From	Mike Hulme	Date	Wed Sep 11 12:39:26 2002
To	Iain Brown (UKCIP)
CC	geoff.jenkins@metoffice.com, x.lu, j.turnpenny
Subject	Re: temporal interpolation for UKCIP scenarios
Iain (and Geoff), Definitive explanations are always dangerous! The reasoning behind this is as follows: - the report only analysed and pictured seasonal and annual data (DJF,MAM, etc.) [in fact, nearly all published maps of climate model outputs show changes in seasonal - 3-month - averages]. This applying a uniform filter over 90 or 360 days. - the requested datasets are at monthly time-steps. The default option for this is in effect applying a uniform 30-day filter. [one might also conceive of weekly or daily time-step files - e.g. changes in Week 13 for the 2050s for precip. for Medium-High or changes for Julian day number 256 for the 2080s for Tmin for Low]. - these are all arbitrary choices of course, dictated by convention. But the important point it seems to me is again a signal to noise issue - the shorter the time-averaging period, the weaker the S/N ratio [i.e., we have more confidence that averaged over a year, Tmin in the UK will increase by, say, 2.7degC for certain scenario, than that for the same scenarios Tmin on 13 June will increase - on average - by 2.6degC and on 14 June only by 2.3degC - is this difference between 2.6 on 13 June and 2.3 on 14 June really meaningful? No - it is most likely due to noise - natural variability]. - this reasoning suggests that as the time-averaging period decreases, one should pay less attention to small differences between adjacent time-averaged periods, e.g. if June precip. goes down by 10%, is the fact that July precip. goes down by 20% and August by 5% really meaningful? - At 10:13 11/09/02 +0100, Iain Brown (UKCIP) wrote: Mike, For the UKCIP Scenarios datasets - both 98 and 02 - temporal interpolation was applied to the raw model data in the form of a 1-2-1 filter. This had the effect of smoothing out monthly values so that there are not as abrupt transitions between adjacent months. Can you provide us with the definitive explanation for the interpolation? Some users (eg. in the recent London study) have noted that there are differences between the maps they have derived from the data and the maps in the UKCIP02 report. best wishes, Iain ----------------------------------- Dr. Iain Brown UK Climate Impacts Programme 12 St. Michael's St. Oxford OX1 2DU