CALIPSO - Data User's Guide - Browse Image Tutorial

Introduction

This section serves to provide enough background information so that some of the terminology used is familiar to users reading this document. This information is not meant to provide a comprehensive description of the lidar level 1 calibration or lidar theory. Much of the following information may be found in section 3.1 of the lidar level 1B ATBD.

CALIOP is a simple three channel lidar, with detectors that collect 532 nm parallel, 532 nm perpendicular, and 1064 nm light that is backscattered from molecules and particulates (i.e. aerosols, clouds) in the atmosphere. The image at right shows a functional diagram of the lidar receiver system. The blocks labeled "Detectors and Electronics" are what we'll refer to generically as "detectors".

Once the signals have been range-scaled, energy-normalized, gain-normalized, and calibrated we can refer to the signals from each detector with the following set of equations, (the equation number are the same that are found in the lidar level 1B ATBD:

	none
	(L1B ATBD, eq. 3.13)
	(L1B ATBD, eq. 3.14)

where β' is the attenuated backscatter, β is the backscatter coefficient, and T² is the two-transmittance for the particular channel.

Total Attenuated Backscatter 532 nm

Image of the total 532 nm attenuated backscatter signal, the sum of the 532 nm parallel and perpendicular return signals, as shown by the following equation:

(L1B ATBD, eq. 3.12)

The signal strength has been color coded such that blues correspond to molecular scattering and weak aerosol scattering, aerosols generally show up as yellow/red/orange. Stronger cloud signals are plotted in gray scales, while weaker cloud returns are similar in strength to strong aerosol returns and coded in yellows and reds.

Some of you might wonder why we use such a unique color scale, and not some generic color scale that is provided by Matlab, or IDL. The answer is that CALIPSO has a significantly lower SNR compared to most ground-based or aircraft instruments, and this color scale has been specifically designed to allow data users to easily pick out and discern features of interest from the molecular backscatter signal and noise flucuations.

Perpendicular Attenuated Backscatter 532 nm

Image of the 532 nm attenuated perpendicular backscatter signal, as shown by the following equation:

(L1B ATBD, eq. 3.13)

The image is generated using the same color scale as the total attenuated backscatter image. This image is useful for discerning the difference between spherical and non-spherical particles. Non-spherical particles (i.e. dust, ice crystals) will change the polarization state of the backscattered light, while spherical particles such as water droplets or spherical aerosols will not.

Because the receiver footprint of the lidar is large (~90 m) the contribution from multiple scattered photons can contribute in a significant way to the lidar return. In water clouds this multiple scattering changes the polarization state of the backscattered light, and this signature increases as a function of penetration depth. So, it is common to see an significant perpendicular backscatter return from water clouds.

Depolarization Ratio 532 nm

Image of the volume depolarization ratio, the ratio of the 532 nm perpendicular and parallel channels, as shown by the following equation:

(Feature Finder ATBD, eq. 6.9)

This image is useful for discerning the difference between spherical and non-spherical particles. Non-spherical particles (i.e. dust, ice crystals) will change the polarization state of the backscattered light, while spherical particles such as water droplets or spherical aerosols will not.

Ice clouds (i.e. cirrus) generally will exhibit a depolarization ratio in the 0.25-0.40 range, dust aerosols are usually in the ~0.15 range. Water clouds will exhibit an increase in depolarization ratio as a function of the penetration depth, this is due to the multiple scattering contribution that was discussed in the previous image.

Total Attenuated Backscatter 1064 nm

Image of the total 1064 nm attenuated backscatter signal, CALIOP does not have separate detectors for the 1064 perpendicular and parallel return signals. The equation for the 1064 attenuated backscatter is:

(L1B ATBD, eq. 3.14)

The same color scale is used here as in the 532 nm total and perpendicular attenuated backscatter images.

The 1064 nm attenuated backscatter image can be useful for picking out faint (weak) scattering layers because the molecular backscatter is virtually non-existent. Also, looking for differences in the 532 nm and 1064 nm attenuated backscatter is useful for inferring information about the particle size. The volume color ratio plot is useful in that regard, see next image (below).

Attenuated Color Ratio

Image of the attenuated color ratio as given by the following equation,

,	(Feature Finder ATBD, eq. 6.12)
where B is the attenuated backscatter coefficient that has been normalized by the molecular and ozone two-transmittance through the atmosphere as shown by,
.	(Feature Finder ATBD, eq. 6.5)

This image is useful for inferring information about the size of the particles in the scattering volume. Because the backscatter coefficient is smaller at 1064 nm compared to 532 nm for small particles, the color ratio will often be ≤ 1 for aerosol layers and $cong; 1 for cloud layers.

For layers where there are large differences in the particulate extinction at the two wavelengths, (i.e. biomass burning aerosols) then the attenuated color ratios can become very large. If,

then the attenuated backscatter at 532 nm becomes very small,

,

and the attenuated color ratio gets real big,

Layer Type

Even though all these images are vertical feature mask images, this one is colloquially referred to as 'The' vertical feature mask. The colors in this image depict the type, (cloud, aerosol, stratospheric, surface, etc.) for each layer found by the level 2 feature finding algorithm.

New in version 3.02, layers that have a low CAD_Score (|CAD_Score| < 20), are plotted in different colors (red for low confidence clouds and brown for low confidence aerosols) to give visual information on these uncertain layers.

Horizontal Averaging Required for Detection

This VFM image show the horizontal averaging required for detection. If you are unfamiliar with the multi-gridded averaging scheme please take a look at the brief introduction in the Essential Reading section of this guide.

Ice / Water Phase

This VFM image shows the ice/water phase of all cloud layers in the scene, as such only cloud layers are shown. Also, data above 20 km is no longer plotted as cloud phase classification is not done for layers in the stratosphere.

The cloud phase algorithm used in Version 2 has been replaced with a new, completely different algorithm. The Version 3 algorithm classifies detected cloud layers as water, randomly-oriented ice (ROI), or horizontally-oriented ice (HOI) based on relations between depolarization, backscatter, and color ratio (Hu et al. 2009).

Users unfamiliar with the new cloud phase algorithm are encouraged to read the data quality statement or journal article referenced above.

Aerosol type

This VFM image shows the aerosol type (i.e. output from the aerosol classification algorithm) for all aerosol layers, as such only aerosol layers are displayed in this image. Also, data above 20 km is no longer plotted as aerosol type classification is not done for layers in the stratosphere.