by Cap Allon, March 2, 2020 in Electroverse

Australia’s “Grand Solar Minimum” summer –which brought record cold/heat, drought/floods, fires, and dust storms– had one final sting in the tail: another flurry of rare summer snow.

While summer down-under officially ended on Saturday, Feb 29, another blast of heavy, unexpected snow began burying parts of Tasmania on Wednesday, Feb 26.

Mountainous areas of the isolated island state reported large accumulations to close out the week, with local meteorologists warning yet more snow could settle above 1,000 m (3,280 ft) –including at Mount Field and Wellington– over the coming days.



NOAA Relies on ‘Russian Collusion’ to Claim January Was Hottest Month on Record

by Anthony Watts, February 29, 2020 in WUWT

In a report generating substantial media attention this month, the National Oceanic and Atmospheric Administration (NOAA) claimed January 2020 was the hottest January on record. In reality, the claim relies on substantial speculation, dubious reporting methods, and a large, very suspicious, extremely warm reported heat patch covering most of Russia.

The January 2020 Climate Assessment Report, released by NOAA’s National Center for Environmental Information (NCEI), was accompanied by a map showing a giant red menace of extraordinary asserted warmth extending from the Russian border with Poland well into Siberia. Yet, the asserted hot spot appears nowhere else.


Figure 1: Map of temperature departure provided by NOAA/NCEII. Note the huge red spot over Russia.

Continuer la lecture de NOAA Relies on ‘Russian Collusion’ to Claim January Was Hottest Month on Record

Tendency, Convenient Mistakes, and the Importance of Physical Reasoning.

by Pat Frank, March 1, 2020 in WUWT

Last February 7, statistician Richard Booth, Ph.D. (hereinafter, Rich) posted a very long critique titled, What do you mean by “mean”: an essay on black boxes, emulators, and uncertainty” which is very critical of the GCM air temperature projection emulator in my paper. He was also very critical of the notion of predictive uncertainty itself.

This post critically assesses his criticism.

An aside before the main topic. In his critique, Rich made many of the same mistakes in physical error analysis as do climate modelers. I have described the incompetence of that guild at WUWT here and here.

Rich and climate modelers both describe the probability distribution of the output of a model of unknown physical competence and accuracy, as being identical to physical error and predictive reliability.

Their view is wrong.

Unknown physical competence and accuracy describes the current state of climate models (at least until recently. See also Anagnostopoulos, et al. (2010), Lindzen & Choi (2011), Zanchettin, et al., (2017), and Loehle, (2018)).

GCM climate hindcasts are not tests of accuracy, because GCMs are tuned to reproduce hindcast targets. For example, here, here, and here. Tests of GCMs against a past climate that they were tuned to reproduce is no indication of physical competence.

When a model is of unknown competence in physical accuracy, the statistical dispersion of its projective output cannot be a measure of physical error or of predictive reliability.

Ignorance of this problem entails the very basic scientific mistake that climate modelers evidently strongly embrace and that appears repeatedly in Rich’s essay. It reduces both contemporary climate modeling and Rich’s essay to scientific vacancy.

The correspondence of Rich’s work with that of climate modelers reiterates something I realized after much immersion in published climatology literature — that climate modeling is an exercise in statistical speculation. Papers on climate modeling are almost entirely statistical conjectures. Climate modeling plays with physical parameters but is not a branch of physics.

I believe this circumstance refutes the American Statistical Society’s statement that more statisticians should enter climatology. Climatology doesn’t need more statisticians because it already has far too many: the climate modelers who pretend at science. Consensus climatologists play at scienceness and can’t discern the difference between that and the real thing.

Climatology needs more scientists. Evidence suggests many of the good ones previously resident have been caused to flee.