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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.

Language: English
Page range: 191 - 205
Submitted on: Jan 15, 2007
Accepted on: Aug 20, 2007
Published on: Jan 1, 2008
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2008 David G. H. Tan, Erik Andersson, Jos de Kloe, Gert-Jan Marseille, Ad Stoffelen, Paul Poli, Marie-Laure Denneulin, Alain Dabas, Dorit Huber, Oliver Reitebuch, Pierre Flamant, Olivier Le Rille, Herbert Nett, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.