Meteorologische Zeitschrift (Aug 2013)

Vertical velocity observed by Doppler lidar during cops ? A case study with a convective rain event

  • Jenny Davis,
  • Chris. Collier,
  • Fay Davies,
  • Ralph Burton,
  • Guy Pearson,
  • Paolo Di Girolamo

DOI
https://doi.org/10.1127/0941-2948/2013/0411
Journal volume & issue
Vol. 22, no. 4
pp. 463 – 470

Abstract

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Convective and Orographically-Induced Precipitation Study (COPS), conducted in the Black Forest region in Southern Germany and Eastern France during the summer of 2007. From the 13 June to the 16 August 2007, the National Centre for Atmospheric Science (NCAS), Facility for Ground-based Atmospheric Measurement (FGAM) 1.5 ?m scanning Doppler lidar was deployed at Super Site R, Achern, in the Rhine Valley, in order to contribute to the extensive COPS observation campaign. The FGAM Doppler lidar system provides measurements of radial wind and aerosol backscatter in the layer 100?1500 m. Profiles of horizontal wind velocity are presented, these being derived from performing azimuth scans. Profiles of vertical velocity, its variance and skewness derived from the vertical scans are also presented and discussed in the paper. Knowledge of vertical velocity skewness is important for the understanding of the structure and origin of turbulent convection in the atmospheric boundary layer (ABL). The skewness of vertical velocity can provide a measure of the asymmetry in the distribution of vertical velocity perturbations within the ABL and can be estimated using the Doppler lidar. In addition, we investigate the behaviour of the boundary layer using data from the FGAM Doppler lidar and Automatic Weather Station (AWS), the University of Basilicata Raman lidar (BASIL) and the DLR's Poldirad C-band radar. A case study event on the 6th August 2007 is selected and investigations of possible causes of layers with positive and negative skewness are presented, along with comparisons with output from the National Center for Atmospheric Research (NCAR) Weather Research and Forecasting (WRF) model to assess the accuracy of the model output, including location and timing of rainfall onset.

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