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| Titel |
Assimilation of Mode-S EHS aircraft observations with a local EnKF |
| VerfasserIn |
Heiner Lange, Tijana Janjic |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250131199
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| Publikation (Nr.) |
 EGU/EGU2016-11580.pdf |
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| Zusammenfassung |
| 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. Between both aircraft observation systems, comparable observation error standard deviations in wind and a larger error in temperature were diagnosed a posteriori using analysis/forecast residuals in observation space (Desrozier’s method).
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. Evolution (every 15 minutes) of forecast kinetic energy spectra compared to the control experiment showed different behavior of COSMO-DE model depending on amount of data assimilated. |
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