### Download Presentation

Wind retrieval from ADM-Aeolus signals

**An Image/Link below is provided (as is) to download presentation**
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

#### Presentation Transcript

**1. **Wind retrieval from ADM-Aeolus signals A.Dabas, M.L. Denneulin, Météo-France
P. Flamant, CNRS
O. Reitebuch, J. Streicher, I. Leike, D. Huber, U. Paffrath, DLR

**2. **How is ADM measuring winds ? ADM-AOLUS implements two direct-detection channels:
The « Rayleigh » channel for the molecular return (broad spectrum FWHM ~ 1.5GHz).
The « Mie » channel for the aerosol return (narrow spectrum, FWHM ~ 50MHz ).
The Mie channel is based on a Fizeau (fringe imaging technique).
The Fizeau forms a linear fringe which position is a function of the center frequency of the incoming light.
The fringe is imaged on a CCD, its position is determined from the CCD samples.
The Rayleigh channel is based on a double Fabry-Perot approach.
The transmission curves of FPA & B have widths comparable to the width of the molecular spectrum and are crossing at l=355nm).
The LOS wind is obtained by « inverting » the Rayleigh response
where NA and NB are the photon numbers at the output.
To improve the efficiency, the double FP is illuminated by the light reflected from the Fizeau.

**3. **The Rayleigh channel

**4. **Inversion of the Rayleigh Response In principle very easy if the response curve can be characterized precisely…
But in reality the response curve does not depend solely on instrument characteristics, it also depends on:
The temperature in the probed volume, which governs the width of the molecular return (proportional to T1/2).
The potential presence of aerosols which add a narrow peak to the retun spectrum.
The pressure in the probed volume because, due to Brillouin scattering, the shape of the molecular return is slightly non Gaussian…

**5. **Rayleigh-Brillouin scattering

**6. **Impact on Rayleigh wind retrievals: T

**7. **Impact on Rayleigh wind retreivals: P

**8. **Impact on Rayleigh wind retreivals: aerosols

**9. **Rayleigh-Brillouin correction A correction scheme has been developed for ADM Rayleigh winds as part of the level 2 processor.
It uses P and T from the first-guess of a NWP model (see presentation by D. Tan et al.).
The so-called Rayleigh-Brillouin correction scheme is in two-steps:
Step 1 (mandatory) corrects P and T effects (and assumes no aerosol contamination). It is based on a look-up-table approach. The LUT is a 3D matrix that gives the inverted LOS wind vr(i,j,k) for a wide range of pressures Pi and temperatures Tj that pave the area of possible conditions in the atmosphere and a large array of Rayleigh responses RR(k).
Step 2 (optional) corrects the aerosol contamination effect. The relative weight of the aerosol return (baer/ bmol) is taken from the Mie channel (if available).
The LUT is computed with spectra modeled by the Tenti S6 model.

**10. **The computation of the LUT

**11. **The processing of the Mie channel (1/2)

**12. **The processing of the Mie channel (2/2) The Mie core algorithm developped for ADM consists in fitting a bin-integrated Lorentzian line to the actual CCD counts.
Estimate for the central frequency.
Estimate for the linewidth used for QC purposes.
Estimate for the strength of the useful part of the Mie return.
Estimate for the level of background noise.
The fit is done in a least-square sense. Tests have shown that the performances are almost optimal (close to maximum likelihood).
Estimates of Mie return strength and background noise levels are combined in order to produce estimates for the signal to noise ratio, and aerosol to backscatter ratio (assuming Rayleigh photons are dominating the background noise).
The non-linear, 4-unknowns fitting procedure is time consuming. At the present, a first rough estimate of the SNR is made first, and the Mie core algorithm is applied whenever the SNR exceeds a pre-defined threshold.

**13. **Conclusions A processing scheme has been developed for the Rayleigh channel that requires external input data on the pressure and temperature inside the sensing volume.
This processing scheme is part of the level 2b ADM processor, the external data are taken from numerical weather prediction first-guess fields (i.e. a weather forecast).
The processing scheme is based on a LUT approach. The LUT is computed from synthetic spectra and requires a careful and precise characterization of the transmission through the FPs. This requires a careful instrument design.
A Mie algorithm was developped. It reaches near optimal performances, but is time consuming (cannot be systematically applied).