by Judith Curry
Circa 2003-2005, we had the “hockey wars”. In 2005-2006, we had the “hurricane wars”. It looks like this is the season for “cloud wars.”
Stephanie Pappas at Environment on msnbc.com provides a good overview of the summer cloud wars:
Call it the Cloud Wars. In the largely political debate over global warming, the role of clouds in the climate system is a perennial topic of argument. Basic research — such as a recent early investigation of the effect of cosmic rays on cloud formation — gets taken out of context, used to support arguments far beyond its scope. Climate blogs blow up with angry back-and-forth banter. As soon as it simmers down, another controversial paper restarts the cycle yet again.
The paper provides good, basic background information on the controversies surrounding the impacts of clouds on climate.
The various climate “wars” are characterized by papers on a timely topic receiving substantial attention in the MSM and the blogosphere, often with a “windshield wiper” effect (Revkin’s term) going back and forth with each paper from opposing sides in the debate. Pappas’ article reflects journalistic maturity in dealing with “wars.” Most of the papers in these wars are not of fundamental scientific importance, in the sense that they will stand the test of time and garner a substantial number of scientific citations [the CERN papers will certainly stand the test of time]. Rather, most of these papers achieve a brief period of fame via press release, blogospheric flame wars, and MSM attention, which dissipates fairly quickly in most instances, unless the the paper becomes immortalized by the IPCC (e.g. MBH).
Cloud radiative effect
There is a new paper by Richard Allen on the cloud radiative effect, which is a solid contribution to the literature. Before discussing that paper, I would to clarify some misunderstandings surrounding “cloud forcing” and “cloud feedback.” This very common confusion was evident in the original WUWT post on this subject (see the comments in that thread).
For those of you that are confused by the terminology and can handle partial derivatives, I recommend Chapter 13 from my text Thermodynamics of Atmospheres and Oceans, specifically 13.4 on Cloud Radiation Feedback. Here is an attempt at an excerpt, minus the equations:
Changes in cloud characteristics induced by a climate change would modify the radiative fluxes, thus altering the surface and atmospheric temperatures and further modify cloud characteristics. The feedback between surface temperature, clouds, and the Earth’s radiation balance is referred to as the cloud-radiation feedback.
To the extent that the net radiative flux at the top of the atmosphere is linearly related to cloud fraction, the sensitivity term can be related to a parameter called the cloud-radiative effect. [Footnote: The term “cloud forcing” is typically used to refer to the cloud-radiative effect. We believe that the word “force” is a misnomer for this effect.]
The cloud-radiative effect is defined to be the actual radiative flux (which depends on cloud amount) minus the radiative flux for cloud-free conditions, all other characteristics of the atmosphere and surface remaining the same. The values of the cloud-radiative effect are negative for cooling and positive for warming. The cloud-radiative effect is most often defined in the context of the net radiative flux at the top of the atmosphere, although the cloud-radiative effect can also be defined in the context of the surface radiative flux. In addition, we can separate the cloud-radiative effect into longwave and shortwave components.
The cloud-radiative effect provides information on the overall effect of clouds on radiative fluxes, relative to a cloud-free Earth. The cloud- radiative effect can be evaluated exactly using a radiative transfer model, where fluxes obtained from a calculation for a cloud-free but otherwise exactly similar atmosphere is subtracted from a calculation for the actual cloudy atmosphere. Determination of the cloud-radiative effect from satellite is accomplished by separating the clear from the cloudy observations. In spite of the simplicity of evaluating the cloud-radiative effect at the top of the atmosphere using satellite data, such evaluations are somewhat ambiguous. Ambiguities arise since the distinction between clear and cloudy regions is not always simple (particularly in polar regions) and because other characteristics of the atmosphere (e.g., water vapor amount, atmospheric and surface temperature) change in cloudy versus clear conditions, even in the same location.
Table 13.1 provides some estimates of the mean annual global cloud radiative forcing at the top of the atmosphere. Clouds reduce the longwave emission at the top of the atmosphere since they are emitting at a colder temperature than the Earth’s surface. At the same time, clouds decrease the net shortwave radiation at the top of the atmosphere because clouds overlying the earth reflect more shortwave radiation than does the cloud-free earth-atmosphere. Because of the partial cancellation of these effects, the net cloud-radiative effect has a smaller magnitude than either the individual longwave or shortwave terms. Both satellite and model estimates agree that the net cloud-radiative effect at the top of the atmosphere is negative and that shortwave effect dominates, i.e. that clouds reduce the global net radiative energy flux into the planet by about 20 W m-2.
Table 13.1. Estimates of the mean annual, globally averaged cloud radiative effect (W m-2) at the top of the atmosphere derived from satellite observations and general circulation models.
Basis Investigation CFLW CFSW CFnet
satellite Ramanathan et al 1989 31 -48 -17
satellite Ardanuy et al. 1991 24 -51 -27
models Cess and Potter 1987 23 to 55 – 45 to -75 -2 to -34
Combining satellite data and models to estimate cloud radiative effect at the surface and in the atmosphere
Richard P. Allan
Abstract: Satellite measurements and numerical forecast model reanalysis data are used to compute an updated estimate of the cloud radiative effect on the global multi-annual mean radiative energy budget of the atmosphere and surface. The cloud radiative cooling effect through reflection of short wave radiation dominates over the long wave heating effect, resulting in a net cooling of the climate system of -21 Wm-2. The short wave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of -53 Wm-2. Clouds impact long wave radiation by heating the moist tropical atmosphere (up to around 40 Wm-2 for global annual means) while enhancing the radiative cooling of the atmosphere over other regions, in particular higher latitudes and sub-tropical marine stratocumulus regimes. While clouds act to cool the climate system during the daytime, the cloud greenhouse effect heats the climate system at night. The influence of cloud radiative effect on determining cloud feedbacks and changes in the water cycle are discussed.
Overall, I find this paper to be a useful addition to the literature on this subject. Here is what I like about the paper:
- the paper is clearly written and provides a good historical overview of the topic
- cloud radiative effects at both the top of atmosphere and surface are considered; the surface effects are important in the context of understanding feedbacks in the coupled system (not just the atmopshere, but also the land, oceans, and cryosphere).
- a careful job has been done in analyzing the satellite data, and a novel approach is provided for determining the surface radiative fluxes
- the results are interpreted in terms of variations with latitude, over the diurnal cycle, and interannual variations. No surprises here, but they provide a nice overview.
My only objection to the paper is that it is lacking any kind of an uncertainty analysis. The results of the top of atmosphere cloud radiative effect are not surprising, they fall within the range of previous studies as outlined in Table 13.1 from my text.
JC conclusions: Clouds and their feedbacks are arguably the source of greatest uncertainty in climate model simulations. The sources of uncertainty range from interactions of atmospheric aerosols in the water/ice nucleation process to unresolved turbulent and convection scales in the climate models. Good progress is being made on the treatment of cloud microphysical processes in climate models (including interactions with aerosols). Stochastic cloud parameterizations are the source of some progress in dealing with unresolved scales of motions, as is increasing the resolution of climate models. But the uncertainty surrounding cloud feedbacks is not going to go away soon. Studies such as Allan’s help the targets for evaluating climate model simulations.