Abstract
Abstract. Meltwater from the Greenland Ice Sheet contributed 1.7–6.12 mm to global sea level between 1993 and 2010 and is expected to contribute 20–110 mm to future sea level rise by 2100. These estimates were produced by regional climate models (RCMs) which are known to be robust at the ice sheet scale but occasionally miss regional- and local-scale climate variability (e.g. Leeson et al., 2017; Medley et al., 2013). To date, the fidelity of these models in the context of short-period variability in time (i.e. intra-seasonal) has not been fully assessed, for example their ability to simulate extreme temperature events. We use an event identification algorithm commonly used in extreme value analysis, together with observations from the Greenland Climate Network (GC-Net), to assess the ability of the MAR (Modèle Atmosphérique Régional) RCM to reproduce observed extreme positive-temperature events at 14 sites around Greenland. We find that MAR is able to accurately simulate the frequency and duration of these events but underestimates their magnitude by more than half a degree Celsius/kelvin, although this bias is much smaller than that exhibited by coarse-scale Era-Interim reanalysis data. As a result, melt energy in MAR output is underestimated by between 16 and 41 % depending on global forcing applied. Further work is needed to precisely determine the drivers of extreme temperature events, and why the model underperforms in this area, but our findings suggest that biases are passed into MAR from boundary forcing data. This is important because these forcings are common between RCMs and their range of predictions of past and future ice sheet melting. We propose that examining extreme events should become a routine part of global and regional climate model evaluation and that addressing shortcomings in this area should be a priority for model development.
Highlights
Since the 1990s, the Greenland Ice Sheet has shifted from a state of near mass balance to one of significant mass loss (Shepherd et al, 2012; Hanna et al, 2013a; van den Broeke et al, 2016), contributing approximately 10 % to the measured global sea level rise during the last 2 decades (Church, 2013)
We apply extreme value analysis to observed daily maximum temperatures from Greenland Climate Network (GC-Net) in order to compile a statistical climatology of extreme temperature events on Greenland (Table 3)
Analysis of GC-Net temperature data shows that the frequency, magnitude and duration of extreme temperature events on Greenland are strongly controlled by geography, though further work is needed to determine the relative contributions of potential physical drivers of extreme events at different locations and over different time periods
Summary
Since the 1990s, the Greenland Ice Sheet has shifted from a state of near mass balance to one of significant mass loss (Shepherd et al, 2012; Hanna et al, 2013a; van den Broeke et al, 2016), contributing approximately 10 % to the measured global sea level rise during the last 2 decades (Church, 2013). In addition to directly removing more of the ice sheet into the sea, melting reduces the reflectivity of the ice sheet and can warm the perennial snowpack (through latent heat release when the meltwater refreezes), both of which act as a positive feedback to further enhance melt. These processes alter the dielectric properties of the ice sheet surface, which makes it more difficult to measure surface height change using satellite-borne radar instruments (McMillan et al, 2016). An understanding of the location, frequency, duration and magnitude of melting is necessary to (1) understand the ice sheet’s response to climate change, (2) interpret contemporary measurements of ice sheet volume change and (3) constrain predictions of future ice sheet state
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
