Abstract

Abstract. 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 <0.6 for stations below 1000 m a.s.l. and >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.

Highlights

  • In recent decades, the Greenland Ice Sheet (GrIS) has been a major contributor to global sea level rise and is expected to remain so in the future (The IMBIE Team, 2019), raising worldwide concerns for coastal flooding and negative impacts on ecosystems (Pörtner et al, 2020)

  • We study the dependency of western Greenland surface energy balance (SEB) and melt on large-scale circulation variability along two GrIS automatic weather stations (AWSs) transects, i.e., the southwestern Kangerlussuaq (K) transect and the northwestern Thule (T) transect

  • Several studies identified a link between anomalously high air temperatures over the GrIS during negative North Atlantic Oscillation (NAO) phases (Hanna and Cappelen, 2003; Chylek et al, 2004)

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Summary

Introduction

The Greenland Ice Sheet (GrIS) has been a major contributor to global sea level rise and is expected to remain so in the future (The IMBIE Team, 2019), raising worldwide concerns for coastal flooding and negative impacts on ecosystems (Pörtner et al, 2020). Strong Greenland blocking episodes have been linked to exceptional surface melting of the western GrIS (Hanna et al, 2014, 2016), and recently a Greenland Blocking Index (GBI) has been defined by Fang (2004) and Hanna et al (2013, 2014, 2015) Another important regional mode of large-scale atmospheric circulation variability is the North Atlantic Oscillation (NAO) (Hurrell et al, 2003; Van den Broeke et al, 2017). We study the dependency of western Greenland SEB and melt on large-scale circulation variability along two GrIS AWS transects, i.e., the southwestern Kangerlussuaq (K) transect and the northwestern Thule (T) transect We put these regional results into a broader spatial context using reanalysis (ERA5, ERA-Interim) products and output from a regional atmospheric climate model (RACMO2.3).

AWS transects
AWS data and processing
ERA-Interim and ERA5
Monthly GBI and NAO index
Model description
SEB model evaluation
Surface height change
SEB components
Relationships with large-scale circulation variability
Summary and conclusions
Full Text
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