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

数值天气预报模型对于恶劣天气和空气质量预报以及河流流量、风能、农业和粮食安全的管理都变得不可或缺。近地面天气参数的模型结果通常直接或经统计后处理提供给最终用户。为了产生更可靠的数值天气预报，必须解决两个主要问题：（i）数值分辨率和（ii）塑造当地天气的近地面条件的表示。虽然计算的进步使数值天气预报模型能够更好地表示真实的世界条件，但表示详细的植被冠层-大气相互作用仍然是一个挑战。这在一定程度上是由于不同尺度上的冠层不均匀性，其变化显著影响了近地面区域的大气。这一近地表区域是无数相关气象过程的宿主，如雾、霜、露和湍流，如果不考虑这些因素，可能会扭曲天气预报。为了解决当前数值天气预测模型的这一局限性，该研究项目的重点是了解和量化植被冠层异质性的影响，并开发新的方法来在数值天气预测模型中正确地解释它们。这将通过风洞测量和高分辨率数值模拟的协同作用来实现。与所获得的数据，新的冠层表示将制定扩展后，目前在数值天气预报模型中使用的传统关系，以便在植被冠层流的时空变化可以很好地捕捉。这项研究计划将提高理解和代表性的冠层-大气相互作用的异质冠层覆盖。在数值天气预报模型中更好地表示树冠将导致更准确的天气预报。该研究项目还为研究生提供学习经验，并涉及STEM领域代表性不足的本科生。PI制定了一项计划，涉及与犹他州大学的难民计划合作，以增加学术界代表性不足的少数民族的数量。

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.