Influence of Forest-Edge Flows on Scalar Transport with Different Vertical Distributions of Foliage and Scalar Sources
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Forest edges have significant impacts on flow dynamics and mass exchange across the forest–atmosphere interface. A better understanding of edge flows and scalar transport has implications for locating and interpreting eddy-covariance flux measurements over finite-size forests with edges. Here the large-eddy simulation module within the Weather Research and Forecasting model is deployed to study the influence of forest edges on flow dynamics and scalar transport for a range of vertical distributions of foliage and scalar sources/sinks. For plant canopies with a relatively dense trunk space, a strong in-canopy flow convergence develops near the leading edge, which dominates the flow dynamics and leads to distinct scalar concentration and flux patterns not only across edges but also across the forest–atmosphere interface for sources near the ground and lower part of the canopy. For plant canopies with a deep, sparse trunk space, a strong and long sub-canopy jet develops, leading to simpler features in flow dynamics and scalar transfer. A real case with scalar sources/sink distributions as simulated by a newly developed multiple-layer canopy module produces even more complex scalar concentration and flux patterns. The budget equations for scalars are also analyzed to quantify the contributions of different terms to scalar fluxes. Our results demonstrate that both the scalar source distributions and canopy structures should be considered when eddy-covariance flux measurements are made over finite-size forests with edges.
KeywordsForest canopy Forest edge Large-eddy simulations Scalar transport Weather Research and Forecasting model
We are grateful to two anonymous reviewers for their constructive comments which greatly improved the quality of this manuscript. We acknowledge support by National Science Foundation AGS under Grants #1419614. We would like to acknowledge high-performance computing support from Cheyenne ( https://doi.org/10.5065/d6rx99hx) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation.
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