My understanding is that The Official Answer is about three decades, more or less.

That being the case, how can the GCM calculations of the effects of Pinatubo, those covered five years, be considered valid calculations? Was the ‘weather noise’ somehow suppressed in the calculations? Were the effects determined by ensemble averaging several runs by several models using several different ICs?

Maybe this has already been covered somewhere nearby.

Thanks

Sorry, I thought I linked you too, and you’d see a track back!

As I said: I do understand why people would suspect the GISS data. To some extent, I think that even if the GISS algorithm is designed to give a warming trend, this fiddling is self limiting. At a certain point, all the weather services, normal human beings etc. know that while it did warm from the 70 – 2000, it really hasn’t warmed recently.

Even without thermometers, I garden. I know spring was delayed. I have photographs of my gardens, and I know I don’t simply mis-remember when peonies or daffodils bloomed in other years.

On the GISS algorithm, I think my favorite all time comment appeared on climate audit yesterday:

Obviously, in statistical terms, the Hansen methodology seems demented. But whether the demented adjustments “matter” is another question.

Perhaps they all just cancel out and the machine just goes zip, bop and whirr without actually making matters worse than making no “urban adjustments” at all. That’s a topic for another day or another month.

It may well be that the method doesn’t introduce any bias in the mean trend. Given some aspects like using April data to correct march data, it may smooth out weather noise, change spectral characteristics of “(weather!)”. This complicates any advanced statistical analysis, but might leave the mean trend intact.

Anyway, I’m pretty much going to use it along with the rest– even though it does appear demented. Meanwhile, I’m interested in seeing what everyone gets using their choices and judgement. (But, I’ll still comment. )

Lucia, I only just saw the issue, and I responded on Anthony’s site. If you don’t mind, I will simply lift it and reproduce it here.

“Basil:
While I respect Lucia’s opinion on which data sets to use, in my mind one has to draw a quality standard somewhere. On top of all of the quality problems that Anthony has documented with the data, I think that there have been adjustment choices made with GISS that are designed to give warming results that increase the trend. I think that this paper does a good job of explaining some of those choices.

http://www.friendsofscience.or.....ctions.pdf

crosspatch also has a good take on it above.

And of course the divergence over the last decade should also tell you something. The decadal divergence is .13C. That is well over half of the .2C decadal trend that is blamed on CO2 by the warmers.

Once we do a better analysis on HadCru data we may find out that it has many problems of its own. But for right now I have to draw a line in the sand somewhere, and my personal choice is not to accept GISS for any purpose. I believe that it would be excusing agenda oriented work to use it. Just my opinion.”

We’ll see if it stays flat. I suspect it will start to rise but…. my expectations aren’t data.

Are you familiar with loess fit regression? If you try it with GISS, you’ll find it in the global warming on hiatus camp. I’ve crafted a quick plot you can look at here:
http://i25.tinypic.com/hspbvs.jpg

I use the same 11 year period under discussion, with the GISS anomaly normalized to the 11 year mean. At the end of the period, the loess fit is ever so slightly less than at the beginning, indicating just a hint of downward trend, but not enough that we couldn’t ignore it if we chose to, and called the trend “flat.”

For HadCRUT, UAH and RSS, for the same period, the loess fits all show a bit more marked declines, in starting higher, and ending lower. Here’s a spaghetti graph of the four of them:

http://s3.tinypic.com/2607ibs.jpg

Will you now reconsider that global warming is on hiatus, at least for the past 11 years, even using GISS?

Basil

Which ever is which, I’ll always show both the cake and the icing!

BTW continue the great job!

Is HadCrut obviously better? The satellites had issues when they were new. Are they better than the land measurements? If yes, do we know this for sure? I think we don’t know.

I agree the satellite data isn’t technically measuring the same thing as the rest. But, it’s been pretty close since the beginning of measurements. I do show everything all together too– and if someone’s point of view really hinged on “pure surface” only, I’d show the NOAA/HadCrut/GISS merge together.

In the long run, it’s difficult for one of the sets to veer off too much without things looking really weird.

There are other datasets, but these are difficult/impossible to compare with others becuase RATPAC is broken into, at most, seasonal timeseries, and RAOBCORE has a difficult website to use, as does INGRA.

I’m not sure I agree with lucia that the average is best, as TLT and GMST are not meant to mix. one could easily argue that you should include radiosondes to, and on and on. In fact, don’t some radiosonde data sets have surface values? I think I’ll put together a more comprehensive look at the different measurements. Say, what pressures does LT represent, anyway? HadAT only reports series at different pressure levels.
http://hadobs.metoffice.com/ha.....l_mean.txt