Figure 1: Severe Dust Storm in Beijing, XiangHe and Bohai Sea on 17th April 2006,where (a) MODIS Terra RGB: 143 composite, (b) SARA retrieved AOD at 500m, (c) MODIS DT AOD at 10 km, (d) MODIS DB AOD at 10 km (adopted from Bilal et al., 2014)
Aerosols are suspended particles in the atmosphere and vary with size and volume. Aerosols emitted from anthropogenic and natural activities are associated with public health, hydrological cycle, Earth’s climate, and atmospheric visibility. For understanding of aerosols, accurate and reliable spatio-temporal measurements of aerosol optical properties such as aerosol optical depth (AOD) are required from local to global scales. The AErosol Robotic NETwork (AERONET) has been providing regular measurements of cloud–screened and quality–assured AOD at higher temporal (every 15 min) and spectral (0.340–1.060 µm) resolutions, but at a limited spatial resolution. This spatial limitation is overcome by satellite remote sensing which provides near–real time global AOD observations.
This post is related to evaluation of the MODerate resolution Imaging Spectroradiometer (MODIS) aerosol retrieval algorithms including the Dark–Target (DT) algorithm [Levy et al., 2013], the Deep–Blue (DB) algorithm [Hsu et al., 2013], and the Simplified Aerosol Retrieval Algorithm (SARA) at 500 m resolution [Bilal et al., 2013] during extreme dust storm and haze events. For reliable aerosol retrievals, accurate method for the estimation of surface reflectance is perhaps the most crucial component.
The DT algorithm estimates the surface reflectance based on the ratio of visible and shortwave infrared channels as a function of a vegetation index and scattering angle. The DT algorithm retrieves AOD only over dark-target surfaces having reflectance between 0.01 and 0.25 in the mid–infrared channel (2.21 µm), and is unable to retrieve AOD over bright surfaces including snow/ice, desert and urban surfaces with reflectance > 0.25 in 2.21 µm channel. The DT AOD observations are available for land and ocean surfaces at 3 km and 10 resolutions [Levy et al., 2013].
The DB algorithm utilizes deep blue (0.412 µm) wavelength, where surface reflectance is lower than for longer wavelength, for AOD retrieval. The surface reflectances are estimated for 0.412, 0.47 and 0.65 µm wavelengths using minimum reflectance technique. The DB algorithm retrieves AOD over all bright surfaces including desert and urban surfaces, except snow/ice, as well as for dark surfaces. The DB AOD observations are available only for land surfaces at 10 km resolution [Hsu et al., 2013].
The SARA algorithm utilizes the surface reflectance from the MODIS operational surface reflectance product (MOD09) available at 500 m resolution. The SARA algorithm retrieves AOD at 500 m resolution directly for singe channel without constructing a comprehensive look–up–table (LUT) based on radiative transfer model. As the SARA algorithm does not have prior knowledge of aerosol types over the region, this algorithm iterates a wide range of aerosol types and conditions to retrieve AOD [Bilal et al., 2013].
Recent studies reported that the DT and DB algorithm are unable to retrieve AOD in the presence of extreme dust storm (coarse aerosol particles) (Figure 1) [Bilal et al., 2014] and haze (fine aerosol particles) (Figure 2) [Bilal and Nichol, 2015] over Beijing–Tianjin–Hebei region due to their limitations for pixel selection criteria and aerosol model schemes used in the LUT. On the other hand, the SARA algorithm has ability to retrieve AOD and represent the true picture of atmospheric pollutants during extreme dust storm and haze pollution events over the region.
Figure 2: Haze event over the Beijing-Tianjin-Hebei region on 5th October 2013: a) Band 4 pseudo color image, b) SARA AOD (500 m), c) MYD04 DT C6 (10 km), and d) MYD04 DB C6 AOD (10 km) (adopted from Bilal and Nichol, 2015).
Bilal, M., J. E. Nichol, M. P. Bleiweiss, and D. Dubois (2013), A Simplified high resolution MODIS Aerosol Retrieval Algorithm (SARA) for use over mixed surfaces, Remote Sens. Environ., 136, 135–145, doi:10.1016/j.rse.2013.04.014.
Bilal, M., J. E. Nichol, and P. W. Chan (2014), Validation and accuracy assessment of a Simplified Aerosol Retrieval Algorithm (SARA) over Beijing under low and high aerosol loadings and dust storms, Remote Sens. Environ., 153, 50–60, doi:10.1016/j.rse.2014.07.015.
Bilal, M., and J. E. Nichol (2015), Evaluation of MODIS aerosol retrieval algorithms over the Beijing-Tianjin-Hebei region during low to very high pollution events, J. Geophysical. Res. Atmos., 120, doi: 10.1002/2015JD023082.
Hsu, N. C., M.-J. Jeong, C. Bettenhausen, A. M. Sayer, R. Hansell, C. S. Seftor, J. Huang, and S.-C. Tsay (2013), Enhanced deep blue aerosol retrieval algorithm: The second generation, J. Geophys. Res. Atmos., 118, 9296–9315, doi:10.1002/jgrd.50712.
Levy, R. C., S. Mattoo, L. A. Munchak, L. A. Remer, A. M. Sayer, F. Patadia, and N. C. Hsu (2013), The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6(11), 2989–3034, , doi:10.5194/amt-6-2989-2013.
About this post: This is a guest post by Dr. Muhammad Bilal Sheikh. Learn more about this blog’s authors here.