Climate Audit

Climate scientists didn't bother checking the Hockey Stick, but they are showing great diligence in going through The Great Global Warming Swindle.

Nathan Rive is the newest entrant; he has cross-checked one of the graphics in Swindle against the original graphic in Lassen and Friis-Christensen and found a discrepancy between the graphic and the original article. BTW I obviously endorse such cross-checking. I focus on the studies cited by IPCC simply because I have limited time and resources, but it's a good idea to cross-check Swindle or Inconvenient Truth (which I've spent relatively little time on).

Rive observes a divergence problem in the solar cycle correlations. I agree that divergence in these sorts of studies is a serious problem as do most CA readers. So I hope that Rive will spend some time with the more serious divergence problem in proxy studies. Read the rest of this entry »

Al Gore's hockey stick version (page 65 of the book "An Inconvenient Truth") is taken from one of the many conflicting versions of Lonnie Thompson's ice core data. Now there is an ongoing controversy about whether Thompson's data is a temperature or precipitation proxy, with pretty much every other scientist except Thompson now viewing the data as more of a precipitation proxy.

There's an interesting and symptomatic change in IPCC wording between the Second Draft and the Final Report, which has the effect of bringing the language more in line with Al Gore.

Here's what Al Gore said:

Nevertheless the so-called global-warming skeptics often say that global warming is really an illusion reflecting nature's cyclical fluctuations. To support this view they frequently refer to the Medieval Warm Period. But as Dr Thompson's thermometer shows, the vaunted Medieval Warm Period (the third little blip from the left below) was tiny compared with the enormous increases in temperature of the last half-century (the red peaks at the far right of the chart).

Those global warming skeptics - a group diminishing almost as rapidly as the mountain glaciers - launched a fierce attack against another measurement of the 1000 year correlation between CO2 and temperature known as the "hockey stick", a grpahic image representing the research of climate scientist Michael Mann and his collegatues. But in fact scientists have confirmed the same basic conclusions in multiple ways - with Thompson's ice core record as one of the most definitive.

Here's an attempt at replicating the graphic in Inconvenient Truth (using the decadal version from Thompson's Climatic Change 2003 article, but as discussed elsewhere, there are many versions of Thompson's data floating around and Thompson has refused to provide sample data to disentangle the mess).

IPCC on Tropical Glaciers

The IPCC has come down on the side that Thompson's ice core data is a precipitation proxy as follows:

Stable isotope data from high-elevation ice cores provide long records and have been interpreted in terms of past temperature variability (Thompson, 2000), but recent calibration and modelling studies, in South America and southern Tibet (Hoffmann et al., 2003; Vuille and Werner, 2005; Vuille et al., 2005), indicate a dominant sensitivity to precipitation changes, at least on seasonal to decadal timescales, in these regions.

Where is the Dendro Truth Squad when we need them? Do you think that they can do ice cores as well? Based on the IPCC, Al Gore's Hockey Stick is simply showing that there is increased precipitation in the 20th century in high altitudes. Of course the increased precipitation may be due to increased warming, but this interpretation of the Thompson ice cores tends to undercut the dire warnings of drought that crop up elsewhere. In the Second Draft, the IPCC continued on, observing that "apparently unprecedented" glacier decline was "possibly" associated with enhanced warming at high altitudes and that other factors besides temperature "can strongly influence" tropical glacier retreat.

Very rapid and apparently unprecedented melting of tropical ice caps has been observed in recent decades (Thompson et al., 2000; Thompson, 2001) (see Box 6.3), possibly associated with enhanced warming at high elevations (Gaffen et al., 2000), but other factors besides temperature can strongly influence tropical glacier mass balance (see Chapter 3).

The unqualified use of "unprecedented" - this could almost be an article in Nature - is an annoying habit that makes climate scientists sound like Creationists. Memo to climate scientists: the earth is more than 4200 years old. There is strong evidence that the Quelccaya glacier is less than 4200 years old and, in my opinion, the evidence for the existence of the Kilimanjaro and Mt Kenya glacier in the Holocene Optimum is virtually non-existent.

Comparing this sentence to the final version, we see that "possibly" has been changed to "likely" and the statement that other factors could affect glacier balance has been removed.

Very rapid and apparently unprecedented melting of tropical ice caps has been observed in recent decades (Thompson et al., 2000; Thompson, 2001; see Box 6.3), likely associated with enhanced warming at high elevations (Gaffen et al., 2000; see Chapter 4).

I haven't seen the version of AR4 that was used in the SPM, so I don't know whether these changes were made before the SPM or after the SPM. It would be nice to know if this particular change was made so that the Report conformed to the SPM or not.

Stable isotope data from high-elevation ice cores provide long records and have been interpreted in terms of past temperature variability (Thompson, 2000), but recent calibration and modelling studies, in South America and southern Tibet (Hoffmann et al., 2003; Vuille and Werner, 2005; Vuille et al., 2005), indicate a dominant sensitivity to precipitation changes, at least on seasonal to decadal timescales, in these regions. Very rapid and apparently unprecedented melting of tropical ice caps has been observed in recent decades (Thompson et al., 2000; Thompson, 2001) (see Box 6.3), possibly associated with enhanced warming at high elevations (Gaffen et al., 2000), but other factors besides temperature can strongly influence tropical glacier mass balance (see Chapter 3).

IPCC AR4 is online - thanks to readers for pointing this out. I didn't notice any press releases or hoopla. The lead author for the millennial paleoclimate section was Keith Briffa, who takes a realclimate line on the debate - surprise, surprise. Their comments on M&M are pretty much the same as in the Second Draft - they essentially disregarded the comments by Ross and myself, even on what we are supposed to have said. The Team features prominently in the chapter - a search on Mann turns up 92 mentions; Briffa 36 mentions; Jones 36 mentions;

Like Mann before him, Briffa used his position as Lead Author to publicize his own work - I don't know whether this sort of behavior is prevalent in other chapters, but it's something that is a risk when authors are parties to controversy, something that I and others (von Storch) criticized in the past. The spaghetti graph in Box 6.4 of Chapter 6 here is taken from the series in Osborn and Briffa 2006. Curiously, although these are exactly the series in Osborn and Briffa 2006, they do not mention this article, instead attributing the series to "proxy records collated from those used by Mann and Jones (2003), Esper et al. (2002) and Luckman and Wilson (2005)". If you look closely at the right hand side and I'll discuss this further, you can see a few proxy-series that peak in mid-century and close at low levels (the Divergence Problem) and a few that close at high values - the high closers are Mann's PC1 - which, despite all the publicity, reappears here bold as brass, a foxtail series and Yamal, like aged streetwalkers with too much mascara.

Box 6.4, Figure 1. The heterogeneous nature of climate during the ‘Medieval Warm Period’ is illustrated by the wide spread of values exhibited by the individual records that have been used to reconstruct NH mean temperature. These consist of individual, or small regional averages of, proxy records collated from those used by Mann and Jones (2003), Esper et al. (2002) and Luckman and Wilson (2005), but exclude shorter series or those with no evidence of sensitivity to local temperature. These records have not been calibrated here, but each has been smoothed with a 20-year filter and scaled to have zero mean and unit standard deviation over the period 1001 to 1980.

Update: This spaghetti graph is changed from the version in the Second Draft. Here's a replication using data from Osborn and Briffa 2006. The two series with high closing values are Mann's PC1 (innocuously called "W USA" by Briffa to distract attention from what it is) and Briffa's version of the Yamal series. The two series which close below the long-term mean are: Fisher's west Greenland composite (which essentially functions like white noise in a reconstruction) and Taimyr. The 4 series with intermediately high closes are: the Yang composite which uses among other things Dulan junipers and Thompson's Dunde and Guliya ice core data (or at least one of the many versions of each); Jacoby's Mongolia series; Tornetrask and Rob Wilson's Jasper reconstruction. All these series have been discussed at length on previous occasions.

To show the PC1 and Yamal series, I've re-plotted this with the Mann PC1 in thick red; Yamal in thin red and other series in light grey. You can see that the rhetorical effect of this diagram depends strongly on these two series. In addition to the discussion of the Mann PC1, Briffa's substitution of the Yamal series for the Polar Urals update has been discussed before.

The series that have been dropped from the illustration in the Second Draft (which were used in Osborn and Briffa 2006) are plotted below. There are 2 series with high closing: foxtails (which grow about 20 miles from the dominant bristlecone site, Sheep Mountain); the short van Engelen documentary series (which is not a "proxy" in the sense that tree rings are a proxy); one series with a slight positive close ( Tirol) and 3 series with negative closings (Chesapeake; Quebec and Mangazeja).

A couple of interesting references and comments on the Cardwell site were sine int. Let's focus on Cardwell and its neighbours a little. Read the rest of this entry »

Yesterday, in a spot check, we observed that Torok and Nicholls had acknowledged a substantial inhomogeneity in the Low Head lighthouse series, used in Jones et al 1990. Given this problem in one of the 49 series, this begs the question of what the other 48 series look like. Here are quite a few plots of individual stations plus some spaghetti graphs. Read the rest of this entry »

Low Head is not a manouevre at a Hollywood party or a physical description of the gnomes of Norwich (the location of CRU), but a lighthouse in Tasmania, which John Daly photographed and brought to the attention of Neil Plummer, who had used it in Jones et al 1990. Plummer wrote back to Daly that the inhomogeneity had been taken into consideration in their revised data in Torok and Nichols. Well, was it? Read the rest of this entry »

Jones said that the names of the Australian sites was unknown. However it turned out that the names of these locations are known to mankind and, with a little effort, that the names of these sites could be tracked down from an Australian reference list through the CSIRO reference numbers at the Jones site. My first pass at finding original data for these sites online at CSIRO proved unsuccessful, although the opportunity for purchasing the data from CSIRO is available.

However, an interesting trove of historical information archived here in 1996 turned up. This proved to be the "high quality" network from Torok and Nicholls 1996, that was mentioned in the correspondence between John Daly and Neil Plummer of CSIRO in 1996. That was the letter in which Plummer responded to Daly's criticism of inhomogeneity at Low Head Lighthouse by saying that Jones et al 1990 made no claim that its stations had been assessed for homogeneity (foolish reader to assume that!) The Maatsuyker lighthouse is mentioned in the Low Head discussion. This post is not just about the Maatsuyker exclusion in the Torok network, but I sort of liked the phrase - it sounds to me like the title of an action novel. Read the rest of this entry »

I'm posting up another script for unzipping a file in R (in part so that I can keep track of this things as well.) I'm trying to figure out how to download the Australian data in R and reviewing some prior successful efforts (which have relied on Nicholas).

Here is how one can get at the NOAA gridded data directly from R. First download the file to a temporary location. I'm not sure what mode="wb" does, but it's something you have to do.

download.file("ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/anom/anom-grid2-1880-current.dat.gz", "anom-grid2-1880-current.dat.gz",mode="wb");

The following will get it into an ASCII file. The unzipping of the Russian meteo script uses the scan function; here readLines works. The file Data is something that can be handled with ordinary techniques.

handle < - gzfile("anom-grid2-1880-current.dat.gz");
Data <- readLines(handle);
close(handle);
length(Data) # 331359

In this case, the data comes out as 12 values per line; 217 lines per month-year combination. There are (217-1)*12=2592 = 72*36 gridcell values. There are 331142 lines in the file currently. The data comes out as latitude in the hour hand (N to S in 5 degree increments) and longitude as the minute hand (W to E from the Dateline in 5 degree increments). To make a collated version of time series with gridcells in each column in the same hour hand-minute hand order (which I try to use consistently), I first identify and remove the 1, 217, … lines with month-year information and then transform the data through matrix operations.

N< -length(Data);N
temp<-!is.na(match(1:N,seq(1,N-216,217)))
Data<-Data[!temp]# 329616
noaa<-cbind(as.numeric(substr(Data,1,6)), as.numeric(substr(Data,7,12)),as.numeric(substr(Data,13,18)),as.numeric(substr(Data,19,24)), as.numeric(substr(Data,25,30)), as.numeric(substr(Data,31,36)),as.numeric(substr(Data,37,42)),as.numeric(substr(Data,43,48)),as.numeric(substr(Data,49,54)), as.numeric(substr(Data,55,60)),as.numeric(substr(Data,61,66)),as.numeric(substr(Data,67,72)) )
rm(Data)
temp<-(noaa== -32768);noaa[temp]<-NA
dim(noaa) #329616 12
# 329616*12/2592 =1526
noaa<- c(t(noaa))
noaa<-array(noaa,dim=c(2592,length(noaa)/2592 ) );dim(noaa)# 2592 1526
noaa<-t(noaa) #1526 2592
#save(noaa,file="d:/climate/data/noaa/noaa.tab")

Nicholas also looked recently at *.Z files, which he described as an obsolete compression format, not supported at present in R. It is used in some climate data sets e.g. cdiac.ornl.gov/ftp/tr055/sta60.dat.Z. Nicholas wrote a routine which he said is slow and which I haven't tried yet. If it's a one-off analysis, it's easy enough to download and unzip manually. The need for automated unzipping occurs when the data is updated or if you need to call individual stations. I'll revisit the *.Z files if and when I get to this situation.

There are a couple of BOM files at ftp.bom.gov.au/anon/home/bmrc/perm/climate/temperature/annual. As an exercise, I tried to see if I could modify Nicholas' methods to unzip this data in R, but so far have been unsuccessful. I'm sure that Nicholas will have an answer.

We've talked about Phil Jones' Russian and Chinese sites, where we've just scratched the surface so far. Warwick Hughes took a first crack at some years ago, but was unsuccessful in identifying the Jones sites. Jones, never making things easy, did not provide the names of any of the Australian sites, nor the WMO identification numbers. However, from the information that he did provide, I've scratched together names for the various sites and WMO identifications. Jones has said that he has no information on how the sites were selected.

To be fair, many of them have rural-looking descriptors and it looks as though a genuine effort was made here to avoid cities. Australians may be able to comment on further. I haven't compared this listing to Warwick's prior efforts.
Read the rest of this entry »

per inquired recently about obtaining a copy of Gerry North's presentation to the newly minted NAS Panel on Assuring the Integrity of Research Data, which held its first hearings last week. Gerry North was appropriately the first speaker, as the new panel was occasioned by problems left unanswered by the North panel, although its terms of reference are much broader. The North presentation is here. Some background and thoughts follow. Read the rest of this entry »

Willis writes in with latest FOI refusal from CRU, saying that they are unable to provide a list of the sites used in HadCRU3. Read the rest of this entry »

Continuation of Unthreaded #8