Thedin Regis, Brandes David, Quon Eliot, Sandhu Rimple, Tripp Charles
National Renewable Energy Laboratory, Golden, CO, USA.
Lafayette College, Easton, PA, USA.
Mov Ecol. 2024 Mar 28;12(1):25. doi: 10.1186/s40462-024-00457-x.
Spatially explicit simulation models of animal movements through the atmosphere necessarily require a representation of the spatial and temporal variation of atmospheric conditions. In particular, for movements of soaring birds that rely extensively on vertical updrafts to avoid flapping flight, accurate and reliable estimation of the vertical component of wind is critical. The interaction between wind and complex terrain shapes both the horizontal and vertical wind fields, highlighting the need to model the coupling between local terrain features and atmospheric conditions at scales relevant to animal movement.
In this work, we propose a new empirical model for estimating the orographic updraft field. The model is developed using computational fluid dynamics simulations of canonical atmospheric conditions over moderately complex terrain. To isolate buoyancy and thermal effects, and focus on terrain-induced effects, we use only simulations of a neutrally stratified atmosphere to develop the model. The model, which we name Engineering Vertical Velocity Estimator (EVVE), is simple to implement and is a function of the underlying terrain elevation map, the desired height above ground level (AGL), and wind conditions at a reference height (80 m). We validate the model with data from the Alaiz mountain (Spain) field campaign.
Compared to observations, the proposed improved model estimates the updrafts at 120 m AGL with a mean error of 0.11 m/s ( m/s), compared to 0.85 m/s ( m/s) for its baseline. For typical land-based wind turbine hub heights of 80 m AGL, the proposed model has a mean error of 0.04 m/s ( m/s), compared to baseline 0.54 m/s ( m/s) estimations. We illustrate an application of the model in movement ecology by comparing simulated tracks and presence maps of golden eagles (Aquila chrysaetos) moving across two distinct landscapes. The tracks and presence maps are obtained using a simple heuristic-based movement model, with the updraft field given by the proposed model and a wind vector-based estimation approach that is currently in wide use in movement ecology studies of raptors and other soaring birds.
We highlight that movement model results can be sensitive to the underlying orographic updraft model, especially in studies of fine-scale movements in regions of complex topography. We suggest adopting the proposed model rather than the wind vector estimation method for studies of soaring bird movements.
动物在大气中运动的空间明确模拟模型必然需要表示大气条件的空间和时间变化。特别是对于广泛依赖垂直上升气流以避免振翅飞行的翱翔鸟类的运动，准确可靠地估计风的垂直分量至关重要。风与复杂地形之间的相互作用塑造了水平和垂直风场，这凸显了在与动物运动相关的尺度上对局部地形特征和大气条件之间的耦合进行建模的必要性。
在这项工作中，我们提出了一种用于估计地形上升气流场的新经验模型。该模型是利用对中等复杂地形上典型大气条件的计算流体动力学模拟开发的。为了分离浮力和热效应，并专注于地形引起的效应，我们仅使用中性分层大气的模拟来开发该模型。我们将该模型命名为工程垂直速度估计器（EVVE），它易于实现，并且是基础地形高程图、地面以上所需高度（AGL）以及参考高度（80米）处的风况的函数。我们使用来自西班牙阿拉伊斯山野外考察的数据对该模型进行了验证。
与观测值相比，所提出的改进模型估计120米AGL处的上升气流时平均误差为0.11米/秒（ 米/秒），而其基线模型的平均误差为0.85米/秒（ 米/秒）。对于典型的地面风力涡轮机轮毂高度80米AGL，所提出的模型平均误差为0.04米/秒（ 米/秒），而基线模型的估计误差为0.54米/秒（ 米/秒）。我们通过比较在两个不同景观中移动的金雕（Aquila chrysaetos）的模拟轨迹和存在地图，展示了该模型在运动生态学中的应用。轨迹和存在地图是使用基于简单启发式的运动模型获得的，上升气流场由所提出的模型给出，以及一种基于风矢量的估计方法，该方法目前在猛禽和其他翱翔鸟类的运动生态学研究中广泛使用。
我们强调运动模型结果可能对基础地形上升气流模型敏感，特别是在复杂地形区域的精细尺度运动研究中。我们建议在翱翔鸟类运动研究中采用所提出的模型而非风矢量估计方法。
