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1
LIDAR Technique for Atmospheric Monitoring in The Pierre
Auger Observatory
Guillermo Manuel Sequeiros
Corso di Dottorato in Fisica – XVIII Ciclo
May , 2005
1. Introduction
For about more than 100 years the fascination of cosmic rays had excited the
physicists. Victor Hess in 1912 was one of the pioneers in observing highly energetic
particles from outer space. In his words: “a radiation of very high penetrating power
entering our atmosphere from above”[1].
The cosmic ray composition and its shape is well known up to energies of 1019
eV.
Nonetheless there are open question about this energy value, such as the right shape of
the spectrum, the existence of the GZK cutoff, their mass composition, the accelerate
sites and mechanisms able to accelerate particles to such high energies, the anisotropy or
isotropy their direction distribution.
With the Pierre Auger Observatory we want to study cosmic rays at the upper end of
the known energy spectrum, i.e. events with energies above 1018
eV, using a combination
of the two techniques used by the previous largest experiments: the Ground Array
technique and the Fluorescence technique.
Measurements of the cosmic-ray air-shower fluorescence at extreme energies requires
precise knowledge of atmospheric conditions. The absolute calibration of the cosmic-ray
energy requires a good estimate of the absorption coefficient [2].
In my PhD pre-thesis I introduce a brief description of The Pierre Auger Observatory,
then the atmospheric techniques used actually in this observatory, describing with details
the LIDAR technique, the hardware and software of the LIDAR systems that our group
have mounted , developed and put in operation the different sites. I described the LIDAR
data as well as the online monitor tools for the control of the data acquisition. Molecular
and aerosol contributions to the LIDAR equation are discussed and an algorithm for
cloud height detection is thoroughly described.
2
2. The Pierre Auger Observatory
The Auger Observatory consists of two parts: the first system is currently installed in
the southern hemisphere in Argentina and the second will be built in the next years in the
northern hemisphere, both sites covering a total surface of 6400 km2
will able to detect
6000 events/year above 1019
eV and 60 events/year above 1020
eV. Both sites are located
at around 35 – 40º latitude allowing altogether a full sky exposure.
The particles detectors are place on an area of about 3000 km2. The site was chosen
according to the necessity of a large almost flat area , 1400 m a.s.l. with sparse human
inhabitants, but with some infrastructure near the array, no significant sources of light
and cloud cover of less than 15 %. The system is described in the following.
2.1. Fluorescence Detector
These detector type used a detection technique which consist in detecting fluorescence
light emitted by de-excitation of nitrogen molecules and nitrogen ions excited from
charged particles of the showers.
The atmosphere on the array will be observed by four fluorescence detector telescopes
each of them covering a 180º x 30ºfield of view (see Figure 1). The duty cycle of these
detectors is ∼10 % considering that the system requires illuminated moon fraction below
50 % and clear sky.
Figure 1: cover zone of the Pierre Auger Observatory in Malargüe Mendoza, Argentina. The dots
represent the array of the 1600 water Cherenkov tanks, are signed with red dots the four fluorescence
telescope stations, Los Leones, Coihueco, Morados and Pampa Amarilla (Norte).
3
Each fluorescence detector is composed of six telescopes, each telescope being made
of segmented spherical mirrors with 3.4 m curvature radius, a corrector ring, a UV filter
and 440 photomultipliers (PMTs) camera placed in the focal plane. Each camera inside a
fluorescence detector is read out separately (see Figure 2).
Figure 2: Scheme of a fluorescence telescope system
The array of PMTs sees the trace of the Extensive Air Shower (EAS) as a light spot
crossing the atmosphere at the speed of light along a line. The pixels on the camera will
be hit sequentially by fluorescence photons coming from these light points.
2.2. Surface Detector
The surface is made of water Cherenkov tanks, the final array will we conform of 1600
tanks separated 1.5 km distance one each other. These detectors observe the Cherenkov
light emitted by secondary particles (muons and electrons) of an EAS when they cross the
water in the tank and their velocity is above the Cherenkov threshold in the water. The
tanks have a sensitive water volume (1.2 m height, 3.4 m diameter) and contain 3 PMTs
which detect the Cherenkov light (see Figure 3 and 4). The duty cycle of these detectors
is 100 %.
4
Figure 3: photograph of a Cherenkov tank Figure 4: Schematic drawing of a tank
installed on the site.
3. Atmospheric Monitoring for the Auger Observatory
As we mention before the detection technique used by the Pierre Auger Observatory
required continuous monitoring of the light attenuation between the fluorescence source
and the detector. A short description of the atmospheric monitoring systems that have
been installed in the observatory is given below.
• Horizontal Attenuation Length Monitor: composed of three systems which
observed tree different light trajectory through the site recording the horizontal
attenuation lengths within or close to the wavelengths values to which the
fluorescence detectors are sensitive. The principal components are a light source
and a CCD camera. These measurements are made at 4 different wave length
throw filters (365 nm, 404 nm, 436 nm, 542 nm).
• Cloud Cameras: clouds can interfered seriously in the fluorescence detection, for
this is necessary to have a sky cloudiness control during the data taking. For this
objective are used infrared cameras installed one in each site of the array which
scan the sky during all the night including the field of view of the Fluorescence
Detector. The spectral range is from 7 – 14 µm and the field of view 45º x 36º.
The cameras give a full sky scan every 15 minutes.
• Weather Stations: There are 3 weather stations one at each fluorescence site and
one at the central site. They monitor daily temperature, wind speed and direction,
pressure, solar radiance and relative humidity.
• Central Laser Facility: The so-called Central Laser Facility (CLF) is based on a
remotely controlled steerable laser (main wavelength: 355 nm, 6 mJ typical beam,
7 ns with). It has been setup at the center of the array, and it produces a calibrated
test beam for the FD. The CLF was conceived to meet a number of atmospheric
monitoring and detector (FD and SD) performance needs, including: 1)
measurement of the aerosol vertical optical depth versus height in the center of
the array with different systematical uncertainties from the backscattered LIDAR;
5
2) measurement of the horizontal uniformity across the aperture of the array; 3)
monitor of the relative timing of the FD, the relative calibration (photons to ADC
values) of the FD; and the trigger efficiency of the FD; 4) monitor of the relative
timing between the FD and SD; 5) check the FD mirror alignment [3].
• LIDAR stations: this system uses an steerable UV laser beam to probe an
specific region of the atmosphere. The beam backscatters on haze and aerosols,
while the reflected light is collected with a mirror onto a photomultiplier read by a
computer (see Fig. 4 and 5). The pulse shape analysis gives the absorption-
coefficient map of the sky.
Campo di vista
dello specchio Fascio laser
Figure 4: Schematic of a LIDAR system
Figure 5: Typical LIDAR signal, and the
overlap produced between the laser beam and
the telescope mirror
4. LIDAR Telescope, Hardware and Software
4.1. The Telescope Components
We have already installed three LIDAR systems in the stations of Los Leones,
Coihueco and Morados(two of them fully operative). These systems consist basically
of recycled EAS-TOP experiment telescopes [5] doing appropriate modifications and
6
replacing mechanics and electronics parts in manner to do them operatives. A short
description of the components parts follows.
• Telescope Structure: it is an steerable alt – alt azimuthal mount that allows
movimentation on two coordinates: the zenith axis rotates the entire structure
within a range of 180º (see Figure 6). The second one “azimuth” permits to the
structure which support the mirrors and the laser 180º movements in azimuth (see
Figure 7). The combination of these two movements allows a complete coverage
of the sky. The movements in the zenith axis are transmitted trough a geared
wheel and a geared belt. The transmission movements in the azimuth axis are
made through a wheel and an iron cable. The telescope structure holds both
motors (and their covers,) both encoders, limit inductive sensors, extra-limit
mechanical switches and the inductive zero position indicators.
Figure 6: LIDAR telescope structure Figure 7: LIDAR telescope structure
scheme movement in zenith axe scheme movement in azimuth axe
• Laser System: the laser is mounted on the telescope. The laser shots into the
atmosphere in a desired direction and the receiving system measure the back-
scattered light as a function of time. At the moment for economic reasons we have
installed two different laser systems in both LIDAR. Their principal
characteristics are: Los Leones laser system: manufacturer: Big Sky
Technologies, model: “Ultra”, type: Nd:YAG , main wavelength: 355 nm, pulse
energy (max): 6 - 7 mJ, pulse rep. freq.(max): 0 to 20 Hz (used at 10 Hz).
Coihueco Laser system: model: DC30-351, manufacturer: Photonics Industry,
laser type: Nd:YLF, main wave length: 351 nm, pulse Energy: 150 uJ, pulse with:
10-25 ns, repetition rate: 0 to 10 kHz (used at 333 Hz).
• Telescope Optic: each LIDAR detector hold up 3 parabolic mirrors (80 cm
diameter and 41 cm focal length) made of Pyrex glass (O2Si) supported in the
modified alt-azimuthal mounting. The pointing accuracy of these steer able
telescopes is 0.05º. The full field of view of these detectors is ~ 1.76º x 1.76º.
7
• Photomultiplier tubes: the signal is received for three Hammamatsu R7400
photomultipliers tubes each one with a module size 60.7 x 25 mm, including a
UVG filter.
• Telescope Cover: all LIDAR telescopes are protected from atmosphere agents
and solar light with a cover (see Figure 8). Both parts of the cover are opened and
closed at the beginning and at the end of the data acquisition through two robust
motors, steel cable and pulleys system.
Figure 8: photograph of the LIDAR
system with the cover closed
• The Acquisition System: The signal is digitized using a three-channel LICEL
transient recorder TR40-160 with 12 bit resolution at 40MHz sampling rate
with 16k trace length combined with a 250MHz single photon counting
system. Maximum detection distance of the hardware is thus, with this
sampling rate and trace length, set to 60 km. However, in real measurements,
atmospheric features up to 30 km only are observed. LICEL is operated using
a PC-Linux system through a National Instruments digital input-output card
(PCI-DIO-32HS) (see Figure 9). The data acquisition system is managed
using a ROOT graphic interface [6] .
8
Figure 9: The LICEL TR40-160 receives the trigger from
the laser and the signal from Hammamatsu R7400 phototube.
The Linux-PC controls the LICEL digitizer through
PCI-DIO-32HS Digital Input/Output card.
4.2. Telescope Control Movement
4.2.1. Hardware
• Control Panel and Electronic: the panel is divided in two parts (see Figure
10), the left one which contains the components powered at 220 V and 110 V
while the right one contains the low voltage components ( 24 V and 5 V).
Figure 10: Schematic of the Control Panel indicated the new components that have been included in
order to upgrade the telescopes
Maestro
modules
transformers
Motion
Coordinator
Module(MC204)
CAN 16 I/O
and CAN 8
Analog Inputs
9
Motion Coordinator Module (MC204): this Trio Technology module is
capable of driving a multi-axis machine and its auxiliary equipment, in our
telescope the module commands 2 axes. The controller was programmed
using the TRIO BASIC programming language. This can be used to build
"standalone programs" or commands can be sent from an external computer
[7]. This system allows adding digital I/O and additional equipment. MC204
contains the processor and logic power supply.
Each MC204 module contains two daughter boards with respective serial
ports used for the encoder communication.
The Motion Coordinator is connected to our computer via an RS-232-C serial
port that we used to both load programs and execute commands from remote.
4. 2. 2. Software
The telescope control software was developed in TrioBASIC, a language similar of
BASIC with predefined functions for the control trough the “Motion Coordinator”.
TrioBASIC is a multitasking language and can run up to five programs
simultaneously .The code is recorded in the MC204 internal memory ( 122 kB flash
EPROM).
The different telescope functions and the associated programs are:
- initialization variables (STARTUP.BAS),
- open cover (OPEN_COVER.BAS),
- close cover (CLOSE_COVER.BAS),
- LIDAR initialization (INIT.BAS),
- manual control (PAD_SON.BAS),
- telescope movement (MOVETO.BAS),
- telescope park (PARK.BAS) ,
- telescope unblock (UNBLOCK.BAS).
Is available the telescope works local mode through a pad which can be connected
to the control panel.
In addition the telescope can work in remote manner, it means, can be driven
from the Central Building. The communication between the MC204 and the Linux
LIDAR computer on each site is established trough the serial port RS 232 that was
mention before. There is a program in C++ which permit to send instructions through
the Linux shell and in the same way permit receiving information from the MC204.
5. LIDAR Data, Data Control and Analysis
5.1. Data Structure
10
The data from Malargüe LIDAR stations is stored in root binary files [8] . Basically
these files contains objects inherited from ROOT TObject .
There are two main objects of concern, one is the object that belong to the class
TRunHeader which has the basic information about the LIDAR run: the acquisition
starting time, the total number of LIDAR events inside the file the number of operational
digitizer modules, the PMT voltages, the laser power, and some remarks or comments.
The other object is TLEvent, used as data container for the LIDAR signal provided by all
operating LICEL transient recorders. For each channel we recorded the number of single
photon counting and the flash ADC trace.
During the acquisition runs, the temporal sequence of LIDAR events is stored in the
file, following a TTree structure. In ROOT a TTree structure is made of a series of
TBranch (in his case assigned to TLEVENT objects) that can be read independently of
each other, as distinct “TTree entries”.
5.2. Strategies for scanning the sky
5.2.1. “AUTOSCAN” strategy
There are four different strategies for the data taking. The AUTOSCAN strategies are
running automatically during all the night covering a sky cone of approximately 50º
(outside of FD field of view), and doing both discrete and continuous scanning:
• Discrete sweeps strategy: in this case the shoot trajectory follow the
equation:
sec1sec ∆+= iθ
where 065.0sec =∆ and θ is the polar angle;
- for the zenith discrete sweep we use: ϕ = 0º, 180º ;
- for the azimuth discrete sweep we use: ϕ = +120º, -120º.
where ϕ is the azimuth angle centered.
• Zenith continuous sweep: the telescope shoots from 54º to -44º in zenith
with azimuth= 0 during the entire scan at 0.075 º/s velocity.
• Azimuth discrete sweep: in this strategy the telescope shoots from 43º to
-29º in azimuth with zenith= 0 during the entire scan at 0.058 º/s
5.2.2. Shoot the Shower (StS) strategy
Through this strategy will be possible to monitor the attenuation coefficients from the
shower path to the Fluorescence Detectors. The intention is that clouds and patches
would be accounted properly, and their effects on the FD reconstruction, corrected.
11
These strategy works only with an important event is seen by at least two of the
fluorescence detectors (see Figure 10), or when the event is seen by both the
fluorescence and the surface detector (“stereo event”). The sequence can be described as
follow:
- the FD generates a trigger (T3) of third level (T3 contains information about the
geometry of the shower, the SDP vector);
- LIDAR receives the T3 from FD;
- Run Control (client of the LIDAR server) calculates the shower track points vector
position;
- are setting new LIDAR steering parameters;
- LIDAR request to enter in the FD field of view (FOV), so the FD toggles Lid Veto ON;
- FD Data Acquisition stops, with the photomultipliers on;
- LIDAR init the Shoot the Shower scanning (see Figure 11);
- when the scanning is done (approximately takes 2 minutes), LIDVeto is put in OFF;
- after this AUTOSCAN strategy restart with a Zenith Discrete sweep;
Figure 10: An event seen by the FDEyeDisplay, this produce
a T3 which is send it to the LIDAR to start the StS strategy.
12
Figure 11: Trajectory that LIDAR described according
do to the shoot the shower strategy (as OLV display
can show).
5.3. Data Control
5.3.1. LIDAR Signal
A typical LIDAR signal (Figure 5) has a big peak, where the laser beam enter
completely in the mirror field of view, this happens at about 150 m. After the maximum
peak the signal decrease in an exponential way.
The overlap signal during the acquisition can suffer variations (even saturation) due to
the high voltage value set to the photomultipliers, the laser intensity, mirror
misalignment, etc. Due to this, we consider necessary to do a control of this data.
5.3.2. Functions implemented to OLV viewer
In in order to control the data quality, we implemented some functions to the existent
software viewer for shifters “OLV”.
“OLV” is a C++ software with a graphic interface QT. This program is launched at the
beginning of the data acquisition and is running during the entire data taking. “OLV”
permit to the shifters visualize the state of the run acquired (event by event), and is
possible select the visualization way: scale, PMT , bin averaging ,etc. (see Figure 12).
According to control the data we had implement to OLV the possibility of seeing the
evolution of the overlap function (peak signal) during all the data taking, the offset
variation and its σ2 (see Figure 13 and 14 ).
13
Figure 12: “OLV” graphic interface where we can visualize
the signal for each event in the “Event Display” window.
Figure 13 and 14: “OLV” graphic interface with the new add function which permit the visualization
of the overlap function (peak signal) during all the data taking, the offset variation and its σ2.
14
5.4. LIDAR Data Analysis
In an extensive air shower the cascade of particles along the shower axis is limited to a
narrow lateral distribution. In this way, fluorescence light is emitted with an intensity
proportional to the number of charged particles in the shower. The calorimetric measure
of the total electromagnetic (EM) component of the shower energy [6] is proportional to
the integral of EM particle density Nem along the shower direction x,
dxxNKE emem )(∫= (1)
with K ≅ 2.2 MeV cm2/g, where x is measured in units of longitudinal air density (g/cm).
E_ em is a lower bound for the energy of the primary cosmic ray. The lower portion of
shower development is usually obscured by the ground so that EM cascade reaching
below ground is included by fitting a functional form to the observed longitudinal profile
and integrating the function past surface depth. The number of photons Nph reaching
fluorescence detector (FD) is proportional to EM particle density Nem at the point of
production x ,so that in turn,
)(
)()(
2
xT
xrNxN
ph
em α (2)
with r(x) being distance between shower point and FD. Light originating within the
shower is certainly affected by the absorption and scattering on molecules and aerosols in
the atmosphere. The number of detected photons is thus reduced due to non-ideal
atmospheric transmission T(x) < 1, where:
)(
0
)(exp)( x
r
edrrrTτα −=
−= ∫ (3)
with α(r) volume extinction coefficient along the line-of-sight, and τ (x) the resulting
atmospheric optical depth (OD) to the shower point x.
In this sense, the atmosphere can be treated as an elementary-particle detector.
However, weather conditions change the atmospheric transmission properties
dramatically, resulting in a time-dependent detection efficiency. Therefore, an absolute
calibration system for fluorescence light absorption is an essential part of FD.
One of the most suitable calibration setups for FD is the backscattering LIDAR system,
where as we mention before, a short laser light pulse is transmitted from FD position in
the direction of interest. With a mirror and a photomultiplier tube, backscattered light is
collected and recorded as a function of time, i.e. as a function of backscatter distance.
In order to extract τ (x) from a backscattered elastic LIDAR signal we have to invert
the LIDAR equation (4):
15
)(2
2
0
0 )(2
)( rer
Ar
tcPrP τβ −= (4)
P(r) is the instantaneous received laser power (backscatter signal) at time t from a
distance r;
P0 is the instantaneous transmitted laser power at time t0;
t0 is the laser pulse width;
β (r) is the backscatter coefficient;
A is the effective receiving area of the detector , proportional to the area of the mirror and
proportional to an overlap between its field of view with the laser beam.
As we can see from Equation (2), the precision of measurement of α and the
corresponding integral τ directly influences the precision of primary particle energy
estimation.
Even if the LIDAR equation (4) can look simple, is difficult to solve it for the two
unknown variables α (r) and β (r), this leads to the ambiguity in their determination: the
equation can not be resolved without additional assumptions about atmospheric
properties.
Correcting for r2 and normalizing to r = r0, we can introduce an auxiliary S function:
[ ] );(2/)(ln)(
)(ln)( 002
00
2
rrrrrP
rrPrS τββ −== (5)
τ (r;r0) corresponds to the atmospheric optical depth between r0 and r, that we want to
estimate;
We consider separately the molecular and aerosol influence, and the coefficients α and
β can be written as the sum of the contribution of two independent components ( the
molecular and the aerosol), in this way:
)()()( hhh am ααα += and )()()( hhh am βββ += (6) and (7)
where αm ,αa, βm, βa correspond to molecular and aerosol attenuation and backscattering
coefficient respectively.
Both quantities are proportional to the local density and from:
)()(180
hd
dh ρ
σβ
Ω= (8)
)()( hh TOT ρσα = (9)
we have:
16
)()( 180 hd
d
hTOT
ασ
σ
βΩ
= (10)
where: º180Ωd
dσ = )º180(P (11)
Then, we can write )(hβ as:
)()º180()()º180()( hPhPh aamm ααβ += (12)
The aerosol phase function Pa(180º) for backscattering has, apart from the wavelength,
also a strong dependence on the optical and geometrical properties of the aerosol
particles. Nevertheless, at wavelength of 355 nm, values in the range 0.025 to 0.05 sr-1
can be assumed for aerosol phase function.
The angular dependence of molecular phase function is defined by the Rayleigh
scattering theory, where Pm(180º) = 3/8π sr-1
.
The molecular density variation with height is well known and have very little seasonal
fluctuations (see Figure 15).
Figure 15: Pure molecular optical depth variation in the different
season.
17
The proportion of clear skies is definitely lower than the percent of nights with aerosol
concentrated in clouds or aerosol layers, this is because the importance of the cloud
detection.
For clear sky the S function is similar to a line in which the pendent decrease lightly
with height (Figure 16), in fact assuming constant the attenuation and backscatter
coefficient we can write:
[ ] )()(2)]/()([ln);(2/)(ln)(
)(ln)( 01
0
00002
00
2
rraadrrrrrrrrP
rrPrS
r
r
−+=−=−== ∫αββτββ
The non linearity of the S function evidence the presence of aerosol or at higher levels
clouds. In this way we can delimit a zone of linearity defining the height in which start a
cloudy zone. In this terms according as we develop in the equations before, knowing or
estimating a αaerosol at this limit height, we can calculate the values of αa at any height
along the clear zone.
Figure 16: S function vs. height, in this graphic we can
observe two zones well define, the portion of clear sky and as
a big reflex ion the zone with cloud presence (RUN 1344 Los
Leones station).
For this propose we consider a method to calculate minimal height of a cloud layer.
The method consists in 1) calculate the derivative to the S function (see Figure 17)
applying a bin averaging chosen (we took a binavg. = 4); 2) consider the signal range in
which we analyze the presence of clouds, this is the range in which the S function has
acceptable error values, 3) put a threshold in the value of the maximum derivative
(according with different tests we chose dS = 0.5 ); 4) observing where the dS value is
evidence of
clouds at ≅
5Km height
linear function in
clear sky portion
18
superior to the threshold value and if this occur for some successive bins; 5) form a
vector with all the cases in which occur this, 6) do a comparison with the other
photomultipliers and take the coincidences, 7) take as cloud minimum height the
minimum value obtain in the coincidences.
Figure 17: derivative of S function (dS). The point line in blue
indicate the beginning of the cloud layer detected by the program, the
point line in red indicate the threshold use in the detection of the
cloud layer.
In order to repeat the calculation sequence for all the runs during a night, month, etc..,
we write a program in C++ named LDA2.cc, the one create an output file with diverse
information ( group of events, shoot angles, signal peak, minimum cloud height, etc…) .
Another program in C++ named histocloud2 make the different histograms and graphics
that represent the results of the night or month in consideration.
We took for our first test a cloudy night : the October 14, 2004 night (Los Leones
LIDAR station). Running LDA2 for the night (runs R2629 to R2649) the results (for all
the groups of events) are shown in Figure 18, the blue bars belong to the LIDAR range in
which is calculated the presence of clouds. We can obtain even a graphic of the cloud
height medium value for each run, during the same night (Figure 19).
As a clear night we analyze the October 10, 2004 night (Los Leones station). The
results are shown in Figure 20 . In Figure 21 a summary for all the data entries (October,
2004) and the respective cloud minimum height.
cloud layer
found at 5.4 Km
19
Figure 18: October 14 night, the blue bars represent the range in
which is calculated the presence of clouds, while the white points
represent the minimum height of the clouds, this is considering all
groups of events in the runs.
Figure 19: October 14, 2004 night, each point represent for each
run the cloud mean height, with the respective error bars.
20
Figure 20: October 10, 2004 night, showing just few points reveling
the cloud presence.
Figure 21: this histogram represent the proportion of cloud at
different altitudes height, taking as data all the events in October
2004 (Los Leones LIDAR station).
We represent even the LIDAR run data taking during all October month (see Figure
22), and the percent of cloud coverage sky according with the data obtain from our
software (see Figure 23)
In my thesis I will discuss the determination of cloud parameters during all the data
taking, the evaluation of the systematic error and its further development.
21
Figure 22: Run data taking during all October month, the
dark band represent the limit of the data acquisition during
twiglight time.
Figure 23: Percent of cloud coverage sky during October 2004(Los Leones station)
according with the data obtains with our method of the height layer cloud detection.
LIDAR run October 2004
% Cloud Coverage October 2004
0102030405060708090
100
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
bad weather
22
References
[1] V. Hess, Phys. Zs, 13, 1912, 1084.
[2] A. Filipcic , M. Horvat, D. Veberic , D. Zavrtanik , and M. Zavrtanik, Analysis of
Lidar Measurements at the Pierre Auger Observatory, (2002).
[3] Brian Fick , James Matthews, John Matthews, Rishi Meyhandan, Megan McEwen,
Miguel Mostafa, Michael Roberts, Paul Sommers, Lawrence Wiencke, The First Central
Laser Facility, Auger GAP 2004-003 (2003).
[4] Iztok Arcon, Andrej Filipcic, Marko Zavrtanik, Jozef Stefan, UV LIDAR System for
Atmospheric Monitoring and Cloud Detection, Auger GAP 99-028 (999).
[5] R. Cester, M. Mostafa, R. Musa, LIDAR Telescopes for Atmospheric Monitoring,
Auger GAP 2001-052 (2001). [6] A. Filipcic, M. Horvat, D. Veberic, D. Zavrtanik, M. Zavrtanik, Scanning Lidar
Based Atmospheric Monitoring for Fluorescence Detectors of Cosmic Shower, Auger
GAP 2003-001 (2003).
[7] Trio Motion Technology Ltd., Motion Coordinator Technical Reference Manual,
(1998).
[8] Antonio R. Biral, Analysis of the 2002 Malargüe LIDAR data through Fernald’s
Method, Auger GAP 2003-008 (2003).
[9] F. G. Fernald, Analysis of Atmospheric LIDAR Observations, Optical Society of
America, 1984.