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DOE OSTI2021

Regional environmental controllers influence continental scale soil carbon stocks and future carbon dynamics

Abstract Understanding the influence of environmental factors on soil organic carbon (SOC) is critical for quantifying and reducing the uncertainty in carbon climate feedback projections under changing environmental conditions. We explored the effect of climatic variables, land cover types, topographic attributes, soil types and bedrock geology on SOC stocks of top 1 m depth across conterminous United States (US) ecoregions. Using 4559 soil profile observations and high-resolution data of environmental factors, we identified dominant environmental controllers of SOC stocks in 21 US ecoregions using geographically weighted regression. We used projected climatic data of SSP126 and SSP585 scenarios from GFDL-ESM 4 Earth System Model of Coupled Model Intercomparison Project phase 6 to predict SOC stock changes across continental US between 2030 and 2100. Both baseline and predicted changes in SOC stocks were compared with SOC stocks represented in GFDL-ESM4 projections. Among 56 environmental predictors, we found 12 as dominant controllers across all ecoregions. The adjusted geospatial model with the 12 environmental controllers showed an R 2 of 0.48 in testing dataset. Higher precipitation and lower temperatures were associated with higher levels of SOC stocks in majority of ecoregions. Changes in land cover types (vegetation properties) was important in drier ecosystem as North American deserts, whereas soil types and topography were more important in American prairies. Wetlands of the Everglades was highly sensitive to projected temperature changes. The SOC stocks did not change under SSP126 until 2100, however SOC stocks decreased up to 21% under SSP585. Our results, based on environmental controllers of SOC stocks, help to predict impacts of changing environmental conditions on SOC stocks more reliably and may reduce uncertainties found in both, geospatial and Earth System Models. In addition, the description of different environmental controllers for US ecoregions can help to describe the scope and importance of global and local models.

58 GEOSCIENCES↗

DOE OSTI2021

Holistic Fuel Cell Electric Vehicle/Hydrogen Station Optimization Model (CRADA CRD-18-00745 Final Report)

The National Renewable Energy Lab (NREL), Argonne National Lab (ANL), Sandia National Lab (SNL), and Frontier Energy, Inc comprise a team that will perform a review of currently available models that can simulate both a hydrogen station and a fuel cell electric vehicle (FCEV), and whose owners are willing to make them available freely. We will then down select to a single model or model pair, secure agreements for their free use, and validate the resulting model or coupled models. For example, we may evaluate an existing 1-D hydrogen fueling model developed by Kyushu University for the Japanese New Energy and Industrial Technology Development Organization (NEDO). The validation will take place using data from various sources, potentially including the European Joint Research Center (JRC) HyTransfer project, SAE testing performed by Powertech to validate SAE J2601, and whole-station validation using the NREL’s Hydrogen Infrastructure Testing and Research Facility (HITRF). The team will make the model and all the validation data open to the public at the end of the project.

1-D hydrogen fueling model↗

NASA NTRS1996

High Temperature Degradation Mechanisms in Polymer Matrix Composites

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using a coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

Cunningham, Ronan A.↗

NASA NTRS1997

High Temperature Degradation Mechanisms in Polymer Matrix Composites

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

Cunningham, Ronan A.↗

NASA NTRS2010

Space Weather Models, Tools and Services at the Community Coordinated Modeling Center

The Community Coordinated Modeling center (CCMC) is a multi-agency partnership to support the research and developmental work necessary to substantially increase space weather modeling capabilities and to facilitate advanced models deployment in forecasting operations. The CCMC conducts unbiased model testing and validation and evaluates model readiness for operational environment. Space weather models and coupled model chains hosted at the CCMC range from the solar corona to the Earth's upper atmosphere. CCMC has developed a number of real-time modeling systems, as well as a large number of modeling and data products tailored to address the space weather needs of NASA's robotic missions. The presentation will demonstrate the rapid progress towards development the system allowing using products derived from space weather models in applications associated with National Space Weather needs. The adaptable Integrated Space Weather Analysis (ISWA) System developed at CCMC for NASA-relevant space weather information combines forecasts based on advanced space weather models hosted at CCMC with concurrent space environment information. The system is also enabling post-impact analysis and flexible dissemination of space weather information.

Kuznetsova, M. M.↗

NASA NTRS2011

Validation of Space Weather Models at Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership to support the research and developmental work necessary to substantially increase space weather modeling capabilities and to facilitate advanced models deployment in forecasting operations. Space weather models and coupled model chains hosted at the CCMC range from the solar corona to the Earth's upper atmosphere. CCMC has developed a number of real-time modeling systems, as well as a large number of modeling and data products tailored to address the space weather needs of NASA's robotic missions. The CCMC conducts unbiased model testing and validation and evaluates model readiness for operational environment. CCMC has been leading recent comprehensive modeling challenges under GEM, CEDAR and SHINE programs. The presentation will focus on experience in carrying out comprehensive and systematic validation of large sets of. space weather models

Kuznetsova, M. M.↗

DOE OSTI2023

Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy

Abstract. The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative, has studied various important challenges related to coupling mesoscale models to microscale models for the use case of wind energy development and operation. Several coupling methods and techniques for generating turbulence at the microscale that is subgrid to the mesoscale have been evaluated for a variety of cases. Case studies included flat-terrain, complex-terrain, and offshore environments. Methods were developed to bridge the terra incognita, which scales from about 100 m through the depth of the boundary layer. The team used wind-relevant metrics and archived code, case information, and assessment tools and is making those widely available. Lessons learned and discerned best practices are described in the context of the cases studied for the purpose of enabling further deployment of wind energy.

17 WIND ENERGY↗

NASA NTRS2007

Parallelization of the Coupled Earthquake Model

This Web-based tsunami simulation system allows users to remotely run a model on JPL s supercomputers for a given undersea earthquake. At the time of this reporting, predicting tsunamis on the Internet has never happened before. This new code directly couples the earthquake model and the ocean model on parallel computers and improves simulation speed. Seismometers can only detect information from earthquakes; they cannot detect whether or not a tsunami may occur as a result of the earthquake. When earthquake-tsunami models are coupled with the improved computational speed of modern, high-performance computers and constrained by remotely sensed data, they are able to provide early warnings for those coastal regions at risk. The software is capable of testing NASA s satellite observations of tsunamis. It has been successfully tested for several historical tsunamis, has passed all alpha and beta testing, and is well documented for users.

Block, Gary↗

DOE OSTI2025

Dynamical coupled-channel models for hadron dynamics

Dynamical coupled-channel (DCC) approaches parametrize the interactions and dynamics of two and more hadrons and their response to different electroweak probes. The inclusion of unitarity, three-body channels, and other properties from scattering theory allows for a reliable extraction of resonance spectra and their properties from data. Here, we review the formalism and application of the ANL-Osaka, the Juelich-Bonn-Washington, and other DCC approaches in the context of light baryon resonances from meson, (virtual) photon, and neutrino-induced reactions, as well as production reactions, strange baryons, light mesons, heavy meson systems, exotics, and baryon-baryon interactions. Finally, we also provide a connection of the formalism to study finite-volume spectra obtained in Lattice QCD, and review applications involving modern statistical and machine learning tools.

Amplitude analysis↗

DOE OSTI2023

Contrasting effects of lake breeze and urbanization on heat stress in Chicago metropolitan area

This study used the latest Weather Research and Forecasting (WRF) model coupled with multi -layer urban canopy models to investigate contrasting effects from urbanization and lake breeze on summer heat stress over the Chicago metropolitan area (CMA). Comparisons between the model and in situ observations show that this coupled modeling system better captures urban locations' diurnal pattern of surface air temperature, skin temperature and relative humidity, with root mean square error reduced from 1.58 to 1.80 degrees C to 1.14-1.31 degrees C, 3.11-3.55 degrees C to 1.81-2.21 degrees C, and 10.73-11.35% to 7.84-8.60%, respectively, compared to WRF without coupling the urban canopy models. Two sensitivity experiments were conducted to isolate the influence of lake breeze and urbanization: one replaced the urban land use with cropland over the CMA, and the other filled all of Lake Michigan with cropland. Three different heat stress indices were computed to assess the uncertainties of heat stress response to changes in air temperature, relative humidity, and wind conditions. Results show that, when the lake has the largest cooling effect on air temperature, it also increases the relative humidity the most, and vice versa for urban warming and drying effects. Urbanization intensifies heat stress at night, and extends the heat caution period by up to 4 h over inland urban grids; the lake breeze relieves heat stress during afternoon (when the heat stress is the worst), and shortens the heat caution period by 1-3 h over inland urban grids and 3-4 h over coastal urban grids. In conclusion, the intensification of heat stress over the CMA due to urbanization is more than four times greater than the reduction from the lake breeze in the late afternoon and evening.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

Gain selection method and model for coupled propulsion and airframe systems

A longitudinal model is formulated for an advanced fighter from three subsystem models: the inlet, the engine, and the airframe. Notable interaction is found in the coupled system. A procedure, based on eigenvalue sensitivities, is presented which indicates the importance of the feedback gains to the optimal solution. This allows ineffectual gains to be eliminated; thus, hardware and expense may be saved in the realization of the physical controller.

Murphy, P. C.↗

NASA NTRS2023

The Projected Future Degradation in Air Quality is Caused by More Abundant Natural Aerosols in a Warmer World

Previous studies suggest that greenhouse gas-induced warming can lead to increased fine particulate matter concentrations and degraded air quality. However, significant uncertainties remain regarding the sign and magnitude of the response to warming and the underlying mechanisms. Here, we show that thirteen models from the Coupled Model Intercomparison Project Phase 6 all project an increase in global average concentrations of fine particulate matter in response to rising carbon dioxide concentrations, but the range of increase across models is wide. The two main contributors to this increase are increased abundance of dust and secondary organic aerosols via intensified West African monsoon and enhanced emissions of biogenic volatile organic compounds, respectively. Much of the inter-model spread is related to different treatment of biogenic volatile organic compounds. Our results highlight the importance of natural aerosols in degrading air quality under current warming, while also emphasizing that improved understanding of biogenic volatile organic compounds emissions due to climate change is essential for numerically assessing future air quality.

Climate and Earth system modelling↗

DOE OSTI2023

Integrable field theories and their CCFT duals

We compute the Mellin transforms of various two-dimensional integrable S-matrices, providing the first explicit, non-perturbative realizations of celestial CFT. In two dimensions, the Mellin transform is simply the Fourier transform in rapidity space, and the “celestial correlator” has no position dependence. The simplified setting allows us to study the analytic properties of CCFT correlators exactly as a function of the conformal dimensions. We find that the correlators exist as real distributions of the conformal weights, with asymptotics controlled by the mass spectrum and three-point couplings of the model. Coupling these models to a flat space limit of JT gravity preserves integrability and dresses the amplitudes by a rapidly varying gravitational phase. We find that the coupling to gravity smooths out certain singular aspects of the Mellin-transformed correlators.

2D Gravity↗

DOE OSTI2022

Description of historical and future projection simulations by the global coupled E3SMv1.0 model as used in CMIP6

Abstract. This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea ice, and land. Due to its high equilibrium climate sensitivity (ECS of 5.3 K), E3SMv1.0 is one of the Coupled Model Intercomparison Project phase 6 (CMIP6) models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated with the global temperature change, while the spatial pattern of the change in runoff is consistent with the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The annual mean Atlantic meridional overturning circulation (AMOC) is overly weak with a slower change from ∼ 11 to ∼ 6 Sv (Sverdrup) relative to other CMIP6 models. The sea ice, especially in the Northern Hemisphere, decreases rapidly with large seasonal variability. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes transient accelerated warming in the all-forcing experiment in the first half of the 21st century. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions, e.g., southern North America, southern Africa, central Africa, and eastern Asia. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Anthromes and forest carbon responses to global change

Human effects on ecosystems date back thousands of years, and anthropogenic biomes—anthromes—broadly incorporate the effects of human population density and land use on ecosystems. Forests are integral to the global carbon cycle, containing large biomass carbon stocks, yet their responses to land use and climate change are uncertain but critical to informing climate change mitigation strategies, ecosystem management, and Earth system modeling. Using an anthromes perspective and the site locations from the Global Forest Carbon (ForC) Database, we compare intensively used, cultured, and wildland forest lands in tropical and extratropical regions. We summarize recent past (1900-present) patterns of land use intensification, and we use a feedback analysis of Earth system models from the Coupled Model Intercomparison Project Phase 6 to estimate the sensitivity of forest carbon stocks to CO 2 and temperature change for different anthromes among regions. Modeled global forest carbon stock responses are positive for CO 2 increase but neutral to negative for temperature increase. Across anthromes (intensively used, cultured, and wildland forest areas), modeled forest carbon stock responses of temperate and boreal forests are less variable than those of tropical forests. Tropical wildland forest areas appear especially sensitive to CO 2 and temperature change, with the negative temperature response highlighting the potential vulnerability of the globally significant carbon stock in tropical forests. The net effect of anthropogenic activities—including land-use intensification and environmental change and their interactions with natural forest dynamics—will shape future forest carbon stock changes. These interactive effects will likely be strongest in tropical wildlands.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗

NASA NTRS2018

The PMIP4 Contribution to CMIP6 - Part 1: Overview and Over-Arching Analysis Plan

This paper is the first of a series of four GMD (Geoscientific Model Development) papers on the PMIP4-CMIP6 (Paleoclimate Modelling Intercomparison Project - Phase 4 -- Coupled Model Intercomparison Project - Phase 6) experiments. Part 2 (Otto-Bliesner et al., 2017) gives details about the two PMIP4-CMIP6 interglacial experiments, Part 3 (Jungclaus et al., 2017) about the last millennium experiment, and Part 4 (Kageyama et al., 2017) about the Last Glacial Maximum experiment. The mid-Pliocene Warm Period experiment is part of the Pliocene Model Intercomparison Project (PlioMIP) - Phase 2, detailed in Haywood et al. (2016). The goal of the Paleoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to different climate forcings for documented climatic states very different from the present and historical climates. Through comparison with observations of the environmental impact of these climate changes, or with climate reconstructions based on physical, chemical, or biological records, PMIP also addresses the issue of how well state-of-the-art numerical models simulate climate change. Climate models are usually developed using the present and historical climates as references, but climate projections show that future climates will lie well outside these conditions. Palaeoclimates very different from these reference states therefore provide stringent tests for state-of-the-art models and a way to assess whether their sensitivity to forcings is compatible with palaeoclimatic evidence. Simulations of five different periods have been designed to address the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6): the millennium prior to the industrial epoch (CMIP6 name: past1000); the mid-Holocene, 6000 years ago (midHolocene); the Last Glacial Maximum, 21,000 years ago (lgm); the Last Interglacial, 127,000 years ago (lig127k); and the mid-Pliocene Warm Period, 3.2 million years ago (midPliocene-eoi400). These climatic periods are well documented by palaeoclimatic and palaeoenvironmental records, with climate and environmental changes relevant for the study and projection of future climate changes. This paper describes the motivation for the choice of these periods and the design of the numerical experiments and database requests, with a focus on their novel features compared to the experiments performed in previous phases of PMIP and CMIP. It also outlines the analysis plan that takes advantage of the comparisons of the results across periods and across CMIP6 in collaboration with other MIPs.

climate↗

DOE OSTI2025

Studies of the influence of heat pipe model and coupling strategy in heat pipe microreactor simulations using Sockeye

This work demonstrates various modeling approaches for thermally coupling heat pipes to a graphite monolithic block in a microreactor context, accounting for the presence of a gap. We show that heat pipe model selection has a significant impact on the transient behavior of a three-dimensional coupled microreactor assembly problem by comparing results obtained using different heat pipe models from the heat pipe code Sockeye. Additionally, we show that the choice of coupling strategy has significant consequences for both accuracy and performance. Furthermore, we found that our heat flux transfer strategy exhibited greater accuracy than our temperature transfer strategy, even when comparing a loose coupling of the heat flux transfer strategy to a tight coupling of the temperature transfer strategy. Although this research uses only theoretical test problems, it provides important insights in modeling thermal fluids phenomena in heat pipe microreactors.

Direwolf↗