Development of fine-resolution analyses and expanded large-scale forcing properties: 1. Methodology and evaluation

Zhijin Li, Sha Feng, Yangang Liu, Wuyin Lin, Minghua Zhang, Tami Toto, Andrew M. Vogelmann, Satoshi Endo

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)654-666
Number of pages13
JournalJournal of Geophysical Research
Issue number2
StatePublished - Jan 27 2015

All Science Journal Classification (ASJC) codes

  • Condensed Matter Physics
  • Materials Chemistry
  • Polymers and Plastics
  • Physical and Theoretical Chemistry


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