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Results for “Climate Science Visualization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Final Report: Modeling coupled ice sheet-ocean interactions in the Model for Prediction Across Scales (MPAS) and in DOE Earth System Models

Ice sheet-ocean interactions are involved in a potential climate tipping point in the climate system. Weakening of dynamical ocean barriers that currently hold warmer waters off the Antarctic continental shelf could lead to warming under Antarctica’s largest ice shelves, causing as much as a hundredfold increase in sub-ice-shelf melting. Increased ice-sheet melting could trigger dynamical instabilities in the ice sheet itself if sufficient buttressing from ice shelves is lost. This project developed and tested several modeling capabilities needed to investigate these phenomena. In collaboration with a number of international groups, notably the climate modeling group at Los Alamos National Laboratory (LANL), the following capabilities were added to the Energy Exascale Earth System Model (E3SM) and its ocean component (the Model for Prediction Across Scales Ocean, MPAS-Ocean): 1) a new vertical coordinate appropriate for ice-shelf cavities; 2) an initialization procedure appropriate for damping waves from imbalances in ocean pressure and that of the overlying ice shelf; 3) A suite of idealized test cases related to ice shelf-ocean interactions; 4) A set of diagnostics for tracking freshwater fluxes and heat budgets from ice-shelf melting; 5) infrastructure for computing ice sheet-ocean fluxes in the E3SM coupler; and 6) A set of analysis and visualization tools for E3SM ocean and sea-ice validation with a particular focus on Antarctic and Southern Ocean climate. Additionally, the project included participation and leadership in a number of international model intercomparison projects (MIPs). Most notably, the PI was a co-chair of the Marine Ice Sheet-Ocean Model Intercomparison Project (MISOMIP), designing the experiment, coordinating participation in the MIP and performing the bulk of the analysis. Although the project was cut short when the PI accepted a staff scientist position at LANL, the project played a role in seven publications and has segued smoothly into ongoing Department of Energy projects in the “ecosystem” surrounding E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Whole plant traits of coastal dune vegetation and implications for interactions with dune dynamics

Abstract Coastal dunes are important protective features against sea level rise and coastal storms. Interactions between dune plant aboveground structures and sediment trapping that allow for dune building and maintenance are well established. More recently, studies documenting belowground biomass for promoting erosion resistance in dominant dune species have been conducted, yet a knowledge gap remains regarding species‐specific characterization of whole plants, specifically with respect to roots, rhizomes, and belowground stems. Our objective was to quantify above‐ and belowground traits of four dominant dune grasses to document the potential for species‐specific effects on dune growth, maintenance, and erosion resistance. We examined above‐ and belowground traits among four prominent dune grasses of the Atlantic and Gulf Coasts of North America: Ammophila breviligulata , Panicum amarum , Spartina patens , and Uniola paniculata . Whole plant samples of each species were collected from the foredune at the US Army Engineer Research and Development Center's Field Research Facility in Duck, North Carolina, USA, and quantified for several above‐ and belowground traits (e.g., stem height, rhizome number and length, root surface area by diameter class, root tensile strength, and mycorrhizal percent infection). Belowground factors known to impact important dune processes, such as rhizome length, mycorrhizal percent infection, and root traits, differed substantially among species. When visualized in multivariate space, all species significantly differed in suites of above‐ and belowground traits. When considering belowground only, Ammophila and Spartina were similar, despite differences in biomass allocation. Species separated along axes related to mycorrhizal association, biomass allocation, and root construction. The four co‐occurring dune grass species were dissimilar in suites of plant traits. Belowground trait differences were driven by those describing root construction, biomass allocation, and mycorrhizal infection. Dissimilarity in above‐ and belowground suites of traits may demonstrate different approaches for surviving the dune environment. Incorporating belowground traits into modeling will enhance predictions of dune response to climate change through interactions between vegetation and dune dynamics that facilitate coastal resistance and resilience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Establishment of the Northeast Coastal Watershed Geospatial Data Network (NECWGDN)

The goals of NECWGDN were to establish integrated geospatial databases that interfaced with existing open-source (water.html) environmental data server technologies (e.g., HydroDesktop) and included ecological and human data to enable evaluation, prediction, and adaptation in coastal environments to climate- and human-induced threats to the coastal marine resources within the Gulf of Maine. We have completed the development and testing of a "test bed" architecture that is compatible with HydroDesktop and have identified key metadata structures that will enable seamless integration and delivery of environmental, ecological, and human data as well as models to predict threats to end-users. Uniquely this database integrates point as well as model data and so offers capacities to end-users that are unique among databases. Future efforts will focus on the development of integrated environmental-human dimension models that can serve, in near real time, visualizations of threats to coastal resources and habitats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The ParFlow Sandtank: An interactive educational tool making invisible groundwater visible

Physical aquifer models are a highly effective teaching tool for hydrology education, however they come with inherent limitations that include the high cost to purchase, the static configuration of the model materials, the time required to visualize hydrogeological phenomena, and the effort to reset and clean them over time. To address these and other limitations, we have developed an interactive computer simulation of a physical aquifer model called the ParFlow Sandtank. In this gamified interface, users run the simulation using a familiar web-app like interface with sliders and buttons while learning real hydrologic concepts. Our user interface allows participants to dive into the world of hydrology, understanding assumptions about model parameters such as hydraulic conductivity, making decisions about inputs to groundwater aquifer systems such as pumping rates, visualizing outputs such as stream flow, transport, and saturation, and exploring various factors that impact real environmental systems such as climate change. The ParFlow Sandtank has already been used in a variety of educational settings with more than 9,000 users per year, and we feel this emerging educational tool can be used broadly in educational environments and can be scaled-up to provide greater accessibility for students and educators. Here we present the capabilities and workflow of the ParFlow Sandtank, two use cases, and additional tools and custom templates that have been developed to support and enhance the reach of the ParFlow Sandtank.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Indexing Permafrost Soil Organic Matter Degradation Using High-Resolution Mass Spectrometry

Microbial degradation of soil organic matter (SOM) is a key process for terrestrial carbon cycling, although the molecular details of these transformations remain unclear. This study reports the application of ultrahigh resolution mass spectrometry to profile the molecular composition of SOM and its degradation during a simulated warming experiment. A soil sample, collected near Barrow, Alaska, USA, was subjected to a 40-day incubation under anoxic conditions and analyzed before and after the incubation to determine changes of SOM composition. A CHO index based on molecular C, H, and O data was utilized to codify SOM components according to their observed degradation potentials. Compounds with a CHO index score between –1 and 0 in a water-soluble fraction (WSF) demonstrated high degradation potential, with a highest shift of CHO index occurred in the N-containing group of compounds, while similar stoichiometries in a base-soluble fraction (BSF) did not. Additionally, compared with the classical H:C vs O:C van Krevelen diagram, CHO index allowed for direct visualization of the distribution of heteroatoms such as N in the identified SOM compounds. We demonstrate that CHO index is useful not only in characterizing arctic SOM at the molecular level but also enabling quantitative description of SOM degradation, thereby facilitating incorporation of the high resolution MS datasets to future mechanistic models of SOM degradation and prediction of greenhouse gas emissions.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2019

Toward Calibrated Language for Effectively Communicating the Results of Extreme Event Attribution Studies

Extreme event attribution studies attempt to quantify the role of human influences in observed weather and climate extremes. These studies are of broad scientific and public interest, although quantitative results (e.g., that a specific event was made a specific number of times more likely because of anthropogenic forcings) can be difficult to communicate accurately to a variety of audiences and difficult for audiences to interpret. Here, we focus on how results of these studies can be effectively communicated using standardized language and propose, for the first time, a set of calibrated terms to describe event attribution results. Using these terms and an accompanying visual guide, results are presented in terms of likelihood of event changes and the associated uncertainties. This standardized language will allow clearer communication and interpretation of probabilities by the public and stakeholders.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

ParNCL and ParGAL: Data-parallel Tools for Postprocessing of Large-scale Earth Science Data

Earth science high-performance applications often require extensive analysis of their output in order to complete the scien- tific goals or produce a visual image or animation. Often this analysis cannot be done in situ because it requires calculating time-series statistics from state sampled over the entire length of the run or analyzing the relationship between similar time series from previous simulations or observations. Many of the tools used for this postprocessing are not themselves high- performance applications, but the new Parallel Gridded Analysis Library (ParGAL) provides high-performance data-parallel versions of several common analysis algorithms for data from a structured or unstructured grid simulation. The library builds on several scalable systems, including the Mesh Oriented DataBase (MOAB), a library for representing mesh data that sup- ports structured, unstructured finite element, and polyhedral grids; the Parallel-NetCDF (PNetCDF) library; and Intrepid, an extensible library for computing operators (such as gradient, curl, and divergence) acting on discretized fields. We have used ParGAL to implement a parallel version of the NCAR Command Language (NCL) a scripting language widely used in the climate community for analysis and visualization. The data-parallel algorithms in ParGAL/ParNCL are both higher performing and more flexible than their serial counterparts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Metrics for evaluating tropical cyclones in climate data

This manuscript describes a software suite that can be used for objective evaluation of tropical cyclones (TCs) in gridded climate data. Using cyclone trajectories derived from 6-hourly data, a comprehensive set of metrics is defined to systematically compare and contrast products to one another. In addition to annual TC climatologies, attention is paid to spatial and temporal patterns of storm occurrence and intensity. Assessment can be performed either on the global scale or regional domains. Simple to visualize ‘scorecards’ allow for rapid credibility assessment. We showcase three key findings enabled by this suite. First, we compare the representation of TCs in seven current-generation global reanalyses and conclude that higher resolution models and those with TC-specific assimilation contain more accurate storm climatologies. Second, using a free-running Earth system model (ESM) we find that full basin refinement is required in variable-resolution configurations to adequately simulate North Atlantic TC frequency. Furthermore, upstream refinement over northern Africa offers little benefit in simulating storm occurrence but spatial genesis patterns are improved. Finally, we show that TCs simulated by ESMs can be highly sensitive to individual parameterizations in climate models, with North Atlantic TC metrics varying greatly depending on version of the Morrison-Gettelman microphysics package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

New framework for benchmarking decadal predictions leveraging the PCMDI Metric Package with interactive visualization

Reliable climate predictions across multiple timescales are increasingly critical as climate-related risks continue to rise. With the growing number and diversity of climate prediction systems, systematic intercomparison has become essential. Here, we present a comprehensive evaluation framework based on the PCMDI Metric Package to assess the performance of multiple decadal climate prediction systems. Unlike uninitialized simulations, initialized predictions exhibit bias and predictive skill that evolve with forecast lead time. To address this, we introduce (1) model-by-lead-time portrait plots, which efficiently summarize metrics of global temperature, precipitation, and Arctic/Antarctic sea-ice extent, and (2) an HTML-based interactive visualization platform that provides detailed regional and seasonal diagnostics of model bias, skill scores, and ensemble spread for each model and lead time. Comparisons with uninitialized simulations further quantify the relative impacts of initialization and external forcing on prediction skill. The proposed framework provides a scalable and transparent approach for multi-model climate prediction assessments and can be readily extended to a wide range of operational and research forecasting systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Degradation Analysis of Field-Exposed Photovoltaic Modules with Non-Fluoropolymer-Based Backsheets

The selection of polymeric materials utilized in photovoltaic (PV) modules has changed relatively little since the inception of the PV industry, with ethylene-vinyl acetate (EVA), polyethylene terephthalate (PET), and fluoropolymer-based laminates being the most widely adopted primary components of the encapsulant and backsheet materials. The backsheet must serve to electrically insulate the solar cells and protect them from the effects of weathering. Due to continued downward pressure on cost, other polymeric materials are being formulated to withstand outdoor exposure for use in backsheets to replace either the PET film, the fluoropoymer film, or both. Because of their relatively recent deployment, less is known about their reliability and if they are durable enough to fulfill the greater than or equal to 25 year warranties of current PV modules. This work presents a degradation analysis of field-exposed modules with polyamide- and polyester-based backsheets. Modules were exposed for up to five years in different geographic locations: USA (Maryland, Ohio), China, and Italy. Surface and cross-sectional analysis included visual inspection, colorimetry, glossimetry, and Fourier-transform infrared spectroscopy. Each module experienced different types of degradation depending on the exposure site, even for the same material and module brand. For instance, the polyamide-based backsheet experienced hairline cracking and greater yellowing and chemical changes in China (Changsu, humid subtropical climate), while in Italy (Rome, hot-summer Mediterranean climate) it underwent macroscopic cracking and greater losses in gloss. Spectroscopic studies have permitted identification of degradation products and changes in polymer structure over time. Comparisons are made to fielded modules with fluoropolymer-based backsheets, as well as backsheet materials in accelerated laboratory exposures. Implications for qualification testing and service life prediction of the non-fluoropolymer-based backsheets are discussed.

14 SOLAR ENERGY↗
DOE OSTI2016

Daylight performance of a microstructured prismatic window film in deep open plan offices

Daylight redirecting systems with vertical windows have the potential to offset lighting energy use in deep perimeter zones. Here, a microstructured prismatic film designed for such use was characterized using goniophotometric measurements and ray tracing simulations. The synthetically-generated bidirectional scattering distribution function (BSDF) data were shown to have good agreement with limited measured data for normal incident angles (0–60°). Measured data indicated that the prismatic film was most efficient when vertical angles of incidence were between 18 and 35° and within ±45° of normal incidence to the plane of the window so maximum energy savings across the full depth of the zone occurred over the equinox to winter solstice period. Annual lighting energy use and visual comfort in a deep open plan office zone were evaluated using the Radiance three-phase method in several climates and for south and east-facing window orientations. Lighting energy savings were 39–43% for a 12 m (40 ft) deep south-facing perimeter zone compared to the same zone with no lighting controls. The prismatic film with and without a diffuser controlled glare for views parallel to the window but produced glare for seated viewpoints looking toward the window. At mature market costs, the system was projected to have a simple payback of 2–6 years. Technical challenges encountered throughout the evaluation led to improvements in measurement and modeling tools and stressed the importance of having accurate input data for product development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Structures of methane and ammonia monooxygenases in native membranes

Methane- and ammonia-oxidizing bacteria play key roles in the global carbon and nitrogen cycles, respectively. These bacteria use homologous copper membrane monooxygenases to accomplish the defining chemical transformations of their metabolisms: the oxidations of methane to methanol by particulate methane monooxygenase (pMMO) and ammonia to hydroxylamine by ammonia monooxygenase (AMO), enzymes of prime interest for applications in mitigating climate change. However, investigations of these enzymes have been hindered by the need for disruptive detergent solubilization prior to structure determination, confounding studies of pMMO and precluding studies of AMO. Here, we overcome these challenges by using cryoEM to visualize pMMO and AMO directly in their native membrane arrays at 2.4 to 2.8 Å resolution. These structures reveal details of the copper centers, numerous bound lipids, and previously unobserved components, including identifiable and distinct supernumerary helices interacting with pMMO and AMO, suggesting a widespread role for these helices in copper membrane monooxygenases. Comparisons between these structures, their metallocofactors, and their unexpected protein–protein interactions highlight features that may govern activity or the formation of higher-order arrays in native membranes. The ability to obtain molecular insights within the native membrane will enable further understanding of these environmentally important enzymes.

Science & Technology - Other Topics↗
DOE OSTI2019

Hurricane Harvey Flood

Online supplement to Attributable human-induced changes in the magnitude of flooding in the Houston, Texas region during Hurricane Harvey, by Michael Wehner and Christopher Sampson. Geospatial data to visualize the attributable flooding in the greater Houston during Hurricane Harvey as simulated by the Fathom hydraulical model in a geotiff file format is provided at https://portal.nersc.gov/cascade/Harvey/ . The public is encouraged to download this open access data and investigate their own neighborhoods of interest using free or commercial software. A detailed validation of the baseline simulated "flood that was" for every neighborhood is outside the scope of this article but individuals can compare the simulation to their own experiences. The public is then invited to compare the "flood that might have been" had there not been a human interference in the climate system to the simulated actual flood in these neighborhoods. The variety of scientific opinions as to the human effect on precipitation and their effect on the flood are presented as detailed in the table below. A pair of high risk scenarios of the effect of a future warmer climate and a hypothetical storm similar to Harvey is also provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data

Abstract Representativeness and quality of collected meteorological data impact accuracy and precision of climate, hydrological, and biogeochemical analyses and predictions. We developed a comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework, consisting of three major phases: Phase I—Preliminary data exploration, i.e., processing of raw datasets, with the challenging problems of time formatting and combining datasets of different lengths and different time intervals; Phase II—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme data; and Phase III—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The paper includes two use cases based on the time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado), and the Barro Colorado Island (BCI, Panama) meteorological station. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Detecting dynamic causal inference in nonlinear two-phase fracture flow

Identifying dynamic causal inference involved in flow and transport processes in complex fractured-porous media is generally a challenging task, because nonlinear and chaotic variables may be positively coupled or correlated for some periods of time, but can then become spontaneously decoupled or non-correlated. In his 2002 paper (Faybishenko, 2002), the author performed a nonlinear dynamical and chaotic analysis of time-series data obtained from the fracture flow experiment conducted by Persoff and Pruess (1995), and, based on the visual examination of time series data, hypothesized that the observed pressure oscillations at both inlet and outlet edges of the fracture result from a superposition of both forward and return waves of pressure propagation through the fracture. In the current paper, the author explores an application of a combination of methods for detecting nonlinear chaotic dynamics behavior along with the multivariate Granger Causality (G-causality) time series test. Based on the G-causality test, the author infers that his hypothesis is correct, and presents a causation loop diagram of the spatial-temporal distribution of gas, liquid, and capillary pressures measured at the inlet and outlet of the fracture. The causal modeling approach can be used for the analysis of other hydrological processes, for example, infiltration and pumping tests in heterogeneous subsurface media, and climatic processes, for example, to find correlations between various meteorological parameters, such as temperature, solar radiation, barometric pressure, etc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Understanding Dynamical Systems in High-Dimensional Parameter Spaces (Final Report)

In the last few decades, computational models, especially of the complex dynamical systems of greatest interest, i.e., climate, high energy density science, combustion, etc. have become increasingly accurate and sophisticated. Consequently, they are now routinely used to predict outcomes of experiments or to inform design decisions. However, many such simulations depend on a (large) number of parameters in order to, for example, approximate physical phenom whose exact solution is unknown or describe material properties in situations with little or no experimental data. Choosing these parameters and understanding how the outcomes of such a simulation changes with respect to the inputs are rapidly becoming some of the primary challenges in many application areas. Simulations have long been too complex for humans to fully comprehend and thus are often treated as black-box systems. The inputs to the systems are typically a collection of parameters with expert-selected ranges, and the outputs are various quantities of interest (QoIs) describing the performance of the system. Therefore, the fundamental challenge can be described as one of understanding a high-dimensional (many input parameters), multi-variate (many QoIs) function. Unfortunately, existing analysis tools are only of limited use for this task as most techniques can neither deal with many input dimensions nor offer opportunities to jointly study several QoIs. Furthermore, data analysis has long relied on an exploratory process in which scientist first visualize the available data, for example, using scatter plots or 3D renderings, form new hypotheses on some phenomena of interest, and subsequently test these hypotheses using dedicated analysis or statistics approaches. However, for high-dimensional functions this exploration is difficult if not impossible using existing tools as there are too many QoIs to simultaneously observe, and visualizations of high-dimensional spaces are abstract and difficult to understand if they exist at all. The goal of this project is to build new analysis techniques and tool that offer high level insights for exploring high-dimensional scientific data. And to extend existing approach beyond single scalar functions and instead consider multiple QoIs simultaneously.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Monitoring the daily evolution and extent of snow drought

Abstract. Snow droughts are commonly defined as below-average snowpack at a point in time, typically 1 April in the western United States (wUS). This definition is valuable for interpreting the state of the snowpack but obscures the temporal evolution of snow drought. Borrowing from dynamical systems theory, we applied phase diagrams to visually examine the daily evolution of snow water equivalent (SWE) and accumulated precipitation conditions in maritime, intermountain, and continental snow climates in the wUS using station observations as well as spatially distributed estimates of SWE and precipitation. Using a percentile-based drought definition, phase diagrams of SWE and precipitation highlighted decision-relevant aspects of snow drought such as onset, evolution, and termination. The phase diagram approach can be used in tandem with spatially distributed estimates of daily SWE and precipitation to reveal variability in snow drought type and extent. When combined with streamflow or other environmental data, phase diagrams and spatial estimates of snow drought conditions can help inform drought monitoring and early warning systems and help link snow drought type and evolution to impacts on ecosystems, water resources, and recreation. A web tool is introduced allowing users to create real-time or historic snow drought phase diagrams.

54 ENVIRONMENTAL SCIENCES↗