Transcript Powerpoint

Aerosol information from the
UV-visible spectrometer GOME-2
Piet Stammes,
KNMI, De Bilt, The Netherlands
7 November 2012
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Contents
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Importance of aerosols
Aerosol microphysics
Spectral absorption by aerosols
GOME-2
Absorbing Aerosol Index
First results on Aerosol Height
Acknowledgements to:
Martin de Graaf, Gijs Tilstra, Ping Wang, Olaf Tuinder (KNMI)
Eyk Boesche (FUB)
Marloes Penning de Vries (MPIC)
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Absorbing Aerosol Index map from SCIAMACHY
Siberian forest fires
in July 2006
Canadian and Alaskan
forest fires June-July 2004
Taklamakan desert
Californian forest fires
Libian desert
Thar desert
Rice straw burning
Desert dust
Sahara
Bodélé
Saudi Arabian
lowlands
Sahel biomass burning
and desert dust storms
Indonesian forest fires
Amazonian rainforest
biomass burning
biomass burning
smoke
biomass burning smoke
Smoke from forest fires
Smoke and Dust
weak
events
strong
events
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more data and information can be found at www.temis.nl
Why are aerosols important?
Air quality / Health
Climate
©IPCC 2007
Air traffic safety
Visibility
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Many aerosol types: chemical compositions,
sizes and shapes
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http://alg.umbc.edu/
Dust aerosols
Sahara dust event
Size distribution
©nasa earthobservatory
- Fine mode aerosols: around 0.1 micron
Absorbing aerosols:
• Desert dust
• Smoke
• Volcanic ash
- Coarse mode aerosols: around 1 micron
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Absorption by smoke above clouds
Observation by SCIAMACHY of absorption spectrum
of smoke aerosols.
This absorption leads to heating of the troposphere
up to 125 W/m2.
De Graaf et al., JGR, 2012
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GOME-2 on Metop
since 2006
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UV-visible-near-IR spectrometer
4 spectral channels, covering 240 - 790 nm
0.2-0.4 nm resolution
Polarization Monitoring Devices (PMDs) at 15 bands
• Main products: ozone, NO2, SO2, minor gases
• Additional products: aerosols, clouds, surface albedo
http://www.esa.int/esaLP/SEMTTEG23IE_LPmetop_0.html
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Pixel size of GOME-2 w.r.t. other sensors
• GOME(-1)
40 km
ERS-2
320 km
• GOME-2
40 km
Metop-A+B
80 km
• SCIAMACHY
Envisat
10 km
30 km
60 km
• OMI
EOS-Aura
40 km
GOME-2 PMD
13 km
24 km
Along track
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Absorbing Aerosol Index (AAI)
Definition:
residue
meas
Rayleigh






R340
R340
10
10
  log 

r  100   log 

R
R


 380 
 380 
where the surface albedo A for the Rayleigh atmosphere
simulations is such that:
meas
Rayleigh
R380
 R380
( A)
A is assumed to be wavelength independent:
A340 = A380
The residue represents the observed 340/380 nm colour as
compared to the pure Rayleigh colour (OMI: 354/388 nm)
AAI is the positive part of the residue
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Reflectance at TOA with absorbing aerosols
Doubling-Adding KNMI
Radiative Transfer Model
Solar zenith angle = 30°
Viewing zenith angle = 0°
Surface albedo = 5%
Absorbing aerosols:
altitude = 3-4 km
optical thickness  = 2
single scattering albedo
0= 0.75
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Reflectance at TOA with absorbing aerosols
and matched Rayleigh reflectance
As
To match the reflectance
in the absorbing aerosol
atmosphere at 380 nm ,
the surface albedo is
decreased in the Rayleigh
atmosphere:
Match at reference wavelength
Rayleigh atmosphere
Surface albedo = 0.6%
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Reflectance at TOA with absorbing aerosols
and matched Rayleigh reflectance
As
The curves don’t match at
340 nm:
Absorbing aerosols create
a positive residue.
Residue
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Generally:
• no clouds, no aerosols
• clouds, no absorbing aerosols
• absorbing aerosols
:r=0
:r<0
:r>0
AAI: r > 0
Pros and Cons:
+ AAI can detect UV absorbing aerosols:
volcanic ash, desert dust and smoke.
+ AAI works in cloudy scenes.
+ AAI works over ocean and land.
- AAI is an index: it depends on AOT (), SSA () and altitude ().
- AAI is very sensitive to absolute calibration.
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Simulations of AAI for biomass burning aerosols
Clear-sky case
Nadir view
Aerosols at 4-5 km
Clouds at 1-2 km
Cloudy case
AAI increases with AOT
AAI decreases with SZA
DAK RTM simulations
Wang et al., ACP, 2012
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Daily AAI map of GOME-2 spectral channels
http://www.temis.nl/airpollution/absaai/
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Daily AAI map from GOME-2 PMDs
PMDs have 8x
higher spatial
resolution than
the spectral channels
http://www.temis.nl/o3msaf/vaac_pmd/
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Information for the VAAC
(volcanic ash advisory centre)
Eyjafjolleruption
of April-May
2010
http://www.temis.nl/o3msaf/vaac_pmd/
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Smoke over Borneo from AAI, 1995 -2010
1997/1998 El Niño: drought caused many forest fires; 120.000 km2 forest burned.
Satellite data sources: GOME, SCIAMACHY, GOME-2
Figure: L.G. Tilstra, KNMI
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UV residue has two parts:
Absorbing Index & Scattering Index
Scattering aerosols and clouds
Absorbing aerosols
GOME-2 Aerosol Indices for July, 2011, cloud fraction < 0.2.
Work of Marloes Penning de Vries (MPIC, Mainz).
Penning de Vries et al., ACP, 2012
Penning de Vries, Visiting Scientist report of O3MSAF, 2012
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Effect of instrument degradation on the AAI
The global mean residue, the mean of all residues on a day between 60°N and
60°S, is about constant, showing only a very mild seasonal variation.
GOME-2
(for individual scan
mirror positions)
Instrument degradation has a very large impact on the residue/AAI:
2.3 % reflectance change ~ 1 AAI point.
Tilstra et al. (JGR, 2012) developed an in-flight degradation correction method.21
Aerosol Height retrieval
Approach: use cloud algorithm FRESCO for aerosol height
- FRESCO algorithm: fit of O2 A-band at 760 nm using a
Lambertian reflector as cloud model.
- FRESCO v6 has two retrieval modes for 2 retrieved
quantities:
Normal: Effective cloud fraction (cloud albedo  0.8) and Cloud height
Alternative: Scene albedo (cloud fraction  1) and Scene height
Wang et al., ACP, 2008
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FRESCO retrievals using simulated O2 A band spectra
for dust aerosols
Aerosol layer
Cloud layer
Clear-sky
Cloudy
Wang et al., ACP, 2012
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Puyehue volcano (Chile), 20110606, Westerly Box
Wang et al., ACP, 2012
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Puyehue volcano (Chile), 20110606, Easterly Box
Wang et al., ACP, 2012
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Conclusions
• Absorbing aerosols, like desert dust, smoke, and
volcanic ash can be detected by GOME-2
• GOME-2 provides near-real-time monitoring
information on these aerosols, with the products:
- AAI for absorbing aerosols
- SCI for scattering aerosols (if cloud mask is
used)
- FRESCO for aerosol height.
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Links
• O3MSAF GOME-2 data products: http://o3msaf.fmi.fi
• TEMIS GOME-2 data products: http://www.temis.nl
• GOME-2 and Metop: http://www.eumetsat.int
• GOME-2 L0 data quality information: http://gome.eumetsat.int
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References on GOME(-2) aerosol retrievals
M. de Graaf, P. Stammes, O. Torres, and R.B.A. Koelemeijer, Absorbing Aerosol Index: Sensitivity analysis, application
to GOME and comparison with TOMS, J. Geophys. Res. 110, D010201, doi:10.1029/2004JD005178, 2005.
M. de Graaf, L.G. Tilstra, P. Wang and P. Stammes, Retrieval of the aerosol direct radiative effect over clouds from
space-borne spectrometry, J. Geophys. Res., 117, D07207, doi: 10.1029/2011JD017160, 2012
M. de Graaf and P. Stammes and E.A.A. Aben, Analysis of reflectance spectra of UV-absorbing aerosol scenes
measured by SCIAMACHY, J. Geophys. Res. 112, D02206, doi: 10.1029/2006JD007249, 2007.
M. Penning de Vries, Beirle, S., and Wagner, T.: UV Aerosol Indices from SCIAMACHY: introducing the SCattering
Index (SCI), Atmos. Chem. Phys., 9, 9555-9567, doi:10.5194/acp-9-9555-2009, 2009
M. Penning de Vries, and Wagner, T.: Modelled and measured effects of clouds on UV Aerosol Indices on a local,
regional, and global scale, Atmos. Chem. Phys., 11, 12715-12735, doi:10.5194/acp-11-12715-2011, 2011.
L.G. Tilstra, M. de Graaf, I. Aben and P. Stammes, In-flight degradation correction of SCIAMACHY UV reflectances and
Absorbing Aerosol Index, J. Geophys. Res., 117, D06209, doi: 10.1029/2011JD016957, 2012.
L.G. Tilstra, M. de Graaf, O.N.E. Tuinder, R.J. van der A, and P. Stammes, Studying trends in aerosol presence using
the Absorbing Aerosol Index derived from GOME-1, SCIAMACHY, and GOME-2, Proceedings of the 2011
EUMETSAT Meteorological Satellite Conference, EUMETSAT P.59, ISBN 978-92-9110-093-4, 2011.
L.G. Tilstra, O.N.E. Tuinder, and P. Stammes, A new method for in-flight degradation correction of GOME-2 Earth
reflectance measurements, with application to the Absorbing Aerosol Index, Proceedings of the 2012 EUMETSAT
Meteorological Satellite Conference, EUMETSAT P.??, ISBN ??????????, 2012.
P. Wang, P. Stammes, R. van der A, G. Pinardi, M. van Roozendael, FRESCO+: an improved O2 A-band cloud retrieval
algorithm for tropospheric trace gas retrievals, Atmospheric Chemistry and Physics, 8, 6565-6576, 2008
P. Wang, O.N.E. Tuinder, L.G. Tilstra, M. de Graaf, and P. Stammes, Interpretation of FRESCO cloud retrievals in case
of absorbing aerosol events, Atm. Chem. Phys., 12, doi: 10.5194/acp-12-9057-2012, 2012.
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Back-up slides
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AAI products from GOME, SCIAMACHY,
GOME-2, and OMI
Wavelength
pair (nm)
Equator
crossing time
Pixel size
(km)
Days needed
for global
coverage
Platform / Operation
period
GOME–1
340 / 380
10 : 30 LT
320 × 40
3
ERS-2
(1995 – 2003*)
SCIAMACHY
340 / 380
10 : 00 LT
60 × 30
6
Envisat
(2002 – 2012)
GOME–2
340 / 380
09 : 30 LT
80 × 40
1.5
MetOp-A
(2006 – present)
OMI
354 / 388
13 : 30 LT
13 × 24
1
Aura
(2004 – present)
*GOME-1: loss of global coverage on 22 June 2003 ; instrument retired on 4 July 2011
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FRESCO retrievals using simulated O2 A band spectra for
biomass burning aerosols
Aerosol layer
Cloud layer
Clear-sky
Cloudy
Wang et al., ACP, 2012
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Australian Wildfires
Feb 7th – Feb 12th 2009
Figure: O. Tuinder, KNMI