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Hurricanes, Climate Models, and Al Gore Wild Guesses
Hurricane
season is upon us. Harvey last week and Irma this week. Both monster
storms and 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 megastorms 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 non-linear 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 non-linear 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?
Brian C Joondeph, MD, MPS, a Denver based physician and writer. Follow him on Facebook, LinkedIn and Twitter.
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