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NASA NTRS2010

Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Barrett, K.↗

NASA NTRS2013

Crater Topography on Titan: Implications for Landscape Evolution

We present a comprehensive review of available crater topography measurements for Saturn's moon Titan. In general, the depths of Titan's craters are within the range of depths observed for similarly sized fresh craters on Ganymede, but several hundreds of meters shallower than Ganymede's average depth vs. diameter trend. Depth-to-diameter ratios are between 0.0012 +/- 0.0003 (for the largest crater studied, Menrva, D approximately 425 km) and 0.017 +/- 0.004 (for the smallest crater studied, Ksa, D approximately 39 km). When we evaluate the Anderson-Darling goodness-of-fit parameter, we find that there is less than a 10% probability that Titan's craters have a current depth distribution that is consistent with the depth distribution of fresh craters on Ganymede. There is, however, a much higher probability that the relative depths are uniformly distributed between 0 (fresh) and 1 (completely infilled). This distribution is consistent with an infilling process that is relatively constant with time, such as aeolian deposition. Assuming that Ganymede represents a close 'airless' analogue to Titan, the difference in depths represents the first quantitative measure of the amount of modification that has shaped Titan's surface, the only body in the outer Solar System with extensive surface-atmosphere exchange.

Implications↗

NASA NTRS2012

Thermal Phase Variations of WASP-12b: Defying Predictions

We report Warm Spitzer full-orbit phase observations of WASP-12b at 3.6 and 4.5 micrometers. This extremely inflated hot Jupiter is thought to be overflowing its Roche lobe, undergoing mass loss and accretion onto its host star, and has been claimed to have a C/O ratio in excess of unity. We are able to measure the transit depths, eclipse depths, thermal and ellipsoidal phase variations at both wavelengths. The large-amplitude phase variations, combined with the planet's previously measured dayside spectral energy distribution, are indicative of non-zero Bond albedo and very poor day-night heat redistribution. The transit depths in the mid-infrared-(R(sub p)/R(sub ∗))(sup 2) = 0.0123(3) and 0.0111(3) at 3.6 and 4.5 micrometers, respectively-indicate that the atmospheric opacity is greater at 3.6 than at 4.5 micrometers, in disagreement with model predictions, irrespective of C/O ratio. The secondary eclipse depths are consistent with previous studies: F(sub day)/F(sub ∗) = 0.0038(4) and 0.0039(3) at 3.6 and 4.5 micrometers, respectively. We do not detect ellipsoidal variations at 3.6 micrometers, but our parameter uncertainties-estimated via prayer-bead Monte Carlo-keep this non-detection consistent with model predictions. At 4.5 micrometers, on the other hand, we detect ellipsoidal variations that are much stronger than predicted. If interpreted as a geometric effect due to the planet's elongated shape, these variations imply a 3:2 ratio for the planet's longest:shortest axes and a relatively bright day-night terminator. If we instead presume that the 4.5 micrometer ellipsoidal variations are due to uncorrected systematic noise and we fix the amplitude of the variations to zero, the best-fit 4.5 micrometer transit depth becomes commensurate with the 3.6 micrometer depth, within the uncertainties. The relative transit depths are then consistent with a solar composition and short scale height at the terminator. Assuming zero ellipsoidal variations also yields a much deeper 4.5 micrometer eclipse depth, consistent with a solar composition and modest temperature inversion. We suggest future observations that could distinguish between these two scenarios.

planetary↗

NASA NTRSDate not supplied

Blue Carbon Stock Estimation of US Coastal Marshes from New York to Georgia How Much Do We Have to Lose?

Valued for their myriad multifunctional roles in preserving habitat for biodiversity, cycling nutrients, protecting shorelines, improving water quality, and sequestering blue carbon, coastal and riverine marshes continue to disappear not only due to land use change but also sea level rise. Blue carbon’s role in the carbon cycle has been underappreciated until the last few decades, and the carbon stocks for U.S. Atlantic coastal margins have previously been estimated for a depth of 0.5-1 meter. We select several North American East Coast databases that have been utilized to study sea level rise and instead use them to estimate marsh depth from New York to Georgia; in local marshes that lack depth data, we present new depth data and perform several full-depth transects. This alongside marsh area data from the National Wetlands Inventory (NWI) enables us to estimate marsh volume. We then utilize an average carbon density of 27 kg/m 3 by Holmquist et al. 2018 to calculate blue carbon stocks. We present the inventories of peat depth by state, marsh area by state, and total marsh volume by state, followed by the blue carbon stocks. The peat depth inventory of eastern U.S. marshes reveals that riverine marshes are significantly deeper than coastal marshes. While both are important, we highlight the jeopardy of rapidly eroding urban marshes due to the heavy metals these marshes have sequestered for centuries as they contaminate the surrounding estuary. Uncertainties and caveats include carbon density values, loss of marsh since the NWI assessment, and depth averages. The high cost of marsh disappearance underscores the urgent need for their preservation.

Coastal marshes↗

DOE OSTI2021

Quantifying Properties for a Mechanistic, Predictive Understanding of Aqueous Impact on Aging of Medium and Low Voltage AC and DC Cabling in Nuclear Power Plants

To address the gap in knowledge in understanding degradation in relevant service conditions, this project aimed to develop a mechanistic, predictive model of medium and low voltage cable failure based on the primary environmental degradation parameters of aqueous immersion time, temperature, and the oxidation extent. To do so, we took a two-fold approach toward evaluating degradation as related to the aqueous condition. First, we evaluated the chemical, mechanical, and electrical properties of polymers that comprise the cabling insulation under varied aqueous conditions at different temperatures. Secondly, we evaluated the performance of insulation materials under similar accelerated aging conditions in addition to the dielectric breakdown of the cabling under submersion conditions. Thermal oxidation and immersion of LDPE thin films were done using a Parr vessel and the extent of oxidation was monitored using the carbonyl index from ATR-FTIR spectrum, a ratio quantifying the carbonyl functionality produced on the LDPE film surface. Increasing the temperature, oxidation time, and oxygen pressure increased the water-vapor permeability and the carbonyl content. Thermogravimetric analysis of the films confirmed that there is indeed an initial weight loss of the smaller molecular weight molecules and volatiles. At higher temperatures, there is a secondary mass loss. Up to 70°C, the mass loss curves were similar until 80°C, when the aged films decreased at a much greater rate with respect to increasing temperature. This was seen in the 10, 50, 90% weight loss temperatures. The mechanical properties of sheet PP and HDPE as well as injection molded LDPE, HDPE, HDPP dog bones were plotted with respect to the time spent in the Parr vessel during thermal oxidation. For the sheet PP and HDPE, the UTS and the modulus of elasticity decreased while the elongation increased. The injection-molded LDPE, HDPE, and HDPP dog bones experienced a similar trend where the changes in the properties were within experimental uncertainty. This analysis of LDPE in dry and immersive oxygen-rich environments is an important baseline for future experiments looking at other degradation mechanisms. A predictive aging model for low-density polyethylene insulative cable housings was developed. This model revealed a combination of physical and chemical processes which lead to an increase in permeability and a decrease in strength of the insulator. In creating this predictive model, a gap of knowledge in the literature was revealed in two areas: understanding how the crystallinity of a polymer changes with time and visualizing the predicted pores formed through the insulator which leads to failure. Developing and using an adapted ATR-FTIR method, crystallinity was monitored and compared to bulk crystallinity found via DSC. Inhomogeneity in crystallinity changes were observed but the FTIR method but was found to be less reliable. Pore visualization was found utilizing electrical impedance spectroscopy saturated aged polyethylene films with synthesized citrate-capped gold nanoparticles, and chloroauric acid precursor. results indicate a decreasing impedance of the polyethylene films caused by the transport of ions through the film. SEM imaging was then performed for elemental analysis of the films and counter electrodes for the presence of ions. Chloride and gold ions were detected; however, no nanoparticles were found. This gives an estimated pore size of at least 0.3 nm through the aged film. Cyclic submergence of polyethylene and polypropylene in aqueous solutions of copper sulfate and Harrison’s solution were examined. It was discovered that aging in these mixed conditions and at 90°C did cause a small, yet significant increase to tensile strength for both unaged polyethylene and polypropylene. The PE and PP in cycled and submerged conditions did not have tensile strengths significantly different from dry-aged after 16 weeks. For both solutions, it was determined that capacitance increases with both water tree depth and cable temperature and is relatively independent of changing water tree AR. As for resistance, there is no apparent change between depth percentages of 10 and 80 for both solutions. This is because the water tree has not yet entered the conductor and thus there is no shorting current flowing through the tree yet. Between 80 and 100% water tree depth, it is observed that for both solutions there is a rapid decrease in resistance because the tree is now impacting the conductor shield and allowing shorting current to flow through it. The relationship between resistance and temperature was found to be inversed. As temperature increases, resistance decreases for both water tree solutions with distilled water having the most apparent difference across the range of temperatures simulated. With regards to water tree AR, resistance was found to be relatively independent at depth percentages of 10, 50, and 70, but there was some relationship at 100% depth for both solutions. At this depth, as water tree AR increased, resistance was found to also increase. Through the examination of voltage and electric field distribution plots, it was confirmed for EPR cables that increasing water tree depth leads to increasing distortion. The increase in shorting current at 100% depth for aqueous copper sulfate compared to distilled water was also visualized. Lastly, the relationship between shorting current and temperature for narrow water trees was visualized and validated using the distribution plots. This study has led to a better understanding of the effect of cable temperature, water tree solution, and geometry of the tree region on cable degradation. Furthermore, this study has documented simulation results of water tree degradation in EPR MV cables, which had been previously lacking in information. Future work in this area will add frequency into the mix and examine what effect it has on the rate of cable degradation as a result of water treeing. To compliment the work being carried by UMD on different polymer chemistries, harvested medium voltage (MV) cables were selected for accelerated aging study at ORNL. These medium voltage cables are representative of the vintages and materials that are currently in use at existing nuclear power plants (NPPs). These cables were immersed in water at 90°C and energized for a period of two years at elevated voltage. Partial discharge was measured during this period of time to track potential degradation. Unfortunately, due to the absence of failure, the extent of integration between the UMD techniques and the harvested MV insulation was limited. However, based on the findings and from the UMD research in the previous sections on polyethylene and polypropylene, follow-on characterization for harvested MV cable insulation should focus on sample preparation to take advantage of the UMD techniques to better understand mechanistic degradation in MV cable insulations. This would include: 1.) Utilization of solutions and impedance measurement insulation to track permeability in harvested and accelerated aging insulation samples, 2.) Adaptation of gold nanoparticle synthesis for electrical impedance spectroscopy with supporting SEM characterization to study pore formation in harvested and accelerated aged insulation samples, & 3.) ATR-FTIR crystallinity with multiple temperature dependent harvested MV cable insulation under different air and submerged accelerated aging. In addition, low voltage dielectric spectroscopy and high voltage dissipation factor, tan δ, could be implemented as a condition monitoring tool for harvested MV cable insulation in submerged environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2016

Derivation and Validation of Supraglacial Lake Volumes on the Greenland Ice Sheet from High-Resolution Satellite Imagery

Supraglacial meltwater lakes on the western Greenland Ice Sheet (GrIS) are critical components of its surface hydrology and surface mass balance, and they also affect its ice dynamics. Estimates of lake volume, however, are limited by the availability of in situ measurements of water depth,which in turn also limits the assessment of remotely sensed lake depths. Given the logistical difficulty of collecting physical bathymetric measurements, methods relying upon in situ data are generally restricted to small areas and thus their application to largescale studies is difficult to validate. Here, we produce and validate spaceborne estimates of supraglacial lake volumes across a relatively large area (1250 km(exp 2) of west Greenland's ablation region using data acquired by the WorldView-2 (WV-2) sensor, making use of both its stereo-imaging capability and its meter-scale resolution. We employ spectrally-derived depth retrieval models, which are either based on absolute reflectance (single-channel model) or a ratio of spectral reflectances in two bands (dual-channel model). These models are calibrated by usingWV-2multispectral imagery acquired early in the melt season and depth measurements from a high resolutionWV-2 DEM over the same lake basins when devoid of water. The calibrated models are then validated with different lakes in the area, for which we determined depths. Lake depth estimates based on measurements recorded in WV-2's blue (450-510 nm), green (510-580 nm), and red (630-690 nm) bands and dual-channel modes (blue/green, blue/red, and green/red band combinations) had near-zero bias, an average root-mean-squared deviation of 0.4 m (relative to post-drainage DEMs), and an average volumetric error of b1%. The approach outlined in this study - image-based calibration of depth-retrieval models - significantly improves spaceborne supraglacial bathymetry retrievals, which are completely independent from in situ measurements.

Spectrally-based depth-retrieval models↗

DOE OSTI2020

Surface Methane Concentrations Along the Mid-Atlantic Bight Driven by Aerobic Subsurface Production Rather Than Seafloor Gas Seeps

Relatively minor amounts of methane, a potent greenhouse gas, are currently emitted from the oceans to the atmosphere, but such methane emissions have been hypothesized to increase as oceans warm. Here, we investigate the source, distribution, and fate of methane released from the upper continental slope of the U.S. Mid-Atlantic Bight, where hundreds of gas seeps have been discovered between the shelf break and ~1,600 m water depth. Using physical, chemical, and isotopic analyses, we identify two main sources of methane in the water column: seafloor gas seeps and in situ aerobic methanogenesis which primarily occurs at 100–200 m depth in the water column. Stable isotopic analyses reveal that water samples collected at all depths were significantly impacted by aerobic methane oxidation, the dominant methane sink in this region, with the average fraction of methane oxidized being 50%. Due to methane oxidation in the deeper water column, below 200 m depth, surface concentrations of methane are influenced more by methane sources found near the surface (0–10 m depth) and in the subsurface (10–200 m depth), rather than seafloor emissions at greater depths.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Blowing Snow at McMurdo Station, Antarctica During the AWARE Field Campaign: Multi-Instrument Observations of Blowing Snow

In polar regions, blowing snow (BLSN) can play a substantial role in regional thermodynamics and radiation properties. The extent of the impact depends upon the depth of the BLSN layer, a property that is difficult to measure and not well understood. The West Antarctic Radiation Experiment (AWARE) Field Campaign saw the deployment of a large suite of observational instruments to McMurdo Station, Antarctica, allowing for in-depth investigation of BLSN. During the year of the campaign, BLSN occurred ~7.4% of the time. In this study, additional remote sensing observations are used to supplement an existing ceilometer-based BLSN characterization algorithm creating a multi-instrument (MI) depth estimation algorithm to yield layer depths with more certainty. Backscatter coefficient and linear depolarization ratios from the micropulse and high spectral resolution lidar (HSRL) are incorporated along with color ratio derived from HSRL backscatter and Ka-band radar reflectivity observations. This provided estimates of BLSN depth that were less impacted by noise/artifacts in any one set of observations. When applied to the data from AWARE, the MI algorithm yielded an average depth of 168.2 m with ~60% of plumes less than 200 m in depth. Events occurring with precipitation saw the most value in the additional instruments, with the suite of observations allowing for more separation of BLSN particles from fallstreaks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Nutrient and carbon concentrations in dated soil cores at US-OWC Ameriflux wetland site (OWC NERR)

Soil cores were sampled at the Old Woman Creek (OWC) National Estuarine Research Reserve at the south shore of Lake Erie, near Huron, Ohio, USA. OWC is a temperate mineral soil marsh. We dated the soil cores using lead isotope analysis and measured the concentrations of carbon and nutrients (nitrogen, phosphorus) throughout the core depths. We analyzed 36 cores, sampled along three transects at areas of the wetland with different hydrological regimes. Each transect included three coring sites at different water depth categories (shallow, intermediate deep) with four core samples per coring site. The data can be used to determine the carbon sequestration rates and nutrient accumulation rates, at multiple locations throughout OWC wetland.Dataset, in csv format, with data variables in columns, and different cores and core depths slices in rows, includes results from 36 sediment cores (0-30 cm depth) taken at 9 locations (4 replicates at each location) along 3 gradients of water depth (shallow, intermediate, deep), each at a different hydrologic location (outflow, backflow, middle). At each depth slice within a core, we provide depth, date (using 210Pb), bulk density, and the concentrations of carbon, nitrogen, phosphorus, d13C, and d15N.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Daily water stable isotopes, transpiration, and matrix potential data for an aspen and engelmann stand in the East River Watershed (version 2)

We provide daily stable isotope (2H & 18O) ratios in soil water and xylem (plant stem) water, as well as the sap flow (transpiration) and the soil's matric potential at a forested site near Gothic, Colorado, in the East River catchment. We measured the stable isotopic composition of the transpiration and the daily transpiration flux sum of three aspen and three engelmann spruce. In both forest stands, we installed a soil profile and measured the soil matric potential at 15, 30, and 60 cm depth as well as the stable isotopes of soil pore water at 5, 10, 30, 60, and 90 cm depths. All isotope measurements were done in situ via vapor probes connected to a cavity ring down spectrometer (Picarro L1240i).We further report the daily meteorological data observed at billy barr near our study site. We also provide for each tree the relative share of root water uptake derived from the isotope measurements via a Bayesian mixing model (MixSIAR).The daily data is provided as a time series in "Iso_MP_Sap_DataDaily_ESSDiveUpload.csv" and the units are provided in "dd.csv"; the location of the instrumented trees and soil profiles are given as latitude and longitude coordinates saved as CSV and KMZ files; and a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata.The data was gathered to investigate the short-term changes of the water sources (i.e., variation of root water uptake from different soil depths) of the studied subalpine trees.Update 07/16/2025: The relative and absolute plant water uptake depths were grouped to ensure that the MixSIAR model was applied with endmembers that differed in their d2H value by at least 3 permill and at least 1 permill for d18O. Whenever the difference between observed d2H values for two or more probes at neighboring depths was less than 3 permill, we used the average value for the source water endmember. For days at which probes that were not next to each other measurements did not differ at least 3 permill, the average of all probes between these two depths was used as the water source endmember representing the depth range between these two probes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Retrospective Analysis of Backwater Habitat Availability Using Remote Sensing

Low-velocity channel-margin habitats serve as important nursery habitats for the endangered Colorado pikeminnow (Ptychocheilus lucius) in the middle Green River between Jensen and Ouray, Utah. These habitats, known as backwaters, are associated with emergent sandbars, and are shaped and reformed annually by peak flows. Our recent knowledge about backwater characteristics and dynamics that is summarized in the synthesis report (Grippo et al. 2015) was based on detailed annual survey data from a relatively small sample of backwaters that were collected from 2003 to 2014 and reach-wide evaluations of backwater surface area based on manual interpretation of aerial and satellite imagery. Methods that bridge the gap between the detailed surveys from a small number of backwaters and the reach-wide assessment of their surface area would enable an assessment of the availability of backwater habitats that meet the minimum depth requirements for suitable habitat for Colorado pikeminnow. In 2015 Argonne National Laboratory (Argonne) tested three regression models—linear, multiple, and partial least square (PLS) regression models—for estimating backwater depth using National Agriculture Imagery Program (NAIP) imagery collected in July 2006 that covered the Jensen-Ouray reach of the Green River (Hamada and LaGory 2016). The results suggested that a PLS regression model showed high correlation with the reference depth (R 2 = 0.69) and had the most unbiased and consistent estimate of backwater depth. The results also indicated that the PLS model would provide reasonable estimates of the amount of habitat providing a minimum suitable depth of 30 cm for young-of-the-year Colorado pikeminnow, even though absolute depth estimates may be uncertain for backwater areas deeper than approximately 40 cm. The study also provided insights regarding the amount and the selection of calibration and validation (cal-val) data needed for improving the accuracy of depth prediction.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Effects of Slope Aspect and Rainfall on Belowground Deep Fine Root Traits and Aboveground Tree Height

The vertical root distribution and rooting depth are the main belowground plant functional traits used to indicate drought resistance in arid and semiarid regions. The effects of the slope aspect on the aboveground traits are visible but not the belowground deep root traits. We aimed to investigate the fine root traits of the locust tree ( Robinia pseudoacacia L.) planted on southerly and northerly aspects, and the variations in the rooting depth in regions with different rainfall, as well as assessing how deep rooting, might affect the response to drought in a loess region. We selected three study sites with different rainfall amounts, with six sampling plots at each site (three each with southerly and northerly aspects). Soil core samples were collected down to the depth where no roots were present. The locust trees tended to develop deeper fine roots rather than greater heights. The tree height and diameter were greater for locust trees on northerly aspects, whereas trees on southerly aspects had significantly deeper rooting depths. Fine root traits (root length, root area, and root dry weight density) were higher in the southerly aspect for both Changwu and Ansai, but lower in Suide. The ratio of the root front depth tree height ranged from 1.04 to 3.17, which was higher on southerly than northerly aspects, and it increased as the rainfall decreased. Locust tree growth traits (belowground fine root and aboveground tree height) were positively correlated with the mean annual rainfall. The soil moisture content of the topsoil decreased as the rainfall decreased, but the pattern varied in the deep layer. Our results suggest that the variations in the belowground rooting depth under different slope aspects may be related to plant survival strategies. The vertical extension of the rooting depth and tree height may be key functional traits that determine plant growth in drought-prone regions.

Lihui, Ma↗

DOE OSTI2023

Antarctic permafrost processes and antiphase dynamics of cold-based glaciers in the McMurdo Dry Valleys inferred from 10 Be and 26 Al cosmogenic nuclides

Abstract. Soil and sediment mixing and associated permafrost processes are not widely studied or understood in the McMurdo Dry Valleys of Antarctica. In this study, we investigate the stability and depositional history of near-surface permafrost sediments to ∼ 3 m depth in the Pearse and lower Wright valleys using measured cosmogenic 10Be and 26Al depth profiles. In Pearse Valley, we estimate a minimum depositional age of ∼ 74 ka for the active layer and paleoactive-layer sediments (< 0.65 m). Combined depth profile modelling of 10Be and 26Al gives a depositional age for near-surface (< 1.65 m) permafrost in Pearse Valley of 180 +20/-40 ka, implying that the deposition of permafrost sediments predates MIS 5 advances of Taylor Glacier. Deeper permafrost sediments (> 2.09 m) in Pearse Valley are thus inferred to have a depositional age of > 180 ka. At a coastal, lower-elevation site in neighbouring lower Wright Valley, 10Be and 26Al depth profiles from a second permafrost core exhibit near-constant concentrations with depth and indicate the sediments are either vertically mixed after deposition or sufficiently young so that post-depositional nuclide production is negligible relative to inheritance. 26Al/10Be concentration ratios for both depth profiles range between 4.0 and 5.2 and are all lower than the nominal surface production rate ratio of 6.75, indicating that prior to deposition, these sediments experienced complex, yet similar, exposure–burial histories. Assuming a single-cycle exposure–burial scenario, the observed 26Al/10Be ratios are equivalent to a total minimum exposure–burial history of ∼ 1.2 Myr. In proximity to the depth profile core site, we measured cosmogenic 10Be and 26Al in three granite cobbles from thin, patchy drift (Taylor 2 Drift) in Pearse Valley to constrain the timing of retreat of Taylor Glacier. Assuming simple continuous exposure, our minimum, zero-erosion exposure ages suggest Taylor Glacier partially retreated from Pearse Valley no later than 65–74 ka. The timing of retreat after 65 ka and until the Last Glacial Maximum (LGM) when Taylor Glacier was at a minimum position remains unresolved. The surface cobble ages and permafrost processes reveal Taylor Glacier advances during MIS 5 were non-erosive or mildly erosive, preserving the underlying permafrost sediments and peppering boulders and cobbles upon an older, relict surface. Our results are consistent with U/Th ages from central Taylor Valley and suggest changes in moisture delivery over Taylor Dome during MIS 5e, 5c, and 5a appear to be associated with the extent of the Ross Ice Shelf and sea ice in the Ross Sea. These data provide further evidence of antiphase behaviour through retreat of a peripheral lobe of Taylor Glacier in Pearse Valley, a region that was glaciated during MIS 5. We suggest a causal relationship of cold-based glacier advance and retreat that is controlled by an increase in moisture availability during retreat of sea ice and perhaps the Ross Ice Shelf, as well as, conversely, a decrease during times of sea ice and Ross Ice Shelf expansion in the Ross Sea.

58 GEOSCIENCES↗

DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗

NASA NTRS1977

Study of lubricant jet flow phenomena in spur gears - Out of mesh condition

An analysis was conducted for oil jet lubrication on the disengaging side of a gear mesh. Results of the analysis were computerized and used to determine the oil jet impingement depth for several gear ratios and oil jet to pitch line velocity ratios. An experimental program was conducted on the NASA gear test rig using high-speed photography to experimentally determine the oil jet impingement depth on the disengaging side of mesh. Impingement depth reaches a maximum at gear ratio near 1.5 where chopping by the leading gear tooth limits the impingement depth. The pinion impingement depth is zero above a gear ratio of 1.172 for a jet velocity to pitch time velocity ratio of 1.0 and is similar for other velocity ratios. The impingement depth for gear and pinion are equal and approximately one-half the maximum at a gear ratio of 1.0. Impingement depth on either the gear or pinion many be improved by relocation of the jet from the pitch line or by changing the jet angle. Results of the analysis were verified by experimental results using a high-speed camera and a well lighted oil jet.

Townsend, D. P.↗

NASA NTRS1996

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground based, aircraft, and satellite measurements taken as part of the First ISCCP Region Experiment (FIRE) cirrus intensive field observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center and top heights and the corresponding temperatures. Coincident GOES-4 4-km visible (0.65 micrometer) and 8-km infrared window (11.5 micrometer) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 062 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance , extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface-based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature wer ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperature and cloud thickness from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. the parameterization of visible reflectance in terms of cloud optical depth and clear sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous advanced very high resolution radiometer (AVHRR) data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloud pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study or cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗

NASA NTRS1990

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground-based, aircraft, and satellite measurements taken as part of the FIRE Cirrus Intensive Field Observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center, and top heights and the corresponding temperatures. Coincident GOES 4-km visible (0.65 micro-m) and 8-km infrared window (11.5 micro-m) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 0.62 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance, extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface- based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature were ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperatures and cloud thicknesses from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. The parameterization of visible reflectance in terms of cloud optical depth and clear-sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous AVHRR data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloudy pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study of cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗

NASA NTRS2003

Inferring Cloud Properties from Passive Solar Sensors

The most common approach for retrieving cloud optical depth from ground-based observations uses downwelling fluxes measured by pyranometers and Multi-Filter Rotating Shadowband Radiometers (MFRSR). The key element in both retrieval techniques is the one-to-one mapping of the "observed" fluxes into cloud optical depth through plane-parallel radiative transfer. Both methods are expected to work well only for completely overcast clouds giving an effective optical depth for the whole sky. To infer cloud optical depth locally one can assume to use a narrow-field-of view radiometer that measures radiances instead of fluxes. However, lack of one-to-one relationships between radiance and cloud optical depth, prevents the direct use of radiances either. Here we discuss a new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (NIR) spectral regions. In addition to an algebraic combinations of spectral radiances such as Normalized Difference Cloud Index (NDCI) that largely removes nonuniqueness and the radiative effects of cloud inhomogeneity but can result in poor retrievals due to its insensitivity to cloud fraction, both RED and NIR radiances as points on the "RED vs. NIR" plane are proposed to be used for retrieval. The proposed retrieval method is applied to a multi- channel sunphotometer (as a part of AERONET) measurements at the ARM site in Oklahoma. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and MFRSR. In addition to cloud optical depth, the new retrieval method also infers a "radiatively effective" cloud fraction.

Marshak, A.↗