scholarly journals A two-dimensional Monte Carlo model of radiative transfer in sea ice

2003 ◽  
Vol 108 (C7) ◽  
Author(s):  
B. Light
Keyword(s):  
Monte Carlo ◽  
Radiative Transfer ◽  
Sea Ice ◽  
Monte Carlo Model ◽  
Two Dimensional

scholarly journals High resolution and Monte Carlo additions to the SASKTRAN radiative transfer model

2015 ◽  
Vol 8 (3) ◽  
pp. 3357-3397 ◽  
Author(s):  
D. J. Zawada ◽  
S. R. Dueck ◽  
L. A. Rieger ◽  
A. E. Bourassa ◽  
N. D. Lloyd ◽  
...  
Keyword(s):  
Monte Carlo ◽  
High Resolution ◽  
Radiative Transfer ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Reference Model ◽  
Monte Carlo Model ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Systematic Bias

Abstract. The OSIRIS instrument on board the Odin spacecraft has been measuring limb scattered radiance since 2001. The vertical radiance profiles measured as the instrument nods are inverted, with the aid of the SASKTRAN radiative transfer model, to obtain vertical profiles of trace atmospheric constituents. Here we describe two newly developed modes of the SASKTRAN radiative transfer model: a high spatial resolution mode, and a Monte Carlo mode. The high spatial resolution mode is a successive orders model capable of modelling the multiply scattered radiance when the atmosphere is not spherically symmetric; the Monte Carlo mode is intended for use as a highly accurate reference model. It is shown that the two models agree in a wide variety of solar conditions to within 0.2%. As an example case for both models, Odin-OSIRIS scans were simulated with the Monte Carlo model and retrieved using the high resolution model. A systematic bias of up to 4% in retrieved ozone number density between scans where the instrument is scanning up or scanning down was identified. It was found that calculating the multiply scattered diffuse field at five discrete solar zenith angles is sufficient to eliminate the bias for typical Odin-OSIRIS geometries.

A Spectrally Accurate 2-D Axisymmetric Photon Monte-Carlo RTE Solver for Hypersonic Entry Flows

2009 ◽  
Author(s):  
Andrew Feldick ◽  
Josh Giegel ◽  
Michael F. Modest
Keyword(s):  
Monte Carlo ◽  
Radiative Transfer ◽  
Ray Tracing ◽  
Hypersonic Flow ◽  
Finite Volume ◽  
Spectral Properties ◽  
Computational Time ◽  
Two Dimensional ◽  
Flow Solver

A two-dimensional axisymmetric ray tracing photon Monte Carlo radiative transfer solver is developed. Like all ray tracing Monte Carlo codes, the ray tracing is performed in 3-D, however, arrangements are made to take advantage of the 2-D nature of the problem, to minimize computational time. The solver is designed to be integrated into finite volume hypersonic flow solvers, and is able to resolve the complex spectral properties of such flows to line-by-line accuracy. The solver is then directly integrated into DPLR, a hypersonic flow solver, and closely coupled calculations are performed.

Role of Inclination Dependent Anisotropy on Boundary Populations during Two-Dimensional Grain Growth

2012 ◽  
Vol 715-716 ◽  
pp. 697-702
Author(s):  
Debashis Kar ◽  
Stephen D. Sintay ◽  
Gregory S. Rohrer ◽  
Anthony D. Rollett
Keyword(s):  
Monte Carlo ◽  
Random Distribution ◽  
Monte Carlo Model ◽  
Grid Method ◽  
Grain Boundary Character Distribution ◽  
Two Dimensional ◽  
Grain Boundary Character ◽  
Character Distribution ◽  
Boundary Character Distribution

A Monte Carlo model is presented, in which the interface anisotropy is primarily inclination dependent. A dual grid method is used to determine boundary inclination in discretized digital microstructures. Evolution of the grain boundary character distribution (GBCD) in polycrystalline systems, from an initially random distribution, is inversely correlated with the anisotropy in interfacial energy, as expected.

Computational Cost and Accuracy in Calculating Three-Dimensional Radiative Transfer: Results for New Implementations of Monte Carlo and SHDOM

2009 ◽  
Vol 66 (10) ◽  
pp. 3131-3146 ◽  
Author(s):  
Robert Pincus ◽  
K. Franklin Evans
Keyword(s):  
Monte Carlo ◽  
Radiative Transfer ◽  
Variance Reduction ◽  
Parallel Implementation ◽  
Monte Carlo Model ◽  
Computational Cost ◽  
Three Dimensional ◽  
Computation Time ◽  
Flux Divergence ◽  
Pixel Intensity

Abstract This paper examines the tradeoffs between computational cost and accuracy for two new state-of-the-art codes for computing three-dimensional radiative transfer: a community Monte Carlo model and a parallel implementation of the Spherical Harmonics Discrete Ordinate Method (SHDOM). Both codes are described and algorithmic choices are elaborated. Two prototype problems are considered: a domain filled with stratocumulus clouds and another containing scattered shallow cumulus, absorbing aerosols, and molecular scatterers. Calculations are performed for a range of resolutions and the relationships between accuracy and computational cost, measured by memory use and time to solution, are compared. Monte Carlo accuracy depends primarily on the number of trajectories used in the integration. Monte Carlo estimates of intensity are computationally expensive and may be subject to large sampling noise from highly peaked phase functions. This noise can be decreased using a range of variance reduction techniques, but these techniques can compromise the excellent agreement between the true error and estimates obtained from unbiased calculations. SHDOM accuracy is controlled by both spatial and angular resolution; different output fields are sensitive to different aspects of this resolution, so the optimum accuracy parameters depend on which quantities are desired as well as on the characteristics of the problem being solved. The accuracy of SHDOM must be assessed through convergence tests and all results from unconverged solutions may be biased. SHDOM is more efficient (i.e., has lower error for a given computational cost) than Monte Carlo when computing pixel-by-pixel upwelling fluxes in the cumulus scene, whereas Monte Carlo is more efficient in computing flux divergence and downwelling flux in the stratocumulus scene, especially at higher accuracies. The two models are comparable for downwelling flux and flux divergence in cumulus and upwelling flux in stratocumulus. SHDOM is substantially more efficient when computing pixel-by-pixel intensity in multiple directions; the models are comparable when computing domain-average intensities. In some cases memory use, rather than computation time, may limit the resolution of SHDOM calculations.

scholarly journals Monte Carlo Study of UAV-Measurable Albedo over Arctic Sea Ice

2018 ◽  
Vol 35 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Igor Podgorny ◽  
Dan Lubin ◽  
Donald K. Perovich
Keyword(s):  
Monte Carlo ◽  
Sea Ice ◽  
Energy Budget ◽  
Monte Carlo Model ◽  
Lower Troposphere ◽  
Monte Carlo Study ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Inhomogeneous Surface ◽  
The Impact

AbstractIn anticipation that unmanned aerial vehicles (UAVs) will have a useful role in atmospheric energy budget studies over sea ice, a Monte Carlo model is used to investigate three-dimensional radiative transfer over a highly inhomogeneous surface albedo involving open water, sea ice, and melt ponds. The model simulates the spatial variability in 550-nm downwelling irradiance and albedo that a UAV would measure above this surface and underneath an optically thick, horizontally homogeneous cloud. At flight altitudes higher than 100 m above the surface, an airborne radiometer will sample irradiances that are greatly smoothed horizontally as a result of photon multiple reflection. If one is interested in sampling the local energy budget contrasts between specific surface types, then the UAV must fly at a low altitude, typically within 20 m of the surface. Spatial upwelling irradiance variability in larger open water features, on the order of 1000 m wide, will remain apparent as high as 500 m above the surface. To fully investigate the impact of surface feature variability on the energy budget of the lower troposphere ice–ocean system, a UAV needs to fly at a variety of altitudes to determine how individual features contribute to the area-average albedo.

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