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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2007

Evaluating Shielding Effectiveness for Reducing Space Radiation Cancer Risks

We discuss calculations of probability distribution functions (PDF) representing uncertainties in projecting fatal cancer risk from galactic cosmic rays (GCR) and solar particle events (SPE). The PDF s are used in significance tests of the effectiveness of potential radiation shielding approaches. Uncertainties in risk coefficients determined from epidemiology data, dose and dose-rate reduction factors, quality factors, and physics models of radiation environments are considered in models of cancer risk PDF s. Competing mortality risks and functional correlations in radiation quality factor uncertainties are treated in the calculations. We show that the cancer risk uncertainty, defined as the ratio of the 95% confidence level (CL) to the point estimate is about 4-fold for lunar and Mars mission risk projections. For short-stay lunar missions (<180 d), SPE s present the most significant risk, however one that is mitigated effectively by shielding, especially for carbon composites structures with high hydrogen content. In contrast, for long duration lunar (>180 d) or Mars missions, GCR risks may exceed radiation risk limits, with 95% CL s exceeding 10% fatal risk for males and females on a Mars mission. For reducing GCR cancer risks, shielding materials are marginally effective because of the penetrating nature of GCR and secondary radiation produced in tissue by relativistic particles. At the present time, polyethylene or carbon composite shielding can not be shown to significantly reduce risk compared to aluminum shielding based on a significance test that accounts for radiobiology uncertainties in GCR risk projection.

Cucinotta, Francis A.↗
NASA NTRS2013

NASA Models of Space Radiation Induced Cancer, Circulatory Disease, and Central Nervous System Effects

The risks of late effects from galactic cosmic rays (GCR) and solar particle events (SPE) are potentially a limitation to long-term space travel. The late effects of highest concern have significant lethality including cancer, effects to the central nervous system (CNS), and circulatory diseases (CD). For cancer and CD the use of age and gender specific models with uncertainty assessments based on human epidemiology data for low LET radiation combined with relative biological effectiveness factors (RBEs) and dose- and dose-rate reduction effectiveness factors (DDREF) to extrapolate these results to space radiation exposures is considered the current "state-of-the-art". The revised NASA Space Risk Model (NSRM-2014) is based on recent radio-epidemiology data for cancer and CD, however a key feature of the NSRM-2014 is the formulation of particle fluence and track structure based radiation quality factors for solid cancer and leukemia risk estimates, which are distinct from the ICRP quality factors, and shown to lead to smaller uncertainties in risk estimates. Many persons exposed to radiation on earth as well as astronauts are life-time never-smokers, which is estimated to significantly modify radiation cancer and CD risk estimates. A key feature of the NASA radiation protection model is the classification of radiation workers by smoking history in setting dose limits. Possible qualitative differences between GCR and low LET radiation increase uncertainties and are not included in previous risk estimates. Two important qualitative differences are emerging from research studies. The first is the increased lethality of tumors observed in animal models compared to low LET radiation or background tumors. The second are Non- Targeted Effects (NTE), which include bystander effects and genomic instability, which has been observed in cell and animal models of cancer risks. NTE's could lead to significant changes in RBE and DDREF estimates for GCR particles, and the potential effectiveness of radiation mitigator's. The NSRM- 2014 approaches to model radiation quality dependent lethality and NTE's will be described. CNS effects include both early changes that may occur during long space missions and late effects such as Alzheimer's disease (AD). AD effects 50% of the population above age 80-yr, is a degenerative disease that worsens with time after initial onset leading to death, and has no known cure. AD is difficult to detect at early stages and the small number of low LET epidemiology studies undertaken have not identified an association with low dose radiation. However experimental studies in mice suggest GCR may lead to early onset AD. We discuss modeling approaches to consider mechanisms whereby radiation would lead to earlier onset of occurrence of AD. Biomarkers of AD include amyloid beta (A(Beta)) plaques, and neurofibrillary tangles (NFT) made up of aggregates of the hyperphosphorylated form of the micro-tubule associated, tau protein. Related markers include synaptic degeneration, dentritic spine loss, and neuronal cell loss through apoptosis. Radiation may affect these processes by causing oxidative stress, aberrant signaling following DNA damage, and chronic neuroinflammation. Cell types to be considered in multi-scale models are neurons, astrocytes, and microglia. We developed biochemical and cell kinetics models of DNA damage signaling related to glycogen synthase kinase-3(Beta) (GSK3(Beta)) and neuroinflammation, and considered multi-scale modeling approaches to develop computer simulations of cell interactions and their relationships to A(Beta) plaques and NFTs. Comparison of model results to experimental data for the age specific development of A(Beta) plaques in transgenic mice will be discussed.

Cucinotta, Francis A.↗
DOE OSTI2021

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer

Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language processing algorithms convert unstructured free text data into structured data that can be extracted and analyzed at scale. In medicine, this unlocking of the rich, expressive data within clinical free text in electronic medical records will help untap the full potential of big data for research and clinical purposes. Recent major NLP algorithmic advances have significantly improved the performance of these algorithms, leading to a surge in academic and industry interest in developing tools to automate information extraction and phenotyping from clinical texts. Thus, these technologies are poised to transform medical research and alter clinical practices in the future. Radiation oncology stands to benefit from NLP algorithms if they are appropriately developed and deployed, as they may enable advances such as automated inclusion of radiation therapy details into cancer registries, discovery of novel insights about cancer care, and improved patient data curation and presentation at the point of care. However, challenges remain before the full value of NLP is realized, such as the plethora of jargon specific to radiation oncology, nonstandard nomenclature, a lack of publicly available labeled data for model development, and interoperability limitations between radiation oncology data silos. Successful development and implementation of high quality and high value NLP models for radiation oncology will require close collaboration between computer scientists and the radiation oncology community. Here, we present a primer on artificial intelligence algorithms in general and NLP algorithms in particular; provide guidance on how to assess the performance of such algorithms; review prior research on NLP algorithms for oncology; and describe future avenues for NLP in radiation oncology research and clinics.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2001

Physical and biological studies with protons and HZE particles in a NASA supported research center in radiation health

NASA has established and supports a specialized center for research and training (NSCORT) to specifically address the potential deleterious effects of HZE particles on human health. The NSCORT in radiation health is a joint effort between Lawrence Berkeley National Laboratory (LBNL) and Colorado State University (CSU). The overall scope of research encompasses a broad range of subjects from microdosimetric studies to cellular and tissue responses to initial damage produced by highly energetic protons and heavy charged particles of the type found in galactic cosmic rays (GCR) spectrum. The objectives of the microdosimetry studies are to determine the response of Tissue Equivalent Proportional Counter (TEPC) to cosmic rays using ground based accelerators. This includes evaluation of energy loss due to the escape of high-energy delta rays and increased energy deposition due to the enhanced delta ray production in the wall of the detector. In this report major results are presented for 56Fe at 1000, 740, 600 and 400 MeV/nucleon. An assessment of DNA repair and early development of related chromosomal changes is extremely important to our overall understanding of enhanced biological effectiveness of high LET particle radiation. Results are presented with respect to the fidelity of the rejoining of double strand breaks and the implications of misrejoining. The relationship between molecular and cytogenetic measurements is presented by studying damage processing in highly heterochromatic supernumerary (correction of sypernumerary) X chromosomes and the active X-chromosome. One of the important consequences of cell's inability to handle DNA damage can be evaluated through mutation studies. Part of our goal is the assessment of potential radioprotectors to reduce the mutation yield following HZE exposures, and some promising results are presented on one compound. A second goal is the integration of DNA repair and mutation studies. Results are presented on a direct comparison of initial double strand breaks induction, the time course and fidelity of double strand break rejoining, cell killing and mutation induction in the same human model system. In order to understand the carcinogenic potential of protons and HZE particles, the role of damaged microenvironment in this process must be understood. In this project it has been postulated that radiation affects the microenvironment, which then modifies cell interactions in a manner conducive to neoplastic progression. Both TGF-beta and FGF-2 are important components of microenvironment. A recent result on the assessment of the role of FGF-2 and its cross-talk with TGF-beta as a function of radiation quality is presented. Theoretical modeling has so far played a central role in analyzing and integrating experimental data on repair and mutation studies and predicting new phenomena. The integrated NSCORT program also provides a broad training experience for students and postdoctoral fellows in space radiation health.

NASA Discipline Radiation Health↗
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↗
DOE OSTI2021

Estimating Surface Solar Irradiance Using Meteosat-8 Satellite for India and Surrounding Regions (2017-2019)

Using the Physical Solar Model, Version 3 (PSM V3), the National Renewable Energy Laboratory—in collaboration with the University of Wisconsin, the National Oceanic and Atmospheric Administration, and Solar Consulting Services—produced modeled surface solar irradiance based on Meteosat-8 satellite cloud information. PSM V3 implements a physics-based radiative transfer approach to model surface solar irradiance using cloud properties processed from raw satellite data and ancillary data such as aerosol optical depth and precipitable water vapor from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Further, the modeled surface solar irradiance was validated using 10 high-quality ground measurement data from the Baseline Surface Radiation Network. The modeled data showed good correlation with the ground measurement, and the overall uncertainty is less than 35% for all validation locations. Because of the satellite viewing geometry, the Indian and European locations demonstrated higher uncertainties than the African locations, where the Meteosat-8 satellite has a more nadir viewing geometry. Further, instruction on how to access the data is provided.

14 SOLAR ENERGY↗
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.↗