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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 91 records · Page 5
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NASA NTRS2002

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

Talbot, Bryan↗
NASA NTRS1994

A spectral formalism for computing three-dimensional deformations due to surface loads. 2: Present-day glacial isostatic adjustment

Using a spherically symmetric, self-gravitating, linear viscoelastic Earth model, we predict present-day three-dimensional surface deformation rates and baseline evolutions arising as a consequence of the late Pleistocene glacial cycles. In general, we use realistic models for the space-time geometry of the final late Pleistocene deglaciation event and incorporate a gravitationally self-consistent ocean meltwater redistribution. The predictions of horizontal velocity presented differ significantly, in both their amplitude and their spatial variation, from those presented in earlier analysis of others which adopted simplified models of both the late Pleistocene ice history and the Earth rheology. An important characteristic of our predicted velocity fields is that the melting of the Laurentide ice sheet over Canada is capable of contributing appreciably to the adjustment in Europe. The sensitivity of the predictions to variations in mantle rheology is investigated by considering a number of different Earth models, and by computing appropriate Frechet kernels. These calculations suggest that the sensitivity of the deformations to the Earth's rheology is significant and strongly dependent on the location of the site relative to the ancient ice sheet. The effects on the predictions of three-dimensional deformation rates of altering the ice history or adopting approximate models for the ocean meltwater redistribution have also been considered and found to be important (the former especially so). Finally, for a suite of Earth models we provide predictions of the velocity of a number of baselines in North America and Europe. We find that, in general, both radial and tangential motions contribute significantly to baseline length changes, and that these contributions are a strong function of the Earth model. We have, furthermore, found a set of Earth models which, together with the ICE-3G deglaciation chronology, produce predictions of baseline length changes that are consistent with very long baseline interferometry measurements of baselines within Europe.

Mitrovica, J. X.↗
NASA NTRS2018

Learning Model Structural Uncertainty with Gaussian Processes

The advent of commercially available quantum computers has marked the beginning of quantum computing as a reality. Both quantum gate and annealing computers have been released by major computer hardware companies. In this work, the D-Wave 2XTM quantum annealing computer housed at the NASA Advanced Systems computational facility is investigated to accelerate Machine Learning (ML) for image registration. NASA collects large amounts of images over the globe remotely using space-based monitoring. Images of a fixed areas of the land surface are taken over time. Due to the orbit of the sensors, the viewing angles deviate slightly, and it is necessary to align or register the images precisely to create image time series over the land surface. Unaligned images can lead to substantial analysis errors. These time-series are then used in modeling Earth Systems models such as hydrological, weather, and carbon monitoring models. In this work, we consider the Moderate Resolution Image Spectrometer (MODIS) data collected by the NASA's terra satellite. Artificial Neural Networks (ANNs) is a natural fit for ML modelling of images. Several successes have been reported using machine learning related to image processing. We investigate the use of ML to register MODIS images. ANNs are investigated in combination with a Restricted Boltzmann Machines (RBM) as an auto-encoder. We will present results showing the accuracy and efficiency of this approach.The D-Wave 2XTM quantum annealer samples the ground-state wave-function of a spin-Ising systems with quadratic interactions between qubits and a Chimera connectivity. The system sits in a ~15 mK thermal bath. One can think of the system as being placed in the ground state initially and subject to thermal excitations governed by Boltzmann statistics. If this is assumed true, one can use the statistics from the D-Wave 2XTM to train RBMs. Generating statistics for training Boltzmann machines is an NP-hard problem and constitutes the largest compute cost. We investigate the use of the D-Wave 2XTM to accelerate the training of the RBMs in our ANNs and report on the results.

Kouatchou, Jules↗
NASA NTRSDate not supplied

Influence of regional anthropogenic changes over Nile region on the climate system during the late Holocene (~2500 years before present)

The societal impacts of climate change during the late Holocene leads to regional anthropogenic changes over the Nile region floodplain and could have acted in tandem with natural factors like major volcanic eruptions on the regional climate system to magnify the local climatic impacts. This study aims to explore and investigate the sensitivity of climatic changes to the regional anthropogenic changes due to various factors over the Nile river floodplains during the late-Holocene (2.5K years before present). The GISS ModelE Earth system model will be used to simulate the various scenarios of regional increasing/decreasing river fraction, changes in vegetation type and cover, along with changes in land surface type against the no-changes scenario in absence of volcanic eruptions. The spatial coverage of the Nile river basin is estimated using the GIS shapefile based on elevation data from Shuttle Radar Topography Mission (SRTM) at 3 Arc-seconds (approx. 90-meter) horizontal resolution. The extent of flooding in the model grid (2.0°x2.5° in latitude and longitude) is estimated using the existing high-resolution (0.125°x0.125°) gridded topographic elevation information and mapped over the Nile river floodplains. This study also focuses on evaluating the NASA GISS ModelE for resolving the climate feedbacks and response on climate system due to anthropogenic changes and volcanic eruptions. It is also aimed to analyze and quantify the impact of various anthropogenic factors over the African monsoon system and rainfall over the region, which feeds the Nile River.

Anthropogenic changes↗
NASA NTRS2024

Global Influence of Organic Aerosol Volatility on Aerosol Microphysical Processes: Composition and Number

We present MATRIX-VBS, a new aerosol scheme that simulates organic partitioning in an aerosol microphysics model, as part of the NASA GISS ModelE Earth System Model. MATRIX-VBS builds on its predecessor aerosol microphysics model MATRIX (Bauer et al., 2008, https://doi.org/10.5194/acp-8-6003-2008) and was developed in the box model framework (Gao et al., 2017, https://doi.org/10.5194/gmd-10-751-2017). The scheme features the inclusion of organic partitioning between the gas and particle phases and the photochemical aging process using the volatility-basis set (Donahue et al., 2006, https://doi.org/10.1021/es052297c). To assess the performance of the new model, we compared its mass concentration, number concentration, and activated number concentration to the original scheme MATRIX, and evaluated its mass concentrations in four seasons against data from the NASA Atmospheric Tomography Mission (ATom) aircraft campaign. Results from MATRIX-VBS show that organics are transported further away from their source, and their mass concentration increases aloft and decreases at the surface compared to those in MATRIX. The mass concentration of organics at the surface agrees well with measurements, and there are discrepancies for vertical profiles aloft. In the new scheme, the global mass load of organic aerosols increased by 50%, there is also an increased number of particles at the surface and fewer activated ones in most regions. The new scheme presents advanced and more comprehensive capability in simulating aerosol processes.

aerosol modeling↗
NASA NTRS1985

Selection of a model of Earth's albedo radiation, practical calculation of its effect on the trajectory of a satellite

Theoretical models of Earth's albedo radiation was proposed. By comparing disturbing accelerations computed from a model to those measured in flight with the CACTUS Accelerometer, modified according to the results. Computation of the satellite orbit perturbations from a model is very long because for each position of this satellite the fluxes coming from each elementary surface of the terrestrial portion visible from the satellite must be summed. The speed of computation is increased ten times without significant loss of accuracy thanks to a stocking of some intermediate results. Now it is possible to confront the orbit perturbations computed from the selected model with the measurements of these perturbations found with satellite as LAGEOS.

Walch, J. J.↗
NASA NTRS2018

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations↗
NASA NTRS2018

Explicit Cloud Representation in the Atmos 1D Climate Model for Earth and Rocky Planet Applications

1D climate models are less sophisticated than 3D global circulation models (GCMs), however their computational time is much less expensive, allowing a large number of runs in a short period of time to explore a wide parameter space. Exploring parameter space is particularly important for predicting the observable properties of exoplanets, for which few parameters are known with certainty. Therefore, 1D climate models are still very useful tools for planetary studies. In most of these 1D models, clouds are not physically represented in the atmosphere, despite having a well-known, significant impact on a planetary radiative budget. This impact is simulated by artificially raising surface albedo, in order to reproduce the observed-averaged surface temperature (i.e. 288 K for modern Earth) and a radiative balance at the top of the atmosphere. This non-physical representation of clouds, causes atmospheric long wave and shortwaves fluxes to not match observational data. Additionally, this technique represents a parameter that is highly-tuned to modern Earth’s climate, and may not be appropriate for planets that deviate from modern Earth’s climate conditions. In this paper, we present an update to the climate model within the Atmos 1­D atmospheric modeling package with a physical representation of clouds. We show that this physical representation of clouds in the atmosphere allows both long wave and shortwave fluxes to match observational data. This improvement will allow us to study the energy fluxes for a variety of cloudy rocky planets, and increase our confidence in future simulations of temperature profile and net energy balance.

Thomas Fauchez↗
NASA NTRSDate not supplied

Ocean and Earth System Modelling

Petascale supercomputing infrastructure + modelling and analysis capabilities + interdisciplinary upper-ocean expertise Multiscale ocean turbulence simulation Physical-biogeochemical interactions Analysis of large data sets from remote sensing and Earth system model ensembles

Ocean↗
NASA NTRS2021

Earth system modeling: can we stay ahead of what's actually happening?

Over the last forty years, Earth System Models have become more and more comprehensive and detailed. They have assimilated previously independent modeling efforts in ocean circulation, atmospheric composition, the stratosphere, land surface, and the cryosphere, and are today demonstrably more skillful than earlier efforts. Yet the structural uncertainty in the latest model projections is actually increasing. Meanwhile, impacts of climate change on, for instance, wildfires, tropical cyclones and sea level, appear to be increasing faster than we have been able to predict. I will address some of the current issues at the bleeding edges of model development and the continuing importance of model evaluation.

Gavin A Schmidt↗
NASA NTRS2017

Reduced ENSO Variability at the LGM Revealed by an Isotope-Enabled Earth System Model

Studying the El Nino Southern Oscillation (ENSO) in the past can help us better understand its dynamics and improve its future projections. However, both paleoclimate reconstructions and model simulations of ENSO strength at the Last Glacial Maximum (LGM; 21 ka B.P.) have led to contradicting results. Here we perform model simulations using the recently developed water isotope-enabled Community Earth System Model (iCESM). For the first time, model-simulated oxygen isotopes are directly compared with those from ENSO reconstructions using the individual foraminifera analysis (IFA). We find that the LGM ENSO is most likely weaker comparing with the preindustrial. The iCESM suggests that total variance of the IFA records may only reflect changes in the annual cycle instead of ENSO variability as previously assumed. Furthermore, the interpretation of subsurface IFA records can be substantially complicated by the habitat depth of thermocline-dwelling foraminifera and their vertical migration with a temporally varying thermocline.

El Niño–Southern Oscillation;isotope-enabled si↗
NASA NTRS2024

Assessing Acetone for the GISS ModelE2.1 Earth System Model

Acetone is an abundant volatile organic compound (VOC) in the atmosphere, with important influences on ozone and oxidation capacity. Direct sources include chemical production from other VOCs and anthropogenic emissions, terrestrial vegetation, biomass-burning emissions, and ocean production. Sinks include chemical loss, deposition onto the land surface, and ocean uptake. Acetone also has a lifetime that is long enough to allow transport and reactions with other compounds remote from its sources. The NASA Goddard Institute for Space Studies (GISS) Earth system model ModelE2.1 simulates a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a more sophisticated acetone scheme in which acetone is a full 3-dimensional tracer with explicit sources, sinks, and atmospheric transport. We first evaluate the new global acetone budget in the context of past literature. Estimated source and sink fluxes fall within the range of previous models, although total atmospheric burden and lifetime are at the lower end of the published literature. Acetone's new representation in ModelE2.1 also results in more realistic spatial and vertical distributions, which we compare against previous models and field observations. The seasonality of acetone-related processes was also studied in conjunction with field measurements, and these comparisons show promising agreement but also shortcomings at high-emission urban locations, where the model's resolution is too coarse to capture the true behavior. Finally, we conduct a variety of sensitivity studies that explore the influence of key parameters on the acetone budget and its global distribution. An impactful finding is that the production of acetone from precursor hydrocarbon oxidation has strong leverage on the overall chemical source, indicating the importance of accurate molar yields. Overall, our implementation is one that corroborates with previous studies and marks a significant improvement in the development of the acetone tracer in GISS ModelE2.1.

Acetone↗
NASA NTRS1979

Modeling the Earth's radiation belts. A review of quantitative data based electron and proton models

The evolution of quantitative models of the trapped radiation belts is traced to show how the knowledge of the various features has developed, or been clarified, by performing the required analysis and synthesis. The Starfish electron injection introduced problems in the time behavior of the inner zone, but this residue decayed away, and a good model of this depletion now exists. The outer zone electrons were handled statistically by a log normal distribution such that above 5 Earth radii there are no long term changes over the solar cycle. The transition region between the two zones presents the most difficulty, therefore the behavior of individual substorms as well as long term changes must be studied. The latest corrections to the electron environment based on new data are outlined. The proton models have evolved to the point where the solar cycle effect at low altitudes is included. Trends for new models are discussed; the feasibility of predicting substorm injections and solar wind high-speed streams make the modeling of individual events a topical activity.

Vette, J. I.↗
NASA NTRS1988

Evaluation of advanced geopotential models for operational orbit determination

To meet future orbit determination accuracy requirements for different NASA projects, analyses are performed using Tracking and Data Relay Satellite System (TDRSS) tracking measurements and orbit determination improvements in areas such as the modeling of the Earth's gravitational field. Current operational requirements are satisfied using the Goddard Earth Model-9 (GEM-9) geopotential model with the harmonic expansion truncated at order and degree 21 (21-by-21). This study evaluates the performance of 36-by-36 geopotential models, such as the GEM-10B and Preliminary Goddard Solution-3117 (PGS-3117) models. The Earth Radiation Budget Satellite (ERBS) and LANDSAT-5 are the spacecraft considered in this study.

Radomski, M. S.↗
NASA NTRS2008

Earth Global Reference Atmospheric Model 2007 (Earth-GRAM07)

GRAM is a Fortran software package that can run on a variety of platforms including PC's. GRAM provides values of atmospheric quantities such as temperature, pressure, density, winds, constituents, etc. GRAM99 covers all global locations, all months, and heights from the surface to approx. 1000 km). Dispersions (perturbations) of these parameters are also provided and are spatially and temporally correlated. GRAM can be run in a stand-alone mode or called as a subroutine from a trajectory program. GRAM07 is diagnostic, not prognostic (i.e., it describes the atmosphere, but it does not forecast). The source code is distributed free-of-charge to eligible recipients.

Leslie, Fred W.↗
NASA NTRS1994

Approaches of comparison for clear-sky radiative fluxes from general circulation models with Earth Radiation Budget Experiment data

In order to compare the clear-sky greenhouse effect and cloud-radiative forcing from general circulation models with Earth Radiation Budget Experiments (ERBE) data, it is necessary to calculate the general circulation model (GCM) clear-sky radiative fluxes in a way consistent with ERBE. This study discusses problems associated with the available methods for clear-sky radiative flux computations in GCMs and proposes a new approach, which uses a statistical relationship between the grid cloud cover and the availability of ERBE clear-sky measurement, established from ERBE pixel data, to sample the model radiative fluxes. Calculations with version 2 of the National Center for Atmospheric Research (NCAR) Community Climate Model using observed sea surface temperature (SST) show good agreement of clear-sky sampling from the proposed method with ERBE sampling. It is also shown that large improvements are achieved in the spatial variability of the model clear-sky radiative fluxes over ocean, with reference to ERBE, by using the new clear-sky sampling method.

Zhang, M. H.↗
NASA NTRS2021

Evaluation of SO2, SO4(2−) and an Updated SO2 Dry Deposition Parameterization in the United Kingdom Earth System Model

In this study we evaluate simulated surface SO2 and sulphate (SO4(2-)) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground based measurement networks in the USA and Europe for the period 1987 to 2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO4(2-) in both Europe and the USA over the period 1987 to 2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3, while under-predicting surface SO4(2-) concentrations by 25-35%. In the cleaner western USA, the model over-predicts both surface SO2 and SO4(2-) concentrations by a factor of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO4(2-) concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model’s global performance, finding that UKESM1 over predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model’s SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO(sup 2-)(sub 4). In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the models over prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations the simulated surface SO4(2-) concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase.

SO2↗