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Use of cloud radar Doppler spectra to evaluate stratocumulus drizzle size distributions in large-eddy simulations with size-resolved microphysics

  • J. Rémillard
  • , A. M. Fridlind
  • , A. S. Ackerman
  • , G. Tselioudis
  • , P. Kollias
  • , D. B. Mechem
  • , H. E. Chandler
  • , E. Luke
  • , R. Wood
  • , M. K. Witte
  • , P. Y. Chuang
  • , J. K. Ayers

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

A case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated with an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.

Original languageEnglish
Pages (from-to)3263-3283
Number of pages21
JournalJournal of Applied Meteorology and Climatology
Volume56
Issue number12
DOIs
StatePublished - Dec 1 2017

Keywords

  • Drizzle
  • Large eddy simulations
  • Marine boundary layer
  • Model evaluation/performance
  • Radars/Radar observations
  • Stratiform clouds

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