date: Tue May 3 11:04:19 2005 from: Tim Osborn subject: Fwd: 2005JD005799 Decision Letter to: Craig Wallace Not good news on our JGR paper. I've only scanned them so far - rev2 is good, rev3 is biased because he/she doesn't see the point of pattern scaling, but rev1 makes some valid criticisms. We need to read these in detail and decide what can be done. Tim X-Mailer: MIME::Lite 3.01 (F2.6; B2.11; Q2.03) Date: Mon, 2 May 2005 18:56:53 UT To: t.osborn@uea.ac.uk Subject: 2005JD005799 Decision Letter From: jgr-atmospheres@agu.org Reply-To: jgr-atmospheres@agu.org X-Spam-Score: 0.2 X-Spam-Level: / Content-Disposition: inline Content-Length: 6317 Content-Transfer-Encoding: binary Content-Type: text/plain Dear Dr. Osborn: Enclosed please find 3 evaluations on your manuscript entitled "Linear and exponential relationships between global temperature change and patterns of precipitation change" [Paper #2005JD005799]. After careful consideration, based on the reviewers' recommendations of your manuscript, I am sorry to inform you that I have decided to reject it for publication in the Journal of Geophysical Research - Atmospheres. If you wish to resubmit this paper, please note that you will need to send a point-by-point response to all of the reviewer's criticisms. In this case, your manuscript will then be treated as a new submission. I am sorry I cannot be more positive. Sincerely, Ruth Lieberman Editor, JGR-Atmospheres ------------------------------------------------------------------------------ Reviewer #1 Evaluations: Assessment: Category 5 Ranking: Select one Annotated Manuscript: No Reviewer #1(Comments): Though this paper is one if the best-written papers I have received for review lately, I must recommend that this paper NOT be accepted for the following reasons: The data in the paper do not support the authors' conclusion that the mixed scaling "replicates GCM data better", there is no attempt at cross-validation, there is no physical basis for the curve-fit, and in fact it is logically inconsistent, and finally, the metrics of goodness-of-fit given here are weak. I addresss each of these points in more detail below, and finish with some techincal points. However, the authors did convince me that an improvement on linear extrapolation would be useful, as well as of the need to develop better metrics. Their method, and this paper fall short, however. Everything presented in this paper is a fit to data, with no cross-validation. That is, the authors do not do not address the problem of extrapolation. Yet this is critical for the applications of this technique. For example, they could have trained the fit on delta-T up to 1K and then "predicted" the higher values. This is purely an exercise in curve fitting. There is no physical basis other than that p>0. To get an idea of the pitfalls of this approach, consider the following thought experiment: Suppose we had run the GCM experiments in reverse -- starting with high values of global temperatures and decreasing GHGs, and suppose that the GCM's followed the same trajectory down the GHG curve as they did up. Where precipitation increased in the "normal" set of runs it would decrease in the "reversed" set. According to the logic of this paper, you would fit the curve with a linear function in the first case and with an exponential in the second case. Yet it would be the same data that you are fitting in two different ways! Their conclusion that the mixed linear-exponential model can " replicate GCM data better" is not supported by the evidence in this paper. The performance of the mixed model was at best...mixed. It depended on the GCM, and even then it depended in an unpredictable way on the actual temperature change. I quote: "Given the clear curvature of local precipitation changes (with respect to global temperature) for HadCM3, it is surprising that the global-mean precipitation is quite linearly related to delta-T, and the exponential and mixed functions are not as food fits as the linear function. For the NCAR PCM model, the slight curvature of the global precipitation-temperature relationship is reasonably captured by the mixed function for delta-T < 1.4K, and by the exponential function for delta-T > 1.6K, but the linear sclaing is a poor fit throughout." Clearly the fit doesn't work for one model, and for another it is dependent on the temperature change in an unpredictable way. No overall metric of goodness of fit - such as mean-square error - is presented. Only "extremes" of drying and wetting -- a small percentage of the globe-- and global-mean precipitation (a weak metric that hits method doesn't really do well at) are looked at. Since the mixed functional fit is "worse" for the HadCM3 globally, then there must be many local regions where their fit is not good at all. Technical points: The method is not documented clearly enough to reproduce. In the title, abstract and in the text clearly state where this temperature is being measured. Is it surface air temperature, surface temperature, or some other measure of global mean temperature? p<6mm/mon (0.2mm/day) ignored. What is the impact of this? Why was this done? If the attempt is to get better scaling for extremes then why exclude the dryest areas? 50 year sliding boxcar(?) window means that the samples used in the fits are not independent. The SRES A2 scenario extends out to the year 2100 -- so there are 3 (1950 - 2100) independent samples. I am not sure whether they have taken this into account in their statistical test if Figure 1. The authors do not mention the length of the runs that they used. Reviewer #2 Evaluations: Assessment: Category 2 Ranking: Very Good Annotated Manuscript: No Reviewer #2(Comments): Review of "Linear and exponential relationships between global temperature change and patterns of precipitation changes" by Osborn and Wallace. This is a well-written, succinct paper that makes some useful points relevant to scaling patterns of precipitation change, and I recommend its publication almost without change. The only changes that I suggest are: 1. ON page 1,line 4, I find it stylistically better to say, "the rate of precipitation decrease tends to decrease .... " 2. On page 2, lines 11-12, I would write, "or WHEN the regional pattern of sulphate aerosol forcing changes through time [ ], although for some models the regional temperature response to aerosol forcing is governed by the pattern of climate feedbacks triggered by overall warming, rather than by the forcing pattern [Harvey, 2004] 3. Page 4, 2nd last line, I find it stylistically better to say, "with a decreasing rate of change ...." Reference: Harvey, L.D.D. 2004. Characterizing the annual-mean climatic effect of anthropogenic CO2 and aerosol emissions in eight coupled atmosphere-ocean GCMs. Climate Dynamics 23: 569-599. Reviewer #3 Evaluations: Assessment: Category 5 Ranking: Poor Annotated Manuscript: No