Fully understanding the effects of aerosols on stratocumulus clouds is important in the climate change discussion. Low-level clouds have a significant cooling effect on the planet. In the 1970s Twomey showed that, all things being equal, by adding pollution (aerosols) to these clouds, they have a higher optical depth and thus reflect more of the incoming sunlight. This cools the surface more than the original cloud. However, things aren’t that simple; they rarely are in science. There are other effects that must be taken into account when looking at the effects of aerosols.

The work done by Guillaume S. Mauger and Joel R. Norris in Stratocumulus Sensitivity to Aerosols and Dynamics [May be behind paywall] is such an example. They attempt to find the causation behind the correlation between aerosol optical depth and cloud cover. The do this by looking at the stability of the boundary layer.

Abstract:

A new technique is presented for quantifying the impacts of aerosols on clouds while controlling for variations in meteorology. The recent work of Kaufman et al (2005a) has shown observational evidence for large aerosol effects on clouds. We present work that builds on these results by separating aerosol from meteorological effects on cloud forcing. The new technique uses parcel back-trajectories to account for differences in cloud history. Observations are obtained from the MODIS instrument aboard Terra, and are supplemented with ECMWF reanalyses. Geographic and seasonal biases are removed so that climatological variations cannot contribute to false correlations between aerosols and cloud properties. The present work is focused specifically on the stratocumulus cloud region of the Northeast Atlantic for June through August 2002, the season of maximum cloud cover. Trajectories are grouped into high and low terciles of aerosol optical depth (AOD) and cloud fraction (CF), and evaluated for systematic aerosol-meteorology correlations. Results show statistically significant differences in the meteorology of polluted versus pristine aerosol cases, indicating that variations in the dynamics are contributing to the observed correlation between aerosols and cloud forcing. Specifically, lower tropospheric stability (LTS) is shown to correlate significantly with both aerosol optical depth and cloud fraction. Resampling while holding LTS constant removes almost the entire aerosol-cloud correlation. We conclude that meteorological variations must be accounted for in assessing aerosol microphysical impacts on cloud forcing.

Remote sensing data have one huge advantange: they have lots and lots and lots of data. This makes finding correlations easy. However, the accuracy and precision of these measurements does not always agree with in situ measurements. For instance, cloud effective radius as measured from space is systematically lower than that measure by in situ measurements. (I don’t have the reference handy, but will look it up upon request.) The problem with remotely sensed data, in addition to the above, is that there is only a limited number of quantities that can be addressed; they are usually optical depth, liquid water path, and effective radius.

This gives no understanding of how the number of cloud droplets is evolving or how the “shape” of the cloud droplet spectrum has on the problem. While I agree that meteorological signals need to be addressed when discussing aerosol indirect effects, I think the authors make one big mistake. We can see the effects of aerosols on stratocumulus clouds. You can see them if you fly over them in an airplane (if you’re lucky), and you can see them in satellite imagery. Therefore, we know that these aerosol have an effect on the cloud albedo, and because they did not find a relationship between aerosol concentration and effective radius (a requisite for the aerosol indirect effect), that may be due to the inaccuracies in remotely sensed effective radius instead of a read phenomenon.

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