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Without evaluating this particular statement about radiosondes, I don't place a whole lot of credibility in what he says. This is based on his reputation. It doesn't guarantee that Goddard is wrong, but it means his claims should be viewed with more skepticism than someone with a better record on climate change issues.

Let us keep in mind that Goddard's "Debunking" of AGW isn't even based on surface temperatures.

And what is interesting is that instead of him asking "Why", he just decided My dat is right, everyone elses is wrong."

Ain't necessarily so. http://journals.ametsoc.org/do...

Goddard has been thorougly debunked and quite often:

http://rankexploits.com/musing...

https://www.skepticalscience.c...

http://reallysciency.blogspot....

https://rhinohide.wordpress.co...

We can read an actual paper about his issue : https://www.gfdl.noaa.gov/bibl...

Enough of this stuff. It won't change any deniers minds even if they continue to spew long debunked Proofs of their position.

10-15 years is too short a time-scale to make a reliable judgment

I think if you study the analysis at Lucia's and also Steve McIntrye's, you'll understand why it must be so.

I don't think neutral is the same as irrelevant, but would accepting otherwise for the sake of argument, would the point that the supposedly independent reviewers weren't independent affect your opinion of the paper?

Really, the paper tries to get a lot more out of the opinions of reviewers on the internet than can possibly be justified.

I don't think you understand what he did. If you read Marcel Crok's comment, all becomes clear.

The guidelines for rating [the] abstracts show only the highest rating value blames the majority of global warming on humans. No other rating says how much humans contribute to global warming. The only time an abstract is rated as saying how much humans contribute to global warming is if it mentions: that human activity is a dominant influence or has caused most of recent climate change (>50%). If we use the system’s search feature for abstracts that meet this requirement, we get 65 results. That is 65, out of the 12,000+ examined abstracts. Not only is that value incredibly small, it is smaller than another value listed in the paper:

Reject AGW 0.7% (78)

Remembering AGW stands for anthropogenic global warming, or global warming caused by humans, take a minute to let that sink in. This study done by John Cook and others, praised by the President of the United States, found more scientific publications whose abstracts reject global warming than say humans are primarily to blame for it.

Perhaps you should read the analysis of Cook's idiotic paper before you accuse me of making things up!

Unfortunately, this paper wasn't particularly scientific. It's got the characteristics of a push poll, in that the most appropriate choice wasn't an available option for the survey. It was based on reviewer's opinions of the articles, with no controls on who was doing the reviewing. Only 68 papers out of 12,000 asserted greater than 50% of the cause to humans, while 78 explicitly rejected it.

This number appears to be as flawed as the "98% of climate scientists" number a few years ago, where they didn't like their initial results and excluded a number of papers to bring the consensus amount up.

Unfortunately, this paper wasn't particularly scientific. It's got the characteristics of a push poll, in that the most appropriate choice wasn't an available option for the survey. It was based on reviewer's opinions of the articles, with no controls on who was doing the reviewing. Only 68 papers out of 12,000 asserted greater than 50% of the cause to humans, while 78 explicitly rejected it.

This number appears to be as flawed as the "98% of climate scientists" number a few years ago, where they didn't like their initial results and excluded a number of papers to bring the consensus amount up.

...that reject AGW than there are that blame humans for most (>50%) of agw.

http://rankexploits.com/musings/2013/on-the-consensus/

"The only time an abstract is rated as saying how much humans contribute to global warming is if it mentions:

that human activity is a dominant influence or has caused most of recent climate change (>50%).

If we use the system’s search feature for abstracts that meet this requirement, we get 65 results. That is 65, out of the 12,000+ examined abstracts. Not only is that value incredibly small, it is smaller than another value listed in the paper:

Reject AGW 0.7% (78)

Remembering AGW stands for anthropogenic global warming, or global warming caused by humans, take a minute to let that sink in. This study done by John Cook and others, praised by the President of the United States, found more scientific publications whose abstracts reject global warming than say humans are primarily to blame for it."

Boy, warmists are really bad at math!

There is some information on this site that gives an overview of the adjustments that have been made to the USHCN data and provides links to further detailed references. I am no expert but my impression is that the adjustments have been made for sound and fairly standard reasons such as time of observation. Furthermore, and the whole point of that page, a different method of adjustment has been applied that yields very similar results. This would tend to suggest that both methods are robust.

It is a standard 'skeptic' tactic to complain vaguely about 'adjustments' to data as if adjustments are intrinsically wrong or suspicious whereas in fact it is rare in science for raw data not to need some pre-processing before robust conclusions may be drawn from it. However I will give you the benefit of the doubt. Unlike me, you might very well be an expert on this topic, so I'd be interested if you could explain specifically what you think is wrong with the adjustments.

Thanks for your points. As I said, I have an open mind on this and will investigate them.

Here's an interesting statistical discussion that appears to have trouble with the Tamino link you gave.
http://rankexploits.com/musings/2010/comparing-proxy-reconstructions/

The link you gave [from 2010] as: http://www.skepticalscience.com/co2-temperature-correlation.htm also appears to look at short-term CO2 correlation (starts in 1900) rather than the much larger timescale given by the Antarctic ice cores as found by the 2012 Copenhagen study. Please take a look at the more recent study when you have the chance.

With regard to the Southern Hemisphere (where I live). I would expect the man-made CO2 concentration and man-made temperature rise to be lower. There is simply a lot more ocean, a lot fewer people/vehicles, and a lot less industry than the Northern Hemisphere, yes? I would expect the Southern Hemisphere to drag the global warming value down since it is not the origin of the man-made atmospheric CO2/greenhouse gasses. Yes? I'm speculating here, because I haven't seen the Southern data against Northern data (just the Antarctic ice core records where the temperature rise precedes that CO2 rise).

Once again, thanks for taking the time to make your points.

I still feel that you completely missed the boat, Phil.

I agree that what MOST people are talking about (comments in the code, etc.) are really no big deal. It is the other emails that concern me... like the ones that show deliberate (and very probably illegal) failure to honor FOI requests and so on. Also, emails that indicate that the data used was improperly handled. Take this exchange, for example (I posted this same link on your other blog entry):

THAT exchange is completely IN context, showing both sides. Yet it indicates that either they used improper data in their calculations, or possibly that they simply are not aware of what data they did use (which amounts to pretty much the same thing). What it does show, pretty clearly and in context, is that they made a mess of this whole study. Add to that the missing data (whether it was done on purpose or not), and what you have is BAD SCIENCE, completely aside from any conspiracy theories.

I am not crying conspiracy, and I don't give the slightest damn about this politics of this whole thing. But you are ignoring the real, demonstrable goofs that these people made... some very big goofs that call their whole set of data into serious question. And when you look at all the OTHER studies done that rely on this very same data... what you have is a travesty and a tragedy. [Lonny Eachus, 2009-12-04]

These are very serious accusations, Lonny. And they're all based on this WUWT article by Willis Eschenbach:

"One of the claims in this hacked CRU email saga goes something like 'Well, the scientists acted like jerks, but that doesn't affect the results, it's still warming.' I got intrigued by one of the hacked CRU emails, from the Phil Jones and Kevin Trenberth to Professor Wibjorn Karlen. In it, Professor Karlen asked some very pointed questions about the CRU and IPCC results. He got incomplete, incorrect and very misleading answers. ... Professor Karlen was quite correct. The claims made by the CRU, and repeated in the IPCC document, were false. Karlen was looking at the evidence. ... Now, I have not taken a stand on whether the machinations of the CRU extended to actually altering the global temperature figures. It seems quite clear from Professor Karlen's observations, however, that they have gotten it very wrong in at least the Fennoscandian region. Since this region has very good records and a lot of them, this does not bode well for the rest of the globe ..."

Even if the methodologies used to establish the base data were sound, there is no doubt that it was later used improperly and irresponsibly. For months now, in these blog posts of Phil's, I have asked anybody - ANYBODY - to refute what is on this page: When Results Go Bad. I have had no takers. Not one. Anybody care to take a shot at it now? [Lonny Eachus, 2010-07-01]

Sure, why not? The next day, Zeke Hausfather wrote When results aren't bad which shows that Prof. Karlen, Eschenbach and Eachus based their accusations on a misunderstanding of the geographical region represented in the IPCC's time series. The first link in Zeke's article leads to Lonny's comment.

I see. The "actual experts in the field all have research that shows the same thing"? Interesting! I would be very interested to see some evidence for that claim! Wait... d

When even the skeptic bloggers turn against you, you know you're fighting a lost cause. Spencer obviously thinks Latour is crap. Lucia thinks "Slaying the Sky Dragon" is crap. Curry thinks it's crap. (I don't link to her blog because the publishers of the book got her blog shut down for daring to criticize them.)

But hey, keep eating up everything the Sky Dragon feeds you, you gullible tool.

Uh, seems the link in my previous post broke, so there's a link to the page containing it.

I would also be interested in knowing about other predictions, in particular predictions with specific numbers backed by plausible theoretical models

Here's one from the same researcher, from 7 years later, after spending half a decade of super-computer time simulating the warming.

To understand the graph, the red line (Hansen A) was calculated assuming and annual increase of atmospheric CO2 of 1.5% per year. The orange line (Hansen B) was calculated assuming that the annual increase of atmospheric CO2 would be constant, and the yellow line (Hansen C) was calculated assuming CO2 output would decrease so much after 1990 that by 2000 it would cease to increase. He was optimistic in the scenario.

You can also look at the first IPCC report from 1990 which predicted a rise of .3 degrees Celsius.

There is someone checking the models, Lucia at the Blackboard. http://rankexploits.com/musings/2011/rss-april-anomaly-up-2/

IPCC AR4 prediction: 0.2 C/decade Multi-model mean prediction: 0.211 C/decade Sat. observations: 0.146 C/decade Ground observations: 0.131 C/decade

So far the predictions are well in excess of observations, but a decade is seen as too small to be significant. We won't really know how wrong the modelling is until 2030 or so.

Straight from the Not-A-Lord Monckton School of Lies. Neither of the predictions made any per decade assertions, but until the end of the century with super-linear growth. Averaging those predictions as linear for one decade proves you either didn't understand, or are determined to deceive.

There is someone checking the models, Lucia at the Blackboard. http://rankexploits.com/musings/2011/rss-april-anomaly-up-2/

IPCC AR4 prediction: 0.2 C/decade
Multi-model mean prediction: 0.211 C/decade
Sat. observations: 0.146 C/decade
Ground observations: 0.131 C/decade

So far the predictions are well in excess of observations, but a decade is seen as too small to be significant. We won't really know how wrong the modelling is until 2030 or so.

Well, if the big picture means anything to you, the results that CRU came up with align with simulations and observations from NASA and other climate research centers around the world. Why don't you take the raw data and devise your own model for it, or use their methodology?
Yeah, it's a lot of work, but others are doing just that sort of thing now - check out the climate-science site "the Blackboard" - good discussion of the issues there.

http://rankexploits.com/musings/
_there are very few sincere AGW skeptics_

Uh, no. You're wrong to say that I'm wrong. Expectation is a statistical term which you'd do well to understand before criticizing my remark.

What is wrong is to say "weather is not climate" therefore the recent temperature means nothing. This is false, and its false because climate is related to weather: climate is the expectation of weather. Therefore a few months of data mean a little something--although not very much. That is, with only a few months data we cannot statistically falsify the IPCC claim that the trend-rate of warming is 2C/century. Nonetheless, with the past 10, 15, 20, etc years of data, we can falsify the IPCC claim, but just barely.

Such analysis is easy to do yourself. You can also find people who have posted their own number-crunching. See for instance this from Lucia Liljegren

And the above collection of data naturally omits the data CRU has been hiding and what they've promised to delete.

If the tree rings don't match the temps lately then there's no reason to believe that they matched way back before we were using thermometers. If some of the trees match the temp lately and only some of the trees diverge, then the trees that diverge shouldn't have been included in the graph. It appears that the best explanation for the inclusion of these divergent trees in the graph was to deceive.

That's tricking yourself into cherry picking. If you choose the data based upon the desired answer, then you're picking data which agrees with your conclusion. It's not quite as bad as intentionally creating false data, but it is not the right way to process data.

What should be done is to understand the mechanism which causes a relationship between tree rings and temperature. Then eliminate rings which don't have that relationship, but not by comparing them to the temperature. For example, if a tree is in a location where it is sensitive to water rather than temperature then eliminate it on that basis. If a tree has been fertilized by farmland runoff and its relationship with temperature has been lost, eliminate it due to that. Obviously that requires more information than tree ring size and temperature -- you can't do such things by comparing rings to temperature. After removing such things, then perform your temperature calculations.

Lucia Liljegren has shown that the IPCC's 2'C/century prediction (sorry, "projection") is statistically rejected as too high. This number was published in 2000, IIRC. It has not changed in the more recent IPCC report. It gets worse if you consider the global mean surface temperature calculations may be biased upwards.

6'C/century is right out according to the measurements. But it makes for a good (i.e., scary) headline.

Lucia Liljegren has shown that the IPCC's 2'C/century prediction (sorry, "projection") is statistically rejected as too high. This number was published in 2000, IIRC. It has not changed in the more recent IPCC report. It gets worse if you consider the global mean surface temperature calculations may be biased upwards.

6'C/century is right out according to the measurements. But it makes for a good (i.e., scary) headline.

Under what mathematical law does the fact that two graphs don't look the same mean that they are not related? This is really sad: Experts spend years analyzing the data, come to an extremely complicated conclusion based on mountains of evidence, and then someone who has not the slightest fucking clue about science or mathematics walks in and says "But those graphs look different!" and decides those experts are all wrong. And worse, other people who share this guy's lack of clue believe his argument because it's the only one simple enough for them to understand.

You mean the kind of experts who do extremely complicated things like this, or this, or maybe even this?

I wonder if there's a graph you can show us to demonstrate this, perhaps in the shape of, say, some kind of hockey stick?

Where are you getting this information? Lucia's analysis shows that the models are under estimating the absolute temperature by around 1'C on average. She has another posting showing that models that take volcanism into account are worse predictors than those that don't. You might want to take model predictions with a grain of salt.

No, that's the measurements of the Urban Heat Island effect and James Hansens personal secret closed source "correction algorithm". If you really want to know something about temperatures, you should look at the UAH satellite data.

http://surfacestations.org/ on GISS and UHI
http://rankexploits.com/musings/2008/uah-temperature-up-in-november/ on UAH global temperatures

I hate to burst your bubble, but even ignoring the high point of 1998, the trend over the last ten years is cooling if you don't cherry pick your source (see e.g., http://rankexploits.com/musings/2008/ipcc-projections-continue-to-falsify/ which uses GISS, HadCRU, MSU, and NOAA).

As I scientist I see it as my job to be skeptical - that is, to pay at least as much attention to falsification as to confirmation. I'm constantly amazed at the shrillness of the climate debate where, for most, scientific detachment seems to have been replaced with emotional involvement.