Daniel Klocke
Max Planck Institute for Meteorology
"Evaluating climate feedbacks in a GCM: focus on methods and clouds"
The sensitivity of earth climate to a given forcing depends highly on the acting of feedback mechanisms, which can dampen or amplify the climate response. The forcing and feedback strength depend to some degree on the chosen analyzing method. Those methods differ mainly on how accurately different feedback parameters get separated from each other and on the time scale on which feedbacks are separated from the forcing.
Cloud feedbacks contribute most to the inter model spread of climate sensitivity (IPCC, 2007). The cloud response is most sensitive to the chosen method as clouds respond on relatively short time scales to a forcing. This time scale is not necessarily the time scale of the change in surface temperature, on which the forcing/feedback concepts are based. This effect is analyzed with the Gregory method (Gregory, 2004), where top of the atmosphere (TOA) radiative fluxes are regressed against the change in surface temperature after quadrupling CO2. This method does not separate different feedbacks accurately. In the clear sky component of the radiative fluxes, feedbacks are not separable which is also valid for the traditionally used cloud radiative effect (CRE) leading to too small estimates of the cloud feedback. To separate feedbacks more accurately, the partial radiative perturbation (PRP) method is commonly used. Under the assumption of linearity and separability, partial derivatives of TOA radiative fluxes are calculated with respect to different model variables. Analyzing several years in a single climate model, the inter annual variability in cloud feedback strength is contributing most to the variability in the total feedback parameter, mostly caused by variability of the short wave component in the cloud feedback. Also geographical patterns stay robust, the (yearly globally averaged) cloud feedback parameter can vary substantially and change singe between years. In an unperturbed climate the CRE can vary between years up to the order of the cloud feedback. The presentation will focus on the peculiarities of the above mentioned methods, in form of their weaknesses and advantages, the temporal variability and the spatial distribution of feedback factors with special emphasis on cloud related processes.
Host: Anthony DelGenio Please note: this seminar will meet at GISS, in the 3rd Floor Conference Room, 2880 Broadway (Broadway and 112th Street)
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