Abstract. Planetary magnetic fields provide critical insight into interior structure, dynamo action, and magnetosphere–ionosphere coupling. However, in situ magnetometer measurements are constrained by spacecraft trajectories, leaving large regions of planetary magnetic environments unexplored. Faraday rotation of radio signals during radio occultation (RO) offers a complementary remote sensing technique capable of probing magnetic fields and plasma simultaneously. We develop an analytical framework to quantify the precision of magnetic field measurements derived from Faraday rotation and establish an error model that propagates phase-tracking and total electron content (TEC) uncertainties into the weighted mean line-of-sight (LOS) magnetic field retrieval. The model incorporates realistic parameters for NASA’s Deep Space Network (DSN) and is validated using Cassini’s dual-polarization S- and X-band solar conjunction data. A sensitivity analysis quantifies how the relative magnetic field uncertainty depends on signal-to-noise ratio, Sun-Earth-probe angle, magnetic field strength, TEC, and TEC uncertainty. Lower frequencies and one-way links yield the smallest errors, while dual-frequency links enable simultaneous measurements of LOS TEC and magnetic field. When TEC uncertainty is below a few percent, phase-tracking noise dominates; at higher values, TEC error becomes the primary limitation. Application to Jupiter using a sample Juno occultation trajectory shows that the two-way S-band link (X-band uplink, S-band downlink) achieves a minimum ∼6% relative uncertainty (1-sigma) near the surface and grows to ∼300% near 4000 km altitude. Faraday-rotation-based RO may therefore provide a practical approach for probing planetary magnetic fields with existing DSN capabilities.
Abstract. Accurate estimation of sea-ice thickness (SIT) is essential for understanding polar climate processes and supporting operational monitoring. This study demonstrates, for the first time, the use of grazing-angle global navigation satellite system reflectometry (GNSS-R) reflectivity from the Spire CubeSat Constellation to retrieve SIT, alongside sea-ice salinity and density. We extend previous work on near-nadir GNSS-R by integrating both near-nadir and grazing-angle observations using a three-layer ice reflectivity model and inversion framework. Weekly SIT products are generated and validated against the CryoSat-2/SMOS (CS2SMOS) reference dataset. The combined retrieval reduces the unbiased root-mean-square error (ubRMSE) to 0.540 m (0.376 m within the 0.5–1 m SIT range), compared with individual full-Arctic product ubRMSEs of 0.609–0.743 m. Within the 0.5–1 m SIT range, where individual Soil Moisture and Ocean Salinity (SMOS) and CryoSat-2 retrievals are less reliable, the combined retrieval achieves lower ubRMSE than every individual GNSS-R product, although a slight positive bias remains. Retrieved salinity and density fields, derived as by-products of the inversion, show spatial patterns consistent with known geophysical behavior. While some seasonal biases remain, especially underestimation during early and late ice growth periods, this study demonstrates the potential of Spire GNSS-R as a complementary observation source for sea-ice remote sensing, offering high revisit frequency and moderate spatial resolution that may contribute to future fused SIT records as the technique matures.
Abstract. During its Grand Finale, the Cassini spacecraft collected crucial gravity data, revealing Saturn's low-degree gravity harmonics and large-scale zonal winds extending about 8,000 km deep. However, determining the high-degree gravity field, essential for understanding small-scale atmospheric dynamics, is challenging due to the limited spatial coverage of Cassini's periapses. To overcome this limitation, we employed Slepian functions, orthogonal within a bounded domain, to represent Saturn's localized high-degree gravity field. Focusing on latitudes from 32°S to 32°N, we estimated Slepian coefficients that represent short-scale latitudinal gravity variations. The reconstructed wind profile that explains low-degree harmonics can also reproduce these high-degree variations, assuming Saturn's atmosphere is, to first order, in thermal wind balance. Our findings suggest that small-scale winds may extend to depths between 7,000 km and 9,000 km, providing strong evidence that Saturn's zonal flows are oriented along coaxial cylinders, rotating at different angular velocities.
Abstract. Signals of opportunity reflectometry (SoOp-R), the reutilization of noncooperative satellite transmissions for communication and navigation, is a promising approach to remote sensing of root-zone soil moisture (RZSM). Satellite transmissions in the frequency ranges of 137–138, 240–270, and 360–380 MHz are of interest due to the increased penetration depth. These can be combined with global navigation satellite system reflectometry (GNSS-R) in L-band (1575.42 MHz) to estimate the subsurface SM profile. The objective is to define requirements (e.g., frequency and polarization combinations, observation error, and temporal coincidence of multisource observations) for satellite-based remote sensing of RZSM. Our approach is to use synthetic observations generated from multiyear time series of in situ SM measurements from seven U.S. climate reference network (USCRN) sites and dynamic vegetation structure based on a simple scaling method. A multifrequency/polarimetric retrieval algorithm is developed and applied to these synthetic observations and used to predict retrieval errors for a range of changes in system parameters. We found that the use of both high and low frequencies improves retrieval accuracy by limiting uncertainties from vegetation and surface SM and providing sensitivity to deeper layers. Moreover, the retrieval errors were found to increase linearly with the reflectivity error and inter-frequency time delays. A bivariate model derived from this linear relationship will be useful for developing requirements on reflectivity precision based upon science requirements for SM/vegetation water content (VWC) retrievals. Although orbits of specific transmitter constellations were used to generate realistic distributions of incidence angle combinations, the method and results could be applied more generally.
Abstract. Signals of Opportunity (SoOp) represents a remote sensing methodology that leverages anthropogenic signals from non-cooperative transmitters to measure the geophysical parameters of the scattering medium. This concept extends the principles of Global Navigation Satellite System Reflectometry (GNSS-R) to signals transmitted in frequency bands not allocated for scientific use. This article introduces a framework for exploring the tradespace of SoOp system parameters, facilitating the high-level design of SoOp missions. The focus is on optimizing multi-frequency SoOp constellations for land applications, addressing challenges related to coverage determination, signal quality assessment, and inter-frequency time delay. A design study is presented, incorporating sensitivity analysis results for root zone soil moisture (RZSM) and vegetation water content (VWC) retrievals. The proposed multi-frequency SoOp constellation involves transmitters from Orbcomm, Mobile User Objective System (MUOS), and four GNSSs (GPS, Galileo, GLONASS, Beidou), with hundreds of design alternatives evaluated based on standard scoring functions that consider cost and coverage metrics. This paper contributes to the understanding and optimization of SoOp missions, supporting their cost-effective implementation with enhanced spatiotemporal resolutions and scientific observation accuracy.