For those tracking the daily global temperature updates at the Discover website, you might have noticed the continuing drop this month in global temperatures. The mid-tropospheric AMSU channels are showing even cooler temperatures than we had at this date with the last (2008) La Nina. The following screen shot is for AMSU channel 6 (click for large version).

A check of the lower stratospheric channels (9, 10) suggests this is not a stratospheric effect bleeding over into the tropospheric channels.

With the current (and forecast to continue) stormy pattern over the U.S., I have to wonder whether the atmosphere is currently in a destabilized state. I doubt that surface temperatures anomalies are as anomalously low as the mid-troposphere temperatures are running, which in combination with anomalously cold mid- and upper-tropospheric temperatures means there is extra energy available for storms. (Since AMSR-E failed in early October, our sea surface temperature plot is no longer showing current data, so I have no easy way to check surface temperatures.)

Of course, this too shall pass. I just thought it was an interesting curiosity during a time when some pundits are claiming global warming is “accelerating”. Apparently, they are still stuck in the last millennium.

I will be revealing some of the evidence we will be submitting to Geophysical Research Letters (GRL) in response to Dessler’s paper claiming to refute our view of the forcing role of clouds in the climate system.

To whet your appetite, here is a draft version of one of the illustrations (click for the large version). It clearly shows the large discrepancy which exists between the IPCC climate models and satellite observations in the way they show the Earth shedding excess radiant energy in response to warming. This is central to question of how much warming can be expected from anthropogenic greenhouse gas emissions, because the less radiant energy the model’s shed per degree of warming, the more the models continue to warm.

The figure above represents 700 years of data (50 years each from all 14 models we have analyzed), and all 20 years of global Earth radiant energy budget data which exists from 2 satellite periods. Each point plotted represents an estimate of how much energy is lost (gained) by the Earth per degree of warming (cooling) during year-to-year climate variations in the individual decades.

Results for various averaging times are shown: Monthly (used by Dessler), 3 and 12 monthly (used by Forster & Gregory, 2006 J. Climate in their analysis of ERBE data, results of which are plotted as blue squares above), and 18 months used by only us in our analysis of the CERES data. We decided showing results for multiple averaging times is better than arguing with our critics over what averaging time is best. (If there are two options, A and B, and we chose A, our critics would claim there was an Exxon-funded conspiracy to exclude B.)

Of course, this evidence also supports one of the main conclusions of our Remote Sensing paper published earlier this year: there is a large discrepancy between the IPCC climate models and observations. That’s the paper which led to the resignation of the journal’s Chief Editor, and an apology from that journal to Kevin Trenberth for even publishing our paper (never mind it was peer reviewed by researchers who also publish on the subject).

The Effect of Volcanoes in Models versus Observations

One new twist that emerges from the above figure comes from the blue triangles, representing the model decades involving large episodic radiative forcing events by volcanic aerosols, compared to decades without volcanic forcing (yellow triangles). These blue triangles clearly show that a low bias in the regression-diagnosed feedback parameter tends to occur when time-varying radiative forcing is present (The volcanoes were Mt. Agung in the 1960s, El Chichon in the 1980’s, and Mt. Pinatubo in the 1990s. 7 of the 14 models included strong, episodic volcanic forcing, as independently decided from data presented by Forster & Taylor, 2006 J. Climate).

Furthermore, comparison of those blue triangles to the Pinatubo-influenced ERBE satellite data (blue squares, separately computed and previously published by IPCC-affiliated researchers) shows even a larger discrepancy than do the yellow (non-volcanic) triangles compared to the (orange) CERES data, which experience no major volcanic events. While one might argue that the CERES satellite measurements (orange circles) are not totally inconsistent with the yellow model triangles, the same cannot be said about the ERBE Pinatubo-influenced observations (blue squares) versus the blue model triangles. This has become a common IPCC defense of the climate models (“…well, the observations aren’t totally inconsistent with all of the models…”), as if this somehow constitutes validation of the climate models.

How Do the Results Jibe with Dessler (2010)?
Dessler (2010) in effect made a calculation representing the single orange circle on the far left. He interpreted it as evidence of positive cloud feedback (all of the IPCC models now exhibit positive cloud feedback), and indeed if I were to take that single circle, with its diagnosed net feedback parameter of only 1.2 W m^-2 K^-1, I might be inclined to agree it does, indeed, suggest positive cloud feedback.

But note how that single orange circle compares to the models (the triangles) when the exact same calculation is made from them. There is a significant discrepancy, which is seen to grow at the longer averaging times where the feedback signal is expected to more clearly emerge.

And the discrepancy appears to be the greatest in decades that experienced major volcanic eruptions.

Conclusion

The evidence keeps mounting that the Earth is more resistant to radiative forcing than are the climate models used by the IPCC to project future climate change. While it doesn’t actually prove the models are wrong in their projections of global warming, I don’t see how discrepancies this large can continue to be ignored.

If not for the public policy implications (which Dessler admits was the impetus for his 2011 paper criticizing our work), evidence as strong as that contained in the above illustration would be easily embraced by the climate research community. Maybe some day.

It will be interesting to see whether GRL rejects our paper out of hand. Maybe it would help if I joined the Union of Concerned Scientists. Hmmmm.

P.S….another tidbit for those following Dessler’s claim that clouds can’t cause climate change…
Dessler claims that changes in ocean temperature are way too large to be caused by clouds. Well, the year-to-year changes in Levitus global ocean heat content of the 0-700 m layer during the 2000-2010 satellite period of record yields a yearly standard deviation of 0.5 Watts per sq. meter for the energy required. In comparison, the yearly standard deviation of the global oceanic CERES satellite radiative fluxes is 0.3 Watts per sq. meter, which represents 60% of the energy required to cause the ocean temperature changes. Using any reasonable feedback parameter combined with the sea surface temperature variations yields only 0.1 Watts per sq. meter.

Thus, cloud variations (or maybe even natural water vapor variations?) can constitute an important natural forcing component of climate variability. And since it is our physical interpretation of observed climate variability that impacts our estimates of climate sensitivity, it also impacts our estimates of future global warming (aka climate change).

At this point, I suspect Dessler’s conclusions to the contrary are partly the result of a large amount of noise in temperature changes with time computed from short-term Levitus ocean heat content data.

…sometimes, the most powerful evidence is right in front of your face…..

I never dreamed that anyone would dispute the claim that cloud changes can cause “cloud radiative forcing” of the climate system, in addition to their role as responding to surface temperature changes (“cloud radiative feedback”). (NOTE: “Cloud radiative forcing” traditionally has multiple meanings. Caveat emptor.)

But that’s exactly what has happened. Andy Dessler’s 2010 and 2011 papers have claimed, both implicitly and explicitly, that in the context of climate, with very few exceptions, cloud changes must be the result of temperature change only.

Shortly after we became aware of Andy’s latest paper, which finally appeared in GRL on October 1, I realized the most obvious and most powerful evidence of the existence of cloud radiative forcing was staring us in the face. We had actually alluded to this in our previous papers, but there are so many ways to approach the issue that it’s easy to get sidetracked by details, and forget about the Big Picture.

Well, the following graph is the Big Picture. It shows the 3-month variations in CERES-measured global radiative energy balance (which Dessler agrees is made up of forcing and feedback), and it also shows an estimate of the radiative feedback alone using HadCRUT3 global temperature anomalies, assuming a feedback parameter (λ) of 2 Watts per sq. meter per deg (click for full-size version):

What this graph shows is very simple, but also very powerful: The radiative variations CERES measures look nothing like what the radiative feedback should look like. You can put in any feedback parameter you want (the IPCC models range from 0.91 to 1.87…I think it could be more like 3 to 6 in the real climate system), and you will come to the same conclusion.

And if CERES is measuring something very different from radiative feedback, it must — by definition — be radiative forcing (for the detail-oriented folks, forcing = Net + feedback…where Net is very close to the negative of [LW+SW]).

The above chart makes it clear that radiative feedback is only a small portion of what CERES measures. There is no way around this conclusion.

Now, our 3 previous papers on this subject have dealt with trying to understand the extent to which this large radiative forcing signal (or whatever you want to call it) corrupts the diagnosis of feedback. That such radiative forcing exists seemed to me to be beyond dispute. Apparently, it wasn’t. Dessler (2011) tries to make the case that the radiative variations measured by CERES are not enough energy to change the temperature of the ocean mixed layer…but that is a separate issue; the issue addressed by our previous 3 papers is the extent to which radiative forcing masks radiative feedback. [For those interested, over the same period of record (April 2000 through June 2010) the standard deviation of the Levitus-observed 3-month changes in temperature with time of the upper 200 meters of the global oceans corresponds to 2.5 Watts per sq. meter]

I just wanted to put this evidence out there for people to see and understand in advance. It will be indeed part of our response to Dessler 2011, but Danny Braswell and I have so many things to say about that paper, it’s going to take time to address all of the ways in which (we think) Dessler is wrong, misused our model, and misrepresented our position.

The global average lower tropospheric temperature anomaly for September, 2011 retreated a little again, to +0.29 deg. C (click on the image for the full-size version):

The 3rd order polynomial fit to the data (courtesy of Excel) is for entertainment purposes only, and should not be construed as having any predictive value whatsoever.

Here are this year’s monthly stats:

YR MON GLOBAL NH SH TROPICS
2011 1 -0.010 -0.055 0.036 -0.372
2011 2 -0.020 -0.042 0.002 -0.348
2011 3 -0.101 -0.073 -0.128 -0.342
2011 4 +0.117 +0.195 +0.039 -0.229
2011 5 +0.133 +0.145 +0.121 -0.043
2011 6 +0.315 +0.379 +0.250 +0.233
2011 7 +0.374 +0.344 +0.404 +0.204
2011 8 +0.327 +0.321 +0.332 +0.155
2011 9 +0.289 +0.309 +0.270 +0.175

The global sea surface temperatures from AMSR-E through the end of AMSR-E’s useful life (October 3, 2011) are shown next. The trend line is, again, for entertainment purposes only:

On the subject of the drop-off in temperatures seen in the AMSR-E data in the last week, I have been getting questions about the daily AMSU tracking data at the Discover website which shows Aqua AMSU channel 5 (which our monthly updates are computed from) is now entering record-low territory (for the date, anyway, and only since the Aqua record began in 2002). While I have always cautioned people against reading too much into week-to-week changes in global average temperature, this could portend a more significant drop in the next (October) temperature update, as the new La Nina approaches.

UPDATE #1: See update at end.

The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) was automatically spun down to its designed 4 rpm safe condition last night after recent increases in the amount of power required to keep it spinning at its nominal 40 rpm were beginning to cause noticeable jitter in NASA’s Aqua satellite.

The instrument has over 480 pounds of spinning mass, and the lubricant in the bearing assembly gradually deteriorates over time. This deterioration has been monitored, and automatic shutdown procedures have been in place for years if the amount of torque required to keep AMSR-E spinning exceeded a certain threshold.

Starting about October 1, AMSR-E was causing yaw vibrations in the Aqua satellite attitude which were increasingly exceeding the +/- 25 arcsecond limits that are required by other instruments on the spacecraft. Last night, the 4.5 Newton-meter torque limit was apparently exceeded, and the instrument was automatically spun down to 4 rpm.

At this point it appears that this event likely ends the useful life of AMSR-E, which has been continuously gathering global data on a variety of parameters from sea ice to precipitation to sea surface temperature. It’s 9+ year lifetime exceeded its 6 year design life.

AMSR-E was provided to NASA by Japan’s Aerospace Exploration Agency (JAXA), and was built by Mitsubishi Electric Company. It was launched aboard the Aqua satellite from Vandenberg AFB on May 2, 2002. It has been an extremely successful experiment, and has gathered a huge quantity of data that will be revealing secrets of weather and climate as scientific research with the archived data continues in the coming years.

As the U.S. Science Team Leader for AMSR-E, I would like to congratulate and thank all of those who made AMSR-E such a success: JAXA, MELCO, NASA, the University of Alabama in Huntsville, the National Snow and Ice Data Center (NSIDC) in Boulder, and the U.S. and Japanese Science Teams who developed the algorithms that turned the raw data collected by AMSR-E into so many useful products.

The good news is that AMSR2, a slightly modified and improved version of AMSR-E, will be launched early next year on Japan’s GCOM-W satellite, and will join Aqua and the other satellites in NASA’s A-Train constellation of Earth observation satellites in their twice-daily, 1:30 a.m./p.m. sun-synchronous polar orbit. It is my understanding that those data will be shared in near-real time with U.S. agencies.

We had hoped that AMSR-E would provide at least one year over data overlap with the new AMSR2 instrument. It remains to be determined – and is only speculation on my part – whether there might be an attempt to gather some additional data from AMSR-E later to help fulfill this cross-calibration activity with AMSR2. [The Aqua satellite can easily accommodate the extra torque imparted to the spacecraft, and last night’s spin-down of AMSR-E was mostly to eliminate the very slight chance of sudden failure of the AMSR-E bearing assembly which could have caused the Aqua satellite to go into an uncontrolled and unrecoverable tumble.]

Again, I want to thank and congratulate all of those who made AMSR-E such a huge success!

UPDATE #1: As of early this morning, the torque required to keep AMSR-E spinning at 4 rpm was too large for its own momentum compensation mechanism to handle, with excessive amounts of momentum being dumped to the spacecraft. As a result, the instrument has now been spun down to 0 rpm. The satellite has shed the excessive momentum, and is operating normally, as are the other instruments aboard the spacecraft (MODIS, CERES, and AIRS).