The weather research and forecasting model's community variational/ensemble data assimilation system: WRFDA

  • Dale Barker
  • , Xiang Yu Huang
  • , Zhiquan Liu
  • , Tom Auligné
  • , Xin Zhang
  • , Steven Rugg
  • , Raji Ajjaji
  • , Al Bourgeois
  • , John Bray
  • , Yongsh Eng Chen
  • , Meral Demirtas
  • , Yong Run Guo
  • , Tom Henderson
  • , Wei Huang
  • , Hui Chuan Lin
  • , John Michalakes
  • , Syed Rizvi
  • , Xiaoyan Zhang

Research output: Contribution to journalArticlepeer-review

417 Scopus citations

Abstract

A community tool, the Weather Research and Forecasting (WRF) model's Community Variational/Ensemble Data Assimilation System (WRFDA), was developed for and widely used by the Weather Research and Forecasting model's international data assimilation research/operational community. A subset of essential features like conventional observations, three-dimensional variational data assimilation (3DVAR) algorithm, portable, supported, and with good documentation was agreed as the initial basic requirement. The WRFDA system can ingest a wide variety of observation types, in addition to the standard conventional observation types. The WRFDA system directly ingests radiances in the National Centers for Environmental Prediction (NCEP) Binary Universal Form for the Representation of Meteorological Data (BUFR) format. The WRFDA system includes a table of observation errors for each major observation type, as used in AFWA applications of WRFDA. Default synoptic-scale climatological forecast error statistics are also provided for initial setup, testing, and training runs. 58.

Original languageEnglish
Pages (from-to)831-843
Number of pages13
JournalBulletin of the American Meteorological Society
Volume93
Issue number6
DOIs
StatePublished - Jun 2012

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