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Lidar remote sensing for the characterization of the atmospheric aerosol on local and large spatial scale. Aerosols interact both directly and indirectly with the Earth’s radiation budget and climate. Minute particles suspended in the atmosphere. - PowerPoint PPT Presentation
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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