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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding processes that control dust spatial distributions with global climate models and satellite observations

Dust aerosol is important in modulating the climate system at local and global scales, yet its spatiotemporal distributions simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate the spatiotemporal variations of dust extinction profiles and dust optical depth (DOD) simulated by the Community Earth System Model version 1 (CESM1) and version 2 (CESM2), the Energy Exascale Earth System Model version 1 (E3SMv1), and the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) against satellite retrievals from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Multi-angle Imaging SpectroRadiometer (MISR). We find that CESM1, CESM2, and E3SMv1 underestimate dust transport to remote regions. E3SMv1 performs better than CESM1 and CESM2 in simulating dust transport and the northern hemispheric DOD due to its higher mass fraction of fine dust. CESM2 performs the worst in the Northern Hemisphere due to its lower dust emission than in the other two models but has a better dust simulation over the Southern Ocean due to the overestimation of dust emission in the Southern Hemisphere. DOD from MERRA-2 agrees well with CALIOP DOD in remote regions due to its higher mass fraction of fine dust and the assimilation of aerosol optical depth. The large disagreements in the dust extinction profiles and DOD among CALIOP, MODIS, and MISR retrievals make the model evaluation of dust spatial distributions challenging. Our study indicates the importance of representing dust emission, dry/wet deposition, and size distribution in GCMs in correctly simulating dust spatiotemporal distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Representing Fine‐Scale Topographic Effects on Surface Radiation Balance in Hyper‐Resolution Land Surface Models

Land surface models are increasingly used to simulate land surface processes at hyper-spatial resolutions (e.g., ∼1 km). As model resolution increases, grid-scale topographic effects on surface radiation fluxes and their interactions between adjacent grids become more pronounced. However, current land surface models routinely neglect the fine-scale topographic effects on surface radiation balance. This study developed physically-based and computationally-efficient parameterizations (fineTOP) that explicitly resolve fine-scale topographic effects on downward shortwave and longwave radiation as well as land surface radiative properties. The newly developed parameterizations were implemented and tested in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Multi-decadal km-resolution ELM simulations over the California Sierra Nevada show that fine-scale topography significantly impacts the surface energy balance and snow processes across seasons. Slope determines the magnitude of topographic effects, while aspect controls their sign. For slopes larger than 30°, topography-induced change in annual surface temperature can be as large as 3.3 K. Regionally, the mean value and standard deviation of topography-induced changes in annual surface temperature are −0.22 ± 0.38 K and +0.25 ± 0.37 K over north-facing and south-facing slopes, respectively. Topography-induced changes in surface radiative properties account for 3.5% ± 13.8% of total topographic effects on annual net radiation. With fineTOP, ELM captures the aspect-dependence of snow cover fraction, snow water equivalent, and land surface temperature found in MODIS satellite observations and a snow reanalysis data set, while the default ELM fails to capture this phenomenon. The enhanced capability to represent fine-scale topographic effects on surface radiation balance can be used to advance understanding of the role of fine-scale topography in land surface processes and land-atmosphere interactions over mountainous regions.

Hao, Dalei [Pacific Northwest National Laboratory ↗
DOE OSTI2024

Quantifying the long-term changes of terrestrial water storage and their driving factors

Global warming is expected to cause changes in terrestrial water storage (TWS) across the land surface, with widespread impacts on ecosystems and society. Although extensive research has been performed to analyze TWS changes and possible drivers during the post-2000 period, longer-term evolution of TWS and associated environmental forcings remain relatively unexplored. In this study, we evaluated the performance of the Energy Exascale Earth System model (E3SM) land model ELM version 1 (ELM v1) in simulating global TWS, and used factorial simulations of ELMv1 to quantify global TWS changes and their drivers during 1948–2012. We found that ELM’s agreed best with existing satellites and reconstruction datasets in temperate regions unaffected by irrigation. Biome- and climate zone-averaged TWS mainly increased at rates between 0 and 10 mm/year over 1948–2012, but the second half of that period saw smaller positive trends than the first half or even negative trends. Climate change explained >80 % of the TWS trends across most biomes and climate zones, followed by land use and land cover change. The physiological and phenological effects of CO2 primarily induced noticeable TWS trends in the more humid biomes and climate zones across different latitudes. In contrast, nitrogen deposition and aerosol deposition generally had smaller and negative impacts across the biomes and climate regions. Among the meteorological drivers analyzed, the long-term average imbalance between precipitation (P), evapotranspiration (E), and runoff (Q) contributed >50 % of the TWS trends in most biomes and climate zones, with nonlinearity being induced by spatially heterogenous changes in E/P and Q/P ratios. The accumulated detrended anomalies in P, E, and Q also often contributed substantially, while the trends difference between P, E, and Q contributed little. Together, these findings unveiled an intensification of the global TWS and its diverse patterns of climate change and different non-withdrawal human-induced alterations, contributing to a more comprehensive understanding and projection of the global water cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Understanding Precipitation Bias Sensitivities in E3SM-Multi-Scale Modeling Framework From a Dilution Framework

We investigate a set of Energy Exascale Earth System Model Multi-scale modeling framework (MMF) (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A PEPS Plugin for TNQVM

This work introduces an extension to the Tensor Network Quantum Virtual Machine (TNQVM) tool, enhancing the existing stack of ExaScale Tensor Network (ExaTN), ExaScale Accelerator (XACC), and TNQVM. It features a new plugin that enables efficient simulation of a Projected Entangled Pair State (PEPS), a 2D tensor network. To improve simulation efficiency for PEPS, we have implemented the snake boundary contraction algorithm. By integrating this capability into the existing stack, we enhance the overall functionality and versatility of the framework. We tested this new PEPS topology for a simple GHZ bell-pair generation quantum circuit and saw that its runtime is very close to that of the MPS topology. We estimate that the real potential of the PEPS topology becomes discernible when quantum circuits with multidimensional entanglement are simulated using tensor networks. In such cases, 1D tensor networks fail to represent or contract them efficiently.

Chundury, Srikar↗
DOE OSTI2023

The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System

We present an efficient and performance portable implementation of the Simple Cloud Resolving E3SM Atmosphere Model (SCREAM). SCREAM is a full featured atmospheric global circulation model with a nonhydrostatic dynamical core and state-of-the-art parameterizations for microphysics, moist turbulence and radiation. It has been written from scratch in C++ with the Kokkos library used to abstract the on-node execution model for both CPUs and GPUs. SCREAM is one of only a few global atmosphere models to be ported to GPUs. As far as we know, SCREAM is the first such model to run on both AMD GPUs and NVIDIA GPUs, as well as the first to run on nearly an entire Exascale system (Frontier). On Frontier, we obtained a record setting performance of 1.26 simulated years per day for a realistic cloud resolving simulation.

Taylor, Mark↗
DOE OSTI2025

Tracking carbon dioxide in the Southern Ocean (Final Technical Report)

We investigated the discrepancy in observed and modeled Southern Ocean carbon dioxide (CO 2 ) absorption through the lens of the Energy Exascale Earth System Model (E3SM), leveraging recent and upcoming E3SM development advances to simulate Lagrangian Biogeochemical-Argo floats. E3SM output, together with observational data streams and output from the evolving CMIP6 archive, are being used to study the spatiotemporal bias in modeled Southern Ocean CO 2 flux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2021

Enabling Scalable and Extensible Memory-mapped Datastores in Userspace

Exascale workloads are expected to incorporate data-intensive processing in close coordination with traditional physics simulations. These emerging scientific, data-analytics and machine learning applications need to access a wide variety of datastores in flat files and structured databases. Programmer productivity is greatly enhanced by mapping datastores into the application process's virtual memory space to provide a unified “in-memory” interface. Currently, memory mapping is provided by system software primarily designed for generality and reliability. However, scalability at high concurrency is a formidable challenge on exascale systems. Also, there is a need for extensibility to support new datastores potentially requiring HPC data transfer services. In this article, we present UMap , a scalable and extensible userspace service for memory-mapping datastores. Furthermore, through decoupled queue management, concurrency aware adaptation, and dynamic load balancing, UMap enables application performance to scale even at high concurrency. We evaluate UMap in data-intensive applications, including sorting, graph traversal, database operations, and metagenomic analytics. Our results show that UMap as a userspace service outperforms an optimized kernel-based service across a wide range of intra-node concurrency by 1.22-1.9 × . We performed two case studies to demonstrate UMap 's extensibility. First, a new datastore residing in remote memory is incorporated into UMap as an application-specific plugin. Second, we present a persistent memory allocator Metall built atop UMap for unified storage/memory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Visualizing an Exascale Data Center Digital Twin: Considerations, Challenges and Opportunities

Digital twins are an excellent tool to model, visualize, and simulate complex systems, to understand and optimize their operation. In this work, we present the technical challenges of real-time visualization of a digital twin of the Frontier supercomputer.We show the initial prototype and current state of the twin and highlight technical design challenges of visualizing such a large High Performance Computing (HPC) system. The goal is to understand the use of augmented reality as a primary way to extract information and collaborate on digital twins of complex systems. This leverages the spatio-temporal aspect of a 3D representation of a digital twin, with the ability to view historical and real-time telemetry, triggering simulations of a system state and viewing the results, which can be augmented via dashboards for details. Finally, we discuss considerations and opportunities for augmented reality of digital twins of large-scale, parallel computers.

Maiterth, Matthias↗
DOE OSTI2021

ExaWorks: Workflows for Exascale

Exascale computers will offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. These software combinations and integrations, however, are difficult to achieve due to challenges of coordination and deployment of heterogeneous software components on diverse and massive platforms. We present the ExaWorks project, which can address many of these challenges: ExaWorks is leading a co-design process to create a workflow Software Development Toolkit (SDK) consisting of a wide range of workflow management tools that can be composed and interoperate through common interfaces. We describe the initial set of tools and interfaces supported by the SDK, efforts to make them easier to apply to complex science challenges, and examples of their application to exemplar cases. Furthermore, we discuss how our project is working with the workflows community, large computing facilities as well as HPC platform vendors to sustainably address the requirements of workflows at the exascale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Disentangling the chemistry and transport impacts of the quasi-biennial oscillation on stratospheric ozone

The quasi-biennial oscillation (QBO) in tropical winds perturbs stratospheric ozone throughout much of the atmosphere via changes in transport of ozone and other trace gases, as well as via temperature changes, both of which alter ozone chemistry. Attributing these causes of QBO–ozone variability may provide insights into model-to-model differences that contribute to ozone simulation. Here we develop a novel metric of steady-state ozone (SSO) to separate these effects: SSO calculates the local steady-state response of ozone due to the changes in temperature, chemical species, and overhead ozone column; the response due to circulation change is presumed when SSO shows no response. It is applied to the nudged Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2) with interactive ozone chemistry to demonstrate its validity. The E3SMv2 simulations nudged to reanalysis data produced reasonable wind and ozone patterns, especially in the tropics. Consistent with previous studies, we find clear demarcations with pressure. Ozone perturbations in the upper stratosphere (<6 hPa) are predicted by temperature changes; those between 6 and 20 hPa are predicted by NO y changes, and those in the lower stratosphere show no temperature or NO y response and are presumably driven by circulation changes. These results are important for diagnosing model-to-model discrepancy in QBO–ozone response and enhancing the reliability of ozone projections.

Xie, Jinbo [Lawrence Livermore National Laboratory↗
DOE OSTI2021

An Integrative Model for Soil Biogeochemistry and Methane Processes: I. Model Structure and Sensitivity Analysis

Abstract Environmental changes are anticipated to generate substantial impacts on carbon cycling in peatlands, affecting terrestrial‐climate feedbacks. Understanding how peatland methane (CH 4 ) fluxes respond to these changing environments is critical for predicting the magnitude of feedbacks from peatlands to global climate change. To improve predictions of CH 4 fluxes in response to changes such as elevated atmospheric CO 2 concentrations and warming, it is essential for Earth system models to include increased realism to simulate CH 4 processes in a more mechanistic way. To address this need, we incorporated a new microbial‐functional group‐based CH 4 module into the Energy Exascale Earth System land model (ELM) and tested it with multiple observational data sets at an ombrotrophic peatland bog in northern Minnesota. The model is able to simulate observed land surface CH 4 fluxes and fundamental mechanisms contributing to these throughout the soil profile. The model reproduced the observed vertical distributions of dissolved organic carbon and acetate concentrations. The seasonality of acetoclastic and hydrogenotrophic methanogenesis—two key processes for CH 4 production—and CH 4 concentration along the soil profile were accurately simulated. Meanwhile, the model estimated that plant‐mediated transport, diffusion, and ebullition contributed to ∼23.5%, 15.0%, and 61.5% of CH 4 transport, respectively. A parameter sensitivity analysis showed that CH 4 substrate and CH 4 production were the most critical mechanisms regulating temporal patterns of surface CH 4 fluxes both under ambient conditions and warming treatments. This knowledge will be used to improve Earth system model predictions of these high‐carbon ecosystems from plot to regional scales.

58 GEOSCIENCES↗
DOE OSTI2023

Evaluating EAMv2 Simulated High Latitude Clouds Using ARM Measurements in the Northern and Southern Hemispheres

Here, this study evaluates high latitude stratiform mixed-phase clouds (SMPC) in the atmosphere model of the Energy Exascale Earth System Model version 2 (EAMv2) by utilizing one-year-long ground-based remote sensing measurements from the Atmospheric Radiation and Measurement (ARM) program. A nudging approach is applied to model simulations for a constrained comparison with the ARM observations. Observed and modeled SMPCs are sampled and collocated to address the difference in data resolution, so that we can consistently evaluate their macrophysical properties at the North Slope of Alaska (NSA) site in the Arctic and the McMurdo (AWR) site in the Antarctic. We found that EAMv2 overestimates SMPC frequency of occurrence at both sites. However, the model captures the observed larger cloud frequency of occurrence at the NSA site. For collocated SMPCs, the annual statistics of observed cloud macrophysics are generally reproduced at the NSA site, while at the AWR site, there are larger biases. Compared to the AWR site, the lower cloud top and cloud base and the warmer cloud top temperature observed at NSA are well simulated. On the other hand, simulated cloud phase is substantially biased. The model largely overestimates liquid water path, and the ice water path is underestimated at NSA, but at AWR, the liquid water path is frequently underestimated due to the dominance of snow in Antarctic SMPCs. As a result, the observed hemispheric difference in cloud phase partitioning is misrepresented in EAMv2. This study implies that additional model development is needed for high latitude mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of present-day extreme precipitation over the United States: an inter-comparison of convection and dynamic permitting configurations of E3SMv1

Abstract Accurate simulation of the present-day characteristics of mean and extreme precipitation at regional scales remains a challenge for Earth system models, which is due in part to deficiencies in model physics such as convective parameterization (CP), and coarse resolution. High horizontal resolution (HR, ∼25 km) and multiscale modeling framework (MMF, i.e. replacing conventional CP with embedded km-scale cloud-resolving models) are two promising directions that could help improve the interaction between subgrid-scale physical processes and large-scale climate. Here, we evaluate simulated extreme precipitation over the United States (US) across three configurations (i.e. low-resolution [LR], HR, and MMF) of the Energy Exascale Earth System Model (E3SMv1) and intercompare them against two gridded observation datasets (climate prediction center daily US precipitation and integrated multi-satellite retrievals for global precipitation measurement). We assess the model’s ability to simulate very heavy seasonal precipitation (illustrated by the difference between the 99th and 90th percentile values) as well as the spatial distributions of several extreme precipitation indices defined by the expert team on climate change detection and indices. Our results show that both the dry (i.e. consecutive dry days (CDD)) and wet (i.e. consecutive wet days, maximum 5 day precipitation, and very wet days) extremes evaluated herein show some improvement as well as degradation with MMF and HR relative to LR. These results vary across seasons and US subregions. For instance, only the very heavy precipitation of winter is improved with MMF and HR. Both configurations alleviate the well-known drizzling bias evident in LR across both winter and summer in many parts of the US, largely due to the overall improvement in intensity and frequency of precipitation. Additionally, our results suggest that while E3SMv1-MMF has higher intensity rates when it does rain, it has too many CDD during the summer, contributing to a low mean precipitation bias.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

MAM4xx

SAND2023-05377O The Modal Aerosol Model with 4 fixed modes (MAM4xx) is a performance-portable, C++ implementation for modeling the chemical reactions of aerosols in the atmosphere. MAM4xx is part of the Energy Exascale Earth System Model (E3SM). The E3SM project is an ongoing Earth system modeling, simulation, and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Overfelt, James↗
DOE OSTI2020

ECP ST Project 2.3.1.06-STPM08-RAJA (Final Report)

Modern high-performance computing architectures are diverse, with hardware designs that feature multicore CPUs and CPUs plus accelerators, such as GPUs or FPGAs. Achieving good application performance often requires using a programming model and managing application data in ways that are best suited to a particular platform. For large codes that are used daily in production, and are under continual development, architecture-specific ports are untenable. Maintainability requires single-source code that is performance portable across a range of architectures and programming model back-ends. This report describes RAJA, Umpire, and CHAI, three software libraries that provide complementary capabilities to enable application portability for high performance computing (HPC) platforms. In particular, these libraries provide software abstractions that insulate application source code from hardware architecture and programming model-specific implementation details. These development of these libraries was motivated by the needs of multiphysics applications in the Weapons Simulation and Computing Program (WSC) at Lawrence Livermore National Laboratory (LLNL). Funding though the Exascale Computing Project (ECP) Software Technology (ST) project 2.3.1.06 RAJA has fostered outreach and collaboration with the ECP application and software technology development communities. In this report, we describe ECP adoption and integration of these tools to this point. The larger goal of the report is to describe to the ECP community what these projects offer, how they are used, and how to approach adoption and integration of them.

97 MATHEMATICS AND COMPUTING↗