Want to SEE a Station’s Temperature Data?
I’ve been doing graphs for each region and country, and thinking that, eventually, I ought to take on the work of doing graphs for each individual station… and stumbled on someone who has already done it.
There is a “top level” with each “Region” laid out (Africa, Asia, South & North America, etc.). You “click a region” then get a list of countries. Pick one and you get ALL the stations listed. While you do need to know the station number to pick one out, that’s not so hard to find.
Two “nice bits”. Each graph starts as a constant scale. This lets you see how that record looks in the overall context of the entire temperature record. From start of the records to the end, from coldest to hottest. Just what is it’s context? The impact of seeing a “tiny little wiggly scrap of data” in a vast box of empty white puts things in perspective. The graphs start at 1850 (in keeping with the CRU / Hadley usage) so you get 30 years more than from GISS. It would be “nice to have” for the graphs to start time in 1720 when the first thermometers start, but that’s probably overkill for most folks. Ok, so you have your high level graph. What then?
You can then click on the graph proper and get a zoomed in version with much stronger ‘wiggle’, (but by now you have the context and know you are not seeing dragons, just small lizards under a very large magnifier…)
There is something about seeing a graph like this one:
From this page:
to put things in perspective…
When you visit the actual pages you will get the “click through” version that gets to the “zoomed in” view. You ALSO will get the “meta data” for that station from two different sources. The NOAA meteorological station location information from NOAA and the GHCN Version 2 “inventory” data.
Nicely done. Just nicely done.
My only complaint would be that the GHCN data are described as “raw”, and as we’ve seen, even the “UN-adjusted” data are not “raw”. But many of us have fallen into that word trap, even me. (After all, GISS calls it “raw” at times, as do many other folks. But “unadjusted” is not raw and does have adjustments in it…)
As another example, the data for “Marble Bar” Australia are graphed here:
This is an interesting graph as you can see the “adjusted” values peaking out (bits of red) from behind the “unadjusted” values. At the far right, you can also see a tiny “lift” to the bottom of the data range as we reach recent years.
I recommend a visit. While I don’t know what else is on the site, the quality looks to be quite good. I expect to spend a while “browsing” around. ;-)
Oh, and the source code to do this yourself is also published:
The site is run by Sinan Ünür and has some focus on Turkish culture and related that also looks like it might well be interesting. Given the quality work done by the Turkish Meteorologists who found cooling in Turkey (as we saw in this paper: http://www3.interscience.wiley.com/journal/114078036/abstract from comments in the Turkey Posting) I think I’m gaining a deeper respect for Turkey and the quality of the work being done there.