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On the connection between continental-scale land surface processes and the tropical climate in a coupled ocean-atmosphere-land system

  • Author(s): Ma, HY
  • Mechoso, CR
  • Xue, Y
  • Xiao, H
  • Neelin, JD
  • Ji, X
  • et al.
Abstract

An evaluation is presented of the impact on tropical climate of continental-scale perturbations given by different representations of land surface processes (LSPs) in a general circulation model that includes atmosphere-ocean interactions. One representation is a simple land scheme, which specifies climatological albedos and soil moisture availability. The other representation is the more comprehensive Simplified Simple Biosphere Model, which allows for interactive soil moisture and vegetation biophysical processes. The results demonstrate that such perturbations have strong impacts on the seasonal mean states and seasonal cycles of global precipitation, clouds, and surface air temperature. The impact is especially significant over the tropical Pacific Ocean. To explore the mechanisms for such impact, model experiments are performed with different LSP representations confined to selected continental-scale regions where strong interactions of climate-vegetation biophysical processes are present. The largest impact found over the tropical Pacific is mainly from perturbations in the tropical African continent where convective heating anomalies associated with perturbed surface heat fluxes trigger global teleconnections through equatorial wave dynamics. In the equatorial Pacific, the remote impacts of the convection anomalies are further enhanced by strong air-sea coupling between surface wind stress and upwelling, as well as by the effects of ocean memory. LSP perturbations over South America and Asia-Australia have much weaker global impacts. The results further suggest that correct representations of LSP, land use change, and associated changes in the deep convection over tropical Africa are crucial to reducing the uncertainty of future climate projections with global climate models under various climate change scenarios. © 2013 American Meteorological Society.

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