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A distributed glacier model for RASM. Jeremy Fyke , Bill Lipscomb Los Alamos National Laboratory. Goal: Simulate the coupled evolution of Arctic glaciers and ice caps within RASM Evolving land ice area A ffects vegetation extent and albedo Evolving land ice volume
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A distributed glacier model for RASM Jeremy Fyke, Bill Lipscomb Los Alamos National Laboratory
Goal: Simulate the coupled evolution of Arctic glaciers and ice capswithin RASM • Evolving land ice area • Affects vegetation extent and albedo • Evolving land ice volume • Affects global mean sea-level andArctic Ocean freshwater fluxes
Why model glaciers and ice caps? • Mass loss from glaciers and ice caps is raising global mean sea level by ~0.5–1.0 mm/yr(Meier et al. 2007, Jacob et al. 2012) • This is comparable to the sea-level contribution from the Greenland and Antarctic ice sheets • Over centuries of warming, ice sheets will dominate, but over upcoming decadal scales (e.g. RASM simulations), glaciers matter
The problem of scale, non-continuity and dependence on fine-scale topography
Dynamic modeling vs. scaling/statistics • The evolution of the Greenland Ice Sheet (and large ice caps?) is best modeled with a dynamic ice sheet model (e.g., CISM). • Need bed topography, 3D SMB, and numerical techniques • It is not practical to model ~100,000 Arctic ice caps/glaciers in the Arctic with explicit dynamics. • For most glaciers we have no bed/thickness data • Small ice caps and glaciers are best modeled (either singly or as a distribution) with semi-empirical area/volume scaling laws. • No bed topography or thickness data needed • Just need elevation-dependent area (hypsometry) & surface mass balance, b(z), at grid-cell scale
Scaling laws • Semi-empirical scaling laws (Bahr et al., 1997, 1998, 2009…) relate characteristic glacier area to characteristic volume, elevation range, accumulation area ratio (AAR) • Can estimate exponents by physical reasoning (e.g., γ=1.37 for glaciers, 1.25 for ice caps) “not good for one glacier, but good for thousands…” Lyell Glacier, California Devon Ice Cap, Canada Bahr et al., 1997
Scaling-law model requirements • Initial location and hypsometry (area-elevation distribution) for every Arctic glacier • Impossible requirement until early 2012 release of Randolph Glacier Inventory: global-coverage database of 153,429 polygon glacier outlines • RGI + ASTER 30m-resolution imagery = individual glacier hypsometry • Annual-average vertical profile of glacier SMB • Currently prescribed (standalone mode) • Coupling to climate model requires land surface calculations at multiple dynamic elevation levels for each land surface grid cell (implemented for CLM, UVic ESCM, in progress at GISS)
Basics of a distributed glacier model • Data provide glacier area-elevation distribution (hypsometry) and number-size distribution • Climate model provides b(z) for a given grid cell. • DGM computes area-integrated glacier mass balance • b > 0 implies glacier advance, b < 0 implies retreat • Volume change: ΔV = b A Δt • Area change: From area-volume scaling, Vi = c Aiγ • Change in terminus elevation: From area-range scaling, Ri = k Aiη • Change in area-elevation distribution: Assume similar shape of hypsometric profile over time? • Repeat…
Prototype prognostic model • Slight deviation from standard recipe: • Prescribe vertical equilibrium line altitude change (from land surface SMB model) • Generate new AAR • Nudge area/volume towards characteristic equilibrium AAR Net gain (accumulation) Net loss (ablation)
Test-case Iceland: forcing • Model forced with an idealized 200 m rise in ELA (equivalent to 2°C temperature change, with no change in precip) • Smoothed hypsometry extracted for 299 glacier outlines in Iceland inventory • Each glacier run forward for 2000 years (a few serial minutes on a laptop for everything – trivial) • Individual ice mass changes converted to integrated change in volume
Test simulation • NEED: volume evolution (SLR equiv) of Iceland
General coupling of glaciers/ice sheets to RASM will require some model development thinking… • Vertical profiles of annual-average SMB multiple dynamic-elevation-dependent land surface calculations per grid cell • ‘virtual’ (zero-area) or ‘allocatable’ land columns • Vegetation model should follow retreating ice margin… …or yield to dynamically advancing ice margin… …and global conservation of heat/moisture should be maintained during any ice margin migration • How to integrate two land ice modules (‘scaling’ for many small glaciers and ‘dynamic’ for few large ice caps) into RASM?
…and science thinking • What is the contribution of glaciers/ice caps to Arctic Ocean freshwater flux (compared to snow melt)? • How important is glacial topography/albedo to regional/pan-Arctic climate on decadal scales? • How does interannual variability affect Arctic SMB (how does RASM simulate interannual variability)?
Issues with individual-glacier approach • Delineated ‘glacier’ polygons in RGI may be multiple dynamic glaciers • Tidewater glaciers break ‘scaling law’ rules • Glacier inception: scaling model cannot grow new glaciers in currently un-glaciated terrain • May not be an issue in a warming climate • 105 glaciers may become a database/memory issue, especially in a parallel environment… continuous glacier number-size distribution n(a) (analogous to sea ice thickness distribution g(h))