Transcript Black Carbon in Snow: Treatment and Results Mark Flanner1 Charlie Zender2 Jim Randerson2 Phil Rasch1 NCARUniversity of California at Irvine.

Black Carbon in Snow:
Treatment and Results
Mark Flanner1
Charlie Zender2
Jim Randerson2
Phil Rasch1
1
NCAR
2
University of California at Irvine
Motivation
Hansen and Nazarenko (2004) Soot climate
forcing via snow and ice albedo, PNAS.
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The SNICAR Model
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Replaces existing snow albedo and heating
representation in CLM
Applies a two-stream, multi-layer radiative transfer
model (Toon et al., 1989) to predict fluxes with any
air/ice/aerosol mixtures.
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
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Mie scattering solutions predicted offline for ice and
aerosols
Assumes internally and externally-mixed BC
Uses 5 spectral bands and vertical layers that
match CLM thermal snow layers
BC (2 species) deposits from atmosphere
(prognostic aerosol model), influences radiation,
and flushes through snow column with meltwater
Prognoses effective grain size with a microphysical3
The importance of snow aging
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Snow exhibits large variability in grain size
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(30 < re < 2000 μm)
Snow effective grain size determines:
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Pure-snow reflectance
Depth-profile of solar absorption
Magnitude of perturbation by impurities
Albedo perturbation caused by a
given mass of BC varies more
than three-fold for a reasonable
range of effective grain size.
Microphysical model predicts snow
specific surface area (effective
radius) from diffusive vapor flux
amongst grains, depending on:
snow T, dT/dz, density, and initial
size distribution (Flanner and
Zender, 2006, JGR).
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Aerosol induced snow heating:
multiple positive feedbacks
(-)
Snow/Ice
Cover
(-)
+
Soot
Albedo
(+)
(-)
(+)
+
R_net
(+)
G
(-)
Snow
Grain
Size
(+)
+
(+) ?
Concentration of hydrophobic and large
impurities at the surface during
melting?
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Measured and modeled BC in snow
Flanner et al. (2007) Present day climate
forcing and response from black carbon in
snow, J. Geophys. Res.
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Radiative forcing
pattern of BC in snow
Forcing operates mostly in local
springtime, when and where
there is large snow cover
exposed to intense insolation,
coincidentally with peak
snowmelt. Hence, it is a strong
trigger of snow-albedo feedback,
which is maximal in spring (Hall
and Qu, 2006).
Forcing is dominated by FF+BF
sources, but strong biomass
burning events can have
significant impact on Arctic
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Global mean forcing and temperature
response
Experiment
1998:
2001:
FF+BF only:
10x 1998:
Forcing (W m-2)
+0.054 (0.007-0.13)
+0.049 (0.007-0.12)
+0.043
+0.28
∆Ts
+0.15
+0.10
Efficacy
4.5
3.3
+0.44
3.1
Hansen, et al. (2005) The efficacy of
climate forcings, J. Geophys. Res.
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Climate response
Earlier snowmelt
Reduced surface albedo
Surface air warming
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Driver of springtime snow cover change
Case PI1: Full pre-industrial equilibrium conditions
Case PI2: PI1 with 380 ppm CO2
Case PI3: PI1 with present-day FF+BF BC+OC active in the atmosphere
Case PI4: PI1 with present-day FF+BF BC active in snow
Case PI5: PI1 with present-day FF+BF BC+OC active in atmosphere and snow
Case PI6: PI5 with 380 ppm CO2
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Conclusions
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Snow microphysical model (SSA evolution) could
be useful for other CHEM studies
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e.g., “bromine explosion”
Springtime snowpack is highly sensitive to
reflectance changes
Snow-albedo and microphysical feedbacks amplify
initial (small) radiative forcing from BC, producing
greater “efficacy” than any other forcing agent
Future: Examine radiative effects of dust (Zender),
OC (new, absorptive optical properties), algae (?)
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