Exploring Aerosol Optical Thickness Using MODIS Satellite Imagery in NEO

"Aerosol Optical Thickness is the degree to which aerosols prevent the transmission of light" in the atmoshpere.¹ "An aerosol optical thickness of less than 0.1 indicates a crystal clear sky with maximum visibility, whereas a value of 4 indicates the presence of aerosols so dense that people would have difficulty seeing the Sun, even at mid-day!" ²

The data are acquired by the MODIS sensor on the Terra and Aqua satellites. They are provided on the NEO web site as 1-day measurements and 8-day and 1-month composites.² The coverage is nearly global. ("Global over oceans, nearly global over land."³)
Note that aerosol optical thickness and aerosol optical depth (τ) are used interchangeably to describe this data set.¹ 

Sources: 
1. http://daac.gsfc.nasa.gov/PIP/shtml/aerosol_optical_thickness_or_depth.shtml
2. https://earthobservatory.nasa.gov/global-maps/MODAL2_M_AER_OD 
3. http://modis-atmos.gsfc.nasa.gov/MOD04_L2/index.html

There are many applications for aerosol optical thickness data:
"(1) Atmospheric correction of remotely sensed surface features
(2) Monitoring of sources and sinks of aerosols
(3) Monitoring of volcanic eruptions and forest fire
(4) Radiative Transfer Model 
(5) Air Quality 
(6) Health and Environment
(7) Earth Radiation Budget 
(8) Climate Change" ¹

"Aerosol particles are important to scientists because they represent an area of great uncertainty in their efforts to understand Earth's climate system. Depending upon their size, type, and location, aerosols can either cool the surface, or warm it. They can help clouds to form, or they can inhibit cloud formation. And if inhaled, aerosols can be harmful to people's health."²

This data can be used to teach or learn the following topics and skills in introductory Earth science:

- Effect of "windblown dust, sea salts, volcanic ash, smoke from fires, and pollution from factories" on the atmosphere ²
- Seasonal/Temporal variations in land-use
- Atmospheric circulation
- CO-aerosol optical thickness relationships
- CO-aerosol optical thickness relationships as they relate to forest fires, pollution, dust storms, and volcanic eruptions.

- Using data to make hypotheses about factors that may increase aerosol optical thickness
- Using data to make hypotheses about factors that influence the spatial and temporal distribution of aerosols in the atmosphere
- Using data to make visualizations of spatial and temporal changes in aerosol optical thickness
- Interpreting individual values, transects, vertical profiles, scatter plots, and multiple y-axis plots, and their representations on maps

The NEO site provides processed aerosol optical thickness data from the MODIS sensor in graphical and text formats from January 2005 to present. The data is available as JPEG, PNG, GeoTiff, GoogleEarth, and CSV formats. The data range from measurements of 0 to measurements of 1.² The data on the NEO site are available from both the Terra and Aqua satellites. (The Terra satellite began measuring this parameter in August 2000.⁴) Seven bands on the MODIS sensor (bands 1-7), as well as "a number of other bands to help with cloud and other screening procedures" are used to develop the aerosol optical thickness data set.5 The data are provided on the NEO web site as 1-day measurements and 8-day and 1-month composites.² The data set coverage is nearly global. ("Global over oceans, nearly global over land."³)

The data are provided as part of the MODIS level II aerosol product (MOD04 from the Terra satellite and MYD04 from the Aqua satellite). These daily "data are produced at the spatial resolution of a 10

The NEO interface makes it very easy to access data. From the NEO home page, users click on the 'Atmosphere' tab, and draw-down to the Aerosol Optical Thickness (MODIS) choice. The default data set is the 1-month Terra/MODIS data set. From there, select the month of interest.

Using the ICE (Image Composite Exploration) tool under the Analysis tab located within NEO, users can create a wide range of graphs and charts. For example, the data from two satellite images can be compared directly by plotting a transect (plotting data along a path) across an area of interest, creating a graph of data values along the transect. If a summary (an average) of the data in a particular area is desired, users can create polygon and the mean value within the polygon is then instantly calculated. Scatter plots and other 2- and 3-dimensional graphics are easily created.

NEO offers a variety of data exploration and analysis tools including simple visual exploration, visualization of graphical displays of the data, mathematical combinations of two or three data sets, and time-series animation. These capabilities exist within the ICE Tool which can be accessed from the NEO homepage by first selecting images with the same temporal resolution (same month) then clicking on the Analysis tab. Users do not have to leave the site to explore, plot, or analyze their data.

NEO—NASA Earth Observations
ICE—Image Composite Exploration
NASA—National Aeronautics and Space Administration
MODIS—Moderate-resolution Imaging Spectroradiometers
AOT—Aerosol Optical Thickness
AOD—Aerosol Optical Depth 
(Greek letter tau)—AOT or AOD
PM—particulate matter

"Prior to MODIS, satellite measurements were limited to reflectance measurements in one (GOES, METEOSAT) or two (AVHRR) channels. There was no real attempt to retrieve aerosol content over land on a global scale. Algorithms had been developed for use only over dark vegetation. The blue channel on MODIS, not present on AVHRR, offers the possibility to extend the derivation of optical thickness over land to additional surfaces. The algorithms will use MODIS bands 1 through 7 and 20 and require prior cloud screening using MODIS data. Over the land, the dynamic aerosol models will be derived from ground-based sky measurements and used in the net retrieval process."³


A good summary of the history of collection methods for AOT is provided by the NASA Earth Observatory:
Aerosol Optical Depth

On land: surface water such as coastal areas and marshes³
On land: surfaces with subpixel snow or ice cover³
satellite look angles⁴
density of vegetation cover⁴
wind speed⁶
cloud contamination⁶
aerosol microphysical properties⁶

Additional sources:
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2005JD006898

Other explanation of biases:
http://modis-atmos.gsfc.nasa.gov/MOD04_L2/index.html
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2005JD006898

http://modis.gsfc.nasa.gov/data/atbd/atbd_mod02.pdf
http://modis-atmos.gsfc.nasa.gov/MOD04_L2/index.html

"Validation of MODIS aerosol observations over the Netherlands with GLOBE student measurements" by Boersma and de Vroom, JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 111, D20311, doi:10.1029/2006JD007172, 2006 (http://www.agu.org/pubs/crossref/2006/2006JD007172.shtml)

1. http://modis-atmos.gsfc.nasa.gov/MOD04_L2/index.html is a page on the MODIS Atmosphere web site to specifically discusses the MODIS Aerosol Products (monitors aerosol type, aerosol optical thickness, particle size distribution, aerosol mass concentration, optical properties, and radiative forcing).
2. Comparison of aerosol optical thickness measurements by MODIS, AERONET sun photometers, and Forest Service handheld sun photometers in southern Africa during the SAFARI 2000 campaign (International Journal of Remote Sensing Vol. 26, No. 19, 10 October 2005, 4169-4183) is an article that addresses the differences between satellite versus ground truth measurements for aerosol optical thickness.
3. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod02.pdf "ALGORITHM FOR REMOTE SENSING OF TROPOSPHERIC AEROSOL FROM MODIS: Collection 5" is an article produced by NASA explaining how to raw satellite data is converted into useable atmospheric values.
4. https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2005JD006898 "MODIS aerosol product analysis for data assimilation: Assessment of over-ocean level 2 aerosol optical thickness retrievals" (JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 111, D22207, doi:10.1029/2005JD006898, 2006) is an article that discusses some of the biases that occur in the aerosol optical thickness data set. 
5. http://vortex.nsstc.uah.edu/~sundar/papers/2003/grl_pm2.5_submit.pdf Wang, J., and S. A. Christopher (2006). Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies. Geophysical Research Letters, 30(21) looks at whether satellite AOT data can be used quantitatively to estimate air quality.

Other related links are sprinkled through out the datasheet.