesses. They should be taken as such, not as gospel. Whether hurricane tracks or climate change. Test and rework the models improving their accuracy, with the understanding that nonlinear chaotic systems are impossible to predict accurately, at least based on current knowledge.

Instead, we have NOAA manipulating climate records to advance the theory of man-made global warming. What kind of science is that? Pseudo-science to advance a political agenda. If we can’t predict the course of a hurricane over a week, how can we predict the climate over a century?

Read more at American Thinker

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