Dorit Huber

The ADM-Aeolus wind retrieval algorithms

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.

ADM-Aeolus retrieval algorithms for aerosol and cloud products

ADM-Aeolus, the wind Lidar under development at ESA, is a High Spectral Resolution Lidar that additionally provides separated information on particles (Mie channel) and molecules (Rayleigh channel). Lidar signals will be accumulated in vertical range bins in order to reach sufficient signal-to-noise ratio for reliable wind estimates. The vertical range bin integration may vary from 250mnear the surface up to 2 kmin the upper troposphere and lower stratosphere. Significant attenuation in a range bin changes the nature of the retrieval problem. The commonly used Lidar inversion techniques appear to be inadequate to process bin-accumulated signals. This paper presents the ‘L2A processor’, conceived to use ADM-Aeolus signals to provide information on aerosol and cloud layers optical properties. The altitude, geometrical depth, optical depth, backscatter-to-extinction ratio and scattering ratio are to be retrieved. The L2A processor algorithms provide a new formulation to the inverse problem for various filling cases of a range bin and it includes a credibility criterion (CC) in order to select the best filling approximation. The effective vertical resolution can be two to four times better than the ADM-Aeolus range bins. The basic concept, the processing algorithms, numerical examples and sensitivity tests are here presented.