Assessment of a Microphysical Ensemble Used to Investigate the OWLeS IOP4 Lake-Effect Storm

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  • 1 Atmospheric Sciences Research Center, Albany, New York
  • 2 National Taiwan University, Taipei, Taiwan
  • 3 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, School of Meteorology, University of Oklahoma, and NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma
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Abstract

Microphysical processes within mixed-phase convective clouds can have cascading impacts on cloud properties and resultant precipitation. This paper investigates the role of microphysics in the lake-effect storm (LES) observed during intensive observing period 4 of the Ontario Winter Lake-effect Systems field campaign. A microphysical ensemble is composed of 24 simulations that differ in the microphysics scheme used (e.g., Weather Research and Forecasting Model microphysics options or a choice of two bulk adaptive habit models) along with changes in the representation of aerosol and potential ice nuclei concentrations, ice nucleation parameterizations, rain and ice fall speeds, spectral indices, ice habit assumptions, and the number of moments used for modeling ice-phase hydrometeors in each adaptive habit model. Each of these changes to microphysics resulted in varied precipitation types at the surface; 15 members forecast a mixture of snow, ice, and graupel, seven members forecast only snow and ice, and the remaining two members forecast a combination of snow, ice, graupel, and rain. Observations from an optical disdrometer positioned to the south of the LES core indicate that 92% of the observed particles were snow and ice, 5% were graupel, and 3% were rain and drizzle. Analysis of observations spanning more than a point location, such as polarimetric radar observations and aircraft measurements of liquid water content, provides insight into cloud composition and processes leading to the differences at the surface. Ensemble spread is controlled by hydrometeor type differences spurred by processes or parameters (e.g., ice fall speed) that affect graupel mass.

Corresponding author address: Lauriana C. Gaudet, The University at Albany, SUNY, 1400 Washington Ave, Albany, NY 12222. E-mail: lgaudet@albany.edu

Abstract

Microphysical processes within mixed-phase convective clouds can have cascading impacts on cloud properties and resultant precipitation. This paper investigates the role of microphysics in the lake-effect storm (LES) observed during intensive observing period 4 of the Ontario Winter Lake-effect Systems field campaign. A microphysical ensemble is composed of 24 simulations that differ in the microphysics scheme used (e.g., Weather Research and Forecasting Model microphysics options or a choice of two bulk adaptive habit models) along with changes in the representation of aerosol and potential ice nuclei concentrations, ice nucleation parameterizations, rain and ice fall speeds, spectral indices, ice habit assumptions, and the number of moments used for modeling ice-phase hydrometeors in each adaptive habit model. Each of these changes to microphysics resulted in varied precipitation types at the surface; 15 members forecast a mixture of snow, ice, and graupel, seven members forecast only snow and ice, and the remaining two members forecast a combination of snow, ice, graupel, and rain. Observations from an optical disdrometer positioned to the south of the LES core indicate that 92% of the observed particles were snow and ice, 5% were graupel, and 3% were rain and drizzle. Analysis of observations spanning more than a point location, such as polarimetric radar observations and aircraft measurements of liquid water content, provides insight into cloud composition and processes leading to the differences at the surface. Ensemble spread is controlled by hydrometeor type differences spurred by processes or parameters (e.g., ice fall speed) that affect graupel mass.

Corresponding author address: Lauriana C. Gaudet, The University at Albany, SUNY, 1400 Washington Ave, Albany, NY 12222. E-mail: lgaudet@albany.edu
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