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Presenter: Xiang-Yu Huang

Seminar Title: WRF 4D-Var: Where We Are adn Where To Go

The 4D-Var idea has been pursued actively by the research community and operational centers over the past two decades. The 4D-Var technique has a number of advantages including the abilities to: 1) implicitly use flow-dependent background errors, which ensures the analysis quality for fast developing weather systems, and 2) use a forecast model as a constraint, which enhances the dynamic balance of the final analysis.

These advantages suggest that the community WRF-Var system should be enhanced by extending the current 3D- to a 4D- capability, using the WRF forecast model as a constraint, in order to provide the best initial conditions for the WRF model. The WRF 4D-Var has been under extensive development since 2004. The prototype 4D-Var was built in 2005 and has undergone continuous refinement since then. Many single observation experiments have been carried out to validate the correctness of the 4D-Var formulation. A series of real data experiments has been conducted to assess the meteorological performance of WRF 4D-Var.

The current version (2.2) of WRF 4D-Var:

• runs as a combination of WRF (the released version 2.2), WRF+ (the WRF tangent linear model and adjoint model) and WRF-Var (the release version 2.1 with 4D-Var extensions) executables,


• uses calls to “system” to invoke the three executables,


• uses disk I/O to handle the communication among WRF, WRF+ and WRF-Var,


• runs on a single processor or multi-processors,


• has a penalty term, Jc, to control noise during the minimization,


• includes a simple vertical diffusion scheme and a large-scale
  condensation scheme in WRF+.

The parallel MPMD system architecture of WRF-Var (4D) has demonstrated encouraging performance and made cycling data assimilation experiments possible. In the seminar, I will review what we have done so far, what we have accomplished and what we have planned for the coming years.

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