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Greenland Ice Sheet model simulations and validation Jeremy Fyke, Bill Lipscomb Los Alamos National Laboratory.

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Presentation on theme: "Greenland Ice Sheet model simulations and validation Jeremy Fyke, Bill Lipscomb Los Alamos National Laboratory."— Presentation transcript:

1 Greenland Ice Sheet model simulations and validation Jeremy Fyke, Bill Lipscomb Los Alamos National Laboratory

2 Outline Simulated Greenland surface mass balance in CESM Greenland Ice Sheet model optimization within CESM framework Ongoing development

3 Background The Glimmer Community Ice Sheet Model (Glimmer- CISM) has been coupled to version 1.0 of the Community Earth System Model (CESM 1.0). – Shallow-ice approximation; Greenland only – Higher-order ice sheet model (CISM 2.0) to be included in CESM 1.1 (aiming for Nov release) The surface mass balance (SMB) of ice sheets is computed in the Community Land Model (CLM) and passed to Glimmer-CISM. – Multiple (~10) glacier elevation classes on CLMs coarse grid – Downscaled and interpolated in z to CISMs fine grid

4 Model details Fully coupled CESM 1.0 with 0.9 o x 1.25 o FV atm/land, 1 o ocean Focusing on the surface mass balance (accumulation minus ablation) of the Greenland ice sheet – SMB(ice+snow) = incoming snow + incoming rain – runoff – sublimation – Positive ice SMB when snow exceeds max depth (1 m water equivalent) and turns to ice – Negative ice SMB when snow depth is zero and bare ice melts – The SMB of ice (not snow) is passed to the ice sheet model Snow and ice physics: – Liquid water can percolate and refreeze in the snow, but not on bare ice – Snow albedo follows SNICAR model (depends on snow grain size, solar angle, etc.) – Bare ice albedo is prescribed (0.60 visible, 0.40 near IR)

5 CMIP5 simulations with glacier elevation classes, SMB evolution NameLengthInitialization Pre-industrialYears yr IG run (snowpack) + BG1850CN 20 th century from year 100 of Pre-industrial 21 st century (RCP8.5) from year 2005 of 20 th century Lower SMB in the 1940s than in the 1990s and 2000s Negative SMB in several years after Pre-industrial SMB = Gt/yr SMB = Gt/ yr

6 Greenland SMB, downscaled to 5 km Pre-industrial (80-99)20th-century ( )RCP8.5 ( ) SMB (Gt/yr) 452 ± ± ± 142 kg m -2 yr ablation rates are higher than pre-industrial in N & NE The equilibrium line rises by ~500 m by end of 21 st century It reaches almost 2000 m in the NE and southern half of E margin High snowfall rates help to keep equilibrium line low in NW and mid-W margins Red = net accumulation Blue = net melting

7 SMB, comparison with RACMO (at 5 km res) (plot )RACMO SMB (Gt/yr)409±106469±41 Good match in ablation zones Accumulation rates are overestimated in the interior and underestimated in the SE (smoother orography in CESM) Snowfall local maxima along W coast and impact on melt (via albedo) are well captured

8 Temperature and SMB: JJA mean temperature over ice sheet Precip Melt RunoffSMB Warm period during 1930s and 1940s, with high melt Precipitation rates are higher in the 1990s High SMB following Pinatubo (Pi) eruption in 1991 Pi -5 o -10 o

9 Temperature anomalies: minus annual JJA MOC reduction reduces warming SE of Greenland JJA increase is highest In ice-free regions to N & E, in part due to stronger sea ice losses (>40%) along the coast In the interior of the ice sheet, which remains below melting point

10 SMB (Gt/yr): Precipitation increases with time Melt and runoff increase by a larger amount SMB is negative for the first time around Blue = Precip Red = Melting Green = Runoff Black = net SMB SMB = 0

11 Summary: Greenland SMB The SMB scheme works well. Greenlands simulated 20 th century surface mass balance and trends are in good agreement with RACMO, a state-of-the-art regional model (with differences due to smoother CESM topography). During the 21 st century simulation, the SMB decreases from ~400 Gt/yr to near zero. Greenland average warming in the 21 st century is roughly equal to global average warming. There is more warming in the North and East (less summer sea ice) than in the Southeast (reduced MOC).

12 Ice sheets in RASM Coupling to CISM is included in the current version of the CESM coupler; should not be hard to include in RASM. The coupler requires the ice-sheet surface mass balance in multiple elevation classes from the land model. Next step is to implement a similar scheme in VIC. How much code can be reused from CLM?

13 Greenland Ice Sheet (GIS) optimization Will be necessary for GIS in RASM Carried out in support of SeaRise: model intercomparison project to assess range of modelled ice sheet responses to idealized climate perturbations (Δclimate, Δdynamics) Initial state of ice sheet should reflect observed ice sheet: exercise in rapid (1 month turnaround) model optimization Tool: Latin Hypercube Sampling of uncertain parameter space

14 Optimization approach Generate 100 GIS realizations with LHS-determined random combinations of: – Ice sheet enhancement factors – Basal sliding coefficients – Geothermal heat fluxes Compare equilibrium state (after 9 kyr simulation) to observed GIS state for: – Ice volume error – Ice area error – RMSE of ice surface elevation – Maximum ice elevation error – Summit horizontal offset error Rank models by worst diagnostic ranking to get best all- around GIS realization

15 Optimization approach 9000 years today SeaRise simulations future

16 Optimization results: volume evolution

17 Optimization results: example GIS model-observed elevation differences

18 Optimization results: rankings for all diagnostics

19 Optimization results: dependence of diagnostics on LHS parameters

20 Optimization results: top-performing ice sheet model realizations

21 Ice sheet spinup issues Spinup/optimization issues to work on: – Thermal timescale of ice sheet (thus, ice viscosity) is 10 5 years – analogous to spinning up the deep ocean (but worse!) – How to spin up a GIS model, using forcing that is continuous between past and future, that captures transient thermal and geometric state of ice sheet? – LHS ensemble limited to sampling internal ice sheet parameters

22 Conclusions LHS sampling provides a fast way to determine optimal initial state for GIS models within a climate model framework Flow factor exerts major control on ice sheet optimization in CISM Similar optimization technique will be necessary to optimize the GIS under RASM forcing RASM surface mass balance field (reflected in long-term GIS spinup geometry) will be sensitive indicator of regional atmospheric model biases

23 Ongoing development New ice-sheet dynamical cores 1.Payne-Price: 3D higher-order, finite difference, structured grid, Trilinos solvers 2.BISICLES: Vertically integrated higher-order, finite volume, Chombo adaptive mesh refinement software 3.FELIX: Full-Stokes/higher-order, finite element, unstructured variable-resolution mesh (MPAS framework), Trilinos solvers BISICLES and FELIX will be further developed under a new 5-year DOE SciDAC project, Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES).

24 Ongoing development Improved physics parameterizations –Subglacial hydrology and basal sliding (S. Price, M. Hoffman) –Calving (based on Potsdam-PIK) Two-way coupling with land model –Requires dynamic landunits (glaciers vegetation) –May not be important on decadal time scales Coupling with ocean model –POP2X simulates ocean circulation beneath ice shelves (X. Asay-Davis); will be applied to Antarctica –May not be practical for RASM in near term; Greenland fjords require very high resolution (~1 km)

25 Extra slides

26 SMB trend (kg m -2 yr -2 ) Negative trend in ablation zones Positive trend in the Southeast, due to increasing precipitation Consistent with RACMO results and altimetry measurements

27 Terms of SMB Units: Gt per yearRACMO CLM Diff CLM-RACMO SMB (net) ± MB (snow)-5 SNOW ± RAIN46135 ± PRECIP ± RUNOFF SUBLIMATION2654 ± 3+28 Units: Gt per yearRACMO MELT (only snow)430 ± 67 MELT (snow + ice) ± MELT+RAIN ± REFREEZING202 (45% of ME+RAIN) 240 ± 27 (36% of ME+RAIN) +38

28 Terms of SMB: Runoff = Melt + Rain - Refreezing > 0 in the interior of the ice sheet, where all available liquid water should refreeze In CLM, rain is overestimated in ice sheet interior (and rain cannot refreeze if snow thickness = 1 m w.e.) SMBMeltRunoffRain

29 21 st century temperature increase (ref: ) regionAnnual (st. dev.)Summer (st. dev.) Global3.6 (0.3) Greenland ice sheet3.8 (0.6)3.5 (0.8) Greenland region3.5 (0.5) Temperature anomalies for global Greenland ice sheet JJA annual Greenland + ocean

30 Terms of SMB: RCP8.5 Units: Gt per year SMB-net403 ± ± 148 MB (snow)-5 SNOW742 ± ± 74 RAIN135 ± ± 45 PRECIP877 ± ± 105 RUNOFF ± 167 SUBLIMATION54 ± 357 ± 5 Units: Gt per year MELT (only snow)430 ± ± 65 MELT (snow + ice)530 ± ± 160 MELT+RAIN665 ± ± 187 REFREEZING240 ± 27 (36% of ME+RAIN) 301 ± 27 (23% of ME+RAIN)

31 Seasonal cycle of melt J F M A M J J A S O N D Length of snow melt season does not change (melt season begins in April) Ice begins to melt ~15 days earlier and melts for ~15 days more in late September Solid black line = Ice melt, Solid red line = Ice melt, Dotted black line = Snow melt, Dotted red line = Snow melt,

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