lidar development and its applications at uprm getting to understand the planets radiation budget...
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LIDAR Development and its Applications at UPRM LIDAR Development and its Applications at UPRM
Getting to understand the planets radiation budget plays an important role in atmospheric studies, and consequently in climate understanding. With the help of a 3 wavelength (355, 532, 1064 nm) fixed LIDAR that will be established at the University of Puerto Rico Mayagüez Campus (UPRM), and a MICROTOPS II sunphotometer, the research community at UPRM will contribute to the climate knowledge, by studying atmospheric constituents such as aerosols. In this research project aerosol parameters such as extinction and backscatter coefficients, are determined using a set of data from the Arecibo Observatory (AO) LIDAR. The data used for the analysis is from two successive days at wavelengths 532 and 589 nm. Previous analysis of the AO data over the months and years, show that aerosol variations for the same months of different years are very small.
AbstracAbstractt
LIDAR LIDAR Development Development
After processing the AO data, the steps to obtain the particle extinction and backscatter coefficients are described by the following equations . Starting whit the standard atmospheric model we have :
ProcedProcedureure
Feature WorkFeature Work
AcknowledgmAcknowledgmentsents
We really appreciate the support to this project by the combined NOAA-CREST grant #NA17AE1625
and NASA-EPSCoR grant # NCC5-595.
Electrical and Computer Engineering Department • University of Puerto Rico, Mayagüez Campus
By: Vazjier M. Rosario, Hamed Parsiani: Vazjier M. Rosario, Hamed Parsiani:
Advisor [email protected] • [email protected]
The AO LIDAR data is composed of measurements (profiles) of some of the stratosphere constituents and the Rayleigh response: R. These constituents are Potassium : K Nitrogen : N, Calcium : Ca, and Iron : F. However, this study will consist in the manipulation of the R and N data only, in order to improve the Aerosol analysis by calculating the extinction and backscattering coefficients, which will lead to the determination of aerosol physical properties such as effective radiuseffective radius, single scattering Albedosingle scattering Albedo, concentrationconcentration, and optical depthoptical depth.
Since the available AO data do not provide profiles of different wavelengths simultaneously in a single night of observation, the data of two consecutive days, 23 Jan 01 and 24 Jan 01 at wavelengths 532 532 and 589 589 nmnm respectively were used to determine the desired aerosol parameters.
In this approach we are assuming that variations between the power profiles of these consecutive days are very small. This assumptions is verified with previous studies of aerosol statistical variations using AO data.
Data Data Overview Overview
As part of our contribution to the atmospheric studies, a 3 wavelength LIDAR will be established at UPRM, which specifications will match those of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) part of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission and the Arecibo Observatory LIDAR. Therefore, a cross validation of the systems data will be possible.The systems specifications are as follow:
UPRM LIDARUPRM LIDAR
Transmits: 1064 nm 532 nm 355 nm RR: 20 Hz
Receives: 1064 nm 532 nm 355 nm 1m telescope
AO LIDARAO LIDAR
Transmits: 1064 nm 532 nm 355 nm RR: 20 Hz
Receives: 770 nm 589 nm 532 nm 422 nm 374 nm1m telescope
CALIOP in CALIPSOCALIOP in CALIPSO
Transmits: 1064 nm 532 nmRR: 20.16 Hz
Receives: 1064 nm 532 nm 1m telescope
Figure 1:UPRM LIDAR Diagram
Figure 3:CALIPSO LIDAR
Figure 2:AO LIDAR Beam
RdR
dTTRT 0)( 11Temperature: Pressure: pRRePRP /)0()( 22
Figure 4:Temperature profile
Figure 5:Pressure profile
Number Density: )()()( RT
RPRN 33
Figure 6:Spatial Number Density
-325s m x102.547 N
-4532 x102.78197 1 - )n(
0279.0
-4589 2.75779E 1 - )n(
aa
bb
dd
cc
76
36
3
]1)([8)( 24
223
s
RayN
n55
Total Rayleigh Cross section
Molecular Extinction Coefficient:)()(),,( 0 RARay RNRR 44
Figure 8:Molecular extinction Coefficient @ 589 nm
Figure 7:Molecular extinction Coefficient @ 532nm
Following the previous procedure, the power profiles were included in the analysis to determine the extinction and backscatter coefficients.
ResultsResults
Figure 10:Power Profile @ 589 nm
Figure 9:Power Profile @ 532 nm
Particle Extinction CoefficientParticle Extinction Coefficient
k
Ram
Ray
RamRayRam
Ray
Ray
zzzzP
zN
dzd
zMM
P
1
)()()(
)(ln
)(2
Particle Backscatter CoefficientParticle Backscatter Coefficient
0
0
))()((
))()((
0
00 *),(
),(
),(
),()()()( z
zPRayMRay
z
zPRamMRam
MM
Pdzzz
dzzz
RA
RA
e
e
RP
RP
RP
RPRRR
Figure 12:Backscatter Coefficient
Figure 13:Aerosol Optical Thickness
Aerosol Optical ThicknessAerosol Optical Thickness
0
)()()(z
z
RamRay zzzAOTMM
Figure 11:Extinction Coefficient
Use the previous results for derivation of aerosol parameters such as effective radius, single scattering Albedo and aerosol concentration.
Validate the data whit the Arecibo Observatory LIDAR data and the CALIOP data when orbiting over the Puerto Rico Region.
Utilize the aerosol physical properties data to improve climate predictions and forecast poor quality air conditions episodes over the western and north-western regions of Puerto Rico.