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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Color graphics workstations used for simultaneous display of satellite and model data sets

Model-measurement display methods for studying actual or synthetic satellite measurements of cloudiness are developed. Visualization and animation techniques are employed to analyze the data. Two types of animation sequences, one based on Insat IR geosynchronous satellite imagery combined with upper level velocity potentials calculations and isoline depictions of the high amplitude centers of low frequency cloudiness activity, and the other combines a mesoscale cloud model simulation of a severe hail storm and synthetic microwave radiation signatures, are described.

Cooper, Harry J.↗
NASA NTRS2000

A Preliminary Data Model for Orbital Flight Dynamics in Shuttle Mission Control

The Orbital Flight Dynamics group in Shuttle Mission Control is investigating new user interfaces in a project called RIOTS [RIOTS 2000]. Traditionally, the individual functions of hardware and software guide the design of displays, which results in an aggregated, if not integrated interface. The human work system has then been designed and trained to navigate, operate and integrate the processors and displays. The aim of RIOTS is to reduce the cognitive demands of the flight controllers by redesigning the user interface to support the work of the flight controller. This document supports the RIOTS project by defining a preliminary data model for Orbital Flight Dynamics. Section 2 defines an information-centric perspective. An information-centric approach aims to reduce the cognitive workload of the flight controllers by reducing the need for manual integration of information across processors and displays. Section 3 describes the Orbital Flight Dynamics domain. Section 4 defines the preliminary data model for Orbital Flight Dynamics. Section 5 examines the implications of mapping the data model to Orbital Flight Dynamics current information systems. Two recurring patterns are identified in the Orbital Flight Dynamics work the iteration/rework cycle and the decision-making/information integration/mirroring role relationship. Section 6 identifies new requirements on Orbital Flight Dynamics work and makes recommendations based on changing the information environment, changing the implementation of the data model, and changing the two recurring patterns.

ONeill, John↗
NASA NTRS1994

The VIS-AD data model: Integrating metadata and polymorphic display with a scientific programming language

The VIS-AD data model integrates metadata about the precision of values, including missing data indicators and the way that arrays sample continuous functions, with the data objects of a scientific programming language. The data objects of this data model form a lattice, ordered by the precision with which they approximate mathematical objects. We define a similar lattice of displays and study visualization processes as functions from data lattices to display lattices. Such functions can be applied to visualize data objects of all data types and are thus polymorphic.

Hibbard, William L.↗
NASA NTRS2020

NASA Global Satellite and Model Data Products and Services for Tropical Meteorology and Climatology

Satellite remote sensing and model data play an important role in research and applications of tropical meteorology and climatology over vast, data sparse oceans and remote continents. Since the first weather satellite was launched by NASA in 1960, a large collection of NASA's Earth science data is freely available to the research and application communities around the world, significantly improving our overall understanding of the Earth system and environment. Established in the mid-80s, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), located in Maryland, USA, is a data archive center for multidisciplinary, satellite and model assimilation data products. As one of the 12 NASA data centers in Earth Sciences, GES DISC hosts several important NASA satellite missions for tropical meteorology and climatology such as the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) mission and the Modern-Era Retrospective analysis for Research and Applications (MERRA). Over the years, GES DISC has developed data services to facilitate data discovery, access, distribution, analysis and visualization, including Giovanni, an online analysis and visualization tool without the need to download data and software. Despite many efforts for improving data access, still quite a number of challenges remain, such as finding datasets and services for a specific research topic or project, especially for inexperienced users or users outside the remote sensing community. In this article, we list and describe major NASA satellite remote sensing and model datasets and services for tropical meteorology and climatology along with examples of using the data and services, in hope that may help users better utilize the information in their research and applications.

tropical meteorology and climatology, data, servic↗
DOE OSTI2024

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion

Abstract. Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Model data for a watershed-scale study in the Portage River Basin (OH) examining the effects of subsurface drainage on the hydrologic response of an agricultural watershed.

This study builds on Rathore et al. (2024, WRR) and investigates the role of artificial tile-drainage on various aspects of watershed hydrological response, with a particular focus on peakflow. The model-data for the original modeling-focused paper (Rathore et al., 2024, WRR) is archived at Rathore et al. (2024, ESS-DIVE). Hence, this model-data archive provides scripts that are specific to this study that includes model updates, processing and analysis scripts. For details and models files of original model, readers are referred to Rathore et al. (2024, ESS-DIVE). The key difference between the model configuration in this study and Rathore et al. (2024, WRR) is that the tile drains are applied to the entire domain, to study the impact of tile-drains on different aspects of hydrological response. Additional scenario considering intensified precipitation after a dry period was also simulated. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Model data for numerical evaluation of photosensitive tracers as a strategy for separating surface and subsurface transient storage in streams

This model-data archive pertains to a study aimed at the numerical evaluation of the photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively). Separating effects of SSZ and HSZ are important for accurately representing stream function as HSZs and SSZs expose solutes to significantly different biogeochemical conditions. We perform numerical experiments using a multiscale reactive transport model for stream corridors implemented in ATS code, which allows for representing multiple storage zones with their respective travel time distributions and biogeochemistry. For each of the numerical experiment, we provide in this model-data archive python wrapper to drive ATS (forward_model.py), synthetic observation (synthetic_btc.py, BTC_observed.csv), forward model files including ATS input (multiscale_transport.tpl), PFLOTRAN inputs (reactions_channel.tpl, reactions_hz.tpl, reactions_sz.tpl), MCMC (mcmc_run.py), predictive uncertainty (pred_uncert.py, BTCs_simulated_day.csv, BTCs_simulated_night.csv), MCMC outputs (tracer_test_GR.npy, tracer_test_logps.npy, tracer_test_parameters.npy) and Jupyter notebook for post-processing and visualization (post-processing.ipynb). For the denitrification application, ATS input file (denitrification_multisubgrid.tpl), PFLOTRAN input files (denitrification_channel.in, denitrification_hz.in), predictive uncertainty (pred_uncert_denitrification.py, BTCs_simulated_DO.csv, BTCs_simulated_DOC.csv, BTCs_simulated_Nitrate.csv).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Control system design for flexible structures using data models

The dynamics and control of flexible aerospace structures exercises many of the engineering disciplines. In recent years there has been considerable research in the developing and tailoring of control system design techniques for these structures. This problem involves designing a control system for a multi-input, multi-output (MIMO) system that satisfies various performance criteria, such as vibration suppression, disturbance and noise rejection, attitude control and slewing control. Considerable progress has been made and demonstrated in control system design techniques for these structures. The key to designing control systems for these structures that meet stringent performance requirements is an accurate model. It has become apparent that theoretically and finite-element generated models do not provide the needed accuracy; almost all successful demonstrations of control system design techniques have involved using test results for fine-tuning a model or for extracting a model using system ID techniques. This paper describes past and ongoing efforts at Ohio University and NASA MSFC to design controllers using 'data models.' The basic philosophy of this approach is to start with a stabilizing controller and frequency response data that describes the plant; then, iteratively vary the free parameters of the controller so that performance measures become closer to satisfying design specifications. The frequency response data can be either experimentally derived or analytically derived. One 'design-with-data' algorithm presented in this paper is called the Compensator Improvement Program (CIP). The current CIP designs controllers for MIMO systems so that classical gain, phase, and attenuation margins are achieved. The center-piece of the CIP algorithm is the constraint improvement technique which is used to calculate a parameter change vector that guarantees an improvement in all unsatisfied, feasible performance metrics from iteration to iteration. The paper also presents a recently demonstrated CIP-type algorithm, called the Model and Data Oriented Computer-Aided Design System (MADCADS), developed for achieving H(sub infinity) type design specifications using data models. Control system design for the NASA/MSFC Single Structure Control Facility are demonstrated for both CIP and MADCADS. Advantages of design-with-data algorithms over techniques that require analytical plant models are also presented.

Irwin, R. Dennis↗
DOE OSTI2021

Model-Data for Joint Estimation of Biogeochemical Model Parameters from Multiple Experiments: A Bayesian Approach Applied to Mercury Methylation

This modeling archive supports the manuscript submitted for publication in the Environmental Modeling and Software. This study is supported by ORNL-SFA and IDEAS-Watershed. This study aims to improve calibration of complex biogeochemical models using datasets from multiple experiments targeting specific subprocesses. The proposed Bayesian joint-fitting scheme calibrates the entire biogeochemical model in one go using all the available datasets and estimate parameter uncertainties using Markov Chain Monte Carlo (MCMC). This allows for complete propagation of uncertainties and utilization of the information shared between different datasets. Mapping joint distribution of parameters guides model improvement by identifying null spaces in the parameter space. This archive contains files used to perform MCMC, post-process outputs and visualize results.

East Fork Poplar Creek↗
NASA NTRS2005

Fundamentals of Modeling, Data Assimilation, and High-performance Computing

This lecture will introduce the concepts of modeling, data assimilation and high- performance computing as it relates to the study of atmospheric composition. The lecture will work from basic definitions and will strive to provide a framework for thinking about development and application of models and data assimilation systems. It will not provide technical or algorithmic information, leaving that to textbooks, technical reports, and ultimately scientific journals. References to a number of textbooks and papers will be provided as a gateway to the literature.

Rood, Richard B.↗
NASA NTRS1984

Soybean canopy reflectance modeling data sets

Numerous mathematical models of the interaction of radiation with vegetation canopies have been developed over the last two decades. However, data with which to exercise and validate these models are scarce. During three days in the summer of 1980, experiments are conducted with the objective of gaining insight about the effects of solar illumination and view angles on soybean canopy reflectance. In concert with these experiment, extensive measurements of the soybean canopies are obtained. This document is a compilation of the bidirectional reflectance factors, agronomic, characteristics, canopy geometry, and leaf, stem, and pod optical properties of the soybean canopies. These data sets should be suitable for use with most vegetation canopy reflectance models.

Ranson, K. J.↗
NASA NTRS2017

Investigating Access Performance of Long Time Series with Restructured Big Model Data

Data sets generated by models are substantially increasing in volume, due to increases in spatial and temporal resolution, and the number of output variables. Many users wish to download subsetted data in preferred data formats and structures, as it is getting increasingly difficult to handle the original full-size data files. For example, application research users such as those involved with wind or solar energy, or extreme weather events are likely only interested in daily or hourly model data at a single point (or for a small area) for a long time period, and prefer to have the data downloaded in a single file. With native model file structures, such as hourly data from NASA Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2), it may take over 10 hours for the extraction of parameters-of-interest at a single point for 30 years. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is exploring methods to address this particular user need. One approach is to create value-added data by reconstructing the data files. Taking MERRA-2 data as an example, we have tested converting hourly data from one-day-per-file into different data cubes, such as one-month, or one-year. Performance is compared for reading local data files and accessing data through interoperable services, such as OPeNDAP. Results show that, compared to the original file structure, the new data cubes offer much better performance for accessing long time series. We have noticed that performance is associated with the cube size and structure, the compression method, and how the data are accessed. An optimized data cube structure will not only improve data access, but also may enable better online analysis services

reanalysis↗
NASA NTRSDate not supplied

Model-data Comparison of Stratospheric Intrusions Over Hampton, Virginia

Stratospheric intrusions are the transport of ozone from the stratosphere to the troposphere. These intrusions are frequent in spring; they can affect local air quality as well as satellites observations, notably limb sounding instruments such as SAGE III. Complex models such as GEOS-CF are used to assess the magnitude and the impact of SI. We present the model-data comparison of several stratospheric intrusion above Hampton, Virginia, in 2019, using the NASA Langley Mobile Ozone Lidar and the GEOS-CF model. We show the limits of the model-data agreement for these events and suggest a method to correct limb-sounding observations.

G. Gronoff↗
NASA NTRSDate not supplied

Interactive Framework to Support Open Model-Data Validation Efforts at the CCMC

Validation of models using observation data has been a central activity at the Community Coordinated Modeling Center (CCMC) over more than a decade. The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework is a database-driven implementation of the interactive analysis of model-data comparisons that simultaneously provides a view across a multitude of locations and time periods. CAMEL thus extends the single-location or single-trajectory timeseries data comparison capabilities provided by the CCMC online visualization that formed the backbone of initial validation efforts. We demonstrate CAMEL capabilities for an example application to study Neutral Density in the upper atmosphere among comparisons in the heliosphere, the Earth’s radiation belt, magnetosphere, and ionosphere-thermosphere-mesosphere domains.

Lutz Rastaetter↗
NASA NTRS2016

Towards a New Generation of Agricultural System Data, Models and Knowledge Products: Design and Improvement

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

Agricultural systems↗
NASA NTRSDate not supplied

GLDAS-2 Land Surface Model Data and Data Services at NASA GES DISC

The goal of the NASA Global Land Data Assimilation System (GLDAS, https://ldas.gsfc.nasa.gov/gldas(https://ldas.gsfc.nasa.gov/gldas)) is to generate optimal fields of land surface states and fluxes by ingesting satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques (Rodell et al., 2004).The GLDAS dataset currently archived at and distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC, https://disc.gsfc.nasa.gov/ (https://disc.gsfc.nasa.gov/)) is GLDAS Version 2 (GLDAS-2). It contains a series of output fields from the upgraded Noah-3.6, Catchment-F2.5, and VIC-4.1.2 Land Surface Models (LSMs) in the Land Information System (LIS-V7, https://lis.gsfc.nasa.gov/ (https://lis.gsfc.nasa.gov/)). GLDAS-2 has three components:GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the upgraded Princeton Meteorological ForcingV2.2 Dataset and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data, with data spanning from 2000 to the present. The GLDAS-2.2 product suite uses data assimilation(DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, varies for different GLDAS-2.2 products. The currently availableGLDAS-2.2 data contain a daily 0.25-degree output from the Catchment-F2.5 LSM in LIS-V7. The data are forced with the meteorological analysis fields from the operational European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) and assimilated with GRACE and GRACE-FO data, ranging from February 1, 2003 to the present. The current GLDAS-2.0 and 2.1 Noah LSM data were reprocessed in November 2019 and January 2020 respectively and their data from Catchment and VIC LSMs are new to the GLDAS-2 collection. This presentation provides a summary of theGLDAS-2 data products, their land surface fields, and their related data services at the GES DISC; and a description of the majorGLDAS-2 climatological characteristics as well as the intercomparison with the data of the previous version.

Hydrology↗
NASA NTRS2007

Eastern U.S. Continental Shelf Carbon Budget: Integrating Models,Data Assimilation, and Analysis

The U.S. East Coast Continental Shelf (USECoS) project was initiated in 2004 with the overall goal of developing carbon budgets for Mid-Atlantic and South Atlantic regions of the eastern U.S. coast. We addressed this goal through a series of specific research questions that were designed to understand carbon inputs and fates in the two regions, dominant food web pathways for carbon cycling, and similarities/differences in carbon cycling in the two continental shelf systems. The USECoS project represents a major effort to simultaneously synthesize and integrate diverse data sets, field measurements, models, and modeling approaches. We expect that the type of approach taken here will result in more insight than would be possible if each component of the program moved forward independently. The primary significance of this project is in providing a strong quantitative basis for the development of future observational and modeling studies of carbon budgets of continental shelf systems. A strong aspect of the USECoS project is the integration of modeling and extensive physical, chemical, and biological data sets, which provides an opportunity for modeling and data analyses to inform one another from the outset. This research is particularly germane to NASA's carbon cycle research focus and coastal research initiative and the U.S. Climate Change Research Program, all of which support the goals of the North American Carbon Program. We highlight primary approaches that have been used, and some of the challenges and results that have come from interactions among our team of investigators. The global scale and interdisciplinary nature of the science questions that we now face in Earth Science are such that integrated teams of investigators are needed to address them.

Hofmann, Eileen↗