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 - 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 -