Long-term surface energy balance of the western Greenland Ice Sheet and the role of large-scale circulation variability

• Published in: The Cryosphere
• Main Authors: B. Huai, M. R. van den Broeke, C. H. Reijmer
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2020
• Subjects: geo; envir; Greenland; Kangerlussuaq; Ice Sheet; North Atlantic; North Atlantic oscillation; The Cryosphere; Thule
• Online Access: https://doi.org/10.5194/tc-14-4181-2020; https://tc.copernicus.org/articles/14/4181/2020/tc-14-4181-2020.pdf; https://doaj.org/article/033e6f678844420bbdd758d0b3282987

We present the surface energy balance (SEB) of the western Greenland Ice Sheet (GrIS) using an energy balance model forced with hourly observations from nine automatic weather stations (AWSs) along two transects: the Kangerlussuaq (K) transect with seven AWSs in the southwest and the Thule (T) transect with two AWSs in the northwest. Modeled and observed surface temperatures for non-melting conditions agree well with RMSEs of 1.1–1.6 K, while reasonable agreement is found between modeled and observed 10 d cumulative ice melt. Absorbed shortwave radiation (Snet) is the main energy source for melting (M), followed by the sensible heat flux (Qh). The multiyear average seasonal cycle of SEB components shows that Snet and M peak in July at all AWSs. The turbulent fluxes of sensible (Qh) and latent heat (Ql) decrease significantly with elevation, and the latter becomes negative at higher elevations, partly offsetting Qh. Average June, July and August (JJA) albedo values are 0.7 for the higher stations. The near-surface climate variables and surface energy fluxes from reanalysis products ERA-Interim, ERA5 and the regional climate model RACMO2.3 were compared to the AWS values. The newer ERA5 product only significantly improves ERA-Interim for albedo. The regional model RACMO2.3, which has higher resolution (5.5 km) and a dedicated snow/ice module, unsurprisingly outperforms the reanalyses for (near-)surface climate variables, but the reanalyses are indispensable in detecting dependencies of west Greenland climate and melt on large-scale circulation variability. We correlate ERA5 with the AWS data to show a significant positive correlation of western GrIS summer surface temperature and melt with the Greenland Blocking Index (GBI) and weaker and opposite correlations with the North Atlantic Oscillation (NAO). This analysis may further help to explain melting patterns on the western GrIS from the perspective of circulation anomalies.