Did You Know the Greatest Two-Year Global Cooling Event Just Took Place?

Did You Know the Greatest Two-Year Global Cooling Event Just Took Place?

[Important to acknowledge these articles, because they need “inclusion” as well. Global cooling doesn’t support the MSM narrative they want everyone to believe.]

global cooling is not newsworthy - Did You Know the Greatest Two-Year Global Cooling Event Just Took Place?

By Aaron Brown

Would it surprise you to learn the greatest global two-year cooling event of the last century just occurred? From February 2016 to February 2018 (the latest month available) global average temperatures dropped 0.56°C. You have to go back to 1982-84 for the next biggest two-year drop, 0.47°C—also during the global warming era. All the data in this essay come from GISTEMP Team, 2018: GISS Surface Temperature Analysis (GISTEMP). NASA Goddard Institute for Space Studies (dataset accessed 2018-04-11 at https://data.giss.nasa.gov/gistemp/). This is the standard source used in most journalistic reporting of global average temperatures.

The 2016-18 Big Chill was composed of two Little Chills, the biggest five-month drop ever (February to June 2016) and the fourth biggest (February to June 2017). A similar event from February to June 2018 would bring global average temperatures below the 1980s average. February 2018 was colder than February 1998. If someone is tempted to argue that the reason for recent record cooling periods is that global temperatures are getting more volatile, it’s not true. The volatility of monthly global average temperatures since 2000 is only two-thirds what it was from 1880 to 1999.

None of this argues against global warming. The 1950s was the last decade cooler than the previous decade, the next five decades were all warmer on average than the decade before. Two-year cooling cycles, even if they set records, are statistical noise compared to the long-term trend. Moreover, the case for global warming does not rely primarily on observed warming; it has models, historical studies and other science behind it. Another point is both February 1998 and February 2016 were peak El Niño months so the record declines are starting from high peaks—but it’s also true that there have been many other peak El Niño months in the past century and none were followed by such dramatic cooling.

My point is that statistical cooling outliers garner no media attention. The global average temperature numbers come out monthly. If they show a new hottest year on record, that’s a big story. If they show a big increase over the previous month, or the same month in the previous year, that’s a story. If they represent a sequence of warming months or years, that’s a story. When they show cooling of any sort—and there have been more cooling months than warming months since anthropogenic warming began—there’s no story.

The public and media case for global warming, unlike the scientific case, depends heavily on short-term observation of actual temperatures. Biased reporting suggests warming is much steadier than it is. If the global temperature really showed half a century of uninterrupted warming—with only warming records, no cooling records—then people with nuanced views of plausible future temperatures could be dismissed as deniers. Annual atmospheric CO2 levels have gone up in pretty much a straight line since 1960, if temperatures did the same thing, the link to CO2 would be direct and obvious. In fact, it is real but complex, and those complexities are important for analyzing policy choices.

Then there is the danger of backlash. Suppose the next five months are similar to the same five months in 2017 and 2016. At some point, the news will leak out that all global warming since 1980 has been wiped out in two and a half years, and those record-setting cooling events went unreported—in fact, the headlines while they were occurring referenced warming from other times. Some people could go from uncritical acceptance of steadily rising temperatures to uncritical refusal to accept any warming at all.

This reminds me of the reporting on police shootings during most of my life. If a police officer was killed it was several big stories—the killing, the hunt for the killer, the funeral of the officer, the trial and punishment of the killer. If a police officer killed a civilian, it was seldom reported at all. If it was, it was in the context of a community reaction to the killing, and quickly diverted into police procedures and community relations rather than the killing itself. The shockingly high death rates in jails, especially in the first three days after arrest, were also not considered newsworthy. As a libertarian, I found this frustrating because it hid from people the violence inherent in the enforcement of laws that no one would think were worth killing for. Then, with Ferguson in August 2014, everything changed and reporting became more even-handed. The issues surrounding violence by and against police were no less complex, but at least the public had more balanced facts to consider.

One way to measure bias in reporting is by ranking events by standard deviations. It’s by no means perfect, but it does provide an objective—if rough—way to compare warming and cooling reporting. The 0.56°C cooling of the last two years is a 3.0 standard deviation event, based on the last century of temperature data. A conventional threshold is 2.0 standard deviations, events below this may be suggestive, but they can also easily be random noise. The two Little Chills in 2016 and 2017 were 3.5 and 2.7 standard deviation events.

Compare that to the news attention if a year is the hottest on record. That happens 12% of the time, a 1.2 standard deviation event. The three years of records in a row (2014, 2015 and 2016)? After a record-setting year, 42% of the time the next year sets a record as well. So this sequence is a 2.1 standard deviation event. Six record-setting years since 2000 is 1.7 standard deviations.

If standard deviations are too abstract, consider the number of times something has happened in the past. There has been saturation coverage of the fact that 13 of the 18 years since 2000 were hotter than any previous year. 37 out of 71 years since 1930 (I start at 1930, 50 years after the global temperature series begins, to make it meaningful that a year is hotter than all previous years) have been followed by 13 or more of the next 18 years hotter than any previous year. That’s more than half the time. Twelve times all 18 years were hotter than any previous year—and many of those were before global warming started. Compare that to the cooling events of the last two years, and of February to June 2016, neither of which had happened in a century; or the cooling event of February to June 2017 which had happened only three times before.

How should the global average temperature data be reported? There should be equal attention to warming and cooling records. Coverage should be based on how unusual the event is, not whether or not it increases support for favored policies. Ordinary events that have happened many times in the past, before global warming, should not be treated as evidence supporting global warming. Mildly unusual events, in the 2 to 3 standard deviation range, should be reported with strong qualifiers that they have little meaning compared to the overall weight of evidence for global warming. Very unusual events, 3 standard deviations and more, deserve investigation, even if that means burdening the reader with the somewhat technical material.

Temperatures may climb from here, so these unusual cooling events need not make mainstream news. But unless that happens soon—and remember that would be bad news—climate reporters will have to discuss cooling, which will mean presenting a more complex story that has been typical in the past. I hope they are up to that task.

Aaron Brown is the author of many books, including The Poker Face of Wall Street.  He’s a long-time risk manager in the hedge fund space.  

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