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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Land surface Verification Toolkit (LVT)

LVT is a framework developed to provide an automated, consolidated environment for systematic land surface model evaluation Includes support for a range of in-situ, remote-sensing and other model and reanalysis products. Supports the analysis of outputs from various LIS subsystems, including LIS-DA, LIS-OPT, LIS-UE. Note: The Land Information System Verification Toolkit (LVT) is a NASA software tool designed to enable the evaluation, analysis and comparison of outputs generated by the Land Information System (LIS). The LVT software is released under the terms and conditions of the NASA Open Source Agreement (NOSA) Version 1.1 or later. Land Information System Verification Toolkit (LVT) NOSA.

surface model↗
NASA NTRS2023

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R 2 ) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr -1 (original) to −57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.

Greenland Ice Sheet↗
NASA NTRS2024

Evaluation of Vertical Patterns in Chlorophyll-A Derived From A Data Assimilating Model of Satellite-Based Ocean Color

Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m −3 , which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 mg Chl m −3 ) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth-resolved observations. Uncertainties in float bio-optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Lionel A Quintero↗
DOE OSTI2026

Neural Scaling Laws for Jet Generation

Recently observed empirical scaling laws describe the performance of foundation-type models as three independent key quantities -- dataset size, compute, and model parameters -- are modified. Extracting these scaling laws informs the training of large complex models for which the tuning of hyperparameters in traditional ways is not feasible. This work for the first time explores if scaling laws can also be observed for the task of particle jet generation -- both relevant as a pre-training objective for foundation models and as in-situ simulation by itself. We indeed replicate the key logarithmic scaling law behavior for model-size scaling. Beyond studying the next token prediction validation loss of the generative model, we also study the sliced Wasserstein distance of five physical quantities that are not immediately available to the model during training. Our study shows that this quantity is monotonically related to the next token prediction validation loss, meaning that this loss is indeed a good proxy for the physics performance. For the scaling with dataset size and compute, we observe substantially weaker scaling behavior of both the loss and the sliced Wasserstein distance. We analyze this behavior by introducing the concept of a learnable window, and argue that autoregressive next token prediction on jet constituents exhibits comparatively rapid saturation relative to language-model studies. We discuss possible origins of this behavior, including the stochastic nature of QCD radiation and differences between generative and supervised learning tasks in collider physics.

Amram, Oz [Fermilab]↗
NASA NTRS2010

Utilizing In Situ Directional Hyperspectral Measurements to Validate Bio-Indicator Simulations for a Corn Crop Canopy

Two radiative transfer canopy models, SAIL and the two-layer Markov-Chain Canopy Reflectance Model (MCRM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the photochemical reflectance index in a cornfield. In situ hyperspectral measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles (psi) at three different view zenith angles (Theta (sub v)), and later used to validate model outputs. Field observations of photochemical reflectance index (PRI) for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, as a function of both Theta (sub v) and psi . Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, the MCRM-simulated PRI values showed satisfactory correlation and RMSE, as compared to in situ values. However, the performance of the MCRM model was significantly improved after defining a lower canopy layer comprised of shaded leaves beneath the upper sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; but unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. Leaf area index (LAI) showed the most significant impact on MCRM-simulated PRI among the parameters studied. This research shows the importance of hyperspectral and narrow band sensor studies, and especially the necessity of including the green wavelengths (e.g., 531 nm) on satellites proposing to monitor carbon dynamics of terrestrial ecosystems.

Cheng, Yen-Ben↗
DOE OSTI2021

Evaluating the grain-scale deformation behavior of a single-phase FCC high entropy alloy using synchrotron high energy diffraction microscopy

We report although the deformation behavior of high-entropy alloys (HEAs) has been extensively studied at the macroscale, many important properties have yet to be explored for these alloys at the microscale, thus hampering accurate prediction of damage and failure processes. Synchrotron high-energy diffraction microscopy (HEDM) and fast-Fourier transform-based crystal plasticity modeling was conducted to investigate the three-dimensional (3D) grain-resolved micromechanical response for approximately 1,900 constituent grains within a single-phase FCC HEA up to 1% applied strain. The evolution of grain-resolved elastic strains, lattice reorientations, and maximum resolved shear stresses (mRSS) were evaluated to quantify elastic, yield, and fully plastic behavior. Overall, the initial critical resolved shear stress (CRSS), determined via in situ HEDM and companion modeling, was found to be > 20% higher than estimated using the classical polycrystalline Taylor factor (M = 3.06). However, a descriptive parameter based on the average grain-resolved Taylor factor ($\overline{M}$) was found to show excellent agreement with plastic yielding behavior observed within HEDM datasets. Noticeable deviations in HEDM lattice reorientations compared to both EVP-FFT simulations and classical predictions for FCC polycrystals were discovered, highlighting the complexity in correlating local lattice reorientations, Taylor, and Schmid factors with plastic response for this material at the grain-scale. Therefore, it is anticipated that the overall trends and parameter identification of 3D grain-resolved properties in this study can serve as an important foundation for continued mesoscale investigation on both well-established and newly developed Cantor-like HEAs.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Demonstration of in-Situ Resource Utilization of Lunar Regolith for Plant Growing Systems Through Scaled Capillary Models

The development of reliable and bioregenerative crop growth production systems is vital for human exploration into deep space. As the National Aeronautics and Space Administration (NASA) prepares for the Artemis missions, scientists need to find a way to provide consistent and sufficient water delivery for all stages of a plant’s life cycle. NASA has been able to successfully model passive flow through felt material, to mimic the water uptake and transport through a plant, in microgravity. However, more studies need to be conducted to adapt the model for a substrate-based system and incorporate how flow will change during each stage of plant growth. For future missions, payload requirements to support crop production systems will need to be limited, leading to the use of available resources, such as lunar regolith. Although numerous lunar regolith simulants are commercially available, few have been evaluated for their suitability in agricultural applications. First, a base regolith simulant will need to be identified based on its physical and chemical properties. Then, additional amendments to improve the properties of the simulants to support plant growth will be identified. The design and composition of the substrate will be based on water transport requirements for different stages of plant growth. Scaled capillary models can be utilized to study surface-tension driven flows through various designer substrates to modify the physical properties of the selected regolith simulant. These models can accurately represent how flow will act in a reduced gravity environment, which can be used to design a full-scale facility for surface missions. This project will aid space researchers in the design of future crop production systems for surface missions by creating a refined model that can be used at all stages of plant growth and utilize in situ resources.

Fluids↗
DOE OSTI2024

Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0–100 μg mL –1 ), europium (0–150 μg mL –1 ), samarium (0–250 μg mL –1 ), praseodymium (0–350 μg mL –1 ), neodymium (0–1000 μg mL –1 ), and HNO 3 (2–4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet–visible–near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9–5.7% for the seven factors. Further, the optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2012

Twenty Years of Progress on Global Ocean Tides: The Impact of Satellite Altimetry

At the dawn of the era of high-precision altimetry, before the launch of TOPEX/Poseidon, ocean tides were properly viewed as a source of noise--tidal variations in ocean height would represent a very substantial fraction of what the altimeter measures, and would have to be accurately predicted and subtracted if altimetry were to achieve its potential for ocean and climate studies. But to the extent that the altimetry could be severely contaminated by tides, it also represented an unprecedented global-scale tidal data set. These new data, together with research stimulated by the need for accurate tidal corrections, led to a renaissance in tidal studies in the oceanographic community. In this paper we review contributions of altimetry to tidal science over the past 20 years, emphasizing recent progress. Mapping of tides has now been extended from the early focus on major constituents in the open ocean to include minor constituents, (e.g., long-period tides; non-linear tides in shelf waters, and in the open ocean), and into shallow and coastal waters. Global and spatially local estimates of tidal energy balance have been refined, and the role of internal tide conversion in dissipating barotropic tidal energy is now well established through modeling, altimetry, and in situ observations. However, energy budgets for internal tides, and the role of tidal dissipation in vertical ocean mixing remain controversial topics. Altimetry may contribute to resolving some of these important questions through improved mapping of low-mode internal tides. This area has advanced significantly in recent years, with several global maps now available, and progress on constraining temporally incoherent components. For the future, new applications of altimetry (e.g., in the coastal ocean, where barotropic tidal models remain inadequate), and new mission concepts (studies of the submesoscale with SWOT, which will require correction for internal tides) may bring us full circle, again pushing further development of tidal models as corrections.

Egbert, Gary↗
NASA NTRS2002

The Development of Midlatitude Cirrus Models for MODIS Using FIRE-I, FIRE-II, and ARM In Situ Data

Detailed in situ data from cirrus clouds have been collected during dedicated field Campaigns, but the use of the size and habit distribution data has been lagging in the development of more realistic cirrus scattering models. In this study, the authors examine the use of in situ cirrus data collected during three field campaigns to develop more realistic midlatitude cirrus microphysical models. Data are used from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)-I (1986) and FIRE-II (1991) campaigns and from a recent Atmospheric Radiation Measurement (ARM) Program campaign held in March-April of 2000. The microphysical models are based on measured vertical distributions of both particle size and particle habit and are used to develop new scattering models for a suite of moderate-resolution imaging spectroradiometer (MODIS) bands spanning visible. near-infrared, and infrared wavelengths. The sensitivity of the resulting scattering properties to the underlying assumptions of the assumed particle size and habit distributions are examined. It is found that the near-infrared bands are sensitive not only to the discretization of the size distribution but also to the assumed habit distribution. In addition. the results indicate that the effective diameter calculated from a given size distribution tends to be sensitive to the number of size bins that are used to discretize the data and also to the ice-crystal habit distribution.

Nasiri, Shaima L.↗
NASA NTRS2018

The Impact of Prior Biosphere Models in the Inversion of Global Terrestrial CO2 Fluxes by Assimilating OCO-2 Retrievals

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emissions and biospheric fluxes. The processes controlling terrestrial biosphere-atmosphere carbon exchange are currently not fully understood, resulting in terrestrial biospheric models having significant differences in the quantification of biospheric CO2 fluxes. Atmospheric transport models assimilating measured (in situ or space-borne) CO2 concentrations to estimate "top-down" fluxes, generally use these biospheric CO2 fluxes as a priori information. Most of the flux inversion estimates result in substantially different spatio-temporal posteriori estimates of regional and global biospheric CO2 fluxes. The Orbiting Carbon Observatory 2 (OCO-2) satellite mission dedicated to accurately measure column CO2 (XCO2) allows for an improved understanding of global biospheric CO2 fluxes. OCO-2 provides much-needed CO2 observations in data-limited regions facilitating better global and regional estimates of "top-down" CO2 fluxes through inversion model simulations. The specific objectives of our research are to: 1) conduct GEOS-Chem 4D-Var assimilation of OCO-2 observations, using several state-of-the-science biospheric CO2 flux models as a priori information, to better constrain terrestrial CO2 fluxes, and 2) quantify the impact of different biospheric model prior fluxes on OCO-2-assimilated a posteriori CO2 flux estimates. Here we present our assessment of the importance of these a priori fluxes by conducting Observing System Simulation Experiments (OSSE) using simulated OCO-2 observations with known "true" fluxes.

Biosphere↗
NASA NTRS2004

Sensitivity Studies for In-Situ Automated Tape Placement of Thermoplastic Composites

This modeling effort seeks to improve the interlaminate bond strength of thermoplastic carbon composites produced by the in-situ automated tape placement (ATP) process. An existing high productivity model is extended to lower values of the Peclet number that correspond to the present operating conditions of the Langley ATP robot. (The Peclet number is the dimensionless ratio of inertial to diffusive heat transfer.) In sensitivity studies, all of the process and material parameters are individually varied. The model yields the corresponding variations in the effective bonding time (EBT) referred to the glass transition temperature. According to reptation theory, the interlaminate bond strength after wetting occurs is proportional to the one-fourth power of EBT. The model also computes the corresponding variations in the thermal input power (TIP) and the mass and volumetric process rates. Process studies show that a 10 percent increase in the consolidation length results in a 20 percent increase in EBT and a 5 percent increase in TIP. A surprising result is that a 10 K decrease in the tooling temperature results in a 25 percent increase in EBT and an 8 percent increase in TIP. Material studies show that a 10 K decrease in glass transition temperature results in an 8 percent increase in EBT and a 8 percent decrease in TIP. A 20 K increase in polymer degradation temperature results in a 23 percent increase in EBT with no change in TIP.

Costen, Robert C.↗
NASA NTRS2022

Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle

The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, RS), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and RS are irreconcilable. When we estimate GPP based on RS measurements and some assumptions about RS:GPP ratios, we found the resulted global GPP values (bootstrap mean 149^(+29)_(−23) Pg C/yr) are significantly higher than most GPP estimates reported in the literature (113^(+18)_(−18) Pg C/yr). Similarly, historical GPP estimates imply a soil respiration flux (Rs(_GPP), bootstrap mean of 68^(+10)_(−8) Pg C/yr) statistically inconsistent with most published RS values (87^(+9)_(−8) Pg C/yr), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R_(S):GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.

Jinshi Jian↗
DOE OSTI2022

Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle

The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and R S are irreconcilable. When we estimate GPP based on R S measurements and some assumptions about R S :GPP ratios, we found the resulted global GPP values (bootstrap mean ${149}^{+29}_{-23}$ Pg C yr ⁻1 ) are significantly higher than most GPP estimates reported in the literature (${113}^{+18}_{-18}$ Pg C yr ⁻1 ). Similarly, historical GPP estimates imply a soil respiration flux (Rs GPP , bootstrap mean of ${68}^{+10}_{-8}$ Pg C yr ⁻1 ) statistically inconsistent with most published R S values (${87}^{+9}_{-8}$ Pg C yr ⁻1 ), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R S :GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Mapping Isoprene Emissions over North America using Formaldehyde Column Observations from Space

I] We present a methodology for deriving emissions of volatile organic compounds (VOC) using space-based column observations of formaldehyde (HCHO) and apply it to data from the Global Ozone Monitoring Experiment (GOME) satellite instrument over North America during July 1996. The HCHO column is related to local VOC emissions, with a spatial smearing that increases with the VOC lifetime. lsoprene is the dominant HCHO precursor over North America in summer, and its lifetime (approx. = 1 hour) is sufficiently short that the smearing can be neglected. We use the Goddard Earth Observing System global 3-D model of tropospheric chemistry (GEOS-CHEM) to derive the relationship between isoprene emissions and HCHO columns over North America and use these relationships to convert the GOME HCHO columns to isoprene emissions. We also use the GEOS-CHEM model as an intermediary to validate the GOME HCHO column measurements by comparison with in situ observations. The GEOS-CHEM model including the Global Emissions Inventory Activity (GEIA) isoprene emission inventory provides a good simulation of both the GOME data (r(sup 2) = 0.69, n = 756, bias = +l1 %) and the in situ summertime HCHO measurements over North America (r(sup 2) = 0.47, n = 10, bias = -3%). The GOME observations show high values over regions of known high isoprene emissions and a day-to-day variability that is consistent with the temperature dependence of isoprene emission. Isoprene emissions inferred from the GOME data are 20% less than GEIA on average over North America and twice those from the U S . EPA Biogenic Emissions Inventory System (BEIS2) inventory. The GOME isoprene inventory when implemented in the GEOS-CHEM model provides a better simulation of the HCHO in situ measurements thaneitherGEIAorBEIS2 (r(sup 2) = 0.71,n= 10, bias = -10 %).

Palmer, Paul I.↗
NASA NTRS2000

Immersive Environment Technologies for Mars Exploration

JPL's charter includes the unmanned exploration of the Solar System. One of the tools for exploring other planets is the rover as exemplified by Sojourner on the Mars Pathfinder mission. The light speed turnaround time between Earth and the outer planets precludes the use of teleoperated rovers so autonomous operations are built in to the current and upcoming generation devices. As the level of autonomy increases, the mode of operations shifts from low-level specification of activities to a higher-level specification of goals. To support this higher-level activity, it is necessary to provide the operator with an effective understanding of the in-situ environment and also the tools needed to specify the higher-level goals. Immersive environments provide the needed sense of presence to achieve this goal. Use of immersive environments at JPL has two main thrusts that will be discussed in this talk. One is the generation of 3D models of the in-situ environment, in particular the merging of models from different sensors, different modes (orbital, descent, and lander), and even different missions. The other is the use of various tools to visualize the environment within which the rover will be operating to maximize the understanding by the operator. A suite of tools is under development which provide an integrated view into the environment while providing a variety of modes of visualization. This allows the operator to smoothly switch from one mode to another depending on the information and presentation desired.

Wright, John R.↗
NASA NTRSDate not supplied

Timing and Geochemical Evolution of Triassic and Jurassic Magmatism during the Break-up of Pangea along the Eastern North American Margin

While our understanding of continental break-up has seen dramatic advances over the past decades, the impact of syn-rift melt generation on the transition from mechanical stretching to seafloor spreading remains enigmatic. Early Mesozoic continental break-up along the U.S. Eastern North American Margin (ENAM) is characterized by protracted Triassic lithospheric stretching and syn-rift deposition interrupted by voluminous Central Atlantic Magmatic Province (CAMP) magmatism. This magmatic phase is followed by ~50 Myr of protracted rifting prior to steady-state seafloor spreading. Mesozoic magmatism recognized in outcrop and aeromagnetic datasets along the ENAM has been summarily attributed to CAMP, although extensive regional dikes preserved in the ENAM proximal rift domain remain largely undated. This study provides new constraints on the timing, duration, and geochemical evolution of syn-rift ENAM magmatism using in-situ apatite U-Pb geochronology and whole-rock geochemistry and integrates these data into a tectonic model. We present in-situ apatite U-Pb ages and whole-rock geochemical data for 16 diabase dikes and sills from NJ, PA, VA, NC, and SC. A Palisades Sill sample yielded an age of 201 ± 8 Ma and agrees with previous 40 Ar/39 Ar and U-Pb ages. Our new in-situ apatite U-Pb ages fall into three clusters and suggest three main pulses of magmatism along the ENAM, with an initial pulse of magmatism at ~205-195 Ma attributed to CAMP. Whole-rock geochemistry of this pulse shows silica (46-53 wt.%), total alkalis (2-4 wt.%), and enrichment of LREEs relative to HREEs, comparable to previously reported geochemical data for CAMP-related rocks along the ENAM. A second magmatic pulse occurred between ~181-175 Ma and shows slightly higher silica and total alkalis, compared to the older CAMP-age phase. The third pulse between ~166-145 Ma generally shows slightly higher silica and total alkalis. LOI and Sr/Yb values of the two younger pulses are similar to CAMP-age samples suggesting no post-crystallization alteration. These new data demonstrate long-lived syn-rift off-axis magmatism persisted ~50 Myr after the onset of CAMP. This post-CAMP off-axis magmatism is likely related to slow magma-limited spreading during the protracted transition to symmetric seafloor spreading along the ENAM.

Z. Foster-Baril↗
NASA NTRS1993

Interpretation of NO(x)/NO(y) observations from AASE-2 using a model of chemistry along trajectories

In situ measurements of NO and NO(y) are used to derive the ratio NO(x)/NO(y) along the flight track of the NASA ER-2 aircraft. Data are presented for two flights at midlatitudes in October 1991 during the Airborne Arctic Stratospheric Expedition-2 (AASE-2). Aerosol particle surface area was concurrently measured. The observations are compared with a photochemical model integrated along back trajectories from the aircraft flight track. Comparison of observations with the model run along trajectories and at a fixed position clearly and quantitatively demonstrates the importance of an air parcel's dynamic history in interpretation of local chemical observations. Comparison of the data with model runs under different assumptions regarding heterogeneous chemistry further reinforces the case for occurrence of the reaction of N2O5 + H2O on sulfate aerosol surfaces in the atmosphere. Finally, comparisons for which relative changes in the model and the data are not consistent caution that our ability to resolve all the observations is not yet complete.

Kawa, S. R.↗