Mass Balance Evolution of Black Rapids Glacier, Alaska, 1980–2100, and Its Implications for Surge Recurrence

Abstract

Surge-type Black Rapids Glacier, Alaska, has undergone strong retreat since it last surged in [1936][1937]. To assess its evolution during the late Twentieth and Twenty-first centuries and determine potential implications for surge likelihood, we run a simplified glacier model over the periods 1980-2015 (hindcasting) and 2015-2100 (forecasting). The model is forced by daily temperature and precipitation fields, with downscaled reanalysis data used for the hindcasting. A constant climate scenario and an RCP 8.5 scenario based on the GFDL-CM3 climate model are employed for the forecasting. Debris evolution is accounted for by a debris layer time series derived from satellite imagery (hindcasting) and a parametrized debris evolution model (forecasting). A retreat model accounts for the evolution of the glacier geometry. Model calibration, validation and parametrization rely on an extensive set of in situ and remotely sensed observations. To explore uncertainties in our projections, we run the glacier model in a Monte Carlo fashion, varying key model parameters and input data within plausible ranges. Our results for the hindcasting period indicate a negative mass balance trend, caused by atmospheric warming in the summer, precipitation decrease in the winter and surface elevation lowering (climate-elevation feedback), which exceed the moderating effects from increasing debris cover and glacier retreat. Without the 2002 rockslide deposits on Black Rapids' lower reaches, the mass balances would be more negative, by ∼ 20% between the 2003 and 2015 mass-balance years. Despite its retreat, Black Rapids Glacier is substantially out of balance with the current climate. By 2100, ∼ 8% of Black Rapids' 1980 area are projected to vanish under the constant climate scenario and ∼ 73% under the RCP 8.5 scenario. For both scenarios, the remaining glacier portions are out of balance, suggesting continued retreat after 2100. Due to mass starvation, a surge in the Twenty-first century is unlikely. The projected retreat will affect the glacier's runoff and change the landscape in the Black Rapids area markedly.

Explaining mass balance and retreat dichotomies at Taku and Lemon Creek Glaciers, Alaska

“…We addressed the lack of ablation zone observations using TSL observations (Kienholz and others, 2017). This involved using available georeferenced imagery (e.g.…”

Impact of glacier loss and vegetation succession on annual basin runoff

“…This assumption is based on a general understanding of the processes that are expected to increase evapotranspiration, including increases in vegetation biomass, type, percentage cover, and temperature (Jaramillo et al, 2018;Andréassian, 2004;Barnett et al, 2005), although we note that there are few studies on changes in evapotranspiration throughout vegetation succession following deglaciation. Overall, results for nonglaciated paired watershed studies show increased biomass and reforestation lead to higher levels of evapotranspiration and decreased annual basin runoff (Sun et al, 2010;Klaar et al, 2015;Jaramillo et al, 2018;Bosch and Hewlett, 1982;Andréassian, 2004).…”

“…First, we assume that the catchment becomes increasingly vegetated following deglaciation and that the type of vegetation within a basin depends only on the time since deglaciation. The assumption is based on the time since deglaciation being highly correlated with vegetation types, biomass, and cover (Crocker and Major, 1955;Burga et al, 2010;Chapin et al, 1994;Klaar et al, 2015;Whelan and Bach, 2017;Fickert et al, 2017;Wietrzyk et al, 2018), and does not account for the effect that altitude has on vegetation levels (Cowie et al, 2014;Whelan and Bach, 2017). However, in some cases succession rates during glacier recession are comparable at different altitudes because changes in air temperature with altitude can be offset by climate warming (Fickert et al, 2017).…”

An Automated Approach for Estimating Snowline Altitudes in the Karakoram and Eastern Himalaya From Remote Sensing

“…Identifying various surfaces on glaciers (fresh snow, clean glacier ice, and supra-glacial debris cover) and extracting glacier snowlines are needed for glacier mass balance calibration and validation, as demonstrated in a growing body of literature (Rabatel et al, 2005(Rabatel et al, , 2008(Rabatel et al, , 2017Gardelle et al, 2013;Huss et al, 2013;Kienholz et al, 2017;Barandun et al, 2018). Snowline altitudes (SLAs), when measured at the end of the melt season, represent the equilibrium line altitude (ELA) of a glacier (Meier, 1962), which is an indicator of seasonal/annual glacier mass balance and its response to climatic variability (Paterson, 1994).…”

“…Thakur et al (2017) used SAR imagery to separate glacier facies for a small sub-basin in the North West Himalayas, but the large scale application of this method might be limited by the availability of the SAR data and the extensive data processing. Kienholz et al (2017) defined the limit between ice/firn and snow in Alaska on the basis of Landsat false color composites and a DEM and manually extracted multitemporal SLAs. Huss et al (2013) and Barandun et al (2018) extracted SLAs based on ground photographs and a DEM using an innovative method, but this was only applied to a few glaciers.…”