The three dimensional Monte Carlo radiation transport model McArtim is extended to account for the simulation of the propagation of polarized radiation and the inelastic rotational Raman scattering which is the cause of the so called Ring effect. From the achieved and now sufficient precision of the calculated Ring effect new opportunities in optical absorption spectroscopy arise. In the calculation the method of importance sampling (IS) is applied. Thereby one obtains from an ensemble of Monte Carlo photon trajectories an intensity accounting for the elastic aerosol particle-, Cabannes- and the inelastic rotational Raman scattering (RRS) and simultaneously an intensity, for which Rayleigh scattering is treated as an elastic scattering process. By combining both intensities one obtains the so called filling-in (FI, which quantifies the filling-in of Fraunhofer lines) as a measure for the strength of the Ring effect with the same relative precision as the intensities. The validation of the polarized radiometric quantities and the Ring effect is made by comparison with partially published results of other radiation transport models. Furthermore the concept of discretisation of the optical domain into grid cells is extended by making grid cells arbitrarily joining into so called clusters, i.e. grid cell aggregates. Therewith the program is able to calculate derivatives of radiometrically or spectroscopically accessible quantities, namely the intensities at certain locations in the atmospheric radiation field and the light path integrals of trace gas concentrations associated thereto, i.e. the product of the DOAS (differential optical absorption spectroscopy) method, with respect to optical properties of aerosols and gases in connected spatial regions. The first and second order derivatives are validated through so called self-consistency tests. These derivatives allow the inversion of three dimensional tracegas and aerosol concentration profiles and pave the way down to 3D optical scattered light tomography. If such tomographic inversion scheme is based solely on spectral intensitites the available second order derivatives allows the consideration of the curvature in the cost function and therefore allows implementation of efficient optimisation algorithms. The influence of the instrument function on the spectra is analysed in order to mathematically assess the potential of DOAS to a sufficient degree. It turns out that the detailed knowledge of the instrument function is required for an advanced spectral analysis. Concludingly the mathematical separability of narrow band signatures of absorption and the Ring effect from the relatively broad band influence of the elastic scattering processes on the spectra is demonstrated which corresponds exactly to the DOAS principle. In that procedure the differential signal is obtained by approximately 4 orders of magnitude faster then by the separate modelling with and without narrow band structures. Thereby the fusion of the separated steps DOAS spectral analysis and subsequent radiation transport modeling becomes computationally feasible.

The three dimensional Monte Carlo radiation transport model McArtim is extended to account for the simulation of the propagation of polarized radiation and the inelastic rotational Raman scattering which is the cause of the so called Ring effect. From the achieved and now sufficient precision of the calculated Ring effect new opportunities in optical absorption spectroscopy arise. In the calculation the method of importance sampling (IS) is applied. Thereby one obtains from an ensemble of Monte Carlo photon trajectories an intensity accounting for the elastic aerosol particle-, Cabannes- and the inelastic rotational Raman scattering (RRS) and simultaneously an intensity, for which Rayleigh scattering is treated as an elastic scattering process. By combining both intensities one obtains the so called filling-in (FI, which quantifies the filling-in of Fraunhofer lines) as a measure for the strength of the Ring effect with the same relative precision as the intensities. The validation of the polarized radiometric quantities and the Ring effect is made by comparison with partially published results of other radiation transport models. Furthermore the concept of discretisation of the optical domain into grid cells is extended by making grid cells arbitrarily joining into so called clusters, i.e. grid cell aggregates. Therewith the program is able to calculate derivatives of radiometrically or spectroscopically accessible quantities, namely the intensities at certain locations in the atmospheric radiation field and the light path integrals of trace gas concentrations associated thereto, i.e. the product of the DOAS (differential optical absorption spectroscopy) method, with respect to optical properties of aerosols and gases in connected spatial regions. The first and second order derivatives are validated through so called self-consistency tests. These derivatives allow the inversion of three dimensional tracegas and aerosol concentration profiles and pave the way down to 3D optical scattered light tomography. If such tomographic inversion scheme is based solely on spectral intensitites the available second order derivatives allows the consideration of the curvature in the cost function and therefore allows implementation of efficient optimisation algorithms. The influence of the instrument function on the spectra is analysed in order to mathematically assess the potential of DOAS to a sufficient degree. It turns out that the detailed knowledge of the instrument function is required for an advanced spectral analysis. Concludingly the mathematical separability of narrow band signatures of absorption and the Ring effect from the relatively broad band influence of the elastic scattering processes on the spectra is demonstrated which corresponds exactly to the DOAS principle. In that procedure the differential signal is obtained by approximately 4 orders of magnitude faster then by the separate modelling with and without narrow band structures. Thereby the fusion of the separated steps DOAS spectral analysis and subsequent radiation transport modeling becomes computationally feasible.:1.1. Radiation Transport Modeling and Atmospheric State Inversion 1.2. Vector RTE Solution Methods 1.3. Scope of the Thesis 1.4. Outline of the Thesis 2.1. General Structure 2.1.1. Chemical Composition of the Gas Phase 2.1.2. The Troposphere, Temperature and Pressure Vertical Structure 2.1.3. The Stratosphere 2.2. Aerosols and Clouds 2.2.1. Classification and Morphology 2.2.2. Water Related Particle Growth and Shrinking Processes 2.2.3. Size Spectra and Modes 3.1. Electromagnetic Waves 3.1.1. Maxwell\''s Equations 3.1.2. Measurement of Electromagnetic Waves 3.1.3. Polarization State of EM Waves 3.1.4. Stokes Vectors 3.2. Scattering and Absorption of EM Waves by Molecules and Particles 3.2.1. General Description of Scattering and Coordinate Systems 3.2.2. Molecular Scattering 3.2.3. Molecular Absorption Processes and Electronic Molecular States 3.2.4. Scattering On Spherical Particles - Mie Theory 3.3. Mathematical Description of Radiation Transport 3.3.1. Radiance and Irradiance 3.3.2. Absorption, Scattering and Extinction Coefficients 3.3.3. Optical Thickness and Transmission 3.3.4. Scattering 3.3.5. Incident (Ir)Radiance 3.3.6. The Black Surface Single Scattering Approximation 3.3.7. Radiative Transfer Equations 4.1. General Monte Carlo Methods 4.1.1. Numerical Integration 4.1.2. Importance Sampling and Zero Variance Estimates 4.1.3. Optimal Sampling 4.1.4. Sampling from Arbitrary Distributions 4.2. Path Generation or Collision Density Estimation 4.2.1. Discretization of the Optical Domain into Cells and Clusters 4.2.2. RTE Integral Form 4.2.3. Formal Solution of the IRTE 4.2.4. Overview on Monte Carlo RTE Solution Algorithms 4.2.5. Crude Monte Carlo 4.2.6. Sequential Importance Sampling (SIS) or Path Generation 4.3. Importance Sampling in Monte Carlo SIS Radiative Transfer 4.3.1. Weights for Alternate Kernels 4.3.2. Weights in the Calculation of RTE Functional Estimates 4.3.3. Application of IS to Mie Phase Functions Scatter Angle Sampling 5.1. Radiances, Intensities and the Reciprocity Theorem 5.1.1. Scalar Radiance Estimates 5.1.2. Backward Monte Carlo Scalar Radiance 5.1.3. Vector Radiances 5.2. Radiance Derivatives 5.2.1. Variables for Radiance Derivatives 5.3. Validation of Functionals 5.3.1. Validation of Vector Radiances 5.3.2. Validation of Radiance Derivatives 6.1. A Simply Structured Instrument Forward Model 6.2. Pure Atmospheric Spectra and Absorption 6.2.1. Direct Light Spectra 6.2.2. Scattered Sun Light Spectra 6.3. (D)OAS from the Perspective of Radiative Transfer Modeling 6.3.1. (Rest) Signatures of Weakly Absorbing Gases 6.3.2. Spectroscopic Measurements and Standard DOAS 6.4. DOAS Analysis Summary 6.4.1. DSCD Retrieval 6.4.2. Inversion 7.1. RRS-Modified RTE 7.1.1. RRS Cross Sections for Scattering out and into a Wavelength 7.1.2. Modification of the RTE Loss and Source Terms 7.2. Intensity Estimates Considering Rotational Raman Scattering 7.2.1. RRS in the Path Sampling Procedure 7.2.2. Adjoint RRS Correction Weights 7.2.3. Local Estimates of Intensities with RRS 7.2.4. Intensity Estimates 7.3. Ring Spectra 7.3.1. Elastic Biasing of the Local Estimates 7.3.2. Cumulative Weights and Local Estimates 7.3.3. Test of the Elastic Biasing 7.4. Validation 7.4.1. Comparison to an Analytic Single Scattering Code 7.4.2. Single Scattering Model Including Rotational Raman Scattering 7.4.3. Multiple Scattering Model Comparison 7.4.4. Comparison with A Measurement 7.4.5. Validation of Approximate Methods For Ring Effect Modeling 7.5. Summary and Discussion 8.1. Status and Summary 8.1.1. Ring-Effect and Absorption Corrected Radiances 8.1.2. Derivatives of Radiometric Quantities Accessible Through Spectroscopy 8.1.3. Polarization 8.1.4. Time Integrated Sensitivities for 3D UV/vis/NIR Remote Sensing 8.2. Outlook A.1. Zero Variance Estimates A.2. Free Path Length Sampling in a Homogeneous Medium A.3. Cumulative Differential Scatter Cross Sections A.3.1. Cardanic formulas A.3.2. Rayleigh and Raman Phase Functions A.3.3. Henyey-Greenstein Model A.3.4. Legendre Polynomial Phase Function Model A.3.5. Table Methods A.4. Greens Function in the Derivation of the IRTE A.5. Source Code For Stokes Vector Transformation Plot B.1. 1st Order Derivatives B.2. 2nd Order Derivatives B.3. Hessian of Integrals Depending on Many Variables C.1. Slit Function f Derivatives C.2. Signal Sn Derivatives C.3. Chi Square Spline Fitting C.3.1. Constrained Non-Linear Least Square Problem C.3.2. Spline Fitting C.3.3. Jacobians and Hessian