WRF Var
- It is based on incremental variational data assimilation technique
- Conjugate gradient method is utilized to minimized the cost function in analysis control variable space
- Analysis is performed on un-staggered Arakawa A-grid
- Analysis increments are interpolated to staggered Arakawa C-grid and it gets added to the background (first guess) to get final analysis at WRF-model grid
- Conventional observation data input may be supplied both in ASCII or “PREPBUFR” format via “obsproc” utility
- Multiple radar data (reflectivity & radial velocity) input is supplied through ASCII format
- Horizontal component of the background (first guess) error is represented via recursive filter (for regional) or power spectrum (for global). The vertical component is applied through projections on climatologically generated averaged eigenvectors and its corresponding eigenvalues
- Horizontal and vertical background errors are non-separable. Each eigen vector has its own horizontal climatologically determined length scale
- Preconditioning of background part of the cost function is done via control variable transform U defined as B= UUT
- It includes “gen_be” utility to generate the climatological background error covariance estimate via the NMC-method or ensemble perturbations
- A utility program to update WRF boundary condition file after WRF-Var
