DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Raindrop Size Spectrum in Deep Convective Regions of the Americas

Abstract

This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter Dm, and normalized droplet concentration Nw) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader Nw distributions in Córdoba. Furthermore, the raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h-1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In themore » light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of Nw in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [2]; ORCiD logo [2]
  1. Univ. of Illinois at Urbana-Champaign, IL (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center; Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1817357
Alternate Identifier(s):
OSTI ID: 1821597
Report Number(s):
PNNL-SA-164875
Journal ID: ISSN 2073-4433
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Atmosphere (Basel)
Additional Journal Information:
Journal Name: Atmosphere (Basel); Journal Volume: 12; Journal Issue: 8; Journal ID: ISSN 2073-4433
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; loud microphysics; particle size distribution; precipitation physics

Citation Formats

Rivelli Zea, Lina, Nesbitt, Stephen W., Ladino, Alfonso, Hardin, Joseph C., and Varble, Adam. Raindrop Size Spectrum in Deep Convective Regions of the Americas. United States: N. p., 2021. Web. doi:10.3390/atmos12080979.
Rivelli Zea, Lina, Nesbitt, Stephen W., Ladino, Alfonso, Hardin, Joseph C., & Varble, Adam. Raindrop Size Spectrum in Deep Convective Regions of the Americas. United States. https://doi.org/10.3390/atmos12080979
Rivelli Zea, Lina, Nesbitt, Stephen W., Ladino, Alfonso, Hardin, Joseph C., and Varble, Adam. Thu . "Raindrop Size Spectrum in Deep Convective Regions of the Americas". United States. https://doi.org/10.3390/atmos12080979. https://www.osti.gov/servlets/purl/1817357.
@article{osti_1817357,
title = {Raindrop Size Spectrum in Deep Convective Regions of the Americas},
author = {Rivelli Zea, Lina and Nesbitt, Stephen W. and Ladino, Alfonso and Hardin, Joseph C. and Varble, Adam},
abstractNote = {This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter Dm, and normalized droplet concentration Nw) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader Nw distributions in Córdoba. Furthermore, the raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h-1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of Nw in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.},
doi = {10.3390/atmos12080979},
journal = {Atmosphere (Basel)},
number = 8,
volume = 12,
place = {United States},
year = {Thu Jul 29 00:00:00 EDT 2021},
month = {Thu Jul 29 00:00:00 EDT 2021}
}