Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation

AMS Citation:
Wang, J., X. Dong, B. Xi, and A. J. Heymsfield, 2016: Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation. Journal of Geophysical Research: Atmospheres, 121, 10,739-10,760, doi:10.1002/2016JD024941.
Date:2016-09-27
Resource Type:article
Title:Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation
Abstract: To investigate liquid-phase (T>3 degrees C) cloud and precipitation microphysical properties within Deep Convective Systems (DCSs), eight DCS cases sampled by the University of North Dakota Citation II research aircraft during Midlatitude Continental Convective Clouds Experiment were selected. A full spectrum of raindrop size distribution (DSD) was constructed from 120 mu m to 4000 mu m through a combination of two-dimensional cloud probe (120 to 900 mu m) and High Volume Precipitation Spectrometer (900 to 4000 mu m) data sets. A total of 1126 five second DSDs have been used to fit to Gamma and Exponential functions within the stratiform rain (SR) regions of DCSs. The Gamma shape and slope parameters are then compared with those derived from surface disdrometer measurements. The similar - relationships but different and value ranges from two independent platforms at different elevations may represent the real nature of DSD shape information in clouds and at the surface. To apply the exponentially fitted DSD parameters to precipitation estimation using Next Generation Weather Radar (NEXRAD) radar reflectivity factor Z(e), the terms N-0E and (E) have been parameterized as a function of Z(e) using an empirical N-0E-(E) relationship. The averaged SR rain rate retrieved from this study is almost identical to the surface measurements, while the NEXRAD Q2 precipitation is twice as large. The comparisons indicate that the new DSD parameterization scheme is robust, while the Q2 SR precipitation estimation based on Marshall-Palmer Z-R relationship, where a constant DSD intercept parameter (N-0E) was assumed, needs to be improved for heavy precipitation cases.
Peer Review:Refereed
Copyright Information:Copyright 2016 American Geophysical Union.
OpenSky citable URL: ark:/85065/d7q241xc
Publisher's Version: 10.1002/2016JD024941
Author(s):
  • Jingyu Wang
  • Xiquan Dong
  • Baike Xi
  • Andrew J. Heymsfield - NCAR/UCAR
  • Random Profile

    SENIOR SCIENTIST

    Recent & Upcoming Visitors