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

Greenland Ice Sheet model simulations and validation

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Greenland Ice Sheet model simulations and validation. Jeremy Fyke, Bill Lipscomb Los Alamos National Laboratory. Outline. Simulated Greenland surface mass balance in CESM Greenland Ice Sheet model optimization within CESM framework Ongoing development. Background. - PowerPoint PPT Presentation

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Page 1: Greenland Ice Sheet model simulations and validation

Greenland Ice Sheet model simulations and validation

Jeremy Fyke, Bill LipscombLos Alamos National Laboratory

Page 2: Greenland Ice Sheet model simulations and validation

Outline

• Simulated Greenland surface mass balance in CESM• Greenland Ice Sheet model optimization within CESM

framework• Ongoing development

Page 3: Greenland Ice Sheet model simulations and validation

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. 2012 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 CLM’s coarse grid– Downscaled and interpolated in z to CISM’s fine grid

Page 4: Greenland Ice Sheet model simulations and validation

Model details• Fully coupled CESM 1.0 with 0.9 ox 1.25o FV atm/land, 1o 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)

Page 5: Greenland Ice Sheet model simulations and validation

CMIP5 simulations with glacier elevation classes, SMB evolutionName Length Initialization

Pre-industrial Years 1-100 100-yr IG run (snowpack) + BG1850CN

20th century 1850-2005 from year 100 of Pre-industrial

21st century (RCP8.5) 2005-2100 from year 2005 of 20th century

• Lower SMB in the 1940s than in the 1990s and 2000s• Negative SMB in several years after 2060

1850 1940 2000 2100Pre-industrial

SMB = 0

400 Gt/yr

SMB = 0

400 Gt/yr

Page 6: Greenland Ice Sheet model simulations and validation

Greenland SMB, downscaled to 5 kmPre-industrial (80-99) 20th-century (1980-1999) RCP8.5 (2080-2099)

SMB (Gt/yr) 452 ± 91 421 ± 107 61 ± 142

kg m-2 yr-1

• 1980-99 ablation rates are higher than pre-industrial in N & NE• The equilibrium line rises by ~500 m by end of 21st 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

Page 7: Greenland Ice Sheet model simulations and validation

SMB, comparison with RACMO (at 5 km res)1958-2007 (plot 1958-2005) RACMO

SMB (Gt/yr) 409±106 469±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

Page 8: Greenland Ice Sheet model simulations and validation

Temperature and SMB: 1850-2005JJA mean temperature over ice sheet

Precip

Melt

Runoff SMB

• 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

-5o

-10o1850 20051850 2005

Page 9: Greenland Ice Sheet model simulations and validation

Temperature anomalies: 2080-99 minus 1980-99annual 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

Page 10: Greenland Ice Sheet model simulations and validation

SMB (Gt/yr): 1980-2100

• Precipitation increases with time• Melt and runoff increase by a larger amount• SMB is negative for the first time around 2030

1980 2100

Blue = PrecipRed = MeltingGreen = RunoffBlack = net SMB

SMB = 0

Page 11: Greenland Ice Sheet model simulations and validation

Summary: Greenland SMB• The SMB scheme works well. Greenland’s simulated 20th

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 21st century simulation, the SMB decreases from ~400 Gt/yr to near zero.

• Greenland average warming in the 21st 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).

Page 12: Greenland Ice Sheet model simulations and validation

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?

Page 13: Greenland Ice Sheet model simulations and validation

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

Page 14: Greenland Ice Sheet model simulations and validation

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

Page 15: Greenland Ice Sheet model simulations and validation

Optimization approach

9000 years today

SeaRise

simulations

future

Page 16: Greenland Ice Sheet model simulations and validation

Optimization results: volume evolution

Page 17: Greenland Ice Sheet model simulations and validation

Optimization results: example GIS model-observed elevation differences

Page 18: Greenland Ice Sheet model simulations and validation

Optimization results: rankings for all diagnostics

Page 19: Greenland Ice Sheet model simulations and validation

Optimization results: dependence of diagnostics on LHS parameters

Page 20: Greenland Ice Sheet model simulations and validation

Optimization results: top-performing ice sheet model realizations

Page 21: Greenland Ice Sheet model simulations and validation

Ice sheet spinup issues

• Spinup/optimization issues to work on:– Thermal timescale of ice sheet (thus, ice viscosity)

is 105 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

Page 22: Greenland Ice Sheet model simulations and validation

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

Page 23: Greenland Ice Sheet model simulations and validation

Ongoing development

• New ice-sheet dynamical cores1. 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).

Page 24: Greenland Ice Sheet model simulations and validation

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)

Page 25: Greenland Ice Sheet model simulations and validation

Extra slides

Page 26: Greenland Ice Sheet model simulations and validation

SMB trend 1958-2005 (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

Page 27: Greenland Ice Sheet model simulations and validation

Terms of SMBUnits: Gt per year RACMO 1958-2007 CLM 1980-1999 Diff CLM-RACMO

SMB (net) 469 403 ± 106 -66

MB (snow) -5

SNOW 697 742 ± 82 +45

RAIN 46 135 ± 23 +89

PRECIP 743 877 ± 98 +134

RUNOFF 248 425 +177

SUBLIMATION 26 54 ± 3 +28

Units: Gt per year RACMO 1958-2007 1980-1999

MELT (only snow) 430 ± 67

MELT (snow + ice) 404 530 ± 109 +126

MELT+RAIN 450 665 ± 117 +215

REFREEZING 202 (45% of ME+RAIN)

240 ± 27 (36% of ME+RAIN)

+38

Page 28: Greenland Ice Sheet model simulations and validation

Terms of SMB: 1980-1999

• 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.)

SMB Melt Runoff Rain

Page 29: Greenland Ice Sheet model simulations and validation

21st century temperature increase (ref: 1980-1990)

region Annual (st. dev.) Summer (st. dev.)

Global 3.6 (0.3)

Greenland ice sheet 3.8 (0.6) 3.5 (0.8)

Greenland region 3.5 (0.5)

Temperature anomalies for 2080-2099

global

Greenland ice sheet

JJA

annual

Greenland + ocean

Page 30: Greenland Ice Sheet model simulations and validation

Terms of SMB: RCP8.5Units: Gt per year 1980-1999 2080-2099

SMB-net 403 ± 106 12 ± 148

MB (snow) -5 -1

SNOW 742 ± 82 807 ± 74

RAIN 135 ± 23 279 ± 45

PRECIP 877 ± 98 1086 ± 105

RUNOFF 425 1018 ± 167

SUBLIMATION 54 ± 3 57 ± 5

Units: Gt per year 1980-1999 2080-2099

MELT (only snow) 430 ± 67 624 ± 65

MELT (snow + ice) 530 ± 109 1040 ± 160

MELT+RAIN 665 ± 118 1320 ± 187

REFREEZING 240 ± 27 (36% of ME+RAIN)

301 ± 27 (23% of ME+RAIN)

Page 31: Greenland Ice Sheet model simulations and validation

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, 1980-1999Solid red line = Ice melt, 2080-2099

Dotted black line = Snow melt, 1980-1999Dotted red line =Snow melt, 2080-2099