Assimilating Grape Doppler Receiver Data into Bayesian Frameworks

The Ham Radio Science Citizen Investigation (HamSCI) joins scientists and volunteers to collect data as part of a personal space weather station (PSWS) project. As part of the PSWS network, the distributed array of high frequency Grape receivers record Doppler shifted signals from national time standard stations such as WWV in Fort Collins, Colorado. The recorded Doppler shift is a result of the signal passing through the earth’s atmosphere and therefore provides insight into the state and variability of the ionosphere. The Grape network includes Grape 1 Doppler receivers, as well as multi-channel Grape 2 and WSPR (Weak Signal Propagation Reporter) Grapes which generate spectral data. Ionospheric measurements are sparse by nature and can’t give a complete picture of the ionosphere. Similarly, although there are extensive models of the ionosphere, they don’t replicate the variability and real-time conditions that data indicates. Therefore reconstruction of an ionospheric event, such as the activity during the 2023 and 2024 solar eclipses, can benefit from incorporating measured data into assumed prior models to estimate the value of a measurement. This poster examines the construction of the Grape inverse problem and mathematical algorithms and techniques to produce an approximation of the ionospheric state during an event.