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Zachary Hoppinen

Publications and source records attributed to Zachary Hoppinen.

2 recordsLinked to original sources

Interferometric Synthetic Aperture Radar (InSAR) for monitoring seasonal snow

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.

Water Resources Research↗

A case study and comparison of mid-winter warming and solar driven wet slab avalanche cycles

Wet slab avalanches are poorly understood and often difficult to forecast. Yet, wet slab avalanches can be destructive and may become more common in a changing climate. As the onset of wet avalanches moves earlier in the winter season due to climate change, understanding snowpack and meteorological characteristics of wet slab avalanches will become increasingly important. In this study, we examined two recent late-January wet slab cycles triggered by warming and solar input in the Rocky Mountains of Idaho and Montana, United States. We posed two questions to help us understand these potentially increasingly frequent, mid-winter wet slab cycles: i) what are the weather and snowpack patterns of two mid-winter wet slab cycles and ii) how did these non-rain-on-snow, mid-winter warming events compare to the historical climate normal? In both locations, a short-lived ridge of high pressure strengthened over the region from late January to early February 2024. Temperatures rapidly increased to 6° C at middle and upper-elevation locations and remained above freezing for 48 to 72 hours. Wet slab avalanches (Montana: n=68, Idaho: n=11) released on a layer of facets resting on a crust formed in late December and slab depths averaged 40 to 150 cm. Avalanches primarily occurred on southeast, south, and southwest aspects at middle and upper elevations. Additionally, positive January monthly temperature trends exist in both locations from 1990 to 2020, and these two cycles from 2024 highlight impacts of midwinter warming events with unstable snowpack conditions. These cycles also highlight how a relatively uncommon mid-winter warming event with low radiative input can produce very large destructive wet slab avalanches. Understanding mid-winter warming events and associated wet slab avalanche cycles will help us prepare and forecast for potentially more common scenarios like this in the future.

Idaho, Montana↗