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NASA NTRS2005

Role of Probabilistic Micromechanics Modeling in Establishing Design Allowables in Composites

One of the major challenges in designing with any new material, and particularly with advanced composite materials, is the fidelity of material design allowables. In the case of composite materials, the concern arises from the inherent nature of these materials, i.e., their heterogeneous make-up and the various factors that affect their properties in a specific design environment. Composites have various scales - micro, macro, laminate and structural, as well as numerous other fabrication related parameters. Many advanced composites in aerospace applications involve complex two- and three-dimensional fiber architectures and requires high-temperature processing. Since there are uncertainties associated with each of these, the observed behavior of composite materials shows scatter. Evaluating the effect of each of these variables on the observed scatter in composite properties solely by teSting is cost and time prohibitive. One alternative is to evaluate these effects by computational simulation. The authors have developed probabilistic composite micromechanics techniques by combining woven composite micromechanics and Fast Probability Integration (FPI) techniques to address these issues. In this paper these techniques will be described and demonstrated through selected examples. Results in the form of cumulative distribution functions (CDF) of the composite properties of a MI (melt-infiltrated) SiC/SiC (silicon carbide fiber in a silicon carbide matrix) Composite will be presented. A CDF is a relationship defined by the value of the property (the response variable) with respect to the cumulative probability of occurrence. Furthermore, input variables causing scatter are identified and ranked based upon their sensitivity magnitude. Sensitivity information is very valuable in quality control. How these results can be utilized to develop design allowables so that these materials may be used by structural analysts/designers will also be discussed.

Mital, Subodh K.↗
NASA NTRS1989

Lagrangian photochemical modeling studies of the 1987 Antarctic spring vortex. II - Seasonal trends in ozone

A photochemical model consisting of 40 species and 107 reactions is integrated along 80-day air parcel trajectories calculated in the lower stratosphere for the springtime Antarctic. For the trajectory starting at 58 deg S, which may be regarded as outside the circumpolar vortex, only a small change in O3 occurs in the model. In contrast, for the air parcel starting in the vortex at 74 deg S, the O3 concentration is reduced by 93 percent during the 80 days from the beginning of August to late October. The model results for several species are compared with measurements from the Airborne Antarctic Ozone Experiment and, in general, good agreement is obtained. In the model, the dentrification of the air parcels in polar stratospheric clouds increases the amount of chlorine present in active form. Heterogeneous reactions maintain high active chlorine which destroys O3 via the formation of the ClO dimer. Results of calculations with reduced concentrations of inorganic chlorine show considerably reduced O3 destruction rates and compare favorably with the behavior of total O3 since the late 1970s. The remaining major uncertainties in the photochemical aspects of the Antarctic ozone hole are highlighted.

Austin, J.↗
NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 16

Contents include the folowing: Experimental Study of Fe-, Co- and Ni-partitioning Between Forsterite and low-Co Fe,Ni-Alloys: Implications for Formation of Olivine Condensates in Equilibrium with Primitive Metal. Channels and Fan-like Features on Titan Surface Imaged by the Cassini RADAR. The Oxygen Isotope Similarity of the Earth and Moon: Source Region or Formation Process? The Mn-53-Cr-53 System in CAIs: An Update. Comparative Planetary Mineralogy: Valence State Partitioning of Cr, Fe, Ti, and V Among Crystallographic Sites in Olivine, Pyroxene, and Spinel from Planetary Basalts. CAI Thermal History Constraints from Spinel: Ti Zoning Profiles and Melilite Boundary Clinopyroxenes. Noble Gas Study of New Enstatite SaU 290 with High Solar Gases. A Marine Origin for the Meridiani Planum Landing Site? A Mechanism for the Formation and Evolution of Tharsis as a Consequence of Mantle Overturn: Large Scale Lateral Heterogeneity in a Stably Stratified Mantle. Endolithic Colonization of Fluid Inclusion Trails in Mineral Grains. Microbial Preservation in Sulfates in the Haughton Impact Structure Suggests Target in Search for Life on Mars. Ascraeus Mons Fan-shaped Deposit, Mars: Geological History and Volcano-Ice Interactions of a Cold-based Glacier. Weathering Pits in the Antarctic Dry Valleys: Insolation-induced Heating and Melting, and Applications to Mars. Mineralogy and Petrography of Lunar Mare Regolith Breccia Meteorite MET 01-210. Geological Mapping of Ganymede. A Quantitative Analysis of Plate Motion on Europa: Implications for the Role of Rigid vs. Nonrigid Behavior of the Lithosphere. Comparison of Terrestrial Morphology, Ejecta, and Sediment Transport of Small Craters: Volcanic and Impact Analogs to Mars. An Integrated Study of OMEGA-Identified Mineral Deposits in Eastern Hebes Chasma, Mars. Global Spectral and Compositional Diversity of Mars: A Test of CRISM Global Mapping with Mars Express OMEGA Data. On Origin of Sedna. Processing ISS Images of Titan s Surface. LA-ICP-MS Study of Trace Elements in the Chaunskij Metal.

Source record↗
NASA NTRS2001

XML-Based Visual Specification of Multidisciplinary Applications

The advancements in the Internet and Web technologies have fueled a growing interest in developing a web-based distributed computing environment. We have designed and developed Arcade, a web-based environment for designing, executing, monitoring, and controlling distributed heterogeneous applications, which is easy to use and access, portable, and provides support through all phases of the application development and execution. A major focus of the environment is the specification of heterogeneous, multidisciplinary applications. In this paper we focus on the visual and script-based specification interface of Arcade. The web/browser-based visual interface is designed to be intuitive to use and can also be used for visual monitoring during execution. The script specification is based on XML to: (1) make it portable across different frameworks, and (2) make the development of our tools easier by using the existing freely available XML parsers and editors. There is a one-to-one correspondence between the visual and script-based interfaces allowing users to go back and forth between the two. To support this we have developed translators that translate a script-based specification to a visual-based specification, and vice-versa. These translators are integrated with our tools and are transparent to users.

Al-Theneyan, Ahmed↗
NASA NTRS2011

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Peters-Lidar, Christa D.↗
NASA NTRS2006

The Global Precipitation Measurement (GPM) Mission: An Overview

The Global Precipitation Measurement (GPM) Mission is an international satellite mission that uses advanced precipitation radar with a constellation of passive microwave radiometers to improve the accuracy, sampling, and coverage of global precipitation measurements. It is a science mission with integrated applications goals focusing on (1) advancing the knowledge of the global watedenergy cycle variability and freshwater availability and (2) improving weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of global precipitation. The GPM Mission is currently a partnership between NASA and the Japanese Aerospace Exploration Agency (JAXA), with opportunities for additional domestic and international partners in satellite constellation buildup and ground validation activities. The GPM Core satellite, which carries a JAXA-provided dual-frequency precipitation radar and a NASAprovided microwave radiometers with high-frequency capabilities for light rain and frozen precipitation measurements, is expected to be launched in the 2010 timeframe. The GPM Core will serve as a precipitation physics laboratory and a calibration system for improved precipitation measurements by a heterogeneous constellation of dedicated and operational microwave radiometers. NASA also plans to provide a "wild card" constellation member with a copy of the radiometer carried on the GPM Core to be placed in an orbit that maximizes the coverage and sampling of the constellation. An overview of the GPM mission concept, instrument capabilities, ground validation plans, and the expected scientific and societal benefits will be presented.

Hou, Arthur Y.↗
NASA NTRS1989

Nonlinear mesomechanics of composites with periodic microstructure

This work is concerned with modeling the mechanical deformation or constitutive behavior of composites comprised of a periodic microstructure under small displacement conditions at elevated temperature. A mesomechanics approach is adopted which relates the microimechanical behavior of the heterogeneous composite with its in-service macroscopic behavior. Two different methods, one based on a Fourier series approach and the other on a Green's function approach, are used in modeling the micromechanical behavior of the composite material. Although the constitutive formulations are based on a micromechanical approach, it should be stressed that the resulting equations are volume averaged to produce overall effective constitutive relations which relate the bulk, volume averaged, stress increment to the bulk, volume averaged, strain increment. As such, they are macromodels which can be used directly in nonlinear finite element programs such as MARC, ANSYS and ABAQUS or in boundary element programs such as BEST3D. In developing the volume averaged or efective macromodels from the micromechanical models, both approaches will require the evaluation of volume integrals containing the spatially varying strain distributions throughout the composite material. By assuming that the strain distributions are spatially constant within each constituent phase-or within a given subvolume within each constituent phase-of the composite material, the volume integrals can be obtained in closed form. This simplified micromodel can then be volume averaged to obtain an effective macromodel suitable for use in the MARC, ANSYS and ABAQUS nonlinear finite element programs via user constitutive subroutines such as HYPELA and CMUSER. This effective macromodel can be used in a nonlinear finite element structural analysis to obtain the strain-temperature history at those points in the structure where thermomechanical cracking and damage are expected to occur, the so called damage critical points of the structure.

Walker, Kevin P.↗
NASA NTRSDate not supplied

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗
NASA NTRSDate not supplied

TPSAS-NF1676L-16833-DND

Semantic Infrastructure is central to realizing the first goal of the ASDC's Strategic Plan: expanding the ASDC's customer base by improving access to ASDC data. ASDC data comprises a widely heterogeneous set of complex products which presents two significant challenges in data access: Helping customers discover, among many available options, the most suitable data products for their purpose; and Guiding customers to easily and appropriately use products. Data products differ significantly in terms of how the data was collected and processed, even with similar subject matter. Understanding differences is critical to using data effectively. To reach a broader customer range, the ASDC must provide prospective users with enough information to quickly and meaningfully compare and evaluate data products. Data formats and structures also differ among products. Applications displaying and analyzing data need access to federated and semantically disambiguated data. Semantic technologies offer functionality for addressing this issue. Ontologies can provide robust, stable domain models serving as common schema for discovering, evaluating, comparing, and integrating data from disparate products. Reasoning engines and triple stores can leverage ontologies to support intelligent search applications allowing users to discover, query, retrieve, and easily reformat data from a broad spectrum of sources.

Beth Huffer↗
NASA NTRS2018

BioSentinel: Optimizing Growth Conditions for Improved Yeast Cell Viability After Long-Term Desiccation

NASA's BioSentinel mission is one of thirteen secondary payloads to be deployed on the Space Launch System Exploration Mission-1 (SLS EM-1). The BioSentinel nanosatellite will be sent into a heliocentric orbit beyond Low Earth Orbit (LEO), to study the effects of deep space radiation on the budding yeast, Saccharomyces cerevisiae. Ionizing radiation encountered in deep space can create damaging lesions in DNA, including double strand breaks (DSBs). Budding yeast is suitable as a biological model to study these effects, as it is eukaryotic, and can be desiccated for prolonged periods while retaining viability, thus serving as a robust analog for human cells. On the ground, yeast cells are grown in liquid medium, then loaded into the wells of microfluidic cards and air dried prior to integration into the payload. Once the spacecraft reaches its target heliocentric orbit, a mixture of growth medium and metabolic indicator dye will be pumped into the microwells at specific time points to rehydrate the cells and allow them to grow. A 3-color LED detection system will measure changes in growth and metabolism resulting from ionizing radiation exposure. BioSentinel contains a wild type control strain and a rad51 mutant that is defective for DNA damage repair. In this study, we will determine the optimal amount of time to grow diploid yeast cells in liquid culture before they are desiccated for space flight. After an extended time in stationary phase, they become more tolerant to desiccation due to stress caused by nitrogen starvation. However, excessive exposure can lead to loss of viability and to a heterogeneous cell population due to sporulation. Since viability loss during desiccation poses a risk to mission success, a stress preconditioning process during initial growth may increase long-term cell viability. To determine the growth period that improves desiccation tolerance but allows for retention of uniform radiation sensitivity, we will grow both strains in liquid medium for a varying number of days (4 to 7), desiccate the cells, and then observe changes to cell viability and ionizing radiation sensitivity over time. Supported by the Space Life Sciences Training Program at NASA Ames Research Center.

Cui, Kaixin↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
NASA NTRS2004

Magnetohydrodynamic Convection in the Outer Core and its Geodynamic Consequences

The Earth's fluid outer core is in vigorous convection through much of the Earth's history. In addition to generating and maintaining Earth s time-varying magnetic field (geodynamo), the core convection also generates mass redistribution in the core and a dynamical pressure field on the core-mantle boundary (CMB). All these shall result in various core-mantle interactions, and contribute to surface geodynamic observables. For example, electromagnetic core-mantle coupling arises from finite electrically conducting lower mantle; gravitational interaction occurs between the cores and the heterogeneous mantle; mechanical coupling may also occur when the CMB topography is aspherical. Besides changing the mantle rotation via the coupling torques, the mass-redistribution in the core shall produce a spatial-temporal gravity anomaly. Numerical modeling of the core dynamical processes contributes in several geophysical disciplines. It helps explain the physical causes of surface geodynamic observables via space geodetic techniques and other means, e.g. Earth's rotation variation on decadal time scales, and secular time-variable gravity. Conversely, identification of the sources of the observables can provide additional insights on the dynamics of the fluid core, leading to better constraints on the physics in the numerical modeling. In the past few years, our core dynamics modeling efforts, with respect to our MoSST model, have made significant progress in understanding individual geophysical consequences. However, integrated studies are desirable, not only because of more mature numerical core dynamics models, but also because of inter-correlation among the geophysical phenomena, e.g. mass redistribution in the outer core produces not only time-variable gravity, but also gravitational core-mantle coupling and thus the Earth's rotation variation. They are expected to further facilitate multidisciplinary studies of core dynamics and interactions of the core with other components of the Earth.

Kuang, Weijia↗
NASA NTRS2003

Mapping a Better Vintage

Vineyards such as those located in California's Napa Valley tend to be subdivided into relatively large fields or blocks that often encompass heterogeneous physical conditions. Since growers typically treat the entire block as a single minimum management unit for cultivation and harvest, mapping and monitoring the variability within a block is a concern. Over the last decade, an increasing number of vineyard managers have utilized digital remote sensing and geographic information systems (GIS) to visualize the variability within their blocks. With computer software designed to overlay remotely sensed imagery with environmental and agronomic geographic data on a map, GIS helps growers recognize and explain patterns that might not have been obvious otherwise. GIS can also serve as a valuable archiving mechanism for future reference. To further develop the use of image technology and GIS for vineyard management support, NASA's Earth Science Enterprise partnered with the U.S. wine and commercial remote sensing industries for a project known as the Viticultural Integration of NASA Technologies for Assessment of the Grapevine Environment (VINTAGE). With project investigators from NASA's Ames Research Center, the California State University at Monterey Bay, and the University of Montana, several prototype products have been developed to support agricultural decisions concerning canopy management and irrigation practice. One key VINTAGE aspect involved the evaluation of satellite and airborne multispectral imagery for delineation of sub-block management zones within a vineyard.

Source record↗
NASA NTRS2015

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC↗
NASA NTRS2002

Meteorology, Macrophysics, Microphysics, Microwaves, and Mesoscale Modeling of Mediterranean Mountain Storms: The M8 Laboratory

Comprehensive understanding of the microphysical nature of Mediterranean storms can be accomplished by a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, from synoptic scale down through the mesoscale, the cloud macrophysical scale, and ultimately the cloud microphysical scale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. This involves intense convective development, stratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that affect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. Insofar as hazardous Mediterranean storms, highlighted in this study by three mountain storms producing damaging floods in northern Italy between 1992 and 2000, developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within a storm domain. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting processes. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size disi:ributions, and fall rates of the various modes of hydrometeors found within hazardous storm environments.

Starr, David O.↗
NASA NTRS2009

Tele-Supervised Adaptive Ocean Sensor Fleet

The Tele-supervised Adaptive Ocean Sensor Fleet (TAOSF) is a multi-robot science exploration architecture and system that uses a group of robotic boats (the Ocean-Atmosphere Sensor Integration System, or OASIS) to enable in-situ study of ocean surface and subsurface characteristics and the dynamics of such ocean phenomena as coastal pollutants, oil spills, hurricanes, or harmful algal blooms (HABs). The OASIS boats are extended- deployment, autonomous ocean surface vehicles. The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. One feature of TAOSF is the adaptive re-planning of the activities of the OASIS vessels based on sensor input ( smart sensing) and sensorial coordination among multiple assets. The architecture also incorporates Web-based communications that permit control of the assets over long distances and the sharing of data with remote experts. Autonomous hazard and assistance detection allows the automatic identification of hazards that require human intervention to ensure the safety and integrity of the robotic vehicles, or of science data that require human interpretation and response. Also, the architecture is designed for science analysis of acquired data in order to perform an initial onboard assessment of the presence of specific science signatures of immediate interest. TAOSF integrates and extends five subsystems developed by the participating institutions: Emergent Space Tech - nol ogies, Wallops Flight Facility, NASA s Goddard Space Flight Center (GSFC), Carnegie Mellon University, and Jet Propulsion Laboratory (JPL). The OASIS Autonomous Surface Vehicle (ASV) system, which includes the vessels as well as the land-based control and communications infrastructure developed for them, controls the hardware of each platform (sensors, actuators, etc.), and also provides a low-level waypoint navigation capability. The Multi-Platform Simulation Environment from GSFC is a surrogate for the OASIS ASV system and allows for independent development and testing of higher-level software components. The Platform Communicator acts as a proxy for both actual and simulated platforms. It translates platform-independent messages from the higher control systems to the device-dependent communication protocols. This enables the higher-level control systems to interact identically with heterogeneous actual or simulated platforms.

Lefes, Alberto↗
NASA NTRS2020

Atmospheric Carbon Cycle Dynamics Over the Above Domain: an Integrated Analysis Using Aircraft Observations (Arctic-CA) and Model Simulations (GEOS)

The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project conducted six airborne surveys of Alaska and northwestern Canada between April and November 2017 to capture the spatial and temporal gradients of northern high-latitude carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO) as part of NASA's Arctic-Boreal Vulnerability Experiment (ABoVE). The Arctic-CAP sampling strategy involved acquiring vertical profiles of CO2, CH4 and CO from the surface to 5 km altitude at 25 sites around the ABoVE domain on a 4- to 6-week time interval. We observed vertical gradients of CO2, CH4 and CO that vary by eco-region and duration of the sampling period, which spanned the majority of the seasonal cycle. All Arctic-CAP measurements were compared to a global simulation using the Goddard Earth Observing System (GEOS) modeling system. Comparisons with GEOS simulations of atmospheric CO2, CH4 and CO highlight the potential of these multi-species observations to inform improvements in surface flux estimates and the representation of atmospheric transport. GEOS simulations provide estimates of the near surface average CO2 and CH4 enhancements that are well correlated with aircraft observations (R=0.74 and R=0.60 respectively), suggesting that GEOS has reasonable fidelity over this complex and heterogeneous region. This model-data comparison over the ABoVE domain reveals that while current state-of-the-art models and flux estimates are able to capture broadscale spatial and temporal patterns in near-surface CO2 and CH4 concentrations, more work is needed to resolve fine-scale flux features that are observed. The study also provides a framework for benchmarking a global model at regional scales, which is needed to use climate models as tools to investigate high-latitude carbon-climate feedbacks.

C Sweeney↗
NASA NTRS2009

Using LIDAR and Quickbird Data to Model Plant Production and Quantify Uncertainties Associated with Wetland Detection and Land Cover Generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Cook, Bruce D.↗