Cloud Remote Sensing during VOCALS- REx: Selected U.S. Efforts

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1 Cloud Remote Sensing during VOCALS- REx: Selected U.S. Efforts Paquita Zuidema, U of Miami Qabs ~ 4xI{(m 2-1)/(m 2 +2)} Qscat ~ 8/3 x 4 (m 2-1)/(m 2 +2) 2 x=2 r/ VOCALS Educational Talk 10/31/08

2 1. Satellite Remote Sensing 2. C130 (& Ron Brown) microwave remote sensing

3 the GOES operational retrievals of droplet size daytime: f(ch1&2);f(0.65,3.9 micron) nighttime: ch4-ch2; micron BTD

4 absorption by liquid water Jackson textbook

5

6 the GOES channels ,5

7 daytime re retrieval channels 1 & 2 (~0.6 & 3.9 micron) = Qscat/(Qscat +Qabs) Qscat ~ 8/3 x 4 (m 2-1)/(m 2 +2) 2 varies w/ droplet radius in near-ir during daytime

8 Nakajima&King, 1990

9 retrievals typically depend on the plane-parallel assumption: clouds are pancakes, radiation completely determined by the cloud properties within a satellite s pixel highly computationally-efficient rf1

10 daytime particle size retrieval corroborated on California stratus

11 deviations from plane-parallel: shadowing/brightening from first-order scattering noticeable at dawn/dusk x=10 x=3 x=1 x=0.1

12 x=3 x=10 photon leakage: multiple scattering phenom rf1

13 for adiabatic clouds Re Neff -1/3 h 1/3 for aerosol indirect effect studies, meteorology (aka LWC) assumed constant

14 recast re(h), as Neff, H (cloud depth) assuming adiabaticity Brenguier, Bennartz... mean CDNC, October [cm 3 ] 1/2 /re(h) 5/2 R.Wood 250 5S S S 50 35S 90W 80W 70W 0 Terra-day David Painemal

15 recast re(h), as Neff, H (cloud depth) assuming adiabaticity Brenguier, Bennartz... H = [10 w / eff re(h) ] 1/2 mean CDNC, October [cm 3 ] R.Wood mean cloud depth, October [m] S 200 5S S S S 25S S 90W 80W 70W 0 35S 90W 80W 70W 180 Terra-day David Painemal

16 Oct.-mean cloud top heights (MODIS, 11 µm) mean cloud depth, October [m] 5S S S 240 Zuidema et al., under review 35S Terra-day 90W 80W 70W

17 the GOES operational retrievals of droplet size nighttime: ch4-ch2; micron BTD daytime: f(ch1&2); f(0.65,3.9 micron)

18 nighttime re retrieval channels 2 & 4 (3.9 & 10.7 micron) = Qscat/(Qscat +Qabs) Qabs ~ 4xI{(m 2-1)/(m 2 +2)}

19 - [ channel 4 - channel 2 ] (-[11-4]) channel 4 (~11 micron) Perez et al., 2000

20 1. Satellite Remote Sensing 2. C130 (& Ron Brown) microwave remote sensing

21 GVR (G-band Vapor Radiometer) prototype instruments intended for dry,cold (Arctic) conditions, first use in stratus C-130 Ron Brown, MP183 + standard 2-channel upward-looking, small

22 Tb clear-sky spectra of 10th and 90th percentile 300 VOCALS-REx domain soundings 250 H2O T b (K) oxygen Oct. 18, rf H2O wvp (mm) 2.33 (90%) 1.30 (10%) 50 /Users/pz/vocals/plot_gvr.pro 29Oct08 19:25: hour (utc) Frequency (GHz) 2channel soundings from:

23 liquid water emission ~ f 1.7 Qabs ~ 4xI{(m 2-1)/(m 2 +2)} total absorption = [ ]LWP UV Visible Near IR Particle Radius Thermal IR Microwave 1 cm 1 mm 100 µm 10 µm 1 µm 0.1 µm 10 nm 1 nm Geometric Optics x=2000 Mie Scattering x=0.2 Rayleigh Scattering x=0.002 Negligible Scattering Hail Raindrops Drizzle Cloud droplets } Dust, Smoke, Haze Aitken Nuclei Air Molecules Qscat ~ 8/3 x 4 (m 2-1)/(m 2 +2) 2 x=2 r/ ; 183GHz = 1.6 mm r~< 50,100 µm okay 0.1 µm 1 µm 10 µm 100 µm 1 mm 1 cm 10 cm Wavelength

24 Issues: How well are the brightness temperatures known? How well can liquid water paths be related to the Tb?

25 Maria Cadeddu calculations based on EPIC, PACS03 soundings suggest: 10 g m -2 clear-sky error, 4 g m -2 bias - but include f= 23.8 GHz 1K instrument 200 ms => 1 g m -2 20s (Barrow)

26 Tb from REx-domain soundings curve-fit calibrated Tb (clear-sky) above-cloud Tb PWVabove-cloud =f(tb) + aircraft-derived WVP best-fit LWP to sub-cloud Tb using WVP estimate physical retrieval? neural net? 5% WVP ~ 5% LWP

27 Starter case: October 18, RF 2 little (no) drizzle, adiabatic cloud structure very low above-cloud RH

28 Tb Oct. 18, rf above-cloud 200 legs /Users/pz/vocals/plot_gvr.pro 29Oct08 19:25: hour (utc) feet

29 sounding-derived above-cloud Tb = f (WVP) all cruise soundings ft T b (K) WVP (mm)

30 best-fit line all cruise soundings T b (K) WVP (mm)

31 RF2-derived above-cloud WVPs 300 RF2, above cloud T b (K) WVP (mm)

32 Wavelength [µm] K Nauru (Tropical Western Pacific) 11/15/98 Radiance [mw / m 2 sr cm -1 ] Barrow, Alaska 3/10/ K Wavenumber [cm -1 ] looking up

33 1e+09 Scattering Phase Function 1e+08 x=10,000 1e+07 1e+06 x=3,000 x=1,000 Thanks! x= p(θ) 1000 x= x=30 10 x=10 1 x=3 x= x=0.3 x= Θ [deg.]

34 Extra slides

35 1e+09 Scattering Phase Function Glory Fogbow x=30 Corona 1e+08 Forward Diffraction Peak x=10,000 Secondary Rainbow 1e+07 Primary Rainbow x=100 x=3,000 1e+06 x=1, x= x=10,000 p(θ) 1000 x=100 x= x=30 x=10 10 x=3 x=3 1 x=1 x=1 0.1 x= x=0.1 x= Θ [deg.]

36 averaging,removing edge pixels, larger spatial scales, optimal sun/ viewing geometry,gets rid of shadow/brightening effects, neglect of other processes inc. above-cloud absorbing layer conspires to reduce retrieved optical depth,increase effective radius

37

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