Researchers from the University of Northern British Columbia were apparently a bit shocked to discover that several Glaciers near the Columbia River were 38% thicker that they were supposed to be. It seems that they may have been part of the Global Warming doomsday machine predicting the end of the world if we don’t reduce CO2 emissions.
One of the researchers commented, “I was surprised that the models were off by that much.” But I am always surprised when they say that because the researchers are the ones who enter their presumptions, biases and data into the computer models.
The Edmonton Journal explains:
Lead author Ben Pelto and his colleagues skied cross country on the glaciers over 182 kilometres, pulling a sled-mounted ice-penetrating radar system to collect thousands of measurements.
They found the total volume of ice in the basin is roughly 122 cubic kilometres, or about 23 per cent more than computer modelling had estimated.
“I was surprised that the models were off by that much,” said Pelto, who completed the work with support from the University of Victoria’s Pacific Institute for Climate Solutions and from B.C. Hydro. “There are about 17,000 glaciers in B.C. and until now we only had ice measurements from a handful of them.”
Of course, this is not the first time researchers have encountered the problem of their biases infecting global warming computer models. In 2014, a group of researchers from the Institute of Marine and Antarctic Studies decided to use an underwater drone to measure how thick the ice was in the Southern Antarctic.
The computer models predicted the ice to be 1 to 2 meters thick (3 to 5 feet). Instead, it was 1.5 meters to 6 meters thick (double their modelling estimates). They expected the maximum thickness to be 16′ (5 meters) instead it was 60′ thick (20 meters.)
However, one of the scientists, Dr. Guy Williams, was honest enough to admit the real problem stating:
“…we were biased towards thinner ice.”
READ: Antarctic ice thicker than previously thought, study finds
And of course, we mustn’t forget that it was the computer models of a now disgraced researcher at Imperial College in Britain that led to the implementation of lockdowns around the world.
Neil Ferguson predicted 2.2 million COVID deaths in the US and over 500,000 COVID deaths in Britain. The numbers are not even close to that, but his doomsday predictions panicked governments. READ: Neil Ferguson’s doomsday prediction of 510k COVID deaths went unchallenged by Chris Whitty and Patrick Vallance – despite warnings it was 12 TIMES too high as No.10 panicked into full lockdown AND Coding that led to lockdown was ‘totally unreliable’ and a ‘buggy mess’, say experts AND: Exclusive: Government scientist Neil Ferguson resigns after breaking lockdown rules to meet his married lover