Surface-Atmosphere Coupling Scale, the Fate of Water, and Ecophysiological Function in a Brazilian Forest

This is the final verison. Available from American Geophysical Union (AGU) via the DOI in this record.The K83 observational data are available from AmeriFlux (ameriflux.lbl.gov), NCEP Reanalysis data provided by NOAA/ESRL/PSD, Boulder, Colorado, USA, from the http://www.cdc.noaa.gov/ website. Model code and output is stored at GitLab (gitlab.com). This project is password protected, and the password can be obtained from the corresponding author at [email protected] upon request.Tropical South America plays a central role in global climate. Bowen ratio teleconnects to circulation and precipitation processes far afield, and the global CO2 growth rate is strongly influenced by carbon cycle processes in South America. However, quantification of basin-wide seasonality of flux partitioning between latent and sensible heat, the response to anomalies around climatic norms, and understanding of the processes and mechanisms that control the carbon cycle remains elusive. Here, we investigate simulated surface-atmosphere interaction at a single site in Brazil, using models with different representations of precipitation and cloud processes, as well as differences in scale of coupling between the surface and atmosphere. We find that the model with parameterized clouds/precipitation has a tendency toward unrealistic perpetual light precipitation, while models with explicit treatment of clouds produce more intense and less frequent rain. Models that couple the surface to the atmosphere on the scale of kilometers, as opposed to tens or hundreds of kilometers, produce even more realistic distributions of rainfall. Rainfall intensity has direct consequences for the “fate of water,” or the pathway that a hydrometeor follows once it interacts with the surface. We find that the model with explicit treatment of cloud processes, coupled to the surface at small scales, is the most realistic when compared to observations. These results have implications for simulations of global climate, as the use of models with explicit (as opposed to parameterized) cloud representations becomes more widespread.National Aeronautics and Space Administration (NASA)National Science Foundation (NSF)National Science Foundation (NSF)U.S. Department of Energy (DOE