Simulating cold palaeo-climate conditions in - Mistra

Simulating cold palaeo-climate
conditions in Europe with a
regional climate model
Gustav Strandberg Rossby Centre, SMHI
Erik Kjellström
Jenny Brandefelt
Ben Smith
Barbara Wohlfarth
Jens-Ove Näslund
Rossby Centre, SMHI & Dept. of Meteorology, University of Stockholm
Dept. of mechanics, KTH
Dept. of Physical Geography and Ecosystems analysis, University of Lund
Dept. of Geology and Geochemistry, University of Stockholm
Swedish Nuclear Fuel and Waste Management Company
Two cases
Last Glacial Maximum (LGM)
21 ka BP
Marine Isotope Stage 3 (MIS 3)
44 ka BP
Insolation
1365 Wm-2
1365 Wm-2
Orbital year
CO2
21 ka BP
185 ppmv
44 ka BP
200 ppmv
CH4
350 ppbv
420 ppbv
N2O
Ozone
Sulphate
Dust, sea salt
200 ppbv
PI
PI
PI / PI x 3
225 ppbv
PI
PI
PI
Ice sheets
ICE-5G
Näslund, CLIMBER2, ICE-5G
Land-sea distr.
Sea level
Topogr., bathym.
ICE-5G
-120 m
ICE-5G, RP
ICE-5G [Whitehouse], RP
-120 m [-70 m]
ICE-5G [Whitehouse]
Vegetation
RP / LGM
RP
LGM
MIS 3
Modelling approach
Climate
GCM: CCSM3 T42
Forcing
RCM: RCA3 50km
More than 2500 years simulated by the
global model
Annual global mean surface temperature
50 year periods downscaled by the regional model
(Brandefelt & Otto-Bliesner, submitted to GRL)
Results from the global model
Annual near-surface temperature compared to PI conditions
°
90 N
°
°
°
135 W 90 W 45 W
°
0
°
45 E
°
°
0
−2.5
−5
−7.5
−10
−12.5
−15
−17.5
−20
−22.5
−25
−27.5
−30
−32.5
−35
90 E 135 E
45° N
0°
°
45 S
90° S
°
°
90 N
°
°
135 W 90 W 45 W
°
0
°
45 E
°
°
90 E 135 E
°
45 N
°
0
°
45 S
90° S
MIS 3 (44 ka BP)
LGM (21 ka BP)
Case
∆Tagm AMOC (Sv)
Pre-Indus
-1.3
21
Recent Past
0
19.4
LGM
-7.5
10
MIS 3
-5.6
10.5
35
30
25
20
15
10
5
0
−5
−10
−15
−20
−25
−30
−35
Results from the global model
LGM
MIS 3
Results from the global model - LGM
CCSM3
Summer
Winter
MARGO
DJF temp. GCM vs. RCM - Sweden
LGM
MIS 3
DJF temp. GCM vs. RCM –
Iberian Peninsula
LGM
MIS 3
Temperature in LGM
Warmest month
Coldest month
Annual mean
Results from the RCM - comparison with proxies
LGM (21 ka BP)
Annual mean
Coldest month
Precipitation in LGM
Warmest month
Coldest month
Annual mean
Anomalies to RP mm/month
Difference in variability
Precip. coldest month
Temp. coldest month
Vegetation in LGM
• Tundra-like and montane woodland in C and S Europe
• Boreal needle leaved trees dominates in forested areas
in continental eastern Europe
Changed vegetation leads to
differences in temperature.
Largest differences in spring
March
Sensitivity LGM (3xdust) compared
to original LGM - temperature
Warmest month
Coldest month
Effect of complete removal of the ice sheet
Coldest month
Warmest month
Conclusions LGM
• Comparison with SST proxies show
that the simulation possibly is too cold
over the North Atlantic
• Relatively good agreement with proxy
data over Europe
• Adding dust and vegetation enhances
the climate signal.
MIS 3 – simulated and proxy based SST
Summer
Winter
Temperature in MIS 3
Warmest month
Coldest month
Annual mean
Precipitation in MIS 3
Warmest month
Coldest month
Anomalies to RP mm/month
Annual mean
Vegetation in MIS 3
• Herbaceous vegetation reaching into Sweden
• Broadleaved and needleleaved trees co-dominate in
forested areas in continental eastern Europe
MIS 3 vegetation changes initial
RCM temperature climate
Warmest month
Coldest month
Conclusions MIS3
• First long simulation with a fully coupled AOGCM
• Simulated climate is favourable for large areas with permafrost
in Scandinavia, and supports a small ice sheet in Scandinavia
Conclusions
• The resulting climate is in a qualitative agreement with the imposed
extent of ice sheets and types of vegetation for the respective climate
case
• The results are in broad agreement with available proxy data and
other climate model simulations
• Given the decadal variability for the North Atlantic and European
sector in 1000 years of the CCSM3 simulation, a 50-year period is a
good representative for the whole 1000-year simulation.
• The results of the iterative simulations with the RCM and DVM show
that this is a viable approach, as the resulting vegetation is close to the
vegetation reconstructed from existing palaeodata
LGM
MIS 3
LGM
MIS 3