by Larry Hamlin, July 28, 2019 in WUWT
The Los Angeles Times is at it again hyping anti science climate alarmist propaganda trying to conceal the global wide Medieval Warm Period and the Little Ice Age that are supported and justified by hundreds of scientific studies.
This climate alarmist propaganda Times article cites a new “study” that ridiculously attempts to deny these clearly established warm and cool periods in our past.
This alarmist hyped new “study” is addressed in a superb article at the JoNova website demonstrating the complete lack of scientific veracity of this studies claims.
There is nothing I can add to show how politically contrived and inane the claims are from this new “study” beyond the excellent presentation in the JoNova article.
Provided below are excerpts from this excellent article which demonstrate the lack of scientific credibility of the new “study” as well as the politically driven anti science climate alarmism bias of the Times.
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by Anthony Watts, July 30 2019 in WUWT
A review of state-of-the-art climate data tells a different story than what NOAA tells the public.
While media outlets scream “hottest ever” for the world in June and July (it’s summer) and opportunistic climate crusaders use those headlines to push the idea of a “climate crisis” the reality is for USA is that so far most of 2019 has been below normal, temperature-wise.
Little known data from the state of the art U.S. Climate Reference Network (which never seems to make it into NOAA’s monthly “state of the climate” reports) show that for the past nine months, six of them were below normal, shown in bold below.
| 201810 |
-0.18°F |
| 201811 |
-2.56°F |
| 201812 |
2.39°F |
| 201901 |
0.63°F |
| 201902 |
-3.15°F |
| 201903 |
-2.81°F |
| 201904 |
1.55°F |
| 201905 |
-1.13°F |
| 201906 |
-0.14°F |
Above: Table 1, U.S. average temperature anomaly from October 2018 to June 2019. Full data file here
Note the below average value for June, 2019 at -0.14°F
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Figure 1, U.S. average temperature anomaly from January 2005 to June 2019. Source of graph, NOAA, available here
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by JoNova, July 24, 2019
It’s all so obvious. If researchers start with models that don’t work, they can find anything they look for — even abject nonsense which is the complete opposite of what the models predicted.
Holy Simulation! Let’s take this reasoning and run with it — in the unlikely event we actually get relentless rising temperatures, that will imply that the climate sensitivity of CO2 is lower. Can’t see that press release coming…
Nature has sunk so low these days it’s competing with The Onion.
The big problem bugging believers was that global warming paused, which no model predicted, and which remains unexplained still, despite moving goal posts, searching in data that doesn’t exist, and using error bars 17 times larger than the signal. The immutable problem is that energy shalt not be created nor destroyed, so The Pause still matters even years after it stopped pausing. The empty space still shows the models don’t understand the climate — CO2 was supposed to be heating the world, all day, everyday. Quadrillions of Joules have to go somewhere, they can’t just vanish, but models don’t know where they went. If we can’t explain the pause, we can’t explain the cause, and the models can’t predict anything.
In studies like these, the broken model is not a bug, it’s a mandatory requirement — if these models actually worked, it wouldn’t be as easy to produce any and every conclusion that an unskeptical scientist could hope to “be surprised” by.
The true value of this study, if any, is in 100 years time when some psychology PhD student will be able to complete an extra paragraph on the 6th dimensional flexibility of human rationalization and confirmation bias.
Busted climate models can literally prove anything. The more busted they are, the better.
University of Exeter
A decade without any global warming is more likely to happen if the climate is more sensitive to carbon dioxide emissions, new research has revealed.
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La géologie, une science plus que passionnante … et diverse
