USGS Alaska Benchmark Glacier Mass Balance Data - Phase 1; Gulkana and Wolverine Glaciers

• Main Authors: Shad O'Neel, Louis Sass, Chris McNeil, Dan McGrath
• Format: Dataset
• Language: unknown
• Published: USGS Science Data Catalog 2016
• Subjects: Cryosphere; Glaciers/Ice Sheets; Glaciology; inlandWaters; Gulkana Glacier; Wolverine Glacier; Alaska; glacier; glaciers
• Online Access: https://search.dataone.org/view/a5cb52a5-6100-407f-ae14-19df831a459c

Since the late 1950s, USGS has maintained a long-term glacier mass-balance program at three North American glaciers. Similar measurements began at Sperry Glacier, MT in 2005. Direct field measurements are combined with weather data and imagery analyses to estimate the seasonal and annual mass balance at each glacier in both a conventional and reference surface format (Cogley and others, 2011). The analysis framework (van Beusekom and others, 2010; O’Neel and others, 2014) is identical at each glacier to enable cross-comparison between output time series. Vocabulary used follows Cogley and others (2011) Glossary of glacier mass balance. Phase one of this data release will include input and output files from the USGS Alaska Benchmark Glacier Program. Three types of input are provided for Wolverine and Gulkana glaciers: 1) time-variable Accumulation Area Distribution; 2) time series of point water balance at three index sites on each glacier (with secondary sites given in recent years); 3) weather data from stations installed along the glacier margins. Two solution sets are output for each glacier: 1) Conventional glacier-wide mass balance from direct observations; 2) Geodetically calibrated, conventional glacier-wide mass balance, which represents our preferred solution. The USGS runs an analysis code to transform the three input data to the output data that will be included in Phase three of this data release. Output data represent surface mass balance estimates. We do not account for basal or englacial accumulation or ablation. Mass balances are reported in water equivalent (w.e.) units, and often represent integration of multiple field measurements. Whenever possible, we average multiple field measurements to account for surface roughness and measurement errors. These ‘unprocessed observables’ will form the basis of Phase two of this data release.