1) Recent advances allow global climate models to realistically simulate surface mass balance of ice sheets, through explicit representation of snow processes, sub-grid elevation effects, and coupling with ice sheet models. 2) When forced by a high emissions scenario, the model projects a doubling of surface melt and a negative surface mass balance over Greenland by 2100, contributing 0.55 meters to sea level rise. 3) This is due to a 4-5°C warming over Greenland, increased cloudiness reducing sunlight while enhancing downwelling longwave radiation, and a 500m average rise in the equilibrium line altitude.

1. Recent breakthrough in including
ice sheets in climate models
and the challenges ahead
Miren Vizcaino
Dep. Geoscience and Remote Sensing,
Delft University of Technology
"Icebergs from Jakobshavn Isbrae”, courtesy of Mark Drinkwater, ESA
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2. Greenland and Antarctic ice
Mean since 1992
sheets are losing mass 0.59 ± 0.20 mm yr
• In response to both
atmospheric and ocean
forcing
• Several surface melt extremes
over GrIS in the last two
decades
• Ocean melt reduces buttressing
360 Gt= 1 mm
of AIS & GIS grounded ice
A Shepherd et al. Science 2012;338:1183-1189
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−1

3. Ice sheets also modify climate
(interactive) locally & globally
Through changes in
• Snow albedo: couples atmosphere and SMB, specially during melt
season
• Topography:
• Elevation effect (thermodynamical): temperature decreases with elevation
• Local climate: katabatic winds, clouds, orographic forcing of precipitation
• Atmospheric circulation: storm-tracks, mean circulation
• Freshwater fluxes:
• Meridional Overturning Circulation
• Sea-ice formation (Bintanja et al. 2013)
• Ocean circulation in fjords and under ice shelves (meltwater feedback)
• Land cover (ice sheet area retreat/advance): affects albedo,
roughness, turbulent fluxes
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4. Modeling climate
ice interaction
Total mass budget= Surface Mass Balance – ice discharge to ocean
Precipitation
Temperature, radiation, wind,
moisture
Global
climate
Meltwater
Ocean melt
SMB
Snow albedo
Topography &
Area
Ice Flow
Model
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5. State of the art
• Very few AOGCMs have been coupled to ice sheet models
(Ridley et al. 2005, Vizcaino et al. 2008,2010)
• Why should we include them?
• Integration of several components of climate system and their
interaction (e.g. ice-ocean, ice-clouds, ice-storm track, land icesea ice)
• Representing feedbacks (e.g. albedo, elevation)
• Integration of different time-scales:
• Relating past, present and future processes in the climate system
• This helps to model validation (for instance, with “black swans”
from paleo and recent observations to identify missing or
misrepresented processes)
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6. Challenges in coupling ice sheet
and global climate models
• Resolution
• Spatial: AOGCMs have resolution of ~100 km. Ice sheet models need higher
resolution (few kms and below) to resolve:
• Fast ice flow
• Atmospheric and ocean forcing: ocean melt in fjords, ocean circulation under ice
shelves, orographic forcing of precipitation, melt gradients at ice sheet margins,…
• Temporal: long time scales involved in ice sheet build-up and complete decay
• Ice sheet initialization: obtaining a realistic present-day ice sheet
• well adjusted to the simulated climate (to avoid non-physical background trend)
• with memory of past climate (ice column temperature, viscosity, basal
conditions)
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7. The SMB challenge
• High Surface Mass Balance gradients at
ice sheet margins (steep topography)
kg m-2 yr-1
Until very recently:
• Climate models considered unsuitable:
coarse resolution (~tens of km needed),
climate biases
• Regional climate models preferred.
But:
• Lateral forcing from GCMs needed
• No direct global climate-ice coupling
(e.g. no meltwater-ocean feedbacks)
• Un-suited for multi-century studies
(e.g. no elevation feedback)
Surface mass balance (precip-su-melt) as
modeled by RACMO2
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8. Ice
climate in RCMs vs. GCMs
Global climate
models
RCMs) Global
climate
Regional
climate models
Lateral
Forcing
Ice sheet flow &
surface models
Regional
climate
Ice sheet
processes
Snow
albedo
feedback
Global
GCMs) climate
Ice sheet
processes
albedo, elevation, meltwater
feedbacks
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9. Recent break-through:
first realistic SMB from global climate
model
• Model is the Community Earth System Model (CESM)
• Results on model validation and 21st-century
projections of GrIS SMB published in J. Climate
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10. CESM compares well (r=0.80) with in-situ
observations from N=475 stations
1960-2005 SMB from CESM downscaled at 5 km & from
N=475 stations (kg m-2 yr-1)
•
•
•
Accumulation rates overestimated in
N interior
Good match in the southern part,
except in the wet SE
67 °N, west margin (“k-transect”)
• Modeled equilibrium line
altitude (~1500 m) is close to
observations
• Small differences over 1000 m
• Gradient is underestimated:
• Local terrain not resolved
(narrow fjord framed by tundra)
•
Local anomaly in bare
ice albedo (“dark zone”)
Vizcaino et al., 2013, J. Clim.
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11. CESM compares well with RCMs
SMB>0
1960-2005 SMB (kg m-2 yr-1)
(standard deviation in
parenthesis)
SMB = PREC-RU-SU
RU=MELT+RAIN-REF
CESM
RACMO2
Other RCMs
Net SMB
359 (120)
376 (117)
288/356/287
PREC
866 (88)
723 (74)
600/696/610
MELT
568 (112)
504 (111)
Refreezing
242 (25)
245 (38)
RUN-OFF
457(95)
306 (86)
SU
54
40
Gt yr-1
CESM, 5 km
CESM
5 km
r= 0.79
SMB<0
RACMO2, 5 km
RACMO2
~11 km
•
•
•
•
•
(MAR/PMM5/ERA40-d)
5/108/38
Bands of precip. maxima are well reproduced
Higher precip. in the interior & lower in SE
Major ablation zones well captured
Narrow SE ablation areas in both models
Refreezing: 35% of available liquid water
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12. Intra-annual mass evolution compares well
with gravimetry data (GRACE)
55
7
6
CESM seasonal cycle of snowmelt, bare ice melt,
refreezing, snowfall, rain, and sublimation (Gt).
Snow Melt
mass (Gt)
5
4
Snowfall
3
RE
2
Ice Melt
1
SU
Rainfall
0
0
90
180
day
cum. mass anomaly (Gt)
300
200
270
360
GRACE
100
0
-100
• Similar maximum, minimum & amplitude,
regardless of influence of climate variability &
“different” periods (GRACE data starts later, in 2003 vs.
CESM
-200
-300
Mean (thick lines) and range (thin lines) of de-trended
monthly cumulative mass anomalies (Gt) for CESM
(1996-2004, blue) and GRACE (2003-2011, black).
1996 of CESM)
995
6 7 8
month
996
FIG. 9. Upper) CESM seasonal cycle of snow melt, bare ice melt, refreezing, snowfall,
997
rain and sublimation. Units are Gt. Lower) Comparison of the seasonal cycle of mass
998
anomalies between CESM (blue) and GRACE (black). Units are Gt. Thick lines represent
1
2
3
4
5
9 10 11 12
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13. The recipe for a good SMB
1. Realistic atmospheric forcing (radiation, wind, humidity)
2. Explicit simulation of snow processes: albedo, compaction,
refreezing.
•
•
SMB in CESM is calculated in land component (giving “immediate”
ice-atmospheric coupling)
Albedo depends on snow grain size, solar zenit angle, spectral
band, snow impurities (SNICAR model)
3. Sub-grid representation of elevation dependency of SMB
① Atmospheric forcing (temperature, humidity) is downscaled to ice
sheet grid
② SMB is re-calculated at several fixed elevations
③ SMB maps are interpolated to ice sheet grid (horizontally &
vertically)
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14. 57
Explicit albedo simulation
At melt season
peak (July)
Before melt
season (April)
a
b
c
0.9
0.825
0.8
0.7
0.6
0.5
0.2
1960-2005
mean
albedos
1008
1009
CESM
(global model)
RACMO2
(regional model)
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FIG. 11. Map of mean April (a) and July (b) albedos for 1960-2005 as simulated by

15. GrIS SMB Projections up to 2100
with CESM
Following high-forcing scenario RCP8.5
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16. Temperature change under RCP8.5
Annual, 2080-99 minus 1980-99 (K)
Summer, 2080-99 minus 1980-99 (K)
b!
Greenland:
+4.1 K
Global: +3.7 K
60-90°N: +7.9 K
Greenland: +4.7 K
• MOC reduction reduces warming SE of Greenland
• JJA increase is highest
• In ice-free regions to N & E, due to stronger sea ice
losses (>40%) along the coast
• In the interior of the ice sheet, which remains below
melting point
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17. Change in surface fluxes (RCP8.5)
Wm-2
2080-99 minus 1980-99
(Only significant anomalies)
albedo
•
•
•
•
•
SWd!
LWd!
More incoming LW
Less incoming SW due to
increased cloudiness
Albedo decreases
Net radiation increases
Turbulent flux increases
albedo!
Vizcaino et al., 2013, J. Clim., Part II
Rnet!
SHF!
LHF!
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18. Change in integrated SMB terms
(Gt yr-1)
SMB = PREC-RUNOFF-SUBLIMATION
RUNOFF=MELT+RAIN-Refreezing
(standard deviation in parenthesis)
% indicates increase 2080-99 wrt 1980-99
Melt
1500
1980-99
SMB
Gt per year
-78 (143)
PRECIPITATION
855 (70)
1158 (74)
+35%
Snowfall
728 (59)
857 (47)
+18%
SURFACE MELT
Snowfall
500
Rain
0
SMB
•
•
•
•
•
372 (100)
552 (119)
1186 (155)
+215%
Refreezing
240 (25)
318 (25)
+33%
RUN-OFF
438 (98)
1168 (168)
+266%
SUBLIMATION
54 (3)
60 (4)
+11%
Run-off
1000
-500
1980
2080-99
2000
2020
2040
year
2060
2080
SMB becomes negative
Snowfall increases by 18%
Melt doubles
Refreezing capacity decreases
5.5 cm SLE by 2100
2100
Vizcaino et al., 2013, J. Clim., Part II
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19. New equilibrium line ~500 m higher
SMB>0
1980-99!
kg m-2 yr-1
2080-99!
SMB<0
•
•
•
•
Ablation area increases from 9% to 28% of ice sheet
Max. increase of eq. line in NE (~1000 m higher)
SMB increases over 2000 m
Map is similar to projections from regional models
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20. Summary
• Ice sheets are not yet interactive components of most
global climate models
• Major challenges come from differences in spatial & temporal
resolutions
• Until recently, global climate models considered unsuited to
reproduce high SMB gradients, due to climate biases and
insufficient resolution
• Now the first global climate model is able to simulate
realistic SMB, due to realistic atmospheric simulation
coupled with explicit representation of snow processes, and
sub-grid representation of vertical gradients
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