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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2

In the Energy Exascale Earth System Model (E3SM) Multi-scale Modeling Framework (MMF), where parameterizations of convection and turbulence are replaced by a 2-D cloud-resolving model (CRM), there are multiple options to represent land–atmosphere interactions. Here, we propose three different coupling strategies, namely the (1) coupling of a single land surface model to the global grid (MMF), (2) coupling a single land copy directly to the embedded CRM (SFLX2CRM), and (3) coupling a single copy of land model to each column of the CRM grid (MAML). In the MAML (Multi-Atmosphere Multi-Land) framework, a land model is coupled to CRM at the CRM-grid scale by coupling an individual copy of a land model to each CRM grid. Therefore, we can represent intra-CRM heterogeneity in the land–atmosphere interaction processes. There are 5-year global simulations run using these three coupling strategies, and we find some regional differences but overall small changes with respect to whether a land model is coupled to CRM or a global atmosphere. In MAML, the spatial heterogeneity within CRM induces stronger turbulence, which leads to the changes in soil moisture, surface heat fluxes, and precipitation. However, the differences in the MAML from the other two cases are rather weak, suggesting that the impact of using MAML does not justify the increase in cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

QuadTune version 1: a regional tuner for global atmospheric models

When a new, better-formulated physical parameterization is introduced into a global atmospheric model, aspects of the global model solutions are sometimes degraded. Then, in order to use the new global model to address science questions, there is an incentive to restore its accuracy. Oftentimes this restoration is achieved by tuning of model parameter values. Unfortunately, the retuning process is expensive because characterizing the parameter dependence requires numerous time-consuming global simulations. To reduce the cost of tuning, this manuscript introduces a “poor man's” model tuner, “QuadTune”. QuadTune carves the globe into regions and approximates the model parameter dependence through the use of an uncorrelated quadratic emulator (i.e., response surface). The simplicity of the emulator reduces the required number of global model simulations and aids explainability of tuner behavior. Tuning removes parametric error but leaves behind model structural error. Structural error manifests itself as regional residual biases, such as stubborn biases and tuning trade-offs. To visualize these residual biases, QuadTune's software includes a set of diagnostic plots. This paper illustrates the use of the plots for characterizing residual biases with an example tuning problem.

Environmental sciences↗
DOE OSTI2015

Evaluation of cloud-resolving model simulations of midlatitude cirrus with ARM and A-train observations

Cirrus clouds are ubiquitous in the upper troposphere and still constitute one of the largest uncertainties in climate predictions. Our paper evaluates cloud-resolving model (CRM) and cloud system-resolving model (CSRM) simulations of a midlatitude cirrus case with comprehensive observations collected under the auspices of the Atmospheric Radiation Measurements (ARM) program and with spaceborne observations from the National Aeronautics and Space Administration A-train satellites. The CRM simulations are driven with periodic boundary conditions and ARM forcing data, whereas the CSRM simulations are driven by the ERA-Interim product. Vertical profiles of temperature, relative humidity, and wind speeds are reasonably well simulated by the CSRM and CRM, but there are remaining biases in the temperature, wind speeds, and relative humidity, which can be mitigated through nudging the model simulations toward the observed radiosonde profiles. Simulated vertical velocities are underestimated in all simulations except in the CRM simulations with grid spacings of 500 m or finer, which suggests that turbulent vertical air motions in cirrus clouds need to be parameterized in general circulation models and in CSRM simulations with horizontal grid spacings on the order of 1 km. The simulated ice water content and ice number concentrations agree with the observations in the CSRM but are underestimated in the CRM simulations. The underestimation of ice number concentrations is consistent with the overestimation of radar reflectivity in the CRM simulations and suggests that the model produces too many large ice particles especially toward the cloud base. Simulated cloud profiles are rather insensitive to perturbations in the initial conditions or the dimensionality of the model domain, but the treatment of the forcing data has a considerable effect on the outcome of the model simulations. Despite considerable progress in observations and microphysical parameterizations, simulating the microphysical, macrophysical, and radiative properties of cirrus remains challenging. Comparing model simulations with observations from multiple instruments and observational platforms is important for revealing model deficiencies and for providing rigorous benchmarks. But, there still is considerable need for reducing observational uncertainties and providing better observations especially for relative humidity and for the size distribution and chemical composition of aerosols in the upper troposphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A consistent prescription of stratospheric aerosol for both radiation and chemistry in the Community Earth System Model (CESM1)

Here we describe an updated parameterization for prescribing stratospheric aerosol in the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1). The need for a new parameterization is motivated by the poor response of the CESM1 (formerly referred to as the Community Climate System Model, version 4, CCSM4) simulations contributed to the Coupled Model Intercomparison Project 5 (CMIP5) to colossal volcanic perturbations to the stratospheric aerosol layer (such as the 1991 Pinatubo eruption or the 1883 Krakatau eruption) in comparison to observations. In particular, the scheme used in the CMIP5 simulations by CESM1 simulated a global mean surface temperature decrease that was inconsistent with the GISS Surface Temperature Analysis (GISTEMP), NOAA's National Climatic Data Center, and the Hadley Centre of the UK Met Office (HADCRUT4). The new parameterization takes advantage of recent improvements in historical stratospheric aerosol databases to allow for variations in both the mass loading and size of the prescribed aerosol. An ensemble of simulations utilizing the old and new schemes shows CESM1's improved response to the 1991 Pinatubo eruption. Most significantly, the new scheme more accurately simulates the temperature response of the stratosphere due to local aerosol heating. Here, results also indicate that the new scheme decreases the global mean temperature response to the 1991 Pinatubo eruption by half of the observed temperature change, and modelled climate variability precludes statements as to the significance of this change.

58 GEOSCIENCES↗
DOE OSTI2014

Atomistic simulation study of short pulse laser interactions with a metal target under conditions of spatial confinement by a transparent overlayer

The distinct characteristics of short pulse laser interactions with a metal target under conditions of spatial confinement by a solid transparent overlayer are investigated in a series of atomistic simulations. The simulations are performed with a computational model combining classical molecular dynamics (MD) technique with a continuum description of the laser excitation, electron-phonon equilibration, and electronic heat transfer based on two-temperature model (TTM). Two methods for incorporation of the description of a transparent overlayer into the TTM-MD model are designed and parameterized for Ag-silica system. The material response to the laser energy deposition is studied for a range of laser fluences that, in the absence of the transparent overlayer, covers the regimes of melting and resolidification, photomechanical spallation, and phase explosion of the overheated surface region. In contrast to the irradiation in vacuum, the spatial confinement by the overlayer facilitates generation of sustained high-temperature and high-pressure conditions near the metal-overlayer interface, suppresses the generation of unloading tensile wave, decreases the maximum depth of melting, and prevents the spallation and explosive disintegration of the surface region of the metal target. At high laser fluences, when the laser excitation brings the surface region of the metal target to supercritical conditions, the confinement prevents the expansion and phase decomposition characteristic for the vacuum conditions leading to a gradual cooling of the hot compressed supercritical fluid down to the liquid phase and eventual solidification. The target modification in this case is limited to the generation of crystal defects and the detachment of the metal target from the overlayer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

On the Dependence of Simulated Convection on Domain Size in CRMs

Abstract We present a heuristic model to explain the suppression of deep convection in convection‐resolving models (CRMs) with a small number of grid columns, such as those used in super‐parameterized or multi‐scale modeling framework (MMF) general circulation models (GCM) of the atmosphere. Domains with few grid columns require greater instability to sustain convection because they force a large convective fraction, driving strong compensating subsidence warming. Updraft dilution, which is stronger for reduced horizontal grid spacing, enhances this effect. Thus, suppression of deep convection in CRMs with few grid columns can be reduced by increasing grid spacing. Radiative‐convective equilibrium simulations using standalone CRM simulations with the System for Atmospheric Modeling (SAM) and using GCM‐coupled CRM simulations with the Energy Exascale Earth System Model (E3SM)‐MMF confirm the heuristic model results.

CRM↗
DOE OSTI2018

Improving Bulk Microphysics Schemes for Deep Convective Systems Using MC3E Data (Final Report)

The centerpiece of the accomplishments under this (and related) grants is the increased knowledge of the capabilities of cloud-resolving models of convective systems, and their associated microphysics, especially of the biases of those models and their microphysics parameterization. Dr. Varble's leadership has been focused especially on the careful comparison of advanced model results with equally advanced observations to uncover and elucidate model successes, but clearly uncovering instances of model biases, in a way that suggests ways of overcoming those biases, toward model improvement in the future. Even a glance at the titles of the papers below will reveal the central significance of these advances; if desired, however, this report can be expanded upon request to discuss these advances in greater detail.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

LOCAL SIMULATIONS OF INSTABILITIES DRIVEN BY COMPOSITION GRADIENTS IN THE ICM

The distribution of helium in the intracluster medium (ICM) permeating galaxy clusters is not well constrained due to the very high plasma temperature. Therefore, the plasma is often assumed to be homogeneous. A nonuniform helium distribution can, however, lead to biases when measuring key cluster parameters. This has motivated one-dimensional models that evolve the ICM composition assuming that the effects of magnetic fields can be parameterized or ignored. Such models for nonisothermal clusters show that helium can sediment in the cluster core, leading to a peak in concentration offset from the cluster center. The resulting profiles have recently been shown to be linearly unstable when the weakly collisional character of the magnetized plasma is considered. In this paper, we present a modified version of the MHD code Athena, which makes it possible to evolve a weakly collisional plasma subject to a gravitational field and stratified in both temperature and composition. We thoroughly test our implementation and confirm excellent agreement against several analytical results. In order to isolate the effects of composition, in this initial study we focus our attention on isothermal plasmas. We show that plasma instabilities, feeding off gradients in composition, can induce turbulent mixing and saturate by rearranging magnetic field lines and alleviating the composition gradient. Composition profiles that increase with radius lead to instabilities that saturate by driving the average magnetic field inclination to roughly 45°. We speculate that this effect may alleviate the core insulation observed in homogeneous settings, with potential consequences for the associated cooling flow problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Model Light Curves for Type Ib and Ic Supernovae

Using the Monte Carlo code SEDONA, multiband photometry and spectra are calculated for supernovae derived from stripped helium stars with presupernova masses of 2.2 to 10.0 M ⊙ . The models are representative of evolution in close binaries and have previously been exploded using a parameterized one-dimensional model for neutrino transport. A subset, those with presupernova masses in the range of 2.2–5.6 M⊙, have many properties in common with observed Type Ib and Ic supernovae, including a median ejected mass near 2 M ⊙ , explosion energies near 1 × 10 51 erg, typical 56 Ni masses of 0.07–0.09 M ⊙ , peak times of about 20 days, and a narrow range for the V - R color index 10 days post-V-maximum near 0.3 mag. The median peak bolometric luminosity, near 10 42.3 erg s -1 , is fainter, however, than several observational tabulations, and the brightest explosion has a bolometric luminosity of only 10 42.50 erg s -1 . The brightest absolute B, V, and R magnitudes at peak are -17.2, -17.8, and -18.0. These limits are fainter than some allegedly typical Type Ib and Ic supernovae and could reflect problems in our models or in the observational analysis. Helium stars with lower and higher masses also produce interesting transients that may have been observed, including fast, faint, blue transients and long, red, faint Type Ic supernovae. New models are specifically presented for SN 2007Y, SN 2007gr, SN 2009jf, LSQ 13abf, SN 2008D, and SN 2010X.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Thermal X-ray spectral tools. I. Parameterizing impulsive X-ray heating with a cumulative initial temperature (CIT) distribution

In collisional ionization equilibrium, the X-ray spectrum from a plasma depends on the differential emission measure (DEM), distributed over temperature. Due to the well-known ill conditioning problem, no precisely resolved DEM can be inverted directly from the spectrum, so often only a gross parameterization of the DEM is used to approximate the data, in hopes that the parameterization can provide useful model-independent constraints on the heating process. However, ill conditioning also introduces ambiguity into the various different parameterizations that could approximate the data, which may spoil the perceived advantages of model independence. Thus, this paper instead suggests a single parameterization for both the heating mechanism and the X-ray sources, based on a model of impulsive heating followed by radiative cooling. This approach is similar to a 'cooling flow' approach but allows injection at multiple initial temperatures and applies even when the steady state is a distribution of different shock strengths, as for a standing shock with a range of obliquities, or for embedded stochastic shocks that are only steady in a statistical sense. This produces an alternative parameterization for X-ray spectra that is especially streamlined for higher density plasmas with efficient radiative cooling and minimal thermal conduction and mixing. The method also provides some internal consistency checks on the validity of its assumptions. A heuristic general version is then applied over a wide range of astrophysical applications to schematically explore potential alternative models for these phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Succinate Overproduction: A Case Study of Computational Strain Design Using a Comprehensive Escherichia coli Kinetic Model

Computational strain-design prediction accuracy has been the focus for many recent efforts through the selective integration of kinetic information into metabolic models. In general, kinetic model prediction quality is determined by the range and scope of genetic and/or environmental perturbations used during parameterization. Here, we apply the k-OptForce procedure on a kinetic model of E. coli core metabolism constructed using the Ensemble Modeling (EM) method and parameterized using multiple mutant strains data under aerobic respiration with glucose as the carbon source. Minimal interventions are identified that improve succinate yield under both aerobic and anaerobic conditions to test the fidelity of model predictions under both genetic and environmental perturbations. Under aerobic condition, k-OptForce identifies interventions that match existing experimental strategies while pointing at a number of unexplored flux re-directions such as routing glyoxylate flux through the glycerate metabolism to improve succinate yield. Many of the identified interventions rely on the kinetic descriptions that would not be discoverable by a purely stoichiometric description. In contrast, under fermentative (anaerobic) condition, k-OptForce fails to identify key interventions including up-regulation of anaplerotic reactions and elimination of competitive fermentative products. This is due to the fact that the pathways activated under anaerobic condition were not properly parameterized as only aerobic flux data were used in the model construction. This study shed light on the importance of condition-specific model parameterization and provides insight on how to augment kinetic models so as to correctly respond to multiple environmental perturbations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Impact of the dynamical core on the direct simulation of tropical cyclones in a high-resolution global model

Our paper examines the impact of the dynamical core on the simulation of tropical cyclone (TC) frequency, distribution, and intensity. The dynamical core, the central fluid flow component of any general circulation model (GCM), is often overlooked in the analysis of a model's ability to simulate TCs compared to the impact of more commonly documented components (e.g., physical parameterizations). The Community Atmosphere Model version 5 is configured with multiple dynamics packages. This analysis demonstrates that the dynamical core has a significant impact on storm intensity and frequency, even in the presence of similar large-scale environments. In particular, the spectral element core produces stronger TCs and more hurricanes than the finite-volume core using very similar parameterization packages despite the latter having a slightly more favorable TC environment. Furthermore, these results suggest that more detailed investigations into the impact of the GCM dynamical core on TC climatology are needed to fully understand these uncertainties. Key Points The impact of the GCM dynamical core is often overlooked in TC assessments The CAM5 dynamical core has a significant impact on TC frequency and intensity A larger effort is needed to better understand this uncertainty

58 GEOSCIENCES↗
DOE OSTI2025

Toward Understanding the Differences between Mesoscale and Large-Eddy Simulations of Tropical Cyclones

In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from categories 1 to 5 on the Saffir–Simpson scale and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10–500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary layer parameterization may be needed.

17 WIND ENERGY↗
DOE OSTI2024

Implementation and Validation of a Generalized Actuator Disk Parameterization for Wind Turbine Simulations Within the FastEddy Model

ABSTRACT Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice.

17 WIND ENERGY↗
DOE OSTI2023

Recent advances in integrated hydrologic models: Integration of new domains

Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, in this study, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Model Intercomparison Study of Aerosol‐Cloud‐Turbulence Interactions in a Cloud Chamber: 1. Model Results

This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties.

54 ENVIRONMENTAL SCIENCES↗