jenny brandefelt kth mechanics - smhi
TRANSCRIPT
Modelling past cold climates
Jenny BrandefeltKTH Mechanics
LANDCLIM workshop in NorrköpingFebruary 23, 2011
Jens-Ove Näslund, Erik Kjellström, Gustav Strandberg, Barbara Wohlfarth, Ben Smith
Outline
To study the Earth's climate
Modelling the Earth's climate
A motivation for studying past climate
Climate model simulations of glacial climate- Last Glacial Maximum (LGM)- Greenland Stadial 3 (GS12)
Equilibration
Comparison to proxy SST
Summary
To study Earth's climateAim
Understand each component of the climate system and how they interact
Improve predictions of future climate change in response to human activities
Tools
Data (from proxy archives and observational records)
Experiments
Laboratory
Modelling (conceptual and numerical)
Past climate variations recorded in natural archives
First example (time series):
Greenland icecore 18O record; a proxy for temperature
Data: NGRIP project members, 2004
~36°C
Past climaterecorded in natural archives
Second example (horizontal patterns): Temperature reconstructed from pollen data for the LGM (Last Glacial Maximum, ~18 ka BP)
Data: Wu et al, 2007
Coldest month of the year temperature anomalies from
the present day climate
Energy balance model
Radiative-convective model
Earth system models of intermediate complexity (EMICs)
Global climate models
Global Earth system models
C
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P
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Numerical models – tools to understand climate
Modelatmospheric circulationocean circulationsea iceupper layers of land surfacefluxes of heat, water vapour and momentum between components
Based on the laws of physics:Newtons mechanicsThermodynamicsConservation of energy and mass
Parameterize small-scale processes, e.g.
cloud formationsmall-scale motions
Neglect/prescribe evolution of ”slow” processes, e.g.
glacier and ice sheet dynamics
vegetation dynamics global bio-geo-chemical
cycles
Global climate / Earth system modelsModel
atmospheric circulationocean circulationsea iceupper layers of land surfacefluxes of heat, water vapour and momentum between components
Based on the laws of physics:Newtons mechanicsThermodynamicsConservation of energy and mass
The equations that describe the dynamics of the atmosphere, oceans, etc are solved numerically
1. Divide the atmosphere, oceans, land surface and sea ice into gridboxes
2. Assign one value of temperature, humidity etc to each gridbox
3. Determine the evolution of the variables based on physical laws
The model
Outline
To study the Earth's climate
Modelling the Earth's climate
A motivation for studying past climate
Climate model simulations of glacial climate- Last Glacial Maximum (LGM)- Greenland Stadial 3 (GS12)
Comparison to proxy SST
Summary
The project
Motivation
The Swedish Nuclear Fuel and Waste Management Co (SKB) are planning for a final repository for nuclear fuel waste.
After 100,000 years the radioactivity of the waste has decreased to enriched uranium levels.
Climate modelling
Identify extreme climate conditions that may occur during the coming 100,000 years. (www.skb.se)
Global and regional modelling
Global climate modelling: Community Climate System Model (CCSM3)
Regional climate modelling:
Rossby Centre Regional Climate
Model (RCA3)Comparison to proxydata
Regional vegetation modelling: LPJ-Guess
Two cold climates
LGM: a cold period with ice sheets covereing Northern Europe
Ca 21 000 years agoHeight (meter)
Two cold climates
LGM: a cold period with ice sheets covering most of Northern Europe
Ca 21 000 years agoHeight (meter)
Permafrost: a cold period with relatively small a relativley small ice sheet over Scandinavia
Ca 44 000 år sedan
A global climate model – forcing and boundary conditions
Forcing: GS12 LGM
Solar insolation Greenhouse gases Ozone pre-industrial concentration Aerosols pre-industrial concentrations
Boundary condtion
Ice sheets Land-sea distribution Sea level -70 m -120 m Topografy & bathymetry Vegetation
En global klimatmodell – drivning och randvillkor
Forcing: Present day GS12 LGM
Solar insolation Greenhouse gases Ozone Aerosols
Boundary condtion
Ice sheets Land-sea distribution Sea level Topografy & bathymetry Vegetation
En global klimatmodell – drivning och randvillkor
CO2
(ppm(v)) 200 185
CH4
(ppb(v)) 420 350
N2O
(ppm(v)) 225 200
Forcing: GS12 LGM
Solar insolation Greenhouse gases Ozone Aerosols
Boundary condtion
Ice sheets Land-sea distribution Sea level Topografy & bathymetry Vegetation
Two cold climatesGS12
LGM
Annual mean temperature (T
2m)
Compared to pre-industrial climate
LGMT
2m and precipitation (relative to recent past)
JJA
DJF
GS12Annual mean precipitation (relative to recent past)
GS12 vs. LGMAnnual mean T
2m and sea ice concentration (50%)
GS12 vs. LGMJanuary-March T
2m and sea ice concentration (50%)
GS12 vs. LGMJuly-September T
2m and sea ice concentration (50%)
Comparison to proxy SSTLGM January-March
Proxy SST: MARGO Project Members, Nature Geoscience, 2009
Proxy SST Simulated SST
Comparison to proxy SSTGS12 January-March
Proxy SST: Kjellström et. al, Boreas, 2010
δ=simulated minus proxy SST
Sea ice edge (50% conc.)
Summary The simulated GS12 climate is in reasonable agreement with
proxy SST and inferred sea ice extent.
The comparison to proxy SST indicates a cold bias in the central North Atlantic, in contrast to the warm bias found in other studies of MIS3 stadial climate (Pollard and Barron, 2003; van Meerbeeck et al, 2009). This difference is associated to a difference in AMOC response to glacial boundary conditions.
The simulated LGM climate is colder than proxy SST, the largest differences are found in the North Atlantic.
Boundary and forcing conditionsLGM GS12
Insolation 1365 W/m² 1365 W/m²Orbital year 21 ka BP 44 ka BPCO2 (ppm
v) 185 200
CH4 (ppbv) 350 420
N2O (ppbv) 200 225
Ozone PI PISulphate PI PIDust, sea salt PI PIIce sheets ICE5G (21ka BP) Näslund,CLIMBER2,ICE5G (14ka BP)
Land–sea dist ICE5G ICE5GSea level -120 m -120 mTopography, bathymetry ICE5G (21kaBP) ICE5G (21kaBP)Vegetation RP RP
PI = pre-industrial RP = recent past (1990AD)
Comparison to proxy SSTLGM annual mean
Proxy SST: MARGO Project Members, Nature Geoscience, 2009
Proxy SST Simulated SST
Comparison to proxy SSTLGM July-September
Proxy SST: MARGO Project Members, Nature Geoscience, 2009
Proxy SST Simulated SST
Comparison to proxy SSTGS12 annual mean
Proxy SST: Kjellström et. al, Boreas, 2010
δ=simulated minus proxy SST
Sea ice edge (50% conc.)
Comparison to proxy SSTGS12 July-September
Proxy SST: Kjellström et. al, Boreas, 2010
δ=simulated minus proxy SST
Sea ice edge (50% conc.)
ENSO teleconnectionsJanuary-March
El Niño minus La Niña anomalies in PSL
Based on Niño3 index
Sida lånad av Erik Kjellström, SMHI