22 January 2018 from 14:30 to 15:30

PhD Defence Brice Noël

Modelling the surface mass balance of the Greenland ice sheet and neighbouring ice caps: a dynamical and statistical downscaling approach

The Greenland ice sheet (GrIS) is the world’s second largest ice mass, storing about one tenth of the Earth’s freshwater. If totally melted, global sea level would rise by 7.4 m, affecting low-lying regions worldwide. Since the mid-1990s, increased atmospheric and oceanic temperatures have accelerated GrIS mass loss through increased meltwater runoff and ice discharge from marine-terminating glaciers. Brice Noël studied the causes of recent GrIS surface mass loss.

Noëls research led to a publication in Nature Communications. Read the press release, the interactive web story and the publication, or watch the video below for an explanation by Noël himself.

Nature Communications
Brice Noël explains the results of his research published by Nature Communications

To study the causes of the recent GrIS surface mass loss, Noël used the Regional Atmospheric Climate Model RACMO2. This meteorological model simulates the GrIS surface mass balance (SMB), i.e. the difference between snowfall accumulation and ablation from meltwater runoff. To cover a large domain at reasonable computational cost, RACMO2 is run at a relatively coarse horizontal resolution of 11 km (1958-2016). At this spatial resolution, the model does not well resolve small glaciated bodies, such as narrow glaciers and small peripheral ice caps (GICs), detached from the main ice sheet. Therefore, Noël developed a statistical downscaling algorithm that reprojects the RACMO2 output on a 1 km grid. This downscaled product allows to quantify mass changes of small ice masses in unprecedented detail.

Tipping point in 1997 

Using the downscaled data set, he identified 1997 as a tipping point for the mass balance of Greenland’s GICs. The GICs are located in relatively dry regions where summer melt nominally exceeds winter snowfall. To sustain these ice caps, the refreezing of meltwater in the snow is a key process. The snow acts as a 'sponge' that buffers a large fraction of meltwater, which subsequently refreezes in winter. The remaining meltwater runs off to the ocean and directly contributes to mass loss.

Snow saturated with refrozen meltwater

Until 1997, the snow layer in the interior of these GICs could compensate for increased melt by refreezing more meltwater. Around 1997, following decades of increased melt, the snow became saturated with refrozen meltwater, so that any additional summer melt was forced to run off to the ocean, tripling the mass loss. This is called a tipping point, as it would take decades to regrow a new, healthy snow layer that could buffer enough summer meltwater. As a result, Greenland’s GICs are expected to undergo irreversible mass loss in the future.

Canadian Arctic Archipelago

Similar mechanisms are at play in the Canadian Arctic Archipelago. While the northern ice caps, that are larger and more elevated, can still efficiently buffer meltwater in their extensive snow-covered accumulation zones, the southern smaller and lower-lying ice fields have already lost most of their meltwater retention capacity, causing uninterrupted mass loss during the last six decades. Consequently, these southern ice caps are expected to disappear within the next 400 years.

Alarm-signal

For now, the main Greenland ice sheet is still safe, as porous snow in the extensive accumulation zone, covering about 90% of the GrIS, still buffers most of the summer melt. At the current rate of mass loss, it would still take 10,000 years to melt the GrIS completely. However, the tipping point reached for the peripheral GICs must be regarded as an alarm-signal for the GrIS in the near future, if temperatures continue to increase.

Start date and time
22 January 2018 14:30
End date and time
22 January 2018 15:30
PhD candidate
B.P.Y. (Brice) Noël
Dissertation
Modelling the surface mass balance of the Greenland ice sheet and neighbouring ice caps: a dynamical and statistical downscaling approach
PhD supervisor(s)
prof.dr. M.R. van den Broeke
Co-supervisor(s)
dr. W.J. van de Berg