Pages2K Revised Arctic Reconstructions

Climateaudit reports

Kaufman and the PAGES2K Arctic2K group recently published a series of major corrections to their database, some of which directly respond to Climate Audit criticism. The resulting reconstruction has been substantially revised with substantially increased medieval warmth. His correction of the contaminated Igaliku series is unfortunately incomplete and other defects remain.

This post is on comparing the revised reconstruction with other data. In the comments Jean S provides a graph that compares the revised graph in red with the previous version in black. I have added some comparative time periods.

  1. The Maunder minimum of 1645-1715 corresponds to a very cold period in the Arctic. The end of the minimum was associated with a rebound in temperatures.
  2. The Dalton minimum of 1790-1820 corresponds to a period of sharply declining temperatures, with the end of the period being the coldest in 2,000 years. The end of the minimum was associated with a rebound in temperatures.
  3. The early twentieth century shows about 1.1oC of warming from trough to peak in a time period that corresponds to the 1911-1944 trough-to-peak warming of the global temperature series. It is about twice the size of that calculated globally by HADCRUT4 and GISTEMPa, consistent with there being greater fluctuations in average temperatures at the poles than in the tropics.
  4. The late twentieth century shows about 0.5oC of warming from trough to peak in a time period that corresponds to the 1976-1998 trough-to-peak warming of the global temperature series. This is broadly in line with that calculated globally by HADCRUT4 and GISTEMPa. This possibly corroborates data of individual weather stations having a warming adjustment bias (e.g. Reykjavik and Rutherglen) along with the national data sets of USA (Steve Goddard) and Australia (Jennifer Marohasy and Joanne Nova). Most of all, Paul Homewood has documented adjustment biases in the Arctic data sets.
  5. The proxy data shows a drop in average temperatures from the 1950s to 1970s. The late twentieth century warming appears to be a mirrored rebound of this cooling. Could the measured reductions in Arctic sea ice cover since 1979 partly be due to a similar rebound?

In conclusion, the Pages2K Arctic reconstruction raises some interesting questions, whilst corroborating some things we already know. It demonstrates the utility of these temperature reconstructions. As Steve McIntyre notes, the improvements partly came about through recognizing the issues in the past data set. Hopefully the work will continue, along with trying to collect new proxy data and refine existing techniques of analysis.

UPDATE 23.00

In the above, it is evident that the early twentieth century (c.1911-1944) Arctic warming in the revised reconstruction was twice the size of late twentieth century (c.1976-1978) warming, when global temperature anomalies show the later period as being greater in size. Steve McIntyre’s latest post shows that at least part of the answer may lie in the inclusion of the Okshola, Norway speleothem O18 and Renland, Greenland O18 series. These proxies both show a downturn at the end of the twentieth century. This might conceivably be a much greater influence on the discrepancy than either adjustment biases in temperature data, or differences between actual, not fully known, temperature anomalies between the Arctic region and the World. However, we will get a better understanding by eliminating the obvious outliers in the proxies and by continuing to positively seeking to eliminate bias in the global surface temperature anomalies.

Kevin Marshall

Notes

  1. Earlier this year I calculated the early twentieth century warming rates for the HADCRUT and GISTEMP series. They are


  2. From the same posting the 1976-1998 warming rates are



     

Lewandowsky’s false inference from an absurd correlation

Steve McIntyre has posted a number of instances where Stephan Lewandowsky has reported correlations for which there is little or no evidence. My comment is

Even more bizarre than absurd correlations, is to draw inferences of cause and effect from correlations, when there are a huge number of equally valid (or invalid) inferences that can be made.

The title of the Hoax paper is “NASA faked the moon landing|Therefore (Climate) Science is a Hoax: An Anatomy of the Motivated Rejection of Science“. The first part implies that, due to coming to believe that the moon landing was faked, survey respondents reasoned that climate science was also a hoax. But, given that this survey was only on climate blogs, is it not more likely that the respondent’s rejection of “official” or orthodox version of events goes the other way?

Looking at the data there is a similar issue of low numbers on support of the paired statements. Only 10/1145 supported CYMoon. Of these only 3 supported CYClimChange. Of these only 2 scored “4” for both. And these were the two faked/scam/rogue respondents 860 & 889 whose support of every conspiracy theory underpinned many of the correlations. The third, 963, also supported every conspiracy theory. Let us assume that they are genuine believers in all the conspiracy theories. Further, let us assume that one of the 13 conspiracies in the survey did trigger a response of the form “because I now know A was a conspiracy, I now believe B is a conspiracy”. There are 2n(n-1)= 312 possible versions of this statement. Or, more likely, no such reasoning process went through any respondent’s mind at all. Given the question was never asked, and there is no supporting evidence for the statement “NASA faked the moon landing|Therefore (Climate) Science is a Hoax” it most likely a figment of someone’s imagination.

Data in support of this statement

In the survey the answer 1 was a strong rejection, 4 a strong support. Out of 1145 responses, only 6 strongly supported the “NASA faked the Moon Landing” hypothesis, and a further 4 lent support to it. Of these 10, only 3 support the “Climate Change is a Hoax” statement.

The strong support for conspiracy theories is shown by giving the average score of respondents over all 13 conspiracy questions. The 3 that supported by CYMoon and CYClimChange had the highest average scores of all 1145 respondents.

Gergis 2012 Mark 2 – Hurdles to overcome

BishopHill reported yesterday on the withdrawn Gergis paper that

The authors are currently reviewing the data and methods. The revised paper will be re-submitted to the Journal of Climate by the end of July and it will be sent out for peer review again.

It is worth listing the long list of criticisms that have been made of the paper. There are a lot of hurdles to overcome before Gergis et al 2012 should qualify for the status of a scientific paper.

My own, quite basic, points are:-

  1. Too few proxies for such a large area. Just 27 for > 5% of the globe.
  2. Even then, 6 are well outside the area.
  3. Of these six, Gergis’s table makes it appear 3 are inside the area. My analysis is below.


  4. Despite huge area, there are significant clusters – with massive differences between proxies at the same or nearby sites.
  5. There are no proxies from the sub-continental land mass of Australia.
  6. Need to remove the Palmyra Proxy because (a) it has errant readings (b) fails the ‘t’ test (c) > 2000km outside of the area, in the Northern Hemisphere.
  7. Without Palmyra the medieval period becomes the warmest of the millennium. But with just two tree ring proxies, one at 42 O South and the other at 43 O S representing an range from 0 to 50O S, this is hardly reliable. See the sum of proxies by year. Palmyra is the coral proxy in the 12th, 14th and 15th centuries.


On top of this are Steve McIntyre’s (with assistance from JeanS and RomanM) more fundamental criticisms:-

  1. The filtering method of Gergis excluded the high quality Law Dome series, but included the lower quality Vostok data, and the Oroko tree ring proxy. McIntyre notes that Jones and Mann 2003 rejected Oroko, but included Law Dome on different criteria.
  2. Gergis screening correlations were incorrectly calculated. JeanS calculated properly. Only 6 out of 27 proxies passed. (NB none of the six proxies outside the area passed)


  3. The Gergis initially screened 62 proxies. Given that the screening included proxies that should not have included 21 proxies, but should it have included some of the 35 excluded proxies. We do not know, as Gergis has refused to reveal these excluded proxies.
  4. Screening creates a bias in the results in favour of the desired result if that correlation is with a short period of the data. RomanM states the issues succinctly here. My, more colloquial take, is that if the proxies (to some extent) randomly show C20th warming or not, then you will accept proxies with a C20th uptick. If proxies show previous fluctuations (to some extent) randomly and (to some extent) independently of the C20th uptick, then those previous fluctuations will be understated. There only has to be a minor amount of randomness to show bias given that a major conclusion was

    The average reconstructed temperature anomaly in Australasia during A.D. 1238-1267, the warmest 30-year pre-instrumental period, is 0.09°C (±0.19°C) below 1961-1990 levels.

UPDATE 03/08/12

The end of July submissions date seems to have slipped to the end of September.

Palmyra Atoll Coral Proxy in Gergis et al 2012

There is a lot of discussion on Bishop Hill (here and here) and Climate Audit of a new paper in Journal of Climate “Evidence of unusual late 20th century warming from an Australasian temperature reconstruction spanning the last millennium“, with lead author, Dr Joëlle Gergis. The reconstruction was based upon 27 climate proxies, one of which was a coral proxy from Palmyra Atoll.

There are two issues with this study.

Location

The study is a “temperature reconstruction for the combined land and oceanic region of Australasia (0°S-50°S, 110°E-180°E)“. The study lists Palmyra Atoll as being at 6° S, 162° E, so within the study area. Wikipedia has the location at 5°52′ N, 162°06′ W, or over 2100Km (1300 miles) outside the study area. On a similar basis, Rarotunga in the Cook Islands (for which there are two separate coral proxy studies), is listed as being at 21° S, 160° E. Again well within the study area. Wikipedia has the location at 21° 14′ 0″ S, 159° 47′ 0″ W, or about 2000Km (1250 miles) outside the study area. The error has occurred due to a table with columns headed “Lon (°E)”, and “Lat (°S). Along with the two ice core studies from Vostok Station, Antarctica (Over 3100km, 1900 miles south of 50° S) there are 5 of the 27 proxies that are significantly outside the region.

Temperature Reconstruction

Palmyra Atoll reconstruction is one of just three reconstructions that has any data before 1430. From the abstract, a conclusion was

The average reconstructed temperature anomaly in Australasia during A.D. 1238-1267, the warmest 30-year pre-instrumental period, is 0.09°C (±0.19°C) below 1961-1990 levels.

From the proxy matrix I have plotted the data.


This indicates a massive change in late twentieth century temperatures, with 1996 being the most extreme on record.

The other two data sets with pre-1430 data are tree ring proxies from Mount Read, Tasmania and Oroko, New Zealand. These I have plotted with a 30 year moving average, with the data point at the last year.


There is something not right with the Palmyra Atoll proxy. The late 20th century trend is far too extreme. In the next posting I will compare to some other coral data sets.