sensitivity of cloud microphysical property retrieval ... · mie linear fit radius [µm] radius...
TRANSCRIPT
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Sensitivity of cloud microphysical property retrieval methods to size distribution
bi-modality: Theoretical considerations and potential implications
MODIS Science Team MeetingMay 7, 2012, Silver Spring, MD
Zhibo Zhang (UMBC), Steven Platnick (NASA GSFC), Andrew Ackerman (NASA GISS), Hyoun-Myoung Cho(UMBC)
Graham Feingold (NOAA ESRL), Robert Pincus (NOAA ESRL), Matthew Lebsock (JPL)
Monday, May 7, 12
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Background
MODIS Operational re(2.1µm)
Monthly Mean Effective Radius of Liquid Water Cloud
CAM5-COSP MODIS simulation
Data courtesy of Jennifer Kay
Substantial difference between observation and GCM.
Monday, May 7, 12
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Background
MODIS Operational re(2.1µm) MODIS Operational re(3.7µm)
Substantial difference between MODIS 2.1µm and 3.7µm.
Monthly Mean Effective Radius of Liquid Water Cloud
Monday, May 7, 12
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Achievements of Year One
• Performed a global assessment of the difference between difference between MODIS re(2.1µm) and re(3.7µm) retrievals (Zhang and Platnick 2011 JGR)
• Developed a MODIS-simulator based on the combination of LES model with bin microphysics and radiative transfer models (both 1-D and 3D)
• Case studies on the effects of cloud horizontal inhomogeneity and drizzle on MODIS effective radius retrievals (Zhang et al. 2012 under revision)
• Collocated MODIS and CloudSat observations of MBL clouds
Monday, May 7, 12
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Probability of Precipitation from collocated CloudSat
Assessment of the difference between MODIS re(2.1µm) and re(3.7µm)
Sub-pixel inhomogeneity indexPPL cloud Broken clouds
Zhang and Platnick 2011 JGR
r e(3
.7µm
)-r e
(2.1µm
)
Regime I:Non-precipitating, PPL clouds
Regime III:Drizzling cloud?
Reg
ime
II:H
ighl
y in
hom
ogen
eous
clo
uds
Whether and How can drizzle affect MODIS Re retrievals?Monday, May 7, 12
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Probability of Precipitation from collocated CloudSat
Assessment of the difference between MODIS re(2.1µm) and re(3.7µm)
Sub-pixel inhomogeneity indexPPL cloud Broken clouds
Zhang and Platnick 2011 JGR
r e(3
.7µm
)-r e
(2.1µm
)
Regime I:Non-precipitating, PPL clouds
Regime III:Drizzling cloud?
Reg
ime
II:H
ighl
y in
hom
ogen
eous
clo
uds
Whether and How can drizzle affect MODIS Re retrievals?Monday, May 7, 12
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Effects of precipitation (Bi-modal PSD)?
Insignificant impacts Significant impacts
Zinner et al. 2011 ACPZhang et al. 2012 JGR
(under review)Painemal et al. 2011 JGR
Nakajima et al. 2010a,bMinnis et al. 2004
Effects of precipitation on passive Re retrieval still remains unclear
LES-based study In-situ measurement Sensitivity Study
Monday, May 7, 12
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Objective: Establish a theoretical understanding of how MODIS Re retrieval response to the drizzle
mode in PSD
Questions:1) Can we derive a “back-of-envelope” formula to estimate
the impact of drizzle mode on MODIS Re retrieval?2) whether and how can bi-modal PSD cause Re retrieval
difference?3) What are the potential implications?
Monday, May 7, 12
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Theoretical Consideration: Simplification of the problem
R(re*,τ *) = R(rc ,rp ,τ c ,τ p )Real retrieval
Simplified retrieval
Assumptions: 1) Single-scattering albedo can be used as surrogate for reflectance for assessing retrieval process (to be justified by RT simulations)2) Cloud is optically thick so that Tau and Re retrievals are independent3) Cloud is homogenous (NO 3-D effect or vertical weighting)
ω c(re*) =ω (rc ,rp ,τ c ,τ p )
Monday, May 7, 12
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Theoretical consideration: Linearization
10 15 20 25 30re [ m]
0.70
0.75
0.80
0.85
0.90
0.95
1.00
PSD
aver
aged
ω
ve=0.06ve=0.10ve=0.16ve=0.20linear fit
30 40 50 60 70 80 90 100re [ m]
0.4
0.5
0.6
0.7
0.8
0.9
1.0
PSD
aver
aged
ω
Mielinear fit
Radius [µm] Radius [µm]
PSD
Ave
rage
d Al
bedo
ω
a) cloud mode b) rain mode
2.1µm 3.7µm 2.1µm 3.7µm
ω c,λ =ω 0c,λ − kc,λre ω r ,λ =ω 0r ,λ − kr ,λre
Gamma distribution Truncated Exponential (Wood et al. 2005 JAS)
Effective radius Effective radius
kc,3.7µm = 0.0061µm−1
kc,2.1µm = 0.0018µm−1
kp,2.1µm = 0.0014µm−1
kc,3.7µm = 0.0021µm−1
1) Albedo decreases linearly with increasing Re 2) Decreasing rate depends on spectral and Re range3) Albedo-Re line is flatter in drizzle region than in cloud region
Monday, May 7, 12
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Theoretical consideration: Formula for estimating effect of drizzle on
MODIS re retrieval
re,λ* = re,c 1+
RWPCWP
kp,λkc,λ
⎛
⎝⎜⎞
⎠⎟−τ pτ c
re,c −ω 0c,λ −ω 0 p,λ
kc,λ
⎛
⎝⎜⎞
⎠⎟
re,λ*
Retrieved effective radius (spectral dependent)
re,c Effective radius of cloud modeStrength of drizzle (in upper part (Tau
-
RT simulations
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
Cloud mode: re = 15µm τ ≈ 20 CWP = 300g /m2
Rai
n m
ode
r e [µ
m]
Rai
n m
ode
r e [µ
m]
Rai
n m
ode
r e [µ
m]
Rai
n m
ode
r e [µ
m]
RWP/CWP RWP/CWP
RWP/CWP RWP/CWP
re*(2.1µm) re
*(3.7µm)
DISORTRef
TheoAlbedo
26
24
22
20
18
16
14
Monday, May 7, 12
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Effect of Bi-Modality on Polarization-based Re retrieval
144 146 148 150 152 154 156Scattering Angle [o]
-0.05
0.00
0.05
0.10
-P12
10 20 30 40 50Effective Radius [µm]
0.02
0.04
0.06
0.08
0.10
Effe
ctiv
e Va
rianc
e
Cloud mode Re=15µmCWP=300g/m2
Rain mode Re=80µm RWP
= 300g/m2
Combined
Retrieval cost function
Polarization-based retrieval ~ 15.5µm
Polarization insensitive to drizzle mode
Monday, May 7, 12
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Effect of Bi-Modality on Polarization-based Re retrieval
144 146 148 150 152 154 156Scattering Angle [o]
-0.05
0.00
0.05
0.10
-P12
10 20 30 40 50Effective Radius [µm]
0.02
0.04
0.06
0.08
0.10
Effe
ctiv
e Va
rianc
e
Cloud mode Re=15µmCWP=300g/m2
Rain mode Re=80µm RWP
= 300g/m2
Combined
Retrieval cost function
Polarization-based retrieval ~ 15.5µm
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
0.2 0.4 0.6 0.8 1.0RLWC/CLWC
60
80
100
120
140
160
180200
Rai
n m
ode r e
[m
]
MODIS 2.1µm retrieval ~22µm Polarization insensitive to drizzle mode
Monday, May 7, 12
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Potential Implications: GCM/MMF-Satellite comparison
Cloud mode re Cloud + Precip. re
MODIS re
Preliminary results:inclusion of precip. mode leads to better agreement between a
MMF simulation and MODIS
MMF data courtesy of Minghuai Wang
Monday, May 7, 12
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Summary
• Observations show correlation between precipitation and MODIS cloud effective radius retrieval “anomaly” (drizzle effects?)
• A simple formula is derived to predict the impact of PSD bi-modality (i.e., drizzle) on MODIS cloud effective radius retrieval
• More investigations are underway
Monday, May 7, 12
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Future Work• LES simulation of heavily drizzling clouds- LES-MODIS simulation- LES-polarimeter simulation• Regime by regime study of cloud microphysics
using collocated MODIS-CloudSat data
• Investigation of the implications for GCM-satellite comparison
• Investigation of air-borne observations?
Monday, May 7, 12
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Thank You!
• Questions?
Monday, May 7, 12