Peter Thorne, over at Moyhu early last month announced that the International Surface Temperature Initiative (ISTI) has gone beta and is available for inspection. The databank and a listing of what is in it is available. As the announcement puts itThis is data that mostly has not been quality controlled or bias corrected. It is important to stress that it therefore does not constitute a climate data record / dataset suitable for monitoring long-term changes. Rather, it provides a basis from which research groups can create algorithms to produce climate datasets. The results from these algorithms can then be compared and benchmarked as part of the International Surface Temperature Initiative activities. We hope that many groups and individuals take up this challenge which will lead to improved understanding of land surface air temperature changes particularly at regional scales.Nick is taking up the challenge and tuning up his toys.
Nice but environmental air carries latent heat not indicated by the temperature. Thus, we can have volumes of air at the same temperature that contain different amount of heat.
ReplyDeleteAnd, as the air in a region (E.g. the Arctic) warms from below freezing to above freezing, it tends to carry a lot more latent heat. As an air mass in the Arctic goes from below freezing to above freezing the change in its heat content is more than when an air mass over the Sahara goes up the same number of degrees.
Thus, we have understated Arctic amplification.
I want a database of Gibbs energy.
OK, so I've put this up here previously, but I think that it's worth putting up again -- it's a nice little visualization tool that demonstrates the amazing robustness of the NASA/NOAA/CRU/whatever global-average temperature results.
ReplyDeleteLinky here: https://docs.google.com/open?id=0B0pXYsr8qYS6aV94WTdoa2E4Umc
It's an animated GIF file that shows global-average temperature results computed from a maximum of 40 randomly-selected globally-scattered rural stations. The first animation frame shows results from just one station; new frames in the animation show updated global-average results as stations are added one by one, up to a max of 40 stations.
The upper plot in the animation shows global-average results from raw data (red), results from adjusted data (green), and the official NASA/GISS GHCN results for comparison purposes (blue).
The lower plot shows how many of the selected stations actually reported data for any given year (results can be fractional -- a station that reports data for 6 months in any particular year is counted as "half a station").
Note how quickly the temperature trends for the raw and adjusted data converge to the official NASA/GISS trend.
The animation drives home the point that you don't need "Better than Best", or even "Best", to confirm the NASA results. All you need is "Good Enough", which turns out to be no more than a few dozen stations.
Quick additional note -- These results were not "cherry-picked" in any way. Stations were pre-screened only for adequate data record length (to ensure decent coverage for the last century or so).
This is the result of my first attempt to do this. I didn't repeat this exercise a bunch of times so that I could select the "best result". Just did it once and uploaded what I got.
Anyway, if you find this helpful/useful, please share with skeptical family/friends/co-workers/etc...
--caerbannog the anonybunny
Mr. Rabett. Thanks for the plug. We really do need beta testing to get this as good as possible.
ReplyDeleteAaron, we looked at moist enthalpy changes just over a year ago in a GRL piece that got highlighted in EOS. You can 'hop over' (groan) to here to find out more. If that doesn't work the doi is doi:10.1029/2011GL048442
Peter