Abstract: The effectiveness of a four-dimensional variational data assimilation (4DVAR) technique for creating ?bogus? vortices in numerical simulations of hurricanes is evaluated in this study. A series of numerical experiments is ...

Abstract: A quasi-inverse linear method has been developed to study the sensitivity of forecast errors to initial conditions for the National Centers for Environmental Prediction?s (NCEP) global spectral model. The inverse is ...

Abstract: Four-dimensional variational data assimilation (4D-Var) seeks to find an optimal initial field that minimizes a cost function defined as the squared distance between model solutions and observations within an assimilation ...

Abstract: The errors in the first-guess (forecast field) of an analysis system vary from day to day, but, as in all current operational data assimilation systems, forecast error covariances are assumed to be constant in time in the ...