SILAM
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SILAM (System for Integrated Modeling of Atmospheric Composition) is a global-to-meso-scale atmospheric dispersion model developed by the Finnish Meteorological Institute (FMI).
Model
[edit | edit source]It provides information on atmospheric composition, air quality, and wildfire smoke (PM2.5) and is also able to solve the inverse dispersion problem. It can take data from a variety of sources, including natural ones such as sea salt, blown dust, and pollen.[1]
The FMI provides three datasets based on SILAM: a 4-day global air pollutant (SO2, NO, NO2, O3, PM2.5, and PM10) forecast based on TNO-MACC (global emission) and IS4FIRES (wildfire), a 5-day global wildfire smoke forecast based on IS4FIRES, and a 5-day pollen forecast for Europe.[2]