Connecting LidarDerived Aerosol Hygroscopicity to Estimated CCN Concentrations

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Connecting Lidar-Derived Aerosol Hygroscopicity to Estimated CCN Concentrations during the Combined HSRL and Raman

Connecting Lidar-Derived Aerosol Hygroscopicity to Estimated CCN Concentrations during the Combined HSRL and Raman Lidar Measurement Study (CHARMS) Kyle Dawson NASA Postdoctoral Program January 13 th, 2020 AMS 100 th Annual Meeting Coauthors: Rich Ferrare, Rich Moore, Tyler Thorsen, Marion Clayton, Ed Eloranta, John Goldsmith

Aerosols, Clouds, and Climate activated aerosol rain aerosol Adapted from IPCC AR 5

Aerosols, Clouds, and Climate activated aerosol rain aerosol Adapted from IPCC AR 5

Aerosol Chemistry and Atmospheric RH Low Relative Humidity dust ammonium sulfate sea-salt black carbon

Aerosol Chemistry and Atmospheric RH Low Relative Humidity dust ammonium sulfate sea-salt black carbon High Relative Humidity Slide adapted from Prof: Nicholas Meskhidze, NCSU

Aerosol Amount Influences Cloud Brightness and Lifetime

Aerosol Amount Influences Cloud Brightness and Lifetime

Humidification Factors

Humidification Factors

System Design MLH • Tandem Lidars • Raman Lidar + HSRL • Retrieves water

System Design MLH • Tandem Lidars • Raman Lidar + HSRL • Retrieves water vapor mixing ratio, temperature, and aerosol optical properties mixed layer • Optical Measurements • Aerosol backscatter coefficients at 3 wavelengths (355, 532, and 1064 nm) • Aerosol extinction coefficients at 2 wavelengths (355 and 532 nm) • Polarization sensitivity at 532 nm surface • Microphysical Retrievals • 3β+2�system • Inversion of aerosol volume, surface area, number concentration, fine and coarse mode effective radius and index of refraction (beta )

 Physically based Functional Parameterization: mixed layer MLH surface Dawson et al. , 2019;

Physically based Functional Parameterization: mixed layer MLH surface Dawson et al. , 2019; submitted

Meteorological conditions must well-mixed requirements. First – Airmass History Dept. of Energy Oklahoma Site

Meteorological conditions must well-mixed requirements. First – Airmass History Dept. of Energy Oklahoma Site Instantaneous Wind Measurements at Site (Doppler Lidar) HYSPLIT Wind History Trajectory Analysis (Model)

Meteorological conditions must then be quantified as “well-mixed” for evaluating f(RH)

Meteorological conditions must then be quantified as “well-mixed” for evaluating f(RH)

Specially designed lidars enable real-time, simultaneous retrievals of aerosol and meteorological properties 2/00 2/06

Specially designed lidars enable real-time, simultaneous retrievals of aerosol and meteorological properties 2/00 2/06 Meteorology 3/00 2/18 2/12 3/06 Time of Day in August, 2015 (day/hour UTC) Vertically Distributes Aerosol Concentration 3/18 Affects Aerosol Water Uptake Retrievals

Retrievals Make Sense Compared to Observations 2015 August 2 nd nephelomete rnephelometer All Data

Retrievals Make Sense Compared to Observations 2015 August 2 nd nephelomete rnephelometer All Data

This information content gives aerosol intrinsic and microphysical properties • (a and b) 355/532

This information content gives aerosol intrinsic and microphysical properties • (a and b) 355/532 nm aerosol extinction coefficient (Raman/HSRL) • (c) Fine mode aerosol volume concentration (inversion retrieval) • (d) Aerosol depolarization ratio (cross to parallel channel ratio) • (e) Aerosol lidar ratio (ratio of extinction to backscatter cross section)

Recapping… • Humidification factors can be retrieved by lidar • Lidar retrievals near cloud

Recapping… • Humidification factors can be retrieved by lidar • Lidar retrievals near cloud base are generally comparable to surface retrievals but show some differences • 3β+2� design gives microphysical properties inching towards direct retrievals of hygroscopic growth factor

Connections to activated CCN and the Indirect Effect

Connections to activated CCN and the Indirect Effect

The Indirect Effect (IE) •

The Indirect Effect (IE) •

Cloud Retrievals from August 2 -3, 2015 Updraft Velocity (Doppler Lidar) IE = 0.

Cloud Retrievals from August 2 -3, 2015 Updraft Velocity (Doppler Lidar) IE = 0. 12 Cloud Droplet Number Concentration (CCN + Doppler) Liquid Water Content (MWR) Cloud Droplet Effective Radius (CCN + Doppler + MWR) Day/HH (UTC) IE = 0. 13

Aerosol indirect effect retrievals at near constant LWP

Aerosol indirect effect retrievals at near constant LWP

Variable (�� ) Aerosol indirect effect retrievals binned by constant LWP/△Z Na (lidar) -0.

Variable (�� ) Aerosol indirect effect retrievals binned by constant LWP/△Z Na (lidar) -0. 24 [-0. 30] rg (lidar) �� ext (neph; lidar) ω (model) -3. 02 [-0. 11] -0. 15; 0. 004 [-0. 03 solubility] -0. 08 [-0. 06] *Comparisons in brackets reported in GRL Feingold (2003) Table 1

Cloud Retrievals from August 2 -3, 2015 Updraft Velocity (Doppler Lidar) IE = 0.

Cloud Retrievals from August 2 -3, 2015 Updraft Velocity (Doppler Lidar) IE = 0. 12 IE = 0. 13 Kappa Extinction from Lidar Cloud Droplet Number Concentration (ACSM + Doppler) Liquid Water Content (MWR) HH: MM (local time) Cloud Droplet Effective Radius (ACSM + Doppler + MWR) Day/HH (UTC) HH: MM (local time) Day/HH (UTC)

Lidar can retrieve aerosol humidification factors f(RH) These f(RH) are retrieved near cloud base

Lidar can retrieve aerosol humidification factors f(RH) These f(RH) are retrieved near cloud base or at the top of the mixed layer Take Home Points 3 beta + 2 alpha volume concentrations diameter growth factor and kappa Aerosol IE retrievals at cloud base are consistent within theoretical limits at constant LWPs Preliminary impacts of aerosol hygroscopicity on IE suggest low sensitivity

Questions?

Questions?

Spectral Dependence of HGF

Spectral Dependence of HGF

Dust Marine Pollution Longitude Dawson et al. , 2017: Aerosol types simulated by GEOS-Chem

Dust Marine Pollution Longitude Dawson et al. , 2017: Aerosol types simulated by GEOS-Chem using clustering algorithm trained from collocated lidar aircraft observations off the eastern US coast during the NASA Ship-Aircraft Bio-Optical Research experiment

Theory • Twomey-Cohard cloud activation • Assume surface activation spectra is representative of below

Theory • Twomey-Cohard cloud activation • Assume surface activation spectra is representative of below cloud aerosol composition • When lidar retrieval of number concentration is available, it is used • Doppler lidar cloud-base average updraft velocity used (doi 10. 11175/JAS-D-14 -0283. 1) • Max supersaturation and Cloud droplet number concentration [#/cm 3] calculated • CCN at 0. 3% supersaturation also calculated • Dcrit and D 99 also retrieved (currently not used)

 • Theory

• Theory

Auxiliary Modeling Slide • Measured fine-mode aerosol chemistry in part (a) is fed into

Auxiliary Modeling Slide • Measured fine-mode aerosol chemistry in part (a) is fed into the Extended Aerosol Inorganic Model (http: //www. aim. env. uea. ac. uk/aim. php) • (b) Water-dependence of the refractive index is estimated by the E-AIM growth factor (c) and by the AERONET retrieved columnar Io. R • (d) AERONET Columnar Size distributions are then trimmed by the lidar-sensitive region (a function of wavelength) and grown by applying the volume growth factor enhancement to all particles in the size range.