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

O

M

P

L

E

X

I

T

Y

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