Session 4A.2 Hourly data assimilation with the Gridpoint Statistical Interpolation for the Rapid Refresh

Tuesday, 26 June 2007: 4:30 PM
Summit A (The Yarrow Resort Hotel and Conference Center)
Dezso Devenyi, NOAA/ESRL/GSD and CIRES/University of Colorado, Boulder, CO; and S. S. Weygandt, T. W. Schlatter, S. G. Benjamin, and M. Hu

Presentation PDF (511.6 kB)

The Rapid Refresh (RR) model and analysis system, currently under development at the Global Systems Division (GSD) of the Earth System Research Laboratory (ESRL), is planned to replace the NCEP operational Rapid Update Cycle (RUC) in 2009. The RUC is a high-frequency (hourly) data assimilation and prediction system designed to provide mesoscale weather guidance for aviation, severe weather, and public forecasting needs. The RR will occupy the same niche as the RUC in the NCEP operational model suite, but will be based on one of the WRF model cores and utilize the Gridpoint Statistical Interpolation (GSI) for the hourly data assimilation cycle. In addition, the RR will run over a domain that is 2.6 times larger than present domain of RUC, including Alaska, Puerto Rico and the Caribbean.

In this presentation we will report on work within GSD to adapt and test the GSI for application within the RR framework. GSI is a versatile variational data assimilation scheme still under development at NCEP with contribution from other organizations, including NASA and ESRL GSD. At ESRL GSD, the main task is the inclusion and adaptation within GSI of RUC-specific analysis features needed for RR, in particular: cloud and hydrometeor analysis and PBL depth dependency for assimilation of surface temperature, dewpoint, and wind observations.

Consistent with the needs listed above, we will discuss issues and results related to:

- using data in the surface layer,

- analysis in the planetary boundary layer using adaptive anisotropic and non-homogeneous background error covariances,

- assimilation of satellite data and their impact on RR performance,

- running a real time experimental cycle over planned RR domain.

The presentation will conclude with analysis of present state of data assimilation for RR and tasks for the near future.

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