Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions
Abstract:Abstract. Data assimilation techniques are one of the most important
ways to reduce the uncertainty in atmospheric chemistry model input and
improve the model forecast accuracy. In this paper, an ensemble optimal
interpolation assimilation (EnOI) system for a regional online chemical
weather numerical forecasting system (GRAPES_Meso5.1/CUACE)
is developed for operational use and efficient updating of the initial
fields of chemical components. A heavy haze episode in eastern China was
selected, and the key fact… Show more
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