Projekt

Annually, thousands of animals are equipped with state-of-the-art sensor technology with the objective of studying the movement and migration behavior of a diverse range of animal species (e.g.migratory birds). The sensors are capable of not only transmitting the position of the animals, but also meteorological environmental variables such as pressure, temperature, wind speed, and direction. Such information could be of great value for numerical weather prediction, which relies on observational data to determine the initial state of meteorological forecast models. Vertical profile measurements in the atmospheric boundary layer (lower 2 km of the atmosphere), which are particularly limited in the global south, play a significant role in this context. The project team aims to investigate the suitability of "bio-logging" data for numerical weather forecasting, with the example of data from migrating white storks. This will include an investigation of data quality, the development of suitable quality controls, bias corrections and the modelling of observation errors. A series of comprehensive experiments will be conducted in which the data will be actively employed in the assimilation system of the German Weather Service, utilizing the methodologies that have been developed. The objective is to investigate whether the quality of the data is sufficient to enhance weather forecasting in particular of Africa, where the storks migrate to in winter and other observations are sparse, but also over Europe. Furthermore, the outcomes will be exploited for the advancement of novel bio-logging transmitters.

• Dr. Annika Schomburg

  Deutscher Wetterdienst DWD
  Forschung und Entwicklung
  Meteorologische Analyse und Modellierung
  Offenbach
  

• Prof. Dr. Martin Wikelski

  Max-Planck-Institut für Verhaltens-
  biologie
  Abteilung für Tierwanderungen
  Radolfzell
  

• Dr. Andrea Flack, D. Phil

  Max-Planck-Institut für Verhaltens-
  biologie
  Abteilung für Tierwanderungen
  Konstanz