Sensitivity of multiangle imaging to aerosol optical depth and to pure‐particle size distribution and composition over ocean

Multiangle, multispectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multiangle Imaging Spectroradiometer (MISR), can significantly improve our ability to constrain aerosol properties from space. Simulations over cloud-free, calm ocean conditions were studied for pure particles with natural ranges of optical depth, particle size, and indices of refraction. According to the theoretical simulations we can retrieve column optical depth from measurements over calm ocean for all but the darkest particles, with typical size distributions and compositions, to an uncertainty of at most 0.05 or 20%, whichever is larger, even if the particle properties are poorly known. For one common particle type, soot, constraints on the optical depth over dark ocean are very poor. The simulated measurements also allow us to distinguish spherical from nonspherical particles, to separate two to four compositional groups based on indices of refraction, and to identify three to four distinct size groups between 0.1 and 2.0 μm characteristic radius at most latitudes. The technique is most sensitive to particle microphysical properties in the “accumulation mode” sizes, where particle scattering undergoes the transition from Rayleigh to large-particle regimes for the MISR wavelengths. On the basis of these results we expect to distinguish air masses containing different aerosol types, routinely and globally, with multiangle remote sensing data. Such data complement in situ and field data, which can provide detailed information about aerosol size and composition locally. An extension of this study to mixtures of pure particles is part of continuing work.

[1]  David J. Diner,et al.  Level 2 Aerosol Retrieval Algorithm Theoretical Basis , 1999 .

[2]  Gottfried Hänel,et al.  The Properties of Atmospheric Aerosol Particles as Functions of the Relative Humidity at Thermodynamic Equilibrium with the Surrounding Moist Air , 1976 .

[3]  Irina N. Sokolik,et al.  Direct radiative forcing by anthropogenic airborne mineral aerosols , 1996, Nature.

[4]  J. Hansen,et al.  Light scattering in planetary atmospheres , 1974 .

[5]  Andrew A. Lacis,et al.  Modeling of particle size distribution and its influence on the radiative properties of mineral dust aerosol , 1996 .

[6]  Bernard Pinty,et al.  Multi-angle Imaging SpectroRadiometer (MISR) instrument description and experiment overview , 1998, IEEE Trans. Geosci. Remote. Sens..

[7]  J. Coakley,et al.  Climate Forcing by Anthropogenic Aerosols , 1992, Science.

[8]  E. Shettle,et al.  Models for the aerosols of the lower atmosphere and the effects of humidity variations on their optical properties , 1979 .

[9]  M. Mishchenko,et al.  Modeling phase functions for dustlike tropospheric aerosols using a shape mixture of randomly oriented polydisperse spheroids , 1997 .

[10]  Andrew A. Lacis,et al.  Sensitivity of cirrus cloud albedo, bidirectional reflectance and optical thickness retrieval accuracy to ice particle shape , 1996 .

[11]  M. Andreae Chapter 10 – Climatic effects of changing atmospheric aerosol levels , 1995 .

[12]  Larry L. Stowe,et al.  Remote sensing of aerosols over the oceans using AVHRR data Theory, practice and applications , 1989 .

[13]  J. Klett,et al.  Microphysics of Clouds and Precipitation , 1978, Nature.

[14]  David J. Diner,et al.  MISR radiometric uncertainty analyses and their utilization within geophysical retrievals , 1998 .

[15]  Carol J. Bruegge,et al.  MISR prelaunch instrument calibration and characterization results , 1998, IEEE Trans. Geosci. Remote. Sens..

[16]  Eric P. Shettle,et al.  Atmospheric Aerosols: Global Climatology and Radiative Characteristics , 1991 .

[17]  Yoram J. Kaufman,et al.  Biomass burning aerosol size distribution and modeled optical properties , 1998 .

[18]  Makiko Sato,et al.  The missing climate forcing , 1997 .

[19]  Bernard Pinty,et al.  Techniques for the retrieval of aerosol properties over land and ocean using multiangle imaging , 1998, IEEE Trans. Geosci. Remote. Sens..

[20]  P. R. Bevington,et al.  Data Reduction and Error Analysis for the Physical Sciences , 1969 .

[21]  Alexander Ignatov,et al.  Development, validation, and potential enhancements to the second‐generation operational aerosol product at the National Environmental Satellite, Data, and Information Service of the National Oceanic and Atmospheric Administration , 1997 .

[22]  J. Penner,et al.  Quantifying and minimizing uncertainty of climate forcing by anthropogenic aerosols , 1994 .

[23]  Robert A. West,et al.  Sensitivity of multiangle remote sensing observations to aerosol sphericity , 1997 .

[24]  Pi-Huan Wang,et al.  Inference of stratospheric aerosol composition and size distribution from SAGE II satellite measurements , 1989 .

[25]  David J. Diner,et al.  A multiangle imaging spectroradiometer for terrestrial remote sensing from the earth observing system , 1991, Int. J. Imaging Syst. Technol..