Modeling the Diurnal Cycle in the Amazon using the Weak Temperature Gradient Approximation
Usama Anber, Pierre Gentine, Shuguang Wang and Adam Sobel
The diurnal and seasonal water cycle in the Amazon remains improperly modeled in general circulation models, exhibiting peak evapotranspiration in the wrong season and rain too early in the day. We show that those biases are not present in cloud-resolving simulations with parameterized large-scale circulation. The improvements are attributed to the representation of the morning fog layer, and to accurate characterization of convection and its coupling with large-scale circulation. The morning fog layer present in the wet season but absent in the dry dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of surface radiation energy budget. These results highlight the importance of the coupling between the energy and hydrological cycles and the key role of cloud albedo feedback for climates over tropical continents.