skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Evaluation of the Multi-scale Modeling Framework Using Data from the Atmospheric Radiation Measurement Program

Abstract

One of the goals of the Atmospheric Radiation Measurement (ARM) program is to provide long-term observations for evaluating and improving cloud and radiation treatment in global climate models. Unfortunately, the traditional parametric approach of diagnosing cloud and radiation properties for gridcells that are tens to hundreds kilometers across from large-scale model fields is not well suited for comparison with time series of ground based observations at selected locations. A recently emerging approach called a multi-scale modeling framework (MMF) has shown promise to bridge the scale gap. The MMF consists of a two-dimensional or small three-dimensional cloud resolving model (CRM) embedded into each grid column of the Community Atmospheric Model (CAM), thereby computing cloud properties at a scale that is more consistent with observations. We present a comparison of data from two ARM sites, one at the Southern Great Plains (SGP) in Oklahoma and one at Nauru Island in the Tropical Western Pacific (TWP) region, with output from both the CAM and MMF. Two sets of one year long simulations are considered: one using climatological sea surface temperatures (SST) and another using 1999 SST. Each set includes a run with the MMF as well as the CAM run with traditional ormore » standard cloud and radiation treatment. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are statistically analyzed. For the TWP site, nearly all parameters of frequency distributions of these variables from the MMF run are shown to be more consistent with observation than those from the CAM run. This change is attributed to the improved representation of convective clouds in the MMF compared to the conventional climate model. For the SGP, the MMF shows little to no improvement in predicting the same quantities. Possible causes of this lack of improvement are discussed.« less

Authors:
; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
882371
Report Number(s):
PNNL-SA-43480
Journal ID: ISSN 0894-8755; JLCLEL; TRN: US200614%%66
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Climate, 19(9):1716-1729; Journal Volume: 19; Journal Issue: 9
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; CLIMATE MODELS; CLOUDS; DOWNWELLING; EVALUATION; ISLANDS; NAURU; OKLAHOMA; PRECIPITATION; RADIATIONS; SEAS; SIMULATION; SOLAR RADIATION; clouds; climate; precipitation

Citation Formats

Ovtchinnikov, Mikhail, Ackerman, Thomas P., Marchand, Roger T., and Khairoutdinov, Marat. Evaluation of the Multi-scale Modeling Framework Using Data from the Atmospheric Radiation Measurement Program. United States: N. p., 2006. Web. doi:10.1175/JCLI3699.1.
Ovtchinnikov, Mikhail, Ackerman, Thomas P., Marchand, Roger T., & Khairoutdinov, Marat. Evaluation of the Multi-scale Modeling Framework Using Data from the Atmospheric Radiation Measurement Program. United States. doi:10.1175/JCLI3699.1.
Ovtchinnikov, Mikhail, Ackerman, Thomas P., Marchand, Roger T., and Khairoutdinov, Marat. Mon . "Evaluation of the Multi-scale Modeling Framework Using Data from the Atmospheric Radiation Measurement Program". United States. doi:10.1175/JCLI3699.1.
@article{osti_882371,
title = {Evaluation of the Multi-scale Modeling Framework Using Data from the Atmospheric Radiation Measurement Program},
author = {Ovtchinnikov, Mikhail and Ackerman, Thomas P. and Marchand, Roger T. and Khairoutdinov, Marat},
abstractNote = {One of the goals of the Atmospheric Radiation Measurement (ARM) program is to provide long-term observations for evaluating and improving cloud and radiation treatment in global climate models. Unfortunately, the traditional parametric approach of diagnosing cloud and radiation properties for gridcells that are tens to hundreds kilometers across from large-scale model fields is not well suited for comparison with time series of ground based observations at selected locations. A recently emerging approach called a multi-scale modeling framework (MMF) has shown promise to bridge the scale gap. The MMF consists of a two-dimensional or small three-dimensional cloud resolving model (CRM) embedded into each grid column of the Community Atmospheric Model (CAM), thereby computing cloud properties at a scale that is more consistent with observations. We present a comparison of data from two ARM sites, one at the Southern Great Plains (SGP) in Oklahoma and one at Nauru Island in the Tropical Western Pacific (TWP) region, with output from both the CAM and MMF. Two sets of one year long simulations are considered: one using climatological sea surface temperatures (SST) and another using 1999 SST. Each set includes a run with the MMF as well as the CAM run with traditional or standard cloud and radiation treatment. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are statistically analyzed. For the TWP site, nearly all parameters of frequency distributions of these variables from the MMF run are shown to be more consistent with observation than those from the CAM run. This change is attributed to the improved representation of convective clouds in the MMF compared to the conventional climate model. For the SGP, the MMF shows little to no improvement in predicting the same quantities. Possible causes of this lack of improvement are discussed.},
doi = {10.1175/JCLI3699.1},
journal = {Journal of Climate, 19(9):1716-1729},
number = 9,
volume = 19,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2006},
month = {Mon May 01 00:00:00 EDT 2006}
}