Advances in Space Research 34 (2004) 2227–2231

www.elsevier.com/locate/asr

Backscatter LIDAR signal simulation applied to spacecraftLIDAR instrument design

J. Fochesatto a, P. Ristori a, P. Flamant b, M.E. Machado c, U. Singh d, E. Quel a,*

a CEILAP(CITEFA – CONICET) San Juan B. De La Salle 4397, (B1603ALO) Villa Martelli, Buenos Aires, Argentinab IPSL, Institut Pierre Simon Laplace, LMD Ecole Polytechnique, (91128) Palaiseau, France

c CONAE, Comision National de Actividades Espaciales, Av. Paseo Colon 751, (1063) Buenos Aires, Argentinad NASA Langley Research Center, Hampton, VA, USA

Received 21 November 2002; received in revised form 28 April 2003; accepted 28 July 2003

Abstract

In the framework of the scientific cooperation between the CEILAP laboratory (Argentina) and IPSL Institut Pierre Simon

Laplace (France), devoted to the development of LIDAR techniques for Atmospheric sciences, a new area of scientific research,

involving LIDARs, is starting in Argentine space technology. This new research area is under consideration at CEILAP in a joint

effort with CONAE, the Argentine space agency, responsible for the development of future space missions. The LIDAR technique is

necessary to improve our knowledge of meteorological, dynamic, and radiative processes in the South American region, for the

whole troposphere and the lower stratosphere. To study this future mission, a simple model for the prediction of backscatter LI-

DAR signal from a spacecraft platform has been used to determine dimensions and detection characteristics of the space borne

LIDAR instrument. The backscatter signal was retrieved from a modeled atmosphere considering its molecular density profile and

taking into account different aerosols and clouds conditions. Signal-to-noise consideration, within the interval of possible dimension

of the instrument parameters, allows us to constrain the telescope receiving area and to derive maximum range achievable, inte-

gration time and the final spatial and temporal resolutions of backscatter profiles.

� 2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Keywords: Space LIDAR; Aerosols; LIDAR simulation

1. Introduction

During the past 10 years, a big effort has been carried

out to develop LIDAR technology in the Southern

Hemisphere. Because of its strong background in laser

technology, the continuous evolution on geophysical

LIDAR applications as well as the constant develop-

ment of space technology, Argentina is currently ingood condition to confront the scientific challenge as-

sociated with the installation of a LIDAR payload on

any of the upcoming spacecraft missions. The scientific

objectives to be achieved by means of this LIDAR in

space project come from different meteorological aspects

such as atmospheric radiative transfer uncertainties

* Corresponding author. Tel.: +54-11-4709-8217; fax: +54-11-4709-

6221.

E-mail address: quel@citefa.gov.ar (E. Quel).

0273-1177/$30 � 2004 COSPAR. Published by Elsevier Ltd. All rights reser

doi:10.1016/j.asr.2003.07.062

involving aerosols and clouds dynamics, and biomass

burning events from Amazonian and agricultural farms

from the southern South America region. Additionally,

this LIDAR mission will be focused on the study of

stratospheric aerosols that are playing a major role in

the polar vortex and the ozone depletion. Complemen-

tary ground based measurements will also be necessary

to determine and understand the role of aerosol andwater vapor transport in the southern regions. These

dynamic processes are driven by mid-latitude migratory

systems from the South Pacific Ocean (Fochesatto et al.,

2002), as well as intrusion events revealed by low level

jet episodes coming from the Amazonian basin (Salio

et al., 2002). These aerosols and clouds distributions are

needed for global climate models, dynamic-chemistry

models and for global atmospheric scale interactionstudies. Therefore, a modeling of the backscatter

LIDAR spectral power can give us an adequate

ved.

2228 J. Fochesatto et al. / Advances in Space Research 34 (2004) 2227–2231

power-dimension ratio of the final instrument perfor-

mance, which should be in accordance with the main

scientific objectives of the mission as mentioned before.

This LIDAR simulation work is based on a previous

calculations reported by one of the authors (Fochesatto

et al., 1994) which was used to construct the first groundbased LIDAR at CEILAP in 1995, that is actually

making routine measurements in Buenos Aires (Foche-

satto et al., 1998; Pazmi~no, 2001). From an analysis of

signal-to-noise ratio level for different acquisition re-

gimes and atmospheric conditions, the main character-

istics of the emitter and receiver, as well as the

acquisition system of the satellite LIDAR instrument

can be deduced. The final results can then be comparedto the main satellite mission specifications to obtain a

compatible LIDAR instrument design according to the

satellite payload recommendations given by CONAE

(see e.g. Machado and Caruso, 2003). The backscatter

simulation was implemented considering various atmo-

spheric hypotheses, as possible geophysical scenarios for

tropospheric and stratospheric aerosols and tropo-

spheric clouds. Finally, the feasibility of this LIDARmission is deduced in terms of the compromise between

the spatio and temporal resolutions and the main per-

formance achievable by the instrument.

2. Backscatter power modeling

The concept design of such a space borne LIDARinstrument is closely related to ground-based systems,

but there are some details concerning power, mechanical

assembly, detection, acquisition system, autonomous

operation and reliability that need to be considered.

Here we are just focusing on the main LIDAR system

characteristics, as related to the atmospheric scenarios

to be measured. The instrument considered for this

mission is a non-resonant backscatter type that canobtain measurements in different regions of the atmo-

spheric spectral transmission bands. The simulation of

the LIDAR backscattered photons is specified for a

system emitting in the linear polarized laser wavelength

at 532 nm, corresponding to a pulsed solid state

Nd:YAG laser operating at frequency and energies in-

tervals that will be determined. These results can also be

extended to other commonly used wavelengths by meansof power-scaling laws such as �Angstr€om parameters for

aerosols (Ristori et al., 2003) and Rayleigh scattering

spectral variation for molecules, always depending on

specific atmospheric conditions. The simulation starts

with the LIDAR power receiving equation in photons

per second as shown in Eqs. (1) and (2), discriminating

the signals coming from backscattered laser photons,

sky background radiation photons and detector elec-tronic system dark current

NBKSPðz; kÞ ¼ NBKSðz; kÞ þ NBKGðz; kÞ þ NDCðkÞ; ð1Þ

where NBKSP is the total number of backscatter photons

per second, received by the lidar collecting optics, NBKS

is the total number of photons per second from the at-mosphere, which is the ‘‘LIDAR signal’’; NBKG is the

number of photons received from background radiation,

which is the ‘‘radiometric signal’’ and NDC is the ‘‘dark

current’’ in the detector element. Expanding the terms

we obtain

NBKSðz; kÞ ¼ K � E0 �k0h � c �

1

sL� c � sL

2� g � A

z2� TR � TF � Qk|fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl}

Instrumental

� bðz; kÞ � T 2ðz; kÞ|fflfflfflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflfflfflffl}Atmosphere

; ð2Þ

where K is the overall optical transmission efficiency; E0

is the linear polarized laser energy per pulse; k0 the laserwavelength; h the Planck constant; c the speed of light;

sL the laser pulse width; g the overlapping factor; A is

the telescope effective collecting area; TR is the receiving

optics efficiency; Qk is the detector quantum efficiency;

bðz; kÞ is the total backscatter from molecules, aerosoland clouds, TF is the overall spectral transmission optics

including light reception optics efficiency and interfer-

ence or etalon/blocking filters and T 2ðz; kÞ is the total

transmission, including extinction from molecules, aer-

osol, clouds and minor constituent species such as

ozone, water vapor, NOx, SOx, etc.

The signal due to background radiation falling into

the detection system can be expressed, according to(Kruse et al., 1962) as,

NBKGðz; kÞ ¼ Lk � A � p4� X � Dk � TF; ð3Þ

where Lk is the incoming spectral irradiance, X is the

receiving optics field of view and Dk is the spectralwidth of the optical filter. Laboratory and field ex-

periments were carried out at CEILAP, to measure

background radiation documented ‘‘in extenso’’ by

(Fraga et al., 1993). Results from these experiments,

obtained both in diurnal and nocturnal conditions, are

considered in our simulation. Nighttime zenithal

measurements were performed and a spectral irradi-

ance L532 nm � 1:1� 1010 m�2 s�1 sr�1 nm�1 was ob-tained, under clear night conditions without moon.

For daytime case and in clear sky conditions the

spectral irradiance was L532 nm � 1:1� 1015 m�2 s�1

sr�1 nm�1. Dark current from typical photomultipliers

tubes in the detector system was also considered, with

values of around 200 counts/s. The backscatter LI-

DAR signal depends on two terms as identified in Eq.

(2). One of them is the instrument parameter perfor-mance, and the other one is the atmospheric sounding

medium optical properties. Therefore, the backscatter

power photons can be studied for different atmo-

J. Fochesatto et al. / Advances in Space Research 34 (2004) 2227–2231 2229

spheric conditions, here called ‘‘scenarios’’, preserving

different instrument characteristics as typical con-

straint parameters in the simulation process. In order

to determine LIDAR receiving system and optical

laser emitter energy per pulse, it is necessary to con-

sider the spectral signal-to-noise ratio at the receivingoptical system level, which is a function of both at-

mospheric and instrument characteristics. This detec-

tion parameter (S/N) is an indicator of instrument

feasibility for each ensemble instrument-scenarios

characteristics to be measured as shown in Eq. (4).

S=Nðz; kÞ ¼ NBKSðz; kÞffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiNBKSðz; kÞ þ NBKGðz; kÞ þ NDCðkÞ

p�

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiDt � fL � TC

p; ð4Þ

where Dt is the temporal bin size for the photon

counting acquisition system, fL is the laser pulse repe-

tition frequency and TC the accumulation time for one

LIDAR profile acquisition.

Fig. 1. Total aerosol concentration profile for the troposphere and

stratosphere.

3. Atmospheric hypothesis for the lidar simulation

The atmospheric term in Eq. (2) can be simulated

taking into account the contribution of molecules, aer-

osol and clouds on the backscatter LIDAR photon rate.

The molecular backscatter has been considered using

the MSIS-E-90 Atmosphere Model from NASA avail-

able in http://nssdc.gsfc.nasa.gov/space/model/models/

msis.html, which has a 1 km vertical resolution. Theatmospheric aerosol and clouds have been considered in

different scenarios, as mentioned above, to explore the

LIDAR performance. This is done using the S/N ratio

as a function of the accumulation time in the acquisi-

tion system, the laser energy and the effective telescope

area, as simulation parameters. The aerosol density has

been included in the model in tropospheric and strato-

spheric layers as a typical vertical profile, shown inFig. 1 and summarized from different field experiments

and measurements compiled by (Hinkley, 1976). Aero-

sols scenarios were calibrated using the extinction val-

ues at the near surface as a function of the horizontal

visibility (Middleton, 1952), considering it as the dis-

tance were a monochromatic beam looses 98% of its

intensity due to extinction. According to Eq. (5), for the

Table 1

Aerosol scenarios summarized to LIDAR spacecraft simulation

Scenario Layer type Optical extinction (k

1 Local/polluted 0.08

2 and 3 Local/unpolluted 0.05

4 Regional/maritime/polluted 0.045

5 Regional/continental/polluted 0.045

6 Regional/continental/unpolluted 0.05

visible wavelength region, the aerosol extinction near

the surface is

aaðz ¼ 0Þ ¼ 3:91

V ðkmÞ �0:55

k ðlmÞ

� �að5Þ

where the �a� exponent is the �Angstr€om coefficient.

Following Middleton�s empirical formula, a ¼ 0:585 �V 1=3 for V < 6 km and a ¼ 1:3 otherwise. The vertical

extinction profile is then calculated from Eq. (6), as re-

ferred in (Fochesatto et al., 1994), using the total aerosol

vertical profile shown in Fig. 1.

aaðzÞ ¼ aaðz ¼ 0Þ � NpðzÞNpðz ¼ 0Þ : ð6Þ

The aerosol backscatter profile was considered using

the backscatter to extinction ratio depending on theair mass type source (see Table 1). Scenarios in the

troposphere are classified in polluted or unpolluted

continental that can be a product of local pollution or

biomass burning, originated in forest fires from farms

regions of Argentina and other parts of South

America.

For the cloud case simulation we consider cirrus

structures with one single layer, and multilayers withdifferent optical and geometrical characteristics. The

scenarios are summarized in Table 2 (Powell et al., 2002).

m�1) Backscatter to extinction ratio (1/sr) Visibility (km)

0.016 20

0.024 50

0.045 5

0.01 15

0.02 70

Fig. 3. Tropospheric aerosol LIDAR detection scenarios number 4, 5

and 6. In false color we show the (S/N) ratio as a function of the height

and the accumulation time. The TC parameter in the acquisition system

ranges from 1 to 1000 s. The normalized instrument constants are

E0 ¼ 1 J, A ¼ 0:1 m2, TR ¼ 0:8, TFBKG ¼ 0:7 and Dt ¼ 2 ls.

Fig. 2. Clouds and aerosol LIDAR detection correspond to scenarios

number 1, 2 and 3. In false color we show the (S/N) instrument ratio in

the region of higher troposphere and stratosphere depending on the

accumulation time for each scenario. The ðTCÞ parameter in the ac-

quisition system is ranging from 1 to 1000 s. The LIDAR normalized

constant in this simulation are E0 ¼ 1 J, A ¼ 0:1 m2, TR ¼ 0:8,

TFBKG ¼ 0:7 and Dt ¼ 2 ls.

Table 2

Clouds scenarios summarized for LIDAR spacecraft simulation

Scenario Layer type Geometrical depth Optical extinction (km�1) Backscatter to

extinction ratio (1/sr)

Depolarization factor

1 Cirrus 10–12 0.25 0.025 0.4

2 Cirrus 16–17 0.025 0.033 0.5

2 Cirrus 9–11 0.2 0.044 0.4

3 Cirrus 16–17 0.025 0.033 0.5

3 Cirrus 7–10 1.0 0.066 0.4

2230 J. Fochesatto et al. / Advances in Space Research 34 (2004) 2227–2231

4. Simulation results

The simulation results were organized using the sce-

narios to check the integral performance of the LIDAR

system. In Figs. 2 and 3 the S/N ratio is shown for a

LIDAR system built with the following characteristics,

1 J per laser pulse, 10 Hz in pulse repetition frequency

and a 0.1 m2 effective collecting area as system param-eter normalization. In Fig. 2 we depict the first three

scenarios that were considered using cirrus and aerosol

data from Tables 1 and 2, as a function of the accu-

mulation time in the horizontal axis, ranging from 1 to

1000 s, corresponding to a broad range of performance

laser emitting systems. In Fig. 3 we can see the S/N ratio

for the case of scenarios 4–6 concerning aerosol remote

sensing in the troposphere and stratosphere.

5. Summary

Aerosol and clouds can be monitored using a LIDAR

spaceborne platform using either minipulse laser or

common diode pumped solid-state laser (McCormick,

2000; Winkler et al., 2000). In all cases, as a result fromthis simulation, the emitter laser at 532 nm linear polar-

ized wavelength can have energies per pulse in the range

of E0 > 100 lJ to 100 mJ taking into account the S/N

ratio and available technology. The pulse repetition fre-

quency can start in fL ¼ 10 Hz, up to a maximum of 250

Hz, to include all the atmospheric scenarios described in

this work. The typical orbital altitude for an Earth ob-

serving mission (600 km) imposes this maximum pulserepetition frequency. The receiving optics can be in-

creased in size, starting in this simulation with 0.1 m2, in

order to improve the S/N ratio for all scenarios. This

ensemble parameters system will allow us to make the

adequate post-processing signal, in order to retrieve

backscatter profiles and derive geophysical parameters

associated with optical and dynamic cloud characteris-

tics, tropospheric and stratospheric aerosols opticalproperties, and atmospheric boundary layer spatial

morphologies. Concerning the final temporal profile

resolution it is depending on the atmospheric region

under consideration. In fact, each atmospheric layer has

a representative spatial scale that dominates it, and

consequently the expected dynamic variable to be re-

J. Fochesatto et al. / Advances in Space Research 34 (2004) 2227–2231 2231

trieved. As an example, configuration data for the lower

troposphere; looking for the Atmospheric Boundary

Layer spatial characteristics, meso-scale clouds and re-

gional transport aerosols can be acquired as single shot

resolution preserving an appropriate equilibrium be-

tween the laser energy per pulse and the pulse repetitionfrequency. Meanwhile, averaging process can improve

profile performance at different post processing levels. In

order to improve the initial profile raw data due to a S/N

reduction for scenarios such as some higher troposphere

clouds cases and aerosols in the stratosphere (see Figs. 2

and 3), data can be acquired with a minimum of aver-

aging (>10 shots) if the LIDAR instrument kept maxi-

mized the mean optical laser power. Finally, the LIDARsystem dimensions are dominated by the telescope sur-

face collecting area, which is the main constraint in the

total instrument dimension–weight relationship. In this

case the instrument is planned to have a Cassegrain

telescope with a multi fiber optic collecting system. In

particular, for this mission the primary mirror diameter

can reach a maximum value of 0.6 m in diameter. Total

weight for the reception system can reach 50 kg ap-proximately. This dimension–weight number corre-

sponds to 80% of the total volume available, as described

in Machado and Caruso (2003).

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