Integrating multicomponent aerosol and cloud responses into climate models S' Ghosh Acknowledgements

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Integrating multi-component aerosol and cloud
responses into climate modelsS. Ghosh
AcknowledgementsProf. M.H. SmithProf. J.C.R.
HuntHadley CentreClimate Change and Urban Areas
US-UK dialogue UCL London 3 April 2006
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Stratocumulus Clouds
Direct Effect
Aerosol particles
Indirect Effect Cloud processing
(photo courtesy UKMO)
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Aerosol particles as CCN Complexities and
Challenges

• Atmospheric aerosol particles hydrophobic,
  water-insoluble but possess hydrophilic sites
• Some water-soluble component (when we consider
  biomass aerosol internally mixed with sulphate
  aerosol)
• Soluble gases dissolve into a growing solution
  droplet prior to activation in cloud. This can
  decrease the critical super-saturation for
  activation
• In-cloud oxidation of SO2

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Current Met Office Simulations
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Aerosol microstructure
Diverse Size Ranges
NaCl 80 µm
(NH4)2SO4 Sub-micron
(NH4)2SO4 80 µm
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Biomass Aerosol

• Vegetation Fires
• Source of gases and AP.
• Fire emissions are
• transported by convection
• into the FT and lower
• stratosphere and are
• distributed from local to the
• meso-scale and even to the
• global scale

(Courtesy Dr S. Wurzler)
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Biomass and Soot Aerosol microstructure
Biomass Aerosol Leaf debris
Soot Aerosol
Chains of spherules with diameters 10 nm
(Courtesy Dr Gunter Helas)
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The Model

• Adiabatic parcel model, fully interactive
  chemistry, treats non-ideal behaviour of solution
  droplets (Pitzer calculations) (ODowd et al
  1999)
• Micro-physics dynamic growth equations for the
  growth of aerosol solution droplets by
  condensation of water vapour on a size resolved
  droplet spectrum
• Mass transport limitations based on Schwartz
  (1986).

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Kohler theory

• Vapor pressure over an aqueous solution droplet
• Kelvin effect increases vapor pressure
• Solute effect decreases vapor pressure

• S(1-B/r3)exp(A/r)
• 1A/r -B/r3
• A4Mwsw/RT?w
• 0.66/T (µm)
• B6nsMw/p?w
• 3.44x1013?ms/Ms
• (µm3)

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Kohler theory

• The maxima occur at the critical radius
• r(3B/A)1/2
• At this size
• S1(4A3/27B)1/2

Rp0.05µm
Rp0.5µm
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Challenges Microphysics

• Need to untangle the intertwined relationships of
  applied super-saturation, particle chemistry, and
  particle size
• Kohlers original theory formulated for one
  electrolyte.
• Need to adapt Kohler theory for aerosol particles
  in the atmosphere insoluble, sparingly soluble,
  surface active chemical compounds and soluble
  gases

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Model Testing and Validation

• Aerosol Characterisation Experiment 2 (ACE-2)
• Bi-component aerosol ammonium sulphate and
  sea-salt both externally mixed
• Considered effect of dissolved SO2 (Ghosh et al
  2005 )

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Model performance ACE-2
R(microns)
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Optical Properties
(Obs. Values)

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Fine mode chemistry
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Bi-component systems predictable behaviour

• Linear increases in
• CDNC with linear
• increases in sulphate
• mass.
• (Jones et al 2001)

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Tri-component model

• a s ?
• (nm) (kg/m3)
• Sulphate 95 1.16 1769
• Smoke 120 1.12 1350
• Salt (film) 100 1.32 2160
• Salt (jet) 1000 1.35 2160
• (salt wind speed dependent)
• U0.2 m/s
• Sol.0.25 (Yamasoe et al 2000)

Initial Spectrum
R(nm)
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Tri-component effects The non-intuitive
behaviour

• Note that CDNC can also decrease
• beyond a critical smoke threshold
• Steady decline in super-saturation
• when smoke conc. increases
• beyond a threshold
• Competition between film mode
• salt particles, sulphate, and smoke

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Tri-component Higher Salt Loading

• Activation scenario
• changes completely.
• The overall CDNC
• values are higher. The
• highest values of CDNC
• are observed only at
• low biomass smoke
• loadings.

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Sensitivity to salt loadings
Salt mass 10.3-27.6 µgm-3
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Tri-component activation contd.

• The CDNC is related to the sulphate and salt mass
  in a complicated non-linear way.

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Sensitivity to smoke loadings
Smoke mass 0.4-2.3 µgm-3
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Tri-component activation contd. importance of
the two salt modes

• Note the perturbing effect of the fine film mode
• The film mode number conc. comparable to smoke
  conc.

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Sensitivity to sulphate
Sulphate mass 0.1-0.9µgm-3
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Sensitivity studies Aerosol ageing (solubility
parameter)

• Increases in the solubility parameter causes a
  broader spectrum due to
• greater SO4 processing
• The total CDNC remains unchanged

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Sensitivity studies contd.

• Particles carrying more hygroscopic material
  consume more water vapour during their growth
  before reaching maximum super-saturation.
• The maximum saturation ratio is typically smaller
  in the case with more soluble material in the
  nascent droplets.

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Sensitivity studies updraught speed

• The Met. Office recommended value is 0.2 m/s
  based on ACE-2 and FIRE stratocumulus cases
• CDNC increases with increases in updraught speed
  up to a threshold 0.2 m/s
• For the given activation scenario higher
  updraught speeds do not increase the CDNC

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Aerosol Non-linear responses Clouds -
Autoconversion
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Aerosol-Cloud droplets-Precipitation New
insights Role of Turbulence

• Current models are
• generally unable to
• predict reasonable
• numbers of large
• droplets.
• These models assume
• that the droplets settle
• in still air

Without turbulence effects
With turbulence
Ghosh, Hunt and others, Proc. Roy. Soc. A, 2005
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Rain droplet spectra The role of turbulence

• Recent studies that have accounted for the faster
  settling rates of cloud droplets in turbulence
  have predicted realistic rain drop spectra

Ghosh, Hunt and others, Proc. Roy. Soc. A. , 2005
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Summary Evaluation of Global Aerosol and Cloud
Models
Data assimilation
Size distributed internal mixture
Multi-component aerosol as an internal mixture
Multi-component aerosol as an external mixture
Role of observations vis-a-vis models is changing
On-line sulphur cycle
Increasing complexity
Off-line sulphur cycle