Abstract

The Assimilative Canadian High Arctic Ionospheric Model (A-CHAIM) is an operational ionospheric data assimilation model that provides a 3D representation of the high latitude ionosphere in Near-Real-Time (NRT). A-CHAIM uses low-latency observations of slant Total Electron Content (sTEC) from ground-based Global Navigation Satellite System (GNSS) receivers, ionosondes, and vertical TEC from the JASON-3 altimeter satellite to produce an updated electron density model above 45° geomagnetic latitude. A-CHAIM is the first operational use of a particle filter data assimilation for space environment modeling, to account for the nonlinear nature of sTEC observations. The large number (>10⁴) of simultaneous observations creates significant problems with particle weight degeneracy, which is addressed by combining measurements to form new composite observables. The performance of A-CHAIM is assessed by comparing the model outputs to unassimilated ionosonde observations, as well as to in-situ electron density observations from the SWARM and DMSP satellites. During moderately disturbed conditions from 21 September 2021 through 29 September 2021, A-CHAIM demonstrates a 40%–50% reduction in error relative to the background model in the F2-layer critical frequency (foF2) at midlatitude and auroral reference stations, and little change at higher latitudes. The height of the F2-layer (hmF2) shows a small 5%–15% improvement at all latitudes. In the topside, A-CHAIM demonstrates a 15%–20% reduction in error for the Swarm satellites, and a 23%–28% reduction in error for the DMSP satellites. The reduction in error is distributed evenly over the assimilation region, including in data-sparse regions.