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Challenges in remote sensing of CCN concentration An assessment based on airborne observations of AOD, CCN, chemical composition, size distribution, light.

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Presentation on theme: "Challenges in remote sensing of CCN concentration An assessment based on airborne observations of AOD, CCN, chemical composition, size distribution, light."— Presentation transcript:

1 Challenges in remote sensing of CCN concentration An assessment based on airborne observations of AOD, CCN, chemical composition, size distribution, light scattering/absorption and humidity response over North America Yohei Shinozuka*, Jens Redemann, Phil Russell, John Livingston, Roy Johnson, S. Ramachandran, Qin Zhang (NASA Ames Research Center), Tony Clarke, Steve Howell, Volodia Kapustin, Vera Brekhovskikh, Cameron M c Naughton, Steffen Freitag (University of Hawai’i), Terry Lathem, Thanos Nenes (Georgia Institute of Technology) *NASA Postdoctoral Program, yohei@hawaii.edu

2 In this talk… Goal and method Preliminary findings

3 Goal To assess challenges in remote sensing of CCN concentration To quantify uncertainties associated with – aerosol chemical composition, – size distribution, – humidity response of light extinction and – vertical structure, using ARCTAS data.

4 Andreae, ACP 2009 Campaign averages.

5 AOD and CCN Concentration AATS-14 Georgia Tech The CCN concentration can be constrained by AOD to within a factor of ~3

6 AOD and CCN Concentration The CCN concentration can be constrained by AOD to within a factor of ~3, and by the light extinction of dried particles, a factor of ~2. Georgia Tech AATS-14HiGEAR (U. Hawaii) neph+PSAP Difference is attributable to the vertical structure and humidity response of light extinction. Georgia Tech

7 ARCTAS Airborne Measurements humidity response of light extinction (fRH nephs) vertical structure (AATS-14, neph+PSAP, lidar) aerosol chemical composition (AMS, SP2) size distribution (DMA, OPC) CCN concentration (CCN counter) for isolating the factors affecting the relationship of column integral optical properties to near-surface CCN concentration.

8 The critical dry diameter at 0.3% supersaturation (right axis) derived from direct CCN measurement and long DMA size distribution is larger than 100 nm for 65% of ARCTAS Canada data, including almost all in forest fire smoke (high extinction; horizontal axis) near the surface (filled marker). CCN Diameter Georgia Tech CCN counter HiGEAR (U. Hawaii) long DMA, neph, PSAP

9 Layer AOD for vertical profiles with Δalt. >1 km HiGEAR layer AODs were typically within ±(10%+0.02) of the AATS-14. [Russell et al. poster Thurs. PM] [Shinozuka et al., in preparation] Δ AOD/(100 m) for segments of vertical profiles with Δalt. = 100 m. 450 nm Comparing sunphotometer and neph+PSAP measurements

10 Example Extinction Spectra Two extinction spectra of – similar near-UV extinction coefficients – different near-IR wavelength dependences – vastly different number concentrations

11 Optically constraining particle concentration The number concentration of fine particles (100 – 400 nm) per extinction tends to increase with the extinction Angstrom exponent for comparable wavelengths, as expected.

12 Optically constraining particle concentration The relationship is stratified by the wavelength dependence of near infrared extinction.

13 AATS-14 fine-mode fraction compared with in situ data FMF derived from the spectral curvature after O’Neill et al. [2001]. SMF measured with neph+PSAP, with and without an impactor. More on AATS-14 tomorrow: Redemann et al. talk 8:15 AM, Russell et al. and Livingston et al., poster afternoon

14 Conclusions Among the NASA P-3 data during ARCTAS Canada, – the CCN concentration below 1 km can be constrained by AOD to within a factor of ~3, and by dry extinction, ~2. – The critical dry diameter derived for 0.3% supersaturation is larger than 100 nm for most cases. – Near UV and near IR extinction helps to constrain the number concentration of fine particles. We are in the process of quantifying the factors that affect the relationship of aerosol optical properties to near-surface CCN concentration.

15 EXTRA SLIDES

16 Including all altitudes, note the log scale.

17 The hygroscopicity parameterization by Petters and Kreidenweis [2007] κ is a function of critical diameter (D d ) and supersaturation (S c ), when surface tension (σ s/a ) and temperature (T) are assumed to be constant. D d = κ (-1/3) * 70 nm at 0.2% supersaturation Approximation: where κ is large, Figures not used in the text.

18 AEROSOL COMPOSITION AND SMOKE TYPE

19 Dark smoke from flaming fires White smoke from smoldering fires White smoldering and black flaming identified based on Tony Clarke’s flight report.

20 Dark smoke from flaming fires White smoke from smoldering fires Aerosol evolution in downwind transport? Characterization of smoke types and age with the wavelength dependence of scattering and SSA Smoke after evolution, or pollution from other sources? To be investigated.


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