Abstract
Glacier mass balance models are needed at sites with scarce long-term observations to reconstruct past glacier mass balance and assess its sensitivity to future climate change. In this study North American Regional Reanalysis (NARR) data are used to force a physically-based, distributed glacier mass balance model of Saskatchewan Glacier for the historical period 1979–2016 and assess it sensitivity to climate change. A two-year record (2014–2016) from an on-glacier automatic weather station (AWS) and a homogenized historical precipitation record from nearby permanent weather stations were used to downscale air temperature, relative humidity, wind speed, incoming solar radiation and precipitation from the nearest NARR gridpoint to the glacier AWS site. The model was run with fixed (1979, 2010) and time-varying (dynamic) geometry using a multi-temporal digital elevation model (DEM) dataset. The model showed a good performance against recent (2012–2016) direct glaciological mass balance observations as well as with cumulative geodetic mass balance estimates. The simulated mass balance showed a large sensitivity to the biases in NARR precipitation and solar radiation, as well as to the prescribed precipitation lapse rate and ice aerodynamic roughness lengths, showing the importance of constraining these parameters with ancillary data. The difference between the static (1979) and dynamic simulations showed small differences (mean = 0.06 m w.e. a−1 or 1.5 m w.e. over 37 yrs), indicating minor effects of elevation changes on the glacier specific mass balance. The static mass balance sensitivity to climate was assessed for prescribed changes in regional mean air temperature between 0 to 7 °C and precipitation between −20 to +20 %, which comprise the spread of ensemble IPCC representative concentration pathways climate scenarios for the mid (2041–2070) and late (2071–2100) 21st century. The climate sensitivity experiments showed that future changes in precipitation would have a small impact on glacier mass-balance, while the temperature sensitivity increases with warming, from −0.65 to −0.93 m w.e. °C−1. Increased melting accounted for 90 % of the temperature sensitivity while precipitation phase feedbacks accounted for only 10 %. Roughly half of the melt response to warming was driven by a positive albedo feedback, in which glacier albedo decreases as the snow cover on the glacier thins and recedes earlier in response to warming, increasing net solar radiation fluxes. About one quarter of the melt response to warming was driven by latent heat energy gains (positive humidity feedback). Our study underlines the key role of albedo and air humidity in modulating the response of winter-accumulation type mountain glaciers and upland icefield-outlet glacier settings to climate.
Highlights
Global warming is expected to cause reduced snowfall in cold regions, earlier snowmelt in spring and a longer ice melt period in summer (e.g. Aygün et al, 2019; Barnett et al, 2005)
Increased melting accounted for 90% of the temperature sensitivity while precipitation phase feedbacks accounted for only 10%
Half of the melt response to warming was driven by a positive albedo feedback, in which glacier albedo decreases as the snow cover on the glacier thins and recedes earlier in response to warming, increasing net solar radiation fluxes
Summary
Global warming is expected to cause reduced snowfall in cold regions, earlier snowmelt in spring and a longer ice melt period in summer (e.g. Aygün et al, 2019; Barnett et al, 2005). Spatially-distributed, physically-based models rely on energy balance calculations to explicitly account for all energy exchanges between the glacier surface and atmosphere They are more 70 complex and contain several parameters that are sometimes difficult to estimate and require several input observations (e.g. Anderson et al, 2010; Anslow et al, 2008; Arnold et al, 1996; Gerbaux et al, 2005; Hock and Holmgren, 2005; Klok and Oerlemans, 2002; Mölg et al, 2008). These models better represent the physical processes which drive glacier ablation and are more suited to simulate glacier mass balance outside of present-day climate conditions (Hock et al, 2007; MacDougall and Flowers, 2011), given that accurate forcing data is available (Réveillet et al, 2018). This makes physically based distributed models an ideal tool to estimate glacier climate sensitivity, i.e., the mass balance response to a change in climate conditions (Braithwaite and Raper, 2002; Che et al, 2019; Ebrahimi and Marshall, 2016; Engelhardt et al, 2015; Hock et al, 2007; Klok and Oerlemans, 2004; Oerlemans et al, 1998)
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