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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Developing ISM Dust Grain Models with Precision Elemental Abundances from IXO

The exact nature of interstellar dust grains in the Galaxy remains mysterious, despite their ubiquity. Many viable models exist, based on available IR-UV data and assumed elemental abundances. However, the abundances, which are perhaps the most stringent constraint, are not well known: modelers must use proxies in the absence of direct measurements for the diffuse interstellar medium (ISM). Recent revisions of these proxy values have only added to confusion over which is the best representative for the diffuse ISM, and highlighted the need for direct, high signal-to-noise measurements from the ISM itself. The International X-ray Observatory's superior facilities will enable high-precision elemental abundance measurements. We ill show how these results will measure both the overall ISM abundances and challenge dust models, allowing us to construct a more realistic picture of the ISM.

Valencic, L. A.↗
NASA NTRS2018

The Apollo Sample Suite: 50 Years of Solar System Insight

The Apollo program was undoubtable a crowning achievement in human history. In addition to the obvious cultural significance, scientific results from the Apollo program had a lasting impression on a range of scientific fields, none more so that the effect the samples had on the fields of geology and cosmochemistry. The six Apollo missions collected 382 kg of rock, regolith, and core samples from geologically diverse locations on the Moon. In the nearly 50 years since the first samples were returned, there have been over 3000 different requests for samples, each yielding insights into fields as disparate as biology, medicine, astronomy, engineering, material science, and of course geology. Early studies of the Apollo samples revealed primary insights into the origin and evolution of the Moon, and of the Earth-Moon system, but the results also had implications for bodies throughout the solar system, e.g., defining crater counting rates. Over the decades, continued study of the Apollo samples by new generations of scientists using new instruments have continued to yield significant new discoveries, including the presence of endogenous water in the Moon and the possible presence of a lunar cataclysm, that in turn has contributed to new models of solar system formation and evolution. The Apollo samples have often been used as a proxy for studying other bodies like Mercury or asteroids. The Apollo samples have also directly contributed to the interpretation of remotely sensed data sets, including their use as ground truth for both Clementine and Lunar Prospector global geochemical maps. Despite the Apollo samples being a static collection, recent efforts will ensure that investigators continue to have access to new samples. For example, there was a recent solicitation for study of previously unopened Apollo samples in vacuum-sealed containers, as well as new access to samples stored frozen or in a He atmosphere. Similarly, the use of X-ray computed tomography as part of the curation process is identifying new clasts within polymict breccias that are available for study. Finally, the MoonDB project is putting all previously published lunar geochemical analyses into a searchable database, which should facilitate new investigations.

Zeigler, Ryan↗
NASA NTRS2014

Variation of a Lightning NOx Indicator for National Climate Assessment

During the past couple of years, an analysis tool was developed by the NASA Marshall Space Flight Center (MSFC) for the National Climate Assessment (NCA) program. The tool monitors and examines changes in lightning characteristics over the conterminous US (CONUS) on a continual basis. In this study, we have expanded the capability of the tool so that it can compute a new climate assessment variable that is called the Lightning NOx Indicator (LNI). Nitrogen oxides (NOx = NO + NO2) are known to indirectly influence our climate, and lightning NOx is the most important source of NOx in the upper troposphere (particularly in the tropics). The LNI is derived using Lightning Imaging Sensor (LIS) data and is computed by summing up the product of flash area x flash brightness over all flashes that occur in a particular region and period. Therefore, it is suggested that the LNI is a proxy to lightning NOx production. Specifically, larger flash areas are consistent with longer channel length and/or more energetic channels, and hence more NOx production. Brighter flashes are consistent with more energetic channels, and hence more NOx production. The location of the flash within the thundercloud and the optical scattering characteristics of the thundercloud are of course complicating factors. We analyze LIS data for the years 2003-2013 and provide geographical plots of the time-evolution of the LNI in order to determine if there are any significant changes or trends between like seasons, or from year to year.

Koshak, William J.↗
NASA NTRS2014

Prospects for Chlorophyll Fluorescence Remote Sensing from the Orbiting Carbon Observatory-2

The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO2. Its main purpose is to allow inversions of net flux estimates of CO2 on regional to continental scales using the total column CO2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0 nm ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750 nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16 days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 0.3-0.5 Wm(exp -2)sr(exp -1) nm(exp -1) (15-25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies.We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle.

vegetation agriculture satellite↗
NASA NTRSDate not supplied

Assimilation of GEO and LEO Satellite Retrievals in WRF-Chem (15 km and 4 km) with ‘Top-Down’ Emissions Estimation

We are constraining concentrations and emissions for all criteria pollutants (CO, O3, NO2, SO2, PM10, and PM2.5) with WRF-Chem/DART in applications for FRAPPE (15-km grid) and COLORADO (4-km grid). Our results show that: (i) dynamic emissions estimation at medium resolutions (15 km) improves forecast skill; (ii) At high resolutions, the results look good, but we do not have validation data; (iii) for what may be the first time, we assimilate O3 retrieval profiles in a regional model. The problem is that the averaging kernels generally extend above the upper boundary of regional models. We use O3 upper boundary conditions from the global model to solve that problem; and (iv) In the high resolution experiments, we document the potential benefits of assimilating TEMPO O3 profile and NO2 tropospheric column retrievals. Here, we assimilate proxy TEMPO retrievals from a GEOS-Chem nature run, so there’s a conceptual problem due to the potential bias of the proxy retrievals, but the point is to demonstrate our ability to assimilate TEMPO and identify its potential impacts.

Chemical data assimilation↗
DOE OSTI2024

Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments

Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips.

58 GEOSCIENCES↗
NASA NTRS1991

Optical variability and pigment biomass in the Sargasso Sea as determined using deep-sea optical mooring data

A 9-month time series of optical data, composed of three separate deployments, from the Biowatt 1987 deep-sea mooring located in the oligotrophic waters of the Sargasso Sea at 32 deg N, 70 deg W, is presented. These data were analyzed using several biooptical models for the purpose of providing a continuous estimate of the spectral diffuse attenuation coefficient and pigment biomass. Results of the first 70-day deployment demonstrate the utility of optical observations as proxy measures of biological parameters, and facilitate a preliminary analysis of the temporal variations and a comparison of the present biooptical observations with concurrent physical observations. Biooptical properties exhibit variation in response to physical forcings, such as diel variations of incident solar irradiance, episodic wind forcing, advective mesoscale eddy layer depth, and succession of phytoplankton. The mooring data are discussed in the context of contemporaneous shipboard observations as well as in terms of future ocean satellite observations.

Smith, R. C.↗
NASA NTRS1997

Analysis of Solar Spectral Irradiance Measurements from the SBUV/2-Series and the SSBUV Instruments

During this period of performance, 1 March 1997 - 31 August 1997, the NOAA-11 SBUV/2 solar spectral irradiance data set was validated using both internal and external assessments. Initial quality checking revealed minor problems with the data (e.g. residual goniometric errors, that were manifest as differences between the two scans acquired each day). The sources of these errors were determined and the errors were corrected. Time series were constructed for selected wavelengths and the solar irradiance changes measured by the instrument were compared to a Mg II proxy-based model of short- and long-term solar irradiance variations. This analysis suggested that errors due to residual, uncorrected long-term instrument drift have been reduced to less than 1-2% over the entire 5.5 year NOAA-11 data record. Detailed statistical analysis was performed. This analysis, which will be documented in a manuscript now in preparation, conclusively demonstrates the evolution of solar rotation periodicity and strength during solar cycle 22.

Cebula, Richard P.↗
DOE OSTI2024

Characterizing climate pathways using feature importance on echo state networks

The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol injection, have been proposed as mitigation strategies, but the downstream effects of such actions on a complex climate system are not well understood. The development of algorithmic techniques for quantifying relationships between source and impact variables related to a climate event (i.e., a climate pathway) would help inform policy decisions. Data-driven deep learning models have become powerful tools for modeling highly nonlinear relationships and may provide a route to characterize climate variable relationships. In this paper, we explore the use of an echo state network (ESN) for characterizing climate pathways. ESNs are a computationally efficient neural network variation designed for temporal data, and recent work proposes ESNs as a useful tool for forecasting spatiotemporal climate data. However, ESNs are noninterpretable black-box models along with other neural networks. The lack of model transparency poses a hurdle for understanding variable relationships. We address this issue by developing feature importance methods for ESNs in the context of spatiotemporal data to quantify variable relationships captured by the model. We conduct a simulation study to assess and compare the feature importance techniques, and we demonstrate the approach on reanalysis climate data. In the climate application, we consider a time period that includes the 1991 volcanic eruption of Mount Pinatubo. This event was a significant stratospheric aerosol injection, which acts as a proxy for an anthropogenic stratospheric aerosol injection. Furthermore, we are able to use the proposed approach to characterize relationships between pathway variables associated with this event that agree with relationships previously identified by climate scientists.

black-box models↗
NASA NTRSDate not supplied

A Climate and History Case Study of 18th- and 19th-Century Multidecadal Droughts in East Africa Using a new Tree-Ring Drought Atlas

Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.

Droughts↗
NASA NTRSDate not supplied

A Climate and History Case Study of 18th- and 19th-Century Multidecadal Droughts in East Africa Using a new Tree-Ring Drought Atlas

Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.

Droughts↗
NASA NTRS1990

Upper atmosphere dynamics

The spatial distribution of stratospheric ozone is useful in diagnosis of some features of the large scale atmospheric circulation, and the ozone may also interact with the atmospheric general circulation. Local maxima in the column ozone distribution are often associated with disturbances in the lower stratosphere and upper troposphere, which may herald cyclone development in the troposphere. One research objective is to explore these issues by means of time series analysis of a zonal index of total column ozone, to suggest the existence or nonexistence of relationships between column ozone and dynamical processes which are known to occur on various time scales. Another objective is to investigate the correlation between the ozone mixing ratio on the 350 K isentropic surface and the column integrated ozone, and to investigate the use of an easily derived parameter as a proxy for ozone mixing ratio, which is conserved in the stratosphere for time scales shorter than the photochemical time scale. The source of data for these studies is the Total Ozone Mapping Spectrometer (TOMS) data set.

Miller, Timothy L.↗
NASA NTRS2011

Demonstrating the Operational Value of Thermodynamic Hyperspectral Profiles in the Pre-Convective Environment

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) Weather Forecasting Offices (WFO). As a part of the transition to operations process, SPoRT attempts to identify possible limitations in satellite observations and provide operational forecasters a product that will result in the most impact on their forecasts. One operational forecast challenge that some NWS offices face, is forecasting convection in data-void regions such as large bodies of water. The Atmospheric Infrared Sounder (AIRS) is a sounding instrument aboard NASA's Aqua satellite that provides temperature and moisture profiles of the atmosphere. This paper will demonstrate an approach to assimilate AIRS profile data into a regional configuration of the WRF model using its three-dimensional variational (3DVAR) assimilation component to be used as a proxy for the individual profiles.

Kozlowski, Danielle↗
NASA NTRS2016

A Space-based, High-resolution View of Notable Changes in Urban Nox Pollution Around the World (2005 - 2014)

Nitrogen oxides (NOxNO+NO2) are produced during combustion processes and, thus may serve as a proxy for fossil fuel-based energy usage and committed greenhouse gases and other pollutants. We use high-resolution nitrogen dioxide (NO2) data from the Ozone Monitoring Instrument (OMI) to analyze changes in urban NO2 levels around the world from 2005 to 2014, finding complex heterogeneity in the changes. We discuss several potential factors that seem to determine these NOx changes. First, environmental regulations resulted in large decreases. The only large increases in the United States may be associated with three areas of intensive energy activity. Second, elevated NO2 levels were observed over many Asian, tropical, and subtropical cities that experienced rapid economic growth. Two of the largest increases occurred over recently expanded petrochemical complexes in Jamnagar (India) and Daesan (Korea). Third, pollution transport from China possibly influenced the Republic of Korea and Japan, diminishing the impact of local pollution controls. However, in China, there were large decreases over Beijing, Shanghai, and the Pearl River Delta, which were likely associated with local emission control efforts. Fourth, civil unrest and its effect on energy usage may have resulted in lower NO2 levels in Libya, Iraq, and Syria. Fifth, spatial heterogeneity within several megacities may reflect mixed efforts to cope with air quality degradation. We also show the potential of high-resolution data for identifying NOx emission sources in regions with a complex mix of sources. Intensive monitoring of the world's tropical subtropical megacities will remain a priority, as their populations and emissions of pollutants and greenhouse gases are expected to increase significantly.

spatial heterogeneity↗
NASA NTRS2014

New Approach to Monitor Transboundary Particulate Pollution over Northeast Asia

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117-265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched.

Data Assimilation↗
DOE OSTI2025

Global teleconnections influencing large-scale drought in the United States using SVDI

Understanding recent large-scale drought patterns and the mechanisms producing extreme drought events is vital for future drought forecasts and understanding future drought risks. Increasingly, vapor pressure deficit (VPD) has been used as an important measure of evaporative demand and proxy for drought detection. In this study, VPD is used to calculate the new Standardized VPD Drought Index (SVDI) with NASA North American Land Data Assimilation System (NLDAS) data. Previous studies have shown that SVDI accurately identifies the timing and magnitude short-term droughts in the United States (U.S). In the present study, SVDI is now used to identify large-scale drought patterns between 1980 and 2021 and drought variability driven by selected global teleconnections originating in the Pacific and Atlantic Oceans. Spatial drought characteristics were extracted from SVDI using empirical orthogonal function (EOF) analysis. Then a k-means clustering algorithm was applied to both EOF principal components and primary teleconnections, including the El Nino-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) to identify drought events driven by the Pacific Ocean. Results show that the SVDI is useful in evaluating large-scale drought variability in the U.S. related to global teleconnections, and that mechanisms influencing summer drought patterns in the Western and Southwestern U.S. are driven by a tropical-extratropical interactions originating in the equatorial Pacific Ocean related to ENSO dynamics with interdecadal variability modulated by PDO. The large-scale droughts in the Central and Southern U.S., like those in 2011 and 2012, on the other hand, are driven by the North Pacific Ocean warm pool during a strong negative PDO, which subsequently influenced variability in the Bermuda-Azores High in the Atlantic Ocean. In summer 2011, the Bermuda-Azores High weakened, reducing the onshore winds and moisture transport along the eastern Gulf of Mexico and contributing to ongoing drought in the region. The Northern Pacific and Atlantic Ocean sea surface temperatures (SSTs) have increased between 1980 and 2021. In conclusion, as SSTs continue to rise in the Northern Pacific Ocean, one consequence of the coupled North Pacific warm pool and atmospheric dynamics, is to increase summer drought variability over a large region in the southern and midwestern U.S. under global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Remote Sensing of Live Fuel Moisture for Wildfires Using SMAP Satellite Observations

Live Fuel Moisture (LFM) is a critical parameter for wildfire risk assessment, traditionally measured by labor-intensive field sampling. However, sampled LFM data are influenced by site-specific factors, such as local vegetation types and plant traits, and are often collected retrospectively after wildfire events, making it difficult to obtain pre-fire data for predictive applications. Here, we evaluate the relationship between LFM and Vegetation Water Content (VWC) and Soil Moisture (SM) retrieved from SMAP L-band brightness temperature using the Maximum Entropy Production (MEP) approach. The MEP-retrieved VWC exhibited strong correlation with in situ measurements of LFM ( r > 0.6) in the Western U.S. The integration of high-resolution vegetation coverage data enhances the detection of sub-grid vegetation heterogeneity. This study demonstrates the operational potential of remote sensing derived VWC as a scalable proxy of LFM, supporting its application in regional assessment of wildfire risk.

Cho, Kyeungwoo [Georgia Institute of Technology, A↗
NASA NTRS1994

Comparisons of the MG II index products from the NOAA-9 and NOAA-11 SBUV/2 instruments

The Mg II index is a proxy indicator of solar UV activity which is produced from measurements of the chromospheric Mg II absortion line at 280 nm. Mg II index data sets have been derived from the NOAA-9 and NOAA-11 SBUV/2 irradiance data sets using both discrete scan measurements about the Mg II line and continuous scan (sweep) measurements over the UV spectrum from 160 - 400 nm. This paper will discuss the rationale behind the creation of the different Mg II index products, and make a quantitative assessment of the differences between these products. Recommendations for future use of the Mg II index will also be presented.

Deland, M. T.↗