Beobachtungsoperator zur Assimilation satellitenbasierter Messungen verschiedener Aerosoltypen in ein Chemie-Transportmodell

Abstract

Using data assimilation methods, numerical weather prediction accuracy could be improved significantly in the last two decades. On the contrary, chemical weather modelling especially of aerosol particles with chemical transport models is still based mainly on static emission databases which cannot treat episodic emissions satisfactorily. An observation operator for a component wise assimilation of satellite measurements is developed to couple chemical mass concentration modelling with satellite-based measurements. It treats water soluble, water insoluble, soot, sea salt and mineral dust aerosol components separately. A two-dimensional, variational assimilation method is then applied on the basis of component wise aerosol optical depth. Separately, for the water soluble, the soot and the mineral dust aerosol components a bias reduction and therefore a root mean square error reduction is observed in the analysis fields for a test period from July to November 2003. Additionally, examples of an improved analysis field in wildfire and dust outbreak situations could be shown.