On Sensitivity Part II: Constraining Cloud Feedback without Cloud Observations

Guest Commentary by Karen M. Shell, Oregon State University

Link to Part I.

Clouds are very pesky for climate scientists. Due to their high spatial and temporal variability, as well as the many processes involved in cloud droplet formation, clouds are difficult to model. Furthermore, clouds have competing effects on solar and terrestrial radiation. Increases in clouds increase reflected sunlight (a cooling effect) but also increase the greenhouse effect (a warming effect). The net effect of clouds at a given location depends the kind of clouds (stratus, cumulus etc.), their distribution in the vertical and on which radiative effect dominates.

Not only is it difficult to correctly represent clouds in climate models, but estimating how clouds and their radiative effects will change with global warming (i.e., the cloud feedback) is very difficult. Other physical feedbacks have more obvious links between temperature and the climate variable. For example, we expect and have strong evidence for the increase in water vapor in a warmer climate due to the increased saturation specific humidity, or the reduced reflection of sunlight due to the melting of snow and ice at higher temperature. However, there isn’t a simple thermodynamic relationship between temperature and cloud amount, and the complexities in the radiative impacts of clouds mean that an increase in clouds in one location may result in net heating, but would correspond to a cooling elsewhere. Thus, most of the uncertainty in the response of climate models to increases in CO2 is due to the uncertainty of the cloud feedback.

So how cool is it then that the recent paper by Fasullo and Trenberth estimates the net climate sensitivity without getting into the details of the cloud feedback then? Quite cool.

Figure 1 from Soden and Held (2006) showing ranges for each model for each of the key atmospheric feedbacks for the CMIP3 models.

The complexity of the cloud feedback means that it is difficult to observe and evaluate. Ideally, we would have accurate global observations of clouds for a number of decades to compare to the climate models. However, without that, we have to estimate cloud feedbacks using the shorter high-quality observational record, and then try to relate the short-term behavior to long-term (century-scale) cloud feedbacks. For some feedbacks, such as the water vapor and ice-albedo feedbacks, there has been some success in evaluating models directly using observations. For example, the modeled water vapor feedback in response to the eruption of Pinatubo agrees with the satellite data (Soden et al., 2002), while modeled Northern Hemisphere (NH) snow and sea-ice feedbacks underestimate the observed feedback (Flanner et al., 2008). Evaluation of cloud feedbacks has been less successful, due to the difficulty of obtaining homogenous global cloud properties from either satellite or surface-based observations. Many assumptions (such as for cloud droplet size or vertical distribution) must be made for these retrievals, and instrument and calibration errors may still be significant. Additionally, there isn’t an obvious correspondence of the short-term cloud behavior with the long-term behavior in climate models (Dessler, 2010; Masters, 2012).

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References

  1. J.T. Fasullo, and K.E. Trenberth, "A Less Cloudy Future: The Role of Subtropical Subsidence in Climate Sensitivity", Science, vol. 338, pp. 792-794, 2012. http://dx.doi.org/10.1126/science.1227465
  2. B.J. Soden, and I.M. Held, "An Assessment of Climate Feedbacks in Coupled Ocean–Atmosphere Models", Journal of Climate, vol. 19, pp. 3354-3360, 2006. http://dx.doi.org/10.1175/JCLI3799.1
  3. B.J. Soden, "Global Cooling After the Eruption of Mount Pinatubo: A Test of Climate Feedback by Water Vapor", Science, vol. 296, pp. 727-730, 2002. http://dx.doi.org/10.1126/science.296.5568.727
  4. M.G. Flanner, K.M. Shell, M. Barlage, D.K. Perovich, and M.A. Tschudi, "Radiative forcing and albedo feedback from the Northern Hemisphere cryosphere between 1979 and 2008", Nature Geoscience, vol. 4, pp. 151-155, 2011. http://dx.doi.org/10.1038/ngeo1062
  5. A.E. Dessler, "A Determination of the Cloud Feedback from Climate Variations over the Past Decade", Science, vol. 330, pp. 1523-1527, 2010. http://dx.doi.org/10.1126/science.1192546
  6. T. Masters, "On the determination of the global cloud feedback from satellite measurements", Earth System Dynamics, vol. 3, pp. 97-107, 2012. http://dx.doi.org/10.5194/esd-3-97-2012