Benestad (2016): A Mental Picture of the Greenhouse Effect

A recent post on touched on the question of what is the best simple mental model of the greenhouse effect that should be used to educate the public. Specifically, the author mentions that it is important to consider how convection affects the optical depth, in addition to the obvious role of radiative transfer. This led me to read the more thorough paper by Rasmus Benestad.

Benestad, R. E., 2016: A mental picture of the greenhouse effect. Theor. Appl. Climatol., doi:10.1007/s00704-016-1732-y.

There will never be an optimum conceptual model for describing the greenhouse effect, but I think there can be an optimized spectrum of conceptual models that address different levels of scientific literacy. This paper provides a conceptual model for the middle of that spectrum.

Benestad focuses on the top of atmosphere (TOA) energy balance following Hulbert (1931). Considering the TOA energy balance is a bit simpler than parsing out the details of the energy balance at the surface (e.g. Boer 1993), but they both involve the inherent complexity of moist convection and surface fluxes.

At the simpler end of the spectrum there is the ubiquitous “blanket analogy”, in which CO2 acts like a blanket to trap heat. Unfortunately, this analogy is inaccurate because a blanket (and a greenhouse) works primarily by blocking convection, and less so by absorption and emission of infrared (IR) radiation.

It seems a major motivation for writing this paper was to present a conceptual model that can easily explain the “warming hiatus” that has been one of the top talking points of skeptics for years now. The explanation of the hiatus that I hear the most is that heat is being stored in the deep ocean, which I find very compelling. But this Benestad paper takes a different approach and uses a TOA-centric approach to show the lack of a hiatus.

The points of this paper are not really specific to CO2, but rather a more general way to think about greenhouse gases (GHG). I would summarize the main points of this conceptual model as follows:

  1. GHGs makes the atmosphere opaque to IR , which slows the cooling rate of the planet and raises the altitude of the effective emission level (i.e. the 254 K isotherm is the average bulk emission level for cloudy and clear regions).
  2. GHGs diffuses surface IR radiation from the surface, so that the TOA IR pattern resembled a smoothed pattern of the surface emission.
  3. GHGs direct some of the upward radiative heat flux back down towards the surface, which means that when GHG concentrations are increased other heat fluxs (e.g. convection) must increase to compensate.

Benestad includes 3 plots to illustrate each of these points. The first is simply the trend of the height of the 254 K temperature surface, which shows a slow steady rise, even through the “hiatus” period. This is a very useful metric since it is influenced by both the radiative heat flux and convective heat flux. So it is entirely plausible that the radiative flux could stagnate while the convective heat flux changes. The trend is 23 +/- 2 m/decade.

The second plot shows the spatial correlation between the TOA outgoing IR radiation and the temperature 2m above the surface. Based on point #2, a higher GHG concentration would make the TOA IR emission look less like the surface, which is exactly what we see!

The third figure shows a measure of the atmospheric overturning circulation in 3 different layers of the atmosphere. The obvious increase in this metric is consistent with an increase of convective heat fluxes (i.e. point #3).

I really like the point of view this paper puts forward, and I’m going to try and make use of it in the future. But I also feel that I could use a better way to describe the greenhouse effect to people who are less scientifically literate, which I would argue is the harder problem. Either way this paper is a step in the right direction.


2 thoughts on “Benestad (2016): A Mental Picture of the Greenhouse Effect

  1. Aaron

    Walter, where on earth is this? Is RH, cloud height and percent cloud cover averaged over the entire planet? Is there a diurnal or seasonal cycle or is this averaged out as well?

    1. Walter Post author

      There are a lot more details in the paper if you follow the link. I don’t think he did anything with cloud height or cloud cover, so I’m confused by your question, but either way the plots reflect monthly global average data with a 12 running mean applied to smooth out the seasonal cycle.


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