Glacies

This editorial highlights a pressing issue in snow and climate research: warming does not imply a simple, uniform decline in snowfall [...]

Glaciers in Wind River Range, Wyoming, have experienced substantial reductions in surface area and volume in recent decades, yet existing inventories contain temporal gaps and often mix glaciers with seasonal snowpack. We mapped and classified glacier outlines using high-resolution satellite imagery in 2006 in Google Earth Pro (version 7.3.7.1327) and compared them against inventories from 1963–1974, 2015, and 2020. A classification approach was applied to distinguish glaciers from snowpack based on Welch’s t-test of significant difference in elevation changes within and surrounding mapped outlines based on four digital elevation models from 2000 to 2019. Results show an 11% decrease in mapped glacier/snowpack features from 1963–1974 to 2006 (476 to 423), with a 21% reduction in mapped outlines classified as glaciers (314 to 247). Total glacier area declined from 48.35 km² in 1963–1974 to 34.06 km² in 2006, while volume decreased from 0.998 km³ to 0.701 km³. From 1963–1974 to 2015, area and volume losses reached 47% and 49%, respectively, consistent with accelerated regional retreat. An unusually low reduction observed from 2015 to 2020 is likely caused by methodological inconsistencies between existing inventories. This study underscores the need for standardized mapping protocols and robust classification between glaciers and snowpack to accurately document glacier changes and assess their impact on water resources.

The Northeast Snow Survey Feasibility Study began in October 2023 to characterize snow monitoring in the Northeastern United States and identify data and knowledge gaps to guide the deployment of a snow monitoring network similar to the western United States’ automated Snow TELemetry (SNOTEL) network. Researchers and interest holders in the region were contacted and engaged through online surveys, interviews, and email, using snowball sampling to identify and evaluate data breadth, gaps, and needs for snow monitoring in the region. Surveys identified important data gaps, including under-sampling of high-elevation areas, temporal gaps early in winter, low-frequency (weekly to monthly) temporal resolution in manual snow survey efforts, and a paucity of automated snow monitoring infrastructure. The data gaps, combined with previously published interest holder data needs, led to the development of three primary network objectives and guided the systems engineering and spatial design. Here, an open-source workflow using Google Earth Engine and R was developed to identify potential sites in the northern New England states of Maine, New Hampshire, and Vermont. This process identified 4015 sq km of suitable land for network siting across the three states that would help overcome the identified spatial and temporal data gaps while meeting interest holder data needs. This study establishes the need for a coordinated snow monitoring network in the Northeastern United States and presents a spatial design workflow that can be implemented to meet the identified objectives.