The Unstoppable Dirty Dozen

Science is good fun. Lately we’ve been working with an unnamed paleoclimatologist who goes by the handle of Delayed.Oscillator. He’s been good enough to answer some questions on dendroclimatology temperature reconstructions. Recently I’ve made comments about the Yamal series data and Briffa’s corrections about not allowing for trees to grow faster as they age. Briffa uses an exponential decay for his corrections to Yamal tree growth which looks like this:

Figure 1

The data is divided by the red line in top pane in the above plots. It has been my contention that since the red line drops well below the rest of the data it amplifies the older data creating an artificial uptick at the end of the reconstruciton. DO has made the following statement at his blog:

Let me be as clear as I can be, there is no sign that I can detect that it is old trees that increase their growth at Yamal (even if identified, this phenomenon would require some hypothesis as to the cause), At Yamal, a portion of the old trees are those that were growing together during a period of climate warming. If you examine the raw ring width, there are a few fossil series that have rapid increases toward the end. If Jeff’s hypothesis were correct, we’d expect these to be the oldest, right? In fact, the seven subfossil samples I identified as having rapidly increasing growth in their later years, six had a wide range of ages from 90 to 180 years (this comes with the caveat that we don’t know the exact pith age).

Now DO beat me to an analysis suggested by Steve Mosher to separate the recent old trees from the historic old trees and verify whether the U shape in pane 1 above (the average of all old trees) is a result of recent climate or is a standard shape in older trees. There are plenty of explanations as to why trees can grow faster in older age that we can be certain DO is aware of so the parenthetic portion is a bit grumpy of him. In DO’s conclusion his plot looked like this:

American Folley

Please read this at Watts Up With That. We don’t have much time left and this is a true tipping point, the suffering will be of a greater magnitude than anything predicted by AGW Advocates.  It will not be localized to America.

A Tale of Two Overkills

It’s time to stop the insanity and bring reason back to governance.

We are such fools.

 

 

 

Hero

This thread is in replacement of the last. You may leave comments here about Kimberly only, at least this we can agree on. The last thread was a bit wild but we’ve said our piece. Please don’t make attempts to continue the last thread here.

Kimberly Munley, the police officer who heroically charged into the enclosed room to confront the extremist Muslim terrorist and put to an end to the worst shooting rampage in US military history and the only extremist attack on US soil since 9/11. She nearly lost her life after being shot by the man multiple times.

Thank you for halting this evil tragedy when you did.

Invisible Elephants

Guest post by Tony Brown investigating the longest temperature records.  Tony has put together a well referenced post containing an interactive graphic which allows clicking on a location to see the individual records. WordPress free version won’t allow it to function so check out the link.   I think you’ll find it interesting.

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This graphic

http://climatereason.com/LittleIceAgeThermometers/

Pic Snapped by Lucy Skywalker

contains some 50 Instrumental temperature records that precede the 1850 Hadley Global temperature information. (Just press on a red dot on the globe)  There will be a well referenced study behind it in due course to put this information into perspective. It will hopefully become an invaluable resource for all researchers of climate.

These records provide a wealth of historic climate data for much of the Northern Hemisphere during a significant portion of the Little Ice Age. The datasets not only chart the considerable temperature variations through the centuries but also reflect the growth of the places they are located in, as many of the locations have developed from small towns in the 17^th Century to large cities today.

I am currently looking for any more long data sets so this facility can be enhanced. Uccle (Belgium), St Petersburg and Lima (Peru) will be added shortly. I am looking for Cadiz/San Fernando and any others not already mentioned here. The criteria are pre 1850,-which can be slipped ten years if it covers an area not already well represented.

The comprehensive study will tell much more, but after sifting through vast amounts of information and corresponding with a wide range of sources I would like to make a few interim observations.

There appear to be a herd of very large elephants in the climate room that are apparently completely invisible. The first is one called ‘global temperatures to 1850’ that has a cousin ‘1880’.

These global datasets are astonishingly complex, based on very small numbers of stations which continually change, and appear to be mainly a record of the 0.2% of the globe that has become urbanised, rather than represent the 99.8% of the world that isn’t. Therefore these creatures are to be treated with the utmost caution.

The next elephant is one called UHI. Many people seem to spend a lot of time looking the other way when UHI rampages by, including the IPCC.

Who’s in Denial

William Connolly has been gracious and not snipped any of my comments on the Tiljander debate at his blog.    I’m about ready to add him to my blogroll so this isn’t an attempt to bash his blog, however he wrote a beauty of an explanation as to why it’s ok to read thermometers upside down again.   It never ceases to amaze how far people can go to reason into almost any position. It’s like people who complain about the idiocy of government and continue to vote for more, like that will fix it.  Anyway his rationale is entertaining.

Imagine a climate proxy, accurate over the last 2kyr, that shows (for example, let us suppose) a warm period around 1000 AD and which, undisturbed, would show the recent warming. Further suppose for definiteness that this proxy is of such a nature that increases in the proxy value represent increases in temperature. Imagine this proxy is contaminated with non-climatic signal over the last 200 years, enough that the climatic signal is overwhelmed. Suppose that this contamination is of such a nature that it leads to a strong decrease in the values of the proxy over the last 200 years. Such a proxy (call it A), fed into the Mea algorithm, will be flipped over (due to its negative correlation with recent instrumental temperature) and will contribute a net cold influence around 1000 AD. How much it contributes will depend on how well it correlates to recent times.

Now there isn’t anything wrong with this paragraph that I can see.  He’s got a good handle on the multivariate nature of some of the regressions.  Consider that last sentence (which is correct) how much it contributes depends on how well it correlates.   Dead on for one of my biggest criticisms, these regressions are a form of data sorting  and are just as significant a no-no as the data elimination sorting where data is physically thrown away.  I think of the weightings of  a MV regression like modulating the data  (information) partially away rather than fully.  The fact that the modulation occurs on a correlation basis makes the complaint about the method exactly the same as the correlation based elimination methods.

Briffa Responds

I’m certain we’ll be hearing more on this today.  This post is copied from a link here.It is a comment from Keith Briffa regarding Steve McIntyre’s recent findings on tree ring data.  The most interesting thing he said was that the Yamal data was NOT pre-sorted according to climate data.  He appears to take offense at the suggestion even though it is standard practice in much of Mannian paleoclimatology.

In addition, he claims his data is the same as the H & S data with different standardizations.  Paper is here. I don’t know a darn thing about corridor standardization but I can infer some detail after my recent study of the Briffa standardization.  On the surface, it seems impossible that standardization might flatten the data to the extent expressed in H & S but we’ll have to wait and see.  There are some points in here which seem to misrepresent reality however, and lead me to wonder what will be said next. i.e. He offers no justification for excluding the original data

Sounds kind of familiar doesn’t it.

I also wonder what he means by unusually high summer temps, there isn’t anything in McIntyre’s statement supporting or denying anything about temperature (my bold in his comment).  Not one comment I recall from Steve. And I’ve seen the temp graphs and there doesn’t seem to be any evidence of unusually high summer temps either.  It’s a distraction which is difficult for me to grasp in the context of reality, as though it is meant to discredit McIntyre while supporting the unprecedentedness of global warming.

UPDATE:

Steve’s reply to Briffa.

==============

The Yamal ring-width chronology of Briffa (2000)

My attention has been drawn to a comment by Steve McIntyre on the Climate Audit website relating to the pattern of radial tree growth displayed in the ring-width chronology “Yamal” that I first published in Briffa (2000). The substantive implication of McIntyre’s comment (made explicitly in subsequent postings by others) is that the recent data that make up this chronology (i.e. the ring-width measurements from living trees) were purposely selected by me from among a larger available data set, specifically because they exhibited recent growth increases.

How to Read RC

Gavin apparently put up a response to Steve McIntyre now as well.  I almost never check over at Real Climate but always know what’s happening from other peoples comments.  Their post is very silly from a scientific perspective but will read well for their attack dogs.    I’m becoming pretty familiar with these reconstructions and methods for an aeronautical engineer and I’m not really interested in defending Steve McIntyre but ya know, sometimes it needs to be said.

So for those who don’t have a year of working code on paleo papers under your belt, this is how the RC post reads to me:

Gridded Daily Sea Ice – NSIDC

I’ve been working on improving the noise rejection of the sea ice area and anomaly from the NSIDC gridded data. These plots are created by summation of the gridded satellite sea ice concentration data the following table is up to date as of 2008

Platform and Instrument	Time Period
Nimbus-7 SMMR	26 October 1978 through 20 August 1987
DMSP-F8 SSM/I	9 July 1987 through 31 December 1991
DMSP-F11 SSM/I	3 December 1991 through 30 September 1995
DMSP-F13 SSM/I	3 May 1995 through the March 26 2008
DMSP-F17 SSM/I	26 Mar 2008 through present

This table is not the official table presented by the NSIDC as I have added the end point for F13 and the beginning point for NOAA-17. I should note that for a time in 2008 overlapping data is presented for both F13 and F17.

My plots still aren’t perfect matches to the NSIDC or Cryosphere but they are very close. Some reasons for differences include:

• No access to final processing routines used to blend and filter daily trends.
• The anomaly for these plots is computed over the whole length of the dataset whereas other scientific institutions limit the anomaly calculation period to different fixed sets of years.
• Filtering differences
• Differences in methods for locating and removing bad points from the near real time data

Either way, differences in the results are quite small and the net trends and absolute magnitude are close. Thanks to the NSIDC for making the data available, their openness gives me an improved comfort in the quality and completeness of the work done by this agency.

How Important is Yamal

Recently there has been a bit of two-way extremism in blogland claiming that hockey sticks that depend on Yamal (don’t matter). A second group of people who are aware of the large quantity of serious flaws in climate science are ready at every new discovery to chuck the whole thing. Unfortunately for those who just want clear answers, neither of these is the case. The following studies are affected to some undetermined degree by Yamal, Quote by Steve McIntyre.

In summary, the apparent problems with Briffa’s Yamal series impact multiple other studies:
Briffa 2000, Mann and Jones 2003 (used in the recent UNEP graphic), Mann et al (EOS 2003), Jones and Mann 2004, Osborn and Briffa 2006, D’Arrigo et al 2006, Hegerl et al 2007, Kaufman et al 2009 (and of course, Briffa et al 2008).

It’s interesting to note that so many popular hockey stick reconstructions employ Yamal. On the other hand AGW advocates are far to quick to say reconstructions don’t matter either – Gavin Schmidt and Michael Mann at Real Climate’s latest, where several hockey sticks with even more severe problems are presented as supporting evidence of the Robustness of the Yamal paper group. Unfortunately for them, it cannot be denied, the Yamal find is a serious issue in climatoloty. Unfortunately for those of us at the mercy of government policy based on these papers, problems in climate science like this are NOT unprecedented.

This is a guest post by John F. Pittman which endeavors to explain the import of proxy temperature recontsructions in the context of the IPCC AR4 report.

Jeff Id

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Why Reconstructions Matter

Wahl and Amman Hockey Stick. Besides the obvious Nike swish popularity, and clear visual impact, there are scientific issues regarding the hockey stick graphs. --- Jeff Id

Introduction:

The AGW blogosphere is busily proclaiming that the recent problems with Briffa’s Yamal do not matter. With the debunking of the Mann MBH9x by M&M0x, and by the NAS and Wegman reports, reconstructions began using the Yamal chronologies. Despite the claim by AGW proponents, it does matter. We start not at the chapters on reconstructions, but rather with understanding and attributing climate change.

Section I

Understanding the Basic Claim

From IPCC AR4 WG1 Chapter 9 p665.

Understanding and Attributing

Climate Change

Greenhouse gas forcing has very likely caused most of the observed global warming over the last 50 years. This conclusion takes into account observational and forcing uncertainty, and the possibility that the response to solar forcing could be underestimated by climate models. It is also robust to the use of different climate models, different methods for estimating the responses to external forcing and variations in the analysis technique. … Anthropogenic influence has been detected in every continent except Antarctica (which has insufficient observational coverage to make an assessment), and in some sub-continental land areas. The ability of coupled climate models to simulate the temperature evolution on continental scales and the detection of anthropogenic effects on each of six continents provides stronger evidence of human influence on the global climate than was available at the time of the TAR. No climate model that has used natural forcing only has reproduced the observed global mean warming trend or the continental mean warming trends in all individual continents (except Antarctica) over the second half of the 20th century.

Yamal- The Dirty Dozen

We’ve all been looking at the Yamal (Steve Mosher named)treemometer ring width data. Yamal is a tree ring series with a huge hockey stick blade used in and likely to be highly influential in a lot of serious studies which demonstrate the unprecedentedness of recent temperatures. When Steve McIntyre replaced 12 of the hockey stick creating proxies (the dirty dozen) with equally valid schweingruber proxies the blade of the hockey stick disappears along with the unprecedentedness. Of course the boys at “Real” Climate made a big stink about it but notably missed any specific criticism of the methods or data chosen. However, in this post I looked at the methods of RCS standardization and the effects it has on the series.

RCS is a method for correcting the ring widths of trees based on the age. For instance, we would expect that a young tree would have thicker rings at its core. As it grew thinner rings would form with diameter and eventually the diameter would become basically a non-factor. So dendro guys figure that they should fit an exponential decay function to tree rings and that will give a basic correction factor for total width.

The function is of the form

correction = A + B * e ^ -(C * age)

Don’t worry too much if that’s not a familiar equation to you, you’ll figure it out either way. I’m sure it is to many of my readers though. This equation is fit to 100% of the data simultaneously in Yamal. The assumption is:

1 – All the trees in the same conditions grow at the same rates.

2 – Fitting the equation to all trees together will average out over all the variable climates and despite different conditions, we can achieve a similar result to #1.

There is a problem with these assumptions which occurs at the endpoints of dendroclimatology reconstructions in that the most recent trees are still alive and therefore on average going to have a skewed age – either younger because they are equal and haven’t died or older (as is the case here) because trees that are long lived are easier to find than partially fossilized mud bound trees.

What it means is that the assumption fails for trees existing in vastly different conditions.

Now what I wanted to see was first, what is the correction factor per year used and second how different is the correction factor when fit to the dirty dozen. After all, tree age, location, group and other conditions affect trees dramatically. So my question was – If we had only the 12 Yamal trees, how would the correction factor look.

Figure 1 - Correction factors

The dozen trees fit to the same function have a very different result when run alone – these trees are different! Now climatology in general may be tempted to call this plot bunk because these trees are chosen in a timeframe where we should see hockey stick temperatures and we have too few samples. However, I would remind climatology that these were the same 12 trees used to create the MASSIVE blade on a 200 plus core study.

A Different Yamal – Corrections and Signals

This post investigates the effects of RCS on the Yamal proxy data. It started out with a thought that it might be possible to create a simple method for creating series from tree ring widths that would act as a sanity check for the other methods. However, it turned into a learning experience with the tree ring data. Here’s what I found.

Figure 1

Figure 1 is an average of the entire Yamal dataset. The change in variance from the zero age to the 400 age is due entirely to the number of trees available in the series. The far left is from 252 trees while the far right is from one. This data is fit to a function of Corrected= a + b * e^-(c*age). However, all the individual trees are fit which of course weights the fit very heavily toward the younger trees. So the question becomes what do the 252 Yamal trees look like when plotted. The red curve is the mean overlaid.

Past Arctic Warming Also Created by Currents

I’ve stated here on several occasions that the ‘Recent’ Arctic ice thinning is more likely a current change issue rather than a temperature issue.  Differences in flow change the transfer of vastly more energy than a couple of degrees of air temp, however changing air temperatures are a strong indicator of differences in regional water flow.  This effect is very visible in the arctic ice videos posted here.  Recently Dr. Arnd Bernaerts asked by email that I call attention to  his paper on Arctic Warming for a period we don’t hear about enough.  He has a shorter version link which he also gave here. I really enjoy the historic discussions of climate and the paper is quite readable so I’ve put the whole paper up instead.

——————

The Circumstances of the Arctic Warming in the early 20^th Century

Author: Arnd Bernaerts

Dr. Arnd Bernaerts
Hamburg, Germany

Abstract

The Arctic has a crucial role in the world’s climatic system, and global warming may have an amplifying effect. The recently observed thinning of the sea ice has alerted scientists and policy makers alike. That was quite different when a similar warming occurred 90 years ago, which is still regarded as one of the most puzzling climatic event during the last century. That needs not to be, if the situation is being viewed from on oceanic perspective, together with the fact that the winter air temperatures in the higher Northern Hemisphere are greatly influenced by the ocean, particularly in the North Atlantic, which is partly free of sea ice up to the Fram Strait. Here also ends the West Spitsbergen Current, a current which supplies the Arctic Ocean with warm and saline Atlantic water. Already back in 1920s air temperature observation showed a strong warming at Spitsbergen during the winter season. By analyzing the winter temperature profile of five coastal stations it can be demonstrated that the climatic shift at the end of the 1910s had been closest to Spitsbergen, allowing the conclusion that circumstances related to the West Spitsbergen Current have caused the early Arctic warming almost a century ago.

---

Introduction

The Arctic is an ocean. By the Fram Strait at about 80° North, between Greenland and Spitsbergen, it is connected with the Atlantic, which serves as a major gate for the supply of warm and saline water to the Arctic Ocean, which is coming with the West Spitsbergen Current. The subject of the paper is whether the warming in the early 20^th Century has been caused here.

The term “circumstances” implies the observation or influence of “existing conditions”. Here the use of the term shall mean the presentation of circumstances which rectify to draw certain conclusions concerning the period of Arctic warming in the early 20^th Century on how it started and how it shaped up. The paper will cover both aspects, but with a clear priority for the circumstances around the year 1919 when the warming started. The method of investigation will be explained in the second section of the paper, based on a general picture that will be presented first of all. The third section is about the “circumstances” which will analyze temperature records in the Northern North Atlantic realm that may provide clues concerning the location, the timing, and the likely source of the warming event, and thereon discuss the information.

Guest Post at Pielke Sr. on RSS UAH Differences

Professor Ben Herman has done a guest post at Roger Pielke Sr’s blog on the differences we’ve seen in UAH and RSS.  The land sea effect was noted in blogland by Chad at treesfortheforest (link on right) but the experts in this case have been paying very close attention to this substantial issue.  Today I will add to this post a video showing the differences between UAH and RSS by month for 3 atmospheric levels.  The video is still uploading.   In the meantime check out Dr. Herman’s post below.

Update: Video added.

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Guest Post By Ben Herman Of The University of Arizona

RSS and UAH Videos

The following are video representations of the published RSS and UAH data.  This time the videos include lower troposphere, mid troposphere and lower stratosphere versions.  As before there are a number of interesting features to the data including oscillations between poles, contrasting anomalies between layers and strong variance in the polar regions compared to the equator.   I find the lack of variance at the equator very interesting as it demonstrates the quality of the signal used to determine whether the IPCC fingerprint exists is actually decent.  Another interesting point is that RSS doesn’t do the spatial filtering  of UAH and has several areas of missing data which show as dark purple where UAH presumably does some infilling.  The size of the polar UAH infilling is also apparent.  My favorite difference is the heating and cooling in the lower troposphere are often opposed by the stratosphere.  If you freeze the frames at different points you can see big lower troposphere hotspots and dark blues in the stratosphere.  In other cases the hot/cold effect switches to cold/hot.

R unfortunately decided to start making a scribble across Russia and Canada even though I’ve set the flags not to do that.  I’ll have to get my money back.

RSS Video YouTube Click to Play

The corresponding UAH video:

Delayed Oscillator Fast Reply

Back in my college days on a whim, a friend and I made an electronic scale from a quad strain gauge taken from a small yet very high precision printing press. The guage was attached to a 0.20 thick piece of spring stainless. Everything except the electronics was taken from junk of one kind or another including a gorgeous precision analog meter from a device I don’t remember. Anyway, during calibration experiments it could weigh a 0.062″ diameter piece of writing paper with a 20% scale deflection so it was very sensitive. Small breezes in the room caused expected problems on the signal by deflecting the beam so the whole thing was intended to go in a breeze tight box.

By the way, the Quad strain guage configuration is good for thermal and side strain corrections so it was ideal and my friend and I spent a week on it. However after it was finished we found an imperceptibly small gust of wind on the room temperature very low power electronics could cause a 5% deflection. As planned, the whole project went into a wind protecting box to guard from any breeze yet because of room temperature drift, the intended accuracy was impossible. We had balanced the electronics plus and minus to account for temp but you know, even our best guess wasn’t enough. – wrong again.

There is no substitute for confirmation of theory.

Today my venting elicited a response from my post on Briffa’s Yamal. DO, is apparently a climatologist of some kind (he’s not saying but if you google DO you can understand) so his knowledge of the detail of the subject of climatology is far better than my own. He’s been quite honest in his email and other replies which is more than I can say for most of the AGW blogs so I’m happy to link.

DO does not understand how a non-climatologist could be frustrated with the state of dendroclimatology and he reacts strongly against the tone of my posts here. I’m not going to apologize for my tone yet am always happy to learn. To explain our (mine and your) collective angst to DO further, I’m forced again to quote Ryan O – “Guage R & R” every dendro should read up on it.

UAH Temperature Anomaly Video

More experience makes better videos.  The following are two UAH TLT (lower troposphere) temperature anomaly videos.  There is a ton of detail in them, you can see the 1998 temperature spike – some have had questions as to where this spike came from.  You can also see the recent cooling wave, Ryan O noticed the oscillation back and forth between the poles.

The first video is high speed and came out quite good.  I’ve worked out some of the video compression difficulties and am producing higher quality videos now.  The 10 fps is just for viewing bulk properties and is way too fast to see small details.  The 5 fps video is much better for watching detail.

UAH TLT Temperature Anomaly 10 Frames per Second - Click to play

The next video is the same thing at a lower frame rate which caused youtube to hesitate every few frames.

Fixing Briffa’s Latest

This is a very difficult post for me because I don’t believe any of this has anything to do with temperature, however some well paid scientists disagree. This is therefore in response to a Keith Briffa pre-paper replying to SteveM’s post on Yamal where he replaced some of the data using a Schweingruber dataset. Briffa presented what he referred to as a sensitivity test of Yamal by adding different datasets in. While he didn’t provide his code, he did provide the data and plots of the RCS corrections applied to the various datasets.

RCS is a generic method of fitting a curve to a set of tree ring data. In the original Yamal an exponential decay was used to represent tree ring widths. I’m critical of the exponential function method because it doesn’t recognize the potential for trees to increase in growth rate as they age. Since nothing I’ve read biologically defines that this is impossible it makes no sense to ignore the possibility unless you want older trees to curve upward after standardization. It’s odd to see it being ignored by the pros but it happens to result in spurious hockey sticks through a complex and surprisingly common mathematical phenomena referred to here as hockestickization.

Yamal is a driver amongst hockey sticks – I mean a good old fashion 1 wood. Straight shaft, sharp blade, wide sweet spot. Since Steve’s discovery the climatoknowledgists have been scrambling to explain how so few trees could define such strong warming around the globe. In Briffa’s response he showed several methods using new data to also create hockey sticks. However, Dr. Briffa again used a method which is functionally identical to the exponential decay method for correcting tree ring widths. It seems he simply cannot recognize that trees may increase in ring width.

Figure D from Briffa's response. Click to expand. This is a series of chronologies included with Yamal to show that you can always get a similar hockey stick.

Circling Yamal 3 – facing the thermometers

This is a guest post by Lucy Skywalker which looks further at the local temperature records from the Yamal region.  Link to the original post is here.

————————————————

Let’s look closely and compare local thermometer records (GISS) with the Twelve Trees, upon whose treerings depend all the IPCC claims of “unprecedented recent temperature rise”.
For my earlier Yamal work, see here and here. For the original Hockey Stick story, see here and here.

Half the Hockey Stick graphs depend on bristlecone pine temperature proxies, whose worthlessness has already been exposed. They were kept because the other HS graphs, which depend on Briffa’s Yamal larch treering series, could not be disproved. We now find that Briffa calibrated centuries of temperature records on the strength of 12 trees and one rogue outlier in particular. Such a small sample is scandalous; the non-release of this information for 9 years is scandalous; the use of this undisclosed data as crucial evidence for several more official HS graphs is scandalous. And not properly comparing treering evidence with local thermometers is the mother of all scandals.

I checked out the NASA GISS page for all thermometer records in the vicinity of Yamal and the Polar Urals, in “raw”, “combined”, and “homogenized” varieties. Here are their locations (white). The Siberian larch treering samples in question come from Yamal and Taimyr. Salehard and Dudinka have populations of around 20,000; Pecora around 50,000; Surgut around 100,000; all the rest are officially “rural” sites. Some are long records, some are short.

Hockeystickization Revisited

I’ve got plenty of posts right now to work on but today Steve McIntyre called our attention to a couple of acerbic replies from Keith Briffa to Steve’s discovery that the Briffa Yamal temperature data which has a HUGE hockey stick blade was actually the EXACT same data as the orignal H&S Yamal which shows NONE. The difference is in the RCS “standardization” method (AKA – hockeysickization) used to correct for tree ring widths. If I don’t miss my guess, we’ll be seeing more of RCS with improper exponentialesque curve standardizations as in my opinion it’s a near guarantee of a hockey stick blade and after Mann and now Briffa I don’t trust these paloclimate ’scientists’ any farther than I can throw them.

I’ve got to say again Briffa’s original Yamal is a disgusting piece of garbage work and the sooner paleo’s drop the P.O.S. the better. It’s got an unreasonable blade created from RCS with NO science or verification to prefer the ‘accidentally’ chosen exponential curve that is ENTIRELY RESPONSIBLE for the big evil bullcrap blade. See one of my posts on this HERE.

Well I’m not happy with Briffa or anyone who chooses to defend this garbage work so I’ve decided to dig through his reply to Steve a bit and make a little trouble. In particular, I want to focus on this little gem by Briffa himself.

We would never select or manipulate data in order to arrive at some preconceived or regionally unrepresentative result. However, as we will show here, the fact that we did not incorporate the KHAD data has no serious implications for the general validity of our published work.

My emphasis. But those of us who follow climate know that is not the case. So I went looking for a few examples from his own PUBLISHED work. Here is an article from Briffa. although Osbourne was the lead author. I assure you this is standard in paleo science where proxy’s are often assumed to be temperature without any verification other than mathematical correlation. There are many papers which have similar statements, Mann08 is no exception. I could write a whole post on the differences between clear and obvious selection or the ‘partial selection’ created by multivariate methods where non-correlating proxies are deweighted rather than deleted resulting in a less transparent selection of data based on preconceived conclusions.

Tax^2

This came to me by an email just to remind people how far we’ve come.  I can’t tell people how much tax is right but I can say we have too much.

 

A Tax Poem

At first I thought this was funny…..
then I realized the awful truth of it.

Be sure to read all the way to the end!…

Tax his land,
Tax his bed,
Tax the table
At which he’s fed.

Satellite Temps Getting Closer

 

Dr. Christy offered some explanations for the divergence in RSS vs UAH which is visually related to land vs sea, originally discovered in blogland by Chad at treesfortheforest – link on the right.  Chad is doing some very interesting work beyond this minor issue.  His plots lately could take a dozen posts up.

First, Dr. Christy gave an explanation of the types of corrections for RSS and UAH which was new to me.

RSS computes diurnal corrections based on climate model diurnal signals for each grid. UAH calculates the effect empirically (from 3 AMSUs which observed the earth simultaneously for about 13 months but at different times of the day – so sampling a specific grid 6 times per day from which we could reconstruct a diurnal cycle for land or ocean for each month of the year.)

UAH focuses on large-scale precision, so at each latitude a single land diurnal correction is applied to all land grids in that band, and similarly for oceans. It turns out that the noise generated in trying to calculate the diurnal correction of a single grid is so great, that more harm than good comes of it. Our goal is to make the zonal and large scale averages as precise as possible, so we deal with large scale corrections since the noise is beaten down that way. In a pleasant outcome, our gridpoint anomalies more precisely match those of radiosondes at those grids than either RSS or ZOU-STAR

So for the pre-2002 years RSS using models to correct for diurnal cycle and UAH using a 3 satellite calulation from actual data came up with what visually seem to be the same answer. The next figure shows that the main difference between the two sets seems to be latitude based prior to 2002. Two completely different methods got what appears to be almost the same result.