Lidar measurements can provide a great deal of information about the structure, location, and scattering properties of cirrus clouds. However, caution must be used when interpreting raw lidar backscatter profiles in terms of relative or absolute extinction distribution, internal cloud structure, and, at times, cloud location. The problem arises because the signal measured from a range by any monostatic lidar system depends on the backscatter cross section at that range and the 2-way optical thickness to the scattering volume. Simple lidar systems, however, produce only one measurement of attenuated backscatter from each range. The general FIRE research community is given aid in interpretation of lidar measurements, and the special capabilities of the High Spectral Resolution Lidar (HSRL) is explained. Some examples are given of conditions under which direct interpretation of cirrus cloud morphology from simple lidar profiles could be misleading

Eloranta, Edwin W.

Grund, Christian John

English

NASA Technical Reports Server

InterpretatIon of the Optlcal and Morphological Properties of Cirrus 
Clouds from Lldar Measurements 
and Edwln W. Eloranta 
University of Wisconsin, Department of Meteorology 
1225 W. Dayton SI., Madison, WI. 53706 
1. lntroductlon 
Lidar measurements can provide a great deal of information about the structure, location, and 
scattering properties of cirrus clouds. However, caution must be used when interpreting raw lidar 
backscatter profiles in terms of relative or absolute extinction distribution, internal cloud structure, and, 
at times, cloud location. The problem arises because the signal measured from a range by any 
monostatic lidar system depends on the backscatter cross section at that range and the 2-way optical 
thickness to the scattering volume. Simple lidar systems, however, produce only one measurement of 
attenuated backscatter from each range. It Is the purpose of this paper to aid the general FIRE 
research community in interpretation of lidar measurements, and to explain the special capabilities of 
the High Spectral Resolution Lidar (HSRL). Some examples will be given of conditions under which 
direct interpretation of cirrus cloud morphology from simple lidar profiles could be misleading. 
II.  Lldar Theory 
Simple lidar systems cannot separate the extinction and backscatter components of the lidar 
signal without additional information or significant assumptions about the atmosphere and/or 
scattering properties of the particles. This may be readily seen from the lidar equation 
R 
-2 j P e w  dr' 
P x m )  e 0 
+ M(R) P(R) = E o e K  
R' 
(1). 
Here, P(R) is the power incident upon the receiver from range R, EO is the energy of the transmitted 
pulse, 6 = A, c / 2 where A, is the receiver area and c is the speed of light. &(R) is the backscatter 
cross section per unit volume, P&(R) is the extinction cross section per unit volume, and M(R) is the 
contribution from multiple scattering. The most frequently reported lidar measurement is P(R)-R2/E0, 
the energy normalized and R2 corrected backscatter. Both Pn(R)/41r and PE(R) are due to the effects 
of particles and molecules. The factor of 2 in the exponential term accounts for the extinction along 
the 2-way path between the lidar and the backscattering volume. 
As can be seen, P(R) depends upon both the local Value of &(R)/47~ and upon !he integral of 
&(R). Only a single measuremen! of P(R) is provided at each range by simple lidar systems leading to 
ambiguities in the direct evaluation of PX/4x or PE. The problem is severe enough so that with certain 
P&(R) profiles or certain penetration angles, it is possible that the clouds could be rendered invisible to 
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simple lidar systems1. This can occur whenever PE(R) increases with penetration in such a way that 
the increase in backscattered energy with range is just offset by the increase in 2-way path 
attenuation. In addition the multiple scattering contribution M( R) can further complicate matters by 
effectively increasing P(R) in a way which depends upon the unknown spatial distributions of the 
scattering phase function and optical thickness between the lidar and the sensed volume2. 
While several techniques have been employed to untangle plr from Pe3*4@516, each method 
requires significant assumptions about the distribution of scatterers and about the nature and profile 
of the particulate backscatter to extinction ratio. The multiple scattering contribution, which can 
become large in returns from cirrus clouds, may be minimized by a narrow field of view (fov) design for 
the lidar system. This solution is often difficult to achieve and is therefore not frequently implemented; 
however, narrow fov (w.32 mrad) is a necessary requirement for the high resolution spectrometer 
employed in the HSRL, thus the uncertainties caused by the effects of multiple scattering processes 
are greatly reduced in the cirrus cloud data acquired with this system?. 
111. HSRL Technique 
The HSRL differs from simple lidar systems in that it separates the particulate backscatter 
component from the molecular backscatter component of the lidar return. Extinction is directly and 
unambiguously determined from the separated molecular backscatter return and an atmospheric 
density profile. This is possible because the atmospheric density determines the molecular 
backscatter cross section, thereby establishing a known target available at every range. 
The HSRL achieves the separation of the molecular and particulate backscatter by utilizing 
spectral distribution differences in the scattered energy. Rapid thermal motion of molecules Doppler- 
broadens the molecular backscatter spectrum. Particulates are more massive than molecules and are 
thus characterized by relatively slow Brownian drift velocities which produce insignificant Doppler 
broadening of the particulate scattered spectrum. Using a multi-etalon pressure-tuned Fabry-Perot 
spectrometer, the HSRL simultaneously observes the lidar return in two channels819. The spectrally 
narrow (w.6 pm FWHM) "particulate channel", centered on the transmitted wavelength (510.6 nm), is 
most sensitive to particulate scattering and to the central region of the Doppler-broadened molecular 
spectrum. With a prominent notch in the center of its bandpass, the spectrally wider (-5 pm FWHM) 
"molecular channel" accepts the entire Doppler-broadened molecular spectrum while rejecting much 
of the particulate scatter. Thus, the signal in each channel represents a different linear combination of 
the aerosol and molecular scattering contributions to P(R). Complete separation of the two channel 
signals requires the determination of a 2x2 matrix of linear inversion coefficients. These coefficients 
are determined by diffusely filling the receiver telescope with attenuated laser light and observing the 
response of the two channel signals to a spectral scan of the receiver'. 
Because the HSRL separately measures molecular and particulate backscatter, two lidar 
equations may be written which are coupled by a common extinction term. Assuming M(R) is 
negligible, the molecular and particulate lidar equations may be written 
R 
-21 BE(f') df 
(21, and, 
178 
R 
The subscripts a and m denote particulate and molecular scattering quantities. The term particulate 
includes both aerosol particles and cirrus cloud particles, and the subscript notation , a, is retained to 
preserve continuity with cited references. In addition, the backscatter cross section has been 
expanded into its component parts 
where Pa(K) denotes the particulate backscatter phase function and Pa,m denote the respective 
scattering cross sections per unit volume, and the molecular backscatter phase function has been 
replaced with its analytic value, 3/8x. 
With knowledge of the profile of atmospheric density from a convenient radiosonde (or from 
climatology), eq. (2) is completely defined, and may be solved explicitly for the extinction. Thus, the 
underdetermination ambiguity in eq. (1) has been eliminated in the HSRL by effectively calibrating the 
system at each range with the known molecular backscatter cross section. The particulate backscatter 
cross section is also unambiguously determined from the ratio of eq. (3) to eq. (2). 
Px(R)I4X = Pa(R) P a  (R,IC)14R + pm(R) 38% (4) 
15) 
In the absence of particulate and gaseous absorption, Pa = PE - Pm; therefore, the backscatter phase 
function is uniquely determined from (5) and the atmospheric density profile 
IV. Example 
Fig. 1 shows an example of the raw R2 corrected backscatter from cirrus clouds ahead of a warm 
front. This data is a plot of 10 minute averaged, un-inverted HSRL returns, and is similar to the 
expected output from a simple lidar system. After calibrating the HSRL and separating the particulate 
and molecular scattering profiles, the extinction corrected backscatter cross section was plotted in fig. 
2. Note the significant altitude differences in the centers of scattering activity between the extinction 
corrected and un-corrected plots, particularly in the latter half OF the record. Cloud tops could easily be 
mispositioned to a lower altitude in the uncorrected plot because extinction has attenuated the 
upper-cloud-scattered energy. 
The layer optical thickness and backscatter phase function plots for this daylo have indicated that 
a substantial portion of the structural details evident in fig. 2 may, in fact, be due to modulations in the 
backscatter phase function, and not simply due to changes in extinction. Because OF this effect, one 
must use caution in interpreting relative changes in backscatter as changes in extinction. Changes in 
backscatter may be related to changes in scatterer phase and habit as well changes in the number 
179 
density or radiative effects of particles. 
V. Summary 
We have explained some of the potential pitfalls of casual application of simple lidar data to the 
determination of cloud morphology and optical parameters. In optically thick clouds, correction for 
extinction may be important for the determination of cloud boundaries, and for the realistic rendering 
of structural details. interpretation of relative backscatter changes as modulations in cloud extinction 
may not be valid for rapidly evolving cloud systems. 
The unique capabilities of the HSRL have been explained and have been used to illustrate the 
potential problems with direct interpretation of one-channel lidar system retrievals. The HSRL has 
several disadvantages when compared to simple lidar systems. In its current state of development, the 
HSRL is complicated and time consuming to maintain, align, operate, and calibrate. Because of the 
many optical surfaces in the receiver, much of the backscattered light is lost before measurement. The 
spectral purity and stability of the transmitter must meet stringent requirements, reducing the choice 
of lasers. With the current CuC12 laser transmitter, output power is limited to 50 mW. Nevertheless, 
successful measurements of optical thickness, backscatter phase function and backscatter cross 
section have been achieved in cirrus clouds with 10 minute time resolution. Internal cbud details of 
backscatter phase function, and time resolution sufficiently short as to allow angle scanning (possibly 
volume scanning), will await integration of a new laser transmitter. The new transmitter will decrease 
averaging times by at least a factor of 40 and will hopefully be ready for operation by the time of this 
meeting. 
Support for this work has been provided under ARO grant DAAG29 - 84 - 0069 and ONR contract 
N00014-85-K-0581. 
References 
1) C.J. Grund and E.W. Eloranta, Optically Significant Cirrus Clouds may be Rendered "Invisible" to 
, Topical Meeting on Laser and Optical 
2) E.W. Eloranta and S.T. Shipley, A Solution for Multiple Scattering, m r i c  AerQSPIS: Their 
Ed. A. Deepak, 227, (1982). 
n solution for processing lidar returns. &QI,Q& 20, pp 
21 1-220. 
4) Spinhirne, J.D., J.A. Reagan, B.M. Herman (1980) Vertical distribution of aerosol extinction cross 
section and inference of aerosol imaginary index in the troposphere by lidar technique. 
ttenuation corrected images from l i a r  data: 
, NASA conference publication 2431, pp. 
6) Weinman, J.A. (1984) Tomographic lidar to meiisure the extinction coefficients of atmospheric 
Space-borne Simple Lidar Systems, 
Remote Sensing: Instrumentation and Techniques, 75, (1987). 
. 
3) 
J.Asnl.Meteor., 19, pp 426-438. 
5) E 
8) Shipley, S.T., D.H. Tracey, E.W. Eloranta, J.T. Trauger, J.T. Sroga, F.L. Roesler, and J.A. Weinman 
(1983) High spectral resolution lidar to optical scattering properties of atmospheric 
9) Sroga, J.T., E.W. Eloranta, S,T. Shipley, F.L. Roesler, and P.J. Tryon (1983) High spectral 
resolution lidar to measure optical properties of atmospheric aerosols. 2: Calibration and analysis. 
10) C.J. Grund and E.W. Eloranta (1988) Cirrus Cloud Optical and Morphological Properties 
Observed by the High Spectral Resolution Lidar During FIRE. Elsewhere in this volume. 
aerosols. 1 : Theory and instrumentation. 22, pp 3716-3724. 
a,22, pp 3725-3732. 
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Interpretation of the optical and morphological properties of Cirrus clouds from lidar measurements

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