TY - JOUR
T1 - Development of fine-resolution analyses and expanded large-scale forcing properties
T2 - 1. Methodology and evaluation
AU - Li, Zhijin
AU - Feng, Sha
AU - Liu, Yangang
AU - Lin, Wuyin
AU - Zhang, Minghua
AU - Toto, Tami
AU - Vogelmann, Andrew M.
AU - Endo, Satoshi
N1 - Funding Information:
The research described in this publication was supported by the U.S. Department of Energy Earth System Modeling (ESM) program via the FAst-physics System TEstbed and Research (FASTER) project www.bnl.gov/faster. The research was carried out, in part, at Jet Propulsion Laboratory (JPL) California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). The authors thank the ARM program for providing the SGP observations. The authors are grateful to Ann Fridlind (NASA Goddard Institute for Space Studies) for numerous stimulating discussions, insightful suggestions, and strong support. The authors thank the anonymous reviewers for comments that were very helpful in improving the manuscript.
Publisher Copyright:
© 2014. American Geophysical Union. All Rights Reserved.
PY - 2015/1/27
Y1 - 2015/1/27
N2 - We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system. Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.
AB - We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system. Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.
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U2 - 10.1002/2014JD022245
DO - 10.1002/2014JD022245
M3 - Article
AN - SCOPUS:84923173815
SN - 0148-0227
VL - 120
SP - 654
EP - 666
JO - Journal of Geophysical Research
JF - Journal of Geophysical Research
IS - 2
ER -