Data Release Version: 1.10
Data Release Date: December 8, 2006
Document Revision Date: December 8, 2006
Data Quality Statement
relating to the Lidar 532-nm Detectors Transient Response
(Version 1.10, December 8, 2006).
Introduction
This document provides a high-level quality assessment of the lidar 532 nm
detector response. As such, it represents the minimum information needed by
scientists and researchers for appropriate and successful use of the lidar
Level 1 and 2 data products. We strongly suggest that all authors, researchers,
and reviewers of research papers review this document for the latest status
before publishing any scientific papers using lidar data products.
The purpose of these data quality summaries is to inform users of the
accuracy of CALIOP data products as determined by the CALIPSO Science Team and
Lidar Science Working Group (LSWG). This document is intended to briefly
summarize key validation results; provide cautions in those areas where users
might easily misinterpret the data; supply links to further information about
the data products and the algorithms used to generate them; and offer
information about planned algorithm revisions and data improvements.
Additional Documentation and References
Page Topics
532 nm detector non-ideal transient recovery
The 532 nm detectors (parallel and perpendicular) photo multiplier tubes (PMTs)
both exhibit a non-ideal recovery of the lidar signal after a 'strong'
backscattering target has been observed. Examples of strong targets are
water clouds and surface returns.
PMT afterpulsing (ionization of residual gas) is the likely cause of the
non-ideal transient recovery. This effect is well documented in the literature
for photon counting applications. The time scale of the effect is dependent on
PMT voltage, gas species, and PMT internal geometry. It is also possible that
the non-ideal transient recovery is what is commonly called signal induced
noise. It is unlikely that the lidar receiver electronics are the source of the
problem because the 1064nm channel uses a similar design and is performing
well.
Example of the non-ideal transient recovery in browse images
 |
 |
Figure 1: Browse images of 532 nm (top) and 1064 nm (bottom) total attenuated
backscatter. The 532 nm non-ideal transient recovery is seen in the 532 nm
image as a gradual transition of colors from high attenuated backscatter values
to lower ones for strong backscatter targets (i.e. stratus deck on the left,
and the Antarctic surface return on the right. Compare these features to the
1064 nm image, where the detector response is normal, and these features appear
as an almost solid band of white.
Note that the cirrus cloud structure (center right) looks about the same in
both the 532 nm and 1064 nm images. This is because there is little to no
contribution from the transient response artifact in these weak scattering
features.
|
Examples of the transient response in profile data
 |
Figure 2: This shows the detector response from laboratory measurements.
The input was a light pulse of constant amplitude for 1 µs (red), and 20
µs (brown). The amplitude corresponds roughly to what would be measured
with the CALIOP instrument on-orbit from an optically dense water cloud. Note
that the duration and amplitude similar to the 20 µs pulse would never be
measured on-orbit from a real atmospheric features due to signal attenuation
through the feature. For ideal detector response the signal should return to
the baseline value (~3x10-5) at time = 0. |
 |
Figure 3: A comparison of the
Langely Airborne HSRL and
CALIPSO coincident measurements of a water cloud from 6/14/2006. Time from the
coincidence is approximately 30 minutes. The recovery artifact is the decaying
portion of lidar signal that extends from ~3100 m to ~1000m. When comparing
these data, keep in mind that the water cloud top has changed between the
observation times. Also, the CALIPSO and HSRL viewing geometries are
considerably different, and there is a contribution from multiple scattering in
the CALIPSO observation. |
 |
 |
Figures 4a and 4b: Comparisons of CALIPSO and
CPL for a cirrus cloud
measurement (left) and with the
Langely Airborne HSRL for an
aerosol layer (right). Both these comparisons demonstrate that the non-ideal
transient recovery from weaker scattering layers is negligible. For the
CPL-CALIPSO observations the small differences can be attributed to spatial and
temporal mismatching and differences in the viewing geometry of the two
instruments. Multiple scattering contributes to some of the differences
observed between the CALIPSO and CPL measurements. |
Analysis and correction techniques
Lab data was collected on flight hardware in 2002 to characterize the 532 nm
parallel and perpendicular channel detectors response. The data set consists of
87 different tests using square wave 'clouds' of varying amplitude and duration.
The surface return can also be used to characterize the non-ideal recovery if
the peak signal is not saturating the low-gain digitizer, and the is sufficient
time between the surface and the last range bin.
Analysis has started on this data set to characterize the non-ideal
transient recovery. So far, the analysis has demonstrated that the non-ideal
recovery behaves like an afterpulse signal. The observed response is a function
of both the signal amplitude and duration.
A Richardson-Lucy
deconvolution algorithm has been applied to the lab data to retrieve the
instrument response function. This was done by assuming that the true signal
was a square wave with the duration as the detector illumination source. The
retrieved response functions from the 532 nm parallel channel detector for
various lighting conditions (different pulse amplitudes and widths) are shown
in figure 5.
 |
Figure 5: Retrieved response function from lab data compared to the surface
return response function measured from a lake at altitude of ~4 km. |
The retrieved response function or a suitable surface return can be used to
remove the non-ideal transient recovery from the lidar Level 1 data using a
Richardson-Lucy type deconvolution algorithm. Care needs to be taken in the
application of such an algorithm because of the non-uniform range binning of
the profile data.
Summary
Further characterization of the non-ideal transient recovery is underway and
techniques are being investigated to remove this artifact from the 532 nm lidar
data.
In the meantime, users of Lidar Level 1B profile data should use extreme
caution when doing investigations of strong backscattering targets, like
optically dense water clouds. Since the non-ideal response of the 532 nm
parallel and perpendicular channels are slightly different, some artifacts in
the calculated depolarization ratio may be observed below strong backscattering
targets.
There is no geophysically meaningful information in the subsurface signal
return. Subsurface can be assumed to be 1 or 2 bins beyond the maximum value
obtained in the surface spike.
Users of Lidar Level 2 layer products can expect that the bases of strong
scattering targets (i.e. optically dense water clouds) will be lower than
expected. In most of these cases however, the observed layer is opaque to the
lidar and the measurement of the true cloud base is not possible.