Here’s a current plot of unadjusted Channel 5 (“600 mb”) global tropospheric temperature anomaly data for the past eighteen months, available from here

There is current blogosphere interest in this because the July, 2009 global anomaly peak is happening at the same time as the annual (boreal summer) peak, creating a “record” absolute temperature.

I added thin green lines to indicate where the typical peaks and valleys align. I added a red dot where I think the anomaly will be in two or three weeks, if past patterns hold.

The plot indicates that the global troposphere experiences some kind of “heat kick” on a roughly regualr basis. The heat then dissipates in rather short order, returning the troposphere to its more-or-less initial state.

My guess is that this, if it is real, is a function of tropical thunderstorm activity, probably Indo-Pacific in origin. Or, maybe somehow it relates to occasional bursts of energy moving from the tropics to the extratropics. Or, maybe it is an illusion created by the measurement system or by my layman’s handling of the data.

If it is real then I’d sure like to understand the physical behavior that underlies the pattern. Opinions welcomed.

For AQUA, ice data starts in mid 2002 so I presume the other measures started then too. The UAH switchover to AQUA was probably later as cross calibration would be necessary.

Re: Jim (#17),

Those circulation cells arise in the models as well. The relative efficiency of heat transfer is a question, though, as for example IIRC, Jerry Browning has stated the jet streams in the models bear little relation in position and velocity distribution to the real world.

If ENSO heating get carried to the Arctic via Hadley/mid-latitue/polar cells, wouldn’t that imply a generality that heat in the LT is rather efficiently carried away and would account for the lack of the “hot spot?” It would also account for polar melting, would it not? (I am just trying to learn more about climate – I’m not even a talented amateur.)

What are the overlaps for the AMSUs in UAH? I’m not too clear on this. AFAIK, data from NOAA-15 AMSU starts around 1998, and AQUA late 2003 or early 2004, but I’m unclear on the details. What were the overlaps involved in these two transitions?

In the case of RSS, I suppose it’s NOAA-15 AMSU alone for the last several years.

Steve,
As implied above, I think the first AMSU (NOAA-15) switchover corresponds to circa 1998 “breakpoint”, while the more recent switch to AQUA AMSU would be circa 2004. I imagine John C. will set us straight as to the exact details.

In general there are two satellites operating at any given time, so for each day we have two values to average. When a replacement is launched for the older, the newer continues to operate as now the new older satellite. E.g. NOAA-10 (0730/1930 orbit crossing) and NOAA-11 (0130/1300 orbit crossing time) operated together with NOAA-10 the first to go up. When NOAA-12 was launched to replace NOAA-10, NOAA-11 was operating across both – hence we have a backbone to carry the data forward without a discontinuity. It’s a bit more convoluted than that (which leads to the RSS shift in 1992) but that’s the basic idea. If you look at the hot-target temperatures shown in Steve’s post you will get an idea of how this worked.

John C.

GHCN global series may provide even more-revealing examples of breakpoints, because of the station-shuffling involved at various time-junctures of the index construction. USHCN has enough century-long records to mute this effect.

I’ll plot up some HadAT series for comparison and clip out a plot from your 2007 article for comparison as well.

Steve, you might also try plotting comparisons with the GISS data. The GISS data seems to track the satellite date better than Hadley CRUT3. See:

http://www.junkscience.com/MSU_Temps/MSUvsGISTEMP.html
http://www.junkscience.com/MSU_Temps/MSUvsHadley.html

John, thanks as always for your comments. The observation that

The surface and the troposphere are somewhat coupled, but respond differently to forcings, so you would expect difference time series as you show to display these type of differences – due to physical properties of the two media.

is obviously something that you’ve discussed in many articles. This is a point of view that seems at odds with the tight coupling of surface and troposphere in the models and is obviously a very big and important question.

I’ll plot up some HadAT series for comparison and clip out a plot from your 2007 article for comparison as well.

I agree with comments about limitations of breakpoints methods – we’ve discussed this from time to time, mostly in connection with USHCN breakpoints methods and GISS.

It seemed interesting to experiment with these methods with the satellite data.

As one plots the results, one sees that the breakpoints methods are definitely attracted to big El Nino’s, which also more or less coincide with satellite changeover in some cases.