Global Mean Surface Temperature

By Bob Tisdale – Re-Blogged From WUWT

This is a long post: 3500+ words and 22 illustrations. Regardless, heretics of the church of human-induced global warming who frequent this blog should enjoy it. Additionally, I’ve uncovered something about the climate models stored in the CMIP5 archive that I hadn’t heard mentioned or seen presented before. It amazed even me, and I know how poorly these climate models perform. It’s yet another level of inconsistency between models, and it’s something very basic. It should help put to rest the laughable argument that climate models are based on well-documented physical processes.


After isolating 4 climate model ensemble members with specific characteristics (explained later in this introduction), this post presents (1) observed and climate model-simulated global mean sea surface temperatures, and (2) observed and climate model-simulated global mean land near-surface air temperatures, all during the 30-year period with the highest observed warming rate before the year 1950. The climate model outputs being presented are those stored in the Coupled Model Intercomparison Project Phase 5 (CMIP5) archives, which were used by the Intergovernmental Panel on Climate Change (IPCC) for their 5th Assessment Report (AR5). Specifically, the ensemble member outputs being presented are those with historic forcings through 2005 and RCP8.5 (worst-case scenario) forcings thereafter. In other words, the ensemble members being presented during this early warming period are being driven with historic forcings, and they are from the simulations that later include the RCP8.5 forcings.

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Reassessing the RCPs

By Kevin Murphy – Re-Blogged From WUWT

A response to: “Is RCP8.5 an impossible scenario?”. This post demonstrates that RCP8.5 is so highly improbable that it should be dismissed from consideration, and thereby draws into question the validity of RCP8.5-based assertions such as those made in the Fourth National Climate Assessment from the U.S. Global Change Research Program.

Analyses of future climate change since the IPCC’s 5th Assessment Report (AR5) have been based on representative concentration pathways (RCPs) that detail how a range of future climate forcings might evolve.

Several years ago, a set of RCPs were requested by the climate modeling research community to span the range of net forcing from 2.6 W/m2 to 8.5 W/m2 (in year 2100 relative to 1750) so that physics within the models could be fully exercised. Four of them were developed and designated as RCP2.6, RCP4.5, RCP6.0 and RCP8.5. They have been used in ongoing research and as the basis for impact analyses and future climate projections.

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Another Climate Propaganda Story Promoting the Normal as Abnormal

By Dr. Tim Ball – Re-Blogged From WUWT

Almost every day there are stories in the media about weather or climate events that create the impression that they are new and outside of the normal pattern. None of them are. The objective is to sensationalize the story, even if it means using a meaningless period. A simple trick is to pick a period in which your claim is valid. This practice of cherry-picking the period of study is not exclusive to the media. It was a clear sign of corruption of climatology brought to a head with Roseanne D’Arrigo’s infamous comment to the 2006 National Academy of Science (NAS) panel that “if you are going to make a cherry pie, you have to pick cherries.”

That doesn’t condone the media use of the technique. All it does is illustrate why it was a convenient technique for creating a deception about what is normal. For example, a 2017 BBC headline said “Hottest June day since summer of 1976 in heatwave.” That is 41 years, which is statistically significant but not climatologically significant. A Youtube story reports “Sydney has wettest November day since 1984.” CBS Pittsburgh reported “NWS: 2018 is the 2nd Wettest Year on Record in Pittsburgh.” The record began in 1871 or 147 years ago, but even that is not climatologically significant. The ones I like are this one from North Carolina, that says, “A Look Back at the Coldest day Ever in North Carolina.” “Ever” is approximately 4.5 billion years.

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We Should Ditch GDP As A Measure Of Economic Activity

By Alasdair Macleod – Re-Blogged From Silver Phoenix

This article exposes the false economic concepts behind GDP, which is only the visible tip of a large iceberg of economic deceit. Describing an increase in GDP as economic growth owes its meagre validity to imprecise definition. An economy does not grow, only the quantity of fiat currency deployed grows. A successful economy progresses our condition, our wealth, our standards of living. The evolution of misleading statistics such as GDP to their current condition is only governed by their usefulness to governments, not as an objective development of sound theory by seekers of truth.

There are perhaps two plausible reasons for producing the GDP statistic, other than employing statisticians, and both have nothing to do with economics. By compiling the figures, a government keeps track of its tax base, and it can enter into the game of my-country-is-bigger-than-yours.

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The ‘Trick’ of Anomalous Temperature Anomalies

By Kip Hansen  Re-Blogged From WUWT

It seems that every time  we turn around, we are presented with a new Science Fact that such-and-so metric — Sea Level Rise, Global Average Surface Temperature, Ocean Heat Content, Polar Bear populations, Puffin populations — has changed dramatically — “It’s unprecedented!” — and these statements are often backed by a graph illustrating the sharp rise (or, in other cases, sharp fall) as the anomaly of the metric from some baseline.  In most cases, the anomaly is actually very small and the change is magnified by cranking up the y-axis to make this very small change appear to be a steep rise (or fall).  Adding power to these statements and their graphs is the claimed precision of the anomaly — in Global Average Surface Temperature, it is often shown in tenths or even hundredths of a Centigrade degree.  Compounding the situation, the anomaly is shown with no (or very small) “error” or “uncertainty” bars, which are, even when shown,  not error bars or uncertainty bars  but actually statistical Standard Deviations (and only sometimes so marked or labelled).


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Almost Earth-like, We’re Certain

By Kip Hansen – Re-Blogged From WUWT

There has been a lot of news recently about exoplanets. An extrasolar planet is a planet outside our solar system.  The Wiki article has a list of exoplanets.  I only mention exoplanets because there is a set of criteria for specifications of what could turn out to be an “Earth-like planet”, of interest to space scientists, I suppose, as they might harbor “life-as-we-know-it” and/or be a potential colonization target.

One of those specifications for an Earth-like planet is an appropriate average surface temperature, usually said to be 15 °C.  In fact, our planet, Sol 3 or simply Earth, is very close to qualifying as Earth-like as far as surface temperature goes. Here’s that featured image full-sized:


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Researcher: Beware Scientific Studies — Most Are Wrong

By AFP – Re-Blogged From Newsmax Health

A few years ago, two researchers took the 50 most-used ingredients in a cookbook and studied how many had been linked with a cancer risk or benefit, based on a variety of studies published in scientific journals.

The result? Forty out of 50, including salt, flour, parsley, and sugar. “Is everything we eat associated with cancer?” the researchers wondered in a 2013 article based on their findings.

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