GGrantIndex
← Search

Organized Turbulence over Forested Landscapes: Theoretical Basis for a Low-Dimensional Transport Model

$403,498FY2002GEONSF

Duke University, Durham NC

Investigators

Abstract

0208258 Albertson The need to understand the coupling between forested landscapes and turbulent fluxes of energy, water, and carbon has become a national priority, as evidenced by both the USGCRP's Water and Carbon Cycle Science Plans. Here, a conceptual model is proposed to describe turbulent transport of mass and energy between forest canopies and the atmosphere in terms of two end-member flow types: mixing layer (over dense vegetation) and rough walled boundary layer. Regions with varying degrees of sparse vegetation are represented as a superposition of the two end member regimes. The overarching goal is the development of a similarity theory for canopy sublayer (CSL) transport, where vertical transport phenomena are described by coupling high resolution surface features (that are readily observed remotely) and coarse resolution atmospheric fields (as both observed and modeled). The project is structured to test three hypotheses regarding the underpinnings of the conceptual model. The focus is on the interplay between canopy morphology and organized turbulent transport. Analysis of Field data is combined with Large, Eddy Simulation (LES) - with the data providing observations of field conditions and the LES providing a full view of the evolving structure of turbulence under controlled boundary conditions. The LES results will be used to identify the essential dynamics and to formulate signatures of the coherent structures that will be used to guide subsequent analysis of the field data sets. Multi-scale decompositions of the turbulence fields are to be used in concert with nonlinear time series analysis tools to begin the development of the low-dimensional model. This approach will provide a unique training experience for a graduate student and post-doc. The PI's will continue recruiting/training under-represented candidates.

View original record on NSF Award Search →