cc: Anders Moberg , Anders , Eduardo.Zorita@gkss.de, esper@wsl.ch, k.briffa@uea.ac.uk, m.allen1@physics.ox.ac.uk, weber@knmi.nl, t.osborn@uea.ac.uk date: Tue, 15 Aug 2006 20:21:50 -0400 from: Gabi Hegerl subject: Re: Figure 5, plus "executive summary" to: Martin Juckes Hi all, First, many apologies for being so late!! (There is this four letter word thats taking lots more of my time than I anticipated... sorry...) Martin, I just crosschecked your email and realized that you wanted this this morning... sorry.... This is very very nice and useful paper, and I really enjoyed reading the MM vs MBH discussion and really liked it. There are some things though that I am worried about that refer more to the other techniques than MBH, the comparison figure, and IPCC. A lot of it is quite self serving, sorry for that, becuase of time constraints, I plowed particularly into segments referring to IPCC or my stuff... sorry for that! The one aspect I worry about is that in figure 1, the CH-blend (cited as hegerl et al., Tom would prefer calling it CH-blend because he is the main recon guy, I am just calibrating and detecting - but ok either way) does not look the same as in our figure in the paper (figure 2). Also, there is several versions, 3 segments of different length, all using same amount of data, for land only, 30-90N, and 2 for land and ocean. I am not sure which one you use, the one you show may be the land and ocean one, while the one our figure 2 shows is the land only. I am happy showing either one, it would be nice to use the full length, you can just use the "long" version before the regular version starts. However, the comparison shown in figure 1 is a bit misleading then, since there are reconstructions for land only extratropics (eg the boreholes) plotted into reconstrucitons of land and ocean all NH (eg Moberg), and all kinds of things in between (Briffa 2001 I think is growing season land only, for example). I think this is ok if its explained, but without explanation gives a misleading idea of the level of disagreement. The boreholes for example are if compared over the same time and space domains consistent with CH-blend (and probably other high-variance recons too) but this is not clear from the comparison in the figure. This could be clarified by labelling what the different reconstructions represent, and adding a sentence to both caption and text discussing it that says that part of the difference in amplitude is due to the difference in the physical domain reconstructed. I am also not quite sure what the reconstruction you show further down (Union etc) does represent, is it 0-90N land and ocean? Another minor worry is that the discussion of reconstruction methods other than MBH gives different results from other work I am aware of, and I think it may be partly due to what exactly is done. For example, the total least squares approach is very similar to the inverse regression approach, and can work pretty nice, at least does in my paper and another work I heard about. I tried inverse regression, too, and its very similar to total least square, and worked very nice for me unless I tried calibrating the records to local temps using it. I think the one used here (please bear with me if I didnt read this careful enough!! sorry in taht case, I was trying to sneak this in between IPCC stuff, final draft deadline approaching phew...) may not be exactly the same as one that only calibrates a (weighted or not) average of the paleo records "paleo" to the hemispheric mean using inverse ols by saying paleo = beta * instrumental + noise, and then using 1/beta. If I am right here, it would be good to say so, if not, then maybe it could be made a bit clearer. Tls might also be mentioned as the case where noise in both is equally considered, but the prize is more estimates / assumptions. If you feel like trying out something, I would find it really interesting to try using inverse regression and variance matching in comparison for going from the composite to the final reconstruction scaled to temperature. This is where in my view tls or inverse regression is nice, since it does not assume that the proxy based composite has the same amount of noise as instrumental data, although the latter are much more tightly sampled and have much less non-temperature variability etc superimposed, all reasons to think that they would have lots less error. On the other hand, it could be that the errors are small relative to the variability in temperature, in which case both would perform similarly. The assumption that the proxy timeseries should jiggle a little bit about the (less noisy) instrumental timeseries due to its extra noise variance seems like a good one to me... But doing or not doing this is totally up to you! So specifically to executive summaryES text sent out about a week ago: 1. The first page after "perturb our climate": It may be good to add there something like: Also, conclusions of the IPCC report (IPCC, 2001) that "most of the observed warming over the last 50 years is likely to have been due to the increase in greenhouse gas concentrations” were based nearly entirely on studies analyzing the instrumental record and distinguishing and estimating the signature of temperature response to greenhouse gas forcing. Therefore, this conclusion is not affected by uncertainties in reconstruction techniques and data (Mitchell et al., 2001). Mitchell, J.F.B., D.J. Karoly, G.C. Hegerl, F.W. Zwiers, and J. Marengo, 2001: Detection of climate change and attribution of causes. In: Climate Change 2001. The Scientific Basis. The Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. [J.T. Houghton, et al. (eds.)]. Cambridge University Press, New York, NY, USA, pp. 695-738 The reason to add this would be that some part of this debate is trying to sink all conclusions about greenhouse warming with the hockeystick, which is a total stretch since the hockeystick doesnt contribute that much to that conclusion at all! Actually, nearly nothing! 2. Section 5 of ES: Are these techniques known in exactly the form they are used here? It looks like the technique known as inverse ols uses a scaling factor that varies from proxy series to proxy series, and I suspect that the usefulness of that technique depends very strongly on how its done. It will do poorly if there is lots of noise (like i tried calibration of local records to temperature) and will be better if there is high correlation (eg if there is already some proxy reconstruction that just needs to be matched to the instrumental in amplitude, as in my paper, in otehr words, if instead of variance matching, tls or inverse ols would be done). So can we qualify the end of the first para of section 5 ES by saying using two techniques of different complexity, The simpler method is known as "Composite... matching", is widely used and gives robust results. The second method is based on inverse regression. Here, the reconstruction and its amplitude is determined using this method, and this variant of inverse regression is found to be sensitive to give less robust results than C...M. This sensitivity is less important if there is relatively good correlation between the target and the reconstruction timeseries, and in those cases it has been shown to work well. In cases where the amount of sampling and random noise on proxy data is substantially larger than on instrumental data, inverse regression produces more reliable amplitude estimates for the reconstruction, which can be important if the amplitude of externally forced signals in proxy reconstructions are used, for example, to estimate climate sensitivity. (Last sentence is just a suggestion!) 3. Last section of last page in ES: I am not quite sure what the little hitch about climate sensitivity is saying, but a certain nature paepr that came out in April (sorry self serving) showed that indeed the constraints from data for the last few hundred years alone provide quite wide pdfs of climate sensitivity. (Hegerl et al, nature, see J Climate paper for reference). If this information is combined with (also wide) pdfs for instrumental data, where the problen is the poorly known ocean heat uptake etc, our understanding of climate sensitivity can narrow a bit. But thats not necessary to say here unless you want, it may be a nice pitch for paleo to say taht if instrumental estimates are combined with those from proxy data, climate sensitivities outside the IPCC range of 1.5 to 4.5 become substantially less likely. One could also add that a further interest for the proxy reconstructions arises because the detection of greenhouse warming depends on model estimates of climate natural variability. Recent simulations of climate variability in the last few millennia are generally in agreement with reconstructions (e.g., Tett et al., others - can find) and suggest that the level of natural variability produced by climate models is reasonable (see also Zorita et al., Hegerl et al., 2006b JCLimate paper). MAIN PAPER (long version, very early August): Abstract: see point 2 above, can this also qualify the inverse regression a bit referring to one particular variant tested here? p.3, see above suggestion 1, would be a good place to add this after the first paragraph (...beyond dispute.) p. 3, beginning of 3rd paragraph: Not sure I understand this! p.4, beginning of last paragraph: HCA is not 0-90N, there is one version tahts 30-90N, and one thats 30-90N land. I am not srue if ECS is 0-90, I was under the impression its also extratropical - do you use the cook-scaled version? p. 6, footnote: I don't agree with the pitch for confidence level vs likelyhood. The overall, expert assessment of the likelyhood that something is true like the 90ies are the warmest period in the millennium, includes both an assessment of the robustness of the method, and of remaining uncertainties. Confidence stuff is still not much used in 4AR drafts at least of my chapter, we tried to use in one case and reviewers didnt like it much. Also, there could be the very confusing result of something being "very likely" true with low confidence (which may well be what you'd conclude from some paleo stuff), which is just confusing. So teh expert assessment is supposed to try to account for all remaining uncertainties. p. 12: Wasn't there a detrending issue with Zorita et al, vs MBH? p. 13, end of first para: If you want, you could add after "under the assumption that the instrumental noise is known" the method then accounts for the uncetainty due to unknown noise in proxy data. (this is something taht not many seem to catch, so I try pitching in for it :) p. 14, detection stuff: We do multiregression, not correlations alone, and we use response to forcings as determined by an Energy Balance Model. (this is important to me, volcanic forcing wouldnt correlate very well with response). So say Hegerl et al. (2003, 2006b) use a multiregression detection and attribution method to determine the fingerprints of temperature response to solar, volcanic and greenhouse gas forcing in a variety of reconstrucitons. They find... variance, namely more than 50% of the decadal variance in all records explored. I need to check what Nanne did, but I think it was a bit different, I remember it was a nice paper. P15, end of first paragraph: This might be a nice place to refer to Osborne et al., nature, for the unusualness of the overall pattern of warming in the proxy records. p. 16, top: Is the IPCC stuff that is referred to the finding that the nineties are unusual, or that most of the observed warming... greenhouse gases? I think the sceptics are (maybe on purpose) murky about this, so we should be very clear and separate between which finding is dicussed. So maybe recite here? p. 18, 2nd last before section 4: typo, remove "and". p. 21, top: Moberg et al., I THINK also find that the time around 16 was colder than the early 19th, and CH-blend suggests that also, although less clearly p. 22, 2nd paragraph from bottom: Its fascinating that union has more variance than the others - is there any explanation available? Its really interesting! This would also be a good place to crossreference that the INVR approach used here is one realization of many possible ways of doing inverse regression. table 3 should get a qualifyer that CH-blend is an outlier because of its lower (decadal) resolution. If possble, it would be nice to explicitly mention it as a reconstruction that uses the same number of records throughout (at least the individual segments from it are). p. 25, 2nd line: "this" reconstruciton is Union, right? Greetings, I'd be happy to more thoroughly read this again, if you want to - if already submitted, maybe we can fix thse things later.. Gabi Martin Juckes wrote: >As Anders pointed out, one curve is not visible in figure 5 -- this is because >it is virtually indistinguishable from others: a better version of the figure >is attached. I'll also modify the caption to give a more complete description >of how each curve is generated. > >Also attached is an "Executive Summary" for the Netherlands Environment >Assessment Agency. This is still a little rough in places, but any views on >the opinions expressed and general layout would be welcome. > >cheers, >Martin > -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Gabriele Hegerl Division of Earth and Ocean Sciences, Nicholas School for the Environment and Earth Sciences, Box 90227 Duke University, Durham NC 27708 Ph: 919 684 6167, fax 684 5833 email: hegerl@duke.edu, http://www.env.duke.edu/faculty/bios/hegerl.html