{"id":22459,"date":"2019-06-25T17:58:02","date_gmt":"2019-06-25T22:58:02","guid":{"rendered":"http:\/\/www.realclimate.org\/?p=22459"},"modified":"2019-06-26T19:46:42","modified_gmt":"2019-06-27T00:46:42","slug":"absence-and-evidence","status":"publish","type":"post","link":"https:\/\/www.realclimate.org\/index.php\/archives\/2019\/06\/absence-and-evidence\/","title":{"rendered":"Absence and Evidence"},"content":{"rendered":"
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Guest commentary by Michael Tobis, a retired climate scientist. He is a software developer and science writer living in Ottawa, Ontario.<\/small><\/em><\/p>\n\n\n\n

A recent opinion piece<\/a> by economist Ross McKitrick in the Financial Post, which attracted considerable attention in Canada, carried the provocative headline \u201cThis scientist proved climate change isn\u2019t causing extreme weather – so politicians attacked\u201d.<\/p>\n\n\n\n

In fact, the scientist referenced in the headline, Roger Pielke Jr., proved no such thing. He examined some data, but he did not find compelling evidence regarding whether or not human influence is causing or influencing extreme events.<\/p>\n\n\n\n

Should such a commonplace failure be broadly promoted as a decisive result that merits public interest? <\/p>\n\n\n\n\n\n\n\n

ABSENCE OF EVIDENCE VERSUS EVIDENCE OF ABSENCE<\/strong><\/p>\n\n\n\n

Statistics is a vital tool of science, but it is not the only one. It is most effective when dealing with large quantities of data. Using statistical methods to detect the effect of one factor among several amounts to proving that the other factors did not align as a matter of happenstance. The more abundant the data, the less likely such a coincidence. <\/p>\n\n\n\n

In the case of extreme weather, the number of sample points is small because extreme events by definition are rare. Up until the beginning of the satellite era, records of past events are often incomplete. There is little we can do to improve the amount of such data at hand. Because the data are irredeemably scarce, and time series short, using purely \u201cfrequentist\u201d statistical methods to decide whether or not climate change makes a certain type of severe event more likely will tend to be inconclusive.<\/p>\n\n\n\n

Limiting attention only to the most severe storms of a particular type, and then further limiting it to those causing the most extreme financial damage, drastically reduces the number of samples considered, and so further reduces the likelihood that a real trend will be detected.<\/p>\n\n\n\n

It\u2019s a well-known motto in research that \u201cabsence of evidence\u201d is not \u201cevidence of absence\u201d. It\u2019s well known because it is a common beginners\u2019 error to conflate these. Scientists in training quickly learn that \u201cwe find no evidence of phenomenon P\u201d is not the same as \u201cwe found evidence that phenomenon P is false\u201d. The proposition in question could well be true but the analysis may lack enough data to show it. (The test is said to be underpowered). Yet a systematic neglect of this simple point is pervasive among those skeptical of the risks of climate change.<\/p>\n\n\n\n

Those who wish to avoid vigorous climate policy have gotten a lot of mileage out of inconclusive results. <\/p>\n\n\n\n

HOW TO GET INCONCLUSIVE RESULTS<\/strong><\/p>\n\n\n\n

There is, along the periphery of climate science, an enthusiastic audience for null results: people who don\u2019t want to accept the seriousness of climate risk will celebrate any absence of a demonstrated trend or inconclusive attribution. But it\u2019s always possible to obtain a null result, i.e., a lack of statistical significance, if one seeks it, by reducing the amount of data under consideration.<\/p>\n\n\n\n

Most science works the other way around, looking for relationships and trends that actually do seem to be happening! There is, under ordinary circumstances an audience for significant results. Were we not operating in a politicized context, detection would be considered more important than lack thereof. <\/p>\n\n\n\n

To increase the likelihood of detection, we can look at larger categories of event. For example, in a 2013 report, the European Academies\u2019 Science Advisory Council, examined trends in the specific extremes of heat and cold, precipitation, storms, winds and surges, and drought. The agency found<\/a> evidence for \u201coverall increases in the frequency and economic costs of extreme events\u201d.<\/p>\n\n\n\n

Much of Pielke\u2019s work focuses largely on insurance costs of landfalling hurricanes in the USA, an especially rare phenomenon influenced by numerous factors and one with especially peculiar statistics. It\u2019s an ideal field in which to get a null result, if that\u2019s what the investigator is seeking.<\/p>\n\n\n\n

An important point in looking at actuarial damages is that building standards and warning systems have systematically improved. In the absence of a climate-driven trend, we\u2019d expect damages to decline. This counter-argument is made in many places, for example Dr. Kevin Trenberth in a book review<\/a>:

\u201c[Pielke] ignores the benefits from improvements in hurricane warning times, changes in building codes, and other factors that have been important in reducing losses.”<\/em>

Another approach to hide climate-driven damage is to blur trends. We expect (from physical arguments and models) and find (from observations) increasing precipitation at higher latitudes and decreasing precipitation in dry subtropical latitudes. Aggregating them, the net result is no global trend in drought, and true to form McKitrick celebrates this result as well.<\/p>\n\n\n\n

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Source<\/a>: A dryer southwest and wetter northeast, so no overall trend. An example of how averaging can obscure significant results.<\/figcaption><\/figure>\n\n\n\n

Aggregating such non-results and obscured results brings us to McKitrick\u2019s sweeping conclusion.<\/p>\n\n\n\n

\u201cThere\u2019s no trend in hurricane-related flooding in the U.S. Nor is there evidence of an increase in floods globally. Since 1965, more parts of the U.S. have seen a decrease in flooding than have seen an increase. And from 1940 to today, flood damage as a percentage of GDP has fallen to less than 0.05 per cent per year from about 0.2 per cent. And on it goes. There\u2019s no trend in U.S. tornado damage (in fact, 2012 to 2017 was below average). There\u2019s no trend in global droughts. Cold snaps in the U.S. are down but, unexpectedly, so are heatwaves.”<\/p><\/blockquote>\n\n\n\n

McKitrick leaves the impression that all these conclusions are unequivocal, and that none of them have been hamstrung by approaches that are unlikely to yield significant trends.<\/p>\n\n\n\n

Even at face value these specific claims, combined with a world-weary \u201cand on it goes\u201d isn\u2019t enough to logically support his broad conclusion that \u201cThe bottom line is there\u2019s no solid connection between climate change and the major indicators of extreme weather.\u201d

Jumping from specific observations to a broad conclusion, as McKitrick does, is rhetorical, not scientific. In addition to being a logical fallacy, it ignores a great deal of evidence to the contrary. 
<\/p>\n\n\n\n

\u201cThis cow is black, and that one, and that one, and on it goes,\u201d is not enough to prove that all cows are black when there are spotted cows aplenty in the field.<\/p>\n\n\n\n

TIME AND TIDE<\/strong><\/p>\n\n\n\n

The evidence to the effect that there is a connection between anthropogenic climate change and increasing severe events, far from being absent, is in fact rapidly accumulating.<\/p>\n\n\n\n

McKitrick makes much of Pielke\u2019s role in a 2006 conference on severe weather which released a consensus document, the Hohenkammer Consensus, that was a fair assessment of knowledge at the time. That report asserts that<\/a> \u201cIn the near future the quantitative link (attribution) of trends in storm and flood losses to climate changes related to GHG emissions is unlikely to be answered unequivocally.\u201d

It is in exactly this pool of equivocality that Pielke has been content to operate. But is that pool shrinking?<\/p>\n\n\n\n

Both science and climate change itself are advancing at a rapid pace. What was true in the \u201cnear future\u201d of 2006 is not necessarily true today! So in using more advanced methods to study a more advanced disruption, has the situation changed?<\/p>\n\n\n\n

In fact it has. Methods for attributing individual severe events partially to climate change have emerged. In 2016, the National Academy of Science of the USA issued a report entitled Attribution of Extreme Weather Events In the Context of Climate Change<\/a>, which enumerates the ongoing efforts. Among its key conclusions: <\/p>\n\n\n\n

“The ability to understand and explain extreme events in the context of climate change has developed very rapidly over the past decade. In the past, a typical climate scientist\u2019s response to questions about climate change\u2019s role in any given extreme weather event was, \u2018We cannot attribute any single event to climate change.\u2019 The science has advanced to the point that this is no longer true.”<\/p><\/blockquote>\n\n\n\n

While not without complexity or controversy, attribution studies are complex and subject to the usual debates and disagreements that evolving fields of science undergo. Such work is extensive and carried out by multiple research groups in multiple countries (see also Going To Extremes<\/a> from this site).<\/p>\n\n\n\n

The Bulletin of the American Meteorological Society has, since 2011, been releasing special issues on the subject of extreme event attribution. In recent issues, cases of severe events have been identified that would have been essentially impossible in the undisturbed climate. New examples have been published recently, indicating that heat waves in Europe and North America<\/a> and in Japan<\/a> couldn\u2019t have occurred in the absence of human-caused climate change.<\/p>\n\n\n\n

So McKitrick\u2019s claim that \u201cthe bottom line is there\u2019s no solid connection between climate change and the major indicators of extreme weather, despite Trudeau\u2019s claims to the contrary\u201d is at best out-of-date and ill-informed. Some might call it deceptive.<\/p>\n\n\n\n

One can always dismiss evidence one doesn\u2019t like as not \u201csolid\u201d, of course. But by now, there\u2019s quite a lot of evidence to dismiss and McKitrick, rather than addressing it avoids any mention of any of it whatsoever. One expects better from an academic.<\/p>\n\n\n\n

SO WHAT IS REALLY GOING ON?<\/strong><\/p>\n\n\n\n

While determining exactly which severe events are more likely already under climate change, and which will become so, we should begin by focusing on what is known currently. <\/p>\n\n\n\n

Quoting from the aforementioned 2006 consensus document<\/a> that McKitrick celebrates, it was already known that:<\/p>\n\n\n\n