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.
malliseminaari_vira.pdf (1324953 bytes)