NSF Award
0417666
A collaboration between mathematical and space scientists provides a novel data assimilation algorithm, capable of handling temporally and spatially inhomogeneous data sets, to assemble (in a model-useful format) an extensive amount of total electron content (TEC) data. These data are assembled from ionosonde networks, GPS receiver networks, satellite electron density measurements, radio occultation data, and other sources. The data are then described in a multi-resolution ionosphere model using spherical wavelet functions, and a regional description of the ionosphere in the equatorial anomaly is a primary focus of the model application. The methodology takes resultant ionospheric multi-dimensional regional ionospheric maps, generated by the data assimilation and the wavelet description, and then updates the International Reference Ionosphere (IRI) model for improved global ionospheric model accuracy. The research expects to significantly improve operational predictive capability.
