Rashmi Shah

Interferometric Synthetic Aperture Radar (InSAR) offers a potential pathway for measuring seasonal snow water equivalent (SWE) and snow depth at spatial and temporal scales needed for basin‐scale hydrology. First proposed for seasonal snow more than 25 years ago, InSAR uses repeat‐pass radar phase differences to estimate changes in SWE or depth caused by microwave propagation through snow. This review synthesizes InSAR‐based snow monitoring from early theoretical and satellite demonstrations through recent tower, airborne, and spaceborne studies. We summarize the retrieval physics, evaluate published validation results, compare performance across wavelengths and snow environments, and identify barriers to operational implementation. The literature shows that InSAR can provide high‐resolution, spatially distributed information on snow accumulation and ablation, especially under dry‐snow conditions when temporal coherence is maintained and snow phase can be separated from atmospheric, vegetation, soil‐moisture, and other non‐snow contributions. Longer wavelengths, particularly L‐band, help maintain coherence, reduce phase‐wrapping ambiguity, and support retrievals in some vegetated environments, making the NASA–ISRO Synthetic Aperture Radar (NISAR) mission a timely opportunity for basin‐scale testing. Remaining challenges include correcting ionospheric and tropospheric delays; defining stable reference phases; identifying, correcting, or flagging coherence loss and phase‐unwrapping errors; accounting for forest‐canopy interactions; collecting spatially distributed validation data; and scaling site demonstrations to regional or global products. Operational use will require algorithmic maturation, robust validation, and integration with other remote sensing and modeling approaches. If these challenges are addressed, InSAR‐capable satellites could become an important component of an integrated global snow observation suite.

U.S. civil spaceborne assets represent the forefront of engineering innovation across remote sensing domains such as gravimetry, thermal radiometry, imaging spectroscopy, light detection and ranging (LiDAR), and synthetic aperture radar (SAR). When acquired from the vantage point of space, these measurements often offer frequent observations that are critical for providing insights into monitoring and understanding Earth's carbon, energy, and water cycles—across the hydrosphere, biosphere, atmosphere, and lithosphere. Critically, they enable global‐ and regional‐scale assessments of national security relevant variables, which inform various activities across the food, water and energy sectors. Despite their immense potential, these Earth observations data sets remain underutilized, primarily due to significant workforce shortfalls in key technical capacities such as geodesy, remote sensing, artificial intelligence (AI), and machine learning (ML). Here, using water security as an example, we (a) elucidate the relevance and potential of Earth observations for national and water security; (b) assess the state of knowledge regarding workforce needs; and (c) discuss strategies to maximize the contributions of the Earth science workforce to reinforce water security capabilities.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

The United States relies on its coastal zones for vital ecosystem goods and services that bolster national socioeconomic well-being and resilience. As coastlines confront converging environmental stressors, the resulting impacts span U.S. stakeholder communities and reveal differing priorities across geographic and governance scales. Therefore, supporting effective coastal decision-making requires an understanding of these nuanced relationships. To address this, we conducted a hybridized literature review across U.S. stakeholder communities, governance scales, and geographic regions. Physical drivers, such as sea level rise, emerged as the dominant thematic focus in U.S. coastal literature (39.36%), with stronger emphasis in literature at the national scale (46.84%) than the regional scale (34.30%). Whereas national scale ecosystem health (12.52%) and water quality challenges (15.93%) was less prevalent than regional ecosystem health (18.15%) and water quality (20.39%). This pattern highlights a granularity gap of coastal information needs, as national scale literature tends to prioritize upstream systems drivers, while regional scale literature focuses on more localized impacts relevant to place-based management. Additionally, challenges, stressors, and sectors are frequently discussed in relation to one another, underscoring the inherently interconnected nature of coastal systems. Taken together, these findings emphasize the importance of linking broad, upstream forcings with the downstream, management decisions. Viewing the coast holistically as a system rather than a collection of isolated components strengthens the foundation for effective decision-making, supports responsive monitoring, and clarifies pathways for resilience and mitigation across the nation’s coastlines.

This study uses spaceborne grazing-angle Global Navigation Satellite System-Reflectometry (GNSS-R) signals to measure surface height variations of the Tonlé Sap Lake in Cambodia. GNSS-R tracks collected by Spire Global from 2021 to 2024 are compared with co-located Surface Water and Ocean Topography (SWOT) and Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) measurements. There is good agreement between all, with surface height correlation coefficients $>0.7$ . Over open water, the average measurement noise is 3, 2.5, and 1.6 cm for GNSS-R, SWOT, and ICESat-2, respectively. However, GNSS-R altimetry maintains a similar noise level under vegetation, while SWOT and ICESat-2 noise increase significantly to 4.6 cm and 6.9 cm, respectively. The ability to measure water height anomalies under vegetation in all weather and times of day highlights the strength of the GNSS-R altimetry method for inland water studies. Finally, persistent water surface anomalies as large as 12 and 15 cm present in all three satellite data suggest an EGM08 geoid anomaly over both the upper and lower part of the lake, and highlight the utility of these satellites for improving geoid representations over large lakes.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.