Cancelling the Tropical Cancellation

Guest Post by Willis Eschenbach

There’s a much-cited paper (129 citations) from 1994 called “On the Observed Near Cancellation between Longwave and Shortwave Cloud Forcing in Tropical Regions” by J. T. Kiehl (hereinafter Kiehl1994), available here. The paper makes the following claim (emphasis mine):

ABSTRACT

Observations based on Earth Radiation Budget Experiment (ERBE) satellite data indicate that there is a near cancellation between tropical longwave and shortwave cloud forcing in regions of deep convective activity. Cloud forcing depends on both cloud macrophysical properties (e.g., cloud amount, cloud height, etc.) and on microphysical properties (e.g., cloud particle size, particle shape, etc.). Hence, the near cancellation in the tropics could be due to either the macrophysical or the microphysical properties of these clouds, or a combination of these effects. 

Now, to me that’s a pretty curious and surprising claim. The paper says that both in the Indonesian Region, as well as over the entire tropical Pacific, deep convective tropical clouds have no net effect on radiation, ostensibly because the longwave (positive) and reflected shortwave radiation (negative) cancel each other out. Let me call this the “cancellation hypothesis”. Kiehl supports the cancellation hypothesis inter alia with his Figure 1:

kiehl figure 1 cancellationFigure 1. The first figure in Kiehl1994. The vertical axis shows shortwave cloud forcing, which is the amount of sunlight reflected by clouds in watts per square metre (W m-2). The horizontal axis shows the longwave cloud forcing, which is the change in top-of-atmosphere longwave forcing from the clouds. By convention, the reflected solar radiation is shown as negative, presumably because it is cooling the earth. Data is from April 1985.

And that looks pretty convincing … but, despite the 129 citations of the paper, I’m a suspicious fellow who believes firmly in the famous fallibility of experts. So I thought I’d use the CERES data and see if the cancellation hypothesis held up. Figure 2 shows that result, for the same Indonesian Region used by Kiehl.

my version kiehl figure 1 cancellationFigure 2. Replication of the Kiehl study, using the ten-year April averages for the specified region to remove annual variations. Each square symbol represents a 1°x1° gridcell (N = 1500).

Instead of one single month’s data, I’ve used the averages of the ten Aprils in the CERES dataset.

Now, as you can see from Figure 2, the Kiehl hypothesis of cancellation has a big problem. The CERES results do not bear out Kiehl’s claims in the slightest. Instead, they support my hypothesis that increased tropical clouds cool the surface. As you can see, on average the loss from the reflected sunlight is about 20% or so greater than the gain from increased IR. This means that there is no cancellation. Instead, the clouds have a net cooling effect.

The paper goes on to say:

One feature of the cloud radiative forcing obtained from the Earth Radiation Budget Experiment ( ERBE) is the near cancellation between the longwave cloud forcing and the shortwave cloud forcing in tropical deep convective regions. This result was clearly shown by Kiehl and Ramanathan ( 1990) for the Indonesian convective region (here reproduced in Fig. 1 ). Further analysis of tropical deep convective regions of net cloud radiative forcing indicates that this is a ubiquitous feature that occurs over either ocean or land regions.

This is a more expansive claim than the one in the Abstract. Here the paper says that the cancellation happens over both land and ocean. So I thought I’d divide the Indonesian Region shown above into land and ocean regions. In addition, rather than average the months as in Figure 2, Figures 3 & 4 show all available April data for the entire time period. First, Figure 3 shows the land. I have colored the points by surface temperature of the gridcell.

my version kiehl figure 1 all land cancellationFigure 3. As in Figure 2, but showing only the land. N=1,320.

Well, this shows that whatever might be happening in the Indonesian Region in the way of a linear relationship between reflected shortwave and longwave, it is definitely NOT happening over the land. The land shows little in the way of any relationship between shortwave and longwave.

Figure 4 shows the ocean data for the same Indonesian region.

my version kiehl figure 1 all ocean cancellationFigure 4. As in Figure 2, but showing only the ocean. Note that the scale is slightly larger, to include all of the individual data. N=17,736

Well, this clarifies matters somewhat. First, about 40% of the land gridcells, but only about 10% of the ocean gridcells, have longwave cloud forcing greater than the shortwave forcing. Next, the land is pretty tightly clustered, with no apparent pattern. The ocean is different. Over the ocean the longwave is proportional to the shortwave … but it is a long ways from cancelling out. Instead, there’s a net cooling of -13.7 watts per square meter over the region. And the amount of cooling increases as the forcings increase. By the time the cloud reflections are up to 100 W m-2, the longwave is only up to 75 W m-2. That is a cooling from the clouds of about 25 W/m2, and not a cancellation under any meaning of the word.

In addition, there are a number of the warmest gridcells (red) which are on the left of the group (lots of reflection, little longwave).

Kiehl goes on to show his Figure 2, which compares the entire tropical Pacific region, from 10N 140E to 10S 90W. He shows a different kind of graph for this region, viz:

kiehl figure 2 cancellationFigure 5. Kiehl Figure 2, showing the longwave and shortwave cloud forcing separately as functions of temperature.

Based on this graph, he makes the even more expansive claim that the cancellation of long-and shortwave radiation occurs across the Pacific, viz:

This figure illustrates that the cancellation between these two forcings occurs not only in the western tropical Pacific region of Fig. 1 but also across the entire tropical Pacific Ocean region. Even in regions of colder SSTs (298 K) the cancellation is apparent.

I found his style of graph in Figure 2 to be notably uninformative regarding the purported Pacific-wide cancellation. So I repeated his Figure 1 style of graph using the Pacific data, to see whether the forcings actually cancelled all across the Pacific. Figures 6 and 7 shows that result, for land and ocean, and reveals that there are large problems with this second claim as well.

my version kiehl figure 2 all land cancellationFigure 6. As in Figure 2, but covering a larger area, the entire tropical Pacific Ocean as specified in the title. This figure shows land only. N=348.

Again, there is no clear pattern over the land, merely a cluster of data.

my version kiehl figure 2 all ocean cancellationFigure 7. As in Figure 6, but covering ocean only. Note the slightly larger scale than in Figure 4. N=63,132.

This actually is pretty interesting. First off, again the ocean and land are different, with the land results clustered as in the Indonesian Region. Regarding the ocean, in only 5% of the gridcells does the longwave ever exceed the shortwave (area above the central diagonal line). In order for Kiehl’s cancellation hypothesis to be true, the average of a number of gridcells over an area would have to fall on the central diagonal line … which is clearly impossible with only 5% of them above the line.

Nor do things get better when we look at the entire dataset, and not just the April data. Figure 8 shows all of the data for the Pacific-wide area shown in Figure 7 (ocean only).

my version kiehl figure 2 all months ocean cancellationFigure 8. All months of data for the Pacific-wide area as in Figure 7

Next, rather than cancellation, there are a whole lot of gridcells where the longwave is smaller, and often much smaller, than the reflected shortwave. When there is solar reflection of a hundred watts per square metre, the longwave is only around sixty watts per square metre, for a full 40 W/m2 of cooling. And even on average the cooling is nearly 20W/m2 … not what we call cancellation on my planet.

Finally, his claim that “Even in regions of colder SSTs (298 K) the cancellation is apparent” is not upheld by the data. The temperature of 298 K [25°C] is shown in blue in Figure 7, and it is the farthest from cancellation of any of the data.

CONCLUSIONS

The main result is that the CERES data clearly and emphatically falsifies the cancellation hypothesis. In general, the longwave and shortwave are far from cancelling each other in the tropical deep convective areas.

A secondary result is that this clearly shows how the politicization of the field has affected the scientific process. Kiehl’s claims were very tempting to the theorists and modelers, because cancellation meant that they didn’t have to concern themselves with the deep convective processes, aka thunderstorms—the could simply repeat Kiehl’s claim that the shortwave and longwave cancelled each other out. And as a result, when more detailed data became available, the original claims of Kiehl1994 were never questioned.

Now, all we need is some automated method to notify the 129 people who cited the cancellation hypothesis in other scientific papers that the rumored cancellation has been cancelled for the duration …

All the best,

w.

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Titan28
December 30, 2013 8:22 pm

Wonderful work & a great way to start off the new year.

Crispin in Waterloo
December 30, 2013 8:39 pm

My compliments, Willis.
This is a data-based confirmation validating your hypothesis moving it to a fully-fledged theory. The cooling effect is so strong that it can be seen on infrared camera trained on a storm path. CERES provides the data and your calculations the methodology.
You should at least write a a Letter to the Journal.

December 30, 2013 8:44 pm

Sciences prizes are given to all the wrong people these days.

December 30, 2013 8:57 pm

Talented amateurs such as yourself should consider writing a paper for peer review and publishing in a journal such as Nature. There have been many amateur scientists who advanced knowledge, no reason I can see for you to not to attempt to join their legion.

December 30, 2013 8:58 pm

Typos abound, sorry about that, no way to edit once posted!
[Fixed. -w.]

Pathway
December 30, 2013 9:13 pm

Excellent analysis.

bones
December 30, 2013 9:15 pm

Willis, that is a great piece of work that needs to be widely distributed and published in a peer reviewed journal. It needs to be in a place where it can’t be ignored or casually dismissed as the work of a loathsome “denier”.

John gardner
December 30, 2013 10:07 pm

Greetings from Oz. Excellent article, Willis, which seems to fairly demolish the fudged claim by Kiehl. I also agree with your thoughts re publishing in peer reviewed journals vs WUWT, despite the high likelihood that the Other Side will use it against you anyway. However, as you say, the outcome you want is to make the article available in a timely (and unimpeded?) manner to All those interested in this field, not just a select few. Great work, please Soldier On!

December 30, 2013 10:17 pm

Confirmation bias trumps intuition. Furthermore climatologists rarely have good intuition…

Lance Wallace
December 30, 2013 10:23 pm

1. Is there a reason why only April is considered?
2. You conclude that the longwave and shortwave do not cancel. Can you expand on your conclusion? What effect does the 20 W/m2 cooling have on the CAGW claims, or on the energy balance calculations?

RockyRoad
December 30, 2013 10:32 pm

Another nail in the coffin of “Global Warming” as imagined by the Warmistas.
Those on “The Team” should be completely embarrassed by now.
Good work, Willis! A most enjoyable read!

lee
December 30, 2013 10:43 pm

Lance Wallace says:
December 30, 2013 at 10:23 pm
1. Is there a reason why only April is considered?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Perhaps to rightfully compare the data.

December 30, 2013 10:57 pm

I partularly like the way you linked the (now falsified) Kiehl94 Cancelation Hypothesis to making the Global Climate Models simple enough to be constructed.
If Kiehl94 is falsified, then the GCMs are falsified. Replacement GCM must be made so complex the compute power would need to increase explosively, if chaos doesn’t make them impossible in theory. The computer waste heat alone might be a significant source of Global Warming 😉

climateace
December 30, 2013 11:11 pm

Willis
If recall correctly, in your last post you pointed out, giving a variety of reasons, that monthly averages were suspect. Yet the basis of this article is monthly averages.
You might, while you are having a look at the CERES data, have a look at the discrepancy between expectations about the nexus between lightning frequency and increasing temperatures, and what is happening. It seems to me that something is amiss.

john robertson
December 30, 2013 11:21 pm

Nice work,clouds matter. Does this mean those papers citing this work now get a note attached ?
Danger assumption no longer valid?
Seriously how does that work?

jorgekafkazar
December 31, 2013 12:00 am

Nice one, Willis! Very well done.

Greg
December 31, 2013 12:17 am

Good work Willis.
My first question of seeing their fig 1 is why only one month of one year to draw conclusions that will be applied to models trying to hindcast and forecast CENTURIES of climate. I smell the foul odour of selection bias is lurking nearby.
“Instead of one single month’s data, I’ve used the averages of the ten Aprils in the CERES dataset.”
A fine way to get a broader look than one year spot reading. Now what effect does selecting a different month make?
Is this cherry picking ? Much of this seems to relate to their previous paper from which fig 1 was drawn.
From your fig 4 I would say the cooler end of the range (blue) look fairly linear though certainly not 1:1 ratio. The warmer end looks decidely non-linear , with LW becoming less and less as the magitudes rise.
This would support your claim that the overall feedback effect is non linear.
The hot end of the pacfic data seems to be about the same though it is impossible to tell what the blue dots show in fig 7 since they are pretty much masked by the warm data. Maybe you need to break them out to a separate graph.

Greg
December 31, 2013 12:31 am

Their 1990 paper from which most of the thinking derives.
www-ramanathan.ucsd.edu/files/pr53.pdf‎

Greg
December 31, 2013 12:49 am

Their 1990 paper is worth reading. It takes a much more thorough look. However, I do not find anything resembling their fig 1 which is claimed to come from that paper.
“Any change in climate which affects the relative distributions of these could types will change the cloud forcing , especially in the tropics.”

Stephen Richards
December 31, 2013 12:56 am

I know Eistein said that science lacked common sense BUT really one can feel the difference on a cloudy day.

Greg
December 31, 2013 1:02 am

Sorry , that’s not the right 1990 paper though it includes Ramanathan.
http://onlinelibrary.wiley.com/doi/10.1029/JD095iD08p11679/abstract;jsessionid=B0E0E9942C33A4AE438E70D67588B781.f01t02
“the Indonesian region where deep convection is present, we consider the statistical correlation between the longwave cloud forcing and the shortwave cloud forcing from the ERBE data and CCM. Results indicate a near cancellation between the SWCF and LWCF for these regions, whereas the model predicts a net cooling. Another major area of discrepancy is over the North Atlantic and Pacific oceans where ERBE shows that clouds significantly reduce the solar heating of the oceans. While the model simulates this cooling, the magnitude is underpredicted by more than a factor of 2.”
Since the claimed cancellation (which is actually that near to cancelling) is based on one month of one year. I doubt the objectivity of applying that result for all months. The prev. paper I linked shows huge variation across the year.

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