The Intergovernmental Panel on Climate Change and Environmental Protection Agency repeatedly assure us that today’s climate change computer models are “highly sophisticated?






The Intergovernmental Panel on Climate Change and Environmental Protection Agency repeatedly assure us that today’s climate change computer models are “highly sophisticated” and able to predict global temperature and climate events with “amazing accuracy.” In reality, they are ridiculously off the mark. They don’t even come close to forecasting what has actually been happening in the real world. And no wonder.

The assumptions and algorithms built into the computer software focus almost entirely on carbon dioxide – and almost entirely ignore the numerous, powerful, interrelated NATURAL forces that drive climate change.

My article with climatology professor David Legates explains why the models are defective, how this came about (follow the money), and what should be done to fix the problem before we spend more money and promulgate more energy-strangling, job-killing laws and regulations based on the current crop of useless and misleading computer models.

Thank you for posting our article, quoting from it, and forwarding it to your friends and colleagues. (Please be sure to include David Legates and his bio.)
Best regards,
Paul

Needed: Accurate climate forecasts
Focusing on carbon dioxide (because that’s where the money is) threatens forecasts, and lives
Paul Driessen and David R. Legates

President Obama’s agreement with China is about as credible as his “affordable care” pronouncements.

Pleistocene glaciers repeatedly buried almost half of the Northern Hemisphere under a mile of ice. The Medieval Warm Period (~950-1250 AD) enriched agriculture and civilizations across Asia and Europe, while the Little Ice Age that followed (~1350-1850) brought widespread famines and disasters. The Dust Bowl upended lives and livelihoods for millions of Americans, while
decades-long droughts vanquished once-thriving Anasazi and Mayan cultures, and flood and drought cycles repeatedly pounded African, Asian and Australian communities. Hurricanes and tornadoes have also battered states and countries throughout history, in numbers and intensities that have been impossible to pattern or predict.

But today we are supposed to believe climate variability is due to humans – and computer models can now forecast climate changes with amazing accuracy. These models and the alarmist scientists behind them say greenhouse gases will increasingly trigger more “severe, pervasive and irreversible impacts for people, species and ecosystems,” a recent UN report insists.

In reality, carbon dioxide’s effect on devastating weather patterns is greatly overstated. We are near a 30-year low in hurricane energy (measured by the ACE index of “accumulated cyclone energy”), and tropical cyclone and storm activity has not increased globally over that period. In fact, as of November 18, it’s been 3,310 days since a Category 3-5 hurricane hit the US mainland – by far the longest stretch since records began in 1900. This Atlantic hurricane season was the least active in 30 years.

Moreover, there has been no warming since 1995, several recent winters have been among the coldest in centuries in the United Kingdom and continental Europe, the 2013-14 winter was one of the coldest and snowiest in memory for much of the United States and Canada – and the cold spell could continue.

Accurate climate forecasts one, five or ten years in advance would certainly enable us to plan and prepare for, adapt to and mitigate the effects of significant or harmful climate variations, including temperatures, hurricanes, floods and droughts. However, such forecasts can never be even reasonably accurate under the climate change hypothesis that the IPCC, EPA and other agencies have adopted. The reason is simple.

Today’s climate research defines carbon dioxide as the principal driving force in global climate change. Virtually no IPCC-cited models or studies reflect the powerful, interconnected natural forces that clearly caused past climate fluctuations – most notably, variations in the sun’s energy output.
They also largely ignore significant effects of urban and other land use changes, and major high-impact fluctuations like the Pacific Decadal Oscillation (El Niño and La Niña) and North Atlantic Oscillation. If we truly want reliable predictive capabilities, we must eliminate the obsession with carbon dioxide as the primary driver of climate change – and devote far more attention to studying all the powerful forces that have always driven climate change, the roles they play, and the complex interactions among them.

We also need to study variations in the sun’s energy output, winds high in the atmosphere, soil moisture, winter snow cover and volcanic eruptions, Weatherbell forecaster Joe D’Aleo emphasizes. We also need to examine unusual features like the pool of warm water that developed in the central Pacific during the super La Niña of 2010-2011 and slowly drifted with the wind-driven currents into the Gulf of Alaska, causing the “polar vortex” that led to the cold, snowy winter of 2013-2014, he stresses.

“The potential for climate modeling mischief and false scares from incorrect climate model scenarios is tremendous,” says Colorado State University analyst Bill Gray, who has been studying and forecasting tropical cyclones for nearly 60 years. Among the reasons he cites for grossly deficient models are their “unrealistic model input physics,” the “overly simplified and inadequate numerical techniques,” and the fact that decadal and century-scale circulation changes in the deep oceans “are very difficult to measure and are not yet well enough understood to be realistically included in the climate models.”

Nor does applying today’s super computers to climate forecasting help matters. NOAA, the British Meteorological Office and other government analysts have some of the world’s biggest and fastest computers – and yet their (and thus the IPCC’s and EPA’s) predictions are consistently and stupendously wrong. Speedier modern computers simply make the “garbage in, garbage out” adage occur much more quickly, thereby facilitating faster faulty forecasts. Why does this continue? Follow the money.

Billions of dollars are doled out every year for numerous “scientific studies” that supposedly link carbon dioxide and other alleged human factors to dwindling frog populations, melting glaciers, migrating birds and cockroaches, and scores of other remote to ridiculous assertions. Focusing on “dangerous human-induced” climate change in research proposals greatly improves the likelihood of receiving grants.

American taxpayers alone provide a tempting $2.5 billion annually for research focused on human factors, through the EPA, Global Change Research Program and other government agencies. Universities and other institutions receiving grants take 40% or more off the top for “project management” and “overhead.” None of them wants to upset this arrangement, and all of them fear that accepting grants to study natural factors or climate cycles might imperil funding from sources that have their own reasons for making grants tied to manmade warming, renewable energy or antipathy toward fossil fuels. Peer pressure and shared views on wealth redistribution via energy policies, also play major roles.

When Nebraska lawmakers budgeted $44,000 for a review of climate cycles and natural causes, state researchers said they would not be interested unless human influences were included. The “natural causes” proposal was ultimately scuttled in favor of yet another meaningless study of human influences.

The result is steady streams of computer model outputs that alarmists ensure us accurately predict climate changes. However, none of them forecast the 18-years-and-counting warming pause, the absence of hurricanes, or other real-world conditions. Nearly every one predicted temperatures that trend higher with every passing year and exceed recorded global temperatures by ever widening margins.

The constant predictions of looming manmade climate disasters are also used to justify demands that developed nations “compensate” poor and developing countries with tens or hundreds of billions of dollars in annual climate “reparation, adaptation and mitigation” money. Meanwhile, those no-longer-so-wealthy nations are implementing renewable energy and anti-hydrocarbon policies that drive up energy costs for businesses and families, kill millions of jobs, and result in thousands of deaths annually among elderly pensioners and others who can no longer afford to heat their homes properly during cold winters.

Worst of all, the climate disaster predictions are used to justify telling impoverished countries that they may develop only to extent enabled by wind and solar power. Financial institutions increasingly refuse to provide grants or loans for electricity generation projects fueled by coal or natural gas. Millions die every year because they do not have electricity to operate water purification facilities, refrigerators to keep food and medicine from spoiling, or stoves and heaters to replace wood and dung fires that cause rampant lung diseases. As Alex Epstein observes in his new book, The Moral Case for Fossil Fuels:

“If you’re living off the grid and can afford it, an installation with a battery that can power a few appliances might be better than the alternative (no energy or frequently returning to civilization for diesel fuel), but [such installations] are essentially useless in providing cheap, plentiful energy for 7 billion people – and to rely on them would be deadly.”

By expanding our research – to include careful, honest, accurate studies of natural factors – we will be better able to discern and separate significant human influences from the powerful natural forces that have caused minor to profound climate fluctuations throughout history. Only then will we begin to improve our ability to predict why, when, how and where Earth’s climate is likely to change in the future. Congress should reduce CO2 funding and earmark funds for researching natural forces that drive climate change.

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