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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Generating Novel Aroma Phenotypes Using Commercial Wine Samples to Characterize an F1 Population

Due to their disease tolerance and cold hardy nature, interspecific hybrid grapes are widely grown in the Midwestern and Northeastern United States, with additional interest worldwide in the face of increased abiotic and biotic stresses from climate change. However, the aroma profile of these hybrids is unique and generally less popular in comparison with Vitis vinifera grapes. One of the challenges in any phenotyping project is first defining the traits of interest. As wine quality was our ultimate metric of interest, the aroma profile of commercial wines produced from the parents of a breeding population ( Vitis aestivalis derived ‘Norton’ x V. vinifera . ‘Cabernet Sauvignon’) was first assessed for traits of interest. We investigated 11 commercial wines each of Norton, a popular hybrid in Missouri and Cabernet Sauvignon (Cab) for their volatile profiles using the more inclusive metabolomics-based workflow. We then analyzed 21 Norton and 21 Cab grapes from different sites and vintages for the free and bound volatile compounds using HS-SPME-GCMS to validate the differences in wine. The GCMS data was processed using XCMS software to find features that were different between the two cultivars. The two cultivars were found to have differences in their volatile profiles, with 304 features different for wine volatiles, 418 features different for free volatiles, and 302 features different for bound volatiles at 0.05 significance level and with at least a 1.5-fold change between the two cultivars. Those features were used to identify several odor-active compounds in both grapes and wines, including β-damascenone, β-ionone, eugenol, 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN), and methyl salicylate. Some of the identified compounds were higher in Norton than Cab; however, several features were higher in Cab. Using the identified aroma compounds as markers, we phenotyped an F1 population of Norton and Cab. The F1 population was found to be segregating for many aroma compounds with some genotypes demonstrating an even higher concentration of aroma volatiles than either of the parents. Ultimately, using commercially available samples paired with untargeted analysis proved to be an efficient way to determine phenotypes of interest for further analysis and may offer an easy way to choose potential parents with desired traits for breeding.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Operations Challenges in a Dynamic Environment: A Three-Year Perspective of SAGE III

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was delivered to the International Space Station (ISS) on 23 February 2017. The SAGE III/ISS payload was robotically installed external to the ISS and began acquiring science measurements on 17 March 2017. The SAGE III/ISS instrument retrieves vertical profiles of atmospheric ozone, multi-wavelength aerosol extinctions, and other gaseous species. This paper will focus on the improvements made to the operations of the SAGE III/ISS payload. A key focus of the operations team following commissioning was to create robust tools that aid in the operations of the payload. A close collaboration with the SAGE III/ISS ground systems team allowed for the development of web-based tools to continuously monitor the health of the payload. The mission operations team also worked with the SAGE III/ISS science team to gain a better sense of how the instrument works to maximize the quality and quantity of the science data collected. Another unique aspect of the SAGE III/ISS payload, that will be discussed, is the challenges of operating a hosted payload on the ISS; an active platform that has frequent attitude maneuvers, dockings, and EVAs. This active environment increases the need for the SAGE III/ISS operations team command to the payload. Through coordination and teamwork, SAGE III/ISS mission has developed an operations team, tool, and procedures that have successfully managed the payload around ISS activities and recovered from multiple instrument upsets. This has led the SAGE III/ISS payload to successfully surpass the acquisition metrics set forth prior to launch, allowing for the continued contribution to studying the atmospheric composition of the stratosphere and how it plays a role in Earth’s climate.

SAGE III↗
DOE OSTI2026

Employment access assessed using the mobility energy productivity (MEP) metric

Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning

Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies to achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Automated Segmentation of Twin Boundaries in TRISO Silicon Carbide Using Deep Neural Networks

Coated particle fuels, such as the tristructural isotropic (TRISO) fuel particle, are essential for high-temperature gas reactor (HTGR) applications due to their efficiency and stability under normal and off-normal conditions. However, widespread commercialization and deployment of this technology for next-generation nuclear applications require robust quality assurance and quality control (QA/QC) methods linking fabrication, properties, and performance. Of the many important metrics for TRISO QA/QC, quantification of the silicon carbide (SiC) microstructure is critical because it correlates with fission product retention during irradiation. Previous work has shown extensive twinning of the SiC microstructure, which strongly affects microstructural metrics; however, twin grain boundaries are not expected play a significant role in fission product diffusion. This report summarizes the initial development, training, and testing of a machine learning image processing algorithm to detect twin grain boundaries in a backscattered electron image, which can be removed so that microstructural metrics can be recalculated for legacy data. Further development and deployment of this model will provide automated, scalable improvement of potential QA/QC methods for the SiC layer of TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2019

Sound Quality Metric Indicators of Rotorcraft Noise Annoyance Using Multilevel Regression Analysis

Although every helicopter in operation has to go through a noise certification process, annoyance due to helicopters still persists within various communities. This implies that certification metrics do not capture the full range of human response and that predicted reactions could be supplemented with other information, which could be acoustic or non-acoustic in nature. The rotorcraft sound quality metric (RoQM) psychoacoustic experiment was designed to determine the relative importance of sound quality metrics (SQMs), such as sharpness, tonality, loudness, fluctuation strength and impulsiveness, on human annoyance to rotorcraft sounds. Starting from a baseline helicopter recording, SQMs were varied synthetically and presented to subjects who responded with an annoyance rating. The RoQM test took place in 2017 at the NASA Langley Research Center in the Exterior Effects Room. A total of 105 sounds were played to 40 subjects. The relationship between helicopter noise sound quality and annoyance is modeled using multilevel regression in this work, which takes into account the variability of responses across subjects. Previous analyses did not consider such a grouping of the data.

Matthew Boucher↗
DOE OSTI2017

China Green Low-Carbon City Index: Report on the Performance of 100+ Cities (2010-2015)

The main purpose of the new China Green Low-Carbon City Index (CGLCI, or City Index ) is to evaluate the status of green and low-carbon development for a large number of Chinese cities. Chinese cities are formulating plans and implementing programs to address national initiatives, especially the national low-carbon pilot program for 36 cities and six provinces. However, there is not yet an established framework for measuring, reporting, or evaluating low-carbon progress across Chinese cities, despite the development of a number of Chinese and international city indicator systems. The new China City Index highlights energy use and carbon emissions of Chinese cities, along with environmental and socio-economic indicators. We selected metrics (indicators) that have data available in China’s statistical system, are commonly used internationally, and reflect Chinese policy goals. (See Table ES-1.) We then benchmarked and ranked Chinese cities in terms of their status and progress, identified potential areas for improvement, and identified top-runners. By “low-carbon” we mean reducing emissions of carbon dioxide (CO 2 ) and methane (CH 4 ), with a focus on energy-related CO 2 . The term “carbon” is used as short-hand for these GHGs throughout the report. By “green” we recognize multiple environmental parameters related to urbanization and climate change: air quality, water use, solid waste, transport networks, and urban green space. In early 2017, China expanded its low-carbon pilot cities program, adding 45 more cities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗
NASA NTRS2021

Coastal California Water Resources: Assessing Estuarine Ecosystems in California for Improved Wetland Monitoring and Management

Estuaries are vital ecosystems that serve important ecological functions. The Marine Life Protection Act aims to protect these ecosystems by establishing a network of marine protected areas (MPAs), in part by requiring regulatory agencies to monitor estuary extent and health. However, California has 23 estuarine MPAs (EMPAs) and approximately 440,000 total acres of estuarine habitat and, therefore, ground-based data collection can be time and resource intensive. This project used remotely sensed data to examine the health of California EMPAs in an effort to supplement ground-based field measurements. Specifically using Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), this project assessed mouth state, inundation extent, turbidity, Chlorophyll-a, and colored dissolved organic matter (CDOM) for estuaries observable with these sensors. The Normalized Water Difference Index (NDWI) from Sentinel-2 MSI was capable of capturing estuary mouth state and inundation extent. Meanwhile, Landsat 8 OLI and Sentinel-2 MSI indicated a capacity to capture differences in water quality metrics coinciding with changes to estuary mouth state using algorithms applied in Google Earth Engine (GEE). The GEE California Estuary Assessment (CEA) tools will allow project partners to better monitor and understand estuarine dynamics and health.

Karina Alvarez↗
DOE OSTI2019

Dark Energy Survey’s Observation Strategy, Tactics, and Exposure Scheduler

The Dark Energy Survey is a “stage III” dark energy experiment, performing an optical imaging survey to measure cosmological equation of state parameters using four independent methods. The scope and complexity of the survey, originally scheduled for 525 nights of observing spread over five years and combining a 5000 degree wide survey with a 10 field weekly time-domain survey, introduced complex strategic and tactical scheduling problems that needed to be addressed. We begin with an overview of the process used to develop DES strategy and tactics, from the inception of the project, to task forces that studied and developed strategy changes over the course of the survey, to the nightly pre-observing meeting in which immediate tactical issues were addressed. We then summarize the strategic choices made for each sub-survey, including metrics, scheduling considerations, choice of time domain fields and their sequences of exposures, and wide survey footprint and pointing layout choices. We go on to describe the detailed process that determined which specific exposures were taken at which specific times. We give a chronology of the strategic and tactical peculiarities of each year of observing, including the proposal and execution of a sixth year. We give an overview of obstac, the implementation of the DES scheduler used to simulate and evaluate strategic and tactical options, and automate exposure scheduling; and describe developments in obstac for use after DES. Appendices describe further details of data quality evaluation, t, and teff; airmass calculation; and modeling of the seeing and sky brightness. The significant corpus of DES data indicates that the simple scaling relations for seeing as a function of wavelength and airmass derived from the Kolmogorov turbulence model work adequately for exposure planning purposes: deviations from these relations are modest in comparison with short time-scale seeing variations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

TENDL-2017: the making of multi-faceted technological nuclear data library - 25340

Multi-purpose methodical nuclear data libraries generated by TALYS/T6 as Evaluated Nuclear Data Library TENDL have been released regularly since 2008. Considerable experience has been acquired during those early production of such unique, truly multi-faceted, multi-particle nuclear data libraries based on the feedback from the developers, evaluators, processing experts and, most importantly, users. The backbone of this achievement is simple and robust: completeness, quality, upgradability and, most of all, reproducibility and methodology. Since TENDL has been seamlessly adopted by many different applications (accelerator, astrophysics, fusion, fission, medical) that require multi-faceted nuclear reaction data forms for shielding, radio-protection, transmutation, materials or earth sciences, it is felt necessary to understand its strengths and remaining weaknesses. The essential knowledge is not the TENDL library itself, but rather the necessary methods, processes, codes, tools and know-how that go into the making of every evaluations of such a library. Current efforts are focused on a proper evaluation of the underlying physics and incorporation of information and metrics into the scientific TALYS/T6 system. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

The Double-edged Sword of Data-driven Super-Resolution: Adversarial Super-resolution Models

Data-driven super-resolution (SR) methods are often integrated into imaging pipelines as preprocessing steps to improve downstream tasks such as classification and detection. However, these SR models introduce a previously unexplored attack surface into imaging pipelines. In this paper, we present AdvSR, a framework demonstrating that adversarial behavior can be embedded directly into SR model weights during training, requiring no access to inputs at inference time. Unlike prior attacks that perturb inputs or rely on backdoor triggers, AdvSR operates entirely at the model level. By jointly optimizing for reconstruction quality and targeted adversarial outcomes, AdvSR produces models that appear benign under standard image quality metrics while inducing downstream misclassification. We evaluate AdvSR on three SR architectures (SRCNN, EDSR, SwinIR) paired with a YOLOv11 classifier and demonstrate that AdvSR models can achieve high attack success rates with minimal quality degradation. These findings highlight a new model-level threat for imaging pipelines, with implications for how practitioners source and validate models in safety-critical applications.

Sullivan, Haley [ORNL] (ORCID:0000000274069217)↗
DOE OSTI2016

Low Temperature Geothermal Play Fairway Analysis For The Appalachian Basin: Phase 1 Revised Report November 18, 2016

Geothermal energy is an attractive sustainable energy source. Yet project developers need confirmation of the resource base to warrant their time and financial resources. The Geothermal Play Fairway Analysis of the Appalachian Basin evaluated risk metrics that communicate the favorability of potential low-temperature geothermal energy resources in reservoirs more than 1000 m below the surface. This analysis is focused on the direct use of the heat, rather than on electricity production. Four risk factors of concern for direct-use geothermal plays in the Appalachian Basin portions of New York, Pennsylvania, and West Virginia are examined individually, and then in combination: 1) thermal resource quality, 2) natural reservoir quality, 3) induced seismicity, and 4) utilization opportunities. Uncertainty in the risk estimation is quantified. Based on these metrics, geothermal plays in the Appalachian Basin were identified as potentially viable for a variety of direct-use-heat applications. The methodologies developed in this project may be applied in other sedimentary basins as a foundation for low temperature (50-150 °C), direct use geothermal resource, risk, and uncertainty assessment. Three methods with which to combine the four risk factors were used. Among these, the averaging of the individual risk factors indicates the most favorable counties within the study area are the West Virginia counties of Monongalia, Harrison, Lewis (dubbed the Morgantown–Clarksburg play fairway), Putnam, and Kanawha (Charleston play fairway), the New York counties of Chemung and Steuben plus adjacent Bradford county in Pennsylvania (Corning–Ithaca play fairway), and the Pennsylvania counties of Mercer, Crawford, Erie, and Warren, and adjacent Chautauqua county in New York (together, the Meadville–Jamestown play fairway). These higher priority regions are surrounded by broader medium priority zones. Also worthy of additional exploration is a broad region near Pittsburgh Pennsylvania, for which the available geological data are insufficient to fully analyze the geological risks but yet the population is high. First, to assess the spatial variation in the depth to which one would need to drill to obtain geothermal temperatures that are useful to a future project, the project used bottom-hole temperature data from Appalachian Basin oil and gas exploration. These bottom hole temperature data are abundant but of low quality. Second, the project examined the potential for sufficient water flow rates through rocks to harvest heat from a geothermal well field, considering only natural reservoirs. This analysis provides a very incomplete picture of spatial variability of natural reservoirs because the oil and gas reservoir data lack key properties and are spatially biased toward those locations with profitable amounts of hydrocarbons in the rock pore spaces. Third, in light of the fact that earthquake activity has been induced in several states by subsurface work related to the oil and gas industry, this project examined the potential for similar activity in the Appalachian Basin. Acknowledging that data for such a task are insufficient, we utilized what was available: records of seismic activity, regional estimates of the orientations of stress in the rocks, and locations and orientations of zones of lateral change in rock properties at depths down to several kilometers below Earth’s surface. With these data, we created a first approximation of spatially variable risks for induced earthquakes. Because no data existed with which to test the reliability of these methods, the results have a high degree of uncertainty. Fourth, we examined the spatial variability of the above-the-ground factors that contribute to the economical viability of projects to tap low-temperature geothermal resources for direct-use. We worked principally with population density as a regionally known variable that would impact the cost of district heating. The resulting maps omit the costs of producing the hot water from the ground, because the below-ground costs are directly coupled to the thermal resource risk factor and natural reservoir risk factor – later analyses of those costs will be needed. The result of the district heating analysis is highly skewed: few census locations yielded a low estimated surface cost. The team also identified more than 165 prospects for high value direct-use geothermal energy opportunities such as industrial sites, university campuses, and federal facilities, among others. At the closure of this regional analysis, the most significant technical uncertainties are 1) reservoir distribution and capacities; 2) validity of thermal resource maps, and 3) the holistic estimation of Levelized Cost of Heat for favorable geological situations.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Reference range of liver corrected T1 values in a population at low risk for fatty liver disease—a UK Biobank sub-study, with an appendix of interesting cases

Purpose: Corrected T1 (cT1) value is a novel MRI-based quantitative metric for assessing a composite of liver inflammation and fibrosis. It has been shown to distinguish between non-alcoholic fatty liver disease (NAFL) and non-alcoholic steatohepatitis. However, these studies were conducted in patients at high risk for liver disease. This study establishes the normal reference range of cT1 values for a large UK population, and assesses interactions of age and gender. Methods: MR data were acquired on a 1.5 T system as part of the UK Biobank Imaging Enhancement study. Measures for Proton Density Fat Fraction and cT1 were calculated from the MRI data using a multiparametric MRI software application. Data that did not meet quality criteria were excluded from further analysis. Inter and intra-reader variability was estimated in a set of data. A cohort at low risk for NAFL was identified by excluding individuals with BMI ≥ 25 kg/m{sup 2} and PDFF ≥ 5%. Of the 2816 participants with data of suitable quality, 1037 (37%) were classified as at low risk. Results: The cT1 values in the low-risk population ranged from 573 to 852 ms with a median of 666 ms and interquartile range from 643 to 694 ms. Iron correction of T1 was necessary in 36.5% of this reference population. Age and gender had minimal effect on cT1 values. Conclusion: The majority of cT1 values are tightly clustered in a population at low risk for NAFL, suggesting it has the potential to serve as a new quantitative imaging biomarker for studies of liver health and disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Evaluation of Time-Series Gap-Filling Methods for Solar Irradiance Applications

A complete solar resource data set is essential for any stage of a solar energy project - from feasibility studies to daily operations. But measured or modeled solar resource data are prone to data gaps and data quality issues. To mitigate these issues, a data imputation process should be implemented to obtain a complete and reliable temporal and spatial data series. This study focused on imputing temporal scales by applying random and artificial data gaps and then implementing eight imputation methods, including the Kalman filtering and smoothing and stine interpolations. These methods were implemented on 1-minute to half hourly irradiance data for 1 year using a few locations from the National Solar Radiation Database (NSRDB) and ground measurement data set. The results demonstrated that some of the simpler methods, such as the stine and linear interpolation methods, were the relatively best models based on the statistical metrics for imputing NSRDB and ground measurement data, respectively.

14 SOLAR ENERGY↗
NASA NTRS2011

Environmental Signatures for Habitability: What to Measure and How to Rank the Habitability Potential of Mars

The environmental signatures for habitability are not necessarily biosignatures, even though on Earth, they are definitive proof of habitability. It is the constant overprint of the chemical signatures of life that makes it difficult to recognize the chemical and physical properties of a potentially habitable environment as distinct from an inhabited one. Mars Science Laboratory (MSL) will soon embark on a mission to Mars to assess its past or present habitability, so it is useful to examine how we measure habitability on Earth and prepare for how that approach may differ for Mars. This exercise includes: (a) articulation of fundamental assumptions about habitability, (b) an inventory of factors that affect habitability, (c) development of metrics, measurement approach and implementation, and (d) a new classification scheme for planetary habitability that goes beyond the binary "yes" or "no." There may be dozens of factors that affect habitability and they can be weighted as a function of specific environment. However a robotic, in situ investigation even on Earth has constraints that prevent the measurement of every environmental factor, so metrics must be reduced to the most relevant subset, given available time, cost, technical feasibility and scientific importance. Many of the factors could be measured with a combination of orbital data and the MSL payload. We propose that, at a minimum, a designation of high habitability potential requires the following conditions be met: (a) thermally stable with respect to extremes and frequency of fluctuation, (b) has more than one energy source, (c) sufficient chemical diversity to make compounds with covalent and hydrogen bonding, (d) can moderate ionizing radiation enough to allow a stable or evolving pool of organic molecules, (e) must have water or other high quality polar solvent, (f) must be able to renew chemical resources (e.g., plate tectonics, volcanism or something else we haven't envisioned). A measurement approach we have taken to measure habitability on Earth is : 1. Study remote sensing data, maps, etc. 2. Decide how big an area to measure. 3. Determine the spatial sampling rate. 4. Determine the temporal sampling rate. 5. Determine the order of measurements 6. Decide where to begin measurements 7. Select locations at field site and proceed While science drives each of the steps, there are additional constraints, e.g., technical, time, cost, safety (risk). This approach is also executable on Mars. Measurement of past habitability is more challenging both for Earth and Mars where access to the past means subsurface access and confrontation with unknowns about preservation of the martian past. Some environments preserve evidence of past habitability better than others, and this is where selection of the landing site to maximize the preservation potential of habitability indicators will be key. Mars presents an opportunity to discover transitional states between habitable or not, and we offer a ranking scale for planetary habitability with Mars as the second test subject: CLASS ONE Uninhabitable and likely has never been so CLASS TWO Has a high potential but no confirmed observation of life (as defined above) CLASS THREE Inhabited (we find life) 3-A Globally inhabited 3-B Primitive life; early in its evolution, but not yet globally established 3-C Exists only in refugia -- planet heading toward class four CLASS FOUR Post-habitable (there once was life, but now it's gone) MSL provides an opportunity to carefully investigate the habitability of at least one site on Mars and it will reveal much about the possible states of planetary habitability

Conrad, Pamela G.↗
NASA NTRS2021

Evaluation of 18 Satellite- and Model-Based Soil Moisture Products Using in Situ Measurements From 826 Sensors

Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo (Merged soil Moisture) and six estimates from the HBV (Hydrologiska Byråns Vattenbalansavdelning) model with three precipitation inputs (ERA5, IMERG, and MSWEP) with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5 cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. We found that application of the Soil Wetness Index (SWI) smoothing filter resulted in improved performance for all satellite products. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3E SWI , SMOS SWI , AMSR2 SWI , and ASCAT SWI , with the L-band-based SMAPL3E SWI (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCI SWI ), MeMo performed better on average (median R of 0.72 versus 0.67), probably due to the inclusion of SMAPL3E SWI . The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale.

Hylke E. Beck↗
NASA NTRS2018

An Overview of Approaches and Challenges for Retrieving Marine Inherent Optical Properties from Ocean Color Remote Sensing

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.

Bio-optics↗