Dr. Roger pielke confirms a point made in comments in my earlier post on BEST about all data coming from a single source, which is the National Climatic Data Center. (NCDC)
By Dr. Roger Pielke Senior
Comment On The Article in the Economist On Rich Muller’s Data Analysis
On Climate Etc, Judy Curry posted
Berkeley Surface Temperatures: Released
which refers the Economist article
A new analysis of the temperature record leaves little room for the doubters. The world is warming
The Economist article includes the text
There are three compilations of mean global temperatures, each one based on readings from thousands of thermometers, kept in weather stations and aboard ships, going back over 150 years. Two are American, provided by NASA and the National Oceanic and Atmospheric Administration (NOAA), one is a collaboration between Britain’s Met Office and the University of East Anglia’s Climate Research Unit (known as Hadley CRU). And all suggest a similar pattern of warming: amounting to about 0.9°C over land in the past half century.
The nearly identical trends is no surprise as they draw from mostly the same raw data!
I discussed this most recently in my post
The new Muller et al study, therefore, has a very major unanswered question. I have asked it on Judy’s weblog since she is a co-author of these studies [and Muller never replied to my request to answer this question].
Hi Judy – I encourage you to document how much overlap there is in Muller’s analysis with the locations used by GISS, NCDC and CRU. In our paper
Pielke Sr., R.A., C. Davey, D. Niyogi, S. Fall, J. Steinweg-Woods, K. Hubbard, X. Lin, M. Cai, Y.-K. Lim, H. Li, J. Nielsen-Gammon, K. Gallo, R. Hale, R. Mahmood, S. Foster, R.T. McNider, and P. Blanken, 2007: Unresolved issues with the assessment of multi-decadal global land surface temperature trends. J. Geophys. Res., 112, D24S08, doi:10.1029/2006JD008229. http://pielkeclimatesci.files.wordpress.com/2009/10/r-321.pdf
we reported that
“The raw surface temperature data from which all of the different global surface temperature trend analyses are derived are essentially the same. The best estimate that has been reported is that 90–95% of the raw data in each of the analyses is the same (P. Jones, personal communication, 2003).”
Unless, Muller pulls from a significanty different set of raw data, it is no surprise that his trends are the same.
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Anthony, I hope Dr. Muller had the courtesy to let you know about (x-posted from BH where I was when I found it):
http://online.wsj.com/article/SB10001424052970204422404576594872796327348.html WSJ October 21, 2011
The Case Against Global-Warming Skepticism
There were good reasons for doubt, until now.
By RICHARD A. MULLER
Are you a global warming skeptic? There are plenty of good reasons why you might be.
As many as 757 stations in the United States recorded net surface-temperature cooling over the past century. Many are concentrated in the southeast, where some people attribute tornadoes and hurricanes to warming.
The temperature-station quality is largely awful. The most important stations in the U.S. are included in the Department of Energy’s Historical Climatology Network. A careful survey of these stations by a team led by meteorologist Anthony Watts showed that 70% of these stations have such poor siting that, by the U.S. government’s own measure, they result in temperature uncertainties of between two and five degrees Celsius or more. We do not know how much worse are the stations in the developing world.
Using data from all these poor stations, the U.N.’s Intergovernmental Panel on Climate Change estimates an average global 0.64ºC temperature rise in the past 50 years, “most” of which the IPCC says is due to humans. Yet the margin of error for the stations is at least three times larger than the estimated warming.
[…]
Without good answers to all these complaints, global-warming skepticism seems sensible. But now let me explain why you should not be a skeptic, at least not any longer.
Over the last two years, the Berkeley Earth Surface Temperature Project has looked deeply at all the issues raised above. I chaired our group, which just submitted four detailed papers on our results to peer-reviewed journals. We have now posted these papers online at http://www.BerkeleyEarth.org to solicit even more scrutiny.
[…]
Global warming is real. Perhaps our results will help cool this portion of the climate debate. How much of the warming is due to humans and what will be the likely effects? We made no independent assessment of that.
REPLY: No, he didn’t your notice is the first I’ve seen of it. But no matter – Anthony
Once again, it’s proven you can’t pull a bucketful of gold out of a septic tank, and all the bucketfuls pulled out will look remarkably similar, smell about the same as well. Go figure.
While the paper does use GHCN data, the last line mentions “In another paper, we will report on the results of analyzing a much larger data set based on a merging of most of the world’s openly available digitized data, consisting of data taken at over 39,000 stations, more than 5 times larger than the data set used by NOAA.” So you may hold out hope that this much larger dataset will show different results, but having worked with much of that data myself (GSOD, GHCN-Daily, ISH, etc.) I wouldn’t advise holding out much hope. Its also worth mentioning that the BEST approach uses raw (rather than homogenized) data and applies their own novel method to deal with breakpoints, but obtains results quite similar to those of NOAA.
The current paper is mostly about developing new methods for station combination (least squares method), homogenization (the scalpel), and spatial interpolation. The next will be a synthesis of the various additional temperature records that they have compiled.
Oh gee, they’ve toned it down a hair. We’re “doubters” now. But what they seem to forget is that nobody doubts or denies anything. The world warms. The world cools. The sea rises. The sea falls. Sorry, we just doubt that the world is climatically invariant, which is your REAL issue, and one you cannot sidestep. The whole crumbling house of cards is built on that constancy premise, so any change must have a “cause”, but it can’t be just normal…or natural. Get over it….!
Download the data and read the file called sources.
The arithmetic mean of Tmax and Tmin is not the ‘average temperature’.
In order, get an ‘average’ you would need to sample randomly or at fixed times and average.
Its time to move on to better datasets than Tmin/Tmax, which do exist, eg in Australia there are fixed time temperature datasets going back 60 years.
And surprise, surprise these datasets don’t show anything like the warming the Tmin/Tmax datasets show.
What they do show is a marked warming just after dawn that reduces thru the day and no warming at all at night.
Something is increasing Tmin, and that something is increased early morning solar insolation due to reduced haze and particulate pollution over the last 50 years.
Let’s see, which book will I buy from this site:
The Hockey Stick Illusion or
Climategate: The Crutape Letters or
The Great Global Warming BLUNDER – How Mother Nature Fooled the World’s Top Climate Scientists or maybe
Evidence-Based Climate Science: Data opposing CO2 emissions as the primary source of global warming?
Or should I just buy the coffee cup that pictures a scientist lying to me, in order to protect his grant money? That one makes me laugh! Or the T-shirt with the dumb scientist that his heating up the weather station with a barbeque. UHH, barbeques are HOT you dummy! LOL.
Whichever it is, gotta move fast, losing Muller is shaking my faith!
Even with 95% overlap in the underlying data, having three independent analyses does serve a purpose. Namely it constrains the extent to which the results can have been bent to achieve the desired result. Also the Climategate revelations essentially completely destroyed the credibility of the CRU so having other people look at the data is helpful.
I thought the science was settled and us sceptics were deniers, mentally deficient and/or deluded?
These people remind me of very insecure children; constantly needing reassurance that what little Johnny says about them in the playground isn’t true, is it?
I red one of the 4 papers, the one I am particularly interested in:
Decadal Variations in the Global Atmospheric Land Temperatures
http://berkeleyearth.org/Resources/Berkeley_Earth_Decadal_Variations
I’ve been looking into the N. Atlantic SST (and its derivative AMO) for some time now, even as a novice in this field, I found it wanting.
If you do understand the AMO, and it appears that even the ‘experts’ do not, have a read.
The first comment above quotes Muller as saying :
“Global warming is real. Perhaps our results will help cool this portion of the climate debate. How much of the warming is due to humans and what will be the likely effects? We made no independent assessment of that.”
Sorry, what are we disagreeing with ?
I think Muller et al may need to do more to distinguish between (1) absolute levels in UHI and non-UHI sites, (2) respective trends thereof, (3) trends in the rates of change of the trends, and (4) eliminate all data sets before 1950, as it was only then that global coverage reached 70%.
From my quick read of this post, I have to add that my take is different. What I really see here is in the category of replication – did they handle their given data correctly, given their conclusions? This is not merely basic, it is fundamental to sound science.
The uncertainties are well noted – something lacking in the breathless SPM media stories and their many iterations. After this come questions about data adjustment and alterations over time – a huge issue, officially untouched. Which means “Trust us – we’re scientists.”
Another issue is data supplementation: should other data sets (for instance, one thinks of DMIs arctic data) be included or not? This is also a large, looming issue.
In short, “it ain’t over ’til it’s over.” Then the pronouncements will gain force, because the data will speak loud and clear.
Dr. Pielke,
I believe the BEST results using all 39,000 stations can be found here: http://berkeleyearth.org/movies.php
As Mosh mentions, the data and code is also available for download.
@- Pielke Sr
“Unless, Muller pulls from a significanty different set of raw data, it is no surprise that his trends are the same.”
The point is not that three groups find the same trend in the same data, its that NONE of the studies show any significance difference in trend between urban and rural sites. The meme that the warming is exaggerated by the UHI effect is refuted.
“philip Bradley says:
October 20, 2011 at 11:31 pm
The arithmetic mean of Tmax and Tmin is not the ‘average temperature’.”
It is definitely an average. However, it is not necessarily an accurate arithmetic mean of all possible temperatures in that population (of a particular moment in time), which is, I think what you are getting at. A single non-random measurement from a population is NEVER an accurate representation of a normal distribution (n=1 lol), which means that many of the parametric statistics employed by AGW “scientists” could and probably does generate misleading and inaccurate results.
.
Wow, the BEST people sure are confident. From their two page summary of the main findings (pdf):
1. They ALREADY know their papers WILL pass peer review and be published and WILL be used for the next IPCC report. What’s the deadline? Is there enough time for any revisions?
2. That’s a manual copying from the document. Using two different pdf readers, all that would copy-and-paste was a string of nonsense characters. So much for “open and accessible.” Anyone else get that problem?
Richard Black of the BBC is all over this ‘news’.
http://www.bbc.co.uk/news/science-environment-15373071
He specifically states that the Berkeley Project ‘validate’ Prof. Jones’ findings.
The BEST analysis is not based on data. It is based on monthly averages. Monthly averages are not a measurable quantity – they are a construction. Monthly averages have been computed “at least 101 different ways” (Peterson, Vose 1997). Mathematically, monthly averages are a strange sort of smooth, albeit with windows of different length (sometimes 28, sometimes 30 and sometimes 31 days) and computed at different intervals. A 30-day moving average would make more sense. It seems, at first blush, that the BEST analysis does not assign any uncertainty to the monthly averages themselves. Indeed, in the file called data.txt, the column labeled “uncertainty” has the value 0.0000 for all monthly average statistics for all stations.
Unless, Muller pulls from a significanty different set of raw data, it is no surprise that his trends are the same.
————-
I also would have been surprised if the results had been different, as I also understood that the raw data was pretty much the same.
However the point of the exercise was to prove whether or not the other analyses were faulty due to either bad analytical techniques or due to deliberate data fudging.
It is now proven that that many of the accusations made against climate scientists in this area were false.
Although I expect that many of the people who will not believe no matter, what will now expand the scope of their favorite conspiracy theory to include the BEST researchers.
Stephen Brown,
Inasmuch as it shows values comparable to HadCRUT using a much larger set of stations (39,000 vs 7,000), I’d consider it a validation. The BEST folks have an updated comparison graph using all stations (rather than just the GHCN stations included in the draft paper) here: http://berkeleyearth.org/analysis.php
Curious statements found in that two page summary (bold added):
and
1. They know the human effect is “discernable” (should be discernible) in the last 50 years, although they have not assessed how much of the warming is human caused. Thus the revealed assumption is that humans have had a large enough effect to discern from the records. Is that a valid assumption?
2. They also know how much of a difference figuring in the oceans makes when figuring the land+sea global warming amount, and will now start figuring how much ocean warming there was to get accurate numbers to figure out what is the land+sea global warming amount. Nothing like the confidence of knowing what the result will be before looking for it.
And having read here many times about the paucity of historical ocean temperature data and the headaches of constructing records resembling anything like reliable and accurate, the BEST team must indeed have a very confident set of cojones!
The BBC are going gangbusters on the melting planet this morning – have even rolled out the Phil Jones ‘significant warming since 1995’ trope.
http://www.bbc.co.uk/news/
Ok, maybe not a conspiracy but sure smacks of an orchestrated PR drive ahead of Durban. But I guess they think the public is too stupid to notice.
Posted on October 20, 2011 by Anthony Watts
By Dr. Roger Pielke Senior
Comment On The Article in the Economist On Rich Muller’s Data Analysis
“The nearly identical trends is no surprise as they draw from mostly the same raw data!”
I think there are some excellent high frequency global temperature reconstructions for the last two millennia (A. Moberg et al.) and they should be the reference for any scientific method to explain the causes. Because of the well known oscillations of the axis of the earth (chandler wobble), atmosphere (QBO) and ENSO [frequency ratio: 4:2:1] it seems to be important to discriminate these terrestrial impedances from the heat power current variation from the Sun.
There is no scientific need for trends in understanding the reconstructed global temperature spectra; each high frequency peak has a cause.
There is a difference in the meaning of reconstructed (absolute) temperature values and its frequencies. The meaning of the frequencies is higher, because they my lead to a physical mechanism. There is no real global temperature, there is a variable heat source named Sun which drives the local temperatures over the time superimposed by the terrestrial impedances.
There is a temperature table from UAH since AD 1659 available including the average temperature of each year. Despite the amplitude of that data it is remarkable look at a comparison of this high frequency data with some synodic frequencies of couples in the solar system with rough hand fitted amplitudes:
http://www.volker-doormann.org/images/uah_1650_2010_ghi6.gif
This graph may demonstrate that the method filtering (“trend”) high frequency temperature data is problematic; it suppresses important high frequency data for the idol of a ‘democratic best absolute global temperature trend’.
V.
I am puzzled that these people here keep on reporting on only the average temp.s differences’, when clearly you have to look at the average temp.s differences of maxima, means and minima together, and their ratio to each other. In other words, there should be 3 plots.
http://www.letterdash.com/HenryP/henrys-pool-table-on-global-warming