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Wind estimation based on thermal soaring of birds

机译:基于鸟类热腾腾的风估计

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摘要

Abstract The flight performance of birds is strongly affected by the dynamic state of the atmosphere at the birds' locations. Studies of flight and its impact on the movement ecology of birds must consider the wind to help us understand aerodynamics and bird flight strategies. Here, we introduce a systematic approach to evaluate wind speed and direction from the high-frequency GPS recordings from bird-borne tags during thermalling flight. Our method assumes that a fixed horizontal mean wind speed during a short (18 seconds, 19 GPS fixes) flight segment with a constant turn angle along a closed loop, characteristic of thermalling flight, will generate a fixed drift for each consequent location. We use a maximum-likelihood approach to estimate that drift and to determine the wind and airspeeds at the birds' flight locations. We also provide error estimates for these GPS-derived wind speed estimates. We validate our approach by comparing its wind estimates with the mid-resolution weather reanalysis data from ECMWF, and by examining independent wind estimates from pairs of birds in a large dataset of GPS-tagged migrating storks that were flying in close proximity. Our approach provides accurate and unbiased observations of wind speed and additional detailed information on vertical winds and uplift structure. These precise measurements are otherwise rare and hard to obtain and will broaden our understanding of atmospheric conditions, flight aerodynamics, and bird flight strategies. With an increasing number of GPS-tracked animals, we may soon be able to use birds to inform us about the atmosphere they are flying through and thus improve future ecological and environmental studies.
机译:摘要鸟类的飞行性能受到鸟类所处位置的动态状态的强烈影响。飞行及其对鸟类运动生态的影响的研究必须考虑风,以帮助我们了解空气动力学和鸟类飞行策略。在这里,我们介绍了一种系统的方法,可在热疗飞行过程中根据鸟类携带的标签的高频GPS记录评估风速和风向。我们的方法假设,在短时间内(18秒,GPS固定为19个),在固定的水平平均风速下,沿着闭环具有恒定的转向角,这是散热飞行的特征,它将为每个随后的位置产生固定的漂移。我们使用最大似然法来估计漂移并确定鸟类飞行位置的风速和空速。我们还为这些GPS衍生的风速估算提供误差估算。我们通过将其风估计值与ECMWF的中分辨率天气再分析数据进行比较,并通过检查大量贴有GPS标签的迁徙鹳的紧密飞行中的成对鸟类的独立风估计,来验证我们的方法。我们的方法可提供准确无偏的风速观测值,以及有关垂直风和隆升结构的其他详细信息。否则,这些精确的测量是罕见且难以获得的,并且将拓宽我们对大气条件,飞行空气动力学和鸟类飞行策略的理解。随着越来越多的GPS追踪动物,我们也许很快就可以利用鸟类来告知我们它们所飞行的大气,从而改善未来的生态和环境研究。

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