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Using Single-Doppler Data to Obtain a Mesoscale Environmental Field

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  • 1 Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada
  • | 2 Meteorological Research Branch, Atmospheric Environment Service, Dorval, and Cooperative Center for Research in Mesometeorology, Montreal, Quebec, Canada
  • | 3 Department of Atmospheric and Oceanic Sciences, McGill University, and Cooperative Center for Research in Mesometeorology, Montreal, Quebec, Canada
  • | 4 Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada
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Abstract

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.

Corresponding author address: Alain Caya, Dept. of Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke St. West, Montreal, QC H3A 2K6, Canada. Email: caya@zephyr.meteo.mcgill.ca

Abstract

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.

Corresponding author address: Alain Caya, Dept. of Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke St. West, Montreal, QC H3A 2K6, Canada. Email: caya@zephyr.meteo.mcgill.ca

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