This is a hasty post as I'm currently living in fear for my life from some wasps that keep harassing me. I just wanted to throw it up on here because I think it's funny. Read this statement:
The figure above shows model runs for the A1B scenario (which is the only scenario with model runs readily available, though its 2016 CO2 concentrations are nearly identical to those of the A2 scenario). AR4 projections between 1970 and 2016 show warming quite close to observations, only 8% higher.
This was in regard for a 2007 set of climate models. It turns out models used for a 2007 report managed to get temperatures largely correct for the period of 1970-2016. Who would have guessed?
Today I'd like to take a break from my recent topics of discussion and look at an example of why people shold be skeptical of the messaging by global warming advocates. This post isn't about science. I'm not going to argue about any facts or theories. I'm not going to question or put forth facts or evidence.
None of those things matter today. Regardless of what one believes about global warming, everyone should be able to agree on a basic principle: Results should be presented in an accurate manner that does not create a misleading impression of what the results show. And based upon that principle, everyone should be able to agree this display is rubbish:
I'm not questioning the data used to make this display. The data doesn't matter today. What matters today is the data is being displayed in a misleading manner.
A question has been bugging me for a while. I'm hesitant to ask it because I feel I might be missing something incredibly obvious. However, after seeing the latest two posts at the blogger Anders's place, I feel I need to ask it. Please try not to be too harsh on me if it's as stupid as I worry it might be.
I often see things I feel merit comment but don't merit a blog post. This week, I happened to come across two separate posts by a blogger I would classify as such. On their own, neither seemed to merit writing a post. Taken together, perhaps they do.
I don't use the word "fraud" lightly. I've long criticized people who do. Not only do I think it is wrong in principle, I think it is wrong from a strategic perspective. If you cry, "Fraud!" over every little thing, nobody will listen when you point out real fraud. It's called a sense of proportion. One's rhetoric should ramp up with the severity of what is being criticized.
I bring this up because I want to follow up on my last post which discussed a case of fraud involving $100,000. Or rather, it was a case of fraud where a person used the false promise of $100,000 to cheat people out of money. You can read that post for the details. It's a long post so I won't re-hash the details here. I'll just give a short summary.
Last year, a man named Douglas Keenan announced he would give $100,000 to anyone who could win a contest he had created. There were tons of red flags which should have made people suspect this was bogus, but despite that, several big names in the global warming "skeptic" movement promoted the contest. After people spent some time publicly discussing how they might try to win the contest, Keenan switched out the data set used in the contest for one the proposed methodologies would be less effective on.
This contest involved a $10 entrance fee. That makes what he did fraud. I've been pointing that out for the last year. Just 24 hours ago, Keenan admitted it. Continue reading
Something which has long bothered me about the global warming debate is how "skeptics" are so quick to cry, "Fraud!" about... well, practically anything. I discussed this recently where an organization made a list of hundreds of pieces of work they took (partial or full) credit for as part of applying for a grant. The list included over 500 items, and it turns out approximately 25 of those items should not have been included. "Skeptics" yelled and screamed about how this was criminal fraud that should be prosecuted.
That's nonsense of course. Nobody was able to show any evidence the inclusion of those extra items was done with the intent to mislead as opposed to having been a simple mistake. Nobody was able to show the inclusion of a small number of extra items in one document submitted along with an application could have had any effect on whether or not the grant was awarded. In other words, nobody was able to show this was anything more than an embarassing mistake.
At the same time, these same "skeptics" are happy to either overlook, promote or even defend criminal fraud when it suits their purposes. I'd like to discuss that today because I find it offensive these "skeptics" have robbed me of $100,000.
Today I am going to discuss something I find confusing, not because it is confusing but because so many people don't seem to understand it. To see what I'm referring to, look at this tweet:
If you follow the climate debate, you've likely heard this claim before. Part of the global warming debate is figuring out how much influence humans are having on the planet's temperatures. This tweet shows a "mainstream" position, that humans are causing all of it and more. You can find this argument posted in many locations. For one example, you can look here to see an argument humans might be causing as much as 160% of global warming.
I'm not going to delve into that today. People are so polarized on climate issues it seems most people will agree with you if you're on their "side" and disagree with you if you're not. I want to avoid that trap. I want to avoid it because what's wrong with that argument has nothing to do with climate or how it might change. It's entirely about logic and forthrightness.
Put simply, it is nonsensical and misleading to say humans have caused 110% of global warming just as it would be nonsensical and misleading to say Black people caused 894% of Hillary Clinton winning the popular vote in the recent United States presidential election.
Readers familiar with my writings will be familiar with the idea of paleoclimatology. It's basically a study of climate over long periods of time. It gives rise to reconstructions of temperatures, precipitation and various other factors over hundreds, thousands or even tens of thousands of years.
I'm not impressed by the field as a whole. I think there is a lot of good work done in it, but I also think a lot of bad work has been allowed to tarnish the field and skew its conclusions. That's not important for today's post though. Today, I just want to show people the most precise estimates I've seen of temperatures nearly two hundred centuries past. I came across them because of a tweet:
Hey guys. I've been having trouble finding a topic to write about this week, so I've decided to re-visit an old issue. People familiar with my writing know I have spent a fair amount of time examining what effect human adjustments to temperature data have had on temperature records. This has mostly focused on the work of the (questionably named) BEST group.
I am not going to re-visit the not insignificant history of this topic today. If you want to read a bit about it, this post should give you a bit of an introduction to the matter. There is one historical point I do need to bring up though. A year and a half ago, in April of 2015, the head of the BEST project Richard Muller gave an interview in which he said:
“Furthermore, because of the interest, we re-analyzed all the data with ZERO adjustments, just to see what we would get. These results have been made available online. What we found was that the conclusions we had previously drawn were unchanged. The data are available here
You can read up about the trials and tribulations surrounding that article here if you would like, but the salient point is the data Muller referred to has never been published. It had not been published in April of 2015 when the interview was given, and it has not been published as of today, in August of 2016.
I don't know why Muller claimed data had been published when it had not. I don't know why that data has never been published. That's a matter for another day though. The reason I bring this up today is I want to point out anyone hoping to analyze the effect human adjustments to recorded data have on the BEST temperature results will face the obstacle of the BEST group falsely having claimed to publish the data which would make that possible without completely redoing the BEST analysis.
Fortunately, as you may have noticed while reading the posts I linked to above, the BEST group has shared that data with me. Unfortunately, that only happened after we exchanged a number of e-mails and I publicly criticized them (multiple times) for failing to publish data then turning around and claiming it was published. Still, the result is I have the data. Continue reading
So I just submitted a comment over at Judith Curry's blog, on her post about a recent Senate committee hearing titled Data or Dogma. The comment didn't appear, which I figure is due to running afoul of some spam/moderation filter. I figured I'd copy it here because I think the subject merits some attention:
So I watched some of the hearing, and I'll try to watch the rest of it later on. There's one thing I have to say right away though. About two hours in (I skipped around) Senator Ted Cruz displayed two charts taken from Steven Goddard, on the basis they show adjustments to the USHCN data set cause massive changes in its results. That's embarrassing. Those charts are complete and utter bunk, and it is shameful they were used in this hearing, much less that they went unchallenged.
The methodology Goddard used to create those charts is trivially wrong and known to introduce biases in the results. This has been discussed on this very site, with a humorous example of its flaws being that applying it to a global data set (GHCN) instead of just one for the United States reverses the results, finding that adjustments reduce global warming by a significant amount.
And while this point is pretty much indisputable, with any technically oriented skeptic acknowledging Goddard's charts are bunk, Goddard continues to defend them. Today I expressed my shock and displeasure with Cruz using Goddard's charts during the hearing on Twitter. A few tweets later, Goddard tweeted:
Zeke Hausfather has written several posts explaining why Goddard's charts are bunk. Steven Mosher has explained the problems with Goddard's methodology as well. Anthony Watts has acknowledged the methodology is wrong. I suspect readers here could think of many other people who have said things like, you have to spatially weight your data or otherwise account for where your data is located so you don't give too much weight to any one area. According to Goddard, they're all frauds.
Goddard says you can just average every station together, without concern for where it is located or what its baseline temperature might be (go ahead and simply average those 30C and 10C areas together). That's the only reason he can come up with the charts Cruz used. And according to him, if you think that's wrong, you're a fraud.
Another reason I decided to copy it here is it lets me delve into the subject more than I could in a comment on someone else's blog. So that's what I'm going to do.