Space Physics Data Facility

Prompt and accurate imaging of the ionosphere is essential to space weather services, given a broad spectrum of applications that rely on ionospherically propagating radio signals. As the 3D spatial extent of the ionosphere is vast and covered only fragmentarily, data fusion is a strong candidate for solving imaging tasks. Data fusion has been used to blend models and observations for the integrated and consistent views of geosystems. In space weather scenarios, low latency of the sensor data availability is one of the strongest requirements that limits the selection of potential datasets for fusion. Since remote plasma sensing instrumentation for ionospheric weather is complex, scarce, and prone to unavoidable data noise, conventional 3D-var assimilative schemas are not optimal. We describe a novel substantially 4D data fusion service based on near-real-time data feeds from Global Ionosphere Radio Observatory (GIRO) and Global Navigation Satellite System (GNSS) called GAMBIT (Global Assimilative Model of the Bottomside Ionosphere with Topside estimate). GAMBIT operates with a few-minute latency, and it releases, among other data products, the anomaly maps of the effective slab thickness (EST) obtained by fusing GIRO and GNSS data. The anomaly EST mapping aids understanding of the vertical plasma restructuring during disturbed conditions.

This chapter contains sections titled: Introduction The NASA Trapped Radiation Models: AP-8 & AE-8 Comparisons with Recent Observations A New Generation of Trapped Radiation Models Summary and Conclusions

Hourly averaged interplanetary magnetic field (IMF) and plasma data from the Advanced Composition Explorer (ACE) and Wind spacecraft, generated from 1 to 4 min resolution data time‐shifted to Earth have been analyzed for systematic and random differences. ACE moments‐based proton densities are larger than Wind/Solar Wind Experiment (SWE) fits‐based densities by up to 18%, depending on solar wind speed. ACE temperatures are less than Wind/SWE temperatures by up to ∼25%. ACE densities and temperatures were normalized to equivalent Wind values in National Space Science Data Center's creation of the OMNI 2 data set that contains 1963–2004 solar wind field and plasma data and other data. For times of ACE‐Wind transverse separations <60 R E , random differences between Wind values and normalized ACE values are ∼0.2 nT for ∣ B ∣, ∼0.45 nT for IMF Cartesian components, ∼5 km/s for flow speed, and ∼15 and ∼30% for proton densities and temperatures. These differences grow as a function of transverse separation more rapidly for IMF parameters than for plasma parameters. Autocorrelation analyses show that spatial scales become progressively shorter for the parameter sequence: flow speed, IMF magnitude, plasma density and temperature, IMF X and Y components, and IMF Z component. IMF variations have shorter scales at solar quiet times than at solar active times, while plasma variations show no equivalent solar cycle dependence.