Note: Intro -- Contents -- List of Contributors -- Preface -- Part I Light Scattering -- 1 Light scattering by atmospheric mineral dust particles -- 1.1 Introduction -- 1.2 Physical properties of dust particles -- 1.2.1 Composition, structure, and shape -- 1.2.2 Mineral dust size distribution -- 1.3 Light-scattering measurements -- 1.4 Light-scattering modeling -- 1.4.1 Definitions -- 1.4.2 Models with simple homogeneous particles -- 1.4.2.1 Spheres -- 1.4.2.2 Spheroids -- 1.4.2.3 Ellipsoids -- 1.4.2.4 Polyhedra -- 1.4.3 Models with complex anisotropic, and inhomogeneous particles -- 1.4.3.1 Homogeneous, isotropic models -- 1.4.3.2 Inhomogeneous or anisotropic models -- 1.4.4 Impact of morphological details and anisotropy on scattering -- 1.4.4.1 Surface roughness -- 1.4.4.2 Inhomogeneity -- 1.4.4.3 Material anisotropy -- 1.5 Discussion and conclusions -- Acknowledgments -- References -- 2 A review of approximate analytic light-scattering phase functions -- 2.1 Introduction -- 2.2 Scattering phase function as a series expansion -- 2.2.1 Expansion in terms of Legendre polynomials -- 2.2.2 The Rayleigh phase function (RPF) -- 2.2.3 The δ −M phase function approximation -- 2.2.4 Peak truncated phase functions -- 2.3 Parametrized phase functions -- 2.3.1 One-parameter phase functions -- 2.3.1.1 The Henyey-Greenstein phase function (HGPF) -- 2.3.1.2 Combined Henyey-Greenstein (HGPF) and Rayleigh phase function -- 2.3.1.3 The Neer-Sandri phase function (NSPF) -- 2.3.1.4 Kagiwada-Kalaba phase function (KKPF) -- 2.3.1.5 The Schlick phase function -- 2.3.1.6 The binomial phase function -- 2.3.1.7 The delta-hyperbolic phase function -- 2.3.1.8 The transport phase function (TPF) -- 2.3.2 Two-parameter phase functions -- 2.3.2.1 The modified Henyey-Greenstein phase function -- 2.3.2.2 The Gegenbauer kernel phase function (GKPF). , 2.3.2.3 The delta-Eddington phase function -- 2.3.2.4 The Liu phase function (LPF) -- 2.3.2.5 The Draine phase function (DPF) -- 2.3.2.6 Phase function for planetary regoliths -- 2.3.3 Three-parameter phase functions (TPPF) -- 2.3.4 Five-parameter phase function -- 2.3.5 Six-parameter phase function -- 2.4 Analytic phase functions dependent on microphysical particle characteristics -- 2.4.1 Phase functions for small spherical particles -- 2.4.2 Larger particles -- 2.4.3 Zhao phase function (ZPF) -- 2.5 Densely packed particles -- 2.6 Role of phase function in ray tracing by the Monte Carlo method -- 2.7 Distribution-specific analytic phase functions -- 2.7.1 Rayleigh-Gans phase function for modified gamma distribution -- 2.7.2 Junge size distribution -- 2.7.3 Phase function for ice clouds -- 2.8 Concluding remarks -- References -- 3 Scattering of electromagnetic plane waves in radially inhomogeneous media: ray theory, exact solutions and connections with po -- 3.1 Complementary levels of description in light scattering -- 3.2 Scattering by a transparent sphere: ray description -- 3.2.1 The ray path integral -- 3.3 Analysis of specific profiles -- 3.4 The generation of exact solutions for radially inhomogeneous media -- 3.4.1 A summary of the method -- 3.4.2 Specific profiles -- 3.4.2.1 Spherically stratified isotropic media -- 3.4.2.2 Cylindrically stratified isotropic media -- 3.4.3 The non-existence of bound state solutions -- 3.5 Scalar wave scattering by a transparent sphere -- 3.5.1 Morphology-dependent resonances: the effective potential Ul(r) (constant n) -- 3.6 Connection with the scattering matrix -- 3.7 The vector problem: the Mie solution of electromagnetic scattering theory -- 3.8 Conclusion -- Appendix 1: Properties of η(r) and interpretation of the ray path integral -- Appendix 2: Poles and resonances on the k-plane and E-plane. , References -- Part II Remote Sensing -- 4 Spectral dependence of MODIS cloud droplet effective radius retrievals for marine boundary layer clouds -- 4.1 Introduction -- 4.2 Operational MODIS re retrieval algorithm -- 4.3 Spectral dependence of MODIS re retrievals for MBL clouds -- 4.3.1 Geographical pattern -- 4.3.2 Correlation with key cloud parameters -- 4.4 Potential reasons for the spectral difference -- 4.4.1 Random error -- 4.4.2 Vertical cloud structure -- 4.4.3 Cloud droplet size distribution -- 4.4.4 Plane-parallel re bias -- 4.4.5 3D radiative transfer effect -- 4.5 Discussion -- 4.5.1 Which one is better? -- 4.5.2 Cloud regime classification -- 4.6 Outlook of future work -- Acknowledgments -- References -- 5 Remote sensing of above cloud aerosols -- 5.1 Introduction -- 5.2 Above cloud aerosols (ACA), and their role in climate -- 5.2.1 Direct effects -- 5.2.2 Indirect and semi-direct effects -- 5.3 Orbital observations of ACA -- 5.3.1 Passive ultraviolet (UV) observations -- 5.3.1.1 Physical basis -- 5.3.1.2 Sources of uncertainty -- 5.3.2 Passive visible (VIS) near-infrared (NIR) observations -- 5.3.2.1 Physical basis -- 5.3.2.2 Sources of uncertainty -- 5.3.2.3 Ongoing developments -- 5.3.3 Passive hyperspectral observations -- 5.3.3.1 Physical basis -- 5.3.3.2 Sources of uncertainty -- 5.3.4 Passive polarimetric observations -- 5.3.4.1 Physical basis -- 5.3.4.2 Sources of uncertainty -- 5.3.4.3 Ongoing developments -- 5.3.5 Active Lidar observations -- 5.3.5.1 Physical basis -- 5.3.5.2 Sources of uncertainty -- 5.3.5.3 Validation and assessment -- 5.3.5.4 Ongoing developments -- 5.4 Validation with in situ and suborbital observations -- 5.4.1 In situ observations from field campaigns -- 5.4.2 Airborne sunphotometers -- 5.4.3 Active sensors -- 5.4.4 Spectrometers -- 5.4.5 Airborne polarimeters. , 5.4.6 RF assessment using observational data and regional climate models -- 5.5 The future for ACA retrievals -- 5.5.1 Upcoming orbital opportunities -- 5.5.2 Data fusion -- 5.5.3 Recommendations for future instruments -- 5.6 Conclusion -- Acronyms and symbols -- References -- Part III Polarimetry -- 6 Principles of the Mueller matrix measurements -- 6.1 Introduction -- 6.2 Mathematics of the Mueller matrix method -- 6.3 Complete Mueller polarimetry -- 6.4 Physical realizability of the experimental Mueller matrix -- 6.5 Partial Mueller polarimetry -- 6.6 Mueller polarimeter optimization -- 6.7 Conclusions -- Appendix A: Some multiplicative and additive Mueller matrix models -- References -- 7 Reflectance and polarization characteristics of various vegetation types -- 7.1 Introduction -- 7.2 Definitions -- 7.2.1 BRF, BRDF -- 7.2.2 Polarization -- 7.3 Theory and modeling -- 7.4 Field and laboratory measurements -- 7.5 Analysis -- 7.5.1 Special features by species -- 7.6 Discussion on specific remote sensing signatures -- 7.6.1 Heterogeneity, or spatial variations -- 7.6.2 Anisotropy -- 7.6.3 Spectral signature -- 7.6.4 Polarization-any new signals? -- 7.7 Discussion on measurement principles -- 7.8 Conclusions -- Acknowledgements -- References -- Part IV Radiative Forcing -- 8 Diurnally averaged direct aerosol-induced radiative forcing from cloud-free sky field measurements performed during seven regi -- 8.1 Introduction -- 8.2 Definitions of diurnally averaged DARF at the ToAand BoA-levels and within the atmosphere -- 8.2.1 The instantaneous DARF effects at ToAand BoA-levels and in the atmosphere -- 8.2.2 Diurnally averaged DARF and aerosol fractional forcing -- 8.2.3 DARF efficiency -- 8.3 Field measurements and calculations of the diurnally averaged DARF at the ToAand BoA-levels and in the atmosphere, with corr. , 8.3.1 DARF evaluations from the CLEARCOLUMN (ACE-2) field measurements in southern Portugal -- 8.3.2 DARF evaluations from the PRIN-2004 project measurements in southern Italy -- 8.3.3 DARF evaluations obtained from the AEROCLOUDS project measurements in northern Italy -- 8.3.4 DARF evaluations from the Ev-K2-CNR project measurements in Himalaya (Nepal) -- 8.3.5 DARF evaluations from the POLAR-AOD project measurements performed at Arctic and Antarctic sites -- 8.3.6 DARF evaluations from the Aerosols99 measurements in the Atlantic Ocean -- 8.3.7 DARF evaluations from the DOE/ARM/AIOP project field measurements in north-central Oklahoma -- 8.4 Conclusions -- Acknowledgements -- References -- Index.