Mark Broomhall

Validation of Aerosol Retrievals from Satellite Measurements

MarkBroomhall
University
Curtin University
Supervisor (Academic)
Dr Mervyn Lynch & Dr Stefan Maier
Projects
mysite
Employment
Scientific programmer at Department of Physics and Astronomy, Curtin University
Thesis Abstract

Aerosol optical depth (AOD) retrieved from satellite data remains one of the most uncertain inputs to the atmospheric compensation process for estimating surface reflectance. The key issue is finding a robust way to estimate the surface reflectance for the wavelength or bands that will be used to derive an estimate of the AOD. The AOD retrieval method presented in this dissertation, called the Reflectance Change (RC) method, uses reflectance predictions (FR) from a Bidirectional Reflectance Distribution Function (BRDF) model and an observed surface reflectance (Rc), which is produced using a fixed AOD amount. These parameters are used to calculate a reflectance change product on a pixel by pixel basis.

RC = Rc − FR. (1)

Radiative transfer code is used to model the RC for a range of conditions. A series of lookup tables are produced using MODTRAN4. These lookup tables contain top of atmosphere reflectance entries for a number of values of view zenith, solar zenith, relative azimuth, surface reflectance and AOD amounts at 550 nm. All other atmospheric constituents are kept constant. A lookup table entry is selected using the view and solar geometries for the overpass and an estimate of the surface reflectance using the FR. This gives a set of Top Of Atmosphere (TOA) reflectance values for a number of AODs. The TOA reflectance value for the initial fixed AOD value (used in the production of the initial surface reflectance product) is then used construct a list of reflectance change values for changes in AOD. The RC is then compared to the list of reflectance change values and interpolated between the closest matches to give a change in AOD for the input RC.
The AOD is then derived by adding the change in AOD to the initial fixed value. This process was investigated for MODIS bands 1 - 5 and 7 but only data for bands 3 and 5 are discussed in this dissertation as these bands have the most sensitivity to change in the AOD level for specific ranges of surface reflectance values.

The derived AOD at 550 nm has been compared against the MOD04 and Deep Blue retrieval algorithms (Collection 4) using in-situ sun photometer data as ’the truth’ at a number of Australian sites. The Lake Argyle site produced the best results with RMS error values (0.0807, 0.0864, 0.0665) and r2 values (0.3043, 0.4409, 0.6845) for MOD04, Deep Blue and the RC algorithm respectively. The poorest quality results occurred at the Tinga Tingana site with RMS error values (0.2655, 0.2268) and r2 values (0.0523, 0.0002) for Deep Blue and band 3 RC retrievals respectively. Conversely, using band 5 RC information from Tinga Tingana the RMS error and r2 values for comparison of AOD at 550 nm were 0.0943 and 0.2791 respectively. This produced better results over bright targets than using RC information from MODIS band 3.

Approximately 2 years of RC data were compared with in-situ sun photometer data over 5 Australian sites. The results were mixed, but better results were achieved at the sites with the greater coverage of green vegetation (Lake Argyle and Jabiru) with the poorest results at the desert sites of Birdsville and Tinga Tingana. The AOD retrievals from the RC algorithm have been shown to be comparable to MOD04 and Deep Blue which shows the potential of the RC algorithm and should encourage further development.