Application of data assimilation in the Whole Atmosphere Community Climate Model to the study of day-to-day variability in the middle and upper atmosphere

To demonstrate the potential of the WACCM+DART for studying short-term variability in the mesosphere and lower thermosphere (MLT), results are presented based on the assimilation of synthetic observations that are sampled from a known model truth.

We assimilate temperature and wind from radiosondes and aircraft, satellite drift winds, and COSMIC refractivity in the lower atmosphere, and SABER temperature observations in the middle/upper atmosphere. Relative to an unconstrained WACCM simulation, the assimilation of only lower atmosphere observations reduces the global root mean square error (RMSE) in zonal wind by up to 40% at MLT altitudes. Using data assimilation to constrain the lower atmosphere can therefore provide significant insight into MLT variability.