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Добірка наукової літератури з теми "Radiative transfer models (RTM)"

Автор: Grafiati

Опубліковано: 11 березня 2023

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Статті в журналах з теми "Radiative transfer models (RTM)"

1

Oh, Yisok, Jisung Geba Chang, and Maxim Shoshany. "An Improved Radiative Transfer Model for Polarimetric Backscattering from Agricultural Fields at C- and X-Bands." Journal of Electromagnetic Engineering and Science 21, no. 2 (April 30, 2021): 104–10. http://dx.doi.org/10.26866/jees.2021.21.2.104.

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The first-order vector radiative transfer model (FVRTM) is modified mainly by examining the effects of leaf curvature of vegetation canopies, the higher-order multiple scattering among vegetation scattering particles, and the underlying-surface roughness for forward reflection on radar backscattering from farming fields at C- and X-bands. At first, we collected the backscattering coefficients measured by scatterometers and space-borne synthetic aperture radar (SAR), field-measured ground-truth data sets, and theoretical scattering models for radar backscattering from vegetation fields at microwaves. Then, these effects on the RTM were examined using the database at the C- and X-bands. Finally, an improved RTM was obtained by adjusting its parameters, mainly related with the leaf curvature, the higher-order multiple scattering, and the underlying-surface small-roughness characteristics, and its accuracy was verified by comparisons between the improved RTM and measurement data sets.

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2

del Águila, Ana, Dmitry S. Efremenko, Víctor Molina García, and Michael Yu Kataev. "Cluster Low-Streams Regression Method for Hyperspectral Radiative Transfer Computations: Cases of O2 A- and CO2 Bands." Remote Sensing 12, no. 8 (April 15, 2020): 1250. http://dx.doi.org/10.3390/rs12081250.

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Current atmospheric composition sensors provide a large amount of high spectral resolution data. The accurate processing of this data employs time-consuming line-by-line (LBL) radiative transfer models (RTMs). In this paper, we describe a method to accelerate hyperspectral radiative transfer models based on the clustering of the spectral radiances computed with a low-stream RTM and the regression analysis performed for the low-stream and multi-stream RTMs within each cluster. This approach, which we refer to as the Cluster Low-Streams Regression (CLSR) method, is applied for computing the radiance spectra in the O2 A-band at 760 nm and the CO2 band at 1610 nm for five atmospheric scenarios. The CLSR method is also compared with the principal component analysis (PCA)-based RTM, showing an improvement in terms of accuracy and computational performance over PCA-based RTMs. As low-stream models, the two-stream and the single-scattering RTMs are considered. We show that the error of this approach is modulated by the optical thickness of the atmosphere. Nevertheless, the CLSR method provides a performance enhancement of almost two orders of magnitude compared to the LBL model, while the error of the technique is below 0.1% for both bands.

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3

Mejia, Felipe A., Ben Kurtz, Keenan Murray, Laura M. Hinkelman, Manajit Sengupta, Yu Xie, and Jan Kleissl. "Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth." Atmospheric Measurement Techniques 9, no. 8 (August 30, 2016): 4151–65. http://dx.doi.org/10.5194/amt-9-4151-2016.

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Abstract. A method for retrieving cloud optical depth (τc) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red–blue ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red–blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (ϑs), and pixel zenith angle/view angle (ϑz). The effects of these parameters are described and the functions for radiance, Iλτc, θ0, ϑs, ϑz, and RBRτc, θ0, ϑs, ϑz are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeasϑs, ϑz, in addition to RBRmeasϑs, ϑz, to obtain a unique solution for τc. The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement (ARM) program site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min et al. (2003) method for overcast skies. τc values ranged from 0 to 80 with values over 80, being capped and registered as 80. A τc RMSE of 2.5 between the Min et al. (2003) method and the USI are observed. The MWR and USI have an RMSE of 2.2, which is well within the uncertainty of the MWR. The procedure developed here provides a foundation to test and develop other cloud detection algorithms.

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4

Vicent, Jorge, Jochem Verrelst, Neus Sabater, Luis Alonso, Juan Pablo Rivera-Caicedo, Luca Martino, Jordi Muñoz-Marí, and José Moreno. "Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)." Geoscientific Model Development 13, no. 4 (April 20, 2020): 1945–57. http://dx.doi.org/10.5194/gmd-13-1945-2020.

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Abstract. Atmospheric radiative transfer models (RTMs) are software tools that help researchers in understanding the radiative processes occurring in the Earth's atmosphere. Given their importance in remote sensing applications, the intercomparison of atmospheric RTMs is therefore one of the main tasks used to evaluate model performance and identify the characteristics that differ between models. This can be a tedious tasks that requires good knowledge of the model inputs/outputs and the generation of large databases of consistent simulations. With the evolution of these software tools, their increase in complexity bears implications for their use in practical applications and model intercomparison. Existing RTM-specific graphical user interfaces are not optimized for performing intercomparison studies of a wide variety of atmospheric RTMs. In this paper, we present the Atmospheric Look-up table Generator (ALG) version 2.0, a new software tool that facilitates generating large databases for a variety of atmospheric RTMs. ALG facilitates consistent and intuitive user interaction to enable the running of model executions and storing of RTM data for any spectral configuration in the optical domain. We demonstrate the utility of ALG in performing intercomparison studies of radiance simulations from broadly used atmospheric RTMs (6SV, MODTRAN, and libRadtran) through global sensitivity analysis. We expect that providing ALG to the research community will facilitate the usage of atmospheric RTMs to a wide range of applications in Earth observation.

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5

Karthikeyan, Lanka, Ming Pan, Dasika Nagesh Kumar, and Eric F. Wood. "Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm." Sensors 20, no. 4 (February 24, 2020): 1225. http://dx.doi.org/10.3390/s20041225.

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Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that is inherent in all τ-ω types of models in passive microwave SM retrieval algorithms. In the process, a new analytical solution for concurrent VOD and SM retrieval is presented, along with two widely used existing analytical solutions. All three solutions are applied to a fixed framework of RTM to retrieve VOD and SM on a global scale, using X-band Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) TB data. Results indicate that, with structural uncertainty, there ensues a noticeable impact on the VOD and SM retrievals. In an era where the sensitivity of retrieval algorithms is still being researched, we believe the structural indeterminacy of RTM identified here would contribute to uncertainty in the soil moisture retrievals.

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6

Seidel, F. C., A. A. Kokhanovsky, and M. E. Schaepman. "Fast and simple model for atmospheric radiative transfer." Atmospheric Measurement Techniques Discussions 3, no. 3 (May 18, 2010): 2225–73. http://dx.doi.org/10.5194/amtd-3-2225-2010.

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Abstract. Radiative transfer models (RTMs) are of utmost importance for quantitative remote sensing, especially for compensating atmospheric perturbation. A persistent trade-off exists between approaches that prefer accuracy at the cost of computational complexity, versus those favouring simplicity at the cost of reduced accuracy. We propose an approach in the latter category, using analytical equations, parameterizations and a correction factor to efficiently estimate the effect of molecular multiple scattering. We discuss the approximations together with an analysis of the resulting performance and accuracy. The proposed Simple Model for Atmospheric Radiative Transfer (SMART) decreases the calculation time by a factor of more than 25 in comparison to the benchmark RTM~6S on the same infrastructure. The approximative computation of the atmospheric reflectance factor by SMART has an uncertainty ranging from about 5% to 10% for nadir spaceborne and airborne observational conditions. The combination of a large solar zenith angle (SZA) with high aerosol optical depth (AOD) at low wavelengths lead to uncertainties of up to 15%. SMART can be used to simulate the hemispherical conical reflectance factor (HCRF) for spaceborne and airborne sensors, as well as for the retrieval of columnar AOD.

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7

Seidel, F. C., A. A. Kokhanovsky, and M. E. Schaepman. "Fast and simple model for atmospheric radiative transfer." Atmospheric Measurement Techniques 3, no. 4 (August 25, 2010): 1129–41. http://dx.doi.org/10.5194/amt-3-1129-2010.

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Анотація:

Abstract. Radiative transfer models (RTMs) are of utmost importance for quantitative remote sensing, especially for compensating atmospheric perturbation. A persistent trade-off exists between approaches that prefer accuracy at the cost of computational complexity, versus those favouring simplicity at the cost of reduced accuracy. We propose an approach in the latter category, using analytical equations, parameterizations and a correction factor to efficiently estimate the effect of molecular multiple scattering. We discuss the approximations together with an analysis of the resulting performance and accuracy. The proposed Simple Model for Atmospheric Radiative Transfer (SMART) decreases the calculation time by a factor of more than 25 in comparison to the benchmark RTM 6S on the same infrastructure. The relative difference between SMART and 6S is about 5% for spaceborne and about 10% for airborne computations of the atmospheric reflectance function. The combination of a large solar zenith angle (SZA) with high aerosol optical depth (AOD) at low wavelengths lead to relative differences of up to 15%. SMART can be used to simulate the hemispherical conical reflectance factor (HCRF) for spaceborne and airborne sensors, as well as for the retrieval of columnar AOD.

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8

Albino, André, Daniele Bortoli, Mouhaydine Tlemçani, Abdeloawahed Hajjaji, and António Joyce. "Sensitivity analysis of atmospheric spectral irradiance model." European Physical Journal Applied Physics 88, no. 1 (October 2019): 11001. http://dx.doi.org/10.1051/epjap/2019190350.

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Many Radiative Transfer Models (RTM) have been developed to simulate and estimate solar irradiance. Theirs accuracy is well documents in literature nonetheless the effect of the parameters uncertainties on the established models has not been well studied yet. This work focuses on implementing a RTM based on the models found in the literature along with some updates, with the aim to study the sensitivity of the model towards the variations of the input parameters. The parameters studied in this paper are: the day of the year, the solar zenith angle, the local atmospheric pressure, the local temperature, the relative humidity, the height of ozone layer concentration, the ozone concentration, the single scattering albedo, the ground albedo, the Ångström’s exponent and the aerosol optical depth. The sensibility analysis is achieved using the Normalized Root Mean Square Error (NRMSE) as an independent function, calculated with a set of simulated measurements of spectral global solar irradiance and a reference spectrum generated with a group of standard input parameters.

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9

del Águila, Ana, and Dmitry S. Efremenko. "Fast Hyper-Spectral Radiative Transfer Model Based on the Double Cluster Low-Streams Regression Method." Remote Sensing 13, no. 3 (January 27, 2021): 434. http://dx.doi.org/10.3390/rs13030434.

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Fast radiative transfer models (RTMs) are required to process a great amount of satellite-based atmospheric composition data. Specifically designed acceleration techniques can be incorporated in RTMs to simulate the reflected radiances with a fine spectral resolution, avoiding time-consuming computations on a fine resolution grid. In particular, in the cluster low-streams regression (CLSR) method, the computations on a fine resolution grid are performed by using the fast two-stream RTM, and then the spectra are corrected by using regression models between the two-stream and multi-stream RTMs. The performance enhancement due to such a scheme can be of about two orders of magnitude. In this paper, we consider a modification of the CLSR method (which is referred to as the double CLSR method), in which the single-scattering approximation is used for the computations on a fine resolution grid, while the two-stream spectra are computed by using the regression model between the two-stream RTM and the single-scattering approximation. Once the two-stream spectra are known, the CLSR method is applied the second time to restore the multi-stream spectra. Through a numerical analysis, it is shown that the double CLSR method yields an acceleration factor of about three orders of magnitude as compared to the reference multi-stream fine-resolution computations. The error of such an approach is below 0.05%. In addition, it is analysed how the CLSR method can be adopted for efficient computations for atmospheric scenarios containing aerosols. In particular, it is discussed how the precomputed data for clear sky conditions can be reused for computing the aerosol spectra in the framework of the CLSR method. The simulations are performed for the Hartley–Huggins, O2 A-, water vapour and CO2 weak absorption bands and five aerosol models from the optical properties of aerosols and clouds (OPAC) database.

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10

Abdelbaki, Asmaa, and Thomas Udelhoven. "A Review of Hybrid Approaches for Quantitative Assessment of Crop Traits Using Optical Remote Sensing: Research Trends and Future Directions." Remote Sensing 14, no. 15 (July 22, 2022): 3515. http://dx.doi.org/10.3390/rs14153515.

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Remote sensing technology allows to provide information about biochemical and biophysical crop traits and monitor their spatiotemporal dynamics of agriculture ecosystems. Among multiple retrieval techniques, hybrid approaches have been found to provide outstanding accuracy, for instance, for the inference of leaf area index (LAI), fractional vegetation cover (fCover), and leaf and canopy chlorophyll content (LCC and CCC). The combination of radiative transfer models (RTMs) and data-driven models creates an advantage in the use of hybrid methods. Through this review paper, we aim to provide state-of-the-art hybrid retrieval schemes and theoretical frameworks. To achieve this, we reviewed and systematically analyzed publications over the past 22 years. We identified two hybrid-based parametric and hybrid-based nonparametric regression models and evaluated their performance for each variable of interest. From the results of our extensive literature survey, most research directions are now moving towards combining RTM and machine learning (ML) methods in a symbiotic manner. In particular, the development of ML will open up new ways to integrate innovative approaches such as integrating shallow or deep neural networks with RTM using remote sensing data to reduce errors in crop trait estimations and improve control of crop growth conditions in very large areas serving precision agriculture applications.

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Дисертації з теми "Radiative transfer models (RTM)"

1

Schlawin, Everett A. "Radiative Transfer Models of the Galactic Center." Oberlin College Honors Theses / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1249300204.

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2

Zhang, Hongbin 1965. "A model radiative transfer problem." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277071.

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The analytical solution to a model time-dependent continuous lethargy photon transport equation is evaluated numerically to obtain a benchmark solution using the Laplace transforms coupled with the multiple collision expansion method. The benchmark solution is then used to check the accuracy of the multigroup approximation. Excellent agreement between continuous lethargy benchmarks and multigroup approximation is obtained.

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3

Frank, Martin [Verfasser]. "Partial Moment Models for Radiative Transfer / Martin Frank." Aachen : Shaker, 2005. http://d-nb.info/1186579609/34.

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4

Hart, Quinn James 1965. "Surface and aerosol models for use in radiative transfer codes." Thesis, The University of Arizona, 1990. http://hdl.handle.net/10150/277334.

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Absolute radiometric calibrations of Landsat 5 Thematic Mapper satellite are improved with the inclusion of a method to invert optical depth measurements to obtain an aerosol particle size distribution and a non-lambertian surface reflectance model. Also, a program is developed to improve speed and standardization of the entire calibration procedure. The inverted size distributions can predict radiances varying from the previous jungian distributions by as much as 5 percent, though the reduction in the estimated error is less than one percent. An empirical model for the surface reflection of White Sands using a two-degree polynomial fit as a function of scattering angle was employed. The model reduced estimated errors in radiance predictions by up to one percent. Satellite calibrations dating from October, 1984 are reprocessed using the improved methods and a linear estimation of satellite counts per unit radiance versus time since launch is determined.

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5

Bozzo, Alessio <1979&gt. "Atmospheric radiative transfer in multiple scattering conditions. Application to NWP models." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1874/1/bozzo_alessio_tesi.pdf.

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High spectral resolution radiative transfer (RT) codes are essential tools in the study of the radiative energy transfer in the Earth atmosphere and a support for the development of parameterizations for fast RT codes used in climate and weather prediction models. Cirrus clouds cover permanently 30% of the Earth's surface, representing an important contribution to the Earth-atmosphere radiation balance. The work has been focussed on the development of the RT model LBLMS. The model, widely tested in the infra-red spectral range, has been extended to the short wave spectrum and it has been used in comparison with airborne and satellite measurements to study the optical properties of cirrus clouds. A new database of single scattering properties has been developed for mid latitude cirrus clouds. Ice clouds are treated as a mixture of ice crystals with various habits. The optical properties of the mixture are tested in comparison to radiometric measurements in selected case studies. Finally, a parameterization of the mixture for application to weather prediction and global circulation models has been developed. The bulk optical properties of ice crystals are parameterized as functions of the effective dimension of measured particle size distributions that are representative of mid latitude cirrus clouds. Tests with the Limited Area Weather Prediction model COSMO have shown the impact of the new parameterization with respect to cirrus cloud optical properties based on ice spheres.

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6

Bozzo, Alessio <1979&gt. "Atmospheric radiative transfer in multiple scattering conditions. Application to NWP models." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1874/.

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Анотація:

High spectral resolution radiative transfer (RT) codes are essential tools in the study of the radiative energy transfer in the Earth atmosphere and a support for the development of parameterizations for fast RT codes used in climate and weather prediction models. Cirrus clouds cover permanently 30% of the Earth's surface, representing an important contribution to the Earth-atmosphere radiation balance. The work has been focussed on the development of the RT model LBLMS. The model, widely tested in the infra-red spectral range, has been extended to the short wave spectrum and it has been used in comparison with airborne and satellite measurements to study the optical properties of cirrus clouds. A new database of single scattering properties has been developed for mid latitude cirrus clouds. Ice clouds are treated as a mixture of ice crystals with various habits. The optical properties of the mixture are tested in comparison to radiometric measurements in selected case studies. Finally, a parameterization of the mixture for application to weather prediction and global circulation models has been developed. The bulk optical properties of ice crystals are parameterized as functions of the effective dimension of measured particle size distributions that are representative of mid latitude cirrus clouds. Tests with the Limited Area Weather Prediction model COSMO have shown the impact of the new parameterization with respect to cirrus cloud optical properties based on ice spheres.

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7

Imran, Hafiz Ali. "Remote Sensing Tools for Monitoring Grassland Plant Leaf Traits and Biodiversity." Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/329592.

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Grasslands are one of the most important ecosystems on Earth, covering approximately one-third of the Earth’s surface. Grassland biodiversity is important as many services provided by such ecosystems are crucial for the human economy and well-being. Given the importance of grasslands ecosystems, in recent years research has been carried out on the potential to monitor them with novel remote sensing techniques. Improved detectors technology and novel sensors providing fine-scale hyperspectral imagery have been enabling new methods to monitor plant traits (PTs) and biodiversity. The aims of the work were to study different approaches to monitor key grassland PTs such as Leaf Area Index (LAI) and biodiversity-related traits. The thesis consists of 3 parts: 1) Evaluating the performance of remote sensing methods to estimate LAI in grassland ecosystems, 2) Estimating plant biodiversity by using the optical diversity approach in grassland ecosystems, and 3) Investigating the relationship between PTs variability with alpha and beta diversity for the applicability of the optical diversity approach in a subalpine grassland of the Italian Alps To evaluate the performance of remote sensing methods to estimate LAI, temporal and spatial observations of hyperspectral reflectance and LAI were analyzed at a grassland site in Monte Bondone, Italy (IT-MBo). In 2018, ground temporal observations of hyperspectral reflectance and LAI were carried out at a grassland site in Neustift, Austria (AT-NEU). To estimate biodiversity, in 2018 and 2019 a floristics survey was conducted to determine species composition and hyperspectral data were acquired at two grassland sites: IT-MBo and University of Padova’s Experimental Farm, Legnaro, Padua, Italy (IT-PD) respectively. Furthermore, in 2018, biochemistry analysis of the biomass samples collected from the grassland site IT-MBo was carried out to determine the foliar biochemical PTs variability. The results of the thesis demonstrated that the grassland spectral response across different spectral regions (Visible: VIS, red-edge: RE, Near-infrared: NIR) showed to be both site-specific and scale-dependent. In the first part of the thesis, the performance of spectral vegetation indices (SVIs) based on visible, red-edge (RE), and NIR bands alongside SVIs solely based or NIR-shoulder bands (wavelengths 750 - 900 nm) was evaluated. A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), it was demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. In the second part, the applicability of the spectral variability hypothesis (SVH) was questioned and highlighted the challenges to use high-resolution hyperspectral images to estimate biodiversity in complex grassland ecosystems. It was reported that the relationship between biodiversity (Shannon, Richness, Simpson, and Evenness) and optical diversity metrics (Coefficient of variation (CV) and Standard deviation (SD)) is not consistent across plant communities. The results of the second part suggested that biodiversity in terms of species richness could be estimated by optical diversity metrics with an R2 = 0.4 at the IT-PD site where the grassland plots were artificially established and are showing a lower structure and complexity from the natural grassland plant communities. On the other hand, in the natural ecosystems at IT-MBo, it was more difficult to estimate biodiversity indices, probably due to structural and biochemical PTs co-variation. The effects of canopy non-vegetative elements (flowers and dead material), shadow pixels, and overexposed pixels on the relationship between optical diversity metrics and biodiversity indices were highlighted. In the third part, we examined the relationship between PTs variability (at both local and community scales, measured by standard deviation and by the Euclidean distances of the biochemical and biophysical PTs respectively) and taxonomic diversity (both α-diversity and β-diversity, measured by Shannon’s index and by Jaccard dissimilarity index of the species, families, and functional groups percent cover respectively) in Monte Bondone, Trentino province, Italy. The results of the study showed that the PTs variability metrics at alpha scale were not correlated with α-diversity. However, the results at the community scale (β-diversity) showed that some of the investigated biochemical and biophysical PTs variations metrics were associated with β-diversity. The SVH approach was also tested to estimate β-diversity and we found that spectral diversity calculated by spectral angular mapper (SAM) showed to be a better proxy of biodiversity in the same ecosystem where the spectral diversity failed to estimate alpha diversity, this leading to the conclusion that the link between functional and species diversity may be an indicator of the applicability of optical sampling methods to estimate biodiversity. The findings of the thesis highlighted that grassland structural heterogeneity strongly affects the ability to retrieve both LAI and biodiversity, with high uncertainties due to structural and biochemical PTs co-variation at complex grassland ecosystems. In this context, the uncertainties of satellite-based products (e.g., LAI) in monitoring grassland canopies characterized by either spatially or temporally varying structure need to be carefully taken into account. The results of the study highlighted that the poor performance of optical diversity proxies in estimating biodiversity in structurally heterogeneous grasslands might be due to the complex relationships between functional diversity and biodiversity, rather than the impossibility to detect functional diversity with spectral proxies.

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8

Smeltzer, Charles David. "In comparing radiative transfer and chemical transport models on OMI NO2 retrievals." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31677.

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Thesis (M. S.)--Earth and Atmospheric Sciences, Georgia Institute of Technology, 2010.
Committee Chair: Dr. Yuhang Wang; Committee Member: Dr. Greg Huey; Committee Member: Dr. Michael Chang. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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9

Caunt, Stuart Edward. "Analytical and numerical models of accretion disks." Thesis, University of Newcastle Upon Tyne, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265485.

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10

Robinson, Tyler D., Jonathan J. Fortney, and William B. Hubbard. "Analytic Scattering and Refraction Models for Exoplanet Transit Spectra." IOP PUBLISHING LTD, 2017. http://hdl.handle.net/10150/627105.

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Observations of exoplanet transit spectra are essential to understanding the physics and chemistry of distant worlds. The effects of opacity sources and many physical processes combine to set the shape of a transit spectrum. Two such key processes-refraction and cloud and/or haze forward-scattering-have seen substantial recent study. However, models of these processes are typically complex, which prevents their incorporation into observational analyses and standard transit spectrum tools. In this work, we develop analytic expressions that allow for the efficient parameterization of forward-scattering and refraction effects in transit spectra. We derive an effective slant optical depth that includes a correction for forward-scattered light, and present an analytic form of this correction. We validate our correction against a full-physics transit spectrum model that includes scattering, and we explore the extent to which the omission of forward-scattering effects may bias models. Also, we verify a common analytic expression for the location of a refractive boundary, which we express in terms of the maximum pressure probed in a transit spectrum. This expression is designed to be easily incorporated into existing tools, and we discuss how the detection of a refractive boundary could help indicate the background atmospheric composition by constraining the bulk refractivity of the atmosphere. Finally, we show that opacity from Rayleigh scattering and collision-induced absorption will outweigh the effects of refraction for Jupiter-like atmospheres whose equilibrium temperatures are above 400-500 K.

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Книги з теми "Radiative transfer models (RTM)"

1

France, Société mathématique de, ed. Mathematical models and numerical methods for radiative transfer. Paris: Société Mathématique de France, 2009.

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2

United States. National Aeronautics and Space Administration., ed. "Studies in the parameterization of cloudiness in climate models and the analysis of radiation fields in general circulation models". West Lafayette, Ind: Dept. of Earth and Atmospheric Sciences, Purdue University, 1990.

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3

Horwitz, James L. [Radiative transfer models]: [final report, Oct. 1990 - Oct. 1992]. [Washington, DC: National Aeronautics and Space Administration, 1992.

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4

W, Bergstrom Robert, and United States. National Aeronautics and Space Administration., eds. Use of ARM measurements to improve radiative transfer models used in climate models. San Francisco, CA: Bay Area Environmental Research Institute, 1995.

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5

J, Wilson S., ed. Radiative transfer in curved media: Basic mathematical methods for radiative transfer and transport problems in participating media of spherical and cylindrical geometry. Singapore: World Scientific, 1990.

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6

Ströhle, Jochen. Spectral modelling of radiative heat transfer in industrial furnaces. Aachen: Shaker, 2004.

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7

F, Cahalan Robert, and Davies Roger, eds. I3RC: Abstracts of the first and second international workshops on the intercomparsion of three-dimensional radiation codes, Tucson, Arizona, November, 2000. [Ariz.?: I3RC], 2000.

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8

W, Bergstrom R., and United States. National Aeronautics and Space Administration., eds. 3ARM: A fast, accurate radiative transfer model for use in climate models. [Washington, DC: National Aeronautics and Space Administration, 1996.

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9

S, Kinne, Toon O. B, and United States. National Aeronautics and Space Administration., eds. Improved prediction of atmospheric heating and cooling rates. [Washington, D.C: National Aeronautics and Space Administration, 1991.

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10

United States. National Aeronautics and Space Administration., ed. Studies of the net surface radiative flux from satellite radiances during FIFE: Final report. [Washington, DC: National Aeronautics and Space Administration, 1993.

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Більше джерел

Частини книг з теми "Radiative transfer models (RTM)"

1

Modest, Michael F., and Daniel C. Haworth. "Radiation Properties, RTE Solvers, and TRI Models." In Radiative Heat Transfer in Turbulent Combustion Systems, 43–83. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27291-7_3.

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2

Serbin, Shawn P., and Philip A. Townsend. "Scaling Functional Traits from Leaves to Canopies." In Remote Sensing of Plant Biodiversity, 43–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33157-3_3.

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AbstractIn this chapter, we begin by exploring the relationship between plant functional traits and functional diversity and how this relates to the characterization and monitoring of global plant biodiversity. We then discuss the connection between leaf functional traits and their resulting optical properties (i.e., reflectance, transmittance, and absorption) and how this related to remote sensing (RS) of functional diversity. Building on this, we briefly discuss the history of RS of functional traits using spectroscopy and imaging spectroscopy data. We include a discussion of the key considerations with the use of imaging spectroscopy data for scaling and mapping plant functional traits across diverse landscapes. From here we provide a review of the general methods for scaling and mapping functional traits, including empirical and radiative transfer model (RTM) approaches. We complete the chapter with a discussion of other key considerations, such as field sampling protocols, as well as current caveats and future opportunities.

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3

Bruzual, A. Gustavo. "Radiative Transfer Models." In The Opacity of Spiral Disks, 33–41. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0381-7_3.

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4

Efremenko, Dmitry, and Alexander Kokhanovsky. "Radiative Transfer Models." In Foundations of Atmospheric Remote Sensing, 149–232. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66745-0_4.

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5

Fouquart, Y. "Radiative Transfer in Climate Models." In Physically-Based Modelling and Simulation of Climate and Climatic Change, 223–83. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-3041-4_5.

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6

Madore, Barry F. "3D Radiative Transfer Models of Galaxies." In Spiral Galaxies in the Near-IR, 263–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-540-49739-4_42.

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7

Puls, Joachim, and Adalbert W. A. Pauldrach. "Radiative Transfer in Expanding Atmospheres — Radiative Acceleration of Wolf-Rayet Envelopes?" In Stellar Atmospheres: Beyond Classical Models, 175–89. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3554-2_17.

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8

Nordlund, Å., and R. F. Stein. "Dynamics of and Radiative Transfer in Inhomogeneous Media." In Stellar Atmospheres: Beyond Classical Models, 263–79. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3554-2_23.

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Kiehl, Jeffrey T. "Radiative Transfer in Troposphere-Stratosphere Global Climate Models." In The Stratosphere and Its Role in the Climate System, 101–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-662-03327-2_8.

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10

Davis, C. G. "The Importance of Radiative Transfer in Stellar Pulsation Models." In Nonlinear Phenomena in Stellar Variability, 325–27. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1062-4_49.

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Тези доповідей конференцій з теми "Radiative transfer models (RTM)"

1

David, Chloe, Wenjun Ge, Somesh P. Roy, Michael F. Modest, and Ramanan Sankaran. "Comparison of Radiation Models for a Turbulent Piloted Methane/Air Jet Flame: A Frozen-Field Study." In ASME 2021 Heat Transfer Summer Conference collocated with the ASME 2021 15th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/ht2021-62417.

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Abstract Numerical modeling of radiative transfer in nongray reacting media is a challenging problem in computational science and engineering. The choice of radiation models is important for accurate and efficient high-fidelity combustion simulations. Different applications usually involve different degrees of complexity, so there is yet no consensus in the community. In this paper, the performance of different radiative transfer equation (RTE) solvers and spectral models for a turbulent piloted methane/air jet flame are studied. The flame is scaled from the Sandia Flame D with a Reynolds number of 22,400. Three classes of RTE solvers, namely the discrete ordinates method, spherical harmonics method, and Monte Carlo method, are examined. The spectral models include the Planck-mean model, the full-spectrum k-distribution (FSK) method, and the line-by-line (LBL) calculation. The performances of different radiation models in terms of accuracy and computational cost are benchmarked. The results have shown that both RTE solvers and spectral models are critical in the prediction of radiative heat source terms for this jet flame. The trade-offs between the accuracy, the computational cost, and the implementation difficulty are discussed in detail. The results can be used as a reference for radiation model selection in combustor simulations.

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2

Li, Hongxu, Kui Peng, and Zhifeng Huang. "CALCULATIONS OF DIRECTIONAL RADIATIVE INTENSITY IN ONE-DIMENSIONAL GASEOUS MEDIA USING LBL AND SNB MODELS." In International Heat Transfer Conference 16. Connecticut: Begellhouse, 2018. http://dx.doi.org/10.1615/ihtc16.rti.023162.

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3

Wang, Liangyu, Daniel C. Haworth, and Michael F. Modest. "A PDF/Photon Monte Carlo Method for Radiative Heat Transfer in Turbulent Flames." In ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems. ASMEDC, 2005. http://dx.doi.org/10.1115/ht2005-72748.

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Thermal radiation plays a dominant role in heat transfer for most combustion systems. Accurate predictions of radiative heat transfer are essential for the correct determination of flame temperature, flame structure, and pollutant emissions in combustion simulations. In turbulent flames, transported probability density function (PDF) methods provide a reliable treatment of nonlinear processes such as chemical reactions and radiative emission. Here a second statistical approach, a photon Monte Carlo (PMC) method, is employed to solve the radiative transfer equation (RTE). And a state-of-the-art model for spectral radiative properties, the full-spectrum k-distribution (FSK) method, is employed. The FSK method provides an efficient and accurate approach for spectral integration in radiation calculations. The resulting model is applied to simulate radiation and turbulence/radiation interactions in nonluminous turbulent non-premixed jet flames. The initial results reported here emphasize sensitivities of computed results to variations in the physical and numerical models. Results with versus without radiation, results obtained using two different RTE solvers, and results with a gray-gas approximation versus a spectral FSK method are compared.

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4

Daun, K. J., S. B. Beale, F. Liu, and G. J. Smallwood. "Radiation Heat Transfer in SOFC Electrolytes." In ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems. ASMEDC, 2005. http://dx.doi.org/10.1115/ht2005-72158.

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Due to their high operating temperature, there has been speculation that thermal radiation may play an important role in the overall heat transfer within the electrode and electrolyte layers of solid oxide fuel cells (SOFCs). This paper presents a detailed characterization of the thermophysical and radiative properties of the composite materials, which are then used to define a simple 2-D model incorporating the heat transfer characteristics of the electrode and electrolyte layers of a typical planar SOFC. Subsequently, the importance of thermal radiation is assessed by comparing the temperature field obtained using a conduction model with fields obtained using coupled conduction/radiation models. Contrary to some published literature, these results show that radiation heat transfer has a negligible effect on the temperature field within these components, and does not need to be accommodated in comprehensive thermal models of planar SOFCs.

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5

Yuen, W. W., and W. K. Chow. "Analysis of Radiation Heat Transfer in an Enclosure Fire Including the Effect of Scattering." In ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems. ASMEDC, 2005. http://dx.doi.org/10.1115/ht2005-72350.

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The need for an accurate simulation of the radiative heat transfer in a fire zone model is demonstrated. Results show that the lack of an accurate model of the relevant physics of radiative heat transfer can lead to uncertainty which can severely limit the usefulness of a fire zone model. An accurate numerical model of radiative exchange including the effect of scattering, is applied to simulate the effect of radiative heat transfer on fire growth. Typical conservation equations in a fire zone models are used.

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6

Pal, Gopalendu, Ankur Gupta, Michael F. Modest, and Daniel C. Haworth. "Comparison of Accuracy and Computational Expense of Radiation Models in Simulation of Non-Premixed Turbulent Jet Flames." In ASME/JSME 2011 8th Thermal Engineering Joint Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ajtec2011-44585.

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The accuracy and computational expense of various radiation models in the simulation of turbulent jet flames are compared. Both nonluminous and luminous methane-air non-premixed turbulent jet flames are simulated using a comprehensive combustion solver. The combustion solver consists of a finite-volume/probability density function-based flow–chemistry solver interfaced with a high-accuracy spectral radiation solver. Flame simulations were performed using various k-distribution-based spectral models and radiative transfer equation (RTE) solvers, such as P-1, P-3, finite volume/discrete ordinates method (FVM/DOM), and Photon Monte Carlo (PMC) methods, with/without the consideration of turbulence-radiation interaction (TRI). TRI is found to drop the peak temperature by close to 150 K for a luminous flame (optically thicker) and 25–100 K for a nonluminous flame (optically thinner). RTE solvers are observed to have stronger effects on peak flame temperature, total radiant heat source and NO emission than the spectral models. P-1 is found to be the computationally least expensive RTE solver and the FVM the most expensive for any spectral model. For optically thinner flames all radiation models yield excellent accuracy. For optically thicker flames P-3 and FVM predict radiation more accurately than the P-1 method when compared to the benchmark line-by-line (LBL) PMC.

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7

Murphy, Thomas E., and Halil Berberog˘lu. "Increased Photobioreactor Productivity Using Algae With Low Pigmentation: A Light Transfer Perspective." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-39482.

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This paper reports a numerical study on the photosynthetic productivity of algae photobioreactors using wild strains and genetically engineered strains with low chlorophyll pigment content. First, the specific photosynthetic rates of the wild strain algae Chlammydomonas reinhardtii CC125 and the truncated chlorophyll transformant tla1 were obtained from experiments as a function of the total available irradiation for each cell. This rate was modeled with a modified Monod function accounting for light saturation and light inhibition. The models were coupled with the radiative transport equation (RTE) to predict both the local and total photosynthetic rate of an open pond photobioreactor. The benefits and limitations of using truncated antenna transformants for increasing productivity of mass algae culturing are discussed.

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8

Irick, Kevin, and Erich Brown. "In-Situ Thermal ROM-Based Optimization Using Borg MOEA: A Preliminary Study." In ASME 2019 Heat Transfer Summer Conference collocated with the ASME 2019 13th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/ht2019-3483.

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Abstract High-fidelity computational thermal models (HFMs) of mechanical systems typically incorporate multi-disciplinary data sources to define boundary conditions, constraints, and dynamic system inputs. Oftentimes, HFMs are used during the planning, design, fabrication, testing, and operational phases of the mechanical systems, however, most of that data is processed during the modeling and test phases to discover and verify system responses. This approach can lead to much unused data and engineering effort that could otherwise provide useful information during the operational phases of the systems. One major bottleneck in using HFMs during the operational phase is data volume and computation time. Reduced-order models (ROMs), such as Gaussian processes, can consolidate data volume, data complexity, and time complexity needed for processing HFMs. The Borg multi-objective evolutionary algorithm (MOEA) presents a possible effective approach for processing ROM information in conjunction with real-time true process data to better understand the real-time state of a system. An investigation is being performed into the use of ROMs with the Borg MOEA to capitalize on engineering effort and simulation data that would otherwise be abandoned. This paper discusses the results of such a study in a steady-state conductive-radiative heat transfer system.

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9

Ripoll, J. F., and A. A. Wray. "ON CLOSURE MODELS FOR RADIATIVE PRESSURE." In RADIATIVE TRANSFER - IV. Fourth International Symposium on Radiative Transfer. New York: Begellhouse, 2004. http://dx.doi.org/10.1615/ichmt.2004.rad-4.200.

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10

Sidwell, T. G., S. A. Lawson, D. L. Straub, K. H. Casleton, and S. Beer. "Conjugate Heat Transfer Modeling of a Film-Cooled, Flat-Plate Test Specimen in a Gas Turbine Aerothermal Test Facility." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-94687.

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The aerothermal test facility at the National Energy Technology Laboratory (NETL) provides experimental data at realistic gas turbine conditions to enable the development of advanced film cooling strategies for future gas turbine components. To complement ongoing experimental studies, Fluent computational fluid dynamics (CFD) models have been developed to provide a framework for comparison of cooling strategies and to provide fundamental understanding of the fluid dynamic and conjugate heat transfer (CHT) processes occurring in the experiments. The results of a parametric study of the effects of mesh density, near-wall refinement, wall treatment, turbulence model and gradient discretization order on the CHT predictions are presented, and the simulation results are compared to experimental data. A flat plate test specimen with a single row of laidback fan-shaped film cooling holes was modeled at a process pressure of 3 bar, a process gas flow rate (m) of 0.325 kg/s (Re ≈ 100,000) and a blowing ratio (M) of 2.75. Three polyhedral mesh cases and three turbulence models (Realizable k-ε, SST k-ω and RSM Stress-ω) were implemented with enhanced wall treatment (EWT) and 1st-order and 2nd-order gradient discretization. The results show that the choice of turbulence model will have little effect on the results when utilizing the finest mesh case and 2nd-order discretization. It was also shown that the SST k-ω turbulence model cases showed minimal mesh sensitivity with 2nd-order discretization, while the Re k-ε turbulence model cases were more sensitive to mesh density and near-wall refinement. The results thus indicate that the SST k-ω turbulence model can predict the convective heat transfer adequately with a relatively coarse mesh, which will save computational resources for later inclusion of radiative heat transfer effects to provide comprehensive CHT predictions.

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Звіти організацій з теми "Radiative transfer models (RTM)"

1

Hodul, M., H. P. White, and A. Knudby. A report on water quality monitoring in Quesnel Lake, British Columbia, subsequent to the Mount Polley tailings dam spill, using optical satellite imagery. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330556.

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In the early morning on the 4th of August 2014, a tailings dam near Quesnel, BC burst, spilling approximately 25 million m3 of runoff containing heavy metal elements into nearby Quesnel Lake (Byrne et al. 2018). The runoff slurry, which included lead, arsenic, selenium, and vanadium spilled through Hazeltine Creek, scouring its banks and picking up till and forest cover on the way, and ultimately ended up in Quesnel Lake, whose water level rose by 1.5 m as a result. While the introduction of heavy metals into Quesnel Lake was of environmental concern, the additional till and forest cover scoured from the banks of Hazeltine Creek added to the lake has also been of concern to salmon spawning grounds. Immediate repercussions of the spill involved the damage of sensitive environments along the banks and on the lake bed, the closing of the seasonal salmon fishery in the lake, and a change in the microbial composition of the lake bed (Hatam et al. 2019). In addition, there appears to be a seasonal resuspension of the tailings sediment due to thermal cycling of the water and surface winds (Hamilton et al. 2020). While the water quality of Quesnel Lake continues to be monitored for the tailings sediments, primarily by members at the Quesnel River Research Centre, the sample-and-test methods of water quality testing used, while highly accurate, are expensive to undertake, and not spatially exhaustive. The use of remote sensing techniques, though not as accurate as lab testing, allows for the relatively fast creation of expansive water quality maps using sensors mounted on boats, planes, and satellites (Ritchie et al. 2003). The most common method for the remote sensing of surface water quality is through the use of a physics-based semianalytical model which simulates light passing through a water column with a given set of Inherent Optical Properties (IOPs), developed by Lee et al. (1998) and commonly referred to as a Radiative Transfer Model (RTM). The RTM forward-models a wide range of water-leaving spectral signatures based on IOPs determined by a mix of water constituents, including natural materials and pollutants. Remote sensing imagery is then used to invert the model by finding the modelled water spectrum which most closely resembles that seen in the imagery (Brando et al 2009). This project set out to develop an RTM water quality model to monitor the water quality in Quesnel Lake, allowing for the entire surface of the lake to be mapped at once, in an effort to easily determine the timing and extent of resuspension events, as well as potentially investigate greening events reported by locals. The project intended to use a combination of multispectral imagery (Landsat-8 and Sentinel-2), as well as hyperspectral imagery (DESIS), combined with field calibration/validation of the resulting models. The project began in the Autumn before the COVID pandemic, with plans to undertake a comprehensive fieldwork campaign to gather model calibration data in the summer of 2020. Since a province-wide travel shutdown and social distancing procedures made it difficult to carry out water quality surveying in a small boat, an insufficient amount of fieldwork was conducted to suit the needs of the project. Thus, the project has been put on hold, and the primary researcher has moved to a different project. This document stands as a report on all of the work conducted up to April 2021, intended largely as an instructional document for researchers who may wish to continue the work once fieldwork may freely and safely resume. This research was undertaken at the University of Ottawa, with supporting funding provided by the Earth Observations for Cumulative Effects (EO4CE) Program Work Package 10b: Site Monitoring and Remediation, Canada Centre for Remote Sensing, through the Natural Resources Canada Research Affiliate Program (RAP).

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2

Barker, Howard, and Jason Cole. 3D Atmospheric Radiative Transfer for Cloud System-Resolving Models: Forward Modelling and Observations. Office of Scientific and Technical Information (OSTI), May 2012. http://dx.doi.org/10.2172/1040616.

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3

Carder, Kendall L., and David K. Costello. Distribution of our CoBOP Results: IOPs and Albedo Spectra for Incorporation into Radiative Transfer Models. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada619754.

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4

Liou, Kuo-Nan. Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications. Office of Scientific and Technical Information (OSTI), February 2016. http://dx.doi.org/10.2172/1237339.

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5

Tsay, Si-Chee, Q. J. Ji, Santiago Gasso, and Jeffrey S. Reid. Characterization of Dust Aerosols and Atmospheric Parameters from Space-borne and Surface-based Remote Sensing: Application of Community Radiative Transfer Algorithms to Navy Electro-Optical Models. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada628826.

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6

Tsay, Si-Chee, Q. J. Ji, Santiago Gasso, and Jeffrey S. Reid. Characterization of Dust Aerosols and Atmospheric Parameters from Space-borne and Surface-based Remote Sensing: Application of Community Radiative Transfer Algorithms to Navy Electro-Optical Models. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada633993.

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7

Xiao, Qingnong, and Xiaolei Zou. User's Guide on the Use of GOES-8, SSM/T and SSM/T-2 Radiance Measurements in MM5: The Radiative Transfer Models, and Their Tangent Linear and Adjoint operators. Fort Belvoir, VA: Defense Technical Information Center, May 1999. http://dx.doi.org/10.21236/ada370827.

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