Picking Cherries in the Gulf of Alaska

The bias arising from ex post selection of sites for regional tree ring chronologies has been a long standing issue at Climate Audit, especially in connection with Briffa’s chronologies for Yamal and Polar Urals (see tag.)  I discussed it most recently in connection with the Central Northwest Territories (CNWT) regional chronology of D’Arrigo et al 2006,  in which I showed a remarkable example of ex post selection.

In today’s post, I’ll show a third vivid example of the impact of ex post site selection on the divergence problem in Gulf of Alaska regional chronologies.  I did not pick this chronology as a particularly lurid example after examining multiple sites. This chronology is the first column in the Wilson et al 2016 N-TREND spreadsheet and was the first site in that collection that I examined closely.  It is also a site for which most (but not all) of the relevant data has been archived and which can therefore be examined. Unfortunately, data for many of the Wilson et al 2016 sites has not been been archived and, if past experience is any guide, it might take another decade to become available (by which time we will have all “moved on”). Continue reading


Cherry-Picking by D’Arrigo

One of the longest standing Climate Audit issues with paleoclimate reconstructions is ex post decisions on inclusion/exclusion of data, of which ex post decisions on inclusion/exclusion of sites/data in “regional [treering] chronologies” is one important family.  This was the issue in the original Yamal controversy, in response to which Briffa stated that they “would never select or manipulate data in order to arrive at some preconceived or unrepresentative result”. However, Briffa and associates have never set out ex ante criteria for site inclusion/exclusion, resulting in the methodology for Briffa regional reconstructions seeming more like Calvinball than science, as discussed in many CA posts.

Unlike Briffa, D’Arrigo has candidly admitted to the selection of data to arrive at a preconceived result. At the 2006 NAS panel workshop, Rosanne D’Arrigo famously told the surprised panelists that you had to pick cherries if you want to make cherry pie.   Again in 2009 (though not noticed at the time), D’Arrigo et al 2009 stated that they could “partially circumvent” the divergence problem by only using data that went up:

The divergence problem can be partially circumvented by utilizing tree-ring data for dendroclimatic reconstructions from sites where divergence is either absent or minimal. (Wilson et al., 2007; Buntgen et al., in press; Youngblut and Luckman, in press).

Portfolio managers would have like to have a similar option in constructing portfolios: if, after the fact, you pick stocks that went up, it would be trivially easy to “circumvent” market downturns.  That paleoclimatologists seem so obtuse to this simple observation is a major puzzlement.

In today’s post, I’ll show an absolutely breathtaking example of biased ex post picking by D’Arrigo et al in the D’Arrigo et al 2006 CNWT chronology.  It was impossible for anyone to identify the full measure of this bias at the time or for many years afterwards, as D’Arrigo and coauthors failed to archive data at the time and refused to provide it when requested. They were supported in their refusal by IPCC WG1 Co-Chair Susan Solomon, who, as CA readers are aware, threatened me with expulsion as an IPCC AR4 reviewer for seeking supporting data for D’Arrigo et al 2006 (then cited in preprint by AR4).   The data showing the cherry picking only became available in 2014 as part of a belated archiving program in the final year of Gordon Jacoby’s life.  

Continue reading

Marvel et al.: Implications of forcing efficacies for climate sensitivity estimates – update

A guest article by Nicholas Lewis

Introduction

In a recent article I discussed the December 2015 Marvel et al.[1] paper, which contends that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) derived from recent observations of changes in global mean surface temperature (GMST) are biased low. Marvel et al. reached this conclusion from analysing the response of the GISS-E2-R climate model in simulations over the historical period (1850–2005) when driven by six individual forcings, and also by all forcings together, the latter referred to as the ‘Historical’ simulation. The six individual forcings analysed were well-mixed greenhouse gases (GHG), anthropogenic aerosols, ozone, land use change, solar variations and volcanoes. Ensembles of five simulation runs were carried out for each constituent individual forcing, and of six runs for all forcings together. Marvel et al.’s estimates were based on averaging over the relevant simulation runs; taking ensemble averages reduces the impact of random variability.

In this article I will give a update on the status of two points I tentatively raised in my original article. Continue reading

Bob Carter

I was very saddened to learn of the sudden death of Bob Carter ( here here).   He was one of the few people in this field that I regarded as a friend.  He was only a few years older than me and we got along well personally.

carterI will not attempt to comment on his work as that is covered elsewhere, but do wish to mention something personal.  In 2003, when I was unknown to anyone other than my friends and family, I had been posting comments on climate reconstructions at a chatline.  Bob emailed me out of the blue with encouragement, saying that I was looking at the data differently than anyone else and that I should definitely follow it through.  Without his specific encouragement, it is not for sure that I ever would have bothered trying to write up what became McIntyre and McKitrick (2003) or anything else.

We’ve met personally on a number of occasions over the years – at AGU in 2004 or 2005, and on several occasions at Erice, most recently last summer.  He was always full of good cheer, despite continuing provocations, and unfailingly encouraging.

R.I.P.

 

 

 

 

 

 

Appraising Marvel et al.: Implications of forcing efficacies for climate sensitivity estimates

A guest article by Nicholas Lewis

Note: This is a long article: a summary is available here.

Introduction

In a recent paper[1], NASA scientists led by Kate Marvel and Gavin Schmidt derive the global mean surface temperature (GMST) response of the GISS-E2-R climate model to different types of forcing. They do this by simulations over the historical period (1850–2005) driven by individual forcings, and by all forcings together, the latter referred to as the ‘Historical’ simulation.

They assert that their results imply that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) derived from recent observations are biased low.

Marvel et al. use the GISS-E2-R historical period simulation responses to revise estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) from three observationally-based studies: Otto et al. 2013, Lewis and Curry 2014 and Shindell 2014. Their revisions give figures that are substantially higher than in the original studies. Remarkably, the Marvel et al. reworked observational estimates for TCR and ECS are, taking the averages for the three studies, substantially higher than the equivalent figures for the GISS-E2-R model itself, despite the model exhibiting faster warming than the real climate system. Not only is the GMST increase simulated by GISS-E2-R is higher than that observed, but the ocean heat uptake rate is well above the observed level.[2] No explanation is given for this surprising result. Continue reading

Update of Model-Observation Comparisons

The strong El Nino has obviously caused great excitement in the warmist community.  It should also cause any honest skeptic/lukewarmer to re-examine whether observations remain inconsistent with models. In today’s post, I’ll show two comparisons: 1) CMIP5 models (TAS) vs HadCRUT4; 2) CMIP5 models (TLT) vs RSS (UAH is only negligibly different).  For this post, I’ve used the same scripts as I used in earlier comparisons.  Continue reading

COP21 Emission Projections

In the wake of COP21, I thought that it would be interesting to compare the respective pathways of China and the U.S (and others) based on official data. I still plan to post on this topic, but obtaining official data on the pathways proved much more difficult than I anticipated.  Leading into the COP21 conference on October 31, 2015, the UNFCCC Secretariat published its  “Synthesis report on the aggregate effect of the intended nationally determined contributions”, the terms of reference of which were described as follows:

synth_mandate

The UNFCCC Synthesis Report was 66 pages long.  However, it contained zero information on the commitments of the individual countries or even regions.   Searching for such information will be the topic of today’s post.  Continue reading

Balascio et al and the Baffin Island Inconsistency

There was some publicity this week on a paper by Young et al (Science Advances, 2015), which, according to Gifford Miller , whose work has been frequently discussed at CA (see  tag), had supposedly put the “coup de grace on the Medieval Warm Period”, that had been so long wished for by the Team.   I will discuss (and dissect) this article in a forthcoming post, but first wish to report on some related developments in an article (Balascio et al, Climate of the Past, 2015) which I had discussed last summer while it was in open review, which I will subsequently connect to the discussion of Young et al. Continue reading

What “Science” is “Telling Us” About Climate Damages to Canada

Just before leaving for Paris, the Canadian government, like many others,  stated that “science” was “telling us” that climate change was “one of the greatest threats of our time”.

The scientific evidence is clear: climate change is one of the greatest threats of our time. The Government of Canada recognizes that global temperature increases must be limited to at most two degrees Celsius, and Canada’s way forward on climate change is being informed by what the science is telling us.

The Canadian government posted up a briefing by “renowned climate scientists Dr. Gregory Flato (Environment Canada) and Mr. Alain Bourque (Ouranos)” to Prime Minister Justin Trudeau, Cabinet Ministers, and provincial and territorial Premiers – see here.

I was particularly interested in their argument on how the “threat” to Canada manifested itself.  How exactly does “science” show that a modest increase of temperature would severely damage Canada?

Too often, expositions of supposed climate damage amount to little more than loud assertions that the science is settled, with occasional interjections of “Look, polar bear!!” (to modify a phrase from And Then There’s Physics). The Flato and Bourque presentation is in this tradition. Its exposition of damages consists of only a few slides accompanied by very short explanatory text.

In today’s post, I will parse the first such slide and will try to parse other slides in future posts.

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Antarctic Ice Mass Controversies

Like many others, I was interested in the recent controversy arising from findings of Zwally et al 2015 that there had been ice mass gain gain of ~112±61 Gt/year over 1992-2001 and ~82±25 Gt/year over 2003-2008.  Zwally’s findings obviously contradict a widely held contrary belief, expressed, for example, in IPCC AR5’s assertion there was “high confidence” that the Antarctic Ice Sheet had been losing mass for the prior two decades and that the rate of loss had “likely increased” to ~147±75 GT/year over 2002-2011 or in NASA’s widely cited statement that “the continent of Antarctica has been losing about 134 billion metric tons of ice per year since 2002”.

I had no prior interest in the literature, but was intrigued by the dramatic contrast between Zwally and IPCC on such a widely covered topic.  This quickly led into a voluminous technical literature, which is the subject of today’s post.   The issues were not only about interpretation of satellite data, but quickly led into thorny interpretations of the history of the entire Holocene.

Warning: the following post is very lengthy, but I think that the details are worth paying attention to.

Continue reading

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