Using cloud resolving model simulations of deep convection to inform cloud parameterizations in large-scale models
Abstract
Cloud parameterizations in large-scale models struggle to address the significant non-linear effects of radiation and precipitation that arise from horizontal inhomogeneity in cloud properties at scales smaller than the grid box size of the large-scale models. Statistical cloud schemes provide an attractive framework to self-consistently predict the horizontal inhomogeneity in radiation and microphysics because the probability distribution function (PDF) of total water contained in the scheme can be used to calculate these non-linear effects. Statistical cloud schemes were originally developed for boundary layer studies so extending them to a global model with many different environments is not straightforward. For example, deep convection creates abundant cloudiness and yet little is known about how deep convection alters the PDF of total water or how to parameterize these impacts. These issues are explored with data from a 29 day simulation by a cloud resolving model (CRM) of the July 1997 ARM Intensive Observing Period at the Southern Great Plains site. The simulation is used to answer two questions: (a) how well can the beta distribution represent the PDFs of total water relative to saturation resolved by the CRM? (b) how can the effects of convection on the PDF be parameterized? In addition tomore »
- Authors:
- Publication Date:
- Research Org.:
- NOAA/GFDL, Princeton, New Jersey (US)
- Sponsoring Org.:
- USDOE Office of Science (SC) (US)
- OSTI Identifier:
- 821594
- Report Number(s):
- DOE/ER/62934-2
TRN: US200412%%548
- DOE Contract Number:
- AI02-00ER62934
- Resource Type:
- Conference
- Resource Relation:
- Conference: In Proceedings of the Twelfth Atmospheric Radiation Measurement Science Team Meeting, Conference location not supplied, Conference dates not supplied; Other Information: These proceedings were edited by D.A. Carrothers, Department of Energy, Richland, WA; PBD: 23 Jun 2003
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; BOUNDARY LAYERS; CLOUDS; CONVECTION; DISTRIBUTION; DISTRIBUTION FUNCTIONS; PRECIPITATION; PROBABILITY; RADIATIONS; SATURATION; SIMULATION; USA; WATER
Citation Formats
Klein, Stephen A, Pincus, Robert, and Xu, Kuan-man. Using cloud resolving model simulations of deep convection to inform cloud parameterizations in large-scale models. United States: N. p., 2003.
Web.
Klein, Stephen A, Pincus, Robert, & Xu, Kuan-man. Using cloud resolving model simulations of deep convection to inform cloud parameterizations in large-scale models. United States.
Klein, Stephen A, Pincus, Robert, and Xu, Kuan-man. 2003.
"Using cloud resolving model simulations of deep convection to inform cloud parameterizations in large-scale models". United States. https://www.osti.gov/servlets/purl/821594.
@article{osti_821594,
title = {Using cloud resolving model simulations of deep convection to inform cloud parameterizations in large-scale models},
author = {Klein, Stephen A and Pincus, Robert and Xu, Kuan-man},
abstractNote = {Cloud parameterizations in large-scale models struggle to address the significant non-linear effects of radiation and precipitation that arise from horizontal inhomogeneity in cloud properties at scales smaller than the grid box size of the large-scale models. Statistical cloud schemes provide an attractive framework to self-consistently predict the horizontal inhomogeneity in radiation and microphysics because the probability distribution function (PDF) of total water contained in the scheme can be used to calculate these non-linear effects. Statistical cloud schemes were originally developed for boundary layer studies so extending them to a global model with many different environments is not straightforward. For example, deep convection creates abundant cloudiness and yet little is known about how deep convection alters the PDF of total water or how to parameterize these impacts. These issues are explored with data from a 29 day simulation by a cloud resolving model (CRM) of the July 1997 ARM Intensive Observing Period at the Southern Great Plains site. The simulation is used to answer two questions: (a) how well can the beta distribution represent the PDFs of total water relative to saturation resolved by the CRM? (b) how can the effects of convection on the PDF be parameterized? In addition to answering these questions, additional sections more fully describe the proposed statistical cloud scheme and the CRM simulation and analysis methods.},
doi = {},
url = {https://www.osti.gov/biblio/821594},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jun 23 00:00:00 EDT 2003},
month = {Mon Jun 23 00:00:00 EDT 2003}
}