期刊
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
卷 11, 期 8, 页码 2523-2546出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2019MS001650
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资金
- NASA [NNX14AI52G]
- Department of Energy [DE-SC0014438]
- National Science Foundation [AGS-1049041]
- National Science Foundation Science and Technology Center for Multi-Scale Modeling of Atmospheric Processes (CMMAP) [ATM-0425247]
- NASA [682404, NNX14AI52G] Funding Source: Federal RePORTER
- U.S. Department of Energy (DOE) [DE-SC0014438] Funding Source: U.S. Department of Energy (DOE)
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.
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