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Funny things happen on the Internet sometimes. Rather spectacular claims were made that 900 days of data “were fabricated”. This claim was described as not just speculation, but “a demonstrable fact”, and worse, the crime was apparently even “admitted to” by the man himself! Except that none of it was real, and three tiny misunderstood dots were not fabricated, not data, and not important. Welcome to a Bermuda-Triangle-moment in blog-land, where facts vanish, ships full of misquotes appear from nowhere, and ghosts-of-malcontent and misunderstanding roam freely. This post here is to slay the last loose ghosts, lest anybody think they might still have life in them, or indeed, think they ever did.
Usually a live debate is a brilliant way for spectators to learn. But in that particular science thread, the main lesson is not science but manners. Common courtesy may seem a quaint anachronism, but without it, logic and reason die on the sword of uninformed passion. A simple polite email and an open mind could have saved the world from a cloud of nonsense.
Thanks to the many valiant souls who fought for common sense.
It’s rare in a complex […]
Leif Svalgaard claims “TSI has not fallen since 2003”. It’s technically true in a sense, but demonstrably false when discussing 11 year smoothed trends (which is written on the graph he was criticizing). Willis Eschenbach sadly was carried along. This post is in response to an overheated thread at WUWT. Both men owe David Evans an apology.
The fuss is over the big fall in TSI. Leif Svalgaard said it was “almost fraudulent” that we claimed there was a fall in TSI since 2003 since there wasn’t a fall in this dataset. He says: “There is no such drop.” I say, look at the graph below, it’s even in your own data. Svalgaard provided the link to his TSI set, and we’ve included that line in the graph below. It’s the light-purple line. (Has he paid attention for the last ten years?)
In his rush to call it “totally wrong” and to declare “the model is already falsified” he didn’t notice we were talking about a trend in 11 year smoothed TSI, and the fall is evident in whole cycles (but takes some wisdom to find in daily or monthly data). I guess that’s a mistake that could happen to […]
The Solar Series: I Background | II: The notch filter | III: The delay | IV: A new solar force? (You are here) | V: Modeling the escaping heat. | VI: The solar climate model | VII — Hindcasting | VIII — Predictions
Implacably, the discovery of a notch suggests a delay of anything from 10 to 20 years but most likely 11 years. (Don’t miss the delay post — two very big important concepts out in two posts). The big mystery is what could cause such a long delay in the correlation of solar radiation with temperatures on Earth?
David and I spent months wondering “what on Earth” could drive it. There were many possibilities though none of them seemed to be able to respond with the right timing: A resonant slop in ocean circulation could absorb extra energy, but it was difficult to see how the timing would be so tight with solar peaks. Likewise changes in ice or land cover. Then there are lunar cycles of 9 – 18 years, potentially generating atmospheric standing waves, but they were not synchronous with the sun.
Given that marine life can produce […]
A new paper (Moffa-Sánchez et al) reports that they looked at layers of dead plankton in ocean mud (otherwise known as foraminifera in marine sediments) and have reconstructed the temperature and salinity of a couple of spots in the North Atlantic between 818AD – 1780 with data on δ18O and the Mg/Ca ratios. One immediate thought, an aside, is that if this technique works, there is no shortage of ocean mud, surely, and perhaps we could drill and analyze more mud for solar correlations in other places. (I hear foraminifera live in the Southern Hemisphere too). Perhaps no one is looking for the connection with the sun?
Moffa-Sánchez et al find the big climate shifts (the 100-year variations) correlate with total solar irradiance (TSI). See especially that orange line black line track in the d graph below. I stress, correlations don’t mean causation and the mechanism is mere speculation. But I find the graph intruiging. There are a lot of turning points, and in pure “curve fitting” type of analysis, this is a better curve fit than the one with CO2. (Find me a turning point that matches with carbon dioxide!) I suspect we’ll be referring back to this paper, […]
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JoNova A science presenter, writer, speaker & former TV host; author of The Skeptic's Handbook (over 200,000 copies distributed & available in 15 languages).
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