School of Earth and EnvironmentINSTITUTE FOR CLIMATE & ATMOSPHERIC SCIENCE

Is the Arctic the most uncertain aerosol environment in the world?

Ken Carslaw, Jo Browse, Lindsay Lee, Graham Mann Kirsty Pringle, Carly Reddington, Graham Mann,

Dom Spracklen, Alex Rap, Piers Forster, Ben DrummondUniversity of Leeds, UK

Jeff PierceColorado State University

Funding: NERC AEROS, GASSP and ACCACIA projects,

EU PEGASOS, the National Centre for Atmospheric Science

Model predictions of Arctic aerosol

Black

Carbon

SulfateCO

Shindell et al., 2008

Annual mean sulfate

Mean concentration and diversity of the “central two-thirds” of 12 AEROCOM microphysics model

AEROCOM microphysics intercomparison: Sulfate diversity

SO4 concentration

SO4 diversitySO4 diversity

1

10

30

1

10

30

Mann et al., ACPD, 2013

AEROCOM microphysics intercomparison: BC diversity

Annual mean BC

Mean concentration and diversity of the “central two-thirds” of 12 AEROCOM microphysics model

Mann et al., ACPD, 2013

BC concentration

BC diversityBC diversity

1

10

30

1

10

30

AEROCOM microphysics intercomparison: Particle concentration diversity

Mann et al., ACPD, 2013

N30 concentration N100 concentration

N30 diversity N100 diversity

1

10

30

1

10

30

Two “aerosol seasons” with very different processes

Svalbard observations show a transition from “Arctic haze” in winter to very clean summer

Korhonen et al., ACP, 2008

Browse et al., ACP, 2012

December-April June-August

Garrett et al (2010): “In the Arctic, the freezing point appears to serve as a ‘scavenging point’ that is only passed in the mid-summer months

A meteorological “scavenging point” temperature

6

8

2

1

6

8

2

1

Observed ratio of winter/summer BC

Winter Spring

Fraction of precip as snow

Browse et al., ACP, 2012

“Fixing” the inverse seasonal cycle problem

Switching off scavenging at -15C, adding summer drizzle

Browse et al., ACP, 2012

More comprehensive sampling of the model uncertainty

Model response surface in one grid box

Model runs

Essentially using the interpolated parameter space to enable a very

dense Monte Carlo sampling of the modelParameter 1

Parameter 2

Ou

tpu

t (e.

g.,

CC

N)

Extend to 28 dimensions with 168 runs

Lee, L.A. et al., Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters, ACP 2011.

Lee, L.A. et al., The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei, ACP 2013.

28 simultaneously perturbed parameters (1/2)

Parameter Lower UpperBCOC mass emission rate (fossil fuel) 0.5 2.0

BCOC mass emission rate (biomass burning) 0.25 4.0

BCOC mass emission rate (biofuel) 0.25 4.0

Sea spray mass flux (coarse/acc) 0.2x 5.0x

SO2 emission flux (anthropogenic) 0.6x 1.5x

SO2 emission flux (volcanic) 0.5x 2.0x

Biogenic monoterpene production of SOA 5 Tg/a 360Tg/a

Anthropogenic VOC production of SOA 2Tg/a 112Tg/a

DMS mass flux 0.5x 3.0x

BCOC mode diameter (fossil fuel) 30 nm 80 nm

BCOC mode diameter (biomass burning) 50 nm 200 nm

BCOC mode diameter (biofuel) 50 nm 200 nm

Subgrid conversion of SO2 to SO4 ("primary SO4“) 0% 1%

Mode diameter of "primary SO4" 20 nm 100 nm

Particle and precursor gas emission rates

Properties of emitted particles

A probability distribution for each parameter was also elicited

Parameter Lower UpperBL nucleation rate k[H2SO4] 4E-7 2E-04

FT nucleation rate (BHN) x0.01 X10

Ageing "rate" from insol to sol (monolayer) 0.3 5

Modal width (accumulation) 1.2 1.8

Modal width (Aitken) 1.2 1.8

Mode separation diameter (nucleation/Aitken) 9 nm 20 nm

Mode separation diameter (Aitken/accumulation) x1.5 x3

Microphysical rates

Model “structural choices”

Cloud drop activation dry diameter 30 100

Reaction SO2 + O3 in cloud water (clean) pH=4 pH=6.5

Reaction SO2 + O3 in cloud water (polluted) pH=3.5 pH=5

Nucleation scavenging dry D (above activation) 0 nm 100 nm

Nucleation scavenging fraction (T> -15C) 0.2 0.99

Dry deposition velocity (Aitken) x0.5 X2.0

Dry deposition velocity (accumulation) X0.1 X10.0

Cloud processing

Dry and wet deposition

28 simultaneously perturbed parameters (2/2)

Current projects extending to host model physics parameters

PDFs of mean CCN concentration in every grid box (July)

Parametric uncertainty in BC and sulfate in one model

Standard deviation divided by the mean (December)

Uncertainty due to 28 parameters

Crude comparison with multi-model ensemble:

Parametric +s/-s ~ 4 compared to +MME/-MME ~ 20

Arctic dominated by model structural uncertainty?

BC uncertainty SO4 uncertainty

0.1

1

2

0.5

0.1

1

2

0.5

BC fraction of variance (January)

BC fraction of variance (July)

CCN fraction of variance (July)

BL nuc

Dry dep

Aitken width

BB ems

BB diam

1750-2000 indirect forcing fraction of variance (July)

BB diam

DMS ems

SO2 ems

CCN and indirect forcing uncertainties are not caused by the same factors

See Carslaw et al., Nature, 2013

Response of marine emissions to loss of sea ice

Present day DMS DMS (no ice)

Sea spray (no ice)Sea spray

Browse et al., The complex response of Arctic cloud condensation nuclei to retreat of sea ice, ACPD 2013.

Response of Arctic aerosol to loss of sea ice

Change in CCN Change in N3

Browse et al., The complex response of Arctic cloud condensation nuclei to retreat of sea ice, ACPD 2013.

In a scavenging dominated environment, the response of CCN to changes in emissions can be complex!

Minimal impact of future Arctic shipping

Future Arctic shipping could contribute locally 10% to BC deposition on snow and ice

There are likely to be much larger changes due to meteorology

Browse et al., Impact of future Arctic shipping on high-latitude black carbon deposition, GRL 2013.

Conclusions

• The AEROCOM global aerosol microphysics multi-model ensemble shows huge diversity in Arctic BC, SO4 and CCN (factor 30 between central 2/3 of models versus <factor 4 elsewhere)

• The parametric uncertainty of aerosol in a single model (GLOMAP) peaks in the Arctic (factor 4 versus <factor 2 elsewhere)

• Structural uncertainty dominates? (although correction of some gross model errors would reduce this substantially)

• The factors controlling the uncertainty in Arctic CCN are different to the factors that control indirect forcing

• Retreat of Arctic ice seems to cause a complex response in CCN

• Changes in Arctic shipping not a major factor for future BC

• The answer is YES: the Arctic is the most uncertain aerosol environment on Earth

Confronting the model with observations

See gassp.org.uk