Physically-based modelling of glacier evolution under climate change in the tropical Andes

Abstract. In recent years, opportunities have opened up to develop and validate glacier models in regions that have previously been infeasible due to observation and/or computational constraints, due to the availability of globally-capable glacier evolution modelling codes and spatially-extensive geodetic validation data. The glaciers in the tropical Andes represent some of the least observed and modelled glaciers in the world, making their trajectories under climate change uncertain. Studies to date, have typically adopted empirical models of the surface energy balance and ice flow to simulate glacier evolution under climate change, but these may miss important non-linearities in future glacier mass changes. We combine two globally-capable modelling codes that provide a more physical representation of these processes: i) JULES which solves the full energy balance of snow and ice; and ii) OGGM which solves a flowline representation of the shallow ice equation to simulate ice flow. JULES-OGGM is applied to over 500 tropical glaciers in the Vilcanota-Urubamba basin in Peru and is evaluated against available glaciological and geodetic mass balance observations to assess the potential for using the modelling workflow to simulate tropical glacier evolution over decadal timescales. We show that the JULES-OGGM model can be parameterised to capture decadal (2000–2018) mass changes of individual glaciers, but that limitations of the JULES prognostic snow model prevent accurate replication of observed surface albedo fluctuations. We conclude that this inhibits the robustness of extrapolating the JULES parameters across multiple glaciers. When driven with statistically-downscaled climate change projections, the JULES-OGGM simulations indicate that, contrary to point-scale energy balance studies, sublimation plays a very minor role in glacier evolution at the basin scale and does not bring about significant non-linearities in the glacier response to climate warming. The ensemble mean simulation estimates that total glacier mass will decrease to 17 % and 6 % of that in 2000 by 2100 for RCP4.5 and RCP8.5 respectively which is more conservative than estimates from some other global glacier models.