The Effects of Meltwater, Refreezing and Modelled Grain Size on Snow Albedo: Gaining Knowledge from Observations at Weather Stations and Numerical Modelling

• Main Author: Saunderson, Dominic
• Format: Dataset
• Language: unknown
• Published: GEUS Dataverse 2020
• Subjects: Greenland; Kangerlussuaq; Ice Sheet
• Online Access: https://dx.doi.org/10.22008/fk2/lf0f4x; https://dataverse01.geus.dk/citation?persistentId=doi:10.22008/FK2/LF0F4X

The extent to which snow and ice surfaces undergo melt is mainly dictated by their absorption of shortwave radiation, and thus the surface albedo is a critical parameter for accurately modelling the surface energy balance and mass balance of the Greenland Ice Sheet (GrIS). Multiple variables affect the surface albedo, including the atmospheric conditions, the solar zenith angle (SZA), and the snowpack’s characteristics. This thesis uses output from a firn evolution model (Vandecrux et al., in review) to explain 8 years of albedo observations from the Kangerlussuaq Upper (KAN_U) automatic weather station (PROMICE; Ahlstrøm et al., 2008). A parameterised model is developed that differentiates between three snow conditions (aged, refrozen, and wet), and uses four variables as input: the SZA; the Sky-Air Temperature Ratio (SATR); the Liquid Water Content (LWC); and the modelled grain size. When compared to the observed albedo at KAN_U, the model could explain more than 60% of the observed albedo variation for 2009, 2010, 2011 and 2015, but this fell below 30% for 2014. So far, no reasons for these differences have been uncovered. Each of the three snow conditions performed approximately equally well, and only the lightly cloudy skies were seen to be identifiable worse compared to any other cloud cover. The model was also largely consistent between months, with the exception of October, when the poor fit is attributed to the very short days and consistently high SZAs. An immediate priority is to test the model against albedo observations from other PROMICE datasets. It is unclear how applicable the model will be to other locations, because it explicitly replicates a rising albedo from the early morning to noon. This was consistently seen in the observational data at KAN_U but contradicts the accepted theory. However, it is possible that the approach used by this parameterisation could be easily modified and tuned to alternative locations.