A Tropical Radiation and Cloud System Feedback Modulated by Sea Surface Temperature
August 25, 2011
Hosted by Graeme Stephens (Advisor), Sue van den Heever, Richard Eykholt (Physics)
A large domain, high resolution cloud system resolving model set up in the tropics over fixed sea surface temperatures (SST) of 298 K and 302 K and run to radiative convective equilibrium has been analyzed with the focus on well equilibrated, domain mean results. The Regional Atmospheric Modeling System (RAMS) is used. The model organizes into disturbed, convective and undisturbed, subsidence regions. The mean profiles of state variables such as temperature, relative humidity (RH), and convective mass flux are analyzed and found to depend on SST in both predictable and unpredictable ways. The characteristics of rain depend on SST such that higher surface temperatures produce greater variability in intensity and lesser frequency. Next, the large-scale mean state is used to understand the convective system-scale setup. A focus is on the controls in the undisturbed regions of the disturbed region, deep convective anvil detrainment. Upper tropospheric radiation, through diabatic convergence, is used as a paradigm to understand the height at which detrainment occurs. The dependence of upper tropospheric radiation on RH is derived explicitly for the first time. From this new equation, temperature and RH are found to control anvil detrainment. The addition of RH as an anvil detrainment control explains why the model leads to an understanding of cooler anvils with higher SST â€“ a positive climate feedback on the system. Other anvil feedbacks exhibited by the model are similar to those proposed in the Iris and Thermostat hypotheses. The convective system components are shown to enhance one another such that the overall system dependence on SST is nonlinear. To understand the circulation system, a heat engine analogue is made that shows the warmer state is able to more efficiently circulate. Finally, observational evidence from Cloudsat and CALIPSO shows that some of the modeled results are also seen in nature.