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Title: Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments

Abstract

This project focused on the variability of clouds that is present across a wide range of scales ranging from the synoptic to the millimeter. In particular, there is substantial variability in cloud properties at scales smaller than the grid spacing of models used to make climate projections (GCMs) and weather forecasts. These models represent clouds and other small-scale processes with parameterizations that describe how those processes respond to and feed back on the largescale state of the atmosphere.

Authors:
Publication Date:
Research Org.:
University of Colorado
Sponsoring Org.:
USDOE
OSTI Identifier:
1013591
Report Number(s):
DOE/03ER63561
DOE Contract Number:  
FG02-03ER63561
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

Pincus, Robert. Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments. United States: N. p., 2011. Web. doi:10.2172/1013591.
Pincus, Robert. Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments. United States. https://doi.org/10.2172/1013591
Pincus, Robert. 2011. "Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments". United States. https://doi.org/10.2172/1013591. https://www.osti.gov/servlets/purl/1013591.
@article{osti_1013591,
title = {Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments},
author = {Pincus, Robert},
abstractNote = {This project focused on the variability of clouds that is present across a wide range of scales ranging from the synoptic to the millimeter. In particular, there is substantial variability in cloud properties at scales smaller than the grid spacing of models used to make climate projections (GCMs) and weather forecasts. These models represent clouds and other small-scale processes with parameterizations that describe how those processes respond to and feed back on the largescale state of the atmosphere.},
doi = {10.2172/1013591},
url = {https://www.osti.gov/biblio/1013591}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue May 17 00:00:00 EDT 2011},
month = {Tue May 17 00:00:00 EDT 2011}
}