Predictability of atmospheric minor constituents validated by a high-performance data assimilation system

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We developed a data assimilation system for atmospheric minor constituents using the Ensemble Kalman filter that is an advanced mathematical statistic scheme. Data assimilation is an informational technology, which merges model simulation results and observation results. The analyses of stratospheric ozone and tropospheric aerosol concentrations were calculated by this data assimilation system. We performed numerical hindcast simulations of the ozone layer and dust aerosol using those analyses as initial conditions. Consequently, the ozone/dust predictability in several hours/several days was evidently improved.