I think Python or Ruby or something like that should be part of any university track high school curriculum. It is maddening that people think Excel is easier or more convenient.
mt On Wed, Feb 4, 2009 at 1:29 PM, [email protected] < [email protected]> wrote: > > > But heat context is proportional to T, not T^4 (ignoring other factors > > like humidity). So redistribution of heat will not affect the simple > > average, but may change this 4th power calculation, which appears to > > be the precise opposite of what you are hoping to achieve. > > I know there's a difference between varying heat flows from a huge > reservoir (the deep ocean and there is a disequilibrium and more heat > is absorbed by Earth than radiated away) and a different distribution > of heat across the Earth's surface (ie the same amount of heat is > radiated away by Earth as a whole, but more heat is radiated away in > some places and less in others). What I was saying was that both might > introduce "weather noise". > > I don't really understand what's driving weather noise or what it even > is (ie I have yet to see a clear definition of it), and it bugs me how > people can have endless discussions about trendlines and "noise" in > temperature data without giving much thought to that. > > Anyway, it would sure be nice, if there was a way of backing out the > "noise". The noise coming from varying heat flows from the deep ocean > might be gotten at by looking at the way ocean heat content changes, > that involves weighting temperatures by thermal mass / heat capacity. > And of course, it wouldn't be surface temperatures that would need to > be weighted, the thermal mass of air is tiny. And the noise from eg > wind moving heat towards Siberia in one month and not the other, maybe > that could be dealt with partially by looking at T^4 averages, with > the T referring to surface temperatures. > > > > Might it be that monthly world temperature averages would be less > > > noisy using fourth powers? > > > > Well it is trivial enough to test - you can easily download data from > > CRU and GISS. > > It would be trivial, if there was an Excel file that had a few hundred > grid points in it together with monthly averages for the last hundred > years. That I could do in less than an hour. Daily readings would I > think already be too much for Excel. I am no good at scripts, > databases and the like, ie I don't have the software and/or experience > with it, so unless I get the data in a format I can easily do > something with, I think I'll be reduced to suggesting something > hopefully useful to others. I think there are plenty of people for > whome it really would be trivial. > > And if nobody except me (and in particular nobody for whom it really > is trivial to calculate, as they've got the tools at their finger > tips) thinks it might be useful, it's probably best if it ends up in > the rubbish bin of poor scientific ideas anyway. > > > > --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups Global Change ("globalchange") newsgroup. Global Change is a public, moderated venue for discussion of science, technology, economics and policy dimensions of global environmental change. Posts will be admitted to the list if and only if any moderator finds the submission to be constructive and/or interesting, on topic, and not gratuitously rude. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/globalchange -~----------~----~----~----~------~----~------~--~---
