Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I: experiments with synoptic-scale data

Abstract

A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or "nudging' is tested using standard rawinsonde data in the Penn State/NCAR limited-area mesoscale model. The main hypothesis to be tested is that use of coarse-resolution rawinsonde observations throughout a model integration, rather than at only the initial time, can limit large-scale model error growth (amplitude and phase errors) while the model generates realistic mesoscale structures not resolved by the data. The results show that the assimilation of both wind and thermal data throughout the model atmosphere had a consistently positive impact on the synoptic-scale and mesoscale mass and wind fields and for the precipitation simulations in the case dominated by large-scale forcing. Other results show that nudging vorticity or the rawinsonde-based mixing ratio analyses tended to seriously degrade the precipitation simulations for both cases and should be avoided. -from Authors