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  • Author or Editor: Thibaut Montmerle x
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Thibaut Montmerle and Yvon Lemaître Lemaître


The present study is devoted to a new analysis of wind measurements from dropsonding and/or radiosonding of Doppler information from multiple Doppler radar scanning and of other wind measurements (sodar, dynamical sensors on board aircraft, and instruments at ground) aimed at retrieving three-dimensional thermodynamical and dynamical fields both in clear air and in precipitating areas of mesoscale phenomena. This analysis, well suited to assimilate data from differing platforms specified at differing spatial/temporal resolutions, is based on the analytical and variational concept of the Multiple Analytical Doppler (MANDOP) analysis and thus is an extension of it. This new analysis presents many advantages, including the same as MANDOP and others well adapted for the verification or the initialization of a mesoscale cloud model. An application to simulated and to real data extracted from the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment database is presented in the paper.

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Alain Caya, Stéphane Laroche, Isztar Zawadzki, and Thibaut Montmerle


A 3D wind analysis based on single-Doppler data is proposed using mass conservation and assuming a linear horizontal wind field, which is constant in a moving reference frame. Data over an assimilation period that includes several volume scans are employed, allowing the retrieval of the full linear wind field, including vorticity. The method proposed here can be considered an extension of the volume velocity processing (VVP) procedure. The robustness of the method is examined in detail and a criterion on the condition number is obtained. The method is tested in the context of synthetic data, which respect the simplified model assumptions. Simulated data from a high-resolution numerical weather prediction model are used to assess the impact of errors in the simplified model. The results indicate that 1) the analysis improves as the assimilation period is lengthened up to 1 h, 2) the best results are obtained when the radar is surrounded by precipitation and is in the middle of the analysis domain, and 3) vorticity is the most sensitive parameter. The addition of a vertical smoothing constraint is shown to be beneficial for the minimization and improves the results.

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