smoke plume optical properties and transport observed by a multi-wavelength lidar, sunphotometer and...
TRANSCRIPT
Smoke plume optical properties and transport observed by a multi-wavelength lidar,
sunphotometer and satellite
Lina Corderoa,b
Yonghua Wua,b, Barry Grossa,b, Fred Mosharya,b,Sam Ahmeda,b
a NOAA-Cooperative Remote Sensing Science and Technology Centerb Optical Remote Sensing Lab, Department of Electrical Engineering,
The City College of New York
AMERICAN METEOROLOGICAL SOCIETY92nd Annual Meeting
New Orleans, January 22-26, 2012
Outline
• Motivation
• Introduction
• Instrumentation
• Methodology
• Observation Results– Case: Aloft smoke plumes from Idaho/Montana forest fires on August
14~15, 2007. (Origin: US northwest, Range: 2~8 km altitude, Angstrom Exponent ~ 1.8)
• Conclusions
• Acknowledgments
2AMERICAN METEOROLOGICAL SOCIETY
92nd Annual Meeting
Motivation
• Large amounts of smoke aerosol can be injected into the atmosphere as a result of forest-fire and biomass burning.
• Observations indicate that aerosol plumes potentially modify cloud physical, chemical and optical properties1.
• Consequently, smoke plumes affect climate radiation, air quality and visibility in the regional and continental scale.
3
Fig. 1 - Plumes of smoke from wildfires in Mexico and Texas on April
27, 2011, captured by MODIS/Aqua satellite
1 Kaufman et al., 2005; Sassen et al., 2003, 2008
AMERICAN METEOROLOGICAL SOCIETY92nd Annual Meeting
Introduction
• Analyze the smoke plume optical characteristics and long-distance transport using a ground-based multi-wavelength lidar, a sunphotometer and satellite observations in the New York City area.
• Long-distance transport and origins of smoke plumes are illustrated by MODIS/Aqua satellite, CALIOP imageries and NOAA/HYSPLIT air backward trajectory analysis.
• Event:– Aloft smoke plumes from Idaho/Montana forest fires on August 14~15,
2007.
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Instrumentation
• Ground-based multi-wavelength elastic-Raman scattering lidar– Observe 2D vertical distribution of
aerosols at wavelengths: 1064-, 532- and 355-nm.
– Aerosol extinction and backscatter coefficient profiles (AOD).
– Derive Angstrom exponents (e.g. spectral dependence of aerosol extinction or backscatter) to discriminate smoke plumes from cloud and dust particles.
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Fig. 2 – Light Detection and Ranging System at the City College of New York
Instrumentation
• AERONET Cimel sun/sky radiometer (CE-318)– Obtain aerosol optical depth (AOD)
at 340~1020 nm by measuring the direct solar radiance wavelengths.
– Derive aerosol microphysics parameters (volume size distribution and refractive index) are inverted from sky radiance measurements.
– Fine-mode and coarse-mode aerosol optical depths from the spectral curvature of AOD.
– Constrain lidar-derived multi-wavelength extinction profiles of aerosol plumes with the column AOD.
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Fig. 3 – AERONET Cimel sun/sky radiometer at the City College of New York
Methodology
• Angstrom exponent profile can be estimated as:
– Small particles such as smoke aerosols have larger Angstrom exponent.
– Large particles such as dust, sea salt and thin cloud have small Angstrom exponent.
– Thus, it can be used to discriminate aerosol type.
AMERICAN METEOROLOGICAL SOCIETY92nd Annual Meeting 7
)/log(
)](/)(log[
21
21
Eq. 1 – Angstrom Exponent
• Smoke plume vertical distribution and optical properties
Observation Results
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11 12 13 14 15 16 17
2
4
6
8
10
12
Local time (hour)
Alti
tude
(km
)
2007 Aug14, Ln(Pz2) at 1064-nm
-2
-1
0
1
2
3
4
11 12 13 14
2
4
6
8
10
12
Local time (hour)
Alti
tud
e (
km)
2007 Aug15, Ln(Pz2) at 1064-nm
-2
-1
0
1
2
3
4
Arriving aerosol plume Two aerosol plumes
Lower plume mixes with PBL
Fig. 4 – Time-height cross section of range-corrected lidar returns at 1064-nm
Observation Results
• Smoke plume vertical distribution and optical properties
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0 0.2 0.4 0.6 0.8 10
2
4
6
8
10
Aerosol extinction coefficient (km-1)
Alti
tud
e (
km)
355
5321064
-1 0 1 2 3 4
Angstrom exponent
Ang.
0 0.2 0.4 0.6 0.8 10
2
4
6
8
Aerosol extinction coefficient (km-1)
Alti
tud
e (
km)
355
5321064
-1 0 1 2 3 4
Angstrom exponent
Ang
Large Angstrom exponents indicate fine particles domination
Aerosol multi-layer with homogeneous particle size
Fig. 5 – Aerosol extinction and Angstrom exponent profiles a) Aug 14, 16:30-16:45 and b) Aug 15, 13:35-13:50
• Smoke plume column optical properties– Aerosol plume intrusion - AOD and Angstrom Exponent increase.
– Aerosol size distribution - Fine-mode volume dominance.
– AOD and Angstrom Exponent remain high on next day.
10-2
10-1
100
101
0
0.02
0.04
0.06
0.08
Radius (m)
dV(r)
/dln
(r) (
m3
/m
2)
sky-err=7.5%
sza=54
440
=0.69
Observation Results
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10 12 14 16 180
0.2
0.4
0.6
0.8
1
Local time (hr)
AO
D-5
00
20070814 AERONET CCNY-site
10 12 14 16 180
0.5
1
1.5
2
2.5A
ngst
rom
exp
.
Total
FineCoarse
Ang.
10 11 12 13 140
0.2
0.4
0.6
0.8
1
Local time (hr)
AOD
-500
20070815 AERONET CCNY-site
10 11 12 13 140
0.5
1
1.5
2
2.5
Angs
trom
exp
.
Total
FineCoarse
Ang.
Fig. 6 – Aerosol optical depth, Angstrom exponent and particle size distribution (16:42 pm, Aug.14) observed by AERONET sunphotometer on Aug.14 and Aug.15, 2007
Observation Results
• Smoke Plume Sources and Transport pathway– Large fires across the Northern Rockies in Idaho and Montana were
captured by MODIS/Aqua satellite at 2:00 pm on Aug.13, 2007. By August 15, the smoke plumes began to canvas the US northeast.
– NOAA-HYSPLIT shows the air mass traveled from Idaho/Montana forest fire area to the lidar site (~40-hour trip).
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Fig. 7 - Satellite images showing smoke and fires area on August 13, 2007 (2pm), and NOAA-HYSPLIT trajectory
Observation Results
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Smoke-Plume Transport – GOES AOD
Observation Results
• Smoke Plume Sources and Spatial distribution
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30354045500
2
4
6
8
10
12
14
Latitude (N,deg)
Altitu
de
(km
)
20070815, 7:01:13~7:06:47 UTC (night), CALIPSO, tot.att.bs532 (log-scale,km-1)
-9
-8
-7
-6
-5
-4
-3
Smoke
Cloud
Fig. 8 - MODIS/Aqua image on 15 August, 2007 (Lines-D1, D2 and N1 are the CALISPO ground-tracks), CALIPSO-attenuated backscatter coefficients (track as shown by line-N1)
Fire-smoke source region
Smoke stripes with mid-level AOD
CALIPSO overpass nearby CCNY-lidar site
showing dense smoke plumes
Observation Results
• Smoke Plume Sources and Spatial distribution
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30354045500
2
4
6
8
10
12
14
Latitude (N,deg)
Altitude (
km
)
Feature Type: CAL-LID-L2-VFM-ValStage1-V3-01.2007-08-15T06-57-06ZN.hdf
0=invalid, 1=clear air, 2=cloud, 3=aerosol, 4=stratospheric feature,5=surface,6=subsurface,7=no signal
0
1
2
3
4
5
6
7
30354045500
2
4
6
8
10
12
14
Latitude (N,deg)
Alti
tude (
km)
Aerosol sub-type: CAL-LID-L2-VFM-ValStage1-V3-01.2007-08-15T06-57-06ZN.hdf
0=not-determ.,1=clean marine, 2=dust, 3=polluted conti.,4=clean conti.,5=polluted dust, 6=smoke,7=other
0
1
2
3
4
5
6
7
CALIPSO VFM products properly classify the layer as aerosol
CALIPSO VFM products further classify them as smoke
Fig. 9 – CALIPSO classification of aerosol/cloud
Observation Results
• Lidar-derived AOD apportionment and smoke influence on local air quality– Aloft smoke plumes intrusion into the PBL, probably resulting in a
significant increase in surface PM2.5 loadings
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Fig. 10 - Time-height cross section of range-corrected lidar returns at 1064-nm and ground level PM 2.5 mass concentration at sites location in NYC nearby the lidar-site
08/13 08/14 08/15 08/16 08/17 08/18 08/190
10
20
30
40
50
60
70
80
Date (mm/dd)
PM
25 ( g
/m3)
PS274
PS154
Park-rowPS219
Freshkills
CCNY (lidar)
11 12 13 14
2
4
6
8
10
12
Local time (hour)
Altitu
de
(km
)
2007 Aug15, Ln(Pz2) at 1064-nm
-2
-1
0
1
2
3
4
Conclusions
• Smoke plumes optical properties and long-distance transport to the US east coast from US northwest are observed with the synergy measurements of ground-based multiple-wavelength elastic-Raman lidar, sun-photometer and satellite.
• High Angstrom exponents indicate the fine-mode dominated in the plumes layers (~1.8).
• The range-resolved lidar observations indicate that the elevated smoke plumes were entrained into the turbulent PBL, and the surface PM2.5 concentrations show the corresponding increasing trends.
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Acknowledgments
• This work is partially supported by the research projects of NOAA #NA17AE1625 and NASA #NCC-1-03009.
• Authors greatly appreciate the data from:– NASA-AERONET,
– NASA-MODIS observations,
– NASA-CALIPSO and DAAC
– NOAA-radiosonde,
– HYSPLIT data,
– Surface PM2.5 data from NYDEC.
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