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Christophe Baehr* , ** , C. Beigbeder*, F. Couvreux*, A. Dabas*, B. Piguet*

Retrieval of the turbulent and backscattering properties using a non-linear filtering technique applied to Doppler LIDAR observation. Christophe Baehr* , ** , C. Beigbeder*, F. Couvreux*, A. Dabas*, B. Piguet*. ISARS 2012 - Boulder, Colorado, USA, 5-8 June 2012.

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Christophe Baehr* , ** , C. Beigbeder*, F. Couvreux*, A. Dabas*, B. Piguet*

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  1. Retrieval of the turbulent and backscattering properties using a non-linear filtering technique applied to Doppler LIDAR observation Christophe Baehr*,**, C. Beigbeder*, F. Couvreux*, A. Dabas*, B. Piguet* ISARS 2012 - Boulder, Colorado, USA, 5-8 June 2012 **Météo-France/CNRS – CNRM/GAME URA1357 ** Institut de Mathématiques de Toulouse - Université de Toulouse III Christophe.Baehr@meteo.fr

  2. Outline • Introduction • How a Doppler lidar and a particle filter can retrieve the properties of a random medium? • Some theoretical elements. • Experimental results : a numerical exercise. • Comparisons with Numerical products • Next Steps Christophe.Baehr@meteo.fr

  3. Introduction • Our final objective is to retrieve the characteristics of a random medium from sparse observations. • The retrieval is done locally, that is, in the vicinity of the observations. • The retrieval technique we have developed has already been applied successfully to in-situ measurements of wind and temperature performed at fixed locations. • We present here the extension of our method to Doppler lidar data for the retrieval of TKE and EDR at a fine temporal resolution. Christophe.Baehr@meteo.fr

  4. How a Doppler lidar and a particle filter can retrieve the properties of a random medium? Christophe.Baehr@meteo.fr

  5. How does it work ? Christophe.Baehr@meteo.fr

  6. How does it work ? Christophe.Baehr@meteo.fr

  7. How does it work ? Christophe.Baehr@meteo.fr

  8. How does it work ? Christophe.Baehr@meteo.fr

  9. How does it work ? Christophe.Baehr@meteo.fr

  10. How does it work ? Christophe.Baehr@meteo.fr

  11. How does it work ? Christophe.Baehr@meteo.fr

  12. How does it work ? Christophe.Baehr@meteo.fr

  13. How does it work ? Christophe.Baehr@meteo.fr

  14. How does it work ? Christophe.Baehr@meteo.fr

  15. How does it work ? Christophe.Baehr@meteo.fr

  16. How does it work ? Christophe.Baehr@meteo.fr

  17. Some theoretical background Christophe.Baehr@meteo.fr

  18. Theoretical Background are a random path and a random field is the acquisition process of the random field along the path is the conditional expectation according to the trajectory. where Christophe.Baehr@meteo.fr

  19. Theoretical Background The probability laws of the random medium considered along a random path: There is a time evolution that required a local model of the probed medium. Here this evolution is given by the Markovian kernel Christophe.Baehr@meteo.fr

  20. Theoretical Background The algorithm in term of state vectors is given by : It is equivalent to the evolution in probability laws : and solve the stochastic dynamical system : Christophe.Baehr@meteo.fr

  21. The Stochastic Lagrangian Model The local Markovian evolution needs a physical model. We have choose to use a Stochastic Lagrangian Model (SLM). The model adapted to wind vertical profiles is excerpt from the 3D SLM we use for the atmospheric measurements : The term is embedded in a truncated normal distribution learned by our algorithm. Christophe.Baehr@meteo.fr

  22. Experimental results : a numerical exercise. Data recorded the June 19th, 2011 every 6s between 13h26 and 14h49 UTC at Lannemezan, France. Leosphere vertical lidar involved during the BLLAST experiment. Christophe.Baehr@meteo.fr

  23. Experimental Results Vertical wind times series ( 6s ) black : reference series Christophe.Baehr@meteo.fr

  24. Experimental Results • Vertical wind times series ( 6s ) black : reference, blue : observation Christophe.Baehr@meteo.fr

  25. Experimental Results Vertical wind times series ( 6s ) black : reference, blue : observation, red : estimated Christophe.Baehr@meteo.fr

  26. Experimental Results Vertical wind, black : reference, blue : observation, red : estimated times series ( 6s ) Power Spectral Density Christophe.Baehr@meteo.fr

  27. Experimental Results Vertical wind PSD, black : reference, blue : observation, red : estimated Christophe.Baehr@meteo.fr

  28. Experimental Results Vertical wind profiles averaged on 1’. Above : reference, bottom : estimated Christophe.Baehr@meteo.fr

  29. Experimental Results TKE times series ( 6s ) Christophe.Baehr@meteo.fr

  30. Experimental Results EDR times series ( 6s ) Christophe.Baehr@meteo.fr

  31. Experimental Results Vertical wind + TKE + EDR profiles averaged on 1’ Christophe.Baehr@meteo.fr

  32. Experimental Results Mean TKE and vertical wind variance profiles Christophe.Baehr@meteo.fr

  33. Comparisons with other Numerical products How it is possible to assess the quality of TKE and EDR estimates ? Comparison with a Meso-NH simulation (for an other day and an other location) to compare the shape of the structures (above : wind, bottom TKE), especially for the TKE. Christophe.Baehr@meteo.fr

  34. Comparisons with other Numerical products • On June 19th, 2011 from 13h26 to 14h49 UTC, the tethered balloon flew at 60m and we compare its data with the lidar range bin 75-125m: • Balloon wind variance ~ 0.39 m2s−2. • lidar filtered signal variance ~ 0.42 m2s−2. • lidar averaged TKE ~ 0.25 m2s−2. • We are waiting for other lidar data to compare with other, more representative balloon flights. Christophe.Baehr@meteo.fr

  35. Next steps • Continue the work on the 3D estimations using hemispherical scanning lidars. • Work on the lidar observation operator. • Full set of numerical comparisons. • MesoNH comparisons with specific BLLAST simulations • Merge the estimation of Doppler lidar and Aerosol lidar to estimate the parameters of a full 3D atmospheric domain. • Work on the assimilation of turbulence parameters in NH models (e. g. Meso-NH). Christophe.Baehr@meteo.fr

  36. Thank you for your attention Acknowledgements : Christophe.Baehr@meteo.fr

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