Shaunna Donaher
MPO 531 Final Project
April 22, 2008
 To design a lesson plan describing the AErosol
RObotic NETwork, the instrumentation used and the
science involved and create a class project to use actual
data to connect to meteorology.
 Lesson
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Introduction to AERONET
Instrumentation
Background science
AERONET locations
 Class Project
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CRYSTAL-FACE
Data Access
Instructions
Assignment/Answers
 The AERONET (AErosol RObotic NETwork) program
is a federation of ground-based remote sensing aerosol
networks collaborated on by national agencies,
institutes, universities, individual scientists, and
partners.
 The program provides a long-term, continuous and
readily accessible public domain database of aerosol
optical depth, microphysical and radiative properties
for aerosol research and characterization, validation of
satellite retrievals, and synergism with other
databases.
 Suspended particles in the atmosphere
 Ranging in size from a few molecules to tens of
micrometers
 Our main interest is aerosols with 0.1<r<20 μm
 1.0 μm is an approximate separation between “fine”
and “course” aerosols
(AOD or τ)
 The integral of the light extinction by aerosols within
an atmospheric column
 Related to aerosol size distribution
 A larger optical depth is related to a thicker
layer/cloud, i.e. more extinction (and vice versa)
 AERONET collaboration provides globally distributed
observations of
 spectral aerosol optical depth (AOD)
 inversions
 precipitable water
 The network imposes standardization of instruments,
calibration, processing and distribution.
 Aerosol optical depth data are computed for three data
quality levels:
 Level 1.0 (unscreened)
 Level 1.5 (cloud-screened)
 Level 2.0 (cloud screened and quality-assured)
Which of the 3 levels would you use to have the
highest confidence in your data set?
Sun photometer system
 The Cimel Electronique 318A spectral radiometer is a
solar-powered, weather-hardy, robotically-pointed sun
and sky spectral sun photometer.
 A sensor head points the sensor head at the sun
according to a preprogrammed routine.
 The Cimel controller, batteries, and Vitel
satellite transmission equipment are usually
deployed in a weatherproof plastic case.
Cimel Spectral Radiometer
 The radiometer makes two basic measurements-either
direct sun or sky-both within several programmed
sequences.
 The direct sun measurements are made in eight spectral
bands requiring approximately 10 seconds
 at wavelengths of 340, 380, 440, 500, 670, 870, 940 and 1020
nm
 the 940 nm channel is used for column water abundance
determination
 A preprogrammed sequence of measurements is taken by
these instruments from 7 am-7pm daily.
Solar radiation
Absorption is the process by
which incident radiant energy
is retained by a substance (i.e.
the atmosphere)
In the solar spectrum some wavelengths have high transmittance and others have high
absorption. These wavelengths are taken advantage of when designing
instrumentation. Instruments transmit at a certain wavelength knowing how much will
be absorbed by a normal atmosphere.
 Optical depth is calculated from spectral extinction of
direct beam radiation at each wavelength based on the
Beer-Lambert-Bouger Law. Attenuation due to
Rayleigh scatter, and absorption by ozone, and gaseous
pollutants is estimated and removed to isolate the
aerosol optical depth (AOD). A sequence of three such
measurements are taken 30 seconds apart creating a
triplet observation per wavelength.
 Relates the absorption of light to the material the light
is traveling through.
 The law states that there is a logarithmic dependence
between the transmission (or transmissivity) of light
through a substance and the product of the absorption
coefficient of the substance, and the distance the light
travels through the material (i.e. the path length).
*Also known as Beer-Lambert-Bouger Law, Beer-Lambert Law, Beer-Bouger Law
For gases
T= I1/I0= 10-αι= 10-ειc
Absorbance
A=-log10 (I1/I0)
transmissivity (T)
absorption coefficient (α)
path length (ι)
molar absorptivity of the absorber (ε)
concentration of absorbing species in the material (c)
absorption cross section (σ)
density of absorbers (N)
The scattering of light by particles much smaller than
the wavelength hitting them.
Small size parameter approximation:
x=2π/λ
Rayleigh scattering occurs when x << 1
 Although the concentration of the ozone in the ozone layer is very small, it is vitally
important to life because it absorbs biologically harmful ultraviolet (UV) radiation
emitted from the Sun.
 UV radiation is divided into three categories, based on its wavelength: UV-A, UV-B,
and UV-C
 UV-C, which would be very harmful to humans, is entirely screened out by ozone at
around 35 km altitude.
 The ozone layer is very effective at screening out UV-B; for radiation with a
wavelength of 290 nm, the intensity at Earth's surface is 350 billion times weaker than
at the top of the atmosphere.
 In addition to the direct solar irradiance measurements
that are made with a field of view of 1.2 degrees, these
instruments measure the sky radiance in four spectral
bands (440, 670, 870 and 1020 nm) along the solar
principal plane (i.e., at constant azimuth angle, with varied
scattering angles) up to nine times a day and along the
solar almucantar (i.e., at constant elevation angle, with
varied azimuth angles) up to six times a day.
 The approach is to acquire aureole and sky radiances
observations through a large range of scattering angles
from the sun through a constant aerosol profile to retrieve
size distribution, phase function and aerosol optical depth.
During the large air mass periods direct sun
measurements are made at 0.25 air mass intervals,
while at smaller air masses the interval between
measurements is typically 15 minutes. The time
variation of clouds is usually greater than that of
aerosols causing an observable variation in the triplets
that can be used to screen clouds in many cases.
Additionally the 15-minute interval allows a longer
temporal frequency check for cloud contamination.
 Sun Photometers absorb direct sunlight energy with an LED light
and convert the intensity into a quantified voltage to measure
aerosols in the atmosphere.
 The intensity of sunlight at the top of the earth's atmosphere is
constant. While the sunlight travels through the atmosphere,
though, aerosols can dissipate the energy by scattering
(Rayleigh) and absorbing the light. More aerosols in the
atmosphere cause more scattering and less energy transmitted to
the surface.
 Knowing the sunlight's energy at the top of the atmosphere, the
thickness of the atmosphere, and the amount of sunlight
transmitted to the earth's surface and can allows us to determine
the amount of scattering, and thus, the amount of aerosols.
http://calipsooutreach.hamptonu.edu/sunphotosim/sunphotometer.html
 Click on LAUNCH
 You can vary sun angle, atmospheric pressure,
haziness, and particle size to see impact on green
channel and red channel sun voltage, and aerosol OD.
 Atmospheric Conditions - Level of haze due to aerosols.
 Sun Angle (Degrees) - (90 degrees is straight overhead)
Decreased sun angle early and late in the day increases the
amount of atmosphere that the light from the sun passes
through before reaching sun photometer.
 Air pressure - Changes in air pressure (due to altitude or
weather systems) change the density of the air. A decrease
in air pressure (decrease in air density) causes less light to
be scattered by air molecules and increases the amount of
light reaching the sun photometer.
 Particle size - The relative scattering of red vs. green light
by aerosol particles is dependent on the particle size.
 The changes in output voltage caused by aerosols can
sometimes be very small. So, it is important to calibrate
sun photometers carefully. Basically, this involves
inferring what the sun photometer would see if there
were no atmosphere between its detector and the sun.
From the ground, this calibration is done by looking at
the sun through varying amounts of atmosphere and
using a mathematical model to predict what would
happen to the output voltage if the atmosphere suddenly
disappeared.
This is time consuming and expensive!!
 Satellite
 Data are transmitted hourly or half hourly from the memory
of the sun photometer microprocessor via the Data Collection
Systems (DCS) to either of three geosynchronous satellites
GOES, METEOSAT or GMS and then retransmitted to the
appropriate ground receiving station.
 Internet
 Data may be downloaded automatically from the Cimel sun
photometer and stored on the local computer. This computer
can run software to automatically transfer K7 files to the
AERONET processing system through the Internet.
Alternatively, users may download K7 files manually from the
instruments using a PC or laptop and manually submit these
files to the processing system.
 Once collected, AERONET data is post-processed with
4 algorithms
 Aerosol Optical Depth (AOD) retrieval
 AOD cloud screening
 Seaprism processing
 Sky Radiance data (Almucantars and Principal Planes)
inversion
 Then it is stored online and access is available to
anyone
• Aerosol Optical Depth (AOD)
• Sun photometer measurements of the direct solar radiation provide
information to calculate the columnar aerosol optical depth (AOD).
• AOD can be used to compute columnar water vapor (Precipitable Water)
and estimate the aerosol size.
• Aerosol Inversions
• Inverting sun photometer radiance measurements produces aerosol
optical properties such as size distribution, single scattering albedo, phase
functions, and the complex index of refraction.
• Solar Flux
• High frequency solar flux calculations. A companion to AERONET.
• Ocean Color
• A new network component called AERONET – Ocean Color (AERONET-
OC). Provides the additional capability of measuring the radiance
emerging from the sea (i.e., water-leaving radiance) with modified sunphotometers installed on offshore platforms like lighthouses,
oceanographic and oil towers.
• AERONET-OC is instrumental in satellite ocean color validation activities
through standardized measurements a) performed at different sites with a
single measuring system and protocol, b) calibrated with an identical
reference source and method, and c) processed with the same code.
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Year(s): Project
1993-1995: Smoke/Sulfates, Clouds And Radiation (SCAR)
1996: Tropospheric Aerosol Radiative Observational eXperiment (TAROX)
1997: The Zambian International Biomass Burning Emissions Experiment (ZIBBEE)
1997: North Atlantic Regional Aerosol Characterization Experiment (ACE-2)
1998-1999: Indian Ocean Experiment (INDOEX)
2000: SAFARI
2000-2001: Argentine Commission on Space Activities (CONAE)-SAC-C
2001 : Asian-Pacific Regional Aerosol Characterization Experiment (ACE-Asia)
July-August 2001: Chesapeake Lighthouse & Aircraft Measurement for Satellites (CLAMS)
2003 – Present: Base Asia - Thailand
2004-Present : African Monsoon Multidisciplinary Analysis (AMMA)
2004: United Arab Emirates Unified Aerosol Experiment (UAE2)
2005-Present : Atmospheric Brown Cloud (ABC)
2006: Megacity Aerosol Experiment in Mexico City (MAX-MEX)
2007: CALIPSO and Twilight Zone (CATZ) - Ground-based Validation
2008-2011 :TIGERZ (India)
 Using AOD data from CRYSTAL-FACE
 What is CF?
 Data Download Process
 Data Analysis Tips
 Assignment
 Possible answers to assignment
 Field experiment designed to investigate tropical cirrus
cloud physical properties and formation processes.
 The primary target region is southern Florida and the
surrounding waters where deep convection is known to
occur frequently in July.
 Instrumented sites that include multi-frequency millimeter
radar, lidar, and radiometry will be located at two
locations.
 A site situated on the southwest coast will allow sampling of
the cirrus outflow from diurnally forced convection.
 Also, a site will be located in southeastern Florida where
cirrus from maritime disturbances and local convection will
be observed.
 We will be using data from July 2002 from the
CRYSTAL-FACE East Site
 In left column, click on Download Tool under Aerosol
Optical Depth
 Click on map a couple of times to zoom in on South
Florida
 Then click on CRYSTAL_FACE (25N,80W) under the
map
 Version 2 Direct Sun Algorithm
 Start Date
1 Jan 2002
 End Date
31 Dec 2002
 Choose Level 2.0 for AOD w/
Precipitable Water
 Choose Single File for
Instrument Information
 Choose Level 2.0 for Total
Optical Depth
 Choose Level 1.5 for AOD
Modes
 Choose All Points for Data
Format
You should be on a page that looks like this
 Click Download
 Accept Conditions
 Save .zip file as 020101_021231_CRYSTAL_FACE
 Use a file extractor to unzip files
 In Windows, simply right click on zipped folder, choose Extract All,
and go through the Extraction Wizard. This will create a new folder
with the 4 unzipped files. (If you still need help, check out the Data
File Help Page at
http://aeronet.gsfc.nasa.gov/new_web/file_help.html).
 Once files have been unzipped, open a spreadsheet program (i.e.
MS Excel). Go to File and Open. Choose the LEV20 file (you may
have to change type to all files to see them).
 Choose Delimited as your data type, then Comma (or tab if columns
don’t show up when you scroll down) as your delimiter.
 Make sure the first column is in Date Format (DMY)- this will work
with Tot20 file, not other 2)
 Repeat with each data file (you should have 3 in total:
Lev20, Oneil_15, and Tot20)- don’t worry about
Solar_Info
 Save each file as an Excel Workbook
 For help with column header meaning and units, visit
http://aeronet.gsfc.nasa.gov/new_web/units.html
 Part 1: Familiarizing yourself with the data
 Using the Tot20 file, you will see that there are several variables
listed for each wavelength. What are they?
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Total Aerosol Optical Depth
Aerosol Optical Depth
Aerosol Optical Depth due to Rayleigh scattering
Aerosol Optical Depth due to O3
Aerosol Optical Depth due to NO2
Aerosol Optical Depth due to CO2
Aerosol Optical Depth due to CH4
Aerosol Optical Depth due to Water Vapor
 Now choose all of the variables for the 1020 nm wavelength except
for the total aerosol optical depth. Create a new column in your
worksheet summing them up. What variable does your new column
equal? What does this tell you about optical depth? (that total
optical depth is the sum of each individual optical depth)
 Also you will see that some wavelengths are not applicable for this
site. What are they?
 1640, 667, 555, 551, 532, 531, 490, 443, 412 (all in nm)
 Now open the Lev20 file. You may have noticed when saving it
that the date function did not convert properly (things don’t
always go smoothly with data processing and analysis!). Also, it is
challenging to combine dd-mm-yy with hh-mm-ss format for
graphing purposes (especially if your data set covers more than
100 years and is not in yyyy format). For that reason, we often
use Julian Day (technically day of year since Jan. 1st at 12:00 am).
This is really useful when dealing with data taken within one year
(or one month as in our case).
 Convert 195.521354 JD to dd-mm-hh-mm-ss. Assume that it is not a leap
year. Show work. 14-07-12-30-45
 Convert 23-04-07-28-30 (Apr 23 at 7:28:30 AM) to Julian Day. Assume
that it is not a leap year. Show work. 113.3114583
195-31 (Jan)-28 (Feb)-31 (Mar)-30 (Apr)-31 (May)-30
(June)=14 (July 14th)
.521354*86400 seconds=45044.9856 seconds
45044.9856/60=750.74976 minutes
750.74976/60=12.512496 hours (12 hours)
.512496*60=30.74976 (30 minutes)
.74976*60=44.9856 (45 seconds)
31 (Jan)+28 (Feb)+31 (Mar)+23 (Apr)=113
Convert 7 hrs into seconds: 7*60*60=25200
25200+28*60=26880+30=26910
26910/86400 seconds in a day=.3114583
113.3114583
 Part 2: Data Analysis
 Using the Tot20 file, plot the total AOD for each wavelength
by JD all on the same plot. What do you notice? (the smaller
wavelengths see higher optical depths). Why do you think
this is? (Aerosol optical depths typically decrease with
increasing wavelength)
1.8
1.6
1.4
AOT_1020-Total
1.2
AOT_870-Total
1
AOT_675-Total
0.8
AOT_500-Total
AOT_440-Total
0.6
AOT_380-Total
0.4
AOT_340-Total
0.2
0
180
185
190
195
200
205
210
215
 Continuing with the Tot20 file, plot the total AOD for 1020 nm
vs. JD. Do you notice any trend over the month? (Not really,
maybe a slight decrease) Now plot the AOD due to Rayleigh
scattering for the same wavelength vs. JD. Is there a trend in this
plot? If so, what is it and why do you think it is occurring? Hint:
You may want to plot the time trends of other variables. (Yes, it is
increasing with time. You could suggest that this is due to
changes in relative humidity, but water vapor AOD plot does not
confirm this. It actually winds up mimicking the trend in
pressure. The AMS glossary states that Rayleigh optical depth is
directly proportional to surface pressure).
AOT_1020-Total
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
AOT_1020-Rayleigh
0.00807
0.00806
0.00805
AOT_1020-Total
0.00804
AOT_1020-Rayleigh
0.00803
0.00802
180
190
200
210
220
0.00801
180
190
200
210
220
 Now let’s look at the Lev20 file. Plot JD vs. water AOD.
Find the lowest water AOD. What is it and what day
does it occur? 3.111052 cm at 208.963958= 7/27/2002.
Now find the highest water AOD? What is it and what
day does it occur? 5.108539 cm at 197.884711=7/16/2002
AOT_1020-Water
0.014
0.012
0.01
0.008
AOT_1020-Water
0.006
0.004
0.002
0
0:00:00
4:48:00
9:36:00
14:24:00
19:12:00
0:00:00
4:48:00
 We are going to look at back trajectories of air masses
to try to determine what caused the difference in water
AOD.
Go back to the Aeronet Web Page
Click on Data Synergy Tool at the top
Click Access Data Synergy Tool
On map at left select Back Trajectory
Zoom in on S. FL. Then click on Dry_Tortugas below
map
 On the new page, under Surface Data check Aeronet and
Under Model Output click Back Trajectory
 Put in the two 2 dates at the calendar in the lower left
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 Using the Lev20 file still, plot JD and Solar Zenith
Angle. What does this suggest to you about the hours
the sun photometer was running? (mostly started
around noon (90 degrees) and ran until later in the
day. This is confirmed by looking closely at JD.)
Solar_Zenith_Angle
90
80
70
60
50
Solar_Zenith_Angle
40
30
20
10
0
180
185
190
195
200
205
210
215
 Now we are going to use the ONeill_15 file for λ=500 nm. Make plots of
 JD vs. total, fine and coarse aerosol OD
 JD vs. standard deviation of total aerosol OD
 Std of fine aerosols vs. std of coarse aerosol OD
 Looking at the plot of total, fine and coarse aerosol optical depths,
what kind of statement(s) can you make about the dominating
aerosols? (There isn’t a big difference between numbers of the two
types most of the time. But there are six cases where the coarse aerosol
OD dominates the total AOD. These could be from strong sea breezes
bringing salt aerosols inland. Also in the middle of the period, there is
a slight increase fine aerosol OD.) Do you think this plot represents an
influence of African dust at any point? Why or why not? (Possibly. The
fine aerosols in the middle of July could be from Saharan dust. Any
answer is OK here as long as it is backed up.)
4.5
4
3.5
3
2.5
AOD_500nm-Total
AOD_500nm-Fine
2
AOD_500nm-Coarse
1.5
1
0.5
0
180
185
190
195
200
205
210
215
 Now look at the plots of standard deviation. Does this
support your conclusion about African dust above? (Could
suggest that the increase in variation in the middle of the
month may be due to an influence of African dust bringing
in more fine particles than normal.) The plot comparing
the two standard deviations has an interesting structure.
What does this suggest to you about the air masses that
were affecting S. FL. during July 2002? (The linear plot
suggests that the air masses typically brought in the same
relationship of fine and coarse particles to S. FL. all month
long. As the variance of AOD for fine particles increased, so
did the variance of AOD for coarse particles and vice versa.
Even the outliers follow the linear pattern).
AOD_500nm_Std-Total
0.012
0.01
0.008
0.006
AOD_500nm_Std-Total
0.004
0.002
0
180
185
190
195
200
205
210
215
AOD_500nm_Std-Coarse
0.3
0.25
0.2
0.15
AOD_500nm_StdCoarse
0.1
0.05
0
0
0.1
0.2
0.3
 This lecture and tutorial are designed to expose undergraduate
students to remote sensing of aerosol properties.
 During the lecture, they will learn about sun photometers and see a
brief explanation of the physics behind light absorption in the
atmosphere.
 The assignment should familiarize students with field experiments and
data management techniques. Students will have to read literature to
determine which variables they are being asked to use. They will have
to connect the physical data to meteorological processes to come up
with a real-world understanding of what the data represents.
 Unfortunately, the goal of including back trajectory analysis does not
work for this site. If the assignment is modified for another site, than
slide 50 could be potentially be used and that question included in the
assignment.
 Obviously, some of this material is advanced and is best
presented towards the end of the semester. Certain slides (i.e.
slides 19 and 20) pertain more towards Physical Meteorology
topics and you may choose to remove them for an
instrumentation class where the focus is on data collection and
manipulation.
 The instructions for data access are very explicit, but beyond that
students should be able to figure out which variables they need
to use and which column those variables are located in. They will
also need to figure out how to plot in Excel and hand in
professional, labeled figures.
 Some of the assignment questions have exact answers, while for
others there will be a wide range of acceptable answers. For the
latter credit should be given as long as students show intelligent
thought processes backed with scientific reasoning.
 http://aeronet.gsfc.nasa.gov/new_web/index.html
 http://en.wikipedia.org/wiki/Beer-Lambert_law
 http://teaching.shu.ac.uk/hwb/chemistry/tutorials/molspec/beers1.htm
 http://en.wikipedia.org/wiki/Rayleigh_scattering
 http://encyclopedia.thefreedictionary.com/Ozone%20layer
 http://www.cem.msu.edu/~reusch/VirtTxtJml/Spectrpy/UV-
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Vis/spectrum.htm
http://www.everythingweather.com/atmospheric-radiation/index.shtml
http://www.pages.drexel.edu/~brooksdr/DRB_web_page/Aerosols/intro_to.ht
m
http://calipsooutreach.hamptonu.edu/sunphoto-sim/sunphotometer.html
http://www.espo.nasa.gov/crystalface/
http://amsglossary.allenpress.com/glossary/search?id=optical-depth1
Levy, R. C., and R. T. Pinker, 2007: Remote sensing of spectral aerosol
properties: A classroom experience. Bull. Amer. Met. Soc., 25-30.