Depolarization of Light by Single Particles: Unraveling the Mysteries of Paris Fog

Transcription

1 Depolarization of Light by Single Particles: Unraveling the Mysteries of Paris Fog Darrel Baumgardner Centro de Ciencias de la Atmósfera Universidad Nacional Autónoma de México Neda Boyouk Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) Laboratoire Meteorologie dynamique (LMD) Seminar November 25, 2010 LMD, Ecole Polytechnique

2 Seminar Outline I II III IV V VI Background Measurement Technique Implementation for Water/Ice Discrimination Implementation for aerosol shape analysis Implementation in Paris Fog Future Outlook

3 Seminar Outline I II III IV V VI Background Measurement Technique Implementation for Water/Ice Discrimination Implementation for aerosol shape analysis Implementation in Paris Fog Future Outlook

4 Non-Spherical Particles in the Atmosphere Discrimination of water and ice is critical problem in understanding cloud microphysical processes. Shape matters! Cloud and aerosol particle lifetime depends on fall velocity = f(mass, area, shape) Radiative flux balance depends on aerosol optical cross section = f(cross sectional area, i.e. shape) Chemical processing by aerosols depends on available surface area. Complex shapes have much more surface area.

5 Droplet Measurement Technologies (DMT) specializes in measuring the size of individual particles using optical techniques. In 2006 a researcher ask DMT to build a detector to detect when an ice crystal had formed in an ice nucleation chamber. The challenge is to separate activated water droplets from activated ice crystals. -6 < T < -40 C OPC Current technique can t measure liquid and water simultaneously.

6 Seminar Outline I II III IV V VI Background Measurement Technique Implementation for Water/Ice Discrimination Implementation for aerosol shape analysis Implementation in Paris Fog Future Outlook

7 Simplified Explanation Single particle, optical analysis uses the interaction between a polarized, focused laser beam and a single particle to derive the particle size, a shape parameter that is related to its non-sphericity (asphericity) and the refractive index that is related to its composition.

8 Simplified Explanation Single particle analysis uses the interaction between a polarized, focusd laser beam and a single particle to derive the particle size, a shape parameter that is related to its non-sphericity (asphericity) and the refractive index that is related to its composition. Optical diameter is derived from the scattered light collected from the particle using Mie Theory.

9 Single Particle Light Scattering Light scattering consists of reflection, refraction and diffraction. The intensity of scattering with respect to angle is complex and depends on size, shape and refractive index. With Mie scattering theory we relate the particle size to the scattered light for a given light collection angle of an instrument. This diagram is for the collection angles of the Fog Monitor and refractive index of water. Scattering Cross Section (cm -2 ) Diameter ( m)

10 Simplified Explanation Single particle analysis uses the interaction between a polarized, focusd laser beam and a single particle to derive the particle size, a shape parameter that is related to its non-sphericity (asphericity) and the refractive index that is related to its composition. Optical diameter is derived from the scattered light collected from the particle using Mie Theory. Asphericity is a function of the amount of light that is scattered at an angle different from the incident angle of laser polarization.

11 P22/P11 is a ratio of two scattering components, the parallel and perpendicularly polarized, that is proportional to the asphericity. 10 Rosette - 4 bullets 10 Rosette - 6 bullets 10 Rosette - 6 rough bullets P22/P Size ( m) Angle 10 Plate Angle Rosette - 6 bullets Angle Very rough aggregates P22/P Angle Angle Angle Calculations by Ping Yang and Qian Feng, Texas A&M

12 Simplified Explanation Single particle analysis uses the interaction between a polarized, focusd laser beam and a single particle to derive the particle size, a shape parameter that is related to its non-sphericity (asphericity) and the refractive index that is related to its composition. Optical diameter is derived from the scattered light collected from the particle using Mie Theory. Asphericity is a function of the amount of light that is scattered at an angle different from the incident angle of laser polarization. The refractive index is proportional to ratio of light collected from different angles.

13 Estimating the Refractive Index The relationship between side and back scattering depends on refractive index, size and shape

14 0.25 Estimating the Refractive Index Refractive Index is taken from a lookup table of back to side scattering ratios as a function of side scattering Backward to Side Scattering Ratio Ratio Back to Forward n=1.33 n=1.44 n= Diameter ( m)

15 Implementation : The Cloud Aerosol Spectrometer with Depolarization (CAS-DPOL)

16 CAS-DPOL (CAS with depolarization) Water/ice discrimination > 2 μm (Depolarization) Shape discrimination (forward to back scatter) Asymmetry factor estimate

17 Studies of water to ice transition with the CAS-DPOL >90% are aspherical No aspherical particles

18 Seminar Outline I II III IV V VI Background Measurement Technique Implementation for Water/Ice Discrimination Implementation for aerosol shape analysis Implementation in Paris Fog Future Outlook

19 The CAS-DPOL was flown on the British Met office aircraft in spring of Here we show the response of the depolarization detector as a function of time and particle diameter. The white trace is the temperature.

20 In warm clouds, when the temperature was > 10 0, the depolarization signal is quite low, < 500 counts (relative signal.) Liquid Phase

21 And the water fingerprint, created by making a map of the back scattering to depolarization ratio, is a way to identify water droplets. Here the depolarization ratio is defined as the signal from the depolarization detector to the back scattering detector.

22 Likewise in cold clouds, when the temperature was < 0 0, the depolarization signal is much higher, > 1000 counts (relative signal.) Mixed Phase

23 And the mixed phase fingerprint is a combination of water and ice.

24 The white line shows the approximate threshold for water.

25 And can be used to distinguish the water part of mixed phase clouds. Here we see that most of the particles were ice.

26 Seminar Outline I II III IV V VI Background Measurement Technique Implementation for Water/Ice Discrimination Implementation for aerosol shape analysis Implementation in Paris Fog Future Outlook

27 APSD Optical Configuration Aerosol Inlet Mangin Mirror Pair 90 o ± 54 o Polarized Backscatter 20 o ± 13 o Non-Polarized Backscatter 20 o ± 13 o

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29 Just like with the water and ice clouds, the maps of the frequency of depolarization ratio versus backscattering highlight differences in the shapes of different ambient particles

30 Examination of six types of dusts, Icelandic volcanic dust and Colorado pine pollen show some distinct differences in their fingerprints and other subtle differences are evident when maps are compared by differencing.

31 Seminar Outline I II III IV V VI Background Measurement Technique Implementation for Water/Ice Discrimination Implementation for aerosol shape analysis Implementation in Paris Fog Future Outlook

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33 SIRTA DMT FM-100 DMT CCN DMT APSD

34 Research Objectives Evaluate the response of the APSD to environmental aerosols. Document the changes in aerosol properties (size, shape and concentration) before, during and after fog events. Evaluate the evolution of fog distributions to the aerosol properties before and after the formation of fog. Document the changes in aerosol properties as a function of air mass origin. Evaluate the relationship between the aerosol properties and the supersaturation spectrum of CCN, visibility and particle mass measured with the TEOM. Compare the APSD with other instruments.

35 Aerosol Cloud Interactions Pre-Cloud Cloud Post-Fog No Change

36 Aerosol Cloud Interactions Pre-Cloud Cloud Post-Fog Inertial scavenging and droplet coalescence lead to changes in number and mass concentration and changes in composition.

37 Aerosol Cloud Interactions Pre-Cloud Cloud Post-Fog Uptake of precursor gases and aqueous processing leads to changes in mass concentration and composition.

38 Aerosol Cloud Interactions Pre-Cloud Cloud Post-Fog Uptake of water may change aspherical particles to spherical as a result of a liquid layer. How does this impact how they interact with light?

39 During some time periods there was significant growth of the size of aerosol particles.and other times there was large increase in the number but not the size.

40 There are significant variations in the number concentration as a function of size over a one week time period.

41 There are also significant variations in the depolarization ratio over a one week time period.

42 There is no consistent relationship between relative humidity and depolarization ratio.

43 There is also no consistent relationship between local wind direction and depolarization ratio.

44 Primary Biological Aerosol Particles?

45 ?

46 Measurements in Europe, using fluorescence to identify PBAP, show dominant signals between 2 and 3 um, similar to what is seen in the APSD.

47 Seminar Outline I II III IV V VI Background Measurement Technique Implementation for Water/Ice Discrimination Implementation for aerosol shape analysis Implementation in Paris Fog Future Work

48 The footprints are clearly different depending on the time period and ambient conditions.

49 Future challenge is to relate the individual patterns to types of aspherical patterns.

50 Acknowledgements Ecole Polytechnique Helene Chepfer Jean-Charles Dupont Martial Haeffelin Mahdi Belaid Christophe Boitel Christophe Pietras Bernard Romand Florian Lapouge DMT Roy Newton Gary Granger DLR Bernadett Weinzierl University of Manchester James Dorsey Martin Gallagher