Heiner Lange, Hans-Ertel-Centre for Weather Research, Data Assimilation Branch, LMU Munich
Assimilation of Mode-S EHS aircraft observations in a local EnKF
Abstract: Aircraft observations of wind and temperature collected by airport surveillance radars (Mode-S EHS) were assimilated in COSMO-KENDA (Kilometre-scale ENsemble Data Assimilation) which couples an Ensemble Kalman Filter to a 40 member ensemble of the convection permitting COSMO-DE (Consortium for Small-Scale Modelling) model.
The number of observing aircrafts in Mode-S EHS was about 15 times larger than in the AMDAR system. In the comparison of both aircraft observation systems, a similar observation error standard deviation was diagnosed for wind. For temperature, a larger error was diagnosed for Mode-S EHS.
With the high density of Mode-S EHS observations, a reduction of temperature and wind error in forecasts of one and three hours was found mainly in the flight level and less near the surface. The amount of Mode-S EHS data was reduced by random thinning to test the effect of a varying observation density.
With the current data assimilation setup, a saturation of the forecast error reduction was apparent when more than 50 percent of the Mode-S EHS data were assimilated. Forecast kinetic energy spectra indicated that the reduction in error is related to analysis updates on all scales resolved by COSMO-DE.