Chemical weather forecasting and data assimilation with the SILAM model

Julius Vira, FMI

The current state and short-term evolution of the atmospheric chemical composition is often referred as the chemical weather, and it can be forecasted by coupling a atmospheric chemical transport model (CTM) with a numerical weather prediction (NWP) model. This presentation discusses applications of the SILAM CTM in regional and continental scale chemical weather forecasting.

As a specific question, the utilization of observations via chemical data assimilation is discussed. The skill of a forecast based on data assimilation are compared with that of a free-running forecast as well as hourly analyses (state estimates based on short-term forecast and observations). The analysis fields show significantly improved agreement with measurements when compared to the free-running forecast. However, the difference decreases during the forecast as the chemical state relaxes towards the one determined by the emissions and meteorology. While the effect of data assimilation depends on the chemical component under consideration, the forecast experiments show that efficient chemical data assimilation requires approaches strongly different from those in NWP.

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