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Complexity of Climate Continues to Confound Modeling


Predicting the future of earth’s climate is seemingly become exponentially more difficult.

Climate change research has increasingly moved away from studying earth’s climate to better understand it to prognosticating in an attempt to control the future. In other words, understanding the science has been overcome by fortune-telling.

In order to better predict the future of the climate, various climate models have been developed to run the numbers. The trouble is, even as these climate models are becoming increasingly complex, weighing and accounting for an ever-increasing range of variables, scientists are still failing to hit the mark. In fact, the climate modeling predictions from the 1970s are showing themselves to be as close to the mark as any of the modern models run with multiple times the computing power.

As climate scientists are finding out, earth’s climate is much more complex and nuanced than many may appreciate. A recent article in The Wall Street Journal notes this reality in reporting on scientists working at the National Center for Atmospheric Research: “The scientists would find that even the best tools at hand can’t model climates with the sureness the world needs as rising temperatures impact almost every region.”

The Journal describes a situation of diminishing returns. The more data is collected and input into the modeling, the less accurate the return. “Even the simplest diagnostic test is challenging,” the Journal says. “The model divides Earth into a virtual grid of 64,800 cubes, each 100 kilometers on a side, stacked in 72 layers. For each projection, the computer must calculate 4.6 million data points every 30 minutes. To test an upgrade or correction, researchers typically let the model run for 300 years of simulated computer time.” And yet, “As algorithms and the computer they run on become more powerful — able to crunch far more data and do better simulations — that very complexity has left climate scientists grappling with mismatches among competing computer models.”

The scale is still simply too big to account for the massive amounts of minute data that directly impact climate. Steven Koonin, Barack Obama’s former undersecretary of science, recently wrote a book titled Unsettled: What Climate Science Tells Us, What It Doesn’t, and Why It Matters, in which he observed: “A simulation that takes two months to run with 100 km grid squares would take more than a century if it instead used 10 km grid squares. The run time would remain at two months if we had a supercomputer one thousand times faster than today’s — a capability probably two or three decades in the future.”

Interestingly, one of the hangups for the climate modelers happens to be clouds. Accounting for the nature of clouds and their impact upon global temperatures is challenging due to the fact that they can contribute to both cooling and heating the climate. And since clouds are ever-changing, understanding how to calculate their impact has proven difficult.

This is why assertions about the future of the planet or demands for immediate catastrophic economic change and socialist policy structures ring of hubris on the part of climate activists. The truth is there is still so much we don’t know or understand about our planet’s climate. To suggest otherwise is to act the part of a fortune-teller, not a scientist.

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