Abstract

Abstract. A simulation of the surface climate of Vatnajökull ice cap, Iceland, carried out with the regional climate model HIRHAM5 for the period 1980–2014, is used to estimate the evolution of the glacier surface mass balance (SMB). This simulation uses a new snow albedo parameterization that allows albedo to exponentially decay with time and is surface temperature dependent. The albedo scheme utilizes a new background map of the ice albedo created from observed MODIS data. The simulation is evaluated against observed daily values of weather parameters from five automatic weather stations (AWSs) from the period 2001–2014, as well as in situ SMB measurements from the period 1995–2014. The model agrees well with observations at the AWS sites, albeit with a general underestimation of the net radiation. This is due to an underestimation of the incoming radiation and a general overestimation of the albedo. The average modelled albedo is overestimated in the ablation zone, which we attribute to an overestimation of the thickness of the snow layer and not taking the surface darkening from dirt and volcanic ash deposition during dust storms and volcanic eruptions into account. A comparison with the specific summer, winter, and net mass balance for the whole of Vatnajökull (1995–2014) shows a good overall fit during the summer, with a small mass balance underestimation of 0.04 m w.e. on average, whereas the winter mass balance is overestimated by on average 0.5 m w.e. due to too large precipitation at the highest areas of the ice cap. A simple correction of the accumulation at the highest points of the glacier reduces this to 0.15 m w.e. Here, we use HIRHAM5 to simulate the evolution of the SMB of Vatnajökull for the period 1981–2014 and show that the model provides a reasonable representation of the SMB for this period. However, a major source of uncertainty in the representation of the SMB is the representation of the albedo, and processes currently not accounted for in RCMs, such as dust storms, are an important source of uncertainty in estimates of snow melt rate.

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