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At least 577 records · Page 32

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

Limaye, Ashutosh S.↗

Integrated Multidisciplinary Optimization Objects

OpenMDAO is an open-source MDAO framework. It is used to develop an integrated analysis and design environment for engineering challenges. This Phase II project integrated additional modules and design tools into OpenMDAO to perform discipline-specific analysis across multiple flight regimes at varying levels of fidelity. It also showcased a refined system architecture that allows the system to be less customized to a specific configuration (i.e., system and configuration separation). By delivering a capable and validated MDAO system along with a set of example applications to be used as a template for future users, this work greatly expands NASA's high-fidelity, physics-based MDAO capabilities and enables the design of revolutionary vehicles in a cost-effective manner. This proposed work complements M4 Engineering's expertise in developing modeling and simulation toolsets that solve relevant subsonic, supersonic, and hypersonic demonstration applications.

Alston, Katherine↗

The interactive global fire module pyrE (v1.0)

Fires affect the composition of the atmosphere and Earth’s radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS (Goddard Institute for Space Studies) interactive fire emissions *module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized by anthropogenic impacts based on population density data. Fire emissions are generated from the flaming phase in pyrE (active fires). Using pyrE, we examine fire occurrence, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE’s ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are biased low by 32 %–42 %, depending on emitted species, compared to the GFED4s (Global Fire Emissions Database) inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Regionally, the resulting AOD of a simulation with interactive fire emissions is underestimated mostly over Indonesia compared to a simulation with GFED4s emissions and to MODIS AOD. In other parts of the world pyrE’s performance in terms of AOD is marginal to a simulation with prescribed fire emissions.

Fires↗

Feasibility of Earthbound Motion in Lunar Gravity

BACKGROUND: Marginal stability of astronaut movement while performing lunar surface tasks has been well documented, and is clearly demonstrated in videos of falls, and near falls, during Apollo Lunar Extravehicular Activities. Referencing mission reports from Apollo 15 and 16 [1, 2], suspected causes for falls include: surface conditions, visibility, and gravitational effects (hypogravity). In this preliminary test, we employ the open-source biomechanical tool OpenSim [3, 4] to analyze the impact of lunar gravity (Lg) on two object-pickup motions performed by a single shirt-sleeved subject. Specifically, we attempt to answer the following questions based on an estimation of the Center of Mass Projection (CoMP) and ground reaction force Center of Pressure (COP) as it relates to the astronaut Base of Support (BOS) for 1g and Lg conditions: 1. Is the task motion, as performed in 1g, dynamically feasible in 1g and Lg? 2. Can we make the motion dynamically feasible in Lg by slowing it down? 3. Is the Lg COP equal to the 1g COP at a theoretically predicted reduction in motion speed? METHODS AND RESULTS: To answer the first question, the gravitational acceleration in the OpenSim model is modified from a nominal 9.81 m/s2 to 1.64 m/s2, and the 1g joint trajectory is input to an OpenSim based method [5] for estimating ground reaction forces and moments. From this method, the position of the CoMP and COP can be estimated and checked to see if they remain within a simulated BOS formed from the footprint of the OpenSim model to determine whether the motion is dynamically feasible. As expected, both of the motions were estimated to be feasible in a 1g environment, however, both motions had periods of infeasibility in Lg. It is well known that crew members make adjustments to motion trajectories in altered gravity fields to maintain balance. As a first step, we considered the simple adjustment of slowing the motion in Lg by a constant factor. This was accomplished by scaling the time stamps in the motion trajectory file by that factor. For the two motions considered, it was found that scale factors of 1.3 and 1.4 kept the COP just within the subject BOS. The CoMP is unchanged by the gravity field. Simple analysis of an inverted pendulum in the Lg environment, which generalizes to a general multibody system, leads to a theoretical prediction that a reduction in speed factor of √1g/Lg, or 2.445, will make the COP trajectory in Lg equivalent to that in 1g. When the above procedure was performed with a factor of 2.445, the estimated COP in Lg, was observed to be very close to that in 1g. In summary, we have developed a method for estimating the CoMP and COP in Lg, for subject motion collected in 1g. We believe this method can prove to be a valuable check and balance for simulated Lg training and testing by exposing potential simulator-induced artifacts that make the simulated task motion seem possible, when in fact, it would violate the above criteria. We also note that a reduction in task speed should tend the task motion towards stability, with a theoretical slowdown factor of √1g/Lg making the motion stability equal to that in 1g according to the CoMP and COP criteria.

R K Huffman↗

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral instruments produce high-resolution and information-dense radiance spectra, thus offering the opportunity to reduce uncertainties in retrieval products. An optimal estimation-based cirrus cloud optical and microphysical product retrieval is under development for the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Earth Surface Mineral Dust Source Investigation (EMIT) instruments, and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder). The spectral coverage of all three instruments includes the ultraviolet, visible, and near-infrared. In this study a very fast radiative transfer model, the Principal Component-based Radiative Transfer Model in the solar spectral region (PCRTM-Solar), is used for forward modeling computations. This will reduce the computational burden in the forward radiance and Jacobian calculations as the cost function is minimized, enabling the entire AVIRIS, EMIT, and CLARREO-Pathfinder spectral range to be used in the optimal estimation framework. Using the entire spectrum will maximize the information content, resulting in a more robust and more accurate retrieval. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water. Preliminary results will be shown.

Jeffrey Mast↗

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral shortwave instruments produce high-resolution and information-dense spectra, thus offering the opportunity to reduce uncertainties in retrieval products. We are in the process of developing a retrieval that uses the very fast Principal Component Radiative Transfer Model in the solar spectral region (PCRTM-Solar) in the forward model calculations. This retrieval will use measured reflectances from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder) instruments. In this manuscript we present progress towards a reference retrieval employing a widely used, verified, accurate, yet computationally slower radiative transfer modeling technique. The reference retrieval, while too slow for using the complete hyperspectral measurement, will allow us to study the behavior of retrieval products and help us verify results from our in-development fast retrieval. Both retrievals will use the optimal estimation retrieval framework. In this manuscript we present results from an uncertainty analysis considering three uncertainty sources for a cirrus cloud retrieval in the form of error covariance matrices: reflectance uncertainty due to water vapor, the reflectance uncertainty due to ice crystal scattering assumptions, and the instrument measurement uncertainty. Results show that the uncertainty due to habit selection is the largest, while that due to water vapor is at most 0.6% relative to channel reflectance. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water.

Cirrus cloud↗

Capturing and Analyzing Requirements with FRET

FRET is an open source tool, developed at NASA Ames, for writing, understanding, formalizing, and analyzing requirements. In practice, requirements are typically written in natural language, which is ambiguous and consequently not amenable to formal analysis. Since formal, mathematical notations are unintuitive, requirements in FRET are entered in a restricted, natural language, called FRETish with precise unambiguous meaning. FRET helps users write FRETish requirements both by providing grammar information and examples during editing, but also through English and diagrammatic explanations to clarify subtle semantic issues. For each requirement, FRET automatically produces formalizations and supports interactive simulation of produced formalizations to ensure that they capture user intentions. Through its analysis portal, FRET connects to analysis tools by exporting verification code. Currently FRET connects to (1) the CoCoSim automated analysis tool for the verification of Simulink and Stateflow models, and (2) the Copilot runtime monitoring tool for the analysis of C programs. FRET also supports the consistency/realizability analysis of requirements for identifying conflicting requirements. In this tutorial, we introduce FRET and learn to speak and analyze FRETish through several examples.

FRET↗

Ocean Carbon From Space: Current Status and Priorities for the Next Decade

The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.

oceanography↗

Sharks Associated With A Large Sand Shoal Complex: Community Insights From Longline and Acoustic Telemetry Surveys

Offshore sand shoals are a coveted sand source for coastal restoration projects and as sites for wind energy development. Shoals often support unique fish assemblages but their habitat value to sharks is largely unknown due to the high mobility of most species in the open ocean. This study pairs multi-year longline and acoustic telemetry surveys to reveal depth-related and seasonal patterns in a shark community associated with the largest sand shoal complex in east Florida, USA. Monthly longline sampling from 2012–2017 yielded 2,595 sharks from 16 species with Atlantic sharpnose (Rhizoprionodon terraenovae), blacknose (Carcharhinus acronotus), and blacktip (C. limbatus) sharks being the most abundant species. A contemporaneous acoustic telemetry array detected 567 sharks from 16 species (14 in common with longlines) tagged locally and by researchers elsewhere along the US East Coast and Bahamas. PERMANOVA modeling of both datasets indicate that the shark species assemblage differed more across seasons than water depth although both factors were important. Moreover, the shark assemblage detected at an active sand dredge site was similar to that at nearby undisturbed sites. Water temperature, water clarity, and distance from shore were habitat factors that most strongly correlated to community composition. Both sampling approaches documented similar single-species and community trends but longlines underestimated the shark nursery value of the region while telemetry-based community assessments are inherently biased by the number of species under active study. Overall, this study confirms that sharks can be an important component of sand shoal fish communities but suggests that deeper water immediately adjacent to shoals (as opposed to shallow shoal ridges) is more valuable to some species. Potential impacts to these nearby habitats should be considered when planning for sand extraction and offshore wind infrastructure.

Shark Management↗

Designing Learning Experiences With A Low-Cost Robotic Arm

Robots have gained immense popularity in Hollywood and growth globally in both industrial manufacturing and non-manufacturing environments and applications such as healthcare, service sector, and space exploration. To date, there are several examples of simple and low-cost educational robotic platforms and commercially available platforms (e.g., Lego Mindstorms, VEX Robotics) for incorporation into existing curriculum. However, most low-cost examples require access to rapid-prototyping tools, such as 3D printers to manufacture the structure of the robot, while commercially available platforms are relatively expensive (> $1,000). Although the low-cost, open-source examples provide increased access, these examples require design and manufacturing tasks that would be considered outside the learning objectives of an upper-level robotics course and are better suited for other introductory courses. Thus, we asked, how can a robotic platform be incorporated into existing robotics curriculum to enhance students' learning experiences? To explore this research question, we introduce a low-cost (<$200), untethered, and transportable robotic platform that is easy to assemble using off-the-shelf components. This kit can be powered from a laptop computer and does not rely on access to rapid-prototyping tools such as 3D printers or laser cutters, making this a more accessible option in undergraduate engineering courses. Specifically, we aimed to investigate the design of experiential learning experiences for the mathematical modeling of the forward and inverse kinematics of a serial robotic arm that complements existing robotics curriculum. The experiential learning experience focuses on traditional written answer, simulation in MATLAB, and finally implementation on a robotic platform. Few studies examined this accessible option when evaluating experiential learning experiences that complement existing robotics curricula. To assess the impact of this robotic arm kit in an undergraduate course, we implemented an educational intervention that allowed us insight into student perceptions, takeaways on the course and activities involving the robotic arm, and the impact of the course on their career outlook when comparing activities that involved use of the robotic arm and those that did not. Details on the design, development and implementation of the learning activities is provided. Both quantitative and qualitative data were collected and analyzed. The results presented in this paper discuss students finding the learning activities on the robotic arms more helpful than those without, and that students found high value in the hands-on experiences and real-world scenarios offered by the activities using the robotic arm. Challenges to implementation of the robotic arms are discussed, including students’ prior knowledge of using robotic arms.

Eric J. Markvicka↗

Enhancing Dataset Discovery and Usage Tracking in Earth Sciences: Integrating Knowledge Graphs and Large Language Models

NASA's Data Active Archive Centers (DAACs) have played a crucial role in supporting a wide range of applied research in Earth and Environmental sciences. To date, over 20,000 publications have been collected, citing more than 3,000 NASA Earth science datasets. We present an innovative approach that links datasets and collected publications through a knowledge graph (KG). This KG enables the tracking of dataset citations throughout the dataset's lifecycle, revealing patterns of dataset usage across various applied research areas. We fine-tuned the pre-trained NASA IMPACT INDUS-Base Retriever Large Language Model (LLM) using a set of labeled publication abstracts. Our results indicate that 87% of the publications were classified into one of twenty applied research areas, while the remaining 13% were categorized into non-applied research areas. The classified publications linked to datasets are used to discover datasets by users interested in specific applied research and by dataset providers to determine dataset usage for applications.

open-source↗

Lessons from Climate Modeling on the Design and Use of Ensembles for Crop Modeling

Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.

Model ensembles↗

Implications of Lag-Luminosity Relationship for Unified GRB Paradigms

Spectral lags (tau(sub lag)) are deduced for 1437 long (T(sub 90) greater than 2 s) BATSE gamma-ray bursts (GRBs) with peak flux F(sub p) greater than 0.25 photons cm(sup -2)/s, near to the BATSE trigger threshold. The lags are modeled to approximate the observed distribution in the F(sub p)-T(sub lag) plane, realizing a noise-free representation. Assuming a two-branch lag-luminosity relationship, the lags are self-consistently corrected for cosmological effects to yield distributions in luminosity, distance, and redshift. The results have several consequences for GRB populations and for unified gamma-ray/afterglow scenarios which would account for afterglow break times and gamma-ray spectral evolution in terms of jet opening angle, viewing angle, or a profiled jet with variable Lorentz factor: A component of the burst sample is identified - those with few, wide pulses, lags of a few tenths to several seconds, and soft spectra - whose Log[N]-Log[F(sub p)] distribution approximates a -3/2 power-law, suggesting homogeneity and thus relatively nearby sources. The proportion of these long-lag bursts increases from negligible among bright BATSE bursts to approx. 50% at trigger threshold. Bursts with very long lags, approx. 1-2 less than tau(sub lag) (S) less than 10, show a tendency to concentrate near the Supergalactic Plane with a quadrupole moment of approx. -0.10 +/- 0.04. GRB 980425 (SN 1998bw) is a member of this subsample of approx. 90 bursts with estimated distances less than 100 Mpc. The frequency of the observed ultra-low luminosity bursts is approx. 1/4 that of SNe Ib/c within the same volume. If truly nearby, the core-collapse events associated with these GRBs might produce gravitational radiation detectable by LIGO-II. Such nearby bursts might also help explain flattening of the cosmic ray spectrum at ultra-high energies, as observed by AGASA.

Norris, J. P.↗

Computational and experimental investigation of cavity flowfields

This paper presents a computational and experimental investigation of supersonic flow past a cavity in a flat plate. The source of the particular interest in this problem is the ongoing study of the aerodynamic interference effects between a separating store and its bay in the parent body. An upwind relaxation scheme, utilizing flux vector splitting and line-Gauss-Seidel iterations, is used to solve Reynolds-averaged Navier-Stokes equations. Spatial discretizations of this two-dimensional analysis are based on implicit and finite-volume methods. Turbulence is modeled and shocks are captured. The flowfield of the symmetry plane at the half-width is computationally visualized and all flow properties are computed. Experimental tests are conducted in the Langley Unitary Plan Wind Tunnel to measure wall pressures and to capture schlieren photographs. Qualitative as well as quantitative data of computations and experiments agree very well. These two vehicles of investigation are merged to show open, closed and transitional cavity flow behaviors.

Baysal, O.↗

Dynamical Interpolation of Mesoscale Flows in the TOPEX/Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (T/P) ground tracks surrounding the US Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, Dennis J., Jr.↗

Dynamical Interpolation of Mesoscale Flows in the TOPEX/ Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (TIP) ground tracks surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, D. J.↗

Shergottite Lead Isotope Signature in Chassigny and the Nakhlites

The nakhlites/chassignites and the shergottites represent two differing suites of basaltic martian meteorites. The shergottites have ages less than or equal to 0.6 Ga and a large range of initial Sr-/Sr-86 and epsilon (Nd-143) ratios. Conversely, the nakhlites and chassignites cluster at 1.3-1.4 Ga and have a limited range of initial Sr-87/Sr-86 and epsilon (Nd-143). More importantly, the shergottites have epsilon (W-182) less than 1, whereas the nakhlites and chassignites have epsilon (W-182) approximately 3. This latter observation precludes the extraction of both meteorite groups from a single source region. However, recent Pb isotopic analyses indicate that there may have been interaction between shergottite and nakhlite/chassignite Pb reservoirs.Pb Analyses of Chassigny: Two different studies haveinvestigated 207Pb/204Pb vs. 206Pb/204Pb in Chassigny: (i)TIMS bulk-rock analyses of successive leaches and theirresidue [3]; and (ii) SIMS analysis of individual minerals[4]. The bulk-rock analyses fall along a regression of SIMSplagioclase analyses that define an errorchron that is olderthan the Solar System (4.61±0.1 Ga); i.e., these define amixing line between Chassigny’s principal Pb isotopic components(Fig. 1). Augites and olivines in Chassingy (notshown) also fall along or near the plagioclase regression [4].This agreement indicates that the whole-rock leachateslikely measure indigenous, martian Pb, not terrestrial contamination[5]. SIMS analyses of K-spars and sulfides definea separate, sub-parallel trend having higher 207Pb/206Pbvalues ([4]; Fig. 1). The good agreement between the bulkrockanalyses and the SIMS analyses of plagioclases alsoindicates that the Pb in the K-spars and sulfides cannot be amajor component of Chassigny.The depleted reservoir sampled by Chassigny plagioclaseis not the same as the solar system initial (PAT) andrequires a multi-stage origin. Here we show a two-stagemodel (Fig. 1) with a 238U/204Pb (μ) of 0.5 for 4.5-2.4 Gaand a μ of 7 for 2.4-1.4 Ga. This is not a unique model butdoes produce a Pb composition that falls on the plagioclaseregression at 1.4 Ga, the approximate igneous age of Chassigny [1]. It should be noted that low-μ single-stage modelsare not capable of producing sufficiently radiogenic 206Pb/204Pb at 1.4 Ga.Relation to Shergottites: The Chassigny K-spars and sulfides fall along a second mixing line defined by leachesand residues of depleted and intermediate shergottites [6]. This mixing line falls above the plagioclase regression.Therefore, we also interpret the radiogenic component of this mixing line to represent indigenous martian Pb. It ispossible that the depleted and intermediate shergottites and the Chassigny plagioclases sample radiogenic Pb from thethe same source, i.e., the mixing lines may intersect at high 206Pb/204Pb.Both K-spar and sulfide are late-stage phases. At the time of their crystallization, the Chassigny system appearsto have remained open to a depleted shergottite Pb reservoir. The depleted component of the shergottite mixing linecan be generated by a single-stage evolution from PAT (4.5 to 1.4 Ga) in a reservoir having a μ ~2. A similar modelfor the most depleted shergottites is also possible: μ = 1.5 for 4.5 to 0.3 Ga.Nakhlites: Nakhlite analyses plot between the shergottite and Chassigny plagioclase regressions [3]. So again,members of the nakhlite/chassignite suite show affinities to shergottite Pb.

Jones, J. H.↗