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Title: Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

Abstract

This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation rate retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.

Authors:
 [1]
  1. McGill Univ., Montreal, QC (Canada). Atmospheric and Oceanic Sciences Dept.
Publication Date:
Research Org.:
McGill Univ., Montreal, QC (Canada)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1343071
Report Number(s):
DOE-MCGILL-0008780
DOE Contract Number:  
SC0008780
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; KAZR; ARM; rain rates; convective/stratiform; precipitation AMIE

Citation Formats

Kollias, Pavlos. Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report. United States: N. p., 2017. Web. doi:10.2172/1343071.
Kollias, Pavlos. Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report. United States. doi:10.2172/1343071.
Kollias, Pavlos. Thu . "Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report". United States. doi:10.2172/1343071. https://www.osti.gov/servlets/purl/1343071.
@article{osti_1343071,
title = {Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report},
author = {Kollias, Pavlos},
abstractNote = {This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation rate retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.},
doi = {10.2172/1343071},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Feb 09 00:00:00 EST 2017},
month = {Thu Feb 09 00:00:00 EST 2017}
}

Technical Report:

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