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Hurricane Matthew and U.S. Science Bashing…

Hurricane Matthew - Model Predictions

Ensemble model predictions for Hurricane Matthew over the next 7-10 days. The models all predict the path up the east coast of Florida, with some very minor variation in exact track. After about 5 days, the modeled tracks start to vary, with uncertainty in the hurricane’s path increasing as you move further and further into the future.

It’s early October. Winter is coming.  From a scientific perspective, we know why.  Given the tilt of the earth in relationship to the sun, the Northern Hemisphere is about to receive far less incoming solar radiation than in the summer months.  The obvious result…cooler temps than in summer.  The depths of winter may be a few months out, but we KNOW what’s going to happen based on some very basic, easily measured scientific information.

If we KNOW it’s going to get colder several  months in advance…why can’t a weatherman tell me if it’s going to rain or snow on Halloween?  That’s much closer, after all.  If a meteorologist can’t tell me what the weather will be like in 3 weeks, how can they possibly know that winter is going to be colder?  Clearly meteorologists and climatologists have no idea what they’re talking about.

THAT is the basic argument that was making the rounds on social media over the last day or two. Climate change skeptics are trying to link uncertainty in hurricane tracks to uncertainty in climate change, stating that if we can’t perfectly predict a hurricane’s track several days in advance, how can we possibly know what the climate will do over the next several decades?  Hurricane Matthew wreaked havoc in the Caribbean, and is about to strike Florida.  As always, National Weather Service continues to monitor the storm, and issue forecasts on the likely future track.  There are uncertainties, of course.  Scientists use “ensemble modeling” to try to account for uncertainties in models.  Any ONE model may or may not have biases and error, but running many different models helps a scientist to visualize overall patterns and describe the most LIKELY outcome.

Fake Hurricane Model Graphic

A graphic circulating widely on social media, giving a false impression of hurricane forecasting.

For hurricane modeling, a common graphic is a hurricane forecast map that shows individual predictions of many different models.  These graphics also typically include an “average” track, created by basically averaging all the different model runs.  Typically an ensemble model graph looks like the image at the top, showing where Hurricane Matthew is likely to go over the next 7-10 days.  Uncertainty is much lower closer to the present time, so model tracks tend to be close to each other at first, and then become more uncertainty as the prediction period lengthens.  In the real Hurricane Matthew example above, the models are all quite consistent in predicting Matthew will hug the Florida coast  They all predict Matthew will take a right turn off the coast of South Carolina, Model paths then diverge some, although in updated predictions from the graphic above, models are mostly predicting a strong clockwise turn that may bring the hurricane back to Florida for a 2nd round.

On social media over the last few days, the 2nd graphic has been circulating.  It gives a very false impression of hurricane predictions, with many more modeled tracks than there are actual hurricane models, winding all over the map like a bowl of spaghetti.  The “punch line” with this graphic on social media?  That meteorologists have no idea where a hurricane is going in a few days, and thus they can’t possibly know that climate change is going to occur in the coming decades.

Other than the misrepresentation in the 2nd graphic of real hurricane model uncertainty, this attack on climate science makes a fundamental error in the difference between short-term weather, and longer-term climate.  It’s similar to the pathetic attack on climate science by James Inhofe on the U.S. Senate floor, where he brought a snowball onto the floor and thereby declared that since it was snowing, climate change clearly wasn’t occurring.  The analogy to the coming winter is quite fitting though. For seasonal change, we KNOW the physical characteristics of the earth/sun system that drive the changes between seasons.  For long-term climate change, we KNOW the physical impact of increased greenhouse gases in the atmosphere.  Just as seasonal change occurs because of solar radiation differences between seasons, we KNOW the climate is going to warm given greenhouse gas influences on the balance between how much solar radiation is maintained in the earth/atmosphere system, versus how much radiates back out to space.

In effect, we’re putting a blanket on the atmosphere, trapping more heat.  It’s a known, physically measurable and quantifiable characteristic of the earth/sun/climate system, just as is the changing of the seasons.Just as it’s much harder to predict short-term variability in weather (including hurricane tracks over the next 7-10 days) versus long-term seasonal trends (hotter in summer, colder in winter), it’s much easier to predict long-term trends in climate, based on how we’re altering the atmosphere.

As a scientist the most frustrating thing about the 2nd graphic and the social media’s false attack on climate science is that it fits a general pattern of “science bashing” in the United States.  Be it evolution, climate change, or a host of other KNOWN scientific processes, there’s an odd anti-science pushback that’s grounded more in religion and politics than actual science.  It’s not a uniquely American phenomenon, but it certainly is much more amplified and prevalent in the U.S. than in most countries.  The politicization of science, the blatant disregard for scientific theory and even real, measurable empirical evidence, turns even something as obvious as evolution or climate change into a faux controversy.

All for the sake of advancing a political or religious agenda.

Don’t fall for the social media bullshit.  Scientists and modelers have done a wonderful job tracking and predicting Matthew’s path, giving millions in its potential path time to prepare or evacuate.  Weather is weather, and modeling an exact path over a week out is still an inexact (but rapidly improving) science.  That uncertainty in NO way relates to our certainty about long-term warming trends in relationship to climate change.

Science MATTERS – A lesson from Joaquin

Graphic of potential paths for Hurricane Joaquin

September 30th, just a couple of days away from Hurricane Joaquin potentially impacting the U.S. coastline, and nearly all U.S.-based models had the hurricane directly striking the U.S. coast. The outlier? The (well-funded) European model that ended up correctly predicting the path far out to sea. A repeat of Hurricane Sandy, which U.S. models also struggled with, but the European model nailed.

It’s more than a bit depressing at times lately, being a U.S. government scientist.  Funding is a big part of that, as funding profiles for science in the U.S. government have definitely been on the downswing.  For my own project, I’ve had to cut quite a few very good people over the last few years, as the funding I receive to do land-use and land-cover modeling (future and past) has declined precipitously.  There are few things more maddening than working on a project, producing something the world has never seen, something that has tremendous value in helping science and society in general cope and plan for coming climate and land-use changes…and seeing your “reward” come in the form of massive budget cuts, forcing the release of great scientists (and friends).

While the budget declines have been disappointing, what’s even worse is the public attitude towards science in general.  Science and scientists used to be revered in this country.  They were representative of progress, of leadership, of the United States’ leading global role.  During the Cold War, scientific progress itself was as busy an arena for West vs. East competition as was geopolitical competition, with the space race captivating the world.

However, in the past decade or so, science has seemingly become the enemy for many.  As the conservative movement politicized what are inherently science issues, not political issues, the public’s opinion of science, and scientists themselves, has taken a hit.  Instead of admiration, there’s a broad sector of the public that now views scientists with skepticism and mistrust.  The politicization of climate change has certainly played a big role, as political talking heads push a pro-business, anti-environment message by attacking not only the science of climate change, but the integrity of the scientists themselves.  Suddenly scientists are being portrayed as liars and swindlers, pushing climate change research only to support some mysterious hidden liberal agenda (SO hidden that even as as a bleeding heart liberal I can’t see it), or to ensure the big research dollars keep flowing (I myself would LOVE to know where conservatives think all these “big liberal research dollars” are coming from….I could use them!!!).

In the meantime, science is suffering in the U.S.  Environmental protection?  Research for clean energy sources?  Spending on environmental monitoring and assessment?  All irrelevant, as they potentially impact short-term profit margins.   It’s not just “fringe” science that’s being impacted, it’s core research and scientific monitoring that’s crucial to keeping Americans safe.

If you followed Hurricane Joaquin last week, there was tremendous uncertainty in the path of the hurricane as it lingered in the Bahamas.  Scientists use “ensemble modeling” to better characterize uncertainty in difficult to predict events, with a wide variety of models used to assess the same phenomena.  Such an approach helps to form a “consensus” of multiple models.  For Hurricane Joaquin, ensemble modeling was used to help identify a variety of potential tracks.  In theory, the most likely path is something that the majority of models agree upon.

Last week, the models were all over the map.  Even by mid-week last week, the vast majority of U.S. based models were predicting Joaquin would track northward from the Bahamas, making a direct strike on the U.S. mainland, somewhere between the Carolinas and the New York area.  Mid week, there was one model, the primary European model, that was an outlier.  The European model predicted a Joaquin would jog to the northeast, missing the U.S. coast completely.  The European model, although the outlier in mid-week predictions, was the closest to the actual hurricane path.  U.S. models performed quite poorly in comparison.

For Hurricane Sandy, there was similar uncertainty.  For Sandy, the European model (correctly) predicted the hook into the New York area, while most U.S. models predicted Sandy would curve northeastward and miss the U.S. coastline.  Again…it was the European model that was correct, with U.S. models performing poorly.

There’s a great story on the New York times on how far behind NOAA and the U.S. Weather Service have fallen in terms of hurricane forecasting.  Raw computing power is an order of magnitude lower for U.S. models than for the systems being used in Europe.  Input data is lacking, as are other aspects of model parameterization.  In short, the U.S. simply has not invested as much in basic weather forecasting and research as has Europe.

As Sandy showed, and now as Joaquin has showed….the lack of adequate research funding for science in the United States has a VERY real impact on the everyday lives of Americans.  Clearly it’s not just weather research that’s an issue. Science funding profiles are declining for nearly all fields. Keeping Americans safe from weather events, natural disasters such as earthquakes and volcanoes, research on treating or curing disease, protection of our air, water, and food resources…all are suffering from lack of investment.

It’s a very curious disconnect right now, with technology-loving Americans seemingly often at war with science in general.  As Joaquin and Sandy showed, and as countless other examples have shown…there’s a real price to be paid for an inadequate investment in science.

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