Collaborative Research: Unfolding the Link between Forest Canopy Structure and Flow Morphology: A Physics-based Representation for Numerical Weather Prediction Simulations

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Numerical weather prediction models are becoming indispensable for severe weather and air quality forecasts as well as for managements in river flows, wind energy, agriculture, and food security. Model results of near-surface weather parameters are routinely supplied to end-users either directly or with statistical post-processing. To produce more reliable numerical weather predictions, two main issues must be addressed: (i) numerical resolution and (ii) representation of the near-surface conditions that shape the local-weather. While advances in computation are enabling a better representation of real world conditions in numerical weather prediction models, representing the detailed vegetated canopy-atmosphere interactions remains a challenge. This is partially the result of canopy heterogeneities present at different scales whose variability significantly affects the near-surface region of the atmosphere. This near-surface region is host to a myriad of relevant meteorological processes such as fog, frost, dew, and turbulence in general, which if not accounted for, can distort weather forecasts. To tackle this limitation of current numerical weather prediction models, the focus of this research project is on understanding and quantifying the effect of vegetated canopy heterogeneities and developing new methodologies to properly account for them within numerical weather prediction models. This will be achieved through the synergy of wind tunnel measurements and high-resolution numerical simulations. With the acquired data, new canopy representations will be formulated that expand upon traditional relationships currently used in numerical weather prediction models such that the spatiotemporal variability of the flow in vegetated canopies can be well captured. This research project will improve the understanding and representation of the canopy-atmosphere interactions on a heterogeneous canopy cover. A better representation of canopies within numerical weather prediction models will lead to more accurate weather forecasts. This research project also provides learning experiences to graduate students and involves underrepresented undergraduate students in the STEM fields. The PIs lay out a plan that involves collaborations with the REFUGES program at University of Utah to increase the number of underrepresented minorities in academia.