Tropical Water Vapor and Cloud Feedbacks in Climate Models: A Further Assessment Using Coupled Simulations by De-Zheng Sun, Yongqiang Yu, and Tao Zhang

There is  a very important new weblog on water vapor and cloud feedbacks within the climate system as represented by the models used to project multi-decadal climate change. The paper is

Sun, D.-Z., Y. Yu, and T. Zhang, 2007: Tropical Water Vapor and Cloud Feedbacks in Climate Models: A Further Assessment Using Coupled Simulations. J. Climate, Submitted. [a powerpoint talk of this research was completed for my class last spring (see Validating and Understanding Feedbacks in Climate Models).

The abstract reads,

By comparing the response of clouds and water vapor to ENSO forcing in nature with that in AMIP simulations by some leading climate models, an earlier evaluation of tropical cloud and water vapor feedbacks has revealed two common biases in the models: (1) an underestimate of the strength of the negative cloud albedo feedback and (2) an overestimate of the positive feedback from the greenhouse effect of water vapor. Extending the same analysis to the fully coupled simulations of these models as well as to other IPCC coupled models, we find that these two common biases persist. Relative to the earlier estimates, the overestimate of the positive feedback from water vapor is alleviated somewhat for most of the models. Improvements in the simulation of the cloud albedo feedback are only found in the models whose AMIP runs suggest a positive or nearly positive cloud albedo feedback. The strength of the negative cloud albedo feedback in all other models is found to be substantially weaker than that estimated from the corresponding AMIP simulations. Consequently, all models analyzed in this study are found to have a weaker negative feedback from the net surface heating over the ocean than that indicated in observations. The weakening in the cloud albedo feedback is linked to a reduced response of deep convection over the equatorial Pacific which is in turn linked to the excessive cold-tongue in the mean climate of these models. The results highlight that the feedbacks of water vapor and clouds—the cloud albedo feedback in particular—depend on the mean intensity of the hydrological cycle. We have also examined whether the variations among models of the feedback from cloud albedo (water vapor) in the ENSO variability are correlated with the variations among models of the feedback from cloud albedo (water vapor) in global warming. While we find a weak positive correlation between the variations among models in the feedback of water vapor during ENSO and the variations among models in the water vapor feedback during global warming, we find no significant correlation between the variations among models in the cloud albedo feedback during ENSO and the variations among models in the cloud albedo feedback during global warming. We thereby suggest that the two common biases revealed in the simulated ENSO variability may not be carried over to the simulated global warming, though these biases highlight the continuing difficulty that models have to simulate accurately the feedbacks of water vapor and clouds on a time-scale we have observations.

The conclusion the paper has the text,

“The extended calculation using coupled runs confirms the earlier inference from the AMIP runs that underestimating the negative feedback from cloud albedo and overestimating the positive feedback from the greenhouse effect of water vapor over the tropical Pacific during ENSO is a prevalent problem of climate models. The estimates from the coupled simulations of both the cloud albedo feedback and the water vapor feedback differ from the estimates from the corresponding AMIP simulations. The changes in the cloud albedo feedback are particularly significant. The previous analysis of Sun et al. (2006) has suggested that the GFDL CM2 may have a cloud albedo feedback that is as strong as observations. The new estimate with the coupled runs puts this suggestion in doubt as the new estimate is significantly weaker than the previous estimate. All models we have examined in this analysis are found to have a weaker negative feedback from the net surface heating than that from observations, indicating that deep convection over the equatorial Pacific in the models has a weaker regulatory effect over the SST in that region. The differences between the values estimated from the coupled runs and the values estimated from the corresponding AMIP runs are shown to be linked to the excessive cold-tongue in the climatology in the coupled models.

The two common biases, shown in the ENSO cycle, however, do not appear to be carried over the global warming simulations. The variations in the cloud albedo feedback among different models are not correlated with the variations in the same feedback in the global warming simulations among different models. The variations in the water vapor feedback among different models during ENSO over the cold-tongue are positively correlated with the variations in the water vapor feedback during global warming, but the correlation is weak. There is no correlation between the feedbacks over the cold-tongue region during ENSO and the globally averaged feedbacks during global warming. Therefore, the overestimate of the water vapor feedback and the underestimate of the cloud albedo feedback during the ENSO cycle in the models do not necessarily imply that the sensitivity of the mean tropical climate to anthropogenic forcing is overestimated by the models. On the other hand, we are not suggesting that the prevalence of these two biases in the models during ENSO should not be of concern for the accuracy of global warming simulated by the models. This is because the lack of correlation in the models between the feedbacks on these two time-scales could be due to error cancellations in the models. In any case, the present results highlight the continuing difficulty that models have in simulating accurately the water vapor and cloud feedbacks in the deep tropics on the time-scale over which we have observations to compare with model simulations. The results should also be of value to the diagnosis of the causes of the biases in the ENSO amplitude in the models.”

An important conclusion from the Sun et al study is that “all models analyzed in this study are found to have a weaker negative feedback from the net surface heating over the ocean than that indicated in observations.”

The authors further state that

“We thereby suggest that the two common biases revealed in the simulated ENSO variability may not be carried over to the simulated global warming, though these biases highlight the continuing difficulty that models have to simulate accurately the feedbacks of water vapor and clouds on a time-scale we have observations”.

However it is not clear how such a bias could be removed when the models are applied in longer term model projections. Indeed, what is the data which says that the biases are removed?

FOLLOW UP

In order to obtain an answer to the above question, I contacted Dr. Sun with the following
“I have set for your paper to be weblogged on in a couple of weeks. However, I have a question on your conclusion that ‘We thereby suggest that the two common biases revealed in the simulated ENSO variability may not be carried over to the simulated global warming, though these biases highlight the continuing difficulty that models have to simulate accurately the feedbacks of water vapor and clouds on a time-scale we have observations’, however it is not clear how such a bias could be removed when the models are applied in longer term model projections. Indeed, what is the data which says that the biases are removed?

Please clarify and I can add to the weblog.”

REPLY FROM DR. SUN

“You are right that no data have shown that those biases will not be removed. We are just mentioning the possibility that there could be error cancellation as global warming may involve more processes that those in ENSO, and the errors may cancel in such a way that prediction of global warming by these models that have these errors may actually get the answer right.  It is just a possibility worth mentioning.”

The message from the Sun et al. study, therefore, is that the models used to make the multi-decadal global climate projections that are reported in the IPCC report are “…that underestimating the negative feedback from cloud albedo and overestimating the positive feedback from the greenhouse effect of water vapor over the tropical Pacific during ENSO is a prevalent problem of climate models.” 

This study indicates that the IPCC models are overpredicting global warming in response to positive radiative forcing.

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