Esper et al (Global Change Biology, in press) “Trends and uncertainties in Siberian indicators of 20th century warming” is relevant to our present consideration of Briffa’s Yamal, which I will get to shortly. The cutline in their abstract declares in effect that the divergence problem is not as “bad as we thought”:
Despite these large uncertainties, instrumental and tree growth estimates for the entire 20th century warming interval match each other, to a degree previously not recognized, when care is taken to preserve long-term trends in the tree-ring data. We further show that careful examination of early temperature data and calibration of proxy timeseries over the full period of overlap with instrumental data are both necessary to properly estimate 20th century longterm changes and to avoid erroneous detection of post-1960 divergence.
However, it doesn’t seem to me that this is supported very convincingly by their data analysis. They analyze the (archived) Schweingruber to 1990-1991 plus a considerable number of recent measurements, all of which are unarchived – non-archiving seems to have become standard practice among Esper and Euro dendros. Esper et al also comment on the instrumental record, worrying about adjustments to a degree that would not be out of a place in a CA thread. Here are a few excerpts.
Here is an excerpt from Esper’s Figure 3, showing the effect of different standardization methods (Hugershoff, Negative Exponential, RCS and 300-year spline) on the average of over 70 chronologies. As you can readily see, on an overall basis, there is a decline in both RW and MXD for a very large population of Siberian sites since 1940 or so. Esper’s abstract and conclusions emphasize the fact that the post-1940 decline in the RCS version (red) is somewhat less than the post-1940 decline in the Hugershoff version (purple) – and also that the 19th century RCS rise is greater than the 19th century Hugershoff rise. However, in our consideration of Yamal, the slight difference in post-1940 decline is irrelevant: once again, the large population doesn’t show the huge Yamal rise. The issue, as stated on many occasions, isn’t just the “divergence” of Briffa’s Yamal chronology from Khadyta River, but its “divergence” from growth patterns throughout western Siberia – making one wonder about possible inhomogeneity in the Yamal population, an issue that I’ll return to.
Esper Fig. 3 Lower Panel Effect of tree-ring detrending… Lower panel shows the same arithmetic means (RCS) together with the mean timeseries derived from HUG, EXD, and SPL detrending. All timeseries were normalized over the 1881–1940 period. RCS, regional curve standardization; TRW, tree-ring width.
Esper specifically showed results from a “new” (and Euro-unarchived) west Siberian network, summarized in the next graphic. The “new” network ends up at a z-score in 2000 of almost exactly zero, while Briffa’s Yamal is exploring stratospheric multi-sigma deviations.
Esper Fig. 6. Updated WSIBnew tree-ring data and coherence with regional temperatures. Top panel shows the seven new MXD and eight new TRW RCS-detrended site chronologies together with their mean (WSIBnew) and the mean of all records in the WSIB clusters C1-3 (WSIB). While the latter extended only until 1990, WSIBnew reached 2000. Middle panel shows the WSIB and WSIBnew tree growth data scaled over the 1881–1990 (WSIB) and 1881–2000 (WSIBnew) periods to regional JJA temperatures. JJA and WSIB data have been decadally smoothed. Bottom panel shows the WSIBnew MXD and TRW timeseries together with JJA temperatures over the 1970–2000 period. Details on the updated WSIBnew sites, and all other tree-ring locations, are listed in supplementary Table S2. RCS, regional curve standardization; TRW, tree-ring width.
Esper also questions a variety of issues in the station histories, mentioning UHI, regional inhomogeneity in adjustment practices (see the Discussion and Conclusion for these) and GHCN adjustments. On regional adjustment to temperature records, they say:
In addition, the homogenization methodologies currently applied particularly in large-scale approaches, have difficulties in identifying and correcting for systematic biases that simultaneously affect data across larger regions (Parker, 1994; Frank et al., 2007a; Thompson et al., 2008). If we, for example, consider the substantial changes of instrumental summer temperatures that were recently applied to early station data in Europe and elsewhere (see both Frank et al., 2007a; Bohm et al., 2009, and references therein), it appears premature to solely use early temperature readings for proxy transfer and evaluation of DP in remote high latitude regions
The top panel below shows a graphic displaying GHCN adjustments of the sort that I did here a couple of years ago in connection with Hansen’s Y2K problem, emphasizing that the adjustments are as large or larger than the temperature changes being measured (a familiar CA point.) In the caption to the bottom panel, he says: “Negative deviations were inverted, combined with positive values, and decadally averaged.” I don’t understand the purpose of this procedure and had enough needles in my eyes for a while.
Esper Fig. 8 Differences between raw and adjusted (GHCN) temperature station records. Upper panel shows the single June, July, and August adjustments of all 13 Siberian stations and their mean timeseries (bold). In the lower panel the adjustments were averaged to mean JJA mean timeseries and sorted by stations in WSIB, ESIB, and NESIB. Negative deviations were inverted, combined with positive values, and decadally averaged. Ust is Ust’-Maja, Sur is Surgut, and Dud is Dudinka (see Table S3).
For our present consideration of Yamal, the evidence from the Esper networks in western Siberia is one of declining ring widths in the last half of the 20th century. Briffa’s Yamal is an exception to this general pattern – a point that is not discussed or reconciled in Briffa’s response thus far. Esper cautions in respect to RCS standardization:
It seems important to note, however, that RCS-detrended data generally contain greatest uncertainties, require large datasets, and are prone to biases caused by inhomogeneous sample collections (Esper et al., 2002, 2003a). Particularly relevant to the Siberian data analyzed here could be biases due to (i) the tendency that the oldest trees often grow most slowly (Melvin, 2004; Esper et al., 2007b; Wunder et al., 2008), and (ii) the composition of data from only living trees and relatively homogeneous age-structure (Esper et al., 2007a, 2009). The former bias is likely more relevant for TRW than MXD – because of the greater amount of variance contained by the agetrend (Schweingruber et al., 1979) – and would ultimately increase positive long-term trends in RCS chronologies.
In his response, Briffa made no effort to defend the methodology of the original Yamal chronology beyond declaring that it was done in good faith, instead moving on to argue that they can “get” a similar chronology from a somewhat larger data set, as presented last week. The most important issue – as stated here and elsewhere by Esper – is the potential “bias caused by inhomogeneous sample collections”, an issue that I’ll consider in connection with the new Yamal data in a forthcoming post.