Infmuence of Turbulent Fluctuations on Cloud Droplet Size Dispersion - PowerPoint PPT Presentation

Introduction Experimental Description Results Summary Infmuence of Turbulent Fluctuations on Cloud Droplet Size Dispersion and Aerosol Indirect Efgects Kamal Kant Chandrakar Dr. Will Cantrell, and Dr. Raymond A. Shaw Michigan Technological University Acknowledgment : NSF, NASA Earth and Space Science Fellowship [1 / 16] Kamal Kant Chandrakar Turbulence Induced Aerosol Efgects Π -Chamber Group

Introduction Experimental Description Results Summary Aerosol Indirect Efgects Theoretical Framework Source: NASA Earth Observatory [2 / 16] Kamal Kant Chandrakar Turbulence Induced Aerosol Efgects

Introduction Experimental Description Kamal Kant Chandrakar [3 / 16] Pontikis & Hicks 1992 r : relative dispersion n : droplet number density; L : liquid water content; Turbulence Induced Aerosol Efgects Theoretical Framework Results Summary Aerosol Indirect Efgects Efgective Radius Parameterization ] 1/3 ∫ r 3 n ( r ) dr [ 3 L r e = r 2 n ( r ) dr ≈ ∫ 4 π ρ l n d k ( d , γ ) d ≡ σ r /¯ γ : skewness; k = r 3 / r 3 e and d ↑ ⇒ k ↓

Introduction Experimental Description Results Summary Aerosol Indirect Efgects Theoretical Framework e : Marine Cloud Continental Cloud Martin et al. JAS 1998 [4 / 16] Kamal Kant Chandrakar Turbulence Induced Aerosol Efgects A linear relation between r 3 and r 3

Introduction X Kamal Kant Chandrakar [5 / 16] Pontikis & Hicks 1992 Dispersion Efgect Lifetime Efgect Twomey Efgect d Experimental Description Theoretical Framework Aerosol Indirect Efgects Summary Results Turbulence Induced Aerosol Efgects k = r 3 / r 3 e and d ↑ ⇒ k ↓ τ ∝ n 1/3

Introduction Experimental Description Kamal Kant Chandrakar [5 / 16] Pontikis & Hicks 1992 Dispersion Efgect Lifetime Efgect Twomey Efgect X X d Theoretical Framework Aerosol Indirect Efgects Summary Results Turbulence Induced Aerosol Efgects k = r 3 / r 3 e and d ↑ ⇒ k ↓ τ ∝ n 1/3 L 2/3

Introduction Experimental Description Kamal Kant Chandrakar [5 / 16] Pontikis & Hicks 1992 Dispersion Efgect Lifetime Efgect Twomey Efgect X Turbulence Induced Aerosol Efgects X d Theoretical Framework Aerosol Indirect Efgects Summary Results k = r 3 / r 3 e and d ↑ ⇒ k ↓ τ ∝ n 1/3 L 2/3 k 1/3 ∆ Z

Introduction Experimental Description Kamal Kant Chandrakar [6 / 16] Miles et al. 2000; Zhao et al. 2006; Lu et al. 2008; Tas et al. 2015 Lohmann 2003 ;Pawlowska et al. 2006; Pandithurai et al. 2012 Martin et al. 1998; Miles et al. 2000; Liu and Daum 2002; Peng and Miles et al. 2000; Lu et al. 2007,2012,2013 Atmospheric Observations Theoretical Framework Aerosol Indirect Efgects Summary Results Turbulence Induced Aerosol Efgects Aerosol ↑ ⇒ d ↓ (Enhanced indirect efgects): Aerosol ↑ ⇒ d ↑ (Suppressed indirect efgects): Aerosol ↑ ⇒ d ⇒ constant or unclear trend:

Introduction Experimental Description Kamal Kant Chandrakar [7 / 16] Supersaturation fmuctuations are not included Small droplet size dispersion Limitations: Yum and Hudson 2005; Liu et al. 2006; Peng et al. 2007 correlation between d and Aerosol Droplet size dispersion decreases with time r dr Adiabatic Condensation Approach Theoretical Framework Aerosol Indirect Efgects Summary Results Turbulence Induced Aerosol Efgects dt ∝ s Aerosol ↑ ⇒ s ↓ ⇒ decreased narrowing: a positive

Introduction Experimental Description Kamal Kant Chandrakar [8 / 16] Chandrakar et al. PNAS 2016, JAS 2018 droplet lifetime. fmuctuation forcing, as well as, on the supersaturation mean and The relative dispersion depends on n d : Droplet concentration fmuctuation s and s’: Supersaturation mean and s o Turbulence Induced Aerosol Efgects t Results Summary Aerosol Indirect Efgects Theoretical Framework s t Stochastic Condensation ¯ dr 2 dt = 2 ξ (¯ s + s ′ ) σ s : std of supersaturation fmuctuations τ t : Turbulence correlation timescale r 2 ∝ ¯ σ s 0 τ 1/2 r n d τ t ) t 1/2 σ r 2 ∝ (1 + C ¯ d ∝ σ s o t − 1/2

Introduction Experimental Description Kamal Kant Chandrakar [9 / 16] Chandrakar et al. PNAS 2016 Turbulence Induced Aerosol Efgects Results Summary Steady-State Turbulent Cloud Turbulent Mixing Cloud Formation in the Π -Chamber cool, humid a) b) steady aerosol injection Bottom 30 cloud droplet 25 activation p v [mbar] p v,mix turbulent 20 Equilibrium Vapor Pressure, p s (T) droplet growth p s (T mix ) convection in turbulent environment 15 T mix 10 Top droplet low high 5 10 15 20 25 sedimentation aerosol aerosol T [ o C] injection injection warm, humid

Introduction e : Kamal Kant Chandrakar [10 / 16] Martin et al. JAS 1998 Experimental Description Turbulence Induced Aerosol Efgects Results Summary Efgective Radius Parameterization Autoconversion Timescale Aerosol Efgect on Relative Dispersion A linear relation between r 3 and r 3 1200 k = 0.66 0.01 k = 0.84 0.1 1000 100 3 [ m 3 ] 80 800 r v 60 3 [ m 3 ] 600 k = 0.62 0.03 60 80 100 120 1200 3 [ m 3 ] r v r e 1000 3 [ m 3 ] 800 400 600 r v 400 200 200 500 1000 1500 3 [ m 3 ] r e 0 0 200 400 600 800 1000 1200 1400 1600 1800 3 [ m 3 ] r e

Introduction Experimental Description Kamal Kant Chandrakar [11 / 16] Chandrakar et al. JAS 2018 Turbulence Induced Aerosol Efgects Autoconversion Timescale Results Summary Efgective Radius Parameterization Aerosol Efgect on Relative Dispersion 0.5 Measurement Stochastic Condensation Model 0.4 0.3 d 0.2 0.1 0 10 2 10 3 n d [cm -3 ]

Introduction Experimental Description Kamal Kant Chandrakar [12 / 16] Chandrakar et al. JAS 2018 function of n d . increasing lifetime is an average droplet since the s o Turbulence Induced Aerosol Efgects Autoconversion Timescale Results Summary Efgective Radius Parameterization Aerosol Efgect on Relative Dispersion 0.5 Measurement d ∝ σ s o Stochastic Condensation Model t − 1/2 0.4 n d ↑ ⇒ d ↓ : 0.3 d 0.2 0.1 0 10 2 10 3 n d [cm -3 ]

Introduction Experimental Description Kamal Kant Chandrakar [13 / 16] Chandrakar et al. GRL 2018 (in review) Turbulence Induced Aerosol Efgects Autoconversion Timescale Results Summary Efgective Radius Parameterization Aerosol Efgect on Relative Dispersion Dispersion efgect enhances the 1 st indirect efgect ( τ ∝ k 1/3 ): 1200 1 k = 0.66 0.01 0.95 k = 0.84 0.1 1000 0.9 100 3 [ m 3 ] 80 0.85 800 r v 60 3 [ m 3 ] 0.8 600 60 80 100 120 k = 0.62 0.03 k 1200 r v 3 [ m 3 ] 0.75 r e 1000 3 [ m 3 ] 800 400 0.7 600 r v 400 0.65 200 200 Measurement 500 1000 1500 0.6 Theory 3 [ m 3 ] r e 0.55 0 0 500 1000 1500 2000 2500 3000 0 200 400 600 800 1000 1200 1400 1600 1800 n d [cm -3 ] 3 [ m 3 ] r e

Introduction Experimental Description Kamal Kant Chandrakar [14 / 16] the clean cloud regime. signifjcantly decreases in The precipitation timescale Chandrakar et al. JAS 2018 Turbulence Induced Aerosol Efgects Results Summary Efgective Radius Parameterization Aerosol Efgect on Relative Dispersion Autoconversion Timescale Dispersion efgect enhances the 2 nd indirect efgect: 10 15 10 10 ( τ a ≡ L ( dL / dt ) − 1 ) a [h] 10 5 10 0 10 0 10 1 10 2 10 3 n d [cm -3 ]

Introduction Experimental Description Kamal Kant Chandrakar [15 / 16] ( depends on droplet removal ). efgects indirect and the ences Turbulence-induced dispersion efgect infmu- Stochastic theory and experiments suggest: trolled laboratory conditions. dius parameterization is observed under con- A commonly-used, empirical efgective ra- Turbulence Induced Aerosol Efgects Results Summary Summary Summary 1200 k = 0.66 0.01 k = 0.84 0.1 1000 100 3 [ m 3 ] 80 800 r v 60 3 [ m 3 ] 600 60 80 100 120 k = 0.62 0.03 1200 r v r e 3 [ m 3 ] 1000 3 [ m 3 ] 800 400 600 r v 400 200 200 500 1000 1500 3 [ m 3 ] r e 0 0 200 400 600 800 1000 1200 1400 1600 1800 3 [ m 3 ] r e 0.5 Measurement Stochastic Condensation Model 0.4 0.3 d 0.2 s o t − 1/2 ; n d ↑ ⇒ t ↑ ⇒ d ↓ d ∝ σ so 0.1 0 10 2 10 3 n d [cm -3 ] 1 10 15 0.95 0.9 0.85 10 10 0.8 a [h] k 1 st 2 nd 0.75 0.7 10 5 0.65 Measurement 0.6 Theory 10 0 0.55 10 0 10 1 10 2 10 3 0 500 1000 1500 2000 2500 3000 n d [cm -3 ] n d [cm -3 ]

Introduction Experimental Description Results Summary Summary Thank You [16 / 16] Kamal Kant Chandrakar Turbulence Induced Aerosol Efgects