Abstract
The influences of forests on the large-scale macroclimate are now established. Through albedo, evapotranspiration, surface roughness, and aerosols, forests influence the climate at large spatial scales. Forest influences on the local microclimate are also being recognized, and forests provide microclimatic refugia to buffer organisms against planetary warming. However, the scientific tools used to study forest influences on climate fail to account for forest microclimates. Earth system models are an important tool to inform land-use policy to mitigate planetary warming. With their big-leaf parameterization of plant canopies, however, the models are not vertically-resolved and do not simulate forest understories. Remotely sensed land surface temperature, another primary research tool to distinguish forest influences from other land cover, differs from the air temperature above and within forests. Multilayer canopy models have received renewed interest over the past several years and are a means to both improve the surface flux parameterizations and simulate vertical profiles within and above plant canopies. We present results of a comparison between the Community Land Model (CLM) multilayer canopy model and observations of air temperature, specific humidity, wind speed, and fluxes (net radiation, sensible heat, latent heat, momentum) taken at multiple heights in a walnut orchard during the Canopy Horizontal Array Turbulence Study (CHATS) from mid-March to mid-June 2007. The dataset provides a benchmark standard with which to test multilayer canopy models. Our model-data comparison highlights the potential of multilayer models to simulate the complex micrometeorology of forest canopies and also points to further research needs.
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