Use of bio-logging data from thermalling white storks as potential atmospheric observations in a global data assimilation system

In-situ observations constitute an essential component of the atmospheric observing system and play a key role in improving Numerical Weather Prediction (NWP), both through their direct assimilation and through their use in diagnostics. By assimilating these observations, the representation of the atmospheric state in the forecast model leads to more accurate Numerical Weather Predictions. However, the availability of in-situ observations is characterized by significant temporal and spatial gaps, particularly in regions of the Global South.

 

In this study, we investigate the potential of a novel type of observation for the global model of the German Weather Service (DWD): bio-logging data collected from small tags attached to white storks (Ciconia Ciconia), originally deployed to study migratory movements and other behavioural aspects of these birds. These tags provide high-frequency measurements of both horizontal and vertical position, but could also provide meteorological information. Here, we assimilate estimated wind speed and direction from the thermalling flight behaviour of white storks using high-frequency GPS recordings from the bio-logging dataset. The data covers a region extending from Germany over France and Spain to West Africa, mainly in a range up to 700 hPa.

 

Preliminary results from a 10-day experiment indicate that the observation-minus-first-guess and observation-minus-analysis statistics fall within physically reasonable ranges. Analysis of vertical profiles and comparison with neighbouring aircraft observations show a general consistency between the assimilated stork and aircraft statistics. In this small sample, the stork observations even show improved agreement with the model at certain flight levels, in terms of both bias and standard deviation.