Remote sensing of mineral dust aerosol using AERI during the UAE: A modeling and sensitivity study

[1] Numerical simulations and sensitivity studies have been performed to assess the potential for using brightness temperature spectra from a ground-based Atmospheric Emitted Radiance Interferometer (AERI) during the United Arab Emirates Unified Aerosol Experiment (UAE) for detecting/retrieving mineral dust aerosol. A methodology for separating dust from clouds and retrieving the dust IR optical depths was developed by exploiting differences between their spectral absorptive powers in prescribed thermal IR window subbands. Dust microphysical models were constructed using in situ data from the UAE and prior field studies while composition was modeled using refractive index data sets for minerals commonly observed around the UAE region including quartz, kaolinite, and calcium carbonate. The T-matrix, finite difference time domain (FDTD), and Lorenz-Mie light scattering programs were employed to calculate the single scattering properties for three dust shapes: oblate spheroids, hexagonal plates, and spheres. We used the Code for High-resolution Accelerated Radiative Transfer with Scattering (CHARTS) radiative transfer program to investigate sensitivity of the modeled AERI spectra to key dust and atmospheric parameters. Sensitivity studies show that characterization of the thermodynamic boundary layer is crucial for accurate AERI dust detection/retrieval. Furthermore, AERI sensitivity to dust optical depth is manifested in the strong subband slope dependence of the window region. Two daytime UAE cases were examined to demonstrate the present detection/retrieval technique, and we show that the results compare reasonably well to collocated AERONET Sun photometer/MPLNET micropulse lidar measurements. Finally, sensitivity of the developed methodology to the AERI’s estimated MgCdTe detector nonlinearity was evaluated.