“HadCRUT4 is the primary dataset used by the Intergovernmental Panel on Climate Change (IPCC) to make its dramatic claims about “man-made global warming”, to justify its demands for trillions of dollars to be spent on “combating climate change” and as the basis for the Paris Climate Accord.
But according to a groundbreaking analysis by Australian researcher John McLean it’s far too sloppy to be taken seriously even by climate scientists, let alone a body as influential as the IPCC or by the governments of the world.” click here
“Nearly seven years ago, on December 7th, 2011, the Free Market Environmental Law Clinic’s (FME Law) sought public records from the University of Arizona related to the Mann-Bradley-Hughes temperature reconstruction that looks like a hockey stick, and development of an Intergovernmental Panel on Climate Change (IPCC) report. They refused much of the request and FME Law sued. Now (on September 18th, 2018) legal counsel for the University informed FME Law that they were done, that they would be withdrawing their appeal of the trial court’s decision, end the case and disclose the records.” click here
“Now isn’t it a bit odd that the authors made absolutely no mention of the ocean cycles in the abstract? As our regular readers know, the ocean cycles run surprisingly synchronous with the fluctuations in global temperatures, i.e. the key factors here are the AMO and PDO.” click here
“No matter how hard climate-catastrophe obsessed alarmists attempt to beat out a little doom from the data, their results still fall far way short of their projections. Moreover, the modest warming the planet has seen over the recent decades is tied more to natural cycles.” click here
“To theorize that 15 ten-millionths of an overall system will control the temperature of that interrelated system, or of any large part of it, is prima facie nonsense. What should surprise us is not that the idea has turned out wrong, but that anyone embraced it in the first place and that it’s taking so long for so many people, including many highly intelligent scientists, to abandon it in the face of the clear empirical evidence of its falsehood.” click here
“Many problems plagued climatology since climate science took over in the 1980s. Each specialist in a different area suddenly became an expert in climate and climate change. They brought their different perspectives, sometimes helpful, but usually unhelpful and even distorting. Most came for funding opportunities, but many for the political objectives. They all lack awareness that climatology is a generalist discipline. It involves putting together, in a systems approach manner, all the studies from specialists who, because they get involved in climate studies, call themselves climate scientists. This piecemeal approach reflects the problems of creating computer climate models. Modellers assemble as many facts as they think apply, or will achieve their result and then, with improper or inadequate connecting mechanisms, put together what they think represents global climate.” click here
Jing-Jia Luo, Gang Wang, Dietmar Dommenget. Many common model biases reduce CMIP5’s ability to simulate the recent Pacific La Niña-like cooling? Climate Dynamics, February 2018, Volume 50, Issue 3–4, pp 1335–1351
Over the recent three decades sea surface temperate (SST) in the eastern equatorial Pacific has decreased, which helps reduce the rate of global warming. However, most CMIP5 model simulations with historical radiative forcing do not reproduce this Pacific La Niña-like cooling. Based on the assumption of “perfect” models, previous studies have suggested that errors in simulated internal climate variations and/or external radiative forcing may cause the discrepancy between the multi-model simulations and the observation. But the exact causes remain unclear. Recent studies have suggested that observed SST warming in the other two ocean basins in past decades and the thermostat mechanism in the Pacific in response to increased radiative forcing may also play an important role in driving this La Niña-like cooling. Here, we investigate an alternative hypothesis that common biases of current state-of-the-art climate models may deteriorate the models’ ability and can also contribute to this multi-model simulations-observation discrepancy. Our results suggest that underestimated inter-basin warming contrast across the three tropical oceans, overestimated surface net heat flux and underestimated local SST-cloud negative feedback in the equatorial Pacific may favor an El Niño-like warming bias in the models. Effects of the three common model biases do not cancel one another and jointly explain ~50% of the total variance of the discrepancies between the observation and individual models’ ensemble mean simulations of the Pacific SST trend. Further efforts on reducing common model biases could help improve simulations of the externally forced climate trends and the multi-decadal climate fluctuations.