Using high resolution GPS tracking data of bird flight for meteorological observations

Abstract

Bird flight is strongly influenced by local meteorological conditions. With increasing amounts of high-frequency GPS data of bird movement becoming available, as tags become cheaper and lighter, opportunities are created to obtain large datasets of quantitative meteorological information from observations conducted by bird-borne tags. In this article we propose a method for estimating wind velocity and convective velocity scale from tag-based high-frequency GPS data of soaring birds in flight. The flight patterns of soaring birds are strongly influenced by the interactions between atmospheric boundary layer processes and the morphology of the bird; climb rates depend on vertical air motion, flight altitude depends on boundary layer height, and drift off the bird’s flight path depends on wind speed and direction. We combine aerodynamic theory of soaring bird flight, the bird’s morphological properties, and three-dimensional GPS measurements at 3-s intervals to estimate the convective velocity scale and horizontal wind velocity at the locations and times of flight. We use wind speed and direction observations from meteorological ground stations and estimates of convective velocity from the Ocean–Land–Atmosphere Model (OLAM) to evaluate our findings. Although not collocated, our wind velocity estimates are consistent with ground station data, and convective velocity–scale estimates are consistent with the meteorological model. Our work demonstrates that biologging offers a novel alternative approach for estimating atmospheric conditions on a spatial and temporal scale that complements existing meteorological measurement systems.