Abstract
This chapter introduces a new area of research in variational data assimilation. The theory that we have presented for both variational and ensemble data assimilation schemes has assumed that the errors are Gaussian distributed. In this chapter we relax the Gaussian assumption to allow for errors that are lognormally distributed. We shall derive the full field and increment 3D and 4D VAR cost functions for both lognormal errors and mixed Gaussian-lognormal errors as well. We shall show results comparing the mixed non-Gaussian approach with the logarithmic approach, as well as with just a Gaussian-fits-all scheme. We finish this chapter with interesting new results with respect to minimization algorithms and a Newton-fractal.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
