An Assessment of Clear-sky Radiative Damping Rates and Their Implications for Climate Feedbacks
| Soden, Brian | UM/RSMAS |
The range of uncertainty in model predictions of climate sensitivity has remained largely unchanged for more than two decades. Establishing confidence in models requires their direct verification against observations. Because climate sensitivity is determined by the rate at which the top-of-atmosphere (TOA) radiative fluxes respond to a change in surface temperature (i.e., the rate of radiative damping), observations of the total-sky and clear-sky radiative fluxes, such as those measured by the Earth Radiation Budget Experiment (ERBE or CERES) provide an obvious starting point for testing climate models. Indeed, many previous studies have compared observed variations in the TOA radiation budget with those predicted from climate model simulations over a range of spatial and temporal scales. Thus the lack of progress in reducing uncertainty in model predictions of climate change is not attributable to a lack of comparisons between observations and models. Rather it reflects a more formidable challenge – namely, relating the observable variability in the climate system to the relevant feedback processes which determine its sensitivity under an externally-forced change. Much of this difficulty stems from the fact that a feedback, being defined as a partial derivative, is not directly observable. That is, we can not statistically manipulate the observations in such a way to insure that only one variable is changing. Because we can not isolate a feedback observationally, we instead are forced to look for ways in which the feedback processes manifest themselves in “observable” forms of natural climate variability, such as ENSO or the seasonal cycle. Of the previous studies which have compared observed variations in the TOA radiation budget with that predicted from climate model simulations, many have focused on the covariance between clear-sky outgoing longwave radiation (OLR) and surface temperature (Ts). Clear-sky OLR is of interest because of its strong dependence upon water vapor in the upper troposphere, the feedback from which plays a key role in model calculations of global warming. These studies have considered , in general, demonstrated consistency between the observed and model simulated variability of clear-sky OLR over a range of space and time scales which is reassuring. However, their relevance may be questioned unless one can establish a quantitative link between the observed covariance of clear-sky OLR with Ts and the climate feedback mechanisms that regulate its behavior under global warming; i.e., the feedbacks from Planck, lapse-rate and water vapor changes. And, more generally, one would like to establish the presence of such links across a range of observable climate variations. In this study, we build on previous work in this area to explore the extent to which observations of clear-sky radiative damping can constrain model predictions of climate sensitivity. The main objectives of this paper are: (1) To demonstrate a quantitatively consistent relationship between the observed rates of clear-sky radiative damping and that predicted from idealized calculations which assume a constant relative humidity feedback from water vapor; (2) To demonstrate the robustness of this relationship across a range of observable sources of natural climate variability; (3) To assess the consistency of these “observable” clear-sky radiative damping rates across a variety different climate models whose output was obtained from the Atmospheric Model Intercomparison Project (AMIP).
This poster will be displayed at the ARM Science Team Meeting.