Ensemble Kalman filtering with applications in space weather

Abstract

The outer radiation belt of the Earth contains energetic electrons whose flux fluctuates in space and time especially during geomagnetically active periods. However, satellite observations provide limited and irregular coverage, as measurements are collected along orbital paths rather than continuously across the full region. This thesis presents electron flux measurements of NOAA-16 and RBSP-A during March 2013 on a common time-L* grid to investigate whether a physically meaningful spatio-temporal interpolation can be achieved out of sparse measurements. The data are synchronized in time, filtered by energy and pitch angle, and overlaid on regular bins which retain observations and gaps.

In this context, the Ensemble Kalman filter is used in its simplest form, with a persistence model and direct observation operator, where the method serves as a structured interpolation technique both spatially and temporally. The results show that the quality of the interpolated fields depends strongly on the data coverage. RBSP-A shows coherent and smooth features whereas NOAA-16 is fragmented as a result of larger gaps. The growth of the size of ensemble leads to the smoothing of the fields, whereas the prevailing structures are not changed and the cost of computation is raised. In general, the approach redistributes the information contained in the observations and its utility is determined by the characteristics of the data.