Lidar remote sensing for the characterization of the atmospheric aerosol

on local and large spatial scale

Atmospheric aerosol

What are THEY and why are THEY so important?

Minute particles suspended in the

atmosphere

Aerosols interact both directly and indirectly

with the Earth’s radiation budget and climate

Aerosols reflect or absorb sunlight

Aerosols modify the size of cloud particles,

changing how the clouds reflect and absorb sunlight

WHAT ABOUT THE ESTIMATION OF THEIR EFFECTS?

MOTIVATION

MOTIVATION

from IntergovernmentalPanelClimateChange

INTERACTION LIGHT - ATMOSPHERE

• Elastic scattering

• Anelastic scattering

a

x2

Mie scattering

Rayleigh scattering

x << 1

moleculesRayleigh scattering Mie scattering Mie scattering,

larger particles

Direction of incident light

AE

Raman scattering

Information on the species concentration

THE REMOTE SENSING LIDAR TECHNIQUE

Sor

gen

te

lase

rN

d-Y

ag

La

ser

Receiver

LIghtDetectionAndRanging

Signal processing

ELASTIC LIDAR EQUATION (SINGLE SCATTERING)

z: altitude

: wavelength

1 equation2 unknown parameters

+ a priori hypothesis Lidar Ratio (LR)

KLETT ALGORITHM(Klett, 1981)

z

0

dς ςλ,α2-L

20

L e zλ,β zλ,ξ 2

cτ

z

A Pz λ,P

PL: laser power

Standard Atmosphere

vertical resolution : efficiency

β = βm + βa backscatter coefficient

ma extinction coefficient

z

A20

acceptance angle 2

cτL

RAMAN LIDAR EQUATION (SINGLE SCATTERING)

No a priori hypothesis

1 Elastic lidar equation + 1 Raman lidar equation2 unknown parameters

WANDINGER ALGORITHM(Wandinger, 1990)

z

0

RLdς ς,λα ς,λα2-

RLRL

20

LRL e z,λ,λβ z,λξ 2

cτ

z

A Pz ,λ,λP

d

drNr RL

RL

,,,,

RCS - RANGE CORRECTED SIGNAL

PBL height

Planetary Boundary Layer

Directly influenced by the presence

of the Earth's surface

Aerosol as tracers

Time (UT)

18:00 20:00 22:00 24:00 02:00 04:00 06:00

He

igh

t a

bo

ve

lid

ar

sta

tio

n

(m)

7000

6000

5000

4000

3000

2000

1000

RCS @ 532 nm (a.u.)Naples, 9-10 May 2005

EARLINET (European Aerosol Research LIdar NETwork)

Since May 2000

ARPAC

Naples station (40.833°N, 14.183°E, 118 m. asl)

• regular measurements twice a week

• special measurements (Saharan dust, forest fires, volcanic eruption, etc…)

• intercomparison both for hardware and software

25 stations

THE NAPLES LIDAR SYSTEM

Lc DBS1

D

M1 M3 M2

PMT3

IF2

Discr

IF4 QP

PMT7

IF3 PMT4

QP

PMT5

PMT2

DBS2

2

QP

IF1

PMT8

IF5 PMT6

PMT1

Nd:

YA

G la

ser

sour

ce

DBS3

2

1.00E+07

1.00E+08

1.00E+09

1.00E+10

1.00E+11

0.00E+00 5.00E+03 1.00E+04 1.50E+04

Altitude (m)

RCS

(a.u

.)

5X beam expanders

Diaphragm

Collimating Lens407

387

387 High

387 Low

407

387 407

355532

355 High

355 Low

355

> 532

532

532 High

532 Low

607

607

CLOUD SCREENING Sharp variation

1.0E+08

1.0E+09

1.0E+10

1.0E+11

0.00E+00 5.00E+03 1.00E+04 1.50E+04 2.00E+04

cloud

RCS (a.u.)

Height (m)

0 5000 10000 15000 20000

108

109

1010

1011

PRE - PROCESSING DATA

PRE - PROCESSING DATA

PILE UP CORRECTION

Measure the same signal:

- D1 at low acquisition rate (< 500kHz)

- D2 at working condition

0 5 10 15 20 250

1

2

3

4

5 Y =668.68516+0.14171 X+3.50923E-9 X2+

-1.48633E-16 X3+5.72961E-24 X4

Ref rate Polinomial fitR

ate

Re

f, M

Hz

Rate R386L, MHz

Polinomial fit

Rate D2 (MHz)

Rat

e D

1 (M

Hz)

PRE - PROCESSING DATA

MERGE

1.0E+08

1.0E+09

1.0E+10

1.0E+11

0.00E+00 5.00E+03 1.00E+04 1.50E+04 2.00E+04

Height (m)

0 5000 10000 15000 20000

108

109

1010

1011

Analog – low height

Photocounting – high heightRCS (a.u.)

CALIBRATION

1.0E+08

1.0E+09

1.0E+10

1.0E+11

0.00E+00 5.00E+03 1.00E+04 1.50E+04 2.00E+04

Height (m)

0 5000 10000 15000 20000

108

109

1010

1011

RCS (a.u.)

PRE - PROCESSING DATA

Molecular signal

“Clean” air