Every winter I start thinking about the processes that lead to brutally cold air masses over regions far removed from the warming influence of the oceans…Siberia, interior Canada, etc. Temperatures in interior Alaska have been routinely dipping into the -50’s F over the last week or so. Europe has been hard hit by unusually cold weather, and Vladimir Putin decided this would be a good time to cut off natural gas supplies to a number of European countries.

As of this writing (January 9), it looks like the coldest temperatures in the Lower 48 are yet to come, as the coldest airmass over northwest Canada finds its way down into the central and eastern U.S. starting around next Wednesday (January 14) or so. Gee, where is global warming when you really need it?

The ‘scientific consensus’ is that these frigid air masses are the ones that should warm the most with manmade global warming. The reasoning goes that since they contain very little water vapor (Earth’s main greenhouse gas), the warming effect of the extra carbon dioxide should be proportionately greater there.

But what causes these air masses to get so cold in the first place? Well, little or no sunlight is the most direct reason, which means they radiatively cool to outer space without any solar heating to offset that infrared cooling.

But what limits how cold they can get? Why do these temperatures seldom fall below -60 or -70 deg. F….temperatures reached fairly early in the winter, but which then level off? The answer is mostly related to the water vapor content of the air.

There is an interesting issue of causation involved with these cold and dry air masses. Contrary to what some meteorologists think, the air doesn’t become dry because of the cold. If that was the case, the air would become continuously saturated with clouds and fog as it keeps cooling, rather than clear and relatively dry as is observed.

No, rather than being dry because it is cold, the air instead becomes cold because it is dry. And the reason the air is so dry is because it has been slowly sinking from high in the atmosphere, where there is very little water vapor. And why is THAT air so dry? Because precipitation processes have removed the water vapor as relatively warmer and moister air ascends in low pressure areas — snowstorms — which move around the periphery of the high pressure zones that are created by the strong cooling.

So, ultimately, it is precipitation processes in regions remote from these cold high pressure areas that mostly determine how cold surface temperatures will get. And since we have little understanding of how these precipitation processes in the upper atmosphere might change with ‘global warming’, there is (in my mind) more uncertainty about water vapor feedbacks than the IPCC has led us to believe.

I thought it would be interesting to examine the behavior of the coldest temperatures in the climate models that are tracked by the IPCC. Monthly gridded data are archived at PCMDI for transient CO2 simulations from these models, and we simply took the minimum monthly average temperature anywhere in the Northern Hemisphere for each month in the first 70 years of those simulations. Some of the results are shown in the figure below (note the temperature scaling is relative, not absolute). The red lines are 12-month running averages.

Across those 22 models, the minimum monthly temperatures warmed by an average of 0.43 deg. C per decade (0.77 deg. F per decade), which is somewhat less than double the average global warming rate in those models. Thus, the coldest air masses in the models do warm much faster than the global average temperature does.

Also, the average minimum monthly temperature for the first February across all 22 models was -50 deg. C (-58 deg. F), indicating that the models do indeed create very cold airmasses.

The model with the greatest rate of warming is also shown: the INM CM3.0 model warmed at an average of 0.80 deg. C per decade (1.44 deg. F per decade). The model with the least warming (actually, it had a zero warming trend) was the FGOALS 1.0, which is also the least sensitive of all the IPCC models analyzed by Forster & Taylor (2006 J. Climate).

What does all this mean for the theory of manmade global warming? How fast have these coldest airmasses warmed, compared to the IPCC models? Well, the location in Siberia that is traditionally the coldest, Ojmjakon, hit -60 deg. C (-76 deg. F) twice last month (December, 2008), a temperature that has been reached only one other time in the last 25 years. So, I suspect that global warming isn’t happening nearly fast enough for the folks who live there.

(Jan. 10 update: A few people seem to have missed the point of this satirical post. It is a counterpoint to Al Gore’s use of “millions of tons” when talking about CO2 emissions. I’m pointing out that relative to the total atmosphere, millions of tons of CO2 is miniscule. And even a 50% increase in a very small number [the CO2 content of the atmosphere] is still a very small number.)

Now that there have been 50 full years of atmospheric carbon dioxide concentration monitoring at Mauna Loa, Hawaii, I thought January1, 2009 would be an appropriate time to take a nostalgic look back.

As you well know from Al Gore’s movie (remember? It’s the one you were required to come to English class and watch or the teacher would fail your kid), we are now pumping 70 million tons of carbon dioxide into the atmosphere every day as if it’s an “open sewer”.

Well, 50 years of that kind of pollution is really taking its toll. So, without further ado, here’s what 50 years of increasing levels of CO2 looks like on the Big Island:

As you can see, there has been a rapid…what? You can’t see it?…oh, I’m sorry. It’s that flat line at the bottom of the graph…here let me change the vertical scale so it runs from 0 to 10% of the atmosphere, rather than 0 to 100%….

Now, as I was saying…you can see there has been a rapid increase…what? what NOW? You still can’t see it?? It’s that blue line at the bottom! Are you color deaf?

Obviously, you had too much to drink at the New Years party last night, and your eyes are a little blurry. Here, I’ll change the scale…AGAIN..to go from 0 to 1% of the atmosphere….

Now can you see it? Good. As I was saying, 50 years of carbon dioxide emissions by humanity has really caused the CO2 content of the atmosphere to surge upward. It might not look like much, but trust me, Mr. Gore says….

NOW what?? Carbon dioxide is what? Necessary for life on Earth?

What are you, some kind of global warming denying right-wing extremist wacko? The polar bears are drowning!!

I can see I’m just wasting my time…sheesh.

Back in 1997, Bob Cess (climate researcher, cloud expert) said in an interview with Science magazine’s Richard Kerr,

“…the [climate models] may be agreeing now simply because they’re all tending to do the same thing wrong. It’s not clear to me that we have clouds right by any stretch of the imagination.”

In the last year or so I have become convinced that this is indeed what has happened…..the models are all doing the “same thing wrong”. While I have addressed this before, I am going to continue to harp on this issue until one or more climate modelers finally has a light bulb go on in their head and says, “Ahhh…I see what you’re talking about now…”. The issue is critical, and could completely change our perception of the role of clouds in climate change.

First, though, a little background for the uninitiated. Modern climate change theory is all about radiative forcing (aka, radiative energy imbalance) of the climate system: Something causes either a change in the rate at which solar energy is absorbed by the Earth (for instance, a major volcanic eruption), or the rate at which the Earth emits infrared energy back to outer space (for instance, increasing atmospheric carbon dioxide concentrations). The resulting global average radiative energy imbalance then causes a temperature change. This part of the theory is seldom disputed.

But that temperature change, in turn, causes other elements of the climate system – clouds, water vapor, etc. – to also be altered, which then feeds back on the original temperature change by amplifying it (positive feedback) or reducing it (negative feedback). Those feedbacks are what will determine whether manmade global warming will be either lost in the noise of natural climate variability, or — as NASA’s James Hansen believes — catastrophic. Feedbacks in the climate system are much less certain than the radiative forcing from extra carbon dioxide.

All twenty climate models tracked by the IPCC now have positive cloud feedbacks, which is partly why they project so much global warming in the future. Obviously, we desperately need to know what cloud feedbacks are occurring in the real climate system. And since one needs global observations to do that, it can only be done (if at all) during the modern satellite era.

But some researchers now think the search for the feedback “Holy Grail” is a lost cause. This is partly because researchers get different answers depending on which years of satellite observations are analyzed.

But I think I have discovered why. The issue is not a new one to the climate research community, and it is really quite simple: In order to estimate radiative feedbacks, one must first remove any sources of radiative forcing present in the data.

This ‘radiative forcing removal’ technique has been performed before by Forster & Gregory (2006 J. of Climate) to estimate feedbacks during the global cooling which occurred after the 1991 eruption of Mt. Pinatubo. They removed an estimate of the radiative forcing caused by the volcanic aerosols in the stratosphere in order to estimate radiative feedbacks.

Similarly, Forster & Taylor (also 2006 J. Climate) removed anthropogenic radiative forcings from the output of 20 IPCC climate models in order to diagnose the radiative feedbacks operating in those models.

Well, what researchers haven’t accounted for is that there are natural cloud variations in the real climate system, and these also cause radiative forcing. So, in order to estimate feedbacks in the real climate system from satellite data, one would need to first remove those radiative forcings. Unfortunately, this is not easy because those forcings are somewhat chaotic…but, as I
show, they have distinctly different signatures in the data.

Because this ‘contamination’ of the feedback signature by internally-generated radiative forcing by clouds has never been taken into account before, diagnosed feedbacks have been both quite variable (depending upon the time period analyzed), AND they have been significantly biased in the direction of positive feedback.

The result has been the illusion of a sensitive climate system with positive cloud feedback….when in fact the satellite evidence, after accounting for this effect, reveals cloud feedbacks to be negative.

The article I posted here contains the details on all of this, including what I believe to be the most stringent test of climate model feedbacks ever performed. In it I present proof that this natural radiative forcing by clouds is strong, and ever-present…even in the climate models themselves!

I also provide the first evidence that the short-term feedbacks in the IPCC models are substantially the same as their long-term feedbacks in response to anthropogenic radiative forcing — a key finding if we are to ever apply our short-term satellite observations to the long-term global warming problem.

I challenge modelers to address this important issue, because the current, crude level of model testing has NOT been sufficient to validate feedbacks in climate models.

And yes, some of our early work on this issue has been published in the peer-reviewed literature (Spencer et al., 2007 GRL; Spencer & Braswell, November 1, 2008 J. of Climate). Unfortunately, our work is either being ignored or marginalized.

If anyone has a legitimate objection to my arguments in that article, or think something I’ve presented is not clear, e-mail me (see bottom of this page) and I will post your question and my reply here if I think it would be of general interest. I will not reply to comments or questions which are submitted anonymously.