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NASA NTRS2002

Space radiation absorbed dose distribution in a human phantom

The radiation risk to astronauts has always been based on measurements using passive thermoluminescent dosimeters (TLDs). The skin dose is converted to dose equivalent using an average radiation quality factor based on model calculations. The radiological risk estimates, however, are based on organ and tissue doses. This paper describes results from the first space flight (STS-91, 51.65 degrees inclination and approximately 380 km altitude) of a fully instrumented Alderson Rando phantom torso (with head) to relate the skin dose to organ doses. Spatial distributions of absorbed dose in 34 1-inch-thick sections measured using TLDs are described. There is about a 30% change in dose as one moves from the front to the back of the phantom body. Small active dosimeters were developed specifically to provide time-resolved measurements of absorbed dose rates and quality factors at five organ locations (brain, thyroid, heart/lung, stomach and colon) inside the phantom. Using these dosimeters, it was possible to separate the trapped-proton and the galactic cosmic radiation components of the doses. A tissue-equivalent proportional counter (TEPC) and a charged-particle directional spectrometer (CPDS) were flown next to the phantom torso to provide data on the incident internal radiation environment. Accurate models of the shielding distributions at the site of the TEPC, the CPDS and a scalable Computerized Anatomical Male (CAM) model of the phantom torso were developed. These measurements provided a comprehensive data set to map the dose distribution inside a human phantom, and to assess the accuracy and validity of radiation transport models throughout the human body. The results show that for the conditions in the International Space Station (ISS) orbit during periods near the solar minimum, the ratio of the blood-forming organ dose rate to the skin absorbed dose rate is about 80%, and the ratio of the dose equivalents is almost one. The results show that the GCR model dose-rate predictions are 20% lower than the observations. Assuming that the trapped-belt models lead to a correct orbit-averaged energy spectrum, the measurements of dose rates inside the phantom cannot be fully understood. Passive measurements using 6Li- and 7Li-based detectors on the astronauts and inside the brain and thyroid of the phantom show the presence of a significant contribution due to thermal neutrons, an area requiring additional study.

STS-91 Shuttle Project↗
NASA NTRS2014

Radiation Quality Effects on Transcriptome Profiles in 3-D Cultures After Charged Particle Irradiation

In this work, we evaluated the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Current risk models for assessment of space radiation-induced cancer have large uncertainties because the models for adverse health effects following radiation exposure are founded on epidemiological analyses of human populations exposed to low-LET radiation. Reducing these uncertainties requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. In order to better quantify these radiation quality effects in biological systems, we are utilizing novel 3-D organotypic human tissue models for space radiation research. These models hold promise for risk assessment as they provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information.

Patel, Zarana S.↗
NASA NTRS2014

Radiation Quality Effects on Transcriptome Profiles in 3-d Cultures After Particle Irradiation

In this work, we evaluate the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Reducing uncertainties in current risk models requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. We are utilizing novel 3-D organotypic human tissue models that provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information. We identified 45 statistically significant gene sets at 0.05 q-value cutoff, including 14 gene sets common to gamma and titanium irradiation, 19 gene sets specific to gamma irradiation, and 12 titanium-specific gene sets. Common gene sets largely align with DNA damage, cell cycle, early immune response, and inflammatory cytokine pathway activation. The top gene set enriched for the gamma- and titanium-irradiated samples involved KRAS pathway activation and genes activated in TNF-treated cells, respectively. Another difference noted for the high-LET samples was an apparent enrichment in gene sets involved in cycle cycle/mitotic control. It is plausible that the enrichment in these particular pathways results from the complex DNA damage resulting from high-LET exposure where repair processes are not completed during the same time scale as the less complex damage resulting from low-LET radiation.

Patel, Z. S.↗
NASA NTRS1992

Commentary 2 to Cox and Little: radiation-induced oncogenic transformation: the interplay between dose, dose protraction, and radiation quality

There is now a substantial body of evidence for end points such as oncogenic transformation in vitro, and carcinogenesis and life shortening in vivo, suggesting that dose protraction leads to an increase in effectiveness relative to a single, acute exposure--at least for radiations of medium linear energy transfer (LET) such as neutrons. Table I contains a summary of the pertinent data from studies in which the effect is seen. [table: see text] This phenomenon has come to be known as the "inverse dose rate effect," because it is in marked contrast to the situation at low LET, where protraction in delivery of a dose of radiation, either by fractionation or low dose rate, results in a decreased biological effect; additionally, at medium and high LET, for radiobiological end points such as clonogenic survival, the biological effectiveness is independent of protraction. The quantity and quality of the published reports on the "inverse dose rate effect" leaves little doubt that the effect is real, but the available evidence indicates that the magnitude of the effect is due to a complex interplay between dose, dose rate, and radiation quality. Here, we first summarize the available data on the inverse dose rate effect and suggest that it follows a consistent pattern in regard to dose, dose rate, and radiation quality; second, we describe a model that predicts these features; and, finally, we describe the significance of the effect for radiation protection.

Review, Tutorial↗
NASA NTRS2022

FOAM Emissivity Modelling with Foam Properties Tuned by Frequency and Polarization

We model the sea foam emissivity as a part of the work done by an international science team on developing a radiative transfer model of reference quality for the ocean surface emissivity from L band to infrared frequencies. The focus here is on the foam emissivity at frequencies from 1 to 89 GHz. Sensitivity study for different foam properties(foam layer thickness and upper limit of the foam void fraction)guided the effort to tune the model by frequency and polarization. The results show that the differences between simulated and observed brightness temperatures decrease when using tuned foam model.

Magdalena D Anguelova↗
NASA NTRS2004

Assessing the Usefulness of AIRS Radiance Observations in a 4D-Var Assimilation Scheme Using the Penn State/NCAR Mesoscale Model Version 5 (MM5) and a Stand Alone Radiative Transfer Algorithm (SARTA)

Short-term precipitation forecast skill remains poor despite further advances in numerical modeling and data analysis. Utilizing indirect observations, such as the radiance observations obtained from the Atmospheric Infrared Sounder (AIRS), in a 4D-Var assimilation scheme may lead to a rapid improvement in the skill of 12-h QPF. In order to investigate the usefulness of AIRS observations, the adjoint code of a radiative transfer model (SARTA) is developed and linked to MM5 4D-Var system. A statistical comparison of the AIRS radiances with those calculated using the linked MMS-SARTA model is carried out to assess errors in the radiative transfer model, MM5 and AIRS data, and to develop a quality control scheme. Outliers and any bias that may exist in radiative transfer model, MM5 and AIRS data are identified. An adjoint sensitivity study, utilizing the SARTA adjoint model, is then done to identify the relative sensitivities of each spectral channel to such parameters as atmospheric temperature, pressure, and mixing ratio. Another sensitivity study is done using the MM5 alone to determine the sensitivity of the 12-h QPF to model parameters such as atmospheric temperature, pressure, and mixing ratio under various weather regimes (i.e. summertime convection, winter snowfall). Results from these two types of adjoint sensitivity studies are used to determine which AIRS channels contribute most to 12-h QPF under differing weather regimes. This information is useful when conducting 4D-Var experiments using a subset of the 2378 AIRS spectral channels. Finally, 4D-Var experiments are done to analyze the impact of the AIRS observations on the quality of the 12-h QPF results. This project falls under the data assimilation general session topic as specified by the conference organizers.

Carrier, M.↗
NASA NTRS2013

Evaluation of GEOS-5 Sulfur Dioxide Simulations During the Frostburg, MD 2010 Field Campaign.

Sulfur dioxide (SO2) is a major atmospheric pollutant with a strong anthropogenic component mostly produced by the combustion of fossil fuel and other industrial activities. As a precursor of sulfate aerosols that affect climate, air quality, and human health, this gas needs to be monitored on a global scale. Global climate and chemistry models including aerosol processes along with their radiative effects are important tools for climate and air quality research. Validation of these models against in-situ and satellite measurements is essential to ascertain the credibility of these models and to guide model improvements. In this study the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) module running on-line inside the Goddard Earth Observing System version 5 (GEOS-5) model is used to simulate aerosol and SO2 concentrations. Data taken in November 2010 over Frostburg, Maryland during an SO2 field campaign involving ground instrumentation and aircraft are used to evaluate GEOS-5 simulated SO2 concentrations. Preliminary data analysis indicated the model overestimated surface SO2 concentration, which motivated the examination of mixing processes in the model and the specification of SO2 anthropogenic emission rates. As a result of this analysis, a revision of anthropogenic emission inventories in GEOS-5 was implemented, and the vertical placement of SO2 sources was updated. Results show that these revisions improve the model agreement with observations locally and in regions outside the area of this field campaign. In particular, we use the ground-based measurements collected by the United States Environmental Protection Agency (US EPA) for the year 2010 to evaluate the revised model simulations over North America.

Air Quality Campaign↗
NASA NTRSDate not supplied

Comparison between Hayabusa 2 Spectral Measurements and Simulations

Recent Hayabusa 2 spectral measurements are compared with state-of-the-art shock-layer radiation simulations resulting from the LAURA/HARA code suite. These simulations include coupled ablation, which accounts for the injection of ablation products into the flowfield, and coupled radiation, which accounts for radiative energy loss in the flowfield. To enable the cou- pled ablation simulations, a best-estimate model is developed for Hayabusa’s carbon-phenolic ablator based on available published information. The comparison between the simulations and measurements focuses on three atomic nitrogen lines, two atomic oxygen lines, one atomic hydrogen line, and the CN Violet band system. Parametric uncertainties are evaluated for these features using a recently developed capability in LAURA/HARA. These uncertainties capture the impact of flowfield and radiation modeling uncertainties on the observed radiation simulations, and include the impact of coupled radiation and ablation product emission. The resulting parametric uncertainties range from 50 to over 100% for the atomic lines, and 80% for CN Violet. Uncertainties in flowfield kinetics and non-Boltzmann modeling provide the dominant contribution to these uncertainties. For the atomic nitrogen and oxygen lines, com- parisons between the nominal simulations and measurements show agreement well within these simulation uncertainty bounds, with the measurements within 20% of the nominal simulation over most of the trajectory, and within 10% at peak emission. This excellent agreement is un- precedented for observed radiation measurements of atomic lines, where previous Stardust and Hayabusa 1 comparisons were significantly worse. The improved agreement for these Hayabusa 2 comparisons is both the result of improved measurement quality and enhanced flowfield and radiation modeling. For the ablation product emission from the 656 nm atomic hydrogen line, the agreement between measurements and simulations is within ±20% for all trajectory points except one outlier. This good comparison is surprising considering this species depends on the ablation rate and is shown to have strong wake contribution, which both contribute to the large ≈±70% parametric uncertainty. For the ablation product emission from CN Violet, the simulations over-predict the measurements by over a factor of two early in the trajectory, with the comparison improving later in the trajectory. This disagreement for CN Violet is consistent with the ≈±80% parametric uncertainty bounds evaluated for the simulations. To utilize the excellent agreement between the atomic line simulations and measurements in the assessment of the radiative heating margin for a future flight vehicle, the flowfield property binning (FPB) approach is applied. Using the Mars Sample Return (MSR) Earth Entry System (EES) as an example, the combination of the excellent Hayabusa comparisons and the FPB analysis justify nearly a 10% reduction in the radiative heating margin from an assumed baseline margin of 30%. This direct quantitative link between observed radiation measurements and the radia- tive heating margin of future flight vehicles demonstrates the value of these observed radiation measurements.

Shock-Layer Radiative Heating↗
NASA NTRS2010

Pathway Model of the Kinetics of the TGFbeta Antagonist Smad7 and Cross-Talk with the ATM and WNT Pathways

Signal transduction controls cellular and tissue responses to radiation. Transforming growth factor beta (TGFbeta) is an important regulator of cell growth and differentiation and tissue homeostasis, and is often dis-regulated in tumor formation. Mathematical models of signal transduction pathways can be used to elucidate how signal transduction varies with radiation quality, and dose and dose-rate. Furthermore, modeling of tissue specific responses can be considered through mechanistic based modeling. We developed a mathematical model of the negative feedback regulation by Smad7 in TGFbeta-Smad signaling and are exploring possible connections to the WNT/beta -catenin, and ATM/ATF2 signaling pathways. A pathway model of TGFbeta-Smad signaling that includes Smad7 kinetics based on data in the scientific literature is described. Kinetic terms included are TGFbeta/Smad transcriptional regulation of Smad7 through the Smad3-Smad4 complex, Smad7-Smurf1 translocation from nucleus to cytoplasm, and Smad7 negative feedback regulation of the TGFO receptor through direct binding to the TGFO receptor complex. The negative feedback controls operating in this pathway suggests non-linear responses in signal transduction, which are described mathematically. We then explored possibilities for cross-talk mediated by Smad7 between DNA damage responses mediated by ATM, and with the WNT pathway and consider the design of experiments to test model driven hypothesis. Numerical comparisons of the mathematical model to experiments and representative predictions are described.

Carra, Claudio↗
NASA NTRSDate not supplied

Illuminating Albedo: Using MOSAiC Data to Assess the CERES Cloud Radiative Swath (CRS) Albedo Quantification Process

Increasing surface and lower tropospheric air temperatures as a result of rising greenhouse gases are expected to be most pronounced over the Arctic. Such rapid changes alter the surface climate of the region, and impacts can be observed atmospherically, oceanographically, and biogeophysically. Accurately quantifying the impact of decreasing surface albedo on the surface energy budget with satellite observations alone is complicated by a lack of shortwave radiation during winter and seasonal/spatial heterogeneity of surface type and associated spectral albedo. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project features the Cloud Radiative Swath (CRS) product, which builds upon the Single Scanner Footprint (SSF) product by using the NASA Langley Fu-Liou radiative transfer model to calculate a robust and high-quality array of surface and atmospheric radiative fluxes on an instantaneous, footprint-level scale. This study aims to use MOSAiC and CRS data to illuminate potential uncertainties in the CERES albedo production process, with goals of determining 1) spectral albedo under clear sky conditions when stratified by ice concentration, 2) the uncertainty associated with CERES surface albedo “history maps” when compared against observations captured during MOSAiC, and 3) the magnitude of variation between meteorological inputs compared to those from MOSAiC.

Emily Monroe↗
NASA NTRS2002

Technical Report Series on Global Modeling and Data Assimilation: A Coupled Ocean-Atmosphere Radiative Model for Global Ocean Biogeochemical Models - Volume 22

An ocean-atmosphere radiative model (OARM) evaluates irradiance availability and quality in the water column to support phytoplankton growth and drive ocean thermodynamics. An atmospheric component incorporates spectral and directional effects of clear and cloudy skies as a function of atmospheric optical constituents, and spectral reflectance across the air-sea interface. An oceanic component evaluates the propagation of spectral and directional irradiance through the water column as a function of water, five phytoplankton groups, and chromophoric dissolved organic matter. It tracks the direct and diffuse streams from the atmospheric component, and a third stream, upwelling diffuse irradiance. The atmospheric component of OARM was compared to data sources at the ocean surface with a coefficient of determination (r2) of 0.97 and a root mean square of 12.1%.

Gregg, Watson W.↗
NASA NTRSDate not supplied

More than RBE: Exploring Two Decades of Space Radiation Quality and Carcinogenesis Research and How NASA Manages Cancer Risk

NASA’s Space Radiation Element (SRE), both as a stand-alone entity and as part of the Human Research Program, has invested heavily into investigating how the different qualities of radiation and low dose rates relevant to the space environment and how these factors effect long term carcinogenesis risk. NASA’s current model to assess astronaut excess cancer risk due to radiation exposure utilizes data generated from both in vitro and in vivo models to inform quality factor and dose-rate functions that scales risk estimates originally established from human cohorts exposed to terrestrial radiation, most notably the Lifespan Study of atomic bomb survivors (LSS). As part of an effort to update these quality function, the SRE hosted a workshop in on radiation quality in September 2021 and a workshop on dose-rate at NASA HRP’s Investigators’ Workshop in February 2022 where current and former grantees presented data that could potentially be incorporated into assessing carcinogenic risk. This presentation is intended to both inform the broader research community of the outcome of those workshops and generate a discussion as to what biological data should be generated to better inform NASA’s risk estimates. Additionally, NASA’s current risk disposition for cancer assessment will be discussed and clarified. We look forward to hearing feedback from the Radiation Research Society community!

Brock J Sishc↗
NASA NTRS2011

Biological Based Risk Assessment for Space Exploration

Exposures from galactic cosmic rays (GCR) - made up of high-energy protons and high-energy and charge (HZE) nuclei, and solar particle events (SPEs) - comprised largely of low- to medium-energy protons are the primary health concern for astronauts for long-term space missions. Experimental studies have shown that HZE nuclei produce both qualitative and quantitative differences in biological effects compared to terrestrial radiation, making risk assessments for cancer and degenerative risks, such as central nervous system effects and heart disease, highly uncertain. The goal for space radiation protection at NASA is to be able to reduce the uncertainties in risk assessments for Mars exploration to be small enough to ensure acceptable levels of risks are not exceeded and to adequately assess the efficacy of mitigation measures such as shielding or biological countermeasures. We review the recent BEIR VII and UNSCEAR-2006 models of cancer risks and their uncertainties. These models are shown to have an inherent 2-fold uncertainty as defined by ratio of the 95% percent confidence level to the mean projection, even before radiation quality is considered. In order to overcome the uncertainties in these models, new approaches to risk assessment are warranted. We consider new computational biology approaches to modeling cancer risks. A basic program of research that includes stochastic descriptions of the physics and chemistry of radiation tracks and biochemistry of metabolic pathways, to emerging biological understanding of cellular and tissue modifications leading to cancer is described.

Cucinotta, Francis A.↗
NASA NTRS2013

Correlated Uncertainties in Radiation Shielding Effectiveness

The space radiation environment is composed of energetic particles which can deliver harmful doses of radiation that may lead to acute radiation sickness, cancer, and even death for insufficiently shielded crew members. Spacecraft shielding must provide structural integrity and minimize the risk associated with radiation exposure. The risk of radiation exposure induced death (REID) is a measure of the risk of dying from cancer induced by radiation exposure. Uncertainties in the risk projection model, quality factor, and spectral fluence are folded into the calculation of the REID by sampling from probability distribution functions. Consequently, determining optimal shielding materials that reduce the REID in a statistically significant manner has been found to be difficult. In this work, the difference of the REID distributions for different materials is used to study the effect of composition on shielding effectiveness. It is shown that the use of correlated uncertainties allows for the determination of statistically significant differences between materials despite the large uncertainties in the quality factor. This is in contrast to previous methods where uncertainties have been generally treated as uncorrelated. It is concluded that the use of correlated quality factor uncertainties greatly reduces the uncertainty in the assessment of shielding effectiveness for the mitigation of radiation exposure.

Werneth, Charles M.↗
NASA NTRS2018

Computational Model Prediction and Biological Validation Using Simplified Mixed Field Exposures for the Development of a GCR Reference Field

The yield of chromosomal aberrations has been shown to increase in the lymphocytes of astronauts after long-duration missions of several months in space. Chromosome exchanges, especially translocations, are positively correlated with many cancers and are therefore a potential biomarker of cancer risk associated with radiation exposure. Although extensive studies have been carried out on the induction of chromosomal aberrations by low- and high-LET radiation in human lymphocytes, fibroblasts, and epithelial cells exposed in vitro, there is a lack of data on chromosome aberrations induced by low dose-rate chronic exposure and mixed field beams such as those expected in space. Chromosome aberration studies at NSRL will provide the biological validation needed to extend the computational models over a broader range of experimental conditions (more complicated mixed fields leading up to the galactic cosmic rays (GCR) simulator), helping to reduce uncertainties in radiation quality effects and dose-rate dependence in cancer risk models. These models can then be used to answer some of the open questions regarding requirements for a full GCR reference field, including particle type and number, energy, dose rate, and delivery order. In this study, we designed a simplified mixed field beam with a combination of proton, helium, oxygen, and iron ions with shielding or proton, helium, oxygen, and titanium without shielding. Human fibroblasts cells were irradiated with these mixed field beam as well as each single beam with acute and chronic dose rate, and chromosome aberrations (CA) were measured with 3-color fluorescent in situ hybridization (FISH) chromosome painting methods. Frequency and type of CA induced with acute dose rate and chronic dose rates with single and mixed field beam will be discussed. A computational chromosome and radiation-induced DNA damage model, BDSTRACKS (Biological Damage by Stochastic Tracks), was updated to simulate various types of CA induced by acute exposures of the mixed field beams used for the experiments. The chromosomes were simulated by a polymer random walk algorithm with restrictions to their respective domains in the nucleus [1]. The stochastic dose to the nucleus was calculated with the code RITRACKS [2]. Irradiation of a target volume by a mixed field of ions was implemented within RITRACKs, and the fields of ions can be delivered over specific periods of time, allowing the simulation of dose-rate effects. Similarly, particles of various types and energies extracted from a pre-calculated spectra of galactic cosmic rays (GCR) can be used in RITRACKS. The number and spatial location of DSBs (DNA double-strand breaks) were calculated in BDSTRACKS using the simulated chromosomes and local (voxel) dose. Assuming that DSBs led to chromosome breaks, and simulating the rejoining of damaged chromosomes occurring during repair, BDSTRACKS produces the yield of various types of chromosome aberrations as a function of time (only final yields are presented). A comparison between experimental and simulation results will be shown.

Hada, M.↗
NASA NTRSDate not supplied

Importance of Radiative Transfer Models in Atmospheric Remote Sensing

Radiative transfer models (RTMs) play a significant role in the development of satellite instruments for remote sensing applications. These models simulate electromagnetic radiation's propagation through the atmosphere, providing valuable insights into atmosphere-radiation interactions. RTMs facilitate the optimization of satellite instrument designs, ensuring their ability to measure targeted atmospheric and surface properties accurately. Moreover, they aid in simulating instrument’s measurements under various atmospheric conditions, enabling calibration and validation processes to enhance data quality and reliability. RTMs are extensively used in the Observing System Simulation Experiments (OSSE), to generate synthetic observations. By incorporating RTMs into OSSE, we can assess the potential impact of future satellite missions, sensor configurations, and data assimilation techniques. This approach allows for the optimization of satellite instruments and constellations and the evaluation of their influence on weather forecasting, climate monitoring, and other Earth science applications. Another crucial application area of RT models is data assimilation, where they play a fundamental role in combining satellite observations with numerical models to improve atmospheric and environmental predictions. RTMs provide the link between observed radiances and atmospheric parameters, enhancing the accuracy of numerical models and generating more reliable forecasts for weather events, air quality assessments, and climate projections. Moreover, adapting RT models to capture the intricate radiation interactions within the Planetary Boundary Layer will significantly contribute to improving weather forecasting and climate change projections. Current community radiative transfer (RT) models are primarily developed and optimized for operational data assimilation of satellite observations. These models excel at assimilating satellite data into numerical weather prediction models to improve forecast accuracy. However, their focus on data assimilation limits their suitability for other important applications, such as satellite instrument development, OSSE, and Planetary Boundary Layer (PBL) studies. Moreover, for PBL studies, RT models need to be adapted to capture the intricate radiation interactions within this crucial atmospheric layer. Developing RT models that can represent the PBL's unique characteristics, such as surface interactions, will contribute significantly to understanding and predicting weather phenomena, air quality, and climate dynamics. This abstract provides a comprehensive overview of the current status of RT models and highlights their limitations concerning satellite instrument development, OSSE, and PBL studies. Addressing these shortcomings requires concerted efforts to enhance RT models' capabilities and expand their applications beyond data assimilation. By investing in research and development to improve these

Isaac Moradi↗
NASA NTRS1978

Simplified multiple scattering model for radiative transfer in turbid water

Quantitative analytical procedures for relating selected water quality parameters to the characteristics of the backscattered signals, measured by remote sensors, require the solution of the radiative transport equation in turbid media. Presented is an approximate closed form solution of this equation and based on this solution, the remote sensing of sediments is discussed. The results are compared with other standard closed form solutions such as quasi-single scattering approximations.

Ghovanlou, A. H.↗