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. 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. 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 GNSS-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 derived and validated against the CryoSat-2/SMOS (CS2SMOS) reference dataset. The combined retrieval achieves improved performance, with a reduced unbiased root mean square error (ubRMSE = 0.540 m) and lower bias relative to individual GNSS-R products. Notably, the method performs well in the 0.5–1 m SIT range, where existing satellite sensors are less reliable. Retrieved salinity and density fields exhibit spatial patterns consistent with known geophysical behavior. While some seasonal biases remain, particularly underestimation during early and late ice growth periods, this study establishes Spire GNSS-R as a viable observational asset for sea-ice remote sensing. The approach offers high revisit frequency, moderate spatial resolution, and the potential for long-term monitoring of sea-ice evolution.
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.