Dust Aerosols (including non-sphericity effects)

Background:
Dust affects visibility, human health, and the Earth energy budget. However, modeling of dust distribution and quantification of its radiative effects are difficult, simply because ground-based measurements for dust aerosols are limited in both space and time.

The satellite measurements have been considered as one of the best tools to characterize the high spatial-temporal variations of aerosols. However, the current dust retrievals from satellite measurements have large uncertainties, mainly because dust particles are non-spherical, and their phase functions can not be calculated/treated properly.

Goals:
Some of the goals of this project include a) Detecting dust aerosols using
satellite remote sensing data, b) Using insitu and ground based data to examine
microphysical properties, c) Retrieve aerosol optical depth from satellite data and
radiative transfer calculations and d) estimate the radiative forcing on regional
climate, e) address non-sphericity issues in calculations.

Figure 1. GOES-8 ch1 enhanced image on 19:31 UTC, July 21 2000. Heavy dust is transported from Africa to the east coast of Unite Stated. The figure describes the heavy dust plumes around the Puerto Rico. The sharp contrast between bright dust pixels with the dark background ocean pixels is very obvious in this image. Some cloud that mixed in the dust layer are also clear. Figure 1 shows dust aerosols transported from the Sahara and now over the Puerto Rico region. The figure to the right shows the non-spherical nature of dust particles.

Our research work

* Using multi spectral and spatial techniques we first identify dust aerosols. We then use a
radiative transfer model to calculate the optical thickness of each pixel identified as dust.
* We then compare the GOES-8 retrieved aerosol optical thickness with sunphotometer measurements made at the ground.
* We also compared the satellite retrieved values with aircraft derived AOT values.
* Our analysis shows the Geostationary data can be used to successfully detect dust aerosols and retrieve aerosol optical thickness. These aerosol retrievals can be used in studies that attempt to model the role of aerosols on regional and global climate.
* The comparison showed that GOES-8 retrieved AOT are in good agreement with the SP derived values, with linear correlation coefficient of 0.91 and 0.80 for the two sites.
* The linear correlation between the GOES-8 retrieved AOT and the aircraft derived value from particle probe data and AATS-6 measurements were 0.88 and 0.83 respectively.
* Sensitivity studies showed that the uncertainties (Dt) of the GOES-8 retrieved AOT values were mainly from the uncertainties due to the imaginary part of refractive index (Dt= ?0.05) and surface reflectance [Dt=?(0.02~0.04)].
* This paper demonstrates the application of geostationary satellites to detect and retrieve dust AOT even at low to moderate AOTs.
* The GOES-8 imager also captures aerosol diurnal variation that can further reduce the uncertainties in the current aerosol forcing estimations caused by the high temporal variations of AOT.
* In the next step we use the GOES-retrieved dust aerosol optical thickness and compute the shortwave aerosol radiative forcing both at the TOA and at the surface during PRIDE.
* Results of this study show that the calculated direct, diffuse and total DSWI are in excellent agreement with the corresponding ground measurement values with biases of 1.8%, -3.3% and 0.5% respectively indicating that dust aerosols are well characterized in the radiative transfer model. This is well within the measurement (1.3%) and model uncertainties (5%).
* Measured dust size distribution (from 3 different sizers) and aerosol light scattering/extinction coefficients (from 3 Nephelometers) are combined together to infer the aerosol effective refractive index, and constrain aerosol properties in the retrievals. Inferred refractive index for dust particles is 1.53-0.0015i, and single scattering albedo is about 0.97~0.98.
* Dust samples were collected from the aircraft measurements and then analyzed through the scanning electronic monograph (SEM). A statistical mode for dust morphologies is created based on the SEM analysis of 60, 500 particles. The model uses 6 size intervals and 15 aspect ratios (1.2~10) to describe the dust size and shape. In this study, we assume dust particles are oblate spheroid. The aerosol optical properties are then computed through the T-matrix calculations.

For further information

Christopher, S.A., J. Wang, Q. Ji and S-C. Tsay, Estimation of Shortwave Dust Aerosol Radiative forcing during PRIDE, J. Geophys. Res., 108(D19), 8956, doi:10.1029/2002JD002787, 2003, (pdf file)

Wang, J., X. Liu, S. A. Christopher, J. S. Reid, E. Reid, and H. Maring, The effects of non-sphericity on geostationary satellite retrievals of dust aerosols, Geophys. Res. Lett., 30(24), 2293, doi:10.1029/2003GL018697, 2003 (pdf file).

Wang, J; Christopher, S. A.; Reid, J.S.; Maring, H.; Savoie, D.; Holben, B.N.; Livingston, J. M.; Russell, P. B.; Yang, S-K., GOES 8 retrieval of dust aerosol optical thickness over the Atlantic Ocean during PRIDE, J. Geophys. Res. Vol. 108, No. D19, 8595, 10.1029/2002JD002494, (pdf file).