Collaborative Research: Space Weather: Wavelet Based Regional Multi-Resolution Ionosphere Modeling: Investigating Structure of the Equatorial Anomaly

数学和空间科学家之间的合作提供了一种新的数据同化算法，能够处理时间和空间不均匀的数据集，组装（在模型有用的格式）的总电子含量（TEC）数据的广泛数量。 这些数据来自电离层探测仪网络、全球定位系统接收器网络、卫星电子密度测量、无线电掩星数据和其他来源。 然后，使用球面小波函数在多分辨率电离层模型中描述数据，赤道异常电离层的区域描述是模型应用的主要焦点。 该方法采用由数据同化和小波描述生成的电离层多维区域电离层图，然后更新国际参考电离层（IRI）模型，以提高全球电离层模型的精度。 该研究预计将显着提高业务预测能力。

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.