Author/Authors :
DAVID G. H. TAN، نويسنده , , ERIK ، نويسنده , , ERSSON ، نويسنده , , JOS DE KLOE، نويسنده , , GERT-JAN MARSEILLE، نويسنده , , AD STOFFELEN، نويسنده , , PAUL POLI، نويسنده , , MARIE-LAURE DENNEULIN، نويسنده , , ALAIN DABAS، نويسنده , , DORIT HUBER، نويسنده , , OLIVER REITEBUCH، نويسنده , , PIERRE FLAMANT، نويسنده , , OLIVIER LE RILLE ، نويسنده , , HERBERT NETT، نويسنده ,
Abstract :
The ADM-Aeolus is primarily a research and demonstration mission flying the first Doppler wind lidar in space. Flexible
data processing tools are being developed for use in the operational ground segment and by the meteorological
community. We present the algorithms developed to retrieve accurate and representative wind profiles, suitable for assimilation
in numerical weather prediction. The algorithms provide a flexible framework for classification and weighting
of measurement-scale (1–10 km) data into aggregated, observation-scale (50 km) wind profiles for assimilation. The
algorithms account for temperature and pressure effects in the molecular backscatter signal, and so the main remaining
scientific challenge is to produce representative winds in inhomogeneous atmospheric conditions, such as strong wind
shear, broken clouds, and aerosol layers. The Aeolus instrument provides separate measurements in Rayleigh and Mie
channels, representing molecular (clear air) and particulate (aerosol and clouds) backscatter, respectively. The combining
of information from the two channels offers possibilities to detect and flag difficult, inhomogeneous conditions. The
functionality of a baseline version of the developed software has been demonstrated based on simulation of idealized
cases