Category Archives: General Science

Climate Exaggerators

Cliff Mass on the academic wages of debunking them:

Every time I correct misinformation in the media like this, I get savaged by some “environmentalists” and media. I am accused of being a denier, a skeptic, an instrument of the oil companies, and stuff I could not repeat in this family friendly blog. Sometimes it is really hurtful. Charles Mudede of the Stranger is one of worst of the crowd, calling me “dangerous” and out of my mind (see example below).

A postdoc at the UW testified at the Environment Committee of the Washington State House saying that I was a contrarian voice. I spoke to her in person a few days later and asked where my science was wrong–she could not name one thing. But she told me that my truth telling was “aiding” the deniers. We agreed to disagree.

My efforts do not go unnoticed at the UW, with my department chairman and leadership in the UW Climate Impacts Group telling me of “concerns” with my complaints about hyped stories on oyster deaths and snowpack. One UW professor told me that although what I was saying was true, I needed to keep quiet because I was helping “the skeptics.” Probably not good for my UW career.

I believe scientists must provide society with the straight truth, without hype or exaggeration, and that we must correct false or misleading information in the media. It is not our role to provide inaccurate information so that society will “do the right thing.” History is full of tragic examples of deceiving the public to promote the “right thing”–such as weapons of mass destruction claims and the Iraq War.

Global warming forced by increasing greenhouse gases is an extraordinarily serious challenge to our species that will require both mitigation (reducing emissions) and adaptation (preparing ourselves to deal with the inevitable changes). Society can only make the proper decisions if they have scientists’ best projections of what will happen in the future, including the uncertainties.

What a concept.

Climate Evangelists

How they’re taking over your weather forecasts.

Pretty sure that meteorologists in general aren’t part of the BS 97%, though. Interesting comment that weather is the only thing keeping local news alive. It’s the only reason I generally turn it on. I haven’t noticed and of the LA weathercasters talking about climate so far, though, fortunately.

Gavin Schmidt

He attempts to discredit Judith Curry, and you’ll never guess what happens next!

There is one wonderful thing about Gavin’s argument, and one even more wonderful thing.

The wonderful thing is that he is arguing that Dr. Curry is wrong about the models being tuned to the actual data during the period because the models are so wrong (!).

The models were not tuned to consistency with the period of interest as shown by the fact that – the models are not consistent with the period of interest. Gavin points out that the models range all over the map, when you look at the 5% – 95% range of trends. He’s right, the models do not cluster tightly around the observations, and they should, if they were modeling the climate well.

Here’s the even more wonderful thing. If you read the relevant portions of the IPCC reports, looking for the comparison of observations to model projections, each is a masterpiece of obfuscation on this same point. You never see a clean, clear, understandable presentation of the models-to-actuals comparison. But look at those histograms above, direct from the hand of Gavin. It’s the clearest presentation I’ve ever run across that the models run hot. Thank you, Gavin.

Yes, thank you.

[Update a while later]

Semi-related: Chelsea HubbellClinton tweets about science, and you’ll never guess what happened next!

Mindless Eating

and mindless research:

Problems with p-hacking are by no means exclusive to Wansink. Many scientists receive only cursory training in statistics, and even that training is sometimes dubious. This is disconcerting, because statistics provide the backbone of pretty much any research looking at humans, as well as a lot of research that doesn’t. If a researcher is trying to tell whether changing something (like the story someone reads in a psychology experiment, or the drug someone takes in a pharmaceutical trial) causes different outcomes, they need statistics. If they want to detect a difference between groups, they need statistics. And if they want to tease out whether one thing could cause another, they need statistics.

The replication crisis in psychology has been drawing attention to this and other problems in the field. But problems with statistics extends far beyond just psychology, and the conversation about open science hasn’t reached everyone yet. Nicholas Brown, one of the researchers scrutinizing Wansink’s research output, told Ars that “people who work in fields that are kind of on the periphery of social psychology, like sports psychology, business studies, consumer psychology… have told me that most of their colleagues aren’t even aware there’s a problem yet.”

I think the hockey stick episode shows that this is a problem with climate research as well.

The point of peer review has always been for fellow scientists to judge whether a paper is of reasonable quality; reviewers aren’t expected to perform an independent analysis of the data.

“Historically, we have not asked peer reviewers to check the statistics,” Brown says. “Perhaps if they were [expected to], they’d be asking for the data set more often.” In fact, without open data—something that’s historically been hit-or-miss—it would be impossible for peer reviewers to validate any numbers.

Peer review is often taken to be a seal of approval on research, but it’s actually more like a small or large quality boost, depending on the reviewers and scientific journal in question. “In general, it still has a good influence on the quality of the literature,” van der Zee said to Ars. But “it’s a wildly human process, and it is extremely capricious,” Heathers points out.

There’s also the question of what’s actually feasible for people. Peer review is unpaid work, Kirschner emphasizes, usually done by researchers on top of their existing heavy workloads, often outside of work hours. That often makes devoting the time and effort needed to catch dodgy statistics impossible. But Heathers and van der Zee both point to a possible generational difference: with better tools and a new wave of scientists who aren’t being asked to change long-held habits, better peer reviews could conceivably start to emerge. Although if change is going to happen, it’s going to be slow; as Heathers points out, “academia can be glacial.”

“Peer review” is worse than useless at this point, I think. And it’s often wielded as a cudgel against dissidents of the climate religion.