cc: John.Lanzante@noaa.gov, "Thomas.R.Karl" , carl mears , "David C. Bader" , "'Dian J. Seidel'" , "'Francis W. Zwiers'" , Frank Wentz , Karl Taylor , Melissa Free , "Michael C. MacCracken" , "'Philip D. Jones'" , Sherwood Steven , Steve Klein , 'Susan Solomon' , "Thorne, Peter" , Tim Osborn , Tom Wigley date: Fri, 28 Dec 2007 16:14:10 -0800 from: Ben Santer subject: Re: [Fwd: sorry to take your time up, but really do need a scrub to: Leopold Haimberger Dear Leo, The Figure that you sent is extremely informative, and would be great to include in a response to Douglass et al. The Figure clearly illustrates that the "structural uncertainties" inherent in radiosonde-based estimates of tropospheric temperature change are much larger than Douglass et al. have claimed. This is an important point to make. Would it be possible to produce a version of this Figure showing results for the period 1979 to 1999 (the period that I've used for testing the significance of model-versus-observed trend differences) instead of 1979 to 2004? With best regards, and frohes Neues Jahr! Ben Leopold Haimberger wrote: > Dear all, > > I have attached a plot which summarizes the recent developments > concerning tropical radiosonde temperature datasets and which could be > a candidate to be included in a reply to Douglass et al. > It contains trend profiles from unadjusted radiosondes, HadAT2-adjusted > radiosondes, RAOBCORE (versions 1.2-1.4) adjusted radiosondes > and from radiosondes adjusted with a neighbor composite method (RICH) > that uses the break dates detected with RAOBCORE (v1.4) as metadata. > RAOBCORE v1.2,v1.3 are documented in Haimberger (2007), RAOBCORE v1.4 > and RICH are discussed in the manuscript I mentioned in my previous email. > Latitude range is 20S-20N, only time series with less than 24 months of > missing data are included. Spatial sampling of all curves is the same > except HadAT which contains less stations that meet the 24month > criterion. Sampling uncertainty of the trend curves is ca. > +/-0.1K/decade (95% percentiles estimated with bootstrap method). > > RAOBCORE v1.3,1.4 and RICH are results from ongoing research and warming > trends from radiosondes may still be underestimated. > The upper tropospheric warming maxima from RICH are even larger (up to > 0.35K/decade, not shown), if only radiosondes within the tropics > (20N-20S) are allowed as reference for adjustment of tropical radiosonde > temperatures. The pink/blue curves in the attached plot should therefore > not be regarded as upper bound of what may be achieved with plausible > choices of reference series for homogenization. > Please let me know your comments. > > I wish you a merry Christmas. > > With best regards > > Leo > > John Lanzante wrote: >> Ben, >> >> Perhaps a resampling test would be appropriate. The tests you have >> performed >> consist of pairing an observed time series (UAH or RSS MSU) with each one >> of 49 GCM times series from your "ensemble of opportunity". Significance >> of the difference between each pair of obs/GCM trends yields a certain >> number of "hits". >> >> To determine a baseline for judging how likely it would be to obtain the >> given number of hits one could perform a set of resampling trials by >> treating one of the ensemble members as a surrogate observation. For each >> trial, select at random one of the 49 GCM members to be the >> "observation". >> From the remaining 48 members draw a bootstrap sample of 49, and perform >> 49 tests, yielding a certain number of "hits". Repeat this many times to >> generate a distribution of "hits". >> >> The actual number of hits, based on the real observations could then be >> referenced to the Monte Carlo distribution to yield a probability that >> this >> could have occurred by chance. The basic idea is to see if the observed >> trend is inconsistent with the GCM ensemble of trends. >> >> There are a couple of additional tweaks that could be applied to your >> method. >> You are currently computing trends for each of the two time series in the >> pair and assessing the significance of their differences. Why not first >> create a difference time series and assess the significance of it's >> trend? >> The advantage of this is that you would reduce somewhat the >> autocorrelation >> in the time series and hence the effect of the "degrees of freedom" >> adjustment. Since the GCM runs are based on coupled model runs this >> differencing would help remove the common externally forced variability, >> but not internally forced variability, so the adjustment would still be >> needed. >> >> Another tweak would be to alter the significance level used to assess >> differences in trends. Currently you are using the 5% level, which yields >> only a small number of hits. If you made this less stringent you would >> get >> potentially more weaker hits. But it would all come out in the wash so to >> speak since the number of hits in the Monte Carlo simulations would >> increase >> as well. I suspect that increasing the number of expected hits would >> make the >> whole procedure more powerful/efficient in a statistical sense since you >> would no longer be dealing with a "rare event". In the current scheme, >> using >> a 5% level with 49 pairings you have an expected hit rate of 0.05 X 49 >> = 2.45. >> For example, if instead you used a 20% significance level you would >> have an >> expected hit rate of 0.20 X 49 = 9.8. >> >> I hope this helps. >> >> On an unrelated matter, I'm wondering a bit about the different >> versions of >> Leo's new radiosonde dataset (RAOBCORE). I was surprised to see that the >> latest version has considerably more tropospheric warming than I recalled >> from an earlier version that was written up in JCLI in 2007. I have a >> couple of questions that I'd like to ask Leo. One concern is that if >> we use >> the latest version of RAOBCORE is there a paper that we can reference -- >> if this is not in a peer-reviewed journal is there a paper in submission? >> The other question is: could you briefly comment on the differences in >> methodology used to generate the latest version of RAOBCORE as >> compared to the version used in JCLI 2007, and what/when/where did >> changes occur to >> yield a stronger warming trend? >> >> Best regards, >> >> ______John >> >> >> >> On Saturday 15 December 2007 12:21 pm, Thomas.R.Karl wrote: >> >>> Thanks Ben, >>> >>> You have the makings of a nice article. >>> >>> I note that we would expect to 10 cases that are significantly >>> different by chance (based on the 196 tests at the .05 sig level). >>> You found 3. With appropriately corrected Leopold I suspect you will >>> find there is indeed stat sig. similar trends incl. amplification. >>> Setting up the statistical testing should be interesting with this >>> many combinations. >>> >>> Regards, Tom >>> >> >> > -- ---------------------------------------------------------------------------- Benjamin D. Santer Program for Climate Model Diagnosis and Intercomparison Lawrence Livermore National Laboratory P.O. Box 808, Mail Stop L-103 Livermore, CA 94550, U.S.A. Tel: (925) 422-2486 FAX: (925) 422-7675 email: santer1@llnl.gov ----------------------------------------------------------------------------