NASA GISS shows 2009 as tied for 2nd warmest year on record

The data are here:

http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts+dSST.txt

The J-D column is January to December. The numbers are the global combined land-ocean surface temperature anomaly in hundredths of a degree centigrade. The 0.57 degrees for 2009 is surpassed only by 2005.

The excellent writeup is posted here, written by James Hansen himself. It discusses, among other things, the reasons for differences between the NASA GISS and the Hadley temperature trends data.

http://www.columbia.edu/~jeh1/mailings/2010/20100115_Temperature2009.pdf


This was not unexpected. Last year, both NASA GISS and the Hadley center had predicted a high likelihood of new all-time high temperatures within the next few years, based largely on the switch from La Nina to El Nino conditions, along with a smaller contribution from the move up from the solar minimum. That La Nina to El Nino switch occurred this spring. Hadley had been estimating that 2009 would come in around 5th, NOAA had been estimating something in the same range. (Hansen gives the standard errors on the annual temperatures, and in practical terms, there are a whole bunch of years this decade whose temperatures are not statistically significantly different from one another.)

I was going to write a pre-emptive piece to answer the usual stuff that'll now get posted, but I've just lost the taste for it. Here are a few scattershot ones.

OK, if you want to post pictures of poorly-sited US ground temperature stations and present that as the reason for ignoring this, then: Put aside the fact that 3/4ths of the globe is water, and that the US is maybe 2% of the total globe surface area. The minimum standard of fair discussion starts with acknowledging that the inclusion of the poorer-quality stations within the overall temperature estimate appears to makes absolutely no difference whatsoever to the estimated temperature trend, as demonstrated by NOAA staff, here:

http://www.ncdc.noaa.gov/oa/about/response-v2.pdf

If you're going to object to the fact that (e.g.) NOAA applies a set of adjustments to the (underlying, dirty) data, then I think a standard of fair discussion would be at least to acknowledge what those are and how long they have been doing them. For example, the single largest positive adjustment to the data is for changes in the time of day at which observing stations end their observing data. That's based on objective, data-based studies going back some decades. The methodology reference is dated 1986 -- so no reasonable person should imply that they instituted that in anticipation of "cooking the books" for the current period. NOAA's adjustment methods are here, NASA uses a different set, their time series tend to agree reasonably well over the long term.

GHCN Global Gridded Data

If you're going to point to "the satellite data", meaning, the UHC Spencer/Christy lower troposphere series, I think a standard of fair discussion is to acknowledge how difficult it is to construct any estimate of temperature whatsoever from the satellite data, as described in part here:

RSS / MSU and AMSU Data / Description

I mean, all it takes is laying out the history of the UAH interpretation and you might conclude, as some have, that the structural uncertainties in the satellite temperature series are large. I mean, Spencer/Christy is now on version 5.2, that should say something about the complextity of the method. Those researchers got their estimate grossly wrong initially (and very publicly stated that there was no warming); fixed one set of errors and very publicly stated that there was warming, but with a very small trend; had the folks at RSS point out yet another error, and finally ended up with their current trend estimate.

In other words, constructing any consistent timeseries from the satellite data is difficult, and large and public errors have been made in the past.

None of the above should be construed as showing that some series provide information and others do not. It's just meant to kick the discussion up a notch. All these data series have issues, all of them provide some information, it's all a question of the strength of the inferences you can make from them.

That said, and acknowledging that the difference between 2nd and (e.g.) 5th warmest is not statistically significant, I thought it was worth posting what the final tally was for the year, from one of the two US organizations of record.

 

Well, this is to be expected. A few things I noticed skimming that report:

Three-quarters of the earth's surface is water. Specific issues with global ocean temperatures raised in this report: zero.

The report brought up the Russian "Institute for Economic Analysis" study and accusations of cherrypicking of the Russian data by CRU. Did the author then check with an independent data source to see whether or not that appears true? No, of course not. As I posted in the IEA thread, the IEA "study" disagrees with (understates) the Russian government's own estimate of warming. In fact, the Russian government estimate is slightly larger than the CRU estimate. So, in effect, the Russian government's own analysis of its own data appears to validate the mainstream view of warming.

Same deal for Canada. The report makes much of thin data used by GISS in Canada (which I am not going to track down the truth or falsity of). But, did the author then bother to check with an independent source of record, to see what Environment Canada says about warming in Canada? No, of course not. Environment Canada finds 1.4 degrees C warming over the past 60 years or so, here: Temperature and Precipitation in Historical Perspective)
So, again, the independent analysis by the country in question appears to back the idea that there has been significant warming.

The report cited the Watts study of the quality of US weather stations. Did the author then cite NOAA's analysis (in my original post) showing that the inclusion or exclusion of the stations made no difference in the trend? No, of course not.

The report says this:

" ... the main data bases of NOAA and CRU have no adjustment for urbanization."

That's simply, flatly wrong. Shoot, I posted the graph of the NOAA urbanization adjustment and even described the method (regression based, dating back to a mid-1980s analysis), in a post on an earlier thread here.

On net, I don't see this as a very credible analysis. I hope that doesn't count as "mocking derision".

 

"I think this is what he is trying to say:

"Hi. Can we discuss this, and assume that all of this temperature data is valid?

"You know, despite the fact that FOIA'ed documents show that we adjust all temperatures multiple times,"
---
The adjustments that NOAA makes are described on the NOAA website, have been for years, with links to the published, peer-reviewed studies that the adjustments are based on. Most of the pieces of the methodology date back at least 20 years.

NASA GISS publishes the code used to clean the data for their GISSTEMP product, here:

Data @ NASA GISS: GISS Surface Temperature Analysis: Sources

And, really, you can't logically have it both ways. Either you can say, hey, the incoming station data have problems, or you can say, hey, they made adjustments to the data. I say, if the incoming data have problems, they have to make adjustments. The adjustments have been on the books for more than two decades (in NOAA's case), just under two decades (for NASA).

The upshot is that they have to make adjustments to the incoming data. The mere fact that they make adjustments may scare people who have never dealt with data before, but that's tough. NOAA's adjustments, in particular, are well laid-out, and the rationale is well documented.

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" ... and practically no one in the world understands which data sets contribute to which other other ones, and who gets what data and how many times they've been manipulated."

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I can't imaging how you could or could not verify that. But here's a funny thing. Practically no one understands any complex, technical topic. Particularly relating to data analysis. Why? Because you have to devote a lot of time to understanding it. Again, people who don't deal with data for a living tend to be scared by that. But, for example, practically nobody understands the work I do, analyzing health care claims data. My clients don't understand what I do. But I make a living doing it. How can that be?

The answer is triangulation. You make sure that your answers are consistent with other available information, and, if not, you work to understand and reconcile the differences.

So, how can you tell that the work is done competently? Well, for example, if NASA GISS says that Australia has warmed over the last century, you could check to see that the Australian government's own analysis says the same thing. Which it does. Ditto Russia. Ditto Canada. And so on. You can see whether or not the four (?) global estimates (Two US, one Great Britain, one Japan) agree, and see whether or not any differences can be reconciled based on differences in methods. On a broader time scale, you can check the estimated warming against other methodologies (e.g. summaries of borehole studies) to see that they agree. And so on and so on and so on.

Where sources disagree significantly, you attempt to reconcile them in some sane fashion. Here's where it would be interesting to be able to talk to somebody who really understood the satellite data.

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"And we also want to discuss it without acknowledging that the same scientists who promote these data sets are shown in ClimateGate emails agreeing that the world has been cooling for over a decade."

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OK, let me lay out the basics here. Nobody at NASA GISS said that, because they mark 2005 as the warmest year on record. The citation above says seven years and clearly notes that this is not statistically significant. The way I read that, what they fellow there is saying is, we're looking at random (noise) variation in the data, and we don't want to feed the dummies who can't understand that.

But, fundamentally, look at the ill-logic of what is being said here. You appear to trust the measured temperatures when they go down. You seem to be saying that the actual surface temperature was falling, as measured by Hadley, and Hadley was "hiding" it by failing to make a lot out of that.

Well, if the (cold) estimated temperature in 2008 was true, why then is the (hot) 2009 year false? What objective information makes you change your mind about the quality of the data based on a single year of observation?

More to the point, if these sneaky climate guys are so darned good at "falsifying" and rigging the data, why the heck did Hadley (but not NASA GISS) let it appear to some people that the globe was not warming, for an entire decade? Why didn't they just rig it to beat the extreme outlier year 1998 some time in the past few years? Why provide all this cheap fodder to the denialists, if they are in the business of rigging the numbers?

In short, to follow this line of reasoning, I have to believe that not only is there a vast international conspiracy on this issue (involving not only the evil CRU team and NASA and NOAA but also the national weather agencies of numerous countries), but I also have to believe that it's a vast and incompetent international conspiracy, because Hadley was too dumb to cook the books enough to break what they show as the 1998 outlier year record.

In short, you can't point to the Hadley data and say, see, it's not warming, then, when it does show warming, say, the data's crap anyway, you can't trust those guys. Logically, you ought to pick one.


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From Wikipedia:

"In 2009, Hansen was awarded the 2009 Carl-Gustaf Rossby Research Medal,[66] the highest honor bestowed by the [ame="http://en.wikipedia.org/wiki/American_Meteorological_Society"]American Meteorological Society[/ame], for his "outstanding contributions to climate modeling, understanding climate change forcings and sensitivity, and for clear communication of climate science in the public arena."

Enough said.