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At least 721 records · Page 40

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

Here, large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model–data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO 2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The assimilation of atmospheric CO 2 , using the general circulation model (GCM) of the Laboratoire de Météorologie Dynamique (LMDz; step 3), provides an overall constraint (i.e., constraint on large-scale net CO 2 fluxes), resulting in an improvement of the fit to the observed atmospheric CO 2 growth rate. Thus, the optimized model predicts a land C (carbon) sink of around 2.2 PgC yr -1 (for the 2000–2009 period), which is more compatible with current estimates from the Global Carbon Project (GCP) than the prior value. The consistency of the stepwise approach is evaluated with back-compatibility checks. The final optimized model (after step 3) does not significantly degrade the fit to MODIS-NDVI and FLUXNET data that were assimilated in the first two steps, suggesting that a stepwise approach can be used instead of the more “challenging” implementation of a simultaneous optimization in which all data streams are assimilated together. Most parameters, including the scalar of the initial soil carbon pool size, changed during the optimization with a large error reduction. This work opens new perspectives for better predictions of the land carbon budgets.

58 GEOSCIENCES↗

'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elements of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.

Big Data↗

Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems

Subsurface applications, including geothermal, geological carbon sequestration, and oil and gas, typically involve maximizing either the extraction of energy or the storage of fluids. Fractures form the main pathways for flow in these systems, and locating these fractures is critical for predicting flow. However, fracture characterization is a highly uncertain process, and data from multiple sources, such as flow and geophysical are needed to reduce this uncertainty. We present a nonintrusive, sequential inversion framework for integrating data from geophysical and flow sources to constrain fracture networks in the subsurface. In this framework, we first estimate bounds on the statistics for the fracture orientations using microseismic data. These bounds are estimated through a combination of a focal mechanism (physics-based approach) and clustering analysis (statistical approach) of seismic data. Then, the fracture lengths are constrained using flow data. In conclusion, the efficacy of this inversion is demonstrated through a representative example.

97 MATHEMATICS AND COMPUTING↗

Advanced Computing Annual Report 2022

National Renewable Energy Laboratory's (NREL) high-performance computing (HPC), efficient data center operation, and state-of-the-art data visualization powered over 300 clean energy projects in Fiscal Year 2022 (FY22). 555 scientists and engineers utilized HPC resources to assess and integrate data into their research. The report highlights the arrival of new HPC Kestrel in 2023, the contributions of the Insight Center, and researchers looking into bias in artificial intelligence, alongside key research collaborations using advanced computing.

advanced computing↗

IMG/M 4 version of the integrated metagenome comparative analysis system

IMG/M (http://img.jgi.doe.gov/m) provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in the context of a comprehensive set of reference genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG/M’s data content and analytical tools have expanded continuously since its first version was released in 2007. Since the last report published in the 2012 NAR Database Issue, IMG/M’s database architecture, annotation and data integration pipelines and analysis tools have been extended to cope with the rapid growth in the number and size of metagenome data sets handled by the system. IMG/M data marts provide support for the analysis of publicly available genomes, expert review of metagenome annotations (IMG/M ER: http://img.jgi.doe.gov/mer) and Human Microbiome Project (HMP)-specific metagenome samples (IMG/M HMP: http://img.jgi.doe.gov/ imgm_hmp).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Observed State of the Water Cycle in the Early Twenty-First Century

This study quantifies mean annual and monthly fluxes of Earth's water cycle over continents and ocean basins during the first decade of the millennium. To the extent possible, the flux estimates are based on satellite measurements first and data-integrating models second. A careful accounting of uncertainty in the estimates is included. It is applied within a routine that enforces multiple water and energy budget constraints simultaneously in a variational framework in order to produce objectively determined optimized flux estimates. In the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are negligible. Fluxes were poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian islands, leading to reliance on atmospheric analysis estimates. Many of the satellite systems that contributed data have been or will soon be lost or replaced. Models that integrate ground-based and remote observations will be critical for ameliorating gaps and discontinuities in the data records caused by these transitions. Continued development of such models is essential for maximizing the value of the observations. Next-generation observing systems are the best hope for significantly improving global water budget accounting.

Numerical analysis/modeling↗

An integrative computational approach for prioritization of genomic variants

An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.

59 BASIC BIOLOGICAL SCIENCES↗

Cybersecurity Standards for Distributed Energy Resources: Gaps and Harmonization Strategy

This report examines cybersecurity standards for Distributed Energy Resources (DERs) in light of their rapid growth and increasing integration into energy systems. It identifies critical gaps in existing frameworks, including inadequate coverage of DER-specific challenges, complexities in implementing comprehensive standards, integration issues with legacy systems, adoption hurdles for newer standards, and a lack of harmonization across regulatory landscapes. The analysis highlights vulnerabilities such as data integrity risks, unauthorized device control, and denial-of-service attacks across various DER technologies like solar PV, wind turbines, energy storage systems, and hydrogen fuel cells. The report proposes a harmonization strategy to address these deficiencies by developing unified cybersecurity requirements, certification programs, and training resources while fostering collaboration among stakeholders such as government agencies, industry groups, DER operators, manufacturers, and research institutions. A phased roadmap is outlined to refine and implement these measures through pilot testing and widespread adoption. Ultimately, the report underscores the urgent need for coordinated efforts to enhance DER cybersecurity and ensure the reliable operation of future energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Mark 3 data base handler

A data base handler which would act to tie Mark 3 system programs together is discussed. The data base handler is written in FORTRAN and is implemented on the Hewlett-Packard 21MX and the IBM 360/91. The system design objectives were to (1) provide for an easily specified method of data interchange among programs, (2) provide for a high level of data integrity, (3) accommodate changing requirments, (4) promote program accountability, (5) provide a single source of program constants, and (6) provide a central point for data archiving. The system consists of two distinct parts: a set of files existing on disk packs and tapes; and a set of utility subroutines which allow users to access the information in these files. Users never directly read or write the files and need not know the details of how the data are formatted in the files. To the users, the storage medium is format free. A user does need to know something about the sequencing of his data in the files but nothing about data in which he has no interest.

Ryan, J. W.↗

A software architecture for multidisciplinary applications: Integrating task and data parallelism

Data parallel languages such as Vienna Fortran and HPF can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are of a multidisciplinary and heterogeneous nature and thus do not fit well into the data parallel paradigm. In this paper we present new Fortran 90 language extensions to fill this gap. Tasks can be spawned as asynchronous activities in a homogeneous or heterogeneous computing environment; they interact by sharing access to Shared Data Abstractions (SDA's). SDA's are an extension of Fortran 90 modules, representing a pool of common data, together with a set of Methods for controlled access to these data and a mechanism for providing persistent storage. Our language supports the integration of data and task parallelism as well as nested task parallelism and thus can be used to express multidisciplinary applications in a natural and efficient way.

Chapman, Barbara↗

International Space Station (ISS) Anomalies Trending Study: Appendices - Volume II

The NASA Engineering and Safety Center (NESC) set out to utilize data mining and trending techniques to review the anomaly history of the International Space Station (ISS) and provide tools for discipline experts not involved with the ISS Program to search anomaly data to aid in identification of areas that may warrant further investigation. Additionally, the assessment team aimed to develop an approach and skillset for integrating data sets, with the intent of providing an enriched data set for discipline experts to investigate that is easier to navigate, particularly in light of ISS aging and the plan to extend its life into the late 2020s. This document contains the Appendices to the Volume I report.

Beil, Robert J.↗

International Space Station (ISS) Anomalies Trending Study

The NASA Engineering and Safety Center (NESC) set out to utilize data mining and trending techniques to review the anomaly history of the International Space Station (ISS) and provide tools for discipline experts not involved with the ISS Program to search anomaly data to aid in identification of areas that may warrant further investigation. Additionally, the assessment team aimed to develop an approach and skillset for integrating data sets, with the intent of providing an enriched data set for discipline experts to investigate that is easier to navigate, particularly in light of ISS aging and the plan to extend its life into the late 2020s. This report contains the outcome of the NESC Assessment.

Beil, Robert J.↗

Tropospheric Ozone Source Attribution in Southern California during Summer 2014 Based on Lidar Measurements and Model Simulations

In the past decades, significant efforts have been made to increase tropospheric ozone long-term monitoring. A large number of ground-based, airborne and space-borne instruments are currently providing valuable data to contribute to better understand tropospheric ozone budget and variability. Nonetheless, most of these instruments provide in-situ surface and column-integrated data, whereas vertically resolved measurements are still scarce. Besides ozonesondes and aircraft, lidar measurements have proven to be valuable tropospheric ozone profilers. Using the measurements from the tropospheric ozone differential absorption lidar (DIAL) located at the JPL Table Mountain Facility, California, and the GEOS-Chem and GEOS-5 model outputs, the impact of the North American monsoon on tropospheric ozone during summer 2014 is investigated. The influence of the Monsoon lightning-induced NOx will be evaluated against other sources (e.g. local anthropogenic emissions and the stratosphere) using also complementary data such as backward-trajectories analysis, coincident water vapor lidar measurements, and surface ozone in-situ measurements.

Lidar↗

Analyzing the Effects of Climate and Thermal Configuration on Community Energy Storage Systems (Presentation)

Community energy storage (CES) has been proposed to mitigate the high variation in output from renewable sources and reduce peak load on the electrical grid. Thousands of these systems may be distributed around the grid to provide benefits to local distribution circuits and to the grid as a whole when aggregated. CES must be low cost to purchase and install and also largely maintenance free through more than 10 years of service life to be acceptable to most utilities.Achieving the required system life time is a major uncertainty for lithium-ion batteries. The lifetime and immediate system performance of batteries can change drastically with battery temperature, which is a strong function of system packaging, local climate, electrical duty cycle, and other factors. In other Li-ion applications, this problem is solved via air or liquid heating and cooling systems that may need occasional maintenance throughout their service life. CES requires a maintenance-free thermal management system providing protection from environmental conditions while rejecting heat from a moderate electrical duty cycle. Thus, the development of an effective, low-cost, zero-maintenance thermal management system poses a challenge critical to the success of CES. NREL and Southern California Edison have collaborated to evaluate the long-term effectiveness of various CES thermal configurations in multiple climates by building a model of CES based on collected test data, integrating it with an NREL-developed Li-ion degradation model, and applying CES electrical duty cycles and historic location-specific meteorological data to forecast battery thermal response and degradation through a 10-year service life.

25 ENERGY STORAGE↗

NASA's Research & Development in Airspace Management for Drones, Air Taxis, and Beyond

Today's National Airspace System is extremely safe. Multiple people and organizations are involved in the handling of flights at all phases. We are, however, at the dawn of a new era in aviation where new entrants are emerging from multiple domains. These new entrants will need to be integrated into the airspace safely and given the flexibility to scale. With that integration and flexibility comes the need and responsibility to develop concepts and systems that will work with the regulatory and operational needs of the Federal Aviation Administration while accounting for the needs of industry. NASA is at the leading edge of research, development, and testing across multiple domains to enable the realization of new entrants such as drones, air cargo and taxis, and high altitude vehicles. Addressing the potential for public good coming from these new capabilities is also a NASA focus area. While there has been considerable effort in the engineering aspects of this research, another thrust that is of importance is that of data integration and visualization. With respect to visualization, NASA Ames Research Center has been leading the advancement in data visualization for these new domains and has spent considerable efforts in the exploration of incorporating Augmented and Mixed Reality as a situation awareness platform. This presentation will outline the new developments in airspace integration and tie in NASA's efforts in visualizing the associated operational data.

airspace management↗

Utilization of wind tunnel instrumentation with software verifications

Software tools developed for the National Full-Scale Aerodynamic Complex (NFAC) for verifying data integrity and troublehooting problems are discussed. The Hardware Check verifies that the incoming signals are properly connected and are being acquired into the real time data system. The Zero/Cal Check program verifies the reliability of the wind tunnel instrumentation by checking the zero and calibration points. The Power Spectral Density Plots help to identify the frequency components of a signal. Drift Program and Thermal Plots tools are also described.

Silva, Betty W.↗

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↗