Why Climate Models Are Less Accurate Than You Think

Why Climate Models Are Less Accurate Than You Think
Morning traffic on the SR2 freeway in Los Angeles on April 25, 2013. Los Angeles ranks as the worst in the nation for ozone pollution and fourth for particulates by the American Lung Association. (David McNew/Getty Images)
Anthony Watts
Everyone wants to save the planet. Yet, in the rush to do so, a new study in the Proceedings of the National Academy of Sciences suggests that basic science is being ignored concerning how climate models deal with carbon soot pollution.

While you might think this is no big deal, the repercussions could be huge.

For years, climate scientists have said the future of the planet is certain: Earth will become significantly warmer. Moreover, they constantly claim the “science is settled” on the topic of global warming because their massive supercomputers run sophisticated climate models that yield “robust” visions of the future.

In essence, they are saying “we’re scientists, trust us, we have thousands of studies and a big computer behind us.”

Yet, given that global warming has turned into a pseudo-scientific social movement buoyed by huge amounts of government funding, there’s an implicit danger that it’s become beholden to group-think and government funding biases.

The study reveals that a very basic error in climate models’ underlying assumptions could have a very large impact on their future predictions, rendering them much less accurate than anticipated. In other words, the vast majority of climate models overstate the likely extent of future warming.

According to a commentary article in the peer-reviewed science journal Nature Climate Change, titled “Ill-sooted models:”
“Atmospheric black carbon (BC) or soot — formed by the incomplete combustion of fossil fuels, biofuel and biomass — causes warming by absorbing sunlight and enhancing the direct radiative forcing of the climate. As BC ages, it is coated with material due to gas condensation and collisions with other particles. These processes lead to variation in the composition of BC-containing particles and in the arrangement of their internal components — a mixture of BC and other material — though global climate models do not fully account for these heterogeneities. Instead, BC-containing particles are typically modelled as uniformly coated spheres with identical aerosol composition, and these simplifications lead to overestimated absorption.”
In a nutshell, in their zeal to model and “prove” global warming, climate researchers assumed that all carbon black particles ejected into the atmosphere have strong warming qualities that don’t diminish over time. In reality, that’s not the case and it is a huge oversimplification of what actually occurs in nature.

That oversimplification causes climate models to predict more future warming than would actually occur had they properly accounted for variations in black carbon soot size, composition, and aging.

The flaws in existing climate models are equivalent to saying that every grain of sand on the beach is exactly the same size, shape, and composition, or that snowflakes aren’t unique, but all are exactly the same. As even a grade-schooler knows, nature doesn’t work like that. Once again, “climate science” fails the tenets of basic science.

This latest revelation adds to the string of criticisms that have been levied against climate modeling over the past 30 years, when many models were created. Since then, climate science has been unable to agree on the value of climate sensitivity, which tells models how much warming to expect for a doubling of climate dioxide in Earth’s atmosphere.
Also, climate models are running warmer than actual temperature measurements. Moreover, one climate scientist did an about-face and declared he’d had enough of inaccurate climate models and told the world that the most-cited climate model was based on a scenario that can’t possibly happen. As a result, “worst-case scenario” climate models should be removed from scientific consideration.

All of this means there’s a huge amount of uncertainty regarding the future warming predicted by climate models. Yet, despite these obvious shortcomings, the models and their faulty predictions continue to be used to form social and public policy, often at great expense and hardship.

It doesn’t matter how big of a supercomputer you have, because if the assumptions programmed into the climate models are wrong, they’ll suffer from that old computer programmer maxim: “Garbage in, garbage out.”

Anthony Watts ([email protected]) is a former television meteorologist and senior fellow at The Heartland Institute. He operates the most viewed website on climate in the world, WattsUpWithThat.com.
Views expressed in this article are opinions of the author and do not necessarily reflect the views of The Epoch Times.
Anthony Watts is former television meteorologist and senior fellow at The Heartland Institute. He operates the most viewed website on climate in the world, WattsUpWithThat.com
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