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Title: Large Scale Ice Water Path and 3-D Ice Water Content

Abstract

Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrainmore » satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.« less

Authors:
Publication Date:
DOE Contract Number:  
DE-AC05-00OR22725
Product Type:
Dataset
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Archive
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Subject:
54 Environmental Sciences
Keywords:
Ice water path; Ice water content
OSTI Identifier:
1169518
DOI:
10.5439/1169518

Citation Formats

Liu, Guosheng. Large Scale Ice Water Path and 3-D Ice Water Content. United States: N. p., 2008. Web. doi:10.5439/1169518.
Liu, Guosheng. Large Scale Ice Water Path and 3-D Ice Water Content. United States. doi:10.5439/1169518.
Liu, Guosheng. 2008. "Large Scale Ice Water Path and 3-D Ice Water Content". United States. doi:10.5439/1169518. https://www.osti.gov/servlets/purl/1169518. Pub date:Tue Jan 15 00:00:00 EST 2008
@article{osti_1169518,
title = {Large Scale Ice Water Path and 3-D Ice Water Content},
author = {Liu, Guosheng},
abstractNote = {Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrain satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.},
doi = {10.5439/1169518},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2008},
month = {1}
}

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