Evaluation of a multivariate variational assimilation of conventional and satellite data for the diagnosis of cyclone systems

A variational data assimilation method for the study of cyclone-scale weather systems is described. The variational data assimilation method is to incorporate primitive equations for a moist, convectively unstable atmosphere and the radiative transfer equation. The variables to be adjusted include the three-dimensional vector wind, height, temperature, and moisture from rawinsonde data, and cloud-wind vectors, moisture, and radiance from satellite data. The development of variational model 1 which contains two nonlinear horizontal momentum equations, an integrated continuity equation, and a hydrostatic equation is examined. Examples applying the assimilation model to rawinsonde and satellite data are presented.