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12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

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.

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12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

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  1. Determination of atmospheric structures, aerosol optical properties and particle type with the R-MAN510 Raman dual polarization lidarsuper ceilometerP. 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)

  2. Introduction • Aerosols and clouds have a strong impact on : • Aerosolscanalsodisturbhumanactivities : - Air quality - Climate (direct, semi-direct and indirect effects) - Meteorology - Reduction of visibility - Air traffic disruption (volcanicashes, desertdust) 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  3. Motivation : needs for ground-basedsensors An ambiguity in the models outputs regarding position and density. Need confirmation using vertical monitoring. Satellite measurements are limited by clouds and do not supply a vertical profile of the ashcloud MODIS image on April 15th 2010 In complement to satellite and models, groundbasedsensors are needed to detect plumes, to determinetheirheight, to identify and quantifythe aerosols.  Needsappropriategroundbasedremotesensors 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  4. Proof of automaticashdetection monitoring over Europe in 2010 with the ALS aerosol lidar 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  5. Motivation: identification of aerosols We are lucky, dust and ash are unspherical dpup to 100% dp>30% Icecrystals Augustine eruption, [Sassen et al,GRL, 2007] 10%<dp<25% dp~0% Desertdust Pollution aerosol 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  6. Characterizing aerosols with depolarization and Raman channels • Example of measurements realized by a ramanlidar prototype during the Eyjafjallajokull eruption • Clear separation between ashs, pollution aerosols and dusts ASH 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  7. RMan510 concept • Detectionof the layers • Getting the position • Classification of the aerosols /clouds • Quantification (more challenging) [Chazette et al. 2011, Donovan et al. 2011, Wienhold, 2011] • Welearntfromourpreviousproducts, redesigned the hardware and software platform and improved the algorithm 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  8. RMan510 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)

  9. An extended range • Ranges for the three channels • Low overlap 98% at 150m, full at 300m Rayleigh fit 10mn average Overlap Range (m) 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  10. Processingchain: structure detection Level 0 Raw data Level 1 PR2 Level 1.5 Detection of structures and opticalproperties Analogelastic // Elastic // signal Detection of structures (Aerosol gradients, aerosol/cloud layers) Photocountingelastic// photocomptage Analogelastic Elastic signal Photocountingelasticphotocomptage Analog N2-Raman analogique N2-Raman signal PhotocountingN2-Raman 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  11. Improvment of RMan510 gradient detection R-Man510 lidar Gradient + 2D method No need for specificthresholding Residual layer Convective layer Stable layer ALS lidar 1D gradient method 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  12. Cloud detection RMAN ALS Pourcentage of good detection Relative errorcomparedwithreference (%) 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  13. Getting more structure detailswith dual polarization Detection on parallelchannel Detection on BOTH polarizationchannels 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  14. Processingchain : opticalproperties Level 0 Raw data Level 1.5 Detection of structures and opticalproperties Level 1 PR2 Analogelastic // Elastic // signal Detection of structures (Aerosol gradients, aerosol/cloud layers) Photocountingelastic// photocomptage Analogelastic Particledepolarization ratio Volume depolarization ratio Elastic signal Photocountingelasticphotocomptage Elastic total signal Analog N2-Raman analogique Extinction, backscatter coefficients, AOD N2-Raman signal PhotocountingN2-Raman 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  15. Optical properties of aerosols and clouds : extinction coefficient and opticaldepth - RMAN1 - RMAN2 Comparison of two RMAN510 : RMSE = 1.7 % R²= 0.93 Comparison of AOD retrievedwithsunphotometer : RMSE ~ 10 % NIGHT DAY NIGHT 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  16. Optical properties of aerosols and clouds : depolarization ratio • Specific design to minimize cross-talk(10-6 max cross-talk followingFreudenthaler, 2010). • Absolute on-site calibration methodrealized for each lidar (Alvarez et al. 2006, lessthan 10% relative error on dp) • Depolarization ratio dpgives information on particlesphericity (lowdp for sphericalparticle ≠ highdp for non sphericalparticles) 50-60% Cirrus clouds 20-30% Dustaerosols 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  17. Processingchain : classificaction Level 0 Raw data Level 1 PR2 Level 1.5 Detection of structures and opticalproperties Analogelastic // Elastic // signal Detection of structures (Aerosol gradients, aerosol/cloud layers) Photocountingelastic// photocomptage Analogelastic Aerosol/cloudtyping Particledepolarization ratio Volume depolarization ratio Elastic signal Photocountingelasticphotocomptage Elastic total signal Analog N2-Raman analogique Extinction, backscatter coefficients, AOD N2-Raman signal PhotocountingN2-Raman 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  18. Aerosoltyping in RMAN510 • Typing can be done unambiguously thanks to lidar ratio (raman channel) vs depolarization ratio diagram (Burton et al.) • 4 types of aerosols: • Continental pollution • Maritime aerosols • Dust mix • Pure dust / Volcanic ashes Source Burton et al., AMTD, 2011 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  19. Aerosol/cloud classification Clouds Aerosols 1 Scattering ratio 2 Height of Structures • High Clouds • Middle clouds • Lowclouds • In the PBL • In the free troposphere 3 Shape (dp) Icecloud/Water cloud Spherical/Unspherical • Continental pollution • Maritime aerosols • Dust mix • Pure dust / Volcanic ashes 4 Lidar ratio + dp values Clouds :CALIOP AlgorithmTheoretical 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)

  20. All together ! Dustdetection Signal cross-polarized @ 355nm Signal co-polarized @ 355nm Lidar Ratio 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  21. Conclusion and perspective • Depolar+ N2 Raman for maximum data availability and detection of aerosols • RMAN510 an industrial and operationnaltool for network monitoring (IAA, evaluation by Meteofrance) • To beused in the lidar/ceilometer network (affordable and operational system) • Under validation by Meteofranceand by EARLINET SCC • Response to ClimateResearch, Air quality and emergency needs. 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  22. Thankyou for your attention 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  23. Quantifying the threat FromLidar measurement to mass concentration of ashparticleswithaccuracy of 70% + = • Local observations • of chemicalproperties of eruptedashes* • Optical refraction • Particlediameter Lidar data Mass concentration of ashlayers Accuracy of 70% (Chazette et al 2011) Conversion factor 0.65 to 1g/m2 at 355nm Wienhold, 2010; Chazette et al ,2010) Pollution layers Accuracy 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)

  24. Cloud mask Signal co-polarized @ 355nm Cirrus Middle Lowcloud 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

  25. Retrieval of depolarization ratio in cirrus R-MAN510 #1 Depolarization ratio in a cirrus at 6.7 km R-MAN510 #2 δcirrus_RMAN1= 30% ± 6% δcirrus_RMAN2= 32% ± 4% AODcirrus_RMAN1 =0.11 ± 0.04 AODcirrus_RMAN2= 0.13 ± 0.05 12th EMS Annual Meeting & 9th ECAC I 10-14 September 2012 I Łódź (Poland)

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