Fog and rain in the Amazon.
The diurnal and seasonal water cycles in the Amazon remain poorly simulated 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 difference is attributed to the representation of the morning fog layer, and to more 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 season, dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of the surface 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.
Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY 10964; Department of Earth and Environmental Sciences, Columbia University, New York, NY 10027; pg2328@columbia.edu uanber@ldeo.columbia.edu.
Usama
U
Anber
Department of Earth and Environmental Engineering and Earth Institute, Columbia University, New York, NY 10027; pg2328@columbia.edu uanber@ldeo.columbia.edu.
Pierre
P
Gentine
Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027.
Shuguang
S
Wang
Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY 10964; Department of Earth and Environmental Sciences, Columbia University, New York, NY 10027; Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027.
Adam H
AH
Sobel
Amazon; cloud-resolving models; fog; hydrologic cycle; land−atmosphere interactions