Shortly after, NASA published their source code on Sept 7, we started noticing puzzling discrepancies in the new data set. On Sep 12, 2007, I inquired about the changes to Hansen and Ruedy, observing that there was no notice of the apparent changes at their website:
Dear Sirs, I notice that you’ve changed the historical data for some US stations since Sep 7, 2007. In particular, I noticed that temperatures for Detroit Lakes MN in the early part of the century were reduced by nearly 0.5 deg C. These changes are subsequent to your changes in August 2007 for the changing versions. To my knowledge, there is no explanation for this most recent change and I was wondering what the reason is.
Figure 1. Difference between Sep 10, 2007 version of Detroit Lakes MN and Aug 25, 2007 version.Thank you for your attention, Steve McIntyre
I posted on the topic on Sept 13 observing:
Since August 1, 2007, NASA has had 3 substantially different online versions of their 1221 USHCN stations (1221 in total.) The third and most recent version was slipped in without any announcement or notice in the last few days – subsequent to their code being placed online on Sept 7, 2007. (I can vouch for this as I completed a scrape of the dset=1 dataset in the early afternoon of Sept 7.)
The impact of the unreported changes was illustrated at Detroit Lakes MN using the same graphic as sent to Hansen and Ruedy. The post included the following prediction:
As you can see, Hansen has clawed back most of the gains of the 1930s relative to recent years – perhaps leading eventually to a re-discovery of 1998 as the warmest U.S. year of the 20th century.
This prediction came true quite quickly. On Sept 15, Jerry Brennan observed that the NASA U.S. temperature history had changed and that 1998 was now co-leader atop the U.S. leaderboard.
By this time, we’d figured out exactly what Hansen had done: they’d switched from using the SHAP version – which had been what they’d used for the past decade or so – to the FILNET version. The impact at Detroit Lakes was relatively large – which was why we’d noticed it, but in the network as a whole the impact of the change was to increase the trend slightly – enough obviously to make a difference between 1934 and 1998 – even though this supposedly was of no interest to anyone.
Average Impact of changing from SHAP to FILNET accounting.
Later on Sept 15, I observed:
This new leaderboard is really something else. I’m going to post on this: but if the SHAP version was what they used for the past decade, it’s a little – shall we say – “convenient” to decide in Sept 2007 that they are going to switch to the FILNET version (without announcing it on their website) and then, surprise, surprise, 1998 is now tied for the warmest year. This is going to send shivers up the spine of any readers familiar with accounting principles.
I’d been planning to write a post on this. There are undoubtedly more Climate Audit readers familiar with GAAP (Generally Accepted Accounting Principles) than at other climate websites, but it’s worth re-stating one of the fundamental GAAP principles:
Principle of the permanence of methods: This principle aims at allowing the coherence and comparison of the financial information published by the company.
Now you may say that this is “science” and accounting principles don’t apply. And my response would be that I’d expect GAAP principles to be a minimum standard for the type of climate statistics being carried out by NASA. Even if NASA climate statisticians are unaware of GAAP per se, they should be adhering to the principles. Sharp practice is sharp practice, however it is gussied up.
Hansen said that the difference between 1998 and 1934 was “statistically insignificant”. But business accountants are familiar with situations where a lot of attention is paid to numbers that may be “statistically insignificant”. I’ll give you an example. For a large corporation, the difference between a small profit and a small loss can be “statistically insignificant”, but there is a big difference in how they are perceived by the public. In some cases, unscrupulous corporations (and you can think of a few, including the most famous recent U.S. bankruptcy) will do whatever they can in terms of deferring expenses or recognizing revenue to change a reported loss into a reported profit. Accounting changes are a red flag to analysts for brokerage companies; there may be “good” reasons but the analyst needs to be right on top of the situation and they will be VERY unimpressed if a company tries to slip a change in without reporting it.
So while the difference between 1934 and 1998 may have been “statistically insignificant”. Hansen was obviously quite annoyed by the attention paid to 1934 being called the “warmest year” even in the U.S. and the change in rankings must have stuck in his craw. Was that motivation in the change from SHAP to FILNET accounting? I certainly hope not. Perhaps long before the Y2K error re-arranged things, NASA had already made long-standing plan to shift from SHAP accounting to FILNET accounting. But if this was not the case, then the timing of the change, especially with the all too “convenient” restoration of 1998 to the top of the leaderboard is certainly unfortunate.
This is precisely the type of situation that would have been avoided by NASA adhering to GAAP principles. Companies cannot change accounting procedures on a whim. Auditors will not permit companies to change methods merely to enhance reported earnings. And if a company changed accounting procedures without any disclosure, it would be viewed very seriously by regulatory agencies – whether or not the company said that it “mattered”. If the change from SHAP to FILNET accounting didn’t “matter”, then Hansen shouldn’t have done it. If it did matter, he still shouldn’t have done it right now just when he was archiving source code for the first time – and to do so without either formal disclosure or a re-statement of prior results simply boggles the imagination.
On Sept 17, Ruedy replied to my email asking that they disclose their changes, more or less refusing on the basis that the new data source could be detected in the “description of input files” in the source code.
Dear Sir,
As indicated in the description of our input files, we switched from the old year 2000 version of USHCN to the current version. The differences you noticed reflect corrections that were made by USHCN within the last six years.
Reto A. Ruedy
But this is not the same as a change statement. There’s no hint in the input file itself that they had changed the input file from what had been used previously and that the code archived on Sept 7 was NOT the code used to produce NASA results prior to Sept 7. They had not merely “simplified” the code; they had changed from SHAP to FILNET accounting. It’s also not good enough to simply slip the accounting change in with the source code. It should have been formally disclosed when the change was instituted, rather than leaving us to try to figure it out and (later disclosing it only when the change had already been discovered.)
In addition, his last sentence here – that the changes “reflect corrections that were made by USHCN within the last six years” is not correct. Both SHAP and FILNET accounts existed when Hansen et al 2001 was written. Hansen decided – for whatever reason- to use SHAP accounting. HE could have used FILNET accounting. And he decided to change in mid-September 2007. Did it “matter”? Well, it mattered enough to go to the trouble of making the change. It also – and perhaps this is sheer coincidence – mattered to the “statistically insignificant” leaderboard as 1998 is now your new co-leader/
Today NASA has attempted to cooper up this mess. At their website, they finally reported the change in accounting that we had already picked up and reported. They state:
September 2007: The year 2000 version of USHCN data was replaced by the current version (with data through 2005). In this newer version, NOAA removed or corrected a number of station records before year 2000. Since these changes included most of the records that failed our quality control checks, we no longer remove any USHCN records. The effect of station removal on analyzed global temperature is very small, as shown by graphs and maps available here.
This seems like a pretty odd description of what they appear to have done and perhaps I’ll re-visit this on another occasion. Hansen includes the following account of the Y2K error (conspicuously deleting his prior recognition of my role in identifying the error) and adding a reference to Usufruct and the Gorilla at the NASA website:
August 2007: A discontinuity in station records in the U.S. was discovered and corrected (GHCN data for 2000 and later years were inadvertently appended to USHCN data for prior years without including the adjustments at these stations that had been defined by the NOAA National Climate Data Center). This had a small impact on the U.S. average temperature, about 0.15’C, for 2000 and later years, and a negligible effect on global temperature, as is shown here.
This August 2007 change received international attention via discussions on various blogs and repetition by some other media, with no graphs provided to show the magnitude of the effect. Further discussions of the curious misinformation are provided by Dr. Hansen on his personal webpage (e.g., his post on “The Real Deal: Usufruct & the Gorilla”).
Obviously his claim that “no graphs had been provided to show the magnitude of the effect” is false. In one of my original posts on the matter, I showed graphics estimating the impact of the error on the U.S. temperature record and the distribution of errors on USHCN stations. I sent the following letter to Hansen and Ruedy today, notifying them that his statement was incorrect as follows:
Dear Sirs,
I see that you have decided to report the change in methodology as requested in my previous email. While you should have reported the change in methodology when it was made, it is better late than never.
In your new webpage, you state: ” This August 2007 change received international attention via discussions on various blogs and repetition by some other media, with no graphs provided to show the magnitude of the effect.” This is incorrect and I request that you correct this statement. On Aug 6, 2007, at Climate Audit, http://www.climateaudit.org/?p=1868 , the two graphs below were provided to estimate the magnitude of the effect. The first graph shown below estimated the impact on the U.S. temperature history at a little more than 0.15 deg C. Despite having no access to your source code, this proved to be an accurate estimate.
The next graph shown below shows the distribution of changes over the 1221 U.S. stations, which are very substantial in individual cases. Despite your professed concern for illustrating the impact of changes, you did not yourself provide any graph to show the magnitude of the changes on individual stations, nor did you even provide explicit notice on your webpage that any changes had been made.
Would you please correct the incorrect information on your webpage. This request is made pursuant to the Data Quality Act.
Yours truly,
Stephen McIntyre
A last point: as I’ve noted previously, as the classification of U.S. sites comes in, the actual GISS methodology for estimating U.S. temperatures looks a lot better than (say) the NOAA methodology. If NASA’s U.S. estimates stand up to scrutiny, that’s fine: that wouldn’t bother me a speck. I’m just trying to understand what weight can be put on which estimates. And regardless of what people may think, in a quick review of my posts, I haven’t located any posts in which I am particularly critical of NASA’s methods in the U.S., aside from the Y2K error. My position has been more: if NASA’s adjustments are right, then Parker 2006 and Jones et al 1990 etc are wrong. I had not personally criticized their lights methodology for classifying stations, preferring to see how station evaluation turned out. I have criticised poor and inaccurate disclosure, some of Hansen’s public comments and surveyed some of the data issues in the ROW (where’s Waldo?).
But I don’t think that I’ve been particularly critical of their U.S. methodology and, if the lights on-lights off criterion is a useful one for urban adjustments, that’s fine with me and I’ll be happy to acknowledge it. As noted elsewhere, that would leave many other open questions pertaining to the ROW, why there are discrepancies between NASA and NOAA, why NASA overall results are so similar to CRU results, if the individual stations are adjusted so differently etc etc.
But these matters are all quite different than (a) changing accounting systems; (b) doing so without notice; (c) archiving source code where the input file had been changed from what had been previously used; (d) making false statements on a NASA website.
UPDATE Sept 17 afternoon: Ruedy responded to my email as follows:
Thanks for bringing to our attention that the term “magnitude of effect” might be interpreted as “size” rather than “relevance”, our obvious intent. We clarified our formulation correspondingly.
They changed their website to read as follows (replacing magnitude with relevance):
This August 2007 change received international attention via discussions on various blogs and repetition by some other media, with no graphs provided to show the relevance of the effect.
Needless to say, this claim remains untrue. I sent the following letter (repeating the graphics shown above) requesting that the webapge be corrected, this time copying the Info Quality person at NASA:
Your revised webpage http://data.giss.nasa.gov/gistemp/ contains the following incorrect statement: “This August 2007 change received international attention via discussions on various blogs and repetition by some other media, with no graphs provided to show the relevance of the effect.”
This is incorrect and I request that you correct this statement. As I advised you previously, on Aug 6, 2007, at Climate Audit, http://www.climateaudit.org/?p=1868 , the two graphs below showed the relevance of the effect to U.S. temperature history and to U.S. stations.
The first graph shown below showed that the error was relevant to U.S. temperature history – a topic specifically considered in Hansen et al 2001.
The NASA website provides individual station histories, as well as U.S. and global estimates. The graph below showed the error was relevant to individual U.S. station histories.
The claim that “no graphs provided to show the relevance of the effect” remains incorrect. Once again, please correct the false statement on the NASA webpage http://data.giss.nasa.gov/gistemp/ . This request is made under the Data Quality Act.
Yours truly,
Steve McIntyre
Climate Audit 
210 Comments
If you smooth out Hansen’s 9/10 adjustments, it becomes an inverse hockey stick!
The shape of the histogram is very sharply bimodal. This sort of bimodality is a stong indicator of a sample which is a mixture from two distinct populations. Is there something that would make the stations with values less than or equal to about .15 different from stations whose values are greater than that value?
This is rank foolishness on the part of Hansen et.al.
Congress is paying attention. Suppose they get fed up and call for a full government audit?
NASA will not like that.
AS I have stated: lawyers may not understand the ins and outs of thermodynamics, accounting they get.
Its all to do with time-of-observation adjustments – going from afternoon to morning or from morning to afternoon. The changes are chunky. There are no changes of 5 minutes or half an hour. The point here is that becauseo f the bimodal distribution the average absolute value of the change was considerably higher than the average change.
Very bad PR moves by Hanson, especially since his shennagins will affect the public’s view of all of NASA. NASA does not need this problem, too.
By my calculation, Hansen is 66 years old. Given his erratic behavior and intemperate remarks in the past year, perhaps it’s time he consider retirement.
The down side to that is– to paraphrase Nixon– we won’t have Hansen to kick around anymore.
I wonder if Hansen et al could be convinced to change their tactics if they can be shown that they are counterproductive. Apple recently changed its marketing strategy for the iPhone. They had already harvested the true believers who were willing to wait hours outside of a store for the chance of buying a rather ordinary cell phone. To address the larger market of people without the same affiliation with the Apple brand, they recently reduced their prices by a large percentage. The Apple true believers were very unhappy but Apple already had their money.
Hansen et al have been using a scientific authority strategy of infallibility in which statements are made ex cathedra. They have achieved significant success with this but have met resistance from people who are unimpressed by unqualified statements even from august scientists. Many of these people have advanced degrees of their own and are not to be convinced that peer reviewed scientific papers are without error. It would seem better to address the concerns of this group directly by admitting that there are doubts about AGW and inviting these people to become involved in solving them.
Hansen’s Y2K blunder is a clear example of this. He is loath to admit that he made any error. I presume that this is because it is contrary to his ex cathedra strategy of scientific infallibility. It may also be because he was always the smartest kid in the class and expect to be the smartest person in the room but the effect is the same. Instead of denying the blunder he should embrace it and use it to show that even astounding blunders of that magnitude cannot shake the case for AGW. The AGW believers wont like this but Hansen already has them and they have nowhere else to go.
Hi Steve McIntyre,
Could you try to summarize what NASA’s current calculation procedure actually is for the USHCN? Here is an explanation of SHAP vs FILNET at the NOAA web site:
http://www.ncdc.noaa.gov/oa/climate/research/ushcn/ushcn.html
My understanding of NOAA’s procedure is:
(1) Raw data
(2) Remove outliers
(3) Correct for TOBS
(4) Correct for station history issues (moves) -> SHAP
(5) Correct for missing data using surrounding stations -> FILNET
(6) Correct for UHI
So, is GISS now using some different procedure for step (5)? This is confusing to me.
Thanks in advance,
Frank K.
#8. Previously they used data with Stage 4 adjustments; they changed to Stage 5 adjusted data. Both Stage 4 and Stage 5 adjustments have been done for years – so they could have used Stage 5 adjusted data in HAnsen et al 2001, but for reasons that no doubt seemed valid at the time, chose to use Stage4 adjusted data.
I’m not arguing that SHAP is better or worse than FILNET – just that Hansen changed methods without providing any notice and then only after the switch had been spotted here and publicized here.
I would speculate that they have lost confidence in their own method of filling in missing values and have “punted” the issue to NOAA and using NOAAs filled data. Not sure which comes first, the chicken or the egg. By that I mean, have they selected data that more closely validates their belief or is that simply happenstance now that they have decided to abandon their method of filling in the missing data?
It’s pretty obvious (to me) that they decided to incorporate these changes to their methodology since they were in the process of updating the code for public consumption anyway.
Back when all this started, they said that they will document the changes in their next paper on temperature analysis, and in their end-of-year summary. For those hanging on every thousandth of a degree change, this must be a big deal, and waiting precious months for the proper description of the changes and justification must be excruciating. For the other ~100% of the population, it won’t be such a problem.
Re #8
I pointed out previously on another thread here that the game has changed.
While this happy crew of auditors is stuck auditing the past, Hansen has moved on to a new game with new rules, one of which is to throw surprises out to keep the auditors running in circles. Cheap entertainment for him!
Rather than play Hansen’s new game, perhaps this happy crew needs to come up with it’s own game? Perhaps building a well audited transparent climate model? There’s been enough reverse engineering of the code to enumerate the categories of algorithms required, data types to be used, etc… A auditable transparent climate code built to the rigour of a professional software development.
12, that’s a big job. That might be doable with some funding, but without some way to keep the pretend physicists out, it would become a mess trying to referee the effort. Too many people who think that they just discovered something that eluded Singer and Lindzen.
When the FILNET step inserts estimates for missing data, it adds a flag to
indicate it has done so: the letter M. In such cases, the GISS code does not
use that data, and will use its own method for handling missing data.
#12: It seems to me that if a model is bad or insufficient then:
1. Its predictions will fail to materialize.
and
2. The predictions that do materialize will be able to be explained by other models.
13, I don’t think Leon is talking about the same type of climate model that you are.
#14 So what method DOES Giss use then, if not FILNET? Isn’t that what releasing the code was all about? Now that they’ve changed the data on which much of the analysis at CA was done, it seems to me it makes it much more difficult if not practically impossible to verify WHAT method they actually used to fill in missing data. If you have any knowledge, please share it.
#14
Thanks JerryB. That’s what I suspected – basically, as crosspatch noted, GISS have dispensed with their own FILNET algorithm (why?) in favor of NOAA’s. So, why didn’t they just say as much at the GISS website?! Why all the obfuscation? It makes no sense whatsoever…
I really think the GISS climate group has become dysfunctional to the point that some reorganization is in order…
#14 (JerryB): Interesting, but isn’t the difference between SHAP and FILNET in those infilled values? If GISS is not using those infilled values, where is the difference coming from? Is it possible that these difference are actually due to differences in USHCN corrections (old and new versions)?
Re #17,
Phil,
The answer, presumably, is in the code that they released.
Ruedy responded to my email as follows:
They changed their website to read as follows (replacing magnitude with relevance):
Needless to say, this claim remains untrue. I sent the following letter (repeating the graphics shown above) requesting that the webapge be corrected, this time copying the Info Quality person at NASA:
GAAP always seems to be a moving target and then there is the Financial Accounting rules vs. Tax Accounting rules and it seems more and more common to have to go back to restate prior years statements. The accountants are paid by those they are accounting and there would seem to be motivation to keep the clients happy. Obviously Climate Auditing has a slightly different set of incentives and no GACAPs.
Are there now stations to be added to the 1221 that AW is having surveyed?
#19, 20. There’s more to the FILNET changes relative to SHAP than simply filling data (Although it does also fill data.) For example, there’s obviously more going on with the Detroit Lakes changes than filling a few missing years.
The explanation does NOT lie in the released code. These adjustments are at the NOAA and we haven’t even begun to explore that set of adjustments yet.
Re #18,
Frank K,
No, they continue to dispense with FILNET’s estimates of missing data, and use
their own method.
Re #19,
Jean S,
According to one USHCN description:
“The FILNET program also completes the data adjustment process for
stations that moved too often for the SHAP program to estimate the
adjustments needed to debias the data.”
However, my interpretation is that most of the differences are as you surmise,
and as I discussed in my post last night in http://www.climateaudit.org/?p=2049
comment 79.
#24
OK – Thanks JerryB. Sorry for the confusion. So the differences seen recently are from “other corrections” – and presumably these “corrections” are reflected in the newly-released GISS codes? It is all becoming clear now…not ;^)
Frank K.
Frank K,
To save typing let me refer you to the comment in the other thread to which I
referred Jean S.
#25. Nope. As I said above, the most recent differences come from changing sources – from SHAP to FILNET. There’s nothing on this in the NASA codes.
Jerry, I agree with this diagnosis of yours:
Many USHCN stations are identical between SHAP and FILNET. Detroit Lakes (as Jerry observed first) has, by chance a large adjustment. But it illustrates that the clause identified by Jerry is not merely passive. What the adjustment actually does is another story.
Let me ask an ignorant question: What does the Data Quality Act actually specify as an improper change to fundamental data and what are the avenues for getting the data producers to revoke the improper change?
This may be unimportant, but I noticed a change in their description of their two-stage modification.
9-17 version.
9-12 version.
9-12 says they try to combine stations. 9-17 says they do combine them. Was there a rule change about this or just reworded?
9-12 has two categories non-rural and rural. With non-rural dropped if no close rural. 9-17 has three categories. Urban, peri-urban and rural. With urban being dropped with no close rural, but no mention of peri-urban being dropped.
Some one needs to let folks know that the class 1 & class 2 classifications
will be changing in the the next two days.
Just kidding.
Now, Imagine what people would say if Anthony suddenly changed the input to
John V.s analysis.
Thanks Jerry (#24), I had missed that. Since this is still slightly confusing, please confirm if I understood everything correctly. You say that there are some (other than infilling values which are not anyhow used by GISS) other differences between SHAP and FILNET versions, but your estimate is that the differencies we are seeing in GISS versions are mainly due to the different SHAP (and possible TOB) corrections (1999 vs. 2007) and only partly due to the switch from using SHAP to FILNET version?
#26, #27
Thanks again Jerry and Steve. I read the link in Jerry’s thread (see #24) and it has now become clearer what was done.
I suppose that as long as you have access to the raw data, you can judge for youself if the adjustments for a given station appear to be appropriate.
Is this paper’s conclusion (use the raw USHCN data set) valid?
“An Introduced Warming Bias in the USHCN Temperature Database Reference
Balling Jr., R.C. and Idso, C.D. 2002. Analysis of adjustments to the United States Historical Climatology Network (USHCN) temperature database. Geophysical Research Letters 10.1029/2002GL014825.
“What was done
The authors examined and compared trends among six different temperature databases for the coterminous United States over the period 1930-2000 and/or 1979-2000.
“What was learned
For the period 1930-2000, the RAW or unadjusted USHCN time series revealed a linear cooling of 0.05°C per decade that is statistically significant at the 0.05 level of confidence. The FILNET USHCN time series, on the other hand – which contains adjustments to the RAW dataset designed to deal with biases believed to be introduced by variations in time of observation, the changeover to the new Maximum/Minimum Temperature System (MMTS), station history (including other types of instrument adjustments) and an interpolation scheme for estimating missing data from nearby highly-correlated station records – exhibited an insignificant warming of 0.01°C per decade.
“Most interestingly, the difference between the two trends (FILNET-RAW) shows “a nearly monotonic, and highly statistically significant, increase of over 0.05°C per decade.” With respect to the 1979-2000 period, the authors say that “even at this relatively short time scale, the difference between the RAW and FILNET trends is highly significant (0.0001 level of confidence).” Over both time periods, they also find that “the trends in the unadjusted temperature records [RAW] are not different from the trends of the independent satellite-based lower-tropospheric temperature record or from the trend of the balloon-based near-surface measurements.”
“What it means
In the words of the authors, the adjustments that are being made to the raw USHCN temperature data “are producing a statistically significant, but spurious, warming trend in the USHCN temperature database.” In fact, they note that “the adjustments to the RAW record result in a significant warming signal in the record that approximates the widely-publicized 0.50°C increase in global temperatures over the past century.” It would thus appear that in this particular case of “data-doctoring,” the cure is worse than the disease. In fact, it would appear that the cure IS the disease.
“Our prescription for wellness? Withhold the host of medications being given and the patient’s fever will subside.
“Reviewed 29 May 2002”
JohnA,
The Data Quality Act mandated establishment of procedures be done by the agency providing the data. NASA guidelines provide for the following:
Steve appears to be following those rules and the NASA response is in accord with the guidelines.
In the event that NASA declines to “fix” something, there is an appeal process outlined within the standards.
re # 12
Sorry, I was referring to a auditable, transparent “Hansen”-like code, not a GCM code. Since a lot of people have put a lot of effort into understanding what it does, and more importantly, what it should do, then documenting the functionality of a audiable, transparent algorithm flow should do, building it cleanly to CMMI level 3 (or an applicable software development quality) might be the eventual goal of this happy crew.
Now back to lurking.
Re #31,
Jean S,
Yes. By the way, TOB adjustments (for any given station/month ) have been
virtually constant through successive USHCN editions, unlike SHAP adjustments.
NASA: This August 2007 change received international attention via discussions on various blogs and repetition by some other media, with no graphs provided to show the relevance of the effect.
My guess as to their next change: ….with no graphs provided to show the relevance of the effect on global temperatures.
What a waste of time this was.
Boris, I guess auditing isn’t your thing. Maybe you could loan me some money for an oil well project, on the promise that I’ll pay you double within a year? Of course, I can’t give you any more details, because you might beat me to the punch.
CMM Level 3? I thought NASA was CMM Level 5
I agree that Hansen has wasted our time. On day 1, at my initial request, he should have provided source code, so that we did not have to try to solve a variety of crossword puzzles. When he made each change, he should have reported the change together with its impact, rather than only reporting the changes after the changes had been identified here. Hansen should not have changed his accounting methodology especially since the only purpose of the changes seems to be to accomplish a statistically insignificant rearrangement of 1934 and 1998.
It’s not just us here. Anthony Watts reports the frustration of one of his volunteers trying to figure out what was happening with Walhalla, as the data kept changing. It never occurred to him that Hansen was changing the books.
Sorting out this nonsense has prevented even getting to the starting line of a statistical assessment of the ROW data. Yes, Hansen’s wasted a lot of people’s time. That’s who you should be blaming, Boris.
Yas Comrade Boris.
You and your Masters are very clever.
Yes, because Hansen has continually hawked 1998 as the warmest year in the US, right? Oh, no. As you well know, he talked about 1998 vs. 1934 as a statistical tie. In fact, the only people who care about 1934 vs 1998 in the U.S. were right wing blogs who seemed, en masse, to confuse global and US temps. Can you find me an example of anyone, anywhere touting the fact that 1998 was the warmest year in the United States? Hansen did not do so, so your theory that he must be trying to get 1998 back in first place makes no sense. He’s been consistent in pointing out the statistical tie between the two years.
#43. Boris, I agree 100% that Hansen’s wasted a lot of people’s time.
Hansen releases his code and then, promptly, starts using a completely different dataset and algorithm.
What does that say?
1. He purposely wasted everyone’s time in trying to analyze the code.
2. His code always was so full of errors and bias that he now must use another code set-up and algorithm.
Solution?
1. Declare Victory. Declare the GISS code dead and unworthy of further analysis since it was full of so many errors anyway.
2. Move onto the NOAA dataset and adjustments.
RE43, Boris says: “Can you find me an example of anyone, anywhere touting the fact that 1998 was the warmest year in the United States?”
Wow, such an easy mark. Sure thing Boris, here are NOAA’s press releases:
1998 WARMEST YEAR ON RECORD, NOAA ANNOUNCES
http://www.publicaffairs.noaa.gov/releases99/jan99/noaa99-1.html
1999: U.S. EXPERIENCES SECOND WARMEST YEAR ON RECORD; GLOBAL TEMPERATURES CONTINUE WARMING TREND
http://www.publicaffairs.noaa.gov/releases99/dec99/noaa99083.html
and before that:
1997 WARMEST YEAR OF CENTURY, NOAA REPORTS
http://www.publicaffairs.noaa.gov/pr98/jan98/noaa98-1.html
I believe it is human nature to want to trust people and especially those who we think should be above reproach. Even when something looks like a duck and walks like a duck we often continue to see something other than the duck. If this issue were not so important we would have no issue with recognising the duck as a duck, pure and simple.
The behaviour of not just Hansen, but Jones and Mann and others when confronted with what is a perfectly reasonable request for information should alert us to the fact that there is a real problem here.
Is it a conspiracy? No. These people never understood that their methods would ever come under such scrutiny and they have slowly but surely realised that their work is not up to scrutiny and so they defend their reputations.
The institutions that have taken their work and used it to covince governments that this is a serious problem are also defending their reputations, having accepted the work of these scientsists as of good quality. Governments are also defending their reputations in having taken the word of institutions like the IPCC.
It is a house of cards.
re 40
Just because one can do CMMI level 5, doesn’t mean level 5 quality is required for this use. Anyhoo, NASA has different ways of rating software for reliability, manned spaceflight rated software is the most rigorous for testing, etc… than prototype code (ala Hansen 🙂
So what is the appropriate quality of code (in the appropriate rating scale) for “spaceship earth”?
RE 48.
Bajingo! Leon Wins. What Hansen is propsing folks is a “flight control” system for
climate earth. A C02 limiter. That control system needs the same kind of testing that
the typical fly by wire quad redundant FCS has.
Leon Palmer September 17th, 2007 at 4:06 pm,
How many lives could you save with $1 Gigabucks?
That is how well rated the software ought to be, i.e. at least to FDA/FAA standards. The standards are clumsy and expensive. They do assure a certain level of quality.
#41 “Sorting out this nonsense has prevented even getting to the starting line of a statistical assessment of the ROW data.”
Maybe that was the point.
Not wanting to put you on the spot, Steve M., but wearing your auditor hat, what series of accounting stratagems would alert you to a conscious attempt at fraud? Can you provide a short list of what an auditor would look for?
Paul, #47, I think you’re being too kind. Hansen and Mann are trained physicists. They each know just exactly what their mathematical methods do. It’s not a formal conspiracy, no. But I’ve pretty much abandoned the thought that they’re innocently negligent. Instead, I think they decided early on that they know what the answer is, and then jimmied their methods to produce that answer, confident that they’d be rescued by confirmatory facts down the line. But nature is cruelly indifferent to occult knowledge claims, and the passionate interest of other people means potentially embarrassing scrutiny always happens. Honest mistakes don’t survive the scrutiny, but they survive the embarrassment. Dishonest mistakes don’t survive either eventuality. Hansen and Mann are being hoisted by their own petard, but the fuses were lit by Steve McIntyre.
BTW for true rigor data must be traced all the way back to NIST.
Love to see those error bars. Heh.
I’m a little thick here so maybe some one could help me.
If rural stations determine the slope of the curve what is the purpose of including all the other stations if you want to know the slope of the curve?
51,
I think that’s correct. According to theory, temperatures are supposed to be taking off robustly. That that didn’t happen has required the construction of delayed-response theories.
I’m sure that in 1990, they were cocksure that things would be taking off exponentially right now. The funny thing about the usufruct memo is that the less the earth obeys the predictions, the more upset they seem to get.
#12: While this happy crew of auditors is stuck auditing the past, Hansen has moved on to a new game with new rules, one of which is to throw surprises out to keep the auditors running in circles.
That strongly reminded me of another eerily similar quote:
Re. #46
First paper declares a tie between 1934 and 1998, so that one is a wash, though technically it counts because it was as warm as the warmest year on record.
Third paper doesn’t have any mention of US temps….
But, second paper gets the prize!!! Quote:
RE57 Sonic I purposely posted both the 1998 and 1999 PR’s to illustrate that something “morphed” within NOAA’s PR engine. They did not actually make a PR with 1998 as the US leaderbaord top title as such, but in 1999 it somehow became that way in the release talking about 1999.
Yep, and it has been the alarmist talking point du jour ever since.
#57 Just for fun:
Hey, it’s getting colder 🙂
Sorry couldn’t resist.
I still haven’t had explained to me how the seasonal variations in CO2 concentration create the seasons.
AW, I figured you had a reason for posting a link with no mention of the supposed burning hell that was 1998, I just didn’t know what it was.
PS. Sorry I haven’t got the Fresno Airport pics yet. I’m lame.
Ode to Hansen, Jones and mann:
So much data,
So little information
Regarding #51- Use a search engine to look up “Benford’s rule fraud”. In the real world,
numbers follow a roughly logarithmic distribution. When the accounting books deviate significantly
from this distribution, there’s an indication of possible fraud.
I don’t know how Benford’s rule could be applied in this case, since we’re dealing with temperature
differences of a few tenths of a degree.
I remember that – Benford’s Law and Zipf’s Law. Supposed you can detect fraud through the distribution of the digits.
46:
Did you read your first link?
“The United States average temperature in 1998 was 54.62°F (12.57°C), which placed the year in a virtual tie with1934 as the warmest year in records dating to 1895.”
Your second link is a much better example. So 1 for NOAA, 1,763,319 (est.) right wing blogs and radio 🙂
Oh, and 0 for Hansen.
Hansen’s recalculation of temps during the brief interlude since admitting the Y2K issue where he has, once again, changed the leaderboard leads me speechless (quite a feat for anyone who knows me). How can any professional, regardless of his/her field of specialty, perform in this manner and expect to continue to be perceived as being at the top of his/her discipline. In addition to GAAP, what about the requirements placed upon the private sector to observe the strictures of Sarbanes-Oxley. As one who works in an industry intensely under the SOX hammer, I am left incredulous that Hansen has the termerity to try and pull this off.
This should immediately bring sanctions against NASA. A full-blown audit of posted results and analysis of methodology is in order. If this doesn’t occur, then anything subsequent that comes out of this agency or Hansen should be completely disregarded.
#70 Sorry, “leads me speechless” should be “leaves me speechless.”
Re #57:
Hansen didn’t have to hype 1998, NOAA was doing it for him. I’m curious where Boris gets hius information that anyone critical of Mann or Hansen is a member of the right wing? Apparently his view on science is colored by politics. And on the subjet of Hansen discounting the US’s lack of a strong positive temperature trend because the US represents a relatively small fraction of this same non-representative of the ROW area, Thwe western US? Howe come he’s so eager to accept the Mann (hockey stick) analysis when the Briffa proxies represent even a smaller fraction of the ROW? That data seems to have been harvested not from
72
Three guesses.
Re #43:
Hansen didn’t have to hype 1998, NOAA was doing it for him. I’m curious where Boris gets his information that anyone critical of Mann or Hansen is a member of the right wing? Apparently his view on science is colored by his politics. And on the subjet of Hansen discounting the US’s lack of a strong positive temperature trend because the US represents a relatively small fraction of the ROW, how come he’s so eager to accept the Mann (hockey stick) analysis when the Briffa proxies represent even a smaller fraction of that same non-representative area…the Western US? Mann’s data seems to have been harvested not from Pinus longaeva but from Prunus cerasus. AGW should be based on science, not faith.
Boris, re #69:
Here is your challenge:
You didn’t specify it had to be Hansen.
#72. Well, one reason why Hansen wasn’t touting 1998 when it happened was because his results then had 1934 as about 0.6 deg C warmer than 1998. See HAnsen et al 1999. Between 1999 and 2001, Hansen made some adjustments and 1998 warmed about 0.6 deg C relative to 1934, creating a virtual tie in 2001. Hansen was for 1934 before he was against it.
It just occurred to me (and maybe I am slow) that Hansen’s bias method also creates a moving target, although a bit more subtle than what we see here. This is because the quarterly and annual estimates he calculates for the latest scribal record depend on averages across the record, which is of course changing as new data is added to the record.
Clever…
Re: #77
[QUOTE]
NASA Home > Life on Earth > Looking at Earth…
Earth Gets a Warm Feeling All Over…02.08.05
[….]
Globally, 1998 has proven to be the warmest year on record, with 2002 and 2003 coming in second and third, respectively. “There has been a strong warming trend over the past 30 years, a trend that has been shown to be due primarily to increasing greenhouse gases in the atmosphere,” Hansen said.
http://www.nasa.gov/vision/earth/lookingatearth/earth_warm.html
[UNQUOTE]
http://www.nasa.gov/vision/earth/environment/2005_warmest.html
And why did the data change John G.? Is it a Hansen conspiracy? Or did it change because it is FUBAR? In the ’90’s AMS was finding 5 to 16 degree errors in the automated systems. In 04 they were going to correct for 1 plus degrees errors. This is an audit right? Where is the raw data to follow the corrections. And the corrections to the corrections? There has been more error in the digital age than in the old days. Corrections are being made from the wrong end.
Im curious where Boris gets his information
Natasha mostly. Bullwinkle in a pinch.
Re: #78
Fooled me. I thought it was Fractured Fairy Tales. The pea under the mattress was always a cliffhanger.
You don’t suppose Dr. Peabody is still around with his faithful Boy?
In 2000, Hansen said:
It only took about one year for Hansen’s prediction to come true, even though 2001 wasn’t very warm. Hansen et al 2001 did a major adjustment to US records and changed 1998 from being about 0.6 deg C cooler than 1934 to a statistical dead heat. 1998 continued to make small gains and the 1934 record was finally broken by 2005 – by a rejuvenated 1998.
Left – from Hansen et al 1999; right – from Hansen et al 2001.
And oh yes, help me here, who is it that is talking about the “record annual” temperatures, now said to be of no interest?
Re: #80
What or who is loading the dice? Is the anthropogenic forcing of the climate records a loading of the statistical records and dice, AGW, a combination, or something else? It is rather interesting to note Hansen himself suggested the climate records he is working upon can be described as loaded dice, and Hansen has been observed to be adjusting those same records in a direction which makes his predictions come true in those records.
I love it when people quote Einstein! There is always a rebuttal.
“The secret to creativity is knowing how to hide your sources.” Albert E.
Re64 Boris did you read 57?
“So 1 for NOAA, 1,763,319 (est.) right wing blogs and radio” So no left wing blogs ever mentioned that? Wow your power of observation is truly incredulous.
BTW, I suppose you really don’t understand how press releases work, do you? All that independent thought going on in the media and all they wouldn’t just repeat that verbatim would they?
A question about the Data Quality Act. Shouldn’t an untouched, unbiased, un-adjusted historical record be available (so if the “new” ajusments are found to be inaccurate, we can return to them)?
How can any future scientist, student, or researcher be sure that the history is good? How could someone who writes an article, or bases their thesis on the data be sure that their conclusions are built on solid data?
#59: I still havent had explained to me how the seasonal variations in CO2 concentration create the seasons.
Well, first of all you have to forget all that stuff about the spinning Earth being tilted at an angle of twenty-something degrees to the ecliptic, and cooling during its Northern winters, warming during its summers. Forget about the Sun. Or better still, think of the Earth as being flat.
Think instead about CO2 in the atmosphere. During summer, when plant photosynthesis is maximum, plants absorb CO2 from the atmosphere, and reduce its levels, and thus reduce global warming, resulting in a subsequent cold winter. During winter, when plant photosynthesis is at a minimum, CO2 levels tend to rise, resulting in global warming – and the subsequent warm summer.
See. Quite easy to explain.
You’ll probably want to know about anthropogenic seasonal variation too. That is, how humans manage to create the seasons. And this happens because, during winter, humans tend to light fires to keep warm, and these fires generate CO2, which causes global warming, and results in warm summers. During these warm summers, humans stop burning fires, and the excess CO2 is absorbed by plants, reducing atmospheric CO2 concentrations, and bringing global cooling, and the subsequent winter.
The result, as I’m sure you’ll see, is that the seasonal cycle of spring-summer-autumn-winter is entirely created by human activity, and if humans would simply stop burning fires in winter, this seasonal variation would vanish, and terrestrial surface temperatures would remain more or less constant.
Convinced? I’m sure you are. If you want to save the world from the endless cycle of the destruction of the creation, all you have to do is to not turn on your heating system when temperatures fall 10 or 20 degrees C below zero. It would also help if you stayed outside, and didn’t wear any clothes, or ate anything. You know by now that it makes no sense to do stupid things like that, right?
Re 12. Leon your point is valid to a certain extent.
However the issue then becomes one of credability.
Climate audit is essential because it is one of the few places where papers are examined and looked at in detail.
As a lot of the detail comes down to statistics, then there are few better places.
As Steve says completely and correctly – it doesnt matter where things fall – only that they are right.
The financial markets are brutual on failures of credability. Try getting a loan when previous prospectus have been proved to be false, either through error or recklessness.
At this point we are starting to see financial markets factor in these issues based on these studies. They will bite them if the underlying work is incorrect.
It is one thing where forecasts are made correctly and the outcome ends up different, another thing entirely where forecasts are made erroneously or to achieve a certain outcome.
Re: #33
I haven’t noticed any comments responding to comment #33, which I think is a very valid question. The following figure is from the Balling / Craig paper referred to in 33:
This is what the authors say about the figure:
It seems that it is time to audit the adjustments made to the USHCN data.
#85 Love it!
#85
Sarcasm well played my friend!
Re: #88:
The authors refer to Christy [2002] and temperatures in northern Alabama. The following figure compares USHCN temperature graphs (left – from the CO2 Science site – which according to previous correspondence with them, they say is the unadjusted data) and GISS graphs (right – from the NASA site – dset=1, as of Sep 17) for two stations in northern Alabama. There is definitely a difference showing up between the data sets in this Waldo-less area.
If the theory and the observational data don’t match, then clearly something is wrong – with the data. The data has to be fiddled until it gives the ‘right’ result. That is how (climate) science works.
No. 47 paul says on September 17th, 2007 at 3:39 pm:
Pyramid of Cards would be more on the money.
From stray comments it is fairly obvious that SteveMc and when he was still around JohnA are well left of center in their politics.
But I’m sure Boris counts this as another conservative site.
Boris has an interesting double standard.
On the skeptics side, every blogger or radio host is counted.
On the alarmist side, It’s Hansen, and only Hansen. (When forced he reluctantly adds NOAA)
Hey Boris, if we are going to count every two bit blog on one side, why not count every two bit blog on the other?
You guys (most of you) need to stop hurling around irrelevant ad hominem comments and leave space here for analysis of the data.
Re: 79 (re Boris)
There’s also the possibility that Boris is Beaker (Dr. Bunsen Honeydew’s able assistant on the Muppets).
href=”http://gallery.surfacestations.org/main.php?g2_itemId=27418&g2_imageViewsIndex=3>Monthly Trends at one Station
Another “nearby” station
I seem to be having trouble linking images and multiple links that worked before, but the above should be sufficient.
OK “Mr. where’s the data?” Please explain why some type of more detailed analysis shouldn’t be performed on the data of nearby urban and rural stations to see if it makes ANY sense to use one to adjust the other. Homogeneity indeed.
Monthly Trends at one Station
Another “nearby” station
I seem to be having trouble linking images and multiple links that worked before, but the above should be sufficient.
OK “Mr. where’s the data?” Please explain why some type of more detailed analysis shouldn’t be performed on the data of nearby urban and rural stations to see if it makes ANY sense to use one to adjust the other. Homogeneity indeed.
Maybe preview doesn’t work so swell under Ubuntu/firefox 2.0.0.6?
Monthly Trends at one Station
Another “nearby” station
I seem to be having trouble linking images and multiple links that worked before, but the above should be sufficient.
OK “Mr. where’s the data?” Please explain why some type of more detailed analysis shouldn’t be performed on the data of nearby urban and rural stations to see if it makes ANY sense to use one to adjust the other. Homogeneity indeed.
One last shot at hand editing.
“If the theory and the observational data dont match, then clearly something is wrong – with the data. The data has to be fiddled until it gives the right result. That is how (climate) science works.”
The way I understood things is that Scientists and Engineers (And Financial Analysts) were supposed to explain why the data changed (varied, trended, etc), not why to change the data.
link
link
James Hansen, The GW Debate, 1999
GISS Surface Temperature Analysis
This would be for the adherents of Eliwabbet (and a test of html on this website)
Test Failed: New test.
“Are there spurious temperature trends in the United States
Climate Division database?”
Seems to depend on whom you ask.
Click to access Keim_GRL2003.pdf
Just an observer, not much a participant, but what a great site. Off topic, dirac angestun gesept, what a great book “Wasp”, by Eric Frank Russell was.
RE:#28
Ha!
My first visit here left me wondering how NASA/NOAA et al have gotten around this law for so long. It appears this law would require full disclosure and Congressional inquiry into the matter since the information disseminated unquestionably is “influential”.
Read the entire Act people. Here is a snippet.
Steve,
The paper mentioned in Comment #33 is hidden behind subscription at GRL. Do you suppose they would permit you to publish it? I’m a data-oriented engineer but not a climatologist. Is this paper as important as it seems to me? Is global warming hanging by such slender threads as paint on the instrument shelters, data adjustment and nearby air conditioners? Is this the basis on which some would have us sitting shivering in the dark?
Regards,
Bill Drissel
There’s a link to the paper at Watts UP:
http://www.norcalblogs.com/watts/
or direct:
Click to access USHCN_Balling_2002GL014825.pdf
Also it’s from CO2Science.org:
Click to access USHCN_Balling_2002GL014825.pdf
Monthly Trends at one Station
Another “nearby” station
I seem to be having trouble linking images and multiple links that worked before, but the above should be sufficient.
OK “Mr. where’s the data?” Please explain why some type of more detailed analysis shouldn’t be performed on the data of nearby urban and rural stations to see if it makes ANY sense to use one to adjust the other. Homogeneity indeed.
One last shot at hand editing.
Big Opps.
Here’s CO2 Science:
http://www.co2science.org/scripts/CO2ScienceB2C/data/ushcn/ushcn_des.jsp
Jean S
A followup to my comment (#36) about TOB adjustments. I subtracted TOB
adjusted temps of the 1999 edition from those of the 2000 edition. Most
of the differences were zero, most of the rest were 0.01 F, and the remaining
three were 0.02 F.
Re #96
Carl,
Here’s a similar plot from a station sorta between the other two:
http://gallery.surfacestations.org/main.php?g2_itemId=27408&g2_imageViewsIndex=2
So, what is going on here? Two of the three stations, to me at least, are more alike than the other. What objective means should be used to decide if, from a climatological viewpoint, any of these three stations are homogeneous enough to use in comparing annual mean temperature data, much less using them to adjust each other?
The message below in “”, was posted yesterday at cryosphere today by W Chapman. Is anybody at Climate Audit interested in an audit? (it changes the March 2007 to current yearly data for Antartica ice extent by approx minus one half to -1,000.000 sq km.
“Correction: we had previously reported that there had been a new SH historic maximum ice area. Unfortunately, we found a small glitch in our software. The timeseries have now been corrected and are showing that we are very close to, but not yet, a new historic maximum sea ice area for the Southern Hemisphere”.
This seems extraordinary and again without explanation. Is it possible to demand data quality info?
RE 111.
JerryB you are the TOBS god.
I’ve started reading Karl.
Click to access i1520-0450-25-2-145.pdf
A couple of thoughts.
1. This would be very nice paper for SteveMc and/or yourself to hold court on, Especially now.
2. Time series are adjusted using this model in order to remove BIAS, The adjustments, the argument
would go, should recover the true mean. However, the adjustment is an estimate with an error.
This error does not make its way into the final error terms of the temperature series. Do you think
this is an issue when people want to make claims about “hottest year on record”
3. It might be a ripe time to revist Karls work, especially with some CRN sites producing continuous
data from 3 sensors. A TOBS validation of sorts.
RE: #113 – That pales in comparison with what he did with NH “data” earlier this year. It was like, the result of some sort of brainstorming session between he, Jones and Hansen.
JerryB..
The plots of the errors in the TOBS model look kinda substantial… Bigger than the
instrument errors.. am I reading that right.. If so, then you have a time series
with an instrument error of ‘e’ and then an adjustment made to that record using a model
that has a error of ‘2e’.. but when final calcs are done, somebody pretends that
the error in the adjustment model vanishes.. Maybe I’m misunderstanding..
Anyway. Other folks out there go ahead and read
Click to access i1520-0450-25-2-145.pdf
if you want to see how USCHN does its TOBS adjustment to raw.
( opens can of worms)
Re #144,
steven,
Watch your language; this is a family friendly blog.
I’be brief, partly because we’re off topic for this thread.
The year to year fluctuations are such as to be a problem for hottest year claims at
any one location; I can’t assess such a claim about averages of several locations.
I don’t have the statistical, or other background, to be holding court on that
paper. Steve may be up to his elbows with other stuff that he would like to do.
A real quick TOB analysis goes like this:
At ~45 deg lat, the Spring and Fall the mean temperature change is on the order of a degree F every three days (the max and mins differ from the Spring to Fall likely due to earth heat capacity and ground temperature). So, if one shifted the measurement off a half a day, all the values for the month would be off a half a day -> 0.18F or 0.1C (correction for the month). Since the mean of the hourly temperature measurements is typically different from the mean of min-max, the adjustment could be different but it wouldn’t seem to be nearly as much as the difference between the hourly mean and min-max mean (which I understand to be ~1.5 deg (F or C I don’t remember). The corrections should be lower for Jan and July (Mean min and max typically).
Nice strawman. We “alarmists” tout global records, yes, and records that are significant in relation to, say, the 1930s. It is absurd to say that alarmists were touting 1998 US temps when it’s far more logical and significant to tout 1998 global temps. Record temps do matter in public relations, and it is not dishonest to use them to underscore the FACT that the earth has warmed, and the FACT that climate scientists are increasingly convinced that human actions are responsible.
And you didn’t tell everyone what Hansen said in 2001: that 34 and 98 were a tie.
Interesting how Boris can’t admit that he was wrong.
First he was full bore that only right wing wackos ever talked about which years were records.
Now he is full bore in proclaiming that the “alarmists” were touting records, but they were justified in doing so for publicity purposes.
Who cares that the data has no validity, it’s getting people sufficiently paniced that matters.
Record temps underscore the “FACT that climate scientists are increasingly convinced that human actions are responsible?”
If you seriously believe what you wrote, then you are pretty hopeless.
Re: 120
Picture of Boris or not? You decide.
Boris, you said:
As others have observed, NOAA issued “warmest U.S. year” press releases. And Hansen said as noted above:
Hansen and NOAA raised the issue.
I’ve talked very specifically about Hansen. In 1999, Hansen said that 1934 was 0.6 deg C warmer than 1998. I agree with you – and I’ve said so on more than one occasion – that Hansen was for 1934, before he was against it.
#119 Boris:
It’s context Boris, context. Warmed as compared to what period? Since the so-called, “Little Ice Age”? Or, in the last ~1600 years BPA? Since the last major Ice Age?
And that is unadulterated hogwash.
While slightly off topic, I thought an article in today’s WSJ seemed relevant:
Most Science Studies Appear to Be Tainted By Sloppy Analysis
From the article: “Statistically speaking, science suffers from an excess of significance. Overeager researchers often tinker too much with the statistical variables of their analysis to coax any meaningful insight from their data sets. “People are messing around with the data to find anything that seems significant, to show they have found something that is new and unusual,” Dr. Ioannidis said.
Highly recommended. Also, dig and read some of the original papers by Prof. Ioannidis.
For it before he was against it? Clever, Steve.
Tell me, when was he aginst it? You don’t seem to want to talk about the fact that Hansen never touted 1998 as the hottest year for the US. Please provide evidence he was “against it” as you say.
#118,
If your description of TOB adjustment is correct then it is seriously flawed. It is inserting a historical trend into data that isn’t necessarily following that trend.
There is a difference between touting a virtual tie in regional temps with touting a clear record in world temps. If you can’t see a difference, perhaps you should join the host of commentators who deny even that there is a consensus.
122:
I’ll ignore your immature little jab to say that my favorite episode was when Beaker was cloned. Good stuff.
Boris demanding evidence. This is rich.
CO2Breath September 18th, 2007 at 6:06 am,
Perhaps you can answer my question.
If climate change (slope of delta T) is what we are looking for and the slope is determined by rural stations, why in the heck are we doing all this adjustment fiddling on non rural stations?
If slope is what we want, why not just find the slope for consistent sections of each record and combine them?
That still leaves other problems: UHI/microsite/instrument etc. But at least it gives us some consistent way to use noisy signals of unknown consistency between different regimes (like a move or a change in instrumentation) to figure out what the slope might be.
I’ve taken a number of truly rural stations in Australia and evaluated them from dailt max and mins 1988-2008. There remains a problem. Some stations show no change, some show an incease, some show Tmax and Tmin converging, othets parallel. The problem is that the noise envelope is so large that you can author any story that appeals to you.
You really don’t get the Kerry ref, B? lol
The thing is that depending on context and year, the story and PR about “warmest year” and expections kept changing, and the adjustments kept moving things, and what was said by one group doesn’t have to be said by the other. The old “Hey, I didn’t say that, they did” game.
I’ve thought of an interesting experiment. What is the temperature of a room? Get an accurate to .01 C thermometer, and measure a room at the four corners and in the wall centers 1 foot from the wall at top middle and bottom of the height of the room. Average them. Do that every hour. Average them over a day. Do that for a week. Average the days. Then you could come out with “warmest day ever!” or “coldest day ever!” and the same for weeks, “week 7 has beat all records!” Then get the trends and start calculating and modeling. Or even better, do multiple rooms and compare them too! “Room 3 is trending down in week 22, and will soon exceed room 7 in week 15 as our all time low!”
Of course, if you were doing 8 rooms, and 2 of them were on the second floor, you’d have to adjust for height and temperature biases. And of course get ratios of the size of the rooms and the heights of the ceilings and adjust for them too. Oh, and rooms with water would have to be treated differently than those without.
Then for fun, different houses or neighboorhoods could be averaged and compared if enough people were doing it.
I’m still trying to figure out the code for central versus window AC bias, oven bias in the kitchen, humidity bias in the shower, and door bias in the garage (and insulated vs not). Do you think the people next door will share their code with me?
That’s what made it clever, SU. lol.
A consensus of what, meta-magical-science where the result is determined prior to the method being applied?
Well sure there is a consensus. Why not?
I seem to recall there was a consensus in 1904 with a few minor problems. Soon to be ironed out.
And never forget. Galileo was a denier.
So yeah. All hail the crowned and conquering consensus. If almost every one believes it must be true. Just do a Bayesian analysis. That will iron out the kinks and put paid to the deniers.
Of course there’s a consensus. And Hansen put the ‘con’ in consensus.
Is Boris Jousting or Jesting?
I’d say obfuscating
Steve,
You’re saying you want scientists to be more like accountants? Is that what you’re saying? You don’t
think this would lead to even more people taking up basket weaving courses in college?
Boris seems now to be interested in Global Warming rather than US warming since the US data doesn’t quite fit his biases. But Boris, a master of the mobile goalposts, is perfectly happy to accept the hockey stick as representing Global climate when Mann’s princple source, his Bristlecone proxies, all came from a very small portion of the US. Situational science is a little like situation ethics, they’re only valid when one wants them to be valid.
Re #114:
I’m glad to see somebody else is finally reviewing Karl’s work. The validity of TOB can be determined easily by anyone who has access to hourly data files. Simply test the diferences between the 24-hour averages and the 24-hour mean as determined by taking once daily max-min readings by selecting any hour of the 24-hour period and recording the max-min derived mean from the prior 24 hourly observations. One will clearly see differences obtained by taking 24-hour max-mins at 7AM local time (double counts the mins) versus taking those obs at about 3PM local time (double counts the maxes). The idea is to derive a formula to estimate the differences between once a day means taken at specific times during the day and means based on Calendar day observations taken once a day at local midnight. These formulas should not be applied to stations with available hourly observations as the real differences can be determined directly.
BTW, Tom Karl is one of the two candidates for President Elect of the AMS. The other is Sandy McDonald who is the Director of Earth System Research Laboratory and Deputy Assistant Administrator for NOAA Research Laboratories and Cooperative Institutes.
Ah well !
Comment on Hansen et al. There is always a ready market for bullsh*t, and there is plenty around to sell.
What I have learnt from visiting this site is that the interpretation of the observed record is just as accurate as the predictive climate models.
You either believe or you don’t !
Ok, THAT is either purposeful, malicious misconstruing of the most egregious kind or a complete absence of grokking so profound as to be embarrassing to the utterer.
I being an “like an accountant” means that scientists should expect to have other people go over their work looking for mistakes.
Then yes, scientists should be more like accountants.
Those who don’t like having other people go over their work can go into ….
I guess they would be out of luck, there are no other professions in which nobody goes over your work.
RE: #139 – virtually all engineering fields and a number of science fields already insist on design-for-quality. In engineering, that refers to designs of things. In science, that refers to designs of experiments, analytical techiques, frameworks of understanding, and in some cases, things. Why this resistence to quality? Wouldn’t improved quality help climate science to argue in the strictly factual realm and to take emotions and politics out of the discussion?
AKA, a typical Climate Audit comment.
I have spent my life working on and testing Rockets and spacecraft, neither of which can tolerate any significant failure or they will not complete their mission. There is an adage in the aerospace business about testing and it is “Test like you fly.” In other words, perform tests that will simulate as much as possible the conditions the vehicle will see while in use.
In aerospace, a lot of time is spent coming up with good ways to put this adage into practice. However, the tests will mean nothing if you don’t take good data during the tests. You must use calibrated instruments, understand all the phenomenon that will affect the measurements, rigorously eliminate anything outside influence that might affect the data, perform an end-to-end error analysis etc.
The reason I mention this is because if somebody who worked for me showed me the data used in global warming calculations, I would fire him on the spot. All the money we have spent measuring temperatures and analyzing the data has pretty much been wasted as far as I can tell. There is no basic understanding of how micro site affects skew the measurements; The sites picked to measure the temps rarely meet the requirements laid out (and where is the rigorous study that laid out those requirements?); The majority of the data is adjusted by some unknown, unproven algorithm; And on and on.
In short, these global warming papers and studies can not be used to conclude anything with any certainty.
BCL #139
I would say that I expect U.S. Government Employees to follow regulations regarding data quality.
And that goes for Scientists, Accountants, and everyone in between.
Re: 129 “little.. immature…jab”
LOL. When I saw that picture of Beaker with the huge flame in front of him, I started laughing hysterically. It seems so appropriate to describe my take on Gorebal Warning Alarmists. I’m actually still laughing, just thinking about it. I’d forgotten just how funny some of the Muppets stuff was(is). The fact that “Bunsen” is close to “Hansen” and is a “Scientist” is just icing on the cake. I had to keep beatin that poor dead horse until somebody complained (Though I thought Carl might rise to the bait.)
Re: #147
I believe bigcitylib meant his comment to be tongue-in-cheek in #139. However, if you do not follow standard data quality procedures, no matter what field you are in, you can be sure it will come back to bite you later.
Another aerospace saying is that data is mainly used during a failure investigation. And believe me, any and all errors in your data, methodology, conclusions or anything else you did not do a good job on will be found in a failure investigation, so you better make sure you do a good job up front.
Paul Linsay says:
September 18th, 2007 at 11:58 am
Re:127
I’m just starting to try to figure out TOB, but given that the concern is primarily when the TOB changes in the data stream, that simple understanding is the first thing that makes some sense to me. Over a calendar year it should average out, except that there are strange days when the temp drops all day from midnight to midnight or rises all day. There are also places with Chinook winds that likely have frequent non standard temp vs. time of day curves where corrections could be problematic.
It would seem that those irregular events are impossible to correct for in the historical record.
#91. Was any anomaly observed during Talledega Nights?
Re: 140
Mark O said “…if somebody who worked for me showed me the data used in global warming calculations, I would fire him on the spot.”
I would too, unless he first said “Look at this crap data”.
Seriously, I agree that the data is corrupted and I don’t know why people continue to use it at all. It reminds me of the gambler who went to a poker game knowing that the game was crooked and he couldn’t possibly win. When asked why he went he replied “Because it is the only game in town”.
When the only game in town is rigged you have to decide if you want to play. When the data in town is corrupt you have to decide whether you want to try to process it anyway even though it can’t be used to justify any theories at all.
Until someone can find a way to “de-corrupt” the data it is pointless to process it. The best that can be claimed is what Steve Mc is doing – proving that whether or not the data are corrupt, the method of adjusting it is not valid.
BTW I don’t believe that the data can be “de-corrupted” because there are far too many unknowns involved. Adjusting this data is as likely to make it worse as it is to make it better because you have no way of knowing if you are closer to the truth. You have no standard to use to determine what constitutes an improvement. How do you know what the measurement “ought” to be? You need an independent standard to evaluate the data and that doesn’t exist.
The orthodox AGW people believe that their theory is the standard, i.e adjusting the data is good to the extent that it brings the data into conformance with the theory. While they don’t state this explicitly, the adjustments seem to be consistently moving the data towards the theory. It also seems that many of the contrarians use their pet theories as the standard of judging the validity of the temperature data.
If the data is bad then it can’t back up any theory so if you’re in this to prove or disprove a theory then you are probably wasting your time.
At the NAS Panel hearings, Mann said that the bristlecones came from a “sweet spot” for estimating world temperatures. Nychka and Bloomfield, the statisticians, accepted this like bumps on a log.
M. Simon says:
September 18th, 2007 at 12:29 pm
“If climate change (slope of delta T) is what we are looking for and the slope is determined by rural stations, why in the heck are we doing all this adjustment fiddling on non rural stations?”
That’s one of my basic questions and so far the answer seems to be : who knows?
Gavin Schmitt of RC and GISS seems to believe that he only needs the data from six good stations to cover the lower 48. Perhaps we can find six such stations as part of Anthony Watts’ surface stations exercise.
I’m troubled by the seeming facts that the CO2 concentration is rather uniform geographically and temporally but the monthly temp trends at the few stations examined are all over the map. My question is” If there is “Global” (ubiquitous) warming, why is it not roughly the same everywhere (or even 100 mi apart, or even from month to month or from day to night)?
It’s becoming clear that this auditing needs to start with the individual station daily records. If we were to find a few geographically dispersed, “good” stations, it might not be too difficult with many hands to get the whole chain of analysis out in the open and reduce the skepticism of the many.
I don’t think you can compare real engineering or real science to climate science.
If there is unknown microsite contamination or messy programming, nobody’s going to die or get hurt badly, like you do if you don’t build a plane correctly or mix acids and bases. Or put in capacitors that explode. It’s just temperature trends as a meaningless overview average, come on. Why bother doing it correctly?
They aren’t the same thing. And least not in operation so far. I make no comment on what it means but it seems pretty clear.
re #150,
CO2Breath,
Some TOB stuff.
Re #150:
The errors (differences between means derived from the actual time of observation and the Calendar day means) do not balance out over time. The reason is that for whatever time of day the observations are taken, the current temperature is counted twice if the obs are taken at or near the max, or at or near the min.
Let’s say that the min occurs at 7AM which is also the ob time. The min shows up on that day’s report and also on the next day’s ob if the temperatures in the subsequent 24-hours are not any lower than the current day’s 7AM min. Similar double counting will occur with the maxes if the time of observation, say in the afternoon, is close to the daily max. This double counting does not wash out with time.
If, let’s say, the daily min did not occur at or close to the 7AM ob time, but imnstead happened in the afternoon or following evening. In this case the min would be counted just once, but counted nevertheless. So on once daily oberservations of max and min temps, the time of day is very important and can differ considerably from means observed at midnight (calendar day) and average temperatures derived from 24 separate hourly observations.
Sam Urbinto said:
“I dont think you can compare real engineering or real science to climate science.”
Since they have alternative medicine then why don’t we call it alternative science?
Steve and Anthony……. I believe the comparison of the temperature trends of ‘high quality’ rural and ‘high quality’ urban stations will be interesting. I had been assuming, and I’m still assuming, rural stations have provided the better data over time. However, a few days ago I caught a few minutes of a talk by Professor Jim O’Brien of COAPS at Florida State. He showed temperature trend examples (raw data, he said)for three stations in Florida. I don’t know if the temps were highs, lows or means for each station. I think they were lows. The two in the panhandle (one was DeFuniak Springs, I remember)showed downward trends – but he said the main driver they reflected was the ongoing reduction of wetlands around each station (and therefore a less moderated temperature drop overnight?). The one station in southern Florida showed an upward trend – but I believe he said the main driver was the gradual introduction of the sugar cane crop to the area, and that sugar cane needs and/or holds more surface water/moisture than the crop it replaced (and therefore moderates the temp drop overnight?). If such gradual land use changes (even some distance away from rural weather stations) do indeed change/reverse long term temperature trends, is there a filter to separate those stations from the rural stations that have always been surrounded by natural, or at least stable, landscapes?
Yep. Land of fruits and nuts (with apologies to Anthony).
BTW, how does a location become a “sweet spot”? Care to expand on that, Dr. Mann?
RE 139.
BCL, Amuse us and post some of your fiction here. I was especially fond of your pathetic
Dinosaur piece.
RE# 155
If the debate was just for academic interest I would agree with you. However, governments are talking about spend billions and billions of dollars, regulating both businesses and individuals, and making major decisions that will have far reaching effects to world economies. That is why it is so important to say: Stop, we do not have good enough data to be talking about such drastic measures.
Instead what should be done is to go back and start doing basic science like figuring out how to get good temperature readings.
Regarding TOB: I’m making some progress in my analysis. The Karl paper helped me understand why my previous simulations failed to show a time of observation bias. My simulations were too simple, and didn’t include the crucial aspects of hourly temperature data that lead to TOB. Thanks to Jerry B for his patience in putting up with someone who is learning.
As usual, the devil will be in the details of how NOAA is applying the adjustment. I recall a link that I didn’t keep that explained how NOAA applied the adjustment, breaking the day into morning observations, midday, and evening or something like that. Can anyone provide that link?
This aspect of the adjustment is crucial, because of how fast the adjustment changes at certain times of day.
Also, if anyone can give me a link to meta-data that would contain a historical record of time-of-observation by stations, and any information (even anectdotal) on the reliability of the time of observation (Does 0600 mean 0600 shrp, or does it mean sometime between 0545 and 0700?). Thanks in advance to the experts.
That statement is foolish.
Yep that is how meta-magical-science works. Start with a politically motivated, predetermined outcome and work backwards to make the science fit.
Ah, but, Mark O, that’s the policy side of it. Not the same issue (but of course related)
I’m just saying the adjustmenting of stations, the performing of organic chemistry experiments, and the designing of buildings are not really the same kind of things when it comes to what results we should expect, and what level of exactness they require or can provide.
Re #164,
Mike B,
We’re spending too much time off topic in this thread. I’ll reply to you
in the current unthreaded thread.
You have been using the term GAAP to describe problems with the provenance and integrity of the data sets being used by NASA. GAAP is a set of standards applied in the preparation of financial statements period. Yes, there are analogus principles whenever one is using quantitative methods, nevertheless using GAAP as an adjective in this case is probably not right.
What you have here is a failure or lack of internal controls. Internal control is a much broader concept. It can and should be properly applied to all activity of an organization. To use a simple example, a liquor pourer has nothing to do per se with accounting principles but using them assures proper portion control. Together with inventory procedures, the organization (a tavern) can minimize loss by cross checking receipts with the inventory drawdown. Steve, this looks to me like a rudimentary bookkeeping problem.
A study of this magnitude with a lot of personnel would properly require a massive amount of documentation like who has the authority to change or adjust what data, when and how. Typically, the most profound weaknesses in IC are centered in the officers and or directors who are in position to short circuit the controls, someone like Hansen.
In this instance, having the code is helpful, but you need to know the policies and procedures used to adjust data. They must have this kind documentation, if they don’t the study is effectively useless.
The raw data needs to be tested and verified with substantive auditing procedures before you can test the algorythms.
#169. There are layers of issues. The “GAAP” issue was the change in accounting policy – going form SHAP accounting to FILNET accounting without disclosure, without a change statement and probably without any approval or review other than Hansen’s fiat. GAAP is an analogy, but the concept of “Permanence of Method” is a useful principle here.
Steve and Christopher:
Here in New Zealand we have a legal framework which allows people to know the policies and procedures of any government department or government funded oranisation which makes decisions which directly affect us as an individual. ALL such policies and procedures have to be made available on request. I would be very surprised if NASA does not have such policies and procedures laid out and documented. Without such policies and procedures large organisations become chaotic and prone to the whims of individual employees.
Re: #153,
Did the NAS panel find the work was robust to the presence/absence of “sweet spots”? 😉
Re: Anthony Watts #83
Interesting treatment about the same thing (not climate science) here.
This site is a sort of irreverant look at the IT industry, but they seem to have a pretty good handle on “how things are done”. They slam “the Beeb” pretty good.
“What you have here is a failure or lack of internal controls.”
If you added “within a fiefdom which has become an embarassment to NASA” it would be completely accurate. I find application of elementary GAAP principals to be an excellent analogy considering the enormous sums likely to be misspent due to ill advised policy decisions.
Would NASA try to generate hardware design based upon data as malleable as that which Dr Hansen manipulates so adroitly?
Re#167: Sam Urbinto
Agreed. In an ideal world, the quality of the data would dictate what real world uses it had. However, with the current state of the climate science debate it is impossible to separate the science from the politics. And I really have no use for people on the left
right who politicize science.
Rick Ballard 174
“Would NASA try to generate hardware design based upon data as malleable as that which Dr Hansen manipulates so adroitly?”
Uh yeah,
The space shuttle foam problem allegedly stems from the removal of cfc’s from the application process. NASA went “green” without weighing the consequences of burning up a shuttle high in the atmosphere.
In post #105, CO2Breath links a paper comparing the temperature data sets of NCDC and USHCN (filenet version) for regions in the NE US. The authors use the USHCN data set as their control for critiquing the NCDC data set by citing it as well adjusted by methods described in peer reviewed literature. They claim by regression analysis that the differences in the data sets are primarily caused by the NCDC stations migrating in latitude, longitude and altitude while the USHCN stations were spatially constant over time. The unexplained part of difference they attribute to the more adjusted status of the USHCN data set.
Regardless of the validity of the main arguments presented in this paper, it does show the same large differences in adjacent and nearby regions for temperature trends that I saw when I used the USHCN (fully adjusted version) dataset to look at local temperature trends in IL. I have listed below some of these differences from the NE.
Temperature trends from 1931-2000 for NCDC for 14 regions in the states of VT, NH, ME, MA, CT and RI:
Range for all regions = +1.3 to -0.7.
Largest 5 trend differences in adjacent regions => 1.9, 1.8, 1.7, 1.5, and 1.4.
Temperature trends from 1931-2000 for USCHN (filenet version) for 14 regions in the states of VT, NH, ME, MA, CT and RI:
Range for all regions = +0.8 to 0.0.
Largest 5 trend differences in adjacent regions => 0.8, 0.7, 0.6, 0.5, and 0.4.
The questions arise as to how much of these differences in trends are errors in measurement and how much of these trends are mitigated by the USHCN adjustments which are more aimed to getting large area trends correct. Finally, what do global and regional temperature trends mean when we see large local differences?
Re: 177
I am interested in why the temperature plots in each graph in that paper appeared identical except for an offset and tilt. How could the shape of the curves look so identical if they were from (at least partly) different station sets?
I’m also curious if in your IL study you looked at daily, monthly or just annual temperature trends? If you looked at daily or monthly, was there strong similarity among stations or not?
If you have a few minutes, would you look at these three plots and see if you see any reason for the patterns that might exist?
http://gallery.surfacestations.org/main.php?g2_itemId=27418&g2_imageViewsIndex=3
http://gallery.surfacestations.org/main.php?g2_itemId=27453&g2_imageViewsIndex=2
http://gallery.surfacestations.org/main.php?g2_itemId=27408&g2_imageViewsIndex=2
Thanks.
RE: #153 – A xerophile slow growing strange tree, in an extreme, 14K foot alpine desert, at the Eastern edge of a semi permanent oceanic High Pressure system, but with maritime air blocked by a 14K foot mountain range, subject in the winter to outbreaks of Yukon air and in the summers of some years, quite a bit of cT air from Mexico, but not in all years, with radically variable moisture availability and temperature on a day to day, week to week, month to month, year to year and even possibly decade scale (as a normal part of the characteristics of its climate zone) on a substrate of intrusive igneous rock with minimal soil, as a sweet spot representative of “global average temperature” Ah, yeah, right …..
RE: #155 – Leaving aside any discussions regarding economic, political or social impacts, consider this. Let’s say that Hansen got his way. Let’s imagine that we had a “sequestration fever” scenario, whereby sequestration of CO2 became an obsession for, at a minimum, the major Western industrial nations, and perhaps the hole world. How would we stop it, and assuming we had such control, where? What if the figure for “where” was wrong? What if we took out too much CO2? Honestly, I fear the potential impacts of that possibility more than I fear doing absolutely nothing. We could literally suffocate the biosphere by drawing down the CO2 too far and wiping out all the chlorophylic flora, thereby leading to mass hypoxia of all fauna.
Layers of issues, well that’s an understatement. I concur,”Permanence of Method” is a reasonable use of this term of art.
AFP is reporting that disgraced South Korean cloning scientist Hwang Woo-Suk has fled to Thailand to escape controversy and continue his research.
The South Korean government banned Hwang from research using human eggs after his claims that he created the first human stem cells through cloning were ruled to be bogus last year.
Hwang remains on trial for embezzlement and fake research but has insisted in court that he could still prove he created the first cloned human stem cells.
With his claim to have paved the way for treatment of incurable diseases by creating stem cells through cloning which would not be rejected when inserted into a patient’s body, Hwang ignited a world-wide political and ethical debate on the use of embryonic stem cells in research.
His results could not be repeated by others, what AFP described as a “key test for scientific method.” His research was called into question after local media and other scientists raised the possibility that the data and photos of stem cells used for his scientific papers were fabricated.
Sound familar?
RE: #171
Paul,
Yes, NASA has a policy entitled “NASA POLICY ON THE RELEASE
OF INFORMATION TO NEWS AND INFORMATION MEDIA”
Click to access 145687main_information_policy.pdf
182, #4 is a gift to Hansen. He was coming under some criticism for spending so much time doing radio interviews on NASA time, and it appears that the new policy gives him cover. That’s not a good item.
Re: #178
The pattern in the Bozeman graph shows a late winter warming trend and a significantly lesser one for the summer. The reduced warming change in November from the adjacent months is both surprising and unexpected. Hebgen, on the other hand, shows an almost opposite trend to Bozeman, while Norris shows almost the same pattern as Bozeman, including the sharp dip in November. I cannot explain these differences within monthly trends nor make any estimates to whether some of it is due to measurement error. I can only wonder what global and regional temperature trends mean in terms of local differences (as I stated above) and here, as you recall it to my attention, significant month to month variations.
I know for IL in the past 100 years or so, warming trends as you go from north to south tend to go from larger to smaller, while at the same time showing significant differences in trends for the same latitudes. The warming trend in the Chicago area is primarily from warmer winters. In fact in past decades the extreme maximum temperatures of summer have occurred less frequently in this area. One should, I suppose, do some research and see what the climate models predict for monthly and local variations if they have that capability. For my IL analysis I looked at annual anomalies, but your graphs have tempted to go back and do some looking at monthly anomalies.
Re #186 Anyone interested in regional or local US temperature trends, for months or seasons or years, can generate their own time series here .
Have just latched on and read some fantastic comments re the climate debate…..excellent.
What put me on to your site was that a comment from your site was published on Free Republic.com. It was comment #85 by dirac angestun gesept. I thought this was so good, I pasted it into an email and it is going to be moving around …globally of course.
In doing so, I hope I didn’t infringe on someone’s rights.
Mahalo, John
John, #190, the last time I engaged on the subject of AGW on FR the tide had seemed to have turned to ‘believers’ instead of ‘deniers’; there were those, it seemed, that had begun to sip the koolaid and bought into GW (if not outright AGW) so effective has the drum beat ongoing in the ‘press’ so as to erode away any healthy skepticism or curiosity on the mechanics or basis for ‘claims’ on this subject. Steve has done yeoman’s work to change this, to audit the process, examine the numbers and bring the light of day to an otherwise ‘closed’ scientific process.
And don’t forget to hit the tip jar on the main page either (this includes you lurkers out there); the ‘counter’ to this site (RC or ‘realclimate.org’) on this subject/issue some say is funded by the dark or non-light side …
Steve, et al: Mahalo nui loa (translating for those in Rio Linda: that was Hawaiian for “thank you very much”), _Jim
#178 I suggest that the differences are due to the changes in water vapor. The more water, the higher the Tmin, the less water the lower the Tmin. Want to bet that the biggest change in all three stations is in Tmin and not Tmax?
RE: 185
David Smith
says:
September 18th, 2007 at 7:27 pm
Re #186 Anyone interested in regional or local US temperature trends, for months or seasons or years, can generate their own time series here.
( http://lwf.ncdc.noaa.gov/oa/climate/research/cag3/cag3.html )
I’ve been fooling with data for individual stations from here:
http://www.co2science.org/scripts/CO2ScienceB2C/data/ushcn/ushcn.jsp
I’ll have to look around the ncdc site more to figure out just which set of data they are uning.
DocMartyn says:
September 19th, 2007 at 4:26 am
#178 I suggest that the differences are due to the changes in water vapor. The more water, the higher the Tmin, the less water the lower the Tmin. Want to bet that the biggest change in all three stations is in Tmin and not Tmax?
I believe that the monthly min/maxs plotted are means of daily data for the stations.
Hebgen is just below an impoundment that freezes in Winter, Norris in a canyon with water running all Winter and Bozeman at the eastern end of a large high valley.
Re: # 81
“The Senate, and the public, wanted to know the cause of parched conditions in the Midwest, where the Mississippi had practically dried up. I said that our numerical climate model indicated a tendency for more frequent and severe droughts as the world became warmer, but a specific drought was a matter of chance, dependent on fluctuating meteorological patterns.”
This is an eggregious error, revealing appalling ignorance of climatic history. Droughts are associated with cooling. Has he never read the literature? It really shows that these are second class math wonks just playing with numbers, who cares where they come from or their quality.
It is a consequence of big, bureaucratic science. The good scientists tend to stay in the lab. The second class types who can’t do science but have ambition and skills in bureaucratic games rise to the top of the institutions. There are exceptions e.g. Fred Singer, but in general I think it is the rule. King in the UK is a glaring example of the rule at work.
It was the replication of this canard of warming=drought by the early GCMs that first alerted me to their inaccuracy. They continue to repeat it for the most part (one run of the Hadley model has a neutral effect of warming for precipitation on the Great Plains).
Clearly, Climate consists of more than temperature.
I’ve been looking for concurrent precipitation (there must be plenty of data as many temp stations I’ve visited had a rain pot associated) plots along with all the temperature plots and then for precip vs temp cross plots. Guess that I’ll have to look harder for some data to plot up myself. If we could reach consensus on which database to draw from, that’d be great.
In doing so, I hope I didnt infringe on someones rights.
Mahalo, John
Be my guest.
Here is the short answer: No.
Mark O: “the current state of the climate science debate it is impossible to separate the science from the politics” Which is why I said it’s not “real” science. It’s some kind of hodgepodge…. Models, proxies, and some kind of odd situation where we think we know what’s going on from sampling air temps and reading the top of the oceans and then combining them into some giant whole, then treat it as if it’s some fact or proof rather than a general idea. However, it’s pretty clear we do have some impact upon the system (of course) with our cities, our farms, our own numbers, our livestock, and the release of particulates and polution on both the atmosphere and land. But it’s fairly impossible to quantify, and I don’t know if you can call it science if you can’t get a better handle on it than we do. Once we get past the actual science of climatology and start talking about what it means and what to do about it, it goes out of being science into politics and public policy.
SteveS: That’s one of the issues; without replicable results and a fairly clear idea of the risk/reward (or “unintended consequences”) we’re just guessing, hence the reason I believe there is inaction; Hansen can’t “get his way”, because the folks making the decisions are going to argue about it, because the issue is polarized in so many ways. Because of the uncertainty. Obviously, if everything was as clear as some make it out to be. If it was that clear, “more” would be “getting done”. Plus, not everyone is oblivious to the fact that there are many unknown impacts. A “The operation was successful, but the patient died” kind of thing. Cure worse than disease. That’s even if you assume that any attempt to “fix” things would have any major impact at all, even if the major Western industrial nations were willing to fund “enough” money to “take action”. Although I do wish that budgets for R&D would be looked at and increased if needed, there doesn’t seem to be enough funding in a number of areas. Those trying to politicize it, they don’t know how to ask for more, perhaps, or at least not effectively.
Ah, water. It all comes down to water. Water vapor, clouds, glaciers, oceans and seas, rivers/lakes/streams, rain, aquifiers, irrigation systems, yard of the month.
Ah, water. It all comes down to water. Water vapor, clouds, glaciers, oceans and seas, rivers/lakes/streams, rain, aquifiers, irrigation systems, yard of the month.
So where are all the precip (and other forms of h2o) studies in the Gorebal Warning Science Journals?
Nobody I’ve seen focuses on the fact that water in its various forms is the largest factor in play here. Relative humidity and temperature anyone?
I’m partial to partial pressures (and absolute Temperature fractions).
CO2breath:
Fresh from the press: Increase in atmospheric moisture tied to human activities
When you heat the planet, you increase the ability of the atmosphere to hold moisture, said Benjamin Santer, lead author from Lawrence Livermore National Laboratorys Program for Climate Modeling and Intercomparison. The atmospheres water vapor content has increased by about 0.41 kilograms per square meter (kg/m²) per decade since 1988, and natural variability in climate just cant explain this moisture change. The most plausible explanation is that its due to the human-caused increase in greenhouse gases.
Using 22 different computer models of the climate system and measurements from the satellite-based Special Sensor Microwave Imager (SSM/I), atmospheric scientists from LLNL and eight other international research centers have shown that the recent increase in moisture content over the bulk of the worlds oceans is not due to solar forcing or gradual recovery from the 1991 eruption of Mount Pinatubo. The primary driver of this atmospheric moistening is the increase in carbon dioxide caused by the burning of fossil fuels.
As I know, day job of Livermores scientists is in nuclear weaponry. Now it is scary.
Ooops, here the link:
http://www.llnl.gov/pao/news/news_releases/2007/NR-07-09-01.html
RE: #199, 200 – Even at a national lab, a hopelessly infantile and statically oriented view – “I heat the flask with water and air in it ….. I measure the RH ….. the RH increases ….. nothing moves …. no convection …… no fronts ….. no baroclinic action ….. etc ….. but GHGs increase …. darefore, it muss be a pawsative feedback thingey”
If such thinking was not causing so much of a headache for so many, it would actually be rather entertaining.
It would seem that a decent Global Climate Model should be able to isolate and measure all of the drivers of the seemingly large annual variation in the global air/sea temperature mean.
If the temperature measurements are precise enough from one year to the next, and the oceans, land and air have enough heat capacity to have time constants of total heat on the order of decades, why do the annual numbers vary so much from one year to the next?
RE #202,
CO2Breath,
There are several major “oscillations” that are not annual, among the most
widely known of which would be ENSO, El Nino/Southern Oscillation.
It is interesting to do a search on Google News using – “James Hansen” NASA. You will see that the issue is getting at least some attention in alternative media, if not mainstream press – yet!
This must be very embarrassing for NASA. Their whole credibility is being jeopardised by James Hansen and his antics. CA participants might like to send a comment to this effect to NASA at public-inquiries@hq.nasa.gov. I’m sure that Administrator Michael Griffin will be pleased to hear from you.
Is the graph of the temperature adjustments correct? I downloaded NASA’s data adjustments from http://data.giss.nasa.gov/gistemp/graphs/US_USHCN.2005vs1999.txt
found the difference and graphed it but got a graphed that crossed the zero line circa 1960 but the shape was about the same. So I wonder if the graph on this page has a mistake or NASA’s reported change.
Re: The McIntyre factor [Deltoid] · Articles. September 24th, 2007 at 9:07 am
Even generally reputable sources, such as the New York Times, (see below), may on occasion distort reality, but they are honest in comparison to the source referenced above.
Excerpt from August 26, New York Times article: … Mr. McIntyre and Dr. Hansen also agree that the NASA data glitch had no effect on the global temperature trend, nudging it by an insignificant thousandth of a degree. … This NYT article seems more like an op-ed than a science report, and could be considered to be misleading in the way it presents information out of context. Reality may better be described as follows?
http://www.climateaudit.org/ amply indicates that McIntyre has serious doubts about US and world data and methods of analysis and measurements. The most important part about the 0.15 C error is that the programs used by NASA did not detect the error and the error of 0.15 C for a 6 year period is not trivial when applied to the US.
Reminder of Hansen’s 9/10 adjustment, see related chart above.
Speaking of Enron:
Here is a bit I wrote on Enron and Carbon Trading. Excerpted from a link provided in the above writing.
Enron commissioned its own internal study of global warming science. It turned out to be largely in agreement with the same scientists that Enron was trying to shut up. After considering all of the inconsistencies in climate science, the report concluded: The very real possibility is that the great climate alarm could be a false alarm. The anthropogenic warming could well be less than thought and favorably distributed.
One of Enrons major consultants in that study was NASA scientist James Hansen, who started the whole global warming mess in 1988 with his bombastic congressional testimony. Recently he published a paper in the Proceedings of the National Academy of Sciences predicting exactly the same inconsequential amount of warming in the next 50 years as the scientists that Enron wanted to gag.
They were a decade ahead of NASA. True to its plan, Enron never made its own findings public, self-censoring them while it pleaded with the Bush administration for a cap on carbon dioxide emissions that it could broker. That pleading continues today the remnant-Enron still views global warming regulation as the straw that will raise it from its corporate oblivion.
Enron stood to profit millions from global warming energy-trading schemes, said Mike Carey, president of the Ohio Coal Association and American Coal Coalition. The investigation into the collapse of Enron will reveal much more about the intricacies of the Baptist-bootlegger coalition which was promoting the Kyoto cause within the Republican Party and within US business circles. Coal-burning utilities would have had to pay billions for permits because they emit more CO2 than do natural gas facilities. That would have encouraged closing coal plants in favor of natural gas or other kinds of power plants, driving up prices for those alternatives. Enron, along with other key energy companies in the so-called Clean Power Group El Paso Corp., NiSource, Trigen Energy, and Calpine would make money both coming and going from selling permits and then their own energy at higher prices. If the Kyoto Protocol were ratified and in full force, experts estimated that Americans would lose between $100 billion and $400 billion each year. Additionally, between 1 and 3.5 million jobs could be lost. That means that each household could lose an average of up to $6,000 each year. That is a lot to ask of Americans just so large energy companies can pocket millions from a regulatory scheme. Moreover, a cost of $400 billion annually makes Enrons current one-time loss of $6 billion look like pocket change.
from: Investigate Magazine March 2006
Are people actually still discussing a global warming “consensus” among scientists??
I remember a big ‘consensus’ issue – which is still going on. My memory may not be 100%, but this is what I recall:
In the early ’70’s, physicist Alan Guth of M.I.T. postulated that the proton decays over time. Dr Guth persuaded a ‘consensus’ of physicists that proton decay was real, and he proposed an elaborate experiment to prove it. Dr Guth certainly didn’t expect the ‘consensus’ opinion to be falsified.
[Falsification is essential to the scientific method; if a conjecture can be proven false (falsified), it’s not scientifically valid. But if it cannot be proven false, it becomes a scientific theory; like the theory of gravity]. See: http://xxx.lanl.gov/abs/0707.1161v2
So in 1982, in order to test Dr Guth’s proton decay physicists built a huge [and very expensive] detector thousands of feet underground called the Kamiokande. But the Kamiokande detector failed to prove that the proton decays, as predicted by scientific ‘consensus.’
Governments and scientists did not give up. Next, they built Kamiokande II in 1985. The scientific consensus was overwhelming that this new, 10X more sensitive detector would prove that the proton decays over time [the lifetime of a proton was assumed – by consensus – to be about 1036 years].
Kamiokande II failed to find any evidence of proton decay. But many physicists were certain that the proton decays [since they had staked their reputations on it]. They prevailed on the government to spend more $billions, and Superkamiokande [SuperK] was completed in 1996. Why? Because the overwhelming scientific consensus was still that the proton decays over time into lighter subatomic particles.
But the ultra-sensitive SuperK failed to show any evidence of proton decay.
The consensus for proton decay was getting a little shaky after many so many $billions were spent [although a few scientists were awarded the Nobel Prize for discovery of neutrinos from supernovas by using the K and SuperK detectors and studying the results for over many years – at a time when the Nobel Prize was more respected than it is now].
Even though the consensus for the proton decay conjecture was finally eroding [after burning through much of the U.S. science budget, thereby starving many other programs], the search for proton decay had taken on an inertia of its own.
In 2006, the latest and greatest detector was put on-line: the SuperK II. As you can probably guess, the SuperK II has shown zero evidence of proton decay. More than $20 billion has been spent so far on the proton decay conjecture – based on the ‘consensus’ of physicists.
It hasn’t been money completely wasted. The purpose of the scientific method is to show whether a conjecture can be falsified. In the case of proton decay, the conjecture was falsified — forcing scientists to acknowledge that they needed a new and entirely diffeerent theory, to provide a hypothesis as to why the proton does not decay.
[snip]
Correction: the proton’s half-life was assumed to be 10,000,000,000,000,000,000,000,000,000,000,000,000 years [apparently my exponent didn’t get through the filter].
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