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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Three-Dimensional Model Synthesis of the Global Methane Cycle

A synthesis of the global methane cycle is presented to attempt to generate an accurate global methane budget. Methane-flux measurements, energy data, and agricultural statistics are merged with databases of land-surface characteristics and anthropogenic activities. The sources and sinks of methane are estimated based on atmospheric methane composition and variations, and a global 3D transport model simulates the corresponding atmospheric responses. The geographic and seasonal variations of candidate budgets are compared with observational data, and the available observations are used to constrain the plausible methane budgets. The preferred budget includes annual destruction rates and annual emissions for various sources. The lack of direct flux measurements in the regions of many of these fluxes makes the unique determination of each term impossible. OH oxidation is found to be the largest single term, although more measurements of this and other terms are recommended.

Fung, I.↗
NASA NTRS2023

Probabilistic Hydrological Estimation of LandSlides (PHELS): Global Ensemble Landslide Hazard Modelling

In this study we present a model for the global Probabilistic Hydrological Estimation of LandSlides (PHELS). PHELS estimates the daily hazard of hydrologically triggered landslides at a coarse spatial resolution of 36 km, by combining landslide susceptibility (LSS) and (percentiles of) hydrological variable(s). The latter include daily rainfall, a 7-day antecedent rainfall index (ARI7) or root-zone soil moisture content (rzmc) as hydrological predictor variables, or the combination of rainfall and rzmc. The hazard estimates with any of these predictor variables have areas under the receiver operating characteristic curve (AUC) above 0.68. The best performance was found with combined rainfall and rzmc predictors (AUC = 0.79), which resulted in the lowest number of missed alarms (especially during spring) and false alarms. Furthermore, PHELS provides hazard uncertainty estimates by generating ensemble simulations based on repeated sampling of LSS and the hydrological predictor variables. The estimated hazard uncertainty follows the behaviour of the input variable uncertainties, is about 13.6 % of the estimated hazard value on average across the globe and in time and is smallest for very low and very high hazard values.

Anne Felsberg↗
NASA NTRS2022

3-D Atmospheric Modeling of the Global Budget of N2O and its Isotopologues for 1980-2019: The Impact of Anthropogenic Emissions

Nitrous oxide (N2O) is the third most important anthropogenic greenhouse gas (GHG) and a major ozone-depleting substance (ODS). Its main sources include anthropogenic activities (mostly agriculture) and natural emissions from ocean and soils. However, emission estimates for individual sources are highly variable due to uncertainties in N2O lifetime estimates and partitioning among sources. We derive annual global N2O emissions for 1990-2019 using NOAA Global Monitoring Laboratory (GML) surface N2O observations and the N2O lifetime calculated in the NASA GEOS-5 chemistry climate model (CCM). The inferred global mean N2O emissions has gradually increased from ~15.8 TgN/yr in the early 1990s to ~17.8 TgN/yr in the 2010s. This implies that anthropogenic N2O emissions have grown rapidly from ~6.7 TgN/yr in the 1990s to about ~8.7 TgN/yr in the 2010s, a ~30% increase. With specially designed N2O isotopic tracers in 3-D GEOSCCM, we estimate that, on global average, stratospheric enrichment contributes about +7.7‰/yr, +7.6‰/yr, +8.0‰/yr to tropospheric N(sup α)-δ(sup 15), N(sup β)-δ(sup 15), and O-δ(sup 18) budget, respectively. To balance the global mean isotopic signature for pre-industrial terrestrial sources of N(sup α)-δ(sup 15) ~ 6.7‰, N(sup β)-δ(sup 15) ~ -12.6‰, O-δ(sup 18) ~ 35.4‰, our 3-D isotopic budget simulation using the GEOSCCM suggests global mean anthropogenic isotopic signatures in the recent decades are N(sup α)-δ(sup 15) ~ -18‰, N(sup β)-δ(sup 15) ~ -20‰, O-δ(sup 18) ~ 19‰. These anthropogenic isotopic estimates are significantly lighter than results from one-box atmospheric model-based estimates with the largest difference seen for N(sup β)-δ(sup 15). More surface isotopic measurements are needed to better quantify the N2O isotopic signatures.

Nitrous oxide↗
NASA NTRS1975

Revised Perturbation Statistics for the Global Scale Atmospheric Model

Magnitudes and scales of atmospheric perturbations about the monthly mean for the thermodynamic variables and wind components are presented by month at various latitudes. These perturbation statistics are a revision of the random perturbation data required for the global scale atmospheric model program and are from meteorological rocket network statistical summaries in the 22 to 65 km height range and NASA grenade and pitot tube data summaries in the region up to 90 km. The observed perturbations in the thermodynamic variables were adjusted to make them consistent with constraints required by the perfect gas law and the hydrostatic equation. Vertical scales were evaluated by Buell's depth of pressure system equation and from vertical structure function analysis. Tables of magnitudes and vertical scales are presented for each month at latitude 10, 30, 50, 70, and 90 degrees.

Justus, C. G.↗
DOE OSTI2024

Performance Results on CPU/GPU Exascale Architectures for OMEGA: The Ocean Model for E3SM Global Applications

The US Department of Energy (DOE) conducts climate simulations on some of the world’s largest supercomputers. These exascale machines use heterogeneous architectures with both CPUs and GPUs, and scientific codes must adapt to make full use of this computing power. Los Alamos National Lab is developing Omega: The Ocean Model for E3SM Global Applications, which is specifically designed for modern exascale computers. It uses external libraries that have been optimized for a variety of architectures to run on different supercomputers. Omega is an unstructured-mesh ocean model based on TRiSK numerical methods. It will be the new ocean component of the DOE’s Energy Exascale Earth System Model (E3SM). The algorithms in Omega follow those of the current ocean component, MPAS-Ocean, but it will be written in C++ rather than Fortran to take advantage of the Kokkos performance portability library. Omega spatial operators are written as Kokkos kernels to run efficiently on both CPUs and GPUs. Work on Omega began in 2023 with a new C++ framework for unstructured mesh partitioning, halo exchanges, parallel IO, and Kokkos interfaces. The current version, Omega-0, is being developed to solve the shallow water equations and at present includes all of the tendency terms but not time stepping. Here we share the results of Omega-0 verification and performance testing. Verification includes unit tests implemented with CTest as well as convergence tests in Polaris, an in-house python package with a large suite of test problems. Performance tests compare simulations conducted on CPUs versus GPUs and across different architectures: tests are run on Frontier, which has AMD “Optimized 3rd Gen EPYC” CPUs and AMD MI250X GPUs, as well as Perlmutter, which is composed of AMD EPYC 7763 CPUs and NVIDIA A100 GPUs.

58 GEOSCIENCES↗
DOE OSTI2021

Regional-scale, sector-specific evaluation of global CO2 inversion models using aircraft data from the ACT-America project

We use vertical profiles of airborne measurements of CO2 from frontal cases during the summer 2016 Atmospheric Carbon and Transport – America (ACT-America) campaign to evaluate the skill of a set of ten global CO2 inversion models participating in the Orbiting Carbon Observatory – 2 (OCO-2) Model Intercomparison Project (MIP). Model errors and biases (model minus observation) were categorized by region (Mid-Atlantic, Midwest, and South), frontal sector (warm or cold), and transport model (predominantly Tracer Model 5 (TM5) and Goddard Earth Observing System – Chemistry (GEOS-Chem)). Overall, the inversions reproduce the general structures of the observed vertical profiles and the enhanced / depleted low-level CO2 in warm / cold sectors, but tend to underestimate the magnitude of the sector difference in each region. In the Midwest and South warm sectors, inversion biases were about 1 ppm above 1500 m AGL, though model spread (quantified by interquartile range) was often even smaller; below 1500 m AGL, model biases were negative and about -2 ppm near the surface. For the Midwest and South cold sectors, models had +2-3 ppm biases below 1500 m AGL, but with comparable model spread. Uniquely, in the Mid-Atlantic there was a consistent difference between TM5 and GEOS-Chem mole fractions for both sectors up to 3000 m AGL (TM5 lower by 2 ppm), on the order of the observation-relative biases. In the MidAtlantic TM5 inversions had negative biases in warm sectors, while GEOS-Chem inversions had positive biases in cold sectors. Possible reasons for the regional variability are discussed.

Gaudet, Brian J.↗
NASA NTRS1979

M2, S2, K1 models of the global ocean tide

Ocean tidal signals appear in many geophysical measurements. Geophysicists need realistic tidal models to aid in interpretation of their data. Because of the closeness to resonance of dissipationless ocean tides, it is difficult for numerical models to correctly represent the actual open ocean tide. As an approximate solution to this problem, test functions derived by solving Laplace's Tidal Equations with ocean loading and self gravitation are used as a basis for least squares dynamic interpolation of coastal and island tidal data for the constituents M2, S2, and Kl. The resulting representations of the global tide are stable over at least a ?5% variation in the mean depth of the model basin, and they conserve mass. Maps of the geocentric tide, the induced free space potential, the induced vertical component of the solid earth tide, and the induced vertical component of the gravitational field for each contituent are presented.

Parke, M. E.↗
NASA NTRS2004

Characterization of Transport Errors in Chemical Forecasts from a Global Tropospheric Chemical Transport Model

We propose a new methodology to characterize errors in the representation of transport processes in chemical transport models. We constrain the evaluation of a global three-dimensional chemical transport model (GEOS-CHEM) with an extended dataset of carbon monoxide (CO) concentrations obtained during the Transport and Chemical Evolution over the Pacific (TRACE-P) aircraft campaign. The TRACEP mission took place over the western Pacific, a region frequently impacted by continental outflow associated with different synoptic-scale weather systems (such as cold fronts) and deep convection, and thus provides a valuable dataset. for our analysis. Model simulations using both forecast and assimilated meteorology are examined. Background CO concentrations are computed as a function of latitude and altitude and subsequently subtracted from both the observed and the model datasets to focus on the ability of the model to simulate variability on a synoptic scale. Different sampling strategies (i.e., spatial displacement and smoothing) are applied along the flight tracks to search for systematic model biases. Statistical quantities such as correlation coefficient and centered root-mean-square difference are computed between the simulated and the observed fields and are further inter-compared using Taylor diagrams. We find no systematic bias in the model for the TRACE-P region when we consider the entire dataset (i.e., from the surface to 12 km ). This result indicates that the transport error in our model is globally unbiased, which has important implications for using the model to conduct inverse modeling studies. Using the First-Look assimilated meteorology only provides little improvement of the correlation, in comparison with the forecast meteorology. These general statements can be refined when the entire dataset is divided into different vertical domains, i.e., the lower troposphere (less than 2 km), the middle troposphere (2-6 km), and the upper troposphere (greater than 6 km). The best agreement between the observations and the model is found in the lower and middle troposphere. Downward displacements in the lower troposphere provide a better fit with the observed value, which could indicate a problem in the representation of boundary layer height in the model. Significant improvement is also found for downward and southward displacements in the upper troposphere. There are several potential sources of errors in our simulation of the continental outflow in the upper troposphere which could lead to such biases, including the location and/or the strength of deep convective cells as well as that of wildfires in Southeast Asia.

Bey, I.↗
DOE OSTI2020

Investigating the Atmospheric Sources and Sinks of Perfluorooctanoic Acid Using a Global Chemistry Transport Model

Perfluorooctanoic acid, PFOA, is one of the many concerning pollutants in our atmosphere; it is highly resistant to environmental degradation processes, which enables it to accumulate biologically. With direct routes of this chemical to the environment decreasing, as a consequence of the industrial phase out of PFOA, it has become more important to accurately model the effects of indirect production routes, such as environmental degradation of precursors; e.g., fluorotelomer alcohols (FTOHs). The study reported here investigates the chemistry, physical loss and transport of PFOA and its precursors, FTOHs, throughout the troposphere using a 3D global chemical transport model, STOCHEM-CRI. Furthermore, this investigation includes an important loss process of PFOA in the atmosphere via the addition of the stabilised Criegee intermediates, hereby referred to as the “Criegee Field.” Whilst reaction with Criegee intermediates is a significant atmospheric loss process of PFOA, it does not result in its permanent removal from the atmosphere. Additionally, the atmospheric fate of the resultant hydroperoxide product from the reaction of PFOA and Criegee intermediates resulted in a ≈0.04 Gg year-1 increase in the production flux of PFOA. Furthermore, the physical loss of the hydroperoxide product from the atmosphere (i.e., deposition), whilst decreasing the atmospheric concentration, is also likely to result in the reformation of PFOA in environmental aqueous phases, such as clouds, precipitation, oceans and lakes. As such, removal facilitated by the “Criegee Field” is likely to simply result in the acceleration of PFOA transfer to the surface (with an expected decrease in PFOA atmospheric lifetime of ≈10 h, on average from ca. 80 h without Criegee loss to 70 h with Criegee loss).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Traveling Weather Disturbances in Mars Southern Extratropics: Sway of the Great Impact Basins

As on Earth, between late autumn and early spring on Mars middle and high latitudes within its atmosphere support strong mean thermal contrasts between the equator and poles (i.e. "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e. transient synoptic-period waves). Within a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, such large-scale, extratropical weather disturbances are critical components of the global circulation. These wave-like disturbances act as agents in the transport of heat and momentum, and moreover generalized tracer quantities (e.g., atmospheric dust, water vapor and water-ice clouds) between low and high latitudes of the planet. The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a high-resolution Mars global climate model (Mars GCM). This global circulation model imposes interactively lifted (and radiatively active) dust based on a threshold value of the instantaneous surface stress. Compared to observations, the model exhibits a reasonable "dust cycle" (i.e. globally averaged, a more dusty atmosphere during southern spring and summer occurs). In contrast to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense synoptically. Influences of the zonally asymmetric (i.e. east-west varying) topography on southern large-scale weather disturbances are examined. Simulations that adapt Mars' full topography compared to simulations that utilize synthetic topographies emulating essential large-scale features of the southern middle latitudes indicate that Mars' transient barotropic/baroclinic eddies are significantly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). In addition, the occurrence of a southern storm zone in late winter and early spring is keyed particularly to the western hemisphere via orographic influences arising from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate fundamental differences amongst such simulations and these are described.

Weather disturbances↗
DOE OSTI2022

Machine Learning for Improving Surface-Layer-Flux Estimates

Abstract Flows in the atmospheric boundary layer are turbulent, characterized by a large Reynolds number, the existence of a roughness sublayer and the absence of a well-defined viscous layer. Exchanges with the surface are therefore dominated by turbulent fluxes. In numerical models for atmospheric flows, turbulent fluxes must be specified at the surface; however, surface fluxes are not known a priori and therefore must be parametrized. Atmospheric flow models, including global circulation, limited area models, and large-eddy simulation, employ Monin–Obukhov similarity theory (MOST) to parametrize surface fluxes. The MOST approach is a semi-empirical formulation that accounts for atmospheric stability effects through universal stability functions. The stability functions are determined based on limited observations using simple regression as a function of the non-dimensional stability parameter representing a ratio of distance from the surface and the Obukhov length scale (Obukhov in Trudy Inst Theor Geofiz AN SSSR 1:95–115, 1946), $$z/L$$ z / L . However, simple regression cannot capture the relationship between governing parameters and surface-layer structure under the wide range of conditions to which MOST is commonly applied. We therefore develop, train, and test two machine-learning models, an artificial neural network (ANN) and random forest (RF), to estimate surface fluxes of momentum, sensible heat, and moisture based on surface and near-surface observations. To train and test these machine-learning algorithms, we use several years of observations from the Cabauw mast in the Netherlands and from the National Oceanic and Atmospheric Administration’s Field Research Division tower in Idaho. The RF and ANN models outperform MOST. Even when we train the RF and ANN on one set of data and apply them to the second set, they provide more accurate estimates of all of the fluxes compared to MOST. Estimates of sensible heat and moisture fluxes are significantly improved, and model interpretability techniques highlight the logical physical relationships we expect in surface-layer processes.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Global tuning of hadronic interaction models with accelerator-based and astroparticle data

In high-energy and astroparticle physics, event generators play an essential role, even in the simplest data analyses. As analysis techniques become more sophisticated, e.g. based on deep neural networks, their correct description of the observed event characteristics becomes even more important. Physical processes occurring in hadronic collisions are simulated within a Monte Carlo framework. A major challenge is the modeling of hadron dynamics at low momentum transfer, which includes the initial and final phases of every hadronic collision. QCD-inspired phenomenological models used for these phases cannot guarantee completeness or correctness over the full phase space. These models usually include parameters which must be tuned to suitable experimental data. Until now, event generators have been developed and tuned mainly on the basis of data from high-energy physics experiments at accelerators. The wealth of data available from the latest generation of astroparticle experiments has not yet been fully exploited, and in many cases is not satisfactorily described. Both kinds of data sets are complementary as astroparticle experiments provide sensitivity especially to hadrons produced nearly parallel to the collision axis and cover center-of-mass energies up to several hundred TeV, well beyond those reached at colliders so far. In this report, we provide an overview of state-of-the-art event generators and their tuning, including the most relevant inputs from high-energy accelerator and astroparticle experiments. We present a road map that shows, for the first time, how the unified tuning of event generators with accelerator-based and astroparticle data can be performed.

Albrecht, J. [Ruhr U., Bochum, RAPP Ctr.; Ruhr U.,↗
NASA NTRSDate not supplied

Improving Simulation of Irrigation in a Global Land Surface Model

Studies have shown that irrigated agriculture has substantial effects on local to regional hydrologic and atmospheric processes. These effects include increased evapotranspiration and near surface humidity, decreased air and ground temperature, augmented downwind precipitation, enhanced recharge, depletion of source water stocks, and overall changes to the regional water budget. However, developers of global offline and coupled modeling systems have been slow to incorporate irrigation. This presentation will describe progress towards simulating irrigation worldwide in the Land Information System (LIS) and Global Land Data Assimilation System (GLDAS). We have developed and refined the ability to simulate sprinkler irrigation, furrow irrigation, paddy irrigation, and drip irrigation. We have reconciled multiple global and national irrigation, land cover, and crop type databases in an effort to (1) distinguish irrigated and rainfed agriculture, (2) simulate the proper distribution of crops (as sub-grid tiles) in each model grid pixel, and (3) apply the most likely irrigation method in each tile based on the crop type and country or state level information on the relative usage of sprinkler, flood, and drip irrigation. Using agricultural water withdrawal data, as available, for calibration and evaluation, we show that the implemented approach is promising but that much fine tuning remains to be done. In particular, irrigation model parameters that produce good results in one location often produce less satisfying results in others.

Matthew Rodell↗
NASA NTRS1996

Numerical Modeling of the Global Atmosphere

Under this grant, we continued development and evaluation of the updraft downdraft model for cumulus parameterization. The model includes the mass, rainwater and vertical momentum budget equations for both updrafts and downdrafts. The rainwater generated in an updraft falls partly inside and partly outside the updraft. Two types of stationary solutions are identified for the coupled rainwater budget and vertical momentum equations: (1) solutions for small tilting angles, which are unstable; (2) solutions for large tilting angles, which are stable. In practical applications, we select the smallest stable tilting angle as an optimum value. The model has been incorporated into the Arakawa-Schubert (A-S) cumulus parameterization. The results of semi-prognostic and single-column prognostic tests of the revised A-S parameterization show drastic improvement in predicting the humidity field. Cheng and Arakawa presents the rationale and basic design of the updraft-downdraft model, together with these test results. Cheng and Arakawa, on the other hand gives technical details of the model as implemented in current version of the UCLA GCM.

Arakawa, Akio↗
DOE OSTI2024

An improved semi-global intrinsic kinetics model for high temperature carbon oxidation

Measurements of the oxidation rates of various forms of carbon (soot, graphite, coal char) have often shown an unexplained attenuation with increasing temperatures in the vicinity of 2000 K, even when accounting for diffusional transport limitations and gas-phase chemical effects (e.g. CO 2 dissociation). With the development of oxy-fuel combustion approaches for pulverized coal utilization with carbon capture, high particle temperatures are readily achieved in sufficiently oxygen-enriched environments. Here, in this work, a new semi-global intrinsic kinetics model for high temperature carbon oxidation is created by starting with a previously developed 5-step mechanism that was shown to reproduce all major known trends in carbon oxidation, except for its high temperature kinetic falloff, and incorporating a recently discovered surface oxide decomposition step. The predictions of this new model are benchmarked by deploying the kinetic model in a steady-state reacting particle code (SKIPPY) and comparing the simulated results against a carefully measured set of pulverized coal char combustion temperature measurements over a wide range of oxygen concentrations in N 2 and CO 2 environments. The results show that the inclusion of the spontaneous surface oxide decomposition reaction step significantly improves predictions at high particle temperatures. Furthermore, the simulations reveal that O atoms released from the oxide decomposition step enhance the radical pool in the near-surface region and within the particle interior itself. Incorporation of literature rates for O and OH reactions with the carbon surface results in a reduction in the predicted radical pool concentrations and a very minor enhancement of the overall carbon oxidation rate.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1999

Global Core Plasma Model

Over 40 years of ground and spacecraft plasmaspheric measurements have resulted in many statistical descriptions of plasmaspheric properties. In some cases, these properties have been represented as analytical descriptions that are valid for specific regions or conditions. For the most part, what has not been done is to extend regional empirical descriptions or models to the plasmasphere as a whole. In contrast, many related investigations depend on the use of representative plasmaspheric conditions throughout the inner magnetosphere. Wave propagation, involving the transport of energy through the magnetosphere, is strongly affected by thermal plasma density and its composition. Ring current collisional and wave particle losses also strongly depend on these quantities. Plasmaspheric also plays a secondary role in influencing radio signals from the Global Positioning System satellites. The Global Core Plasma Model (GCPM) is an attempt to assimilate previous empirical evidence and regional models for plasmaspheric density into a continuous, smooth model of thermal plasma density in the inner magnetosphere. In that spirit, the International Reference Ionosphere is currently used to complete the low altitude description of density and composition in the model. The models and measurements on which the GCPM is currently based and its relationship to IRI will be discussed.

Gallagher, Dennis L.↗