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Intro 1. Part 1. Black Carbon in Arctic snow: concentrations and effect on surface albedo Tom Grenfell & Steve Warren University of Washington Tony Clarke (University of Hawaii) Vladimir Radionov (AARI, St. Petersburg) Other UW participants: Dean Hegg, Richard Brandt,

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Intro 1

Intro 1

Part 1. Black Carbon in Arctic snow:

concentrations and effect on surface albedo

Tom Grenfell & Steve Warren

University of Washington

Tony Clarke (University of Hawaii)Vladimir Radionov (AARI, St. Petersburg)

Other UW participants:

Dean Hegg, Richard Brandt,

Sarah Doherty, Steve Hudson,

Mike Town, Hyun-Seung Kim,

Lora Koenig, Ron Sletten (ESS)

Jamie Morison, Andy Heiberg, Mike Steele (APL)

Project website: www.atmos.washington.edu/sootinsnow


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Primary influence of BC on Spectral Albedo was first characterized by Warren and Wiscombe 1980.(i) visible wavelengths(ii) grain radius

0.5ppm

0.05ppm

5 ppm

Snow Albedo

0.05 ppm

0.5 ppm

5 ppm


Where and when does this matter

Where and when does this matter (?)

  • Where and when does variation of snow albedo matter for climate?

  • Whenever large areas of snow are exposed to significant solar energy

  • Arctic snow

  • Tundra in spring

  • Sea ice in spring (covered with snow)

  • Greenland Ice Sheet in spring (cold snow)

  • Greenland Ice Sheet in summer (melting snow)

  • Glacier ice and sea ice:

  • Ablation zone of Greenland Ice Sheet in summer

  • Arctic sea ice in summer

  • Non-Arctic snow

  • Great Plains of North America

  • Steppes of Asia: Kazakhstan, Mongolia, Xinjiang, Tibet


Pioneering effort 1983 4 survey

Pioneering Effort – 1983/4 Survey


Clarke noone sites

Clarke & Noone Sites

Soot in snow 1983-4 (Clarke & Noone) Most amounts are 5-50 parts per billion.

1983


Expected magnitude of albedo reduction

Expected magnitude of albedo reduction

Warren & Wiscombe (1985);

Warren &

Clarke

(1986)

Soot contents from Clarke & Noone (1985)


Difficulties with remote sensing

Difficulties with remote sensing

Difficulties in the use of remote sensing to determine BC's effect on snow albedo

1. It's hard to distinguish snow from clouds-over-snow, which hide the surface. Thin near-surface layers of atmospheric ice crystals ("diamond-dust") are common in the Arctic.

2. The bidirectional reflectance (BRDF) is affected by:

a. small-scale surface roughness: ripples, sastrugi, suncups, pressure-ridges. (The effects of sastrugi on BRDF are different at different wavelengths, because they depend on the ratio of sastrugi width to flux-penetration depth.)

b. when thin surface-fog (or diamond-dust layer) covers the rough snow, the forward peak is enhanced and the nadir view is darker. This darkening at nadir could be mistaken for BC contamination.

c. Grain shape

3. Albedo reduction by BC in snow can be mimicked by:- thin snow. Sooty snow has the same spectral signature as thin snow.

- increase of grain size with depth (common situation) preferentially reduces visible albedo - sub-grid-scale leads in the Arctic Ocean. - BC in the atmosphere above the snow (Arctic haze).


Our sites

Our Sites

Our 4-year project (begun

in spring 2006): a

comprehensive surface-based survey

of BC in Arctic snow,

to repeat and extend Clarke & Noone’ssurvey from 1983/4.


Sampling profiles

Sampling Profiles


Filter apparatus deployed in the field

Filter Apparatus deployed in the field


Filters

Filters

Filters are compared to standard calibration filters. They will be scanned with a spectrophotometer to quantify BC, dust, & other components – different spectral absorption curves.


Greenland sector

BC in snow (ppb)

Median values

K. Steffen automatic

weather stations +

Greenland Sector


Canada sector

Canada Sector

BC in Snow (ppb)

M. Sturm (CRREL)

+


Russian sector

Russian Sector

T. Grenfell and Steve Hudson, Western Arctic Russia March-May 2007

Permissions were granted to enter restricted border areas;

International Polar Year (IPY) has prominence in Russia.


Representative profile khatanga

Representative Profile - Khatanga


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Новости МПГ

IPY News Information Bulletin June 2007

Stephen Hudson (left), a graduate student at the University of Washington, traveling up the Khatanga River


Table of results

Table of Results

*

*strong haze event


Enhancements

Enhancements

(1) Do particles collect at the surface as the snow melts?

Greenland (Dye-2) August 2007, melting snow:

surface 9 ppb, subsurface 3 ppb

(2) Snow grain size increases markedly with spring melt onset magnifying the effect of a given soot load – accelerating

melt. Δ(albedo) changes from -0.01 to -0.03 for 35 ngC/g


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Spectral albedo of snow observed at selected sites for closure - soot observations, RT modeling, and spectral albedo. Svalbard, March 2007


New snow loading and scavenging experiments tony clarke

New Snow Loading and Scavenging Experiments - Tony Clarke


Plans for 2008

Plans for 2008

January: Artificial snowpack to quantify effect of soot on snow albedo with homogeneous grain size and known BC loading - (Rich Brandt, Steve Warren – Adirondacks)

March-May: Snow sampling in Eastern Siberia (Grenfell & Warren)

April: Albedo & BC intercomparison with Norwegian Polar Institute

(Gerland, Brandt)

April-May: Redistribution of BC during melt (Sanja Forsstrøm at Tromsø)

July: Greenland melting-snow zone: redistribution study - fine vertical BC sampling of top 20 cm; spectral albedo (Brandt & Warren)

Calibrate new spectrophotometer; quantify BC, dust, other components (Sarah Doherty, Tom Grenfell); further comparisons with SP2 (Joe McConnell, Tony Clarke)

Scanning Electron Microscope and chemical analysis of samples to investigate source signatures (Hegg, Grenfell, Warren)


Thanks to

Thanks to:

Jim Hansen

for inspiring us to take on this project

Clean Air Task Force and NSF Arctic Program

for support


International polar year collaborations

International Polar Year Collaborations

This project has benefited from the increased scientific activity in the Arctic, 2007-9.

Collaborations:

Norwegian Polar Institute (Svalbard) Sebastian Gerland

Danish Polar Center (Northeast Greenland) Carl-Egede Bøggild

Arctic and Antarctic Research Institute (Russia) Vladimir Radionov

Volunteers who have collected snow for this project in 2007:

Konrad Steffen & Thomas Phillips (Univ. Colorado). Automatic weather stations in Greenland

Matthew Sturm (U.S. Army Cold Regions Lab, Fairbanks, Alaska).

Snowmobile traverse of Arctic Alaska and Canada

Jacqueline Richter-Menge (U.S. Army Cold Regions Lab, Hanover, NH).

Snow on sea ice in the Beaufort Sea

Jamie Morison, Andy Heiberg & Mike Steele (UW Applied Physics Lab).

North Pole Environmental Observatory and Switchyard Expt, Arctic Ocean.

Matt Nolan (Univ. Alaska). McCall Glacier, northern Alaska

Von Walden (Univ. Idaho). Ellesmere Island, Canada

Shawn Marshall (Univ. Calgary). Devon Island Ice Cap, Canada.


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Part 2. Source Attribution of Black Carbon in Arctic SnowDean Hegg, Tom Grenfell, Steve WarrenU. of Washington, Seattle, WA


Current data base

Current Data Base

  • 36 sites - Canada, Greenland, Russia, North Pole

  • BC estimates from filter samples

  • 26 soluble co-analytes from filtered, melted snow

a. Anions – ion chromatography

b. Hydrocarbons – liquid chromatography, mass spectrometer detection

c. Elements – ICP-OES (inductively coupled plasma with optical emission spectroscopy)


Bc concentration 3 most highly correlated analytes and a biomass fire tracer levoglucosan

BC concentration, 3 most highly correlated analytes, and a biomass fire tracer (Levoglucosan)

Levoglucosan is not simply correlated with BC but is identified by the factor analysis.


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PMF (Positive matrix factorization) model results (tentative) for available data base. The five most significant factors explained 90% of variance.

90 % of the mass of BC is associated with this and the next factor.


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PMF Results continued. Factor shown had next highest BC loading. These two factors accounted for over 90% of the BC

90 % of the mass of BC is associated with this and the previous factor.


Preliminary interpretation

Preliminary Interpretation

  • Both factors had appreciable levoglucosan, suggesting a strong biomass component to the BC


Preliminary interpretation1

Preliminary Interpretation

  • Both factors had appreciable levoglucosan, suggesting a strong biomass component to the BC

  • The 1st factor was associated primarily with the Russian sites, the 2nd with the Canadian sites


Preliminary interpretation2

Preliminary Interpretation

  • Both factors had appreciable levoglucosan, suggesting a strong biomass component to the BC

  • The 1st factor was associated primarily with the Russian sites, the 2nd with the Canadian sites

  • Both factors also indicated a pollution component of different composition for the two locales. This is expected and may be a geographic discriminator.

  • More species are needed to explore the attribution in detail.


Further analysis

Further Analysis

  • Analysis of non-filtered snow melt

  • Chemical analysis of snow filters for insoluble tracers.

  • In particular, analysis of filter deposits for PAH’s (polycyclic aromatic hydrocarbons).

  • More elaborate receptor modeling


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