Using satellite observations to investigate natural aerosol loading

Colette L. HealdDavid A. Ridley, Kateryna Lapina

UPMC ParisMarch 22, 2011

DUST FROM NORTH AFRICA: IMPACTING AQ AND THE BIOSPHERE DOWN-WIND

More than half of dust emitted globally from N. Africa

TOMS: June 13-21, 2001

summer

winter/spring

Miami (1989-1997)

[Prospero et al., 1999]

[Prospero et al., 1981]

French Guiana (1978-1979)

SATELLITE CONSTRAINTS ON DUST SOURCE & TRANSPORT

Dave RidleyGEOS-Chem overestimates observed AOD in source region, underestimates summertime export

REALISTIC APPORTIONMENT OF SUB-MICRON DUST MASS

Shifted mass to larger sub-micron sizes (less optically efficient). Reduces AOD in better agreement with satellite & AERONET observations

[Haywood et al., 2003]

Observed Saharan dust size distribution

Simulated decrease in AOD

OLDNEW

DUST TRANSPORT FROM NORTH AFRICA

CALIOP GEOS-Chem CALIOP GEOS-ChemWINTER SUMMER

Annual Mean AOD

Good model simulation of dust transport and removal in winter/spring. Underestimate in dust in the SAL in summertime.

DEPOSITION OF AFRICAN DUST & PHOSPHOROUS IN THE AMAZON

We estimate 13 Tg/yr transported to Amazon annually. This is ~10-25% of the P supply for the Amazon. Otherwise from fires and biogenic particles [Mahowald et al., 2005].

Impact of greening of the Sahel on productivity of the Amazon?

[Ridley et al., in prep]

ANNUAL

ANNUAL MEAN AOD OVER THE REMOTE OCEANS

MODIS GEOS-Chem

% Difference GEOS-Chem Sea Salt

GEOS-Chem underestimates (~30%) marine AOD observed by MODIS . Likely fine aerosol [Jaegle et al., 2010], but does not match simulated sea salt.

Gong [2003] sea salt scheme updated to include SST dependence & validated against observations [Jaeglé et al., 2010]

Kateryna Lapina

COMPARISON WITH MARTIME AEROSOL NETWORK (MAN)

Model AOD (over remote regions) is also ~13% low compared to MAN

OTHER POSSIBLE FINE MARINE PARTICLE SOURCES

[O’Dowd et al., 2004]

GEOS-Chem simulation of sulfate relatively unbiased not the problem.BUT under biologically active conditions, OA dominates sub-micron aerosol mass.

SeaWIFS

Comparison of simulated sulfate to recent cruise observations (AMS) Observed aerosol composition

at Mace Head

IS THE OCEAN AN IMPORTANT SOURCE OF OA?Previous estimates range from 2.3 to 75 TgC/yr

No marine OA With marine OA

Observations from 5 ship cruises show that marine OA from 2 schemes

[Spracklen et al., 2008; Langmann et al., 2008] of ~8 TgC/yr are more than

sufficient to reproduce sub-micron OA.

Makes very little contribution to AOD (0.003).

[Lapina et al., ACPD, 2011]

OA Emissions

ORGANIC AEROSOL MAKES UP AN IMPORTANT FRACTION OF OBSERVED AEROSOL

Globally makes up 25-75% of total fine aerosol at the surface (ignoring soot here)

[Zhang et al., 2007]SulfateOrganics

CHALLENGES IN MODELING THE RIGHT LEVELS OF OA

SOA measured/modeled = 4-100!

[Volkamer et al., 2006]

Models do get it right sometimes (even more puzzling?) but is it for the right reason?

ITCT-2K4

IMPEXAMAZE-08

AMMA

Egbert

WHY DON’T MODELS GET IT RIGHT….

Terpenes(gas-phase)PBAP

Hydrocarbons(gas-phase & particulate)

Uncertain Formation (Missing sources? Poorly understood processes?)

Continuing Oxidation/Partitioning in the Atmosphere

10,000’s of (unidentified?) compounds with variable properties

CAN SATELLITE OBSERVATIONS SHED ANY LIGHT ON THE BUDGET OF OA?

SURFACE REFLECTANCE

Bottom-up calculations suggest that SOA source may be anywhere from 140-910 TgC/yr [Goldstein and Galbally, 2007].

topz

0

AOD= α RH z M z dz

Organicaerosol

Sulfate Dust

Sea SaltNitrate

SATELLITE AOD

Assumptions:Optical PropertiesSize Distributions

Aerosol Distributions

AEROSOL SPECIATED MASS CONCENTRATIONS

Soot

IF ONLY AEROSOL IN THE ATMOSPHERE WAS OA, WHAT LOADING IS IMPLIED BY SATELLITE AOD?

Calculate the “hypothetical” AOD implied by a constant 1 g/sm3 profile over the land, and see how we need to scale this locally to make up ENTIRE AOD reported by MISR.

Inverted OA loading is 3.5 TgC over land.Assume a 6 days lifetime = 215 TgC/yr

extrapolate to include outflow ~430 TgC/yr. (middle of Goldstein & Galbally range)

Inverted total MISR AOD: Surface OA concentrations

topz

0

AOD= α RH z M z dz

Estimate that ~150 TgC/yr source is required to close the

MISR-GEOS-Chem* discrepancy.

DJF JJA

MISR

GEOS-Chem*

MISR-GEOS-Chem*

*excluding OA

A MORE REALISTIC POSSIBILITY:REMOVE CONTRIBUTIONS FROM DUST, BC, INORGANICS

(assuming all the negative bias in the model is ONLY OA)

UNCERTAINTY ANALYSIS (boring but important!)

Assumed optical properties based on GADS database and log-normal size distribution recently

evaluated by Drury et al. [2010]

Uncertainty on estimated OA source = 80%

Estimated uncertainty on OA budget due to: Uncertainty on OA optical properties

* Except over high RH regions

Aerosol optical propertiesSize parametersRefractive indicesAerosol water uptake (growth factor)Relative humidity (assuming 5% uncertainty in GEOS-5 fields)

50%20%10%6%*

Conversion from burden to sourceAerosol lifetime (including effects of vertical profile and export fraction)

50%

Global budget of “other” aerosols simulated in GEOS-Chem

25%

MISR AOD measurements 10%

Total Error (added in quadrature) 80%

This is more than THREE TIMES what is currently included in global models….

BUT at the low end of Goldstein & Gallbally [2007] range.

HAVE WE REDUCED THE UNCERTAINTY ON THE OA BUDGET?

910

47 Existing GEOS-Chem sources

140 Our satellite top-down estimate 150

Range estimated

by: Goldstein

and Galbally [2007]

All units in TgCyr-1

[Heald et al., 2010]

Acknowledgments: Easan Drury, Sonia Kreidenweis, Dominick Spracklen, Steve Arnold, James Allan, Hugh Coe and Gordon

McFiggans, Soeren Zorn, Frank Drewnick, Tim Bates, Lelia Hawkins, Lynn Russell, Sasha Smirnov, Colin O’Dowd, Andy Hind and MISR,

MODIS & CALIOP retrieval teams