Atmospheric Measurement Techniques (Feb 2018)

Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations

  • I. Veselovskii,
  • I. Veselovskii,
  • I. Veselovskii,
  • P. Goloub,
  • T. Podvin,
  • D. Tanre,
  • A. da Silva,
  • P. Colarco,
  • P. Castellanos,
  • P. Castellanos,
  • M. Korenskiy,
  • Q. Hu,
  • D. N. Whiteman,
  • D. Pérez-Ramírez,
  • P. Augustin,
  • M. Fourmentin,
  • A. Kolgotin

DOI
https://doi.org/10.5194/amt-11-949-2018
Journal volume & issue
Vol. 11
pp. 949 – 969

Abstract

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Observations of multiwavelength Mie–Raman lidar taken during the SHADOW field campaign are used to analyze a smoke–dust episode over West Africa on 24–27 December 2015. For the case considered, the dust layer extended from the ground up to approximately 2000 m while the elevated smoke layer occurred in the 2500–4000 m range. The profiles of lidar measured backscattering, extinction coefficients, and depolarization ratios are compared with the vertical distribution of aerosol parameters provided by the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The MERRA-2 model simulated the correct location of the near-surface dust and elevated smoke layers. The values of modeled and observed aerosol extinction coefficients at both 355 and 532 nm are also rather close. In particular, for the episode reported, the mean value of difference between the measured and modeled extinction coefficients at 355 nm is 0.01 km−1 with SD of 0.042 km−1. The model predicts significant concentration of dust particles inside the elevated smoke layer, which is supported by an increased depolarization ratio of 15 % observed in the center of this layer. The modeled at 355 nm the lidar ratio of 65 sr in the near-surface dust layer is close to the observed value (70 ± 10) sr. At 532 nm, however, the simulated lidar ratio (about 40 sr) is lower than measurements (55 ± 8 sr). The results presented demonstrate that the lidar and model data are complimentary and the synergy of observations and models is a key to improve the aerosols characterization.