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Fasullo and Trenberth find spurious success, make headlines, but still the models crash

It’s worse than we thought — again….

Fusulo and Trenberth scored headlines around the world recently with a new paper that suggested that a few models got the relative humidity right in some tropical spots, and they also happened to be the models that predicted the hottest global outcomes.

John Christie pointed out that the models with the highest climate sensitivity are also the ones which are the worst at predicting future temperatures.

But there is more to this. It is a likely a case of twenty models predicting 40 parameters, and you can take your pick of the permutations and combinations which give one or two models a “success” here and there on one or two factors. But in the end, as Richard Courtney says, all the models are different so only one model can possibly be The Right One for the whole atmosphere, and quite likely they are all wrong.

In this case, they are still all wrong. The hot spot is still missing, and the region below it with which they scored some success is not that important.

The words hot spot and humidity over the tropics lead many commentators to think this was something to do with the hotspot, but lets make it clear: the (missing) hotspot is at a higher altitude than the area they are referring too. That prediction of warming in the upper troposphere is up around 200-300 hPa. This reduction in relative humidity is centered well below that, at 500Hpa.

Why does that matter? Because the most powerful greenhouse gas (water vapor) does its thing at the top of the troposphere (around 200 hPa) — that’s where it radiates energy out to space. Below that level the energy is effectively ricocheting back and forward — bouncing between molecules or causing collisions and generally rarely getting out to space where it is then gone for good.

This explains the paradox that humidity at lower levels can be relatively unimportant compared to the humidity in the top most layers of our troposphere. Water is so important that the wet part of our atmosphere has a different name to the dry part — that’s the troposphere versus the stratosphere above it. But for most of the thickness of the troposphere there is generally so much water vapor — even at low pressures — that the radiative effect of water is saturated. It’s only on the surface boundary, right at the top of the troposphere, that a change in humidity matters, because it changes the amount of energy that flows off the planet.

Note the strange technique in the graph below of doing relative humidity with the lower numbers on the right. The marketing department probably felt that a line of stars rising from left to right fitted the scare campaign better than a falling line would.  This is PR-science, not science for scientists.

In this graph the colours are for relative humidity, the contour lines are for model predicted cloud loss.


Figure 2: The zonal height structure over ocean of observed climatological annual mean RH from AIRS (2002–2007) (color scale), with model mean projected changes in cloud amount from the CMIP3 model archive (contour lines, 0.5% intervals, dashed for cloud loss). The cloud loss in a warming climate at about 40°N/S coincides with broadening of the dry zones, as indicated by the arrows.  Figure 2 from FS12.

The red bars are the latitude points where the change in shortwave flux as predicted in models matches  the ECS at the 5% level. (Note that this is not longwave, or infra red flux, this is the UV flux — light coming in from the sun and bouncing off clouds.)

Figure 3: Median change in simulated top-of-atmosphere net shortwave flux as a function of latitude under 21st-century warming in CMIP3 SRES A1B projections. Red bars denote latitudes at which the change in net shortwave flux correlates with ECS at the 5% confidence limit.  Figure 3a from FS12.


The boxes here are the parts of the atmosphere the models do best at predicting relative humidity. These wet and dry regions matched observations at the 1% level. (Everything outside those boxes didn’t). Remember the part of this graph that really matters (in order to predict the radiation that leaves the planet) is the layer around 200-300 hPa near the equator. The models could get the rest right and still exaggerate the amount of heat that was trapped if they get this critical region — the “hot spot” — wrong.

Figure 4: Zonal mean vertical structure of the correlation between present-day (1980–1999) simulated RH over ocean from May to August in CMIP3 models and ECS. Boxed regions highlight peak positive and negative correlations in the moist (M) and dry (D) zones, respectively, where the statistical significance of the relationships exceeds the 1% confidence limit.  Figure 3b from FS12.


If the relative humidity is falling between 500 hPa and 300 hPa that could mean clouds are forming at that height, or clouds are forming lower. It seems that high clouds are those above 400hpa, and more often those high clouds are cirrus, the warming kind of cloud. But it doesn’t appear that this paper can tell us which sort of clouds are forming and at which height. About a third of all clouds observed exist between 700 – 400hpa, (and about one third are below that and one third above that). We’re stabbing in the dark with clouds.

The predictions that matter

Note the all important hot-spot below from the IPCC in 2007 (not mentioned in this paper). Even advocates of man-made global warming admit it is missing from observations and is important. It’s between 200-300 hPa (about 10km up, over the tropics).

…IPCC AR4 page 675.

Above is what the climate models predict as a profile of temperature trends.

The observations that don’t match

Below is what many millions of radiosondes (weather balloons) recorded. The scales are different, but you get the picture. The models are wildly wrong, and since the upper troposphere matters because it’s the part that radiates energy to space, the changes there count.


Skepticalscience thinks this is evidence from clouds?

Follow the reasoning.

1. Clouds feedbacks are uncertain, and we don’t have much data:

“Unfortunately, as FS12 discuss, the currently available observational cloud data are not very good.

“Constraining simulated clouds is a challenge, however, as clouds are complex and difficult to observe. The historical record is plagued by errors associated with the drift and failure of satellites, inconsistencies in the detection of clouds, and instrument biases. Moreover, clouds can vary not just in their bulk characteristics but also in their microphysical properties, for which global observations are lacking generally, and considerable uncertainty persists regarding the feedbacksnof various cloud types that may occur in a changing climate.”

2. So instead of examining the data we don’t have, we’ll look at relative humidity instead. It’s like looking at a cloud, really,  and if we just knew all the details of what conditions exactly  form clouds (seeding particles anyone?), it would be almost as good as having actual cloud data.

“Thus rather than examining clouds directly, FS12 take a different approach and instead look at the conditions in which clouds form.

“Variations in clouds and relative humidity (RH) are inherently linked in nature, and the approach here is motivated by the fact that models generally use RH to parameterize clouds”

So if models use relative humidity to generate clouds, and we know that the models don’t work, does that tell us something about how much we don’t know about cloud formation?

They have a failed theory on their hands, and many of the world’s bureaucrats and politicians have staked their reputations on it, not to mention the billions of dollars at risk. What if people find out they are wrong? Hmmm, tricky situation. Papers like this one help provide the cover and delay the inevitable. The Team knows they can cite it, and most people won’t check the details. Journalists will just reprint the press release.


Fasulo, J., &  Trenberth, K.  (2012): A Less Cloudy Future: The Role of Subtropical Subsidence in Climate Sensitivity, Science, Vol. 338 no. 6108 pp. 792-794  DOI: 10.1126/science.1227465 [Abstract]

 My posts on the missing hot spot

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