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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Long-term velocity enhancements in the solar wind

Throughout most of the last three solar cycles, the Pioneer 10, Pioneer 11, Voyager 2, IMP 8, and Pioneer Venus Orbiter spacecraft have observed long-term enhancements in solar wind velocity. These enhancements are typically on the order of 100-200 km/s, with durations on the order of several months to over a year. They are observed over a range of heliocentric distances that ranges from 0.72 to more than 60 AU, which suggests that they are a characteristic feature throughout the entire heliosphere, at least in the vicinity of the solar equator. They appear to be related to the 'long term velocity shifts' reported by Gazis [1987], but are much more widespread. Since the last solar minimum, they have recurred with the 13-year periodicity reported by Richardson et al [1994], but prior to the last solar minimum there were long intervals were his periodicity was different or absent. We examine and characterize these long-term velocity enhancements and compare them to shorter-term variations in the solar wind such as CMEs, interaction regions, merged interaction regions (MIRs) and global merged interaction regions (GMIRs).

Gazis, P. R.↗
NASA NTRS1995

Long term periodicity in solar wind velocity during the last three solar cycles

Solar wind measurements from the Pioneer 10, Pioneer 11, Voyager 2, IMP 8, and Pioneer Venus Orbiter (PVO) spacecraft were examined to search for long-term periodicities during the last three solar cycles. For the time of the last solar maximum, these measurements confirm the existence of the periodic 1.3-year enhancements in solar wind velocity reported by Richardson et al. (1994). For most of the preceding two solar cycles, long-term velocity enhancements occurred that were similar in structure but lacked the 1.3-year periodicity. It appears that long-term enhancements in solar wind velocity, with durations on the order of a few months to a year, are a common feature throughout the heliosphere.

Gazis, P. R.↗
NASA NTRSDate not supplied

Continuing Long-term Global SO 2 Data Record with JPSS OMPS Instruments

NASA’s long-term Earth Observing System (EOS) SO 2 climate data record (CDR) started with Aura/Ozone Monitoring Instrument (OMI, launched in 2004) and is now being continued with the SNPP/Ozone Mapping and Profiler Suite (OMPS, launched in 2011). Both OMI and SNPP/OMPS SO 2 CDRs are produced with the Goddard principal component analysis (PCA) spectral fitting algorithm. By inherently accounting for various instrumental factors, the PCA technique enables highly consistent retrievals between different instruments. In this presentation, we will provide an overview on our effort to further extend the EOS SO 2 CDR, by implementing the PCA SO 2 algorithm with multiple OMPS instruments flying on the Joint Polar Satellite System (JPSS) constellation, including NOAA-20 (launched in 2017) and NOAA-21 (launched in 2022). We will present results analyzing our new NOAA-20/OMPS PCA SO 2 EOS continuity product, to be publicly released in fall of 2023. We will show statistical analyses on the quality of NOAA-20 PCA SO 2 product, such as retrieval noise, biases over background areas, and long-term stability. We will employ a previously established top-down method to estimate SO2 emissions from selected large point sources, using NOAA-20 SO 2 retrievals and assimilated wind fields as input. The SO 2 emission estimates derived from NOAA-20 retrievals will be compared with those from OMI, SNPP/OMPS, and S5P/TROPOMI (TROPOspheric Monitoring Instrument). We will also demonstrate the application of a new machine learning technique that further reduces the noise of NOAA-20 SO 2 retrievals. Finally, we will present preliminary PCA SO 2 retrievals from recently launched satellite sensors, including NOAA-21/OMPS and NASA’s geostationary TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument.

SO2↗
NASA NTRS2022

The Origins of Long-Term Variability in Martian Upper Atmospheric Densities

We quantify and interpret the long-term variability of dayside Martian upper thermosphere and lower exosphere densities within 180–275 km altitudes. Atmospheric CO2, N2, O, and Ar densities are from NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) observations during the time period of 2015–2020 near solar minimum. These neutral measurements, together with contemporaneous solar irradiance measurements at Mars, enable disentanglement of the orbital effect (due to the annual Sun-Mars distance change with solar longitude) and the solar extreme ultraviolet (EUV) effect in atmospheric density variations. The relative importance of these two effects, which is obtained using a statistical method of Dominance Analysis, reveals the competition between the indirect effect of solar infrared (via the upward coupling from the middle atmosphere) and the direct effect of solar EUV (due to local heating). Our results show that, unlike the orbital effect which is relatively constant at low altitudes and then decreases with increasing altitude, the solar EUV effect nearly monotonically increases. These two effects are comparable at high altitudes (about 240/270/205 km for CO2/N2/O). This analysis is extended to include long-term exospheric mass density estimates near 400 km from Mars Global Surveyor and Mars Odyssey data, with a focus on representative solar cycle phases of solar minimum and maximum. It is found that near 400 km, the orbital effect is always a key driver regardless of the solar cycle phase, while the solar EUV effect plays a minor role during solar minimum and is greatly enhanced and slightly exceeds the orbital effect during solar maximum.

Xiaohua Fang↗
NASA NTRS2003

Causes of Long-Term Drought in the United States Great Plains

This study examines the causes of long term droughts in the United States Great Plains (USGP). The focus is on the relative roles of slowly varying SSTs and interactions with soil moisture. The results from ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to- Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) show that the SSTs account for about 1/3 of the total low frequency rainfall variance in the USGP. Results from idealized experiments with climatological SST suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a five-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the deep soil is forced by white noise and damped with a time scale of about 2 years. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

Schubert, Siegfried D.↗
DOE OSTI2022

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system. Methods: We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ) and ground-level ozone (O 3 ), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ longterm exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage. Results: Among the 151105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM 2.5 (1.70 µg/m 3 ), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO 2 . We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O 3 for hospital admission, ICU admission and death, respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients

Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and efficient utilization of resources. Accessibility of electronic health records (EHR) has enabled data-driven predictive modeling using machine learning. However, very few studies rely solely on unstructured clinical notes from the EHR for mortality prediction. In this work, we propose a framework to predict short, mid, and long-term mortality in adult ICU patients using unstructured clinical notes from the MIMIC III database, natural language processing (NLP), and machine learning (ML) models. Depending on the statistical description of the patients’ length of stay, we define the short-term as 48-hour and 4-day period, the mid-term as 7-day and 10-day period, and the long-term as 15-day and 30-day period after admission. We found that by only using clinical notes within the 24 hours of admission, our framework can achieve a high area under the receiver operating characteristics (AU-ROC) score for short, mid and long-term mortality prediction tasks. The test AU-ROC scores are 0.87, 0.83, 0.83, 0.82, 0.82, and 0.82 for 48-hour, 4-day, 7-day, 10-day, 15-day, and 30-day period mortality prediction, respectively. We also provide a comparative study among three types of feature extraction techniques from NLP: frequency-based technique, fixed embedding-based technique, and dynamic embedding-based technique. Lastly, we provide an interpretation of the NLP-based predictive models using feature-importance scores.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1985

Long-term changes in Saturn's troposphere

Attention is given to the results of a long term monitoring study of Saturn's H2 quadrupole and CH4 band absorptions outside the equatorial zone, over an interval of half a Saturn year that covers most of the perihelion half of Saturn's elliptical orbit (which is approximately bounded by the equinoxes). Marked long term changes are noted in the CH4 absorption, accompanied by weakly opposite changes in the H2 absorption. Seasonal changes are inferred on the basis of temporal variations in absorption. Spatial measurements have also been made in the 6450 A NH3 band since the 1980 equinox.

Trafton, L.↗
NASA NTRS2009

Characterizing Space Environments with Long-Term Space Plasma Archive Resources

A significant scientific benefit of establishing and maintaining long-term space plasma data archives is the ready access the archives afford to resources required for characterizing spacecraft design environments. Space systems must be capable of operating in the mean environments driven by climatology as well as the extremes that occur during individual space weather events. Long- term time series are necessary to obtain quantitative information on environment variability and extremes that characterize the mean and worst case environments that may be encountered during a mission. In addition, analysis of large data sets are important to scientific studies of flux limiting processes that provide a basis for establishing upper limits to environment specifications used in radiation or charging analyses. We present applications using data from existing archives and highlight their contributions to space environment models developed at Marshall Space Flight Center including the Chandra Radiation Model, ionospheric plasma variability models, and plasma models of the L2 space environment.

Minow, Joseph I.↗
NASA NTRS1975

Problems in the long-term storage of data obtained from scientific space experiments

It is shown that long-term data storage systems can be achieved when the system which organizes and conducts the scientific space experiments is equipped with a specialized subsystem: the information filing system. Its main functions are described along with the necessity of stage-by-stage development and compatibility with the data processing systems. The requirements for long-term data storage media are discussed.

Zlotin, G. N.↗
DOE OSTI2024

Reliability, stability during long-term storage, and intra-individual variation of circulating levels of osteopontin, osteoprotegerin, vascular endothelial growth factor-A, and interleukin-17A

Background: Studies in many populations have reported associations between circulating cytokine levels and various physiological or pathological conditions. However, the reliability of cytokine measurements in population studies, which measure cytokines in multiple assays over a prolonged period, has not been adequately examined; nor has stability during sample storage or intra-individual variation been assessed. Methods: We assessed (1) analytical reliability in short- and long-term repeated measurements; (2) stability and analytical reliability during long-term sample storage, and (3) variability within individuals over seasons, of four cytokines—osteopontin (OPN), osteoprotegerin (OPG), vascular endothelial growth factor-A (VEGF-A), and interleukin-17A (IL-17A). Measurements in plasma or serum samples were made with commercial kits according to standard procedures. Estimation was performed by fitting a random or mixed effects linear model on the log scale. Results: In repeated assays over a short period, OPN, OPG, and VEGF-A had acceptable reliability, with intra- and inter-assay coefficients of variation (CV) less than 0.11. Reliability of IL-17A was poor, with inter- and intra-assay CV 0.85 and 0.43, respectively. During long-term storage, OPG significantly decayed (-33% per year; 95% confidence interval [-54, -3.7]), but not OPN or VEGF-A (-0.3% or -6.3% per year, respectively). Intra- and inter-assay CV over a long period were comparable to that in a short period except for a slight increase in inter-assay CV of VEGF-A. Within-individual variation was small for OPN and VEGF-A, with intra-class correlations (ICC) 0.68 and 0.83, respectively, but large for OPG (ICC 0.11). Conclusions: We conclude that OPN and VEGF-A can be reliably measured in a large population, that IL-17A is suitable only for small experiments, and that OPG should be assessed with caution due to degradation during storage and intra-individual variation. The overall results of our study illustrate the need for validation under relevant conditions when measuring circulating cytokines in population studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network

Understanding the carbon fluxes and dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. Short-term, single-location studies have limited applicability, but long-term data from a network of many locations can provide a broader understanding across gradients of climate and management choices. Here we examine eddy covariance measured carbon dioxide (CO 2 ) fluxes from cropland sites across the United States Department of Agriculture's Long-Term Agroecosystem Research (LTAR) network. The dataset was collected between 2001 and 2020, spanning 13 sites for a total of 182 site-years. Average seasonal patterns of net ecosystem CO 2 exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco ) were determined, and subsequent regression analysis on these “flux climatologies” was used to identify relationships to mean annual temperature (MAT), mean annual precipitation (MAP), cropping systems, and management practices. At rainfed sites, carbon fluxes were better correlated with MAP (r2 ≤ 0.5) than MAT (r2 ≤ 0.22). Net carbon balance was different among cropping systems (p < 0.001), with the greatest net carbon uptake occurring in sugarcane (Saccharum spp. hybrids) and the least in soybean (Glycine max) fields. Crop type had a greater effect on carbon balance than irrigation management at a Nebraska site. Across cropping systems, grain crops often had higher GPP and were more likely to have net uptake when compared to legume crops. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research using eddy covariance measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Long-Term Assessment of Commercial Building Energy and Carbon Emissions in the Northwestern Region Under Future Weather Trend

The future climate significantly impacts building performance and increases uncertainties in energy simulations. A rising temperature trend is expected to heighten cooling loads during summer and result in more carbon emissions. Understanding the impact of future climate on building performance is significant for policymakers to make informed decisions. Building retrofit measures can improve building energy efficiency and reduce operational carbon emissions, yet their effects under future climate conditions have not been fully investigated so far. Thus, we proposed an assessment methodology for evaluating long-term energy consumption and operational carbon reduction potential using a building stock dataset. For this study, commercial buildings in the northwestern (NW) region were utilized to assess the impacts of future climate and building retrofit. In addition, we selected Montana with a cold and dry climate as an example to analyze and discuss the carbon emission reduction potential in buildings. The main findings are: (1) Under future climate trends, changes in energy use intensity (EUI) will fluctuate due to variations in heating and cooling degree-days (HDDs and CDDs) and increasing HDDs will lead to increasing EUI. (2) After applying annual building retrofitting, the long-term EUI reduction potential of buildings in the NW region will decrease with the increasing retrofitting degree, and the short-term EUI reduction potential will be impacted by the change of heating and cooling degree days. (3) In Montana, the long-term carbon intensity reduction potential of retrofitted buildings will decrease under future climate trends with the increasing renewable energy penetration.

building energy modeling↗
NASA NTRS2001

Broad Band Long Term Monitoring of X-Ray Bursters

We have analysed the BATSE (Burst and Transient Source Experiment) long term monitoring data of X-ray bursters. We generated the long-term light-curves of several X-ray bursters and studied their spectral evolution and compared them with black hole X-ray binaries. Our research results have been published in two papers.

Zhang, Shuang Nan↗
NASA NTRS2014

Long-Term Changes in Lower Tropospheric Baseline Ozone Concentrations:

Two recent papers have quantified long-term ozone (O3) changes observed at northernmidlatitude sites that are believed to represent baseline (here understood as representative of continental to hemispheric scales) conditions. Three chemistry-climate models (NCAR CAM-chem, GFDL-CM3, and GISS-E2-R) have calculated retrospective tropospheric O3 concentrations as part of the Atmospheric Chemistry and Climate Model Intercomparison Project and Coupled Model Intercomparison Project Phase 5 model intercomparisons. We present an approach for quantitative comparisons of model results with measurements for seasonally averaged O3 concentrations. There is considerable qualitative agreement between the measurements and the models, but there are also substantial and consistent quantitative disagreements. Most notably, models (1) overestimate absolute O3 mixing ratios, on average by approximately 5 to 17 ppbv in the year 2000, (2) capture only approximately 50% of O3 changes observed over the past five to six decades, and little of observed seasonal differences, and (3) capture approximately 25 to 45% of the rate of change of the long-term changes. These disagreements are significant enough to indicate that only limited confidence can be placed on estimates of present-day radiative forcing of tropospheric O3 derived from modeled historic concentration changes and on predicted future O3 concentrations. Evidently our understanding of tropospheric O3, or the incorporation of chemistry and transport processes into current chemical climate models, is incomplete. Modeled O3 trends approximately parallel estimated trends in anthropogenic emissions of NO(sub x), an important O3 precursor, while measured O3 changes increase more rapidly than these emission estimates.

atmospheric composition↗
DOE OSTI2020

Effect of Pressure and Thermal Cycling on Long-Term Oxidation in CO 2 and Supercritical CO 2

Concentrating solar power plant designers are interested in supercritical CO 2 (sCO 2 ) for the power block to achieve > 50% electrical efficiency at > 700 °C. The goal of this project was to develop a long-term (> 100 kh) lifetime model for sCO 2 compatibility using 10–15 kh laboratory exposures. Three Ni-based alloys (625, 282 and 740H) and an advanced austenitic stainless steel were evaluated here in long-term exposures at 700–800 °C using 500-h cycles in laboratory air, 0.1 MPa industrial grade (IG) CO 2 and 30 MPa supercritical IG CO 2 and using 10-h cycles in 0.1 MPa IG CO 2 and O 2 . Mass change data and quantification of the oxide scale thickness and depth of internal attack after 1000–10,000 h exposures at 750 °C indicate that these materials are compatible with the sCO 2 environments with modeling used to predict long-term behavior. Comparison of the 0.1 and 30 MPa 500-h cycle results did not show a significant effect of pressure on the reaction, and no significant internal carburization was observed under these conditions, even for the stainless steel, suggesting that chromia scales may be better C diffusion barriers than expected. For the Ni-based alloys, thermal cycling to simulate the solar duty cycle did not result in scale spallation after 15 kh in 10-h cycles or 4 kh in 1-h cycles at 750 °C. However, the stainless steel specimens formed an Fe-rich oxide after ~ 1500-h cumulative exposure time in both 1- and 10-h cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Long-term warming in a Mediterranean-type grassland affects soil bacterial functional potential but not bacterial taxonomic composition

Abstract Climate warming is known to impact ecosystem composition and functioning. However, it remains largely unclear how soil microbial communities respond to long-term, moderate warming. In this study, we used Illumina sequencing and microarrays (GeoChip 5.0) to analyze taxonomic and functional gene compositions of the soil microbial community after 14 years of warming (at 0.8–1.0 °C for 10 years and then 1.5–2.0 °C for 4 years) in a Californian grassland. Long-term warming had no detectable effect on the taxonomic composition of soil bacterial community, nor on any plant or abiotic soil variables. In contrast, functional gene compositions differed between warming and control for bacterial, archaeal, and fungal communities. Functional genes associated with labile carbon (C) degradation increased in relative abundance in the warming treatment, whereas those associated with recalcitrant C degradation decreased. A number of functional genes associated with nitrogen (N) cycling (e.g., denitrifying genes encoding nitrate-, nitrite-, and nitrous oxidereductases) decreased, whereas nifH gene encoding nitrogenase increased in the warming treatment. These results suggest that microbial functional potentials are more sensitive to long-term moderate warming than the taxonomic composition of microbial community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Long-term effects of thinning and woody control on longleaf pine plantation development, understory abundance, and tree damage from an ice storm

Longleaf pine (Pinus palustris) plantations have been established across the southeastern United States as the first step in restoring the declining savanna ecosystem, yet their long-term stability and development to open canopied woodlands may depend on early density and vegetation management treatments. Commercial thinning (CT) was applied in 2012 (year 18) to a long-term study of longleaf pine community restoration at the Savannah River Site near Aiken, SC to increase abundance of herb species. Although precommercial thinning (PCT) and woody vegetation control increased herb species cover during the first five years of the study, measurements from years 17 to 22 indicated a continuing decline in their cover since year 9 despite application of CT in year 18. Herb species richness, however, increased from 21 to 43 species per 100 m2 area during the last six years of the study, likely a result of disturbances associated with CT and an ice storm in year 20. Application of PCT in 1994, when the plantations were 8–11 years old, reduced their susceptibility to stem bending and breakage from the ice storm, which occurred 20 years later in 2014. Measured 5 months before the storm, pine height: dbh ratio (HD) averaged 78 and 90 for trees growing with and without PCT, respectively, and stem breakage (% of trees) from the ice storm increased linearly (r2 = 0.53) with HD. Pine mortality from the combined effects of glaze ice and wind differed with (28%) versus without (45%) PCT, indicating that long-term stability of longleaf pine plantations depends on early density management.

54 ENVIRONMENTAL SCIENCES↗