The “Science of Global Warming” is settled, as the brainless libtard liars like to say.
The sham science of the so-called “Man-Made Global Warming” lie has been exposed over and over, and a new study even shows that the Earth would be exactly the same temperature even if Man never existed.
All the evidence suggests that the planet was about a degree warmer during the Medieval Warming Period than it is now; and that there is nothing unnatural or unprecedented about late 20th century and early 21st century “climate change”.
The liars in the corrupt liberal media will never spend one second of airtime on any report debunking their “Global Warming” baby, the biggest lie the world has ever known, for fear that their lie will quickly unravel, and the microscopic amount of credibility the networks currently have will instantly disappear.
In fact, even the so-called “conservative news” network (FOX) has ditched their conservative viewers in favor of a more CNN-like shit sandwich of Democrat talking points and lies, which are basically the same thing.
Most global warming is natural and even if there had been no Industrial Revolution current global temperatures would be almost exactly the same as they are now, a study has found.
The paper, by Australian scientists John Abbot and Jennifer Marohasy, published in GeoResJ uses the latest big data technique to analyse six 2,000 year-long proxy temperature series from different geographic regions. “Proxies” are the markers scientists use – tree rings, sediments, pollen, etc – to try assess global temperature trends in the days before the existence of thermometers. All the evidence suggests that the planet was about a degree warmer during the Medieval Warming Period than it is now; and that there is nothing unnatural or unprecedented about late 20th century and early 21st century “climate change”.
This contradicts the claims of alarmist scientists at the Intergovernmental Panel on Climate Change that “man made” global warming is a worrying and dangerous phenomenon.
Time-series profiles derived from temperature proxies such as tree rings can provide information about past climate. Signal analysis was undertaken of six such datasets, and the resulting component sine waves used as input to an artificial neural network (ANN), a form of machine learning. By optimizing spectral features of the component sine waves, such as periodicity, amplitude and phase, the original temperature profiles were approximately simulated for the late Holocene period to 1830 CE. The ANN models were then used to generate projections of temperatures through the 20th century. The largest deviation between the ANN projections and measured temperatures for six geographically distinct regions was approximately 0.2 °C, and from this an Equilibrium Climate Sensitivity (ECS) of approximately 0.6 °C was estimated. This is considerably less than estimates from the General Circulation Models (GCMs) used by the Intergovernmental Panel on Climate Change (IPCC), and similar to estimates from spectroscopic methods.
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