After launch we discovered that the CALIOP daytime measurements were subject to thermally induced beamdrift,and this caused the calibration to vary by as much as 30% during the course of a single daytime orbit segment. Using an algorithm developed by Powell et al.(2010), empirically derived correction factors are now computed in near realtime as a function of orbit elapsed time, and these are used to compensate for the beam wandering effects

Avery, Melody

Getzewich, Brian

Howell, Joe

Hu, Yong

Hunt, Bill

Kuehn, Ralph

Lamberth, Jim

Lee, Kam-Pui

Liu, Zhaoyan

Lucker, Pat

Omar, Ali

Powell, Kathy

Tackett, Jason

Trepte, Chip

Vaughan, Mark

Winker, Dave

Young, Stuart

NASA Technical Reports Server

CALIOP VERSION 3 DATA PRODUCTS: A COMPARISON TO VERSION 2
DAYTIME CALIBRATION
The Problem:
After launch we discovered that the
CALIOP daytime measurements
were subject to thermally induced
beam drift, and this caused the
calibration to vary by as much as
30% during the course of a single
daytime orbit segment.
The Solution:
Using an algorithm developed by
Powell et al. (2010), empirically
derived correction factors are now
computed in near real time as a
function of orbit elapsed time, and
these are used to compensate for
the beam wandering effects
The black line shows the mean
attenuated scattering ratio
measured during nighttime in
clear air regions between 8-km
and 12-km. Assuming that the
diurnal changes in aerosol
loading in this region are
insignificant, the weekly mean
scattering ratio during daytime
should be essentially identical
to the weekly mean scattering
ratio measured at night. As
seen in the figure to the left,
the correction coefficients
computed for the version 3
processing perform substan-
tially better than those used for
version 2.
Mark Vaughan a, Ali Omar a, Bill Hunt b, Brian Getzewich b, Jason Tackett b, Kathy Powell a, 
Melody Avery a, Ralph Kuehn b, Stuart Young c, Yong Hu a, Zhaoyan Liu d, Chip Trepte a, 
Dave Winker a, Pat Lucker b, Kam-Pui Lee a, Joe Howell b, and Jim Lambeth b
AEROSOL BASE EXTENSION IN THE PBL
CALIOP DAYTIME DATA
4 AUGUST 2007
Version 2.01
Version 3.01
SOLUTION: If the mean attenuated backscatter at 532 nm is greater 
than zero in the region between the base of the lowest aerosol layer 
and the top of the lidar-detected surface, EXTEND the aerosol base 
altitude down to the range bin immediately above the surface
PROBLEM: Aerosol attenuation causes the layer detection algorithm 
to prematurely terminate, resulting in bases altitudes that are 
separated from the surface by as much as 2-km.
Comparisons to HSRL measurements made
~30 minutes earlier: Aerosol optical depth
retrievals improve markedly when layer boundaries are
extended
Optical Depths
Lidar Ratio
A new procedure has been incorporated into version 3 of the
CALIPSO level 2 analyses. As was done in all previous versions,
all features within a scene are assigned an initial classification by
the cloud-aerosol discrimination (CAD) algorithm and either the
aerosol sub-typing algorithm or the cloud phase algorithm. In
the version 2 processing, the next and final step in the analysis
was to launch the extinction and optical properties retrievals. For
version 3 processing, an intermediate step is inserted: the initial
classification is now followed by an assessment of the lowest layer
within each column. If the lowest layer is initially classified as an
aerosol and
a) the layer is not opaque (i.e., the surface was detected below);
b) the initial layer base is within some minimum distance of the
surface (2.5-km for the version 3 processing); and
c) the 532 nm integrated attenuated backscatter in the region
between the initial base altitude and the top of the surface
echo is positive
then the estimate of the layer base altitude is revised downward
to a point three range bins (~90 m) above the top of the surface
spike.
(a) NASA Langley, Hampton VA USA; (b) SSAI, Hampton VA USA; (c) CSIRO, Aspendale, VIC Au; (d) NIA, Hampton VA USA
CLOUD-AEROSOL DISCRIMINATION
In version 2, the CALIOP cloud-aerosol
discrimination (CAD) algorithm used
three attributes to distinguish between
feature types: the mean attenuated
backscatter at 532 nm, the integrated
attenuated back-scatter color ratio
(1064/532), and mid-layer altitude. The
version 3 CAD algorithm adds two
addition attributes: latitude and layer
integrated volume depolarization ratio.
When these new 5 dimensional (5D)
probability density functions (PDFs) are
used, the resulting separation between
clouds and aerosols is much more
complete than when 3D PDFs are used.
In particular, as demonstrated in the
plots to the right, the 5D PDFs provide a
much improved ability to distinguish very
dense aerosol layers from clouds.
PDF Improvements
Other CAD Changes
While the operation of the
CAD algorithm changed
somewhat (i.e., the original
3D PDFs were replaced with
5D PDFs), in the planetary
boundary layer (PBL) a much
larger change in the fraction
of layers identified as
aerosols occurred as a result
of the repairs made to the
cloud-clearing codes. This
change is illustrated in the
plots to the right, which
show globally compiled
vertical profiles of cloud and
aerosol fraction for both
daytime and nighttime and
both version 2 and version 3.
These profiles are derived
using all data acquired
during the fall of 2009.
September, October, November 2009
DAYTIME
At any altitude, the sum of the solid lines 
(V3.01 data) equals one and the sum of the 
dashed lines (V2.01 data) equals one.
September, October, November 2009
NIGHTTIME
At any altitude, the sum of the solid lines 
(V3.01 data) equals one and the sum of the 
dashed lines (V2.01 data) equals one.
Very Dense Desert Dust
2007-01-01, ~00:49 UTC
V2.01, 3D CAD
misclassification @ 5-km
V3.01, 5D CAD
correct classification @ 5-km
PDF Layer Classification Results
The “continuum” seen here in the 3D PDF is an artifact 
introduced by the cloud-clearing bug described above
CLOUD CLEARING
The MODIS images above are overlaid with CALIOP cloud identifications (a) reported in the Version 2 vertical feature mask
product (i.e., detected at all resolutions), and (b) reported in the Version 2 1/3-km layer product (i.e., detected at single
shot resolution only). CALIOP’s 1/3-km detection results are entirely consistent with the MODIS image. However, layers
detected at coarser resolutions (1-km and above) are frequently misclassified as cloud. This situation is illustrated in the
right two panels below, which show the layer classifications and layer detection resolutions reported in the CALIPSO version
2.01 data products. Compared with the CALIPSO Level 1 image (shown above between the MODIS images) the layer
detection appears reasonably accurate; however, the layer classification is rife with errors. This state of affairs was
subsequently determined to be strictly a coding error, and not related to algorithm design. The errors were traced to the
cloud-clearing module, which, after removing high resolution clouds, failed to properly re-average all of the relevant
quantities required by the cloud-aerosol discrimination routines. The results reported in the Version 3.01 data for this same
scene are shown below in the two panels on the right.
VERTICAL FEATURE MASK, VERSION 2.01
surface
aerosolcloud
AVERAGING REQUIRED FOR DETECTION, V2.01
single shot (1/3-km) layer detection
AVERAGING REQUIRED FOR DETECTION, V3.01
single shot (1/3-km) layer detection
VERTICAL FEATURE MASK, VERSION 3.01
cloud
aerosol
surface
(a) CALIOP clouds detected at all resolutions
MODIS, 2007-03-09
(b) CALIOP clouds detected at 1/3-km resolution
MODIS, 2007-03-09CALIOP Level 1 532 nm Attenuated Backscatter
Many thanks to Chris Yost and members of the CERES team for the high quality bug report 
that led us to identify the source of this deep-seeded rascal.
NEW PROFILE PRODUCT ARCHITECTURE
532 nm Attenuated Backscatter Coefficients
Version 2.01: Aerosol Profile Product Resolution
40 km Horizontal, 120 m Vertical
Version 3.01: Aerosol Profile Product Resolution
5 km Horizontal, 60 m Vertical
New Parameters Enhanced QA/QC Information
• Particulate Depolarization Ratios
• Cloud Ice-Water Content
• Column Optical Depths for Clouds and Aerosols
• Uncertainties for all Optical Properties
• Extinction QC Flags
• Classification Confidence (CAD Scores)
• “Atmospheric Volume Description”
• Initial Lidar Ratios
Cirrus (ROI)
Cirrus (HOI)
Water Cloud
Unknown
N/A
Ice-Water Phase: 5 August 2007
Ice Water Content
1
0
C
IWC C
1000
σ =  
 
C0 = 119 g/m3 C1 = 1.22
σ = extinction coefficient (km-1)
http://www-calipso.larc.nasa.gov/
LAYER DETECTION
The figure to the left counts the number of range bins in
which layers were detected in the CALIOP Version 3 data as
a function of altitude for all data acquired during the fall
months (September, October, November) of 2009. Layer
detection counts are shown separately for daytime and
nighttime data acquisition. The figure on the right shows
the Version 3 daytime and nighttime layer detection
frequencies as fractions of the Version 2 quantities. By
examining these two figures, the following conclusions can
be drawn:
1) Nighttime layer detection is largely unchanged from
Version 2 to Version 3. Where large fractional changes
are seen (right hand plot), the layer detection counts
are especially low.
2) Daytime layer detection increases by a factor of ~50%
above about 16-km, and by 5% to 8% below 4-km.
Both changes arise from the same source: the changes
made to the daytime calibration procedures, which
increase the magnitude of the attenuated scattering
ratio profiles that are used by the layer detection
algorithms.
The uniform distribution of layers in the 20-30 km region suggests 
that these daytime “detections” are largely false positives.
The vertical distribution of layers
is similar day and night. However,
because the solar background
signal present during daytime
measurements greatly reduces
the SNR, the daytime detection
totals are uniformly lower.
https://ntrs.nasa.gov/search.jsp?R=20100037236 2019-08-30T12:19:52+00:00Z


CALIOP Version 3 Data Products: A Comparison to Version 2

CALIOP Version 3 Data Products: A Comparison to Version 2

Abstract

Similar works

Full text

Available Versions

NASA Technical Reports Server