Retrieval of the real part of the refractive index of smoke particles from Sun/sky measurements during SCAR‐B
Márcia Akemi Yamasoe, Yoram J. Kaufman, Оleg Dubovik, L. A. Remer, B. N. Holben, Paulo Artaxo
- Year
- 1998
- Citations
- 78
Abstract
A method is used to retrieve the real part of the refractive index of ambient aerosol particles in the entire vertical column using ground‐based measurements of the angular dependence of the spectral sky radiance. The method is applied to smoke aerosol particles using spectral Sun/sky data measured by the AERONET (Aerosol Robotic Network) radiometers in Cuiabá, Brazil, during the SCAR‐B (Smoke, Clouds, and Radiation‐Brazil) experiment in 1995. The refractive index is retrieved from comparison between measurements taken in the solar almucantar and calculations using Mie theory. First the aerosol size distribution is derived from sky radiance at scattering angles less then 40°, then the refractive index is derived from sky radiances for angles of 20°–100°. Simulations and sensitivity studies are presented showing that the expected error is ±0.03, Application of the method to the Cuiabá region, which is dominated by smoke from cerrado vegetation burning, resulted in a mean value for the real part of the index of refraction of 1.53±0.04, 1.55±0.04, 1.59±0.02, and 1.58±0.01, respectively, for wavelengths of 438, 670, 870, and 1020 nm. Though we do not have independent verification of the results, we tested the effect of water vapor on the refractive index. The low humidification factors measured in Brazil and the lack of high relative humidities suggested a small effect of water vapor. In fact, as expected, a nonsignificant correlation was observed between the retrieved values of refractive index and total precipitable water vapor. Application to aerosol in the eastern United States (not reported here), with high humidity and high humidification factors, did show a strong reduction of the refractive index with increase of the total precipitable water vapor, thus generating confidence in the methodology.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992