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The world’s highest chairlift in Breckenridge, Colorado is 12,840 feet (3,914 m) high, but it could soon be surpassed by a new lift project at the world’s highest ski resort.
The Gulmarg ski resort in India’s Kashmir region already boasts the world’s second highest ski area, with runs up to three miles (5 km) long and the world’s third highest gondola bringing skiers to an altitude of over 13,000 feet (4,000m).
SkiRebel.com has learned that a new lift set to be constructed at Gulmarg this month could potentially add to that resumé, should it surpass the altitude of the lift at Breckenridge. It is not yet clear how high the new lift will be.
The construction of the new lift at an estimated cost of $2 million was announced last week by Nawang Rigzin Jora, the Minister for Tourism and Culture for the Jammu and Kashmir regions during a tour of Gulmarg.
The world’s highest ski area is Jade Dragon Snow Mountain in China, and Bolivia claimed the second highest before it was closed due to climate change melting the snow pack. The world’s two highest gondolas are both in China.
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There has been atmospheric cooling the last 8 years, and no new high global annual temperatures in the last 11 years. Anthropogenic (or man caused) global warming is not proved. None of the computer models replicate this fact.
The global warming adherents base their argument of proof on more than 20 different computer models called general circulation models (also known as global climate models or GCMs). Each computer model is composed of dozens of mathematical equations representing known scientific laws, theories, and hypotheses. Each equation has one or more constants. The constants associated with known laws are very well defined. The constants associated with known theories are generally accepted but probably some of them may be off by a factor of 2 or more, maybe even an order of magnitude. The equations representing hypotheses, well, sometimes the hypotheses are just plain wrong. Then each of these equations has to be weighted against each other for use in the computer models, so that adds an additional variable (basically an educated guess) for each law, theory, and hypothesis. This is where the models are tweaked to mimic past climate measurements.
The SCIENTIFIC METHOD is: (1) Following years of academic study of the known physical laws and accepted theories, and after reviewing some data, come up with a hypothesis to explain the data. (2) Develop a plan to obtain and analyze new data. (3) Collect and analyze the data, this may even require new technology not previously available. (4) Determine if the hypothesis is correct, needs refinement, or is wrong. Either way, new data is available for other researchers. (5) Submit results, including data, for peer review and publication.
The output of the computer models run out nearly 90 years forward is considered to be data, but it is not a measurement of a physical phenomenon. Also, there is no way to analyze this so called data to determine if any or which of the hypotheses in the models are correct, need refinement, or are wrong. Also, this method cannot indicate if other new hypotheses need to be generated and incorporated into the models. IT JUST IS NOT THE SCIENTIFIC METHOD.
The worst flaw in the AGW argument is the treatment of GCM computer generated outputs as data. They then use it in follow on hypotheses. For example, if temperature rises by X degrees in 50 years, then Y will be effected in such-and-such a way resulting in Z. Then the next person comes along and says, well, if Z happens, the effect on W will be a catastrophe. “I need (and deserve) more money to study the effects on W.” Hypotheses, stacked on hypotheses, stacked on more hypotheses, all based on computer outputs that are not data, using a process that does not lend to proof using the SCIENTIFIC METHOD. Look at their results, IF, MIGHT, and COULD are used throughout their news making results. And when one of the underlying hypotheses is proven incorrect, well, the public only remembers the doomsday results 2 or three iterations down the hypotheses train. The hypotheses downstream are not automatically thrown out and can even be used for more follow on hypotheses.