UAH’s temperature anomaly sagged to 0.001C in June, drooping further relative to the 0.04C May value. Despite VG’s encouragement, the tempeature anomaly did not break through the zero barrier. Here’s a plot showing longer and shorter term trends, and highlighting June temperature readings.
My quick scan indicates VG may have posted the closest specific guess in comments of +0.015C. El Niño conditions are underway way, so I bet UAH will rebound in July.
Update: No… ZerOth beat VG with 0.10C! I’ll have to read more carefully to see if anyone beat Zer0th.
Hat tip: Roy Spencer who calculated it and Andrew_FL who posted a comment while I was at the hairdresser.
:blush: I’m quick on the draw, eh?
Andrew_FL. One of my readers always beats me to it! It seems the only way I can scoop everyone is to make up weird metrics no one else would bother to report (like the average of channel 5.)
The current anomaly is 0.22C or so below the regression trendline.
What natural variation is responsible for this? The ENSO would be a very small component (0.03C) and the AMO and PDO are likely to be very close to Zero. Maybe the solar decline is kicking in but the solar cycle variability is only +/-0.035C from the trend.
So either this is just random noise or (my vote) the regression trendline is spurious to start with and the real trendline is lower.
Bill Illis–
Monthly temperature are pretty noisy. Look how far above and below the trend line the 1998 El Nino got. I wouldn’t be surprised if the next El Nino gets us to a similar level. ( Bear in mind, if the trend is 2 C/century, we sort of expect to break the 1998 El Nino, though, nothing is certain.)
Lucia,
OT, but please allow me to wish everyone here a very happy 4th of July.
The concept of ‘luke warming’ seems to get more compelling with every new report.
Oh Heck! I missed by -0.0011
Actually my prediction is that temps will continue to flatline or go negative even with El Nino. Weel see what excuse the warmistas will come up this time LOL
Thanks hunter. I already bought a watermelon. 🙂
hunter (Comment#15642)
‘luke warming’ , wasn’t he a character on General Hospital? ;-^
Weird question, probably due to my market research background. If I looked at the dataset in your chart for almost any other subject, I would ask myself what the trend looks like without the outliers. Has anybody done that?
‘Luke Warming’ sounds like a very metrosexual character ;^)
Watermelon is very popular right now in our more-than-luke-warm part of Texas, lol.
Tom– Some people have taken outliers out but I can’t remember off the bat. I haven’t because it’s a bit dicey to throw away 1998 and not have people howl. Maybe someone here can tell you if they have.
Is there any particular criterion you used to decides what’s an outliers? A certain number of standard deviations? If so, do you select based on the number of data points?
When I did laser doppler velocimetry, and took 10s of thousands of data points to get the velocity measurement had a criteria that depended on the number of data point, and we only threw things away if they were really far out. ( With LDV, shot noise can result in some real wild hairs– as in a measurement that looks like it’s mach 10 when the rest of the flow is 10 m/s.)
On removing “outliers”-I think it’s probably better to try and account for the various ups and downs in the data with various sources of variability. Lucia tends to think that this causes cascading uncertainties and she’s probably right. However, some people have tried. There is an old paper here:
http://arxiv.org/ftp/physics/papers/0411/0411002.pdf
Which needs updating. However, they factor in solar cycles, ENSO, and volcanoes. They find an underlying linear trend, too, which I guess is at least partly, or maybe more than partly, due to CO2 etc.
Since there have been no major volcanoes since the Douglass paper that Andrew_FL linked, it would be interesting to see what the current trend is using that data to remove volcano effects from UAH data.
Steve Reynolds-I’ve been meaning to repeat the analysis one day, but one problem I run into is that I don’t quite understand the actual methods they used. Now, I could just use the same coefficients, but I really want make sure that the coefficients haven’t changed. Also, they include TSI, but I can’t find a monthly TSI data set anywhere, either from ACRIM or PMOD.
ENSO and volcanoes are done here, with a sort of proxy TSI in latitude, to isolate an AGW caused trend;
http://arxiv.org/ftp/arxiv/papers/0809/0809.0581.pdf
cohenite, that is a very good paper. I am sure it will keep our AGW friends properly worked up.
Lucia,
I just noticed that your link over at WUWT is missing. Do you know why?
Since you’re looking at trendlines, RSS/Hadley/UAH all have negative trendlines for the last 12 years of data. GISS is the outlier with a negative trendline for approximately the last 8 and 1/2 years.
* RSS monthly data Feb 1997 to May 2009; trendline slope is negative
* Hadley monthly data Mar 1997 to May 2009; trendline slope is negative
* UAH monthly data May 1997 to June 2009; trendline slope is negative
* GISS monthly data Dec 2000 to May 2009; trendline slope is negative
Hi all,
I was thinking of one standard deviation–I would have thought it a normal check… what am I missing? With all the uncertainty about measurement methodologies and such…
This June is 0.1º C colder than June 1979. Last month I was wondering what the odds were when the RSS showed no change between May 1979 and May 2009.
A simple minded trend of 0.2ºC/decade indicates this June should have been 0.6ºC higher. Clearly the data is noisy and one really should not just look at endpoints but it is hard to see why I should be worried when almost the same temperature is replicated 30 years on.
Now that hot seems to be disappearing into the future we need some finer graduations of lukewarming. Anyone know if tepid is above or below lukewarm?
Hunter– Anthony reorganized his links. Look for “luke warmers” just above “political climate”.
Tom– 1 standard deviation would remove 1/3rd of the data. That’s more than the what I call outliers. I ordinarily only remove outliers if I think there is a chance they are errors. That is: mis-measurements, mis-logging etc. Otherwise, they describe some physics.
Jorge–
You’re question can be answered. It’s a variation of Tamino’s recent post on “breaking records”. Heh!