cc: i.harris@uea.ac.uk, "Tett, Simon" date: Tue Aug 30 11:25:59 2005 from: Phil Jones subject: Fwd: sorry about this review to: "Brohan, Philip" , "Kennedy, John" Philip, I had a more detailed look at the comments over the long weekend. Here are a few thoughts. 1. If you want to know more about the structural uncertainty, that Tom P. is talking about, then talk to either Peter Thorne or David Parker. This term seems to have become widespread with the CCSP meetings on the lower tropospheric/surface temperatures differences. Basically, it is that errors don't include the effects of assumptions made in the dataset construction. So, when you get new or modified data, such as the revised SST data around WW2, the new data shouldn't change things more than the earlier error estimates - if these were correct. 2. It would seem that the error bars appear too small for SST. I said after the quick read, that I didn't think any more work is needed, but I think you are going to have to add two things. First, it will be necessary to produce HadCRUT3v a different way (the old HadCRUT2v way) of merging the land and marine components - just to show that it makes very little difference. Second, some comparison of the Smith and Reynolds dataset and its error bars will have to be included. The problem you'll find with SR, is that they have infilled data everywhere, so their long-term trends are smaller, because the infilling is mostly with near zero values, so the 1880-1920 period is warmer wrt 1961-90 than it should be. As for Tom's points His 4 is a good point. 6 will just need some additional words. This might need a sentence saying how few stations these less good means relate to. 7 is mostly secondary points that won't be that important. r-bar isn't calculated the way Tom thinks or maybe the paper implies. If you look back and re-read Jones et al. (1997) you'll see that r-bar is estimated from the earlier grid-box dataset. Probably just needs a few extra sentences. 8. Is a reasonable point, but this will likely make the error bars smaller? 9. I agree on this ! 10. If you compare with the old method merging this will show that this isn't that important. All that seems to be required is some more detailed explanation. The reason SST's appear better is that the autcorrelation from day-to-day and measurement- to-measurement is high (much higher than land). 11. A model could also be used to demonstrate this. Better than NCEP/NCAR. Minor Points A. My copy had these odd citations. There is an @ sign after each reference. Probably came about when making the pdf? B. WWR volumes for the 1991-2000 were not included. We've just received these last week. Haven't had time to add them in. Harry will likely do this but not till early next year, when we have some more funds for him. D. Good point E. More text needed, with a reference back. Maybe get David P to read through, if he hasn't already. F. We use anomalies G Good point. H. I thought I'd caught all these. I. This is a good point. It would be useful to say that there isn't a master dataset that we all draw from. We just use all we can get. This will answer N as well. I can write this. I have been in touch with Tom Peterson about this over the summer wrt Roger Pielke. J. Better explanation needed. K. These sd's differ though? P. Errors should be independent. Some rephrasing needed. Q. Agree that this needs to be clearer. S. More text needed. U. The recent periods are too short. May stations/countries haven't made the relevant simultaneous measurements. X will get answered in one of the main points. Z comparison of the different weighting schemes will show this doesn't have much effect. EE One of these is the average station variance. Hope these are of some use. Cheers Phil Prof. Phil Jones Climatic Research Unit Telephone +44 (0) 1603 592090 School of Environmental Sciences Fax +44 (0) 1603 507784 University of East Anglia Norwich Email p.jones@uea.ac.uk NR4 7TJ UK ----------------------------------------------------------------------------