The fake news press is 100% certain that US hurricanes are getting worse and more common due to global warming.

Not long ago, they were blaming the record low number of hurricanes on global warming.

The reality is that hurricane season temperatures have plummeted at all US Atlantic and Gulf Coast states.

The last really hot hurricane season was in 1954, which was also one of the worst hurricane seasons on record. In 1954, New England was hit by two major hurricanes within ten days. They were the last major hurricanes to hit New England

11 Sep 1954, Page 1 – The Edwardsville Intelligencer

The Senator Joe McCarthy hearings were going on during those hurricane strikes. Senator McCarthy was  despised by Democrats because they felt he was prosecuting people based on their beliefs – which is now the standard practice of the Democratic Party.

01 Sep 1954, Page 1 – The Evening Independent

A few weeks later, the most powerful hurricane of the summer, Hazel, also damaged New England. It was Canada’s deadliest hurricane on record.

16 Oct 1954, Page 1 – The Burlington Free Press

The frequency of hurricanes and major hurricanes has declined in the US over the past 150 years.

Climate scientists have been making the same idiotic forecasts about hurricanes for at least 30 years.

Ellensburg Daily Record – Google News Archive Search

As with everything else in climate science, it is all based on junk science, superstition about a trace gas, and fraud.

via The Deplorable Climate Science Blog

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September 9, 2017 at 09:52AM

A recent post at Friends of Science alerted me to an important proof against the CO2 global warming claim. It was included in John Christy’s testimony 29 Mar 2017 at the House Committee on Science, Space and Technology. The text below is from that document which can be accessed here. (My bolds)

Main Point: IPCC Assessment Reports show that the IPCC climate models performed best versus observations when they did not include extra GHGs and this result can be demonstrated with a statistical model as well.

(5)  A simple statistical model that passed the same “scientific-method” test

The IPCC climate models performed best versus observations when they did not include extra GHGs and this result can be demonstrated with a statistical model as well. I was coauthor of a report which produced such an analysis (Wallace, J., J. Christy, and J. D’Aleo, “On the existence of a ‘Tropical Hot Spot’ & the validity of the EPA’s CO2 Endangerment Finding – Abridged Research Report”, August 2016 (Available here ).

In this report we examine annual estimates from many sources of global and tropical deep-layer temperatures since 1959 and since 1979 utilizing explanatory variables that did not include rising CO2 concentrations. We applied the model to estimates of global and tropical temperature from the satellite and balloon sources, individually, shown in Fig. 2 above. The explanatory variables are those that have been known for decades such as indices of El Nino-Southern Oscillation (ENSO), volcanic activity, and a solar activity (e.g. see Christy and McNider, 1994, “Satellite greenhouse signal”, Nature, 367, 27Jan). [One of the ENSO explanatory variables was the accumulated MEI (Multivariate ENSO Index, see http://ift.tt/2k0cMgq) in which the index was summed through time to provide an indication of its accumulated impact. This “accumulated-MEI” was shown to be a potential factor in global temperatures by Spencer and Braswell, 2014 (“The role of ENSO in global ocean temperature changes during 1955-2011 simulated with a 1D climate model”, APJ.Atmos.Sci. 50(2), 229-237, DOI:10.1007/s13143-014- 001-z.) Interestingly, later work has shown that this “accumulated-MEI” has virtually the same impact as the accumulated solar index, both of which generally paralleled the rise in temperatures through the 1980s and 1990s and the slowdown in the 21st century. Thus our report would have the same conclusion with or without the “accumulated-MEI.”]

The basic result of this report is that the temperature trend of several datasets since 1979 can be explained by variations in the components that naturally affect the climate, just as the IPCC inadvertently indicated in Fig. 5 above. The advantage of the simple statistical treatment is that the complicated processes such as clouds, ocean-atmosphere interaction, aerosols, etc., are implicitly incorporated by the statistical relationships discovered from the actual data. Climate models attempt to calculate these highly non-linear processes from imperfect parameterizations (estimates) whereas the statistical model directly accounts for them since the bulk atmospheric temperature is the response-variable these processes impact. It is true that the statistical model does not know what each sub-process is or how each might interact with other processes. But it also must be made clear: it is an understatement to say that no IPCC climate model accurately incorporates all of the non-linear processes that affect the system. I simply point out that because the model is constrained by the ultimate response variable (bulk temperature), these highly complex processes are included.

The fact that this statistical model explains 75-90 percent of the real annual temperature variability, depending on dataset, using these influences (ENSO, volcanoes, solar) is an indication the statistical model is useful. In addition, the trends produced from this statistical model are not statistically different from the actual data (i.e. passing the “scientific-method” trend test which assumes the natural factors are not influenced by increasing GHGs). This result promotes the conclusion that this approach achieves greater scientific (and policy) utility than results from elaborate climate models which on average fail to reproduce the real world’s global average bulk temperature trend since 1979.

The over-warming of the atmosphere by the IPCC models relates to a problem the IPCC AR5 encountered elsewhere. In trying to determine the climate sensitivity, which is how sensitive the global temperature is relative to increases in GHGs, the IPCC authors chose not to give a best estimate. [A high climate sensitivity is a foundational component of the last Administration’s Social Cost of Carbon.] The reason? … climate models were showing about twice the sensitivity to GHGs than calculations based on real, empirical data. I would encourage this committee, and our government in general, to consider empirical data, not climate model output, when dealing with environmental regulations.

Summary

Planning requires assumptions because no one has knowledge of the future, only informed opinions.  Christy makes the case that our assumptions should be based on empirical data rather than models that are driven by theoretical assumptions.  When the CO2 sensitivity assumption is removed from climate models they come much closer to observed temperature measurements.  Statistical analysis shows that at least 75% of observed warming comes from factors other than CO2.  That analysis also correlates with the accumulated effects of oceanic circulations, principally the ENSO index.

via Science Matters

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September 9, 2017 at 09:32AM

Despite where we are in the sun’s cycle, activity on the sun has dramatically picked up over the past few days. We don’t yet fully understand everything that is happening.

If you still have your solar viewing glasses from the eclipse, now is a good time to slap them on and look up at the sun. You’ll see two big dark areas visible on our star. These massive sunspots are regions of intense and complicated magnetic fields that can produce solar flares – bursts of high-energy radiation. You can just make them out with solar viewing glasses, but they’re better viewed through a solar telescope.

These two huge sunspots are currently causing quite a bit of consternation and interest. The solar storms they’ve sent toward Earth may affect communications and other technologies like GPS and radio signals. They’re causing amazing displays of the Northern and Southern Lights. And space weather scientists like us are excited because we wouldn’t normally expect this much activity from the sun at the moment.

The sun goes through 11-year cycles of solar activity. What scientists call a solar maximum is the time in the cycle when the sun is putting out the most energy. That’s when we tend to see the most sunspots, solar flares and associated solar storms. Some solar maxima are larger or more active than others – such as the 1990-1991 solar max. But this last cycle, which peaked in 2014, was quite small, and there were few large geomagnetic storms.

We’re heading into the bottom of solar minimum, when the sun tends to have fewer sunspots, solar flares and coronal mass ejections – large expulsions of plasma, electrons and ions, and magnetic fields. But despite where we are in the sun’s cycle, activity on the sun has dramatically picked up over the past few days. On and off, these two sunspots have been flaring and shooting out coronal mass ejections, directed toward Earth.

So what’s going on with the sun? And should we be concerned about this somewhat out-of-character solar behavior?

Here’s what’s happened so far

On September 4, the sun started sputtering. A moderately large flare (classified as an M5.5) erupted at approximately 18:30 UTC. It produced a coronal mass ejection aimed at Earth.

The sun continued to flare on September 5. A solar energetic particle event from the previous day’s activity arrived at the Earth, where it likely affected radio communications as well as the health of satellite systems.

On September 6, the sun produced two massive X-class flares. This is the category for the strongest of all solar flares.

NASA announced one was the most powerful since at least 2008. It produced another coronal mass ejection.

Over the next day, the same sunspots continued to spit out more solar flares. It took about an hour for the solar energetic particles they emitted to arrive at Earth. These protons are incredibly fast-moving. They can affect communication systems, typically in the polar regions where they are more likely to enter into the Earth’s atmosphere. As with all increases of radiation in space, they can also affect satellite systems and the health of astronauts.

Early in the morning hours of September 7 in the U.S., that first coronal mass ejection that erupted from the sun three days earlier arrived at Earth. Because of the way its magnetic field aligned with Earth’s, it generated only a small geomagnetic storm.

After being detected by spacecraft upstream from Earth in the solar wind, the massive coronal mass ejection from September 6 also hit Earth on the evening of September 7 EDT. Its arrival was a few hours earlier than space weather forecasting agencies around the world predicted.

Full post

via The Global Warming Policy Forum (GWPF)

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September 9, 2017 at 06:45AM

By Paul Homewood

 

 

A welcome dose of reality from Cato:

 

 

“Harvey Is What Climate Change Looks Like: It’s time to open our eyes and prepare for the world that’s coming.” That August 28 Politico article by Slate weatherman Eric Holthaus was one of many trying too hard to blame the hurricane and/or flood on climate change.

Such stories are typically infused with smug arrogance. Their authors claim to be wise and well-informed, and anyone who dares to question their “settled science” must need to have their eyes pried open and their mouths shut.

There will doubtless be similar “retroactive forecasting” tales about Irma, so recent story-telling about Harvey may provide a precautionary warning for the unwary.

I am an economist, not a climatologist.* But blaming Harvey on climate change apparently demands much lower standards of logic and evidence than economists would dare describe as serious arguments.

Atlantic’s climate journalist said, “Harvey is unprecedented—just the kind of weird weather that scientists expect to see more of as the planet warms.” But Harvey’s maximum rainfall of 51.88 inches barely exceeded that from Tropical Storm Amelia in 1978 (48”) and Hurricane Easy in 1950 (45”). And what about Tropical Storm Claudette in 1979, which put down 42 inches in 24 hours near Houston (Harvey took three days to do that)? In such cases, attributing today’s extreme weather to “climate change” regardless of what happens (maybe droughts, maybe floods) is what the philosopher Karl Popper called “pseudoscience.” If some theory explains everything, it can’t be tested and it is therefore not science. (Popper’s favorite examples of pseudoscience were communism and psychoanalysis.)

Seemingly plausible efforts to connect Harvey to climate change are precariously based on another unusual event in 2015–16, not long-term climate trends. In the Atlantic, Robinson Meyer wrote that “Harvey benefitted from unusually toasty waters in the Gulf of Mexico. As the storm roared toward Houston last week, sea-surface waters near Texas rose to between 2.7 and 7.2 degrees Fahrenheit above average.” Thank you, 2015–16 El Nino.

Meyer’s source is a single unsourced sentence from “Climate Signals beta” from the Rockefeller Foundation’s “Climate Nexus” project run by Hunter Cutting (“a veteran political director who develops communications strategy”). Perhaps it would be wiser to consult the National Hurricane Center about Gulf temperatures, which shows they are averaging about one degree (F) above the baseline.

Looking back at any unpredicted weather anomaly, “fact-checking” journalists can always count on Michael Mann and Kevin Trenberth to spin some tale explaining why any bad weather (but never good weather!) must surely be at least aggravated by long-term global climate trends. “It’s a fact: climate change made Hurricane Harvey more deadly,” writes Michael Mann. Gulf sea surface temperatures have increased from about 86 degrees to 87 “over the past few decades,” he says, causing “3–5% more moisture in the atmosphere.” He neglected to point out other compensatory things he surely knows, like that the same climate science predicts a more stable tropical atmosphere, reducing the upward motion necessary for hurricanes.

Even The Washington Post’s esteemed Jason Samenow got onto shaky ground, writing that “rainfall may have been enhanced by 6 percent or so, or a few inches.” It would have been nice if he noted that Harvey’s maximum observed rainfall of 51.88 inches is statistically indistinguishable from the aforementioned Amelia’s 48, forty years ago.

In either case, to blame the Gulf’s temperature and moisture in August 2017 on a sustained global increase in water temperatures requires more than theory or “confidence” (faith). It requires evidence.

As it happens, sea surface temperatures (SSTs) were not rising significantly, if at all, during the years between the two super-strong El Ninos of 1997–98 and 2015–16. On the contrary, a January 2017 survey of four major data sources finds that “since 1998, all datasets show a slowdown of SST increase compared with the 1983–1998 period.” That may sound as if SST had been increasing rapidly before 1998, but that too is unclear: “Prior to 1998, the temperature changes in Global, Pacific, and Southern Oceans show large discrepancies among [four leading estimates], hindering a robust detection of both regional and global OHC [ocean heat content] changes.”

From 1998 to 2012, the evidence on sea surface temperatures becomes even more inconvenient. Two of the four studies show “weak warming” near the surface while the other two show “cooling, coincident with the global surface temperature slowdown [emphasis added].” In other words, the embarrassingly prolonged 1997–2014 pause or “hiatus” in global warming is also apparent in oceanic surface temperatures, not just land and atmospheric temperatures.

Keep in mind what the vaunted “climate change consensus” means. By averaging four estimates, NASA declares “Globally-averaged temperatures in 2016 were 1.78 degrees Fahrenheit (0.99 degrees Celsius) warmer than the mid-20th century mean.” The underlying yearly estimates are deviations from that mid-century meanؙ—“anomalies” rather than actual temperatures.

To convert anomalies into degrees NASA had to use computer models to add anomalies to temperatures in the base period, 1951–80, where the data are hardly perfect. As a result, “For the global mean,” NASA explains, “the most trusted models produce a value of roughly 14°C, i.e. 57.2°F, but it may easily be anywhere between 56 and 58°F and regionally, let alone locally, the situation is even worse.”

It might be rude to notice the range of error between 56 and 58°F globally (“let alone locally”) is larger than NASA’s supposed increase of 1.78 degrees over many decades. Note too that NASA’s ostensibly cooler base period, 1951–80, includes the second and third biggest floods in U.S. history.

My main point here is simple: Weather is highly variable. There’s a great deal of noise in hurricane and flood data, and it is impossible to attribute a single hurricane or a flood to the slight rise in temperature. Yes, warmer ocean temperatures would logically seem to correlate with more or stronger hurricanes, but as shown below, they don’t.

*Cato climate scientist Patrick Michaels contributed his $0.02 to this post, and the Accumulated Cyclone Energy chart comes from meteorologist Ryan Maue, also with Cato.

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via NOT A LOT OF PEOPLE KNOW THAT

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September 9, 2017 at 06:06AM