Wind estimation based on thermal soaring of birds

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.

From ecology to remote sensing: using animals to map land cover

“…As first proposed by Weinzierl et al. () in the field of atmospheric simulation, our study suggests animals are useful sensors and we showed they can also provide valuable ground‐truth data for remote sensing‐based land cover classification. We mapped agricultural land over three test regions (R1, R2, R3) based on White Stork movement data and achieved high accuracies in R1 and R3.…”

Vultures respond to challenges of near-ground thermal soaring by varying bank angle

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Where eagles soar: Fine‐resolution tracking reveals the spatiotemporal use of differential soaring modes in a large raptor

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