Interannual variability of summer surface mass balance and surface melting in the Amundsen sector, West Antarctica

Abstract

Understanding the interannual variability of surface mass balance (SMB) and surface melting in Antarctica is key to quantify the signal-to-noise ratio in climate trends, identify opportunities for multi-year climate predictions and assess the ability of climate models to respond to climate variability. Here we simulate summer SMB and surface melting from 1979 to 2017 using the Regional Atmosphere Model (MAR) at 10 km resolution over the drainage basins of the Amundsen Sea glaciers in West Antarctica. Our simulations reproduce the mean present-day climate in terms of near-surface temperature (mean overestimation of 0.10 • C), near-surface wind speed (mean underestimation of 0.42 m s −1 ), and SMB (relative bias < 20 % over Thwaites glacier). The simulated interannual variability of SMB and melting is also close to observation-based estimates.For all the Amundsen glacial drainage basins, the interannual variability of summer SMB and surface melting is driven by two distinct mechanisms: high summer SMB tends to occur when the Amundsen Sea Low (ASL) is shifted southward and westward, while high summer melt rates tend to occur when ASL is shallower (i.e. anticyclonic anomaly). Both mechanisms create a northerly flow anomaly that increases moisture convergence and cloud cover over the Amundsen Sea and therefore favors snowfall and downward longwave radiation over the ice sheet. The part of interannual summer SMB variance explained by the ASL longitudinal migrations increases westward and reaches 40 % for Getz. Interannual variation in the ASL relative central pressure is the largest driver of melt rate variability, with 11 % to 21 % of explained variance (increasing westward). While high summer SMB and melt rates are both favored by positive phases of El Niño-Southern Oscillation (ENSO), the Southern Oscillation Index (SOI) only explains 5 % to 16 % of SMB or melt rate interannual variance in our simulations, with moderate statistical significance. However, the part explained by SOI in the previous austral winter is greater, suggesting that at least a part of the ENSO-SMB and ENSO-melt relationships in summer is inherited from the previous austral winter. Possible mechanisms involve sea ice advection from the Ross Sea and intrusions of circumpolar deep water combined with melt-induced ocean overturning circulation in ice shelf cavities. Finally, we do not find any correlation with the Southern Annular Mode (SAM) in summer.

Future ice-sheet surface mass balance and melting in the Amundsen region, West Antarctica

“…Our projections of the West Antarctic surface climate for the end of the 21 st century are based on version 3.9.3 of the MAR regional atmospheric model (Gallée and Schayes, 1994;Agosta et al, 2019). Our regional configuration is centred on the Amundsen Sea sector, covers 2800×2400 km, and was developed by Donat-Magnin et al (2020). The horizontal resolution is 10 km and and we use 24 vertical sigma levels located from approximately 1 m above the ground to 0.1 hPa.…”

“…The simulation representative of the present climate is the one descried in Donat-Magnin et al (2020). It is forced laterally (pressure, wind, temperature, specific humidity), at the top four levels (temperature, wind), and at the surface (sea ice concentration, sea surface temperature) by 6-hourly outputs of the ERA-interim reanalysis (Dee et al, 2011), which has a good representation of the Antarctic climate (Bromwich et al, 2011;Huai et al, 2019).…”

“…Computing projections of future SMB and surface melt rates remains challenging, because of the strong natural variability at regional scales (Lenaerts et al, 2016;Donat-Magnin et al, 2020), biases in global climate models (GCMs) (Bracegirdle et al, 2013;Swart and Fyfe, 2012) and GCM resolutions that are too coarse to resolve the orographic processes in the relatively steep coastal area (Krinner et al, 2008;Lenaerts et al, 2012;Agosta et al, 2013). Most models that participated in the 5 th Climate Model Intercomparison Project (CMIP5 Taylor et al, 2012) overestimated the present-day Antarctic precipitation, by more than 100% in some cases (Palerme et al, 2017).…”

“…These models also had a generally poor representation of the snow-pack energy balance, which is why future melt rate estimates have often been derived from simulated air temperatures rather than directly provided by the models (Davies et al, 2014;Trusel et al, 2015), and most limitations remain relevant in the CMIP6 models (Mudryk et al, 2020). Recent versions of regional climate models (RCMs) with a comprehensive representation of polar processes are now able to simulate melt rates in reasonable agreement with observational estimates (Lenaerts et al, 2018;Datta et al, 2019;Donat-Magnin et al, 2020). Using this kind of RCMs to downscale projections from GCMs can significantly reduce surface biases (Fettweis et al, 2013).…”

El Niño Southern Oscillation signal in a new East Antarctic ice core, Mount Brown South

“…El Niño (La Niña) events are also known to weaken (strengthen) the Amundsen Sea Low, a quasi-stationary low pressure region in the South Pacific, and have a significant influence on the West Antarctic climate (Hosking et al 2013). However, several studies also suggest a complex and limited relationship with ENSO, at least for the Surface Mass Balance (SMB) and melt, as part of summer variability is inherited from the previous austral winter (e.g., Donat-Magnin et al 2020). Signals for the ENSO in East Antarctica are more muted, however a significant signal for the ENSO is preserved in the summer sea salt record from LD (Vance et al 2013).…”