12th ems annual meeting & 9th ecac i 10-14 september 2012 i Łódź (poland)
DESCRIPTION
Determination of atmospheric structures, aerosol optical properties and particle type with the R-MAN 510 Raman dual polarization lidar super ceilometer P . Royer , A . Bizard , L . Sauvage, M . Boquet , L. Thobois , M. Renaudier , B. Bennai. - PowerPoint PPT PresentationTRANSCRIPT
Determination of atmospheric structures, aerosol optical properties and particle type with the R-MAN510 Raman dual polarization lidar super
ceilometer
P. Royer, A. Bizard, L. Sauvage, M. Boquet, L. Thobois, M. Renaudier, B. Bennai
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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Aerosols and clouds have a strong impact on :
Aerosols can also disturb human activities :
- Air quality- Climate (direct, semi-direct and indirect effects)- Meteorology
- Reduction of visibility - Air traffic disruption (volcanic ashes, desert dust)
Introduction
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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Satellite measurements are limited by clouds and do not supply a vertical profile of the ash cloud
An ambiguity in the models outputs regarding position and density. Need confirmation using vertical monitoring.
MODIS image on April 15th 2010
In complement to satellite and models, ground based sensors are needed to detect plumes, to determine their height, to identify and quantify the aerosols.
Needs appropriate ground based remote sensors
Motivation : needs for ground-based sensors
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
4Proof of automatic ash detection monitoring over Europe in 2010 with the
ALS aerosol lidar
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
5Motivation: identification of aerosols
Augustine eruption, [Sassen et al,GRL, 2007]
Pollution aerosol
Ice crystals
Desert dust
dp>30%
10%<dp<25% dp~0%
dp up to 100%
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
We are lucky, dust and ash are unspherical
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Characterizing aerosols with depolarization and Raman channels
ASH
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
• Example of measurements realized by a raman lidar prototype during the Eyjafjallajokull eruption
• Clear separation between ashs, pollution aerosols and dusts
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RMan510 concept
Detection of the layers Getting the position Classification of the aerosols /clouds Quantification (more challenging) [Chazette et al.
2011, Donovan et al. 2011, Wienhold, 2011]
We learnt from our previous products, redesigned the hardware and software platform and improved the algorithm
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
8RMan510 Raman lidar Super Ceilometer Networkable operational tool:
• Stand alone with a low maintenance laser (3 years maintenance cycle)
• 24/7 , high data availability
3 channels : 355 //, 355 , 387 N2
• Identify aerosols thanks to → Cross-polarization channel (depolarization ratio)→ 387 nm Raman channel (lidar ratio)
• Improve the retrieval of optical atmospheric parameters
→ Raman channel for the extinction coefficient
Stand alone remote sensor• Self and continuous calibration thanks to the Raman channel• No nephelometer or sun photometer are needed
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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Ranges for the three channels
Low overlap 98% at 150m, full at 300m
30s (Day/Night)
10min (Day/Night)
PR2 // 10 / 16.6 km 13 / 21 kmPR2 7 / 17 km 11.2 / 21 km
PR2 Raman 1.8 / 10 km 3.5 / 18 km
Rayleigh fit 10mn average
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
An extended range
Range (m)
Ove
rlap
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Elastic signal
Detection of structures (Aerosol gradients,
aerosol/cloud layers)
N2-Raman signal
Elastic // signal
Analog elastic //
Level 0Raw data
Level 1PR2
Level 1.5Detection of structures and optical properties
Photocounting elastic //
photocomptage
Analog elastic
Analog N2-Raman analogique
Photocounting N2-Raman
Photocounting elastic
photocomptage
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Processing chain:structure detection
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R-Man510 lidar
Gradient + 2D methodNo need for specific
thresholding
ALS lidar1D gradient method
Stable layerConvective layer
Residual layer
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Improvment of RMan510 gradient detection
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RMANALS
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Cloud detection
Relative error compared with reference (%)
Pour
cent
age
of g
ood
dete
ction
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Getting more structure details with dual polarization
Detection on parallel channel Detection on BOTH polarization channels
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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Elastic signal
Volume depolarization
ratio
Elastic total signal
Extinction, backscatter
coefficients, AOD
Detection of structures (Aerosol gradients,
aerosol/cloud layers)
N2-Raman signal
Elastic // signal
Particle depolarization
ratio
Analog elastic //
Level 0Raw data
Level 1PR2
Level 1.5Detection of structures and optical properties
Photocounting elastic //
photocomptage
Analog elastic
Analog N2-Raman analogique
Photocounting N2-Raman
Photocounting elastic
photocomptage
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Processing chain : optical properties
15Optical properties of aerosols and clouds : extinction coefficient and optical
depth
NIGHT NIGHTDAY
RMSE = 1.7 %R²= 0.93
Comparison of two RMAN510 :
RMSE ~ 10 %
Comparison of AOD retrieved with sunphotometer :
- RMAN1- RMAN2
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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Specific design to minimize cross-talk (10-6 max cross-talk following Freudenthaler, 2010).
Absolute on-site calibration method realized for each lidar (Alvarez et al. 2006, less than 10% relative error on dp)
Depolarization ratio dp gives information on particle sphericity (low dp for spherical particle ≠ high dp for non spherical particles)
Optical properties of aerosols and clouds : depolarization ratio
20-30%Dust aerosols
50-60%Cirrus clouds
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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Elastic signal
Volume depolarization
ratio
Elastic total signal
Extinction, backscatter
coefficients, AOD
Detection of structures (Aerosol gradients,
aerosol/cloud layers)
N2-Raman signal
Elastic // signal
Particle depolarization
ratio
Aerosol/cloud typing
Analog elastic //
Level 0Raw data
Level 1PR2
Level 1.5Detection of structures and optical properties
Photocounting elastic //
photocomptage
Analog elastic
Analog N2-Raman analogique
Photocounting N2-Raman
Photocounting elastic
photocomptage
Processing chain : classificaction
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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Typing can be done unambiguously thanks to lidar ratio (raman channel) vs depolarization ratio diagram (Burton et al.)
4 types of aerosols:o Continental pollutiono Maritime aerosolso Dust mixo Pure dust / Volcanic ashes
Source Burton et al., AMTD, 2011
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Aerosol typing in RMAN510
19Aerosol/cloud classificationScattering ratio Clouds Aerosols
Ice cloud/Water cloud Spherical/Unspherical
High Clouds Middle clouds Low clouds
In the PBL In the free troposphere
Continental pollution Maritime aerosols Dust mix Pure dust / Volcanic ashes
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Height of Structures2
Shape (dp)3
Lidar ratio + dp values
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Clouds :CALIOP Algorithm Theoretical Basis Document, Part 3: Scene Classification Algorithms (Liu et al, 2005)
Aerosols : Burton et al 2011, Communication G.Pappalardo 2012, T. Petzold, DLR, Royer 2011, David et al 2012 …
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
20All together ! Dust detectionSignal co-polarized @ 355nm Signal cross-polarized @ 355nm
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Lidar Ratio
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Depolar+ N2 Raman for maximum data availability and detection of aerosols
RMAN510 an industrial and operationnal tool for network monitoring (IAA, evaluation by Meteofrance)
To be used in the lidar/ceilometer network (affordable and operational system)
Under validation by Meteofrance and by EARLINET SCC
Response to Climate Research, Air quality and emergency needs.
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Conclusion and perspective
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Thank you for your attention
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
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From Lidar measurement to mass concentration of ash particles with accuracy of 70%
Lidar dataLocal observationsof chemical properties of erupted ashes*•Optical refraction•Particle diameter
+ =
Mass concentration of ash layersAccuracy of 70% (Chazette et al 2011)Conversion factor 0.65 to 1g/m2 at 355nmWienhold, 2010; Chazette et al ,2010)
Pollution layersAccuracy of 19 to 32% (Royer et al , 2010)Conversion factor 4.5g/m2 at 355nm (Rault et al, 2009)
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
Quantifying the threat
24Cloud maskSignal co-polarized @ 355nm
Cirrus
Middle
Low cloud
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)
25Retrieval of depolarization ratio in cirrus
δcirrus_RMAN1 = 30% ± 6%δcirrus_RMAN2 = 32% ± 4%AODcirrus_RMAN1 =0.11 ± 0.04AODcirrus_RMAN2= 0.13 ± 0.05
R-MAN510 #2
R-MAN510 #1 Depolarization ratio in a cirrus at 6.7 km
12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)