cc: email@example.com, willmottatXYZxyzl.edu
date: Sat, 31 Jan 2009 05:48:15 -0000 (GMT)
subject: RE: More Thoughts
to: "Scott Robeson" <srobesonatXYZxyziana.edu>
Yes - I did mean excluding points that aren't more than
90% complete in any fixed grid analysis.
The v version makes the last you your plots more stable
through time (the 90 minus 10 plot). Maybe our work
on the SST for the period from 1945-1960
and also more SSTs in the WW2 years will lower the
slight bump in the plot at that time as well.
There should be a new version with these changes in
the late spring.
In the meantime best to concentrate on the land only
versions. The SST part does have lower variability.
Hemispheric analyses would be a useful addition. Interesting
to see an SH land one - to see what impact Antarctica after 1957 has.
> Thanks for the helpful comments. Interesting week here -- 30+ cm of snow,
> which is not typical for southern Indiana.
> I have picked up the new datasets and run them through 2008.
> - The v version showed some differences from the previous results -- the
> difference in the trends between the percentiles actually seems to be
> in the v version. Please see the attachment. Note that these are for the
> HadCRUT data (previous results were for CRUTEM). I also did a time series
> of 90th minus 10th percentile time series and the post-war discontinuity
> SSTs seems evident here.
> - Yes, you're right about the high latitude areas (more variable regions)
> driving the high and low percentiles, but data from all over the globe
> contribute somewhat. So, in a sense the trends in the percentiles are
> representative of these high-latitude regions. I could start to do some
> regional analyses, but I'd like to keep the focus on how spatial
> is changing across large spatial scales. Perhaps a hemispheric analysis
> might be useful along those lines and at least it would ensure that
> something like having all the 10th percentiles from the SH and 90th
> percentiles from the NH isn't happening.
> - Fig. 2 is more erratic since the 1970s as the trends are calculated over
> increasingly shorter time periods. The last several points on that graph
> are only for about 30 years while the first ones are for the whole
> period. The trend analysis still uses the monthly data, but I just
> calculated one trend per year (Jan 1881 to Dec 2008, then Jan 1882 to Dec
> 2008, etc.). So, the original figure caption was misleading in that it
> didn't mention the months used.
> - I had thought of a fixed grid analysis too -- then we would know if the
> changes are due to the inclusion of a larger number of more-variable
> later in the record or to "real" changes in the structure of the thermal
> anomalies. When you say 90% complete time series, do you mean that a grid
> point is included if it has 90% data available for a given time period
> (i.e., excluded if it has more than 10% missing)?
> -----Original Message-----
> From: P.JonesatXYZxyz.ac.uk [mailto:P.Jones@uea.ac.uk]
> Sent: Wednesday, January 28, 2009 11:28 AM
> To: srobesonatXYZxyziana.edu
> Cc: willmottatXYZxyzl.edu
> Subject: More Thoughts
> I picked up a copy of your docs/pics etc in Norwich on
> Monday. I've now had a read through, so here's some thoughts
> from Switzerland.
> I think running the v version through would be worthwhile,
> as a sensitivity test. If it shows little difference, then you
> have something that is quite robust.
> I don't think there are many data issues, just coverage changes.
> Can you run with a fixed grid - say 90% complete time series
> over the 1901-2007 period?
> I'm still wondering where the big increase in 90th percentiles
> is coming from? I can see how you calculate it, but spatially to
> my mind this would be dominated by the more variable regions. Maybe
> if you split into two groups - north of 30N and south of 30N.
> Seems like your Fig 2 is more erratic since the 1970s. This
> is an annual whereas Fig 1 is all months. To get annual do you
> do things annually or average the months.
> By the way 2008 is complete now.