ESTIMATED DESERT-DUST ICE NUCLEI

Transcription

1 ESTIMATED DESERT-DUST ICE NUCLEI PROFILES FROM CALIPSO Eleni Marinou *, Vassilis Amiridis, Albert Ansmann, Athanasios Nenes, Dimitris Balis, Rodanthi Mamouri, Alexandra Tsekeri, Ioannis Binietoglou, Dimitra Mamali, Ronny Engelmann, Holger Baars, Michael Kottas, Emmanouil Proestakis, Dimitra Konsta, Panos Kokkalis, Franko Marenco, Philippe Goloub, Jann Schrod, Michael Pikridas, Iasonas Stavroulas, Jean Sciare * IAASARS, National Observatory of Athens *Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki

2 Outline Cyprus Campaign - April 2016 Ice Nuclei Particle Concentration profiles from Polly-ΧΤ & CALIPSO Lidars More campaigns to be analyzed IN vs IWC from CALIPSO

3 Cyprus Campaign - April km Polly-XT Lidar UAV flights 32 km away In-situ

4 Polly-XT Observations during campaign Clouds Log of range corrected signal 1064nm Dust Events & cloud formation Clouds Transported Layer ML Elevated Layers Ice IN Linear Volume depolarization ratio 532nm Ice formation Ice clouds Dust Events & cloud formation Local dust Dust + Pollution Pure Dust Courtesy of Philippe Goloub AOD (550 nm) Angstrom ( nm) Nicosia

5 UAV Flights Clouds Log of range corrected signal 1064nm Dust Events & cloud formation Clouds Elevated Layers Ice IN Linear Volume depolarization ratio 532nm Ice formation Ice clouds Agia Marina

6 UAV Flights Clouds CALIPSO Lidar Log of range corrected signal 1064nm Dust Events & cloud formation Clouds Elevated Layers Ice IN Linear Volume depolarization ratio 532nm Ice formation Ice clouds Agia Marina

7 21/4/2016 Dust Event

8 21/4/2016 Dust Event Polly-XT measurements [Timeseries] 24hrs Log 1064nm of range corrected signal 1064nm CALIPSO measurements [10:36 UTC] Attenuated Backscatter 532nm Reflectance

9 21/4/2016 Dust Event Polly-XT measurements [Timeseries] 24hrs Ice cloud formation Log 1064nm of range corrected signal 1064nm CALIPSO measurements [10:36 UTC] Attenuated Backscatter 532nm Reflectance

10 21/4/2016 Dust Event Polly-XT measurements [Timeseries] 24hrs Ice cloud formation Log 1064nm of range corrected signal 1064nm CALIPSO measurements [11:06 UTC] ±80 m Attenuated Backscatter 532nm Reflectance

11 Polly Level 2 retrievals Night Day NF Ext b355/b532 b532/b1064 vol.depol 532 part. depol 532 vol. depol 355 part. depol NF Ext b355/b532 b532/b1064 vol.depol 532 part. depol 532 vol. depol 355 part. depol 355 Height a.s.e. (Km) Height a.s.e. (Km) Bsc.Coef. (Mm -1 sr -1 ) Ext. Coef. (Mm -1 ) Lidar Ratio (sr) Angstrom Exponent Depolar. Ratio Bsc.Coef. (Mm -1 sr -1 ) Ext. Coef. (Mm -1 ) Lidar Ratio (sr) Angstrom Exponent Depolar. Ratio UTC UTC

12 Estimated aerosol distributions Deser Dust: 31% Non-dust: 0.05% Fine & Coarse particle separation Dust Non-dust Dust Non-dust Mass Concentration Corse dust fine dust non dust Height a.s.e. (Km) Bsc.Coef. (Mm -1 sr -1 ) Depol. Ratio Bsc.Coef. (Mm -1 sr -1 ) Ext. Coef. (Mm -1 ) Mass Conc. (µgm -3 ) UTC Ansmann et al., ACP, 2012

13 Estimated aerosol distributions Deser Dust: 31% Non-dust: 0.05% Fine & Coarse particle separation Dust Non-dust Dust Non-dust Mass Concentration Corse dust fine dust non dust Dust Particle Concentration For Dust R>100 R>250 Dust Surface Conc. CCN INPC Height a.s.e. (Km) Height a.s.e. (Km) D15 N12 S15 ss ice Bsc.Coef. Depol. Ratio Bsc.Coef. Ext. Coef. Mass Conc. (Mm -1 sr -1 ) (Mm -1 sr -1 ) (Mm -1 ) (µgm -3 ) UTC Ansmann et al., ACP, n 100,dry (cm -3 ) n 250,dry (cm -3 ) s dry (10-12 m 2 cm -3 ) n CCN (cm -3 ) n INP (L -1 ) Conversions based on AERONET parameterizations Mamouri and Ansmann, ACP, 2016: Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters

14 Estimated aerosol distributions Height a.s.e. (Km) Deser Dust: 31% Non-dust: 0.05% 0.28 Fine 7& Coarse particle separation Dust 6 Non-dust Height a.s.e. (Km) o C -20 o C -10 o C o C Dust Non-dust 80 Mass Concentration Corse dust fine dust non dust 150 DeMott et al. (2015) Niemand et al. (2012) Steinke et al (2015) [ss ice 1.15] Height a.s.e. (Km) Dust Particle Concentration For Dust R>100 R>250 Dust Surface Conc CCN INPC D15 N12 S15 ss ice Bsc.Coef. Depol. Ratio Bsc.Coef. Ext. Coef. Mass Conc. n (Mm -1 sr -1 ) (Mm -1 sr -1 ) (Mm -1 ) INP (L -1 ) (µgm -3 ) UTC Ansmann et al., ACP, n 100,dry (cm -3 ) n 250,dry (cm -3 ) s dry (10-12 m 2 cm -3 ) n CCN (cm -3 ) n INP (L -1 ) Mamouri and Ansmann, ACP, 2016: Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters

15 Dust CCN and INPC distributions from CALIPSO Noon 11:06 UTC Bcs. Coeff. 532 nm Dust Mass Concentration (μg/m 3 ) High values but noisy data Particle depol. ratio 532nm Niemand et al Dust INPC (L -1 ) For 5-6 km: L -1

16 21/4/ hrs Ice cloud formation Log 1064nm of range corrected signal 1064nm ±80 m

17 21/4/ hrs Ice cloud formation Log 1064nm of range corrected signal 1064nm o C o C -30 o C -30 o C -30 o C Height a.s.e. (Km) o C -10 o C 0 o C g ( ) DeMott et al. (2015) Niemand et al. (2012) 2 Steinke et al (2015) [ss ice 1.15] o C -20 o C -20 o C <0.1 < o C 0 o C CALIPSO DeMott et al. (2015) Niemand et al. (2012) Steinke et al (2015) [ss ice 1.15] -10 o C 0 o C DeMott et al. (2015) Niemand et al. (2012) Steinke et al (2015) [ss ice 1.15] -10 o C 0 o C DeMott et al. (2015) Niemand et al. (2012) Steinke et al (2015) [ss ice 1.15] -20 o C -10 o C 0 o C n INP (L -1 ) n INP (L -1 ) n INP (L -1 ) n INP (L -1 ) T [ o C]

18 21/4/ hrs Ice cloud formation Log 1064nm of range corrected signal 1064nm UAV Measurements In 2 Altitudes: km & km Inside the dust layer ±80 m 99% Saharan mineral dust [electron microscopy analysis Martin Ebert, TU Darmstadt] RH: Jann Schrod schrod@iau.uni-frankfurt.de Analysis Temperature (C) INPC (L -1 )

19 21/4/ hrs Ice cloud formation Log 1064nm of range corrected signal 1064nm UAV Measurements In 2 Altitudes: km & km Inside the dust layer INPC UAV measurements was acquired with FRIDGE isostatic diffusion chamber FRIDGE: covers deposition and condensation mode De Motte 2015 & Niemand 2012: predicts immersion mode Steinke 2015: predicts deposition mode Jann Schrod schrod@iau.uni-frankfurt.de Schrod et al., AMT, 2016: Re-evaluating the Frankfurt isothermal static diffusion chamber for ice nucleation. Schrod et al., to be summited: Ice nucleation particles over the Mediterranean measured from unmanned aircraft systems.

20 More Campaigns: ICE-D 2015 Above Barbados

21 More Campaigns: Fennec 2011 & 2012 CALIPSO Flight Estimation of the uncertainties of dust particle concentration

22 More campaigns: April 2017 Targeting: Aerosol size distribution, particle concentration & CCN ERC of Bernadett Weinzierl DLR Falcon ERC of Bernadett Weinzierl EUFAR ClIma (Amiridis) DoGMA (Slobodan) SEAMAN (Kanakidou) Finokalia Cyprus: Cy-CARE FLEX ESA cal val Polly-XT measurements in Israel in-situ UAVs PollyXT lidar Cimel

23 Dust IN particle concentration close to clouds Dust backscatter 532nm CAIPSO INPC Mamouri & Ansmann, ACP, 2016 Formation of ice clouds from dust particles CALIPSO IWC

24 Analysis of IN activation at collocated dust & cloud areas above Europe & North Africa Ice Water Content (IWC) vs. Ice Nuclei Particle Concentration (INPC) for the entire 2012 Mediterranean Sahara PBL Elevated layers 3 clusters emerge, that depend on altitude/location Low clouds (Saharan and Mediterranean) (P>500mb) have two clusters with IN L -1 : important for initiating secondary ice. Elevated clouds (P<500 mb) contain IN L -1 : very important for cirrus clouds development. The sensitivity to IN parameterization form still needs to be assessed.

25 Feature work Finalize the IN product evaluation process through the comparisons with airborne measurements Conclude on the parameterization schemes to be applied Improve INPC retrievals by considering all modes of freezing when necessary in the parameterizations Apply the refined methodology on CALIPSO in order to provide a global climatology of dust IN concentrations

26 Back up slides

27 Typical Uncertainties in the Lidar-estimated properties