Avery, Melody

Beaumont, Ken

Cai, Xia

Detweiler, Paula

Garnier, Anne

Getzewich, Brian

Holz, Bob

Hunt, Bill

Kar, Jay

Lambeth, Jim

Lee, Kam-Pui

Liu, Zhaoyan

Lucker, Pat

Magill, Brian

Murray, Tim

Omar, Ali

Pelon, Jacques

Phillips, Josh

Rodier, Sharon

Ryan, Rob

Tackett, Jason

Toth, Travis

Trepte, Chip

Vaughan, Mark

Winker, Dave

Young, Stuart

Zeng, Shan

NASA Technical Reports Server

CALIPSO
Lidar Science Working Group
Mark Vaughan (1)March 1-3, 2016
CALIPSO-CLOUDSAT 2016 SCIENCE TEAM MEETING
Mark Vaughan, Anne Garnier, Jason Tackett, Stuart Young, Jay Kar, Melody Avery, Ali Omar, 
Zhaoyan Liu, Brian Getzewich, Kam-Pui Lee, Bill Hunt, Dave Winker, Jacques Pelon, Chip Trepte, 
Bob Holz, Travis Toth, Pat Lucker, Sharon Rodier, Jim Lambeth, Brian Magill, Rob Ryan, 
Josh Phillips, Shan Zeng, Xia Cai, Tim Murray, Ken Beaumont, Paula Detweiler
The Top 10 Improvements to the Version 4 
Level 2 CALIPSO Lidar Data Products
https://ntrs.nasa.gov/search.jsp?R=20160007809 2019-08-29T17:49:33+00:00Z
CALIPSO
Lidar Science Working Group
Mark Vaughan (2)March 1-3, 2016
THE TOP 10 LIST
1. CALIBRATION
2. SURFACE DETECTION
3. CLOUD-AEROSOL DISCRIMINATION
4. STRATOSPHERIC AEROSOL
CLASSIFICATION
5. TROPOSPHERIC AEROSOL
CLASSIFICATION
6. ICE-WATER CONTENT AND ICE-
WATER PHASE
7. CIRRUS MULTIPLE SCATTERING
8. EXTINCTION RETRIEVALS
9. A-TRAIN SYNERGIES
10.NEW DATA PRODUCT(S)
CALIPSO
Lidar Science Working Group
Mark Vaughan (3)March 1-3, 2016
V4 CALIBRATION VALIDATION USING LaRC HSRL
POSTER: GETZEWICH ET AL., “UPDATES TO THE VERSION 4 CALIOP LEVEL 1 ALGORITHM”
2006 – 2014
118 Flights
Daytime Bias Nighttime Bias
Version 3 Version 4 Version 3 Version 4
Mean (HSRL-CALIOP) 2.0% -0.2% 2.2% 0.2%
Standard Deviation 3.5% 3.9% 2.2% 2.4%
CALIPSO 2009-02-07LaRC HSRL 2009-02-07
CALIPSO
Lidar Science Working Group
Mark Vaughan (4)March 1-3, 2016
SURFACE DETECTION
POSTER: VAUGHAN ET AL., “IMPROVEMENTS TO THE CALIOP SURFACE DETECTION ALGORITHM”
Opaque Water Clouds
S = 18.9, h = 0.42
2H O
1
0.063
2 S
  
h
Opaque Ice Clouds
S = 29.5, h = 0.55
ice
1
0.031
2 S
  
h
“clear air”
clear 0.011 
DEM Errors
(GTOPO30)
CALIPSO
Lidar Science Working Group
Mark Vaughan (5)March 1-3, 2016
SURFACE DETECTION
POSTER: VAUGHAN ET AL., “IMPROVEMENTS TO THE CALIOP SURFACE DETECTION ALGORITHM”
V3 Failure V3 Success
V4 Failure 0.3481 0.0047
V4 Success 0.1503 0.4969
0.50160.6472
CALIPSO
Lidar Science Working Group
Mark Vaughan (6)March 1-3, 2016
CLOUD-AEROSOL DISCRIMINATION
POSTER: KAR ET AL., “CLOUD AEROSOL DISCRIMINATION (CAD) UPDATES IN CALIOP VERSION 4”
532 nm Attenuated Backscatter
2008-03-15
532 nm Volume Depolarization Ratio
2008-03-15
Attenuated Backscatter
Color Ratio (1064/532)
Version 3 Vertical Feature MaskVersion 3 Vertical Feature Mask Version 4 Vertical Feature Mask
CALIPSO
Lidar Science Working Group
Mark Vaughan (7)March 1-3, 2016
CLOUD-AEROSOL DISCRIMINATION
POSTER: KAR ET AL., “CLOUD AEROSOL DISCRIMINATION (CAD) UPDATES IN CALIOP VERSION 4”
CAD AT SINGLE SHOT RESOLUTION
Version 3.01 Production Version 4 Prototype
CALIPSO
Lidar Science Working Group
Mark Vaughan (8)March 1-3, 2016
STRATOSPHERIC AEROSOL CLASSIFICATION
POSTER: TACKETT ET AL., “NEW STRATOSPHERIC AEROSOL SUBTYPES IN CALIOP VERSION 4”
Volcanic Plume from 
Puyehue-Cordon
Version 3 CAD
stratospheric layers
Version 4 CAD
clouds and aerosol
Version 4
CAD Everywhere
-
CALIPSO
Lidar Science Working Group
Mark Vaughan (9)March 1-3, 2016
TROPOSPHERIC AEROSOL CLASSIFICATION
POSTER: OMAR ET AL., “AEROSOL SUBTYPING AND LIDAR RATIO SELECTION FOR CALIOP VERSION 4”
Version 3 Version 4
Marine 20 sr 23 sr
Dusty Marine N/A 37 sr
Pure Dust 40 sr 44 sr
Polluted Dust 55 sr 55 sr
Polluted Continental 70 sr 70 sr
Clean Continental 35 sr 53 sr
Biomass Burning 70 sr 70 sr
CALIPSO
Lidar Science Working Group
Mark Vaughan (10)March 1-3, 2016
ICE-WATER CONTENT AND ICE-WATER PHASE
POSTER: AVERY ET AL., “CHANGES TO CALIOP CLOUD ICE AND WATER PHASE DISCRIMINATION”
Revised parameterization agrees better with retrievals 
from in-situ cloud probe measurements of very cold 
(< -80° C) ice clouds during CR-AVE
CALIPSO V3
Heymsfield et al., 2005
(http://dx.doi.org/10.1029/2005GL022742)
 IWC ba  
SPEC 2DS IWC (mg/m3)
H
e
y
m
sf
ie
ld
e
t 
a
l.,
 2
0
0
5
 I
W
C
 (
m
g
/m
3
)
 4
      
   
e
e
D T T exp T T
IWC ,T D Tc
  
  
SPE  2 S I  ( g/ 3)
H
e
y
m
sf
ie
ld
e
t 
a
l.,
 2
0
1
4
 I
W
C
 (
m
g
/m
3
)
14
(http:/ dx.doi.org/10.1 75/JAMC-D-13-087.1)
Ice Water Content
HOI
ROI
H2O
Ice Water Phase
Hu et al., JTECH 2009
Version 34
CALIPSO
Lidar Science Working Group
Mark Vaughan (11)March 1-3, 2016
CIRRUS MULTIPLE SCATTERING
POSTER: GARNIER ET AL., “CIRRUS LIDAR RATIOS AND MULTIPLE SCATTERING FACTORS IN CALIOP VERSION 4”
Garnier et al., AMT 2015
CALIPSO
Lidar Science Working Group
Mark Vaughan (12)March 1-3, 2016
CIRRUS LIDAR RATIO RETRIEVALS
POSTER: GARNIER ET AL., “CIRRUS LIDAR RATIOS AND MULTIPLE SCATTERING FACTORS IN CALIOP VERSION 4”
CALIPSO
Lidar Science Working Group
Mark Vaughan (13)March 1-3, 2016
CIRRUS LIDAR RATIO RETRIEVALS
POSTER: GARNIER ET AL., “CIRRUS LIDAR RATIOS AND MULTIPLE SCATTERING FACTORS IN CALIOP VERSION 4”
V4 2008 Night
cloud type
constrained 
solutions
total 
samples
constrained 
fraction
unknown 60729 2050089 2.96%
ROI 1795117 7642958 23.49%
water 72724 6243186 1.16%
HOI 10915 725420 1.50%
V4 2008 Day
cloud type
constrained 
solutions
total 
samples
constrained 
fraction
unknown 60063 2160802 2.78%
ROI 1418617 7808434 18.17%
water 153502 6989054 2.20%
HOI 15796 494730 3.19%
V3 2008 Night
cloud type
constrained 
solutions
total 
samples
constrained 
fraction
unknown 672 1265336 0.05%
ROI 659449 7640625 8.63%
water 31854 6155917 0.52%
HOI 51455 1460019 3.52%
V3 2008 Day
cloud type
constrained 
solutions
total 
samples
constrained 
fraction
unknown 52 1422951 0.00%
ROI 43921 7953237 0.55%
water 2293 7145668 0.03%
HOI 5053 1161500 0.44%
CALIPSO
Lidar Science Working Group
Mark Vaughan (14)March 1-3, 2016
EXTINCTION RETRIEVALS
POSTER: YOUNG ET AL., “V4 ALGORITHMS FOR RETRIEVING OPTICAL PROPERTIES OF OPAQUE ICE CLOUDS”
Version 3 V4 Test08
min -0.40 -0.19
max 10.41 9.77
median 0.29 0.39
mean 0.71 1.47
stdev 0.95 2.04
samples 7616446 7558033
Lidar ratios now RETRIEVED for opaque 
layers; revised retrieval scheme eliminates 
artifacts in V4 optical depth distribution Constrained retrievals 23.5%
Opaque retrievals 17.9%
Unconstrained solutions 58.6%
CALIPSO
Lidar Science Working Group
Mark Vaughan (15)March 1-3, 2016
CIRRUS LIDAR RATIO RETRIEVALS
POSTER: YOUNG ET AL., “V4 ALGORITHMS FOR RETRIEVING OPTICAL PROPERTIES OF OPAQUE ICE CLOUDS”
CALIPSO
Lidar Science Working Group
Mark Vaughan (16)March 1-3, 2016
NEW DATA PRODUCTS
POSTER: RYAN ET AL., “CALIPSO'S NEW 5KM MERGED LAYER PRODUCT FOR V4 LEVEL 2 DATA PRODUCTS”
 Expanded reporting of surface characteristics; e.g.
o Color ratio
o Depolarization ratio
o Integrated backscatter
 1/3-km layer detection results in 5-km layer 
products
 Lidar ratio uncertainties in 5-km layer products
 Layer centroid temperatures in all layer products
 Layer attenuated scattering ratio statistics in all 
layer products
 5-km merged cloud and aerosol layer product
Aerosol Layer Product
Cloud Layer Product
Merged Layer Product
CALIPSO
Lidar Science Working Group
Mark Vaughan (17)March 1-3, 2016
A-TRAIN SYNERGIES
Figure 10. The CALIOP unconstrained IOT but processed using a modified lidar ratio of 32 is
compared to the new single habit ice scattering LUT used in the updated MODIS C6 IOT retrievals
in the left (a) panel. Notice the improved bias relative to the MODIS C5 and V3 CALIOP retrievals
presented in Fig. 1. The radiative closure analysis using the updated retrievals is presented in the
right (b) panel. The modifications have greatly improved agreement with the measured MODIS 11
μm channel compared to MODIS C5 and the current V3 CALIOP retrievals presented in Fig. 2.
Holz et al., ACPD 2015: 
Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals
CALIOP Cloud Optical Depth Calculated – Measured @ 11 mm (K)
M
O
D
IS
 C
lo
u
d
 O
p
ti
ca
l 
D
e
p
th
N
o
rm
a
liz
e
d
 F
re
q
u
e
n
cy
CALIPSO
Lidar Science Working Group
Mark Vaughan (18)March 1-3, 2016
IN CASE THERE ARE QUESTIONS…
CALIPSO
Lidar Science Working Group
Mark Vaughan (19)March 1-3, 2016
MATHEMATICS OF TOTALLY ATTENUATING LAYERS
VERSION 3
1
2 S
 
h
Platt’s Equation:  
1
ln 1 2 S
2
 
    h  
h 
21 T
2 S
h
 
h
for totally attenuating layers, T
2h
= 0, so

to solve, must choose S so that (1 – 2hS ’) is positive
1
S
2

h
and thus
when the CALIPSO extinction algorithm encounters a totally attenuating layer for
which the estimated value of S is too large, it successively reduces the value of S
in increments of 5% until a solution is achieved. so…
for cirrus clouds, h = 0.6, so that  
1
ln 0.05
2 0.6
 
  
 
2.496
 
1 1 1
ln 1 2 0.95 ln 0.05
2 2 2
       
    h           h h h       
First presented at the CALIPSO Science Team Meeting, March 11-13 2008


The Top 10 Improvements to the Version 4 Level 2 CALIPSO Lidar Data Products

The Top 10 Improvements to the Version 4 Level 2 CALIPSO Lidar Data Products

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