A recent update to the LC15 paper published by Nic Lewis and Judith Curry in the Journal of Climate (“The impact of recent forcing and ocean heat uptake data on estimates of climate sensitivity“) determines that “high ECS and TCR values derived from a majority of CMIP5 climate models are inconsistent with observed warming during the historical period.”
In other words, the models predict way to much warming and do not match reality. More about the update here.
“As a result, we see that some ‘very likely’ and ‘likely’ conclusions from the AR4 and AR5 that are ‘very likely’ to be overturned by the AR6.” –Judith Curry
Reblogged from NoTricksZone
By Dr. Sebastian Lüning and Prof. Fritz Vahrenholt
(German text translated/edited by P Gosselin)
Droughts increase the risk of forest fires; that’s logical. However it is false to reflexively assign every forest fire to climate change. There have always been droughts and forest fires. Anyone wishing to shift the blame over to climate change first has to show that the trend has already deviated from the range of natural variability. For many, that is simply too much work.
2004 – 2014 burn acreage trend is falling. Chart source: Tony Heller.
A new study by Yin and Porporato published on December 22 in Nature Communications, concludes that “most GCMs present considerable discrepancies in the standard deviation (σ) and centroid (c) of cloud cycles.” The authors conclude that the systematic error in the models leads to an over estimate of radiative energy from the sun of 1 to 2 watts per square meter which is roughly half of the 3.7 watts additional radiative forcing attributed to all the CO2 produced since the beginning of the industrial age.
Guest essay by Sheldon Walker
In my last article I attempted to present evidence that the recent slowdown was statistically significant (at the 99% confidence level).
Some people raised objections to my results, because my regressions did not account for autocorrelation in the data. In response to these objections, I have repeated my analysis using the AR1 model to account for autocorrelation.
By definition, the warming rate during a slowdown must be less than the warming rate at some other time. But what “other time” should be used. In theory, if the warming rate dropped from high to average, then that would be a slowdown. That is not the definition that I am going to use. My definition of a slowdown is when the warming rate decreases to below the average warming rate. But there is an important second condition. It is only considered to be a slowdown when…
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