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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Numerical study of proppant transport and settling processes in fractures

Reservoir stimulation by creating hydraulically conductive fractures is the key step for enabling enhanced geothermal systems (EGS). The effectiveness of stimulation is significantly influenced by the deposition of proppant inside induced fractures. The transportation and settling of proppant in a propagating fracture is controlled by a multitude of operational and physical parameters, including the fracturing fluid rheology, injection rate, proppant concentration, fracture length/aperture evolution, proppant size/density/shape, etc. A numerical tool that robustly and efficiently accounts for all important attributes can facilitate the design and optimization of reservoir stimulation. This study presents the novel computational tool ELK (ELectrical fracKing) developed for the numerical simulation of proppant-fluid mixture circulation in a fractured geothermal reservoir. We enriched the MOOSE-based PorousFlow module with a suite of equations to consider the fluid-proppant mixture with particle-particle/fluid interactions, which include gravitational settling, particle convection, particle hampering, and strong density and viscosity contrasts. The computational tool is validated by comparing the predicted proppant bed evolution against two different laboratory scale experiments of proppant transport in a fixed aperture channel. Further parameter studies were performed, and the modeling results show that the proppant deposition is determined by the mixing characteristics and settling of the particles from the slurry. Concentration-dependent density and viscosity lead to an inhomogeneous distribution of the proppant, particle collision, and enhanced settling at the bottom of the fractures. Preliminary coupling with dynamic fracture propagation shows promising results and will be further developed to simulate hydraulic stimulation at high fidelity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Vertical Structure and Ice Production Processes of Shallow Convective Postfrontal Clouds over the Southern Ocean in MARCUS. Part II: Modeling Study

Abstract Part I of this series presented a detailed overview of postfrontal mixed-phase clouds observed during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign. In Part II, we focus on a multiday (23–26 February 2018) case with the aim of understanding ice production as well as model sensitivity to ice process parameterizations using the Weather Research and Forecasting (WRF) Model. The control simulation with the Predicted Particle Properties (P3) microphysics scheme underestimates the ice content and overestimates the supercooled liquid water content, contrary to the bias common in global climate models. The simulations targeted at ice production processes show negligible sensitivity to cloud droplet number concentrations. Further, neither increasing ice nuclei particle (INP) concentrations to an unrealistic level nor adjusting it to MARCUS field estimations alone guarantees more ice production in the model. However, the simulated clouds are found to be highly sensitive to the implementation of immersion freezing, the thresholding of condensation/deposition freezing initiation, and the rime splintering process. By increasing immersion freezing of cloud droplets, relaxing thresholds for condensation/deposition freezing, or removing rime splintering thresholds, the model significantly improves its performance in producing ice. The relaxation of the immersion freezing temperature threshold to the observed cloud-top temperature suggests an in-cloud seeder–feeder mechanism. The results of this work call for an increase in observations of INP, especially over the remote Southern Ocean and at relatively high temperatures, and measurements of ice particle size distributions to better constrain ice nucleating processes in models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Porosity-Permeability Evolution During Simultaneous Mineral Dissolution and Precipitation

Permeability in reactive porous media evolves in complex ways that are hard to predict. Macroscopic empirical equations are often used to estimate permeability evolution but fail to reflect the impact of pore scale reactions on permeability. This work aims to understand the evolution of permeability in systems where mineral dissolution and precipitation occur simultaneously. Pore network models are used for permeability simulation of a Paluxy sandstone using pore and pore-throat size distributions from the analysis of X-ray CT images. Pore and pore-throat radii are increased and decreased to reflect the effects of dissolution and precipitation reactions. Varying spatial distributions of reactions are simulated and the resulting porosity and permeability values compared with commonly used macroscopic equations. It is observed that when dissolution occurs at the inlet and precipitation at the outlet, porosity increases while permeability decreases. Similar results are also observed in the respective opposite scenario where precipitation occurs at the inlet and dissolution at the outlet. When dissolution and precipitation reactions are randomly distributed throughout the network, porosity increases with little change in permeability that is not captured by the empirical equations. When reactions are controlled by pore and pore-throat sizes, such as dissolution occurring in pores and pore-throats of small size and precipitation in pores and pore-throats of larger size, porosity and permeability decrease. When precipitation occurs in pores and pore-throats of smaller size and dissolution in pores and pore-throats of larger size, porosity and permeability increase and is described relatively well by the Verma-Pruess porosity-permeability equation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗
DOE OSTI2024

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗
DOE OSTI2019

Entropy and Enthalpy Mediated Segregation of Bottlebrush Copolymers to Interfaces

The composition of polymer blends near interfaces can differ from the average blend composition because the attraction of each polymer toward surfaces is controlled by its chemistry, size, and architecture. In this work, we studied thin film blends of bottlebrush copolymers and linear homopolymers to understand the enthalpic and entropic effects that drive preferential segregation of one constituent to film interfaces. Bottlebrush copolymers containing polystyrene (PS) and poly(methyl methacrylate) (PMMA) side chains were blended with either linear PS or linear PMMA, and time-of-flight secondary ion mass spectroscopy was used to quantify the distribution of bottlebrushes through the film thickness as a function of homopolymer type, homopolymer molecular weight, and processing conditions. We found that the bottlebrush copolymers segregated to air and substrate interfaces above a critical molecular weight of the linear homopolymer, consistent with an entropic preference for chain ends and shorter chains toward the interfaces. This segregation was used to tailor the surface wettability of blend films using bottlebrush additives as a minority component. Modeling using self-consistent field theory highlighted effects of conformational entropy and enthalpic interactions in driving almost complete segregation from the interior of the films toward interfaces. Furthermore, enthalpic interactions were predicted to cause lateral phase segregation in cases where the homopolymer is preferred over the bottlebrush copolymer at the substrate, an effect that was also observed in experiments. Finally, this study demonstrates that bottlebrush copolymer additives can be designed to spontaneously segregate to surfaces in thermal blends, providing a possible route to decouple surface properties from bulk properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-Resolution Near-Surface Imaging at the Basin Scale Using Dark Fiber and Distributed Acoustic Sensing: Toward Site Effect Estimation in Urban Environments

Near-surface seismic structure, particularly the shear wave velocity (V s ), can strongly affect local site response, and should be accurately estimated for ground motion prediction during seismic hazard assessment. The Imperial Valley (California), occupying the southern end of the Salton Trough, is a seismically active basin with thick surficial lacustrine sedimentary deposits. In this study, we utilize ambient noise records and local earthquake events for high-resolution near-surface characterization and site effect estimation with an unlit fiber-optic telecommunication infrastructure (dark fiber) in Imperial Valley by using the distributed acoustic sensing (DAS) technique. We apply ambient noise interferometry to retrieve coherent surface waves from DAS records, and evaluate performances of three different surface wave methods on DAS ambient noise dispersion imaging. We develop a quality control workflow to improve the dispersion measurement of noisy portions of the DAS data set by using a data selection strategy. Using the joint inversion of both the fundamental mode and higher overtones of Rayleigh waves, a high resolution two-dimensional (2D) V s structure down to 70 m depth is obtained. We successfully achieve an improved V s 30 (the time-averaged shear-wave velocity in the top 30 m) model with higher spatial-resolution and reliability compared to the existing community model for the area. We also explore the potential for utilizing DAS earthquake events for site amplification estimation. The preliminary results reveal a clear anti-correlation between the approximated site response and the V s 30 profile. In conclusion, our results indicate the potential utility of DAS deployed on dark fiber for near-surface characterization in appropriate contexts.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

AEGIS: Autonomous Entity Global Intelligence System for Urban Air Mobility

This paper presents a global intelligence system that synthesizes aerial vehicles’ real-time physical data, planned actions, and historical behavior into engineered data frames representing the collective state of the airspace and suitable for efficient machine learning consumption. These data frames are then learnt by a deep neural net to build a prediction model that estimates the expected evolution path of the current state, thereby identifying potential future conflicts. This approach lends itself to an automated early warning system that the aerial vehicles can implement onboard with a suitable edge computing module more efficiently and effectively than non-AI methods, and eventually take preventive or corrective measures towards self/collaborative resolution of the issues. Contrary to a centralized early warning system where all vehicles’ task-space eventually converges to a global optimum state, the presented distributed global intelligence system brings in a balance between local utility functions of each vehicle and the global operating framework. This contributes to effectively handle the potential massive scaling in urban air mobility in the near future.

Artificial Intelligence↗
DOE OSTI2026

Multiscale modeling of packed-bed microwave reactors and estimation of intrinsic materials' permittivity

Modeling of packed-bed microwave reactors relies on an accurate representation of particle size, shape, and distribution within the bed, as well as the particles' dielectric properties. The measured permittivity of microwave susceptors (powders or structured materials) depends on the geometric features of the particles and the porosity of the bed, as well as the specific form factor of a structured material. These are effective properties and cannot be used to analyze other reactor configurations unless the geometric effects are removed. Therefore, we introduce a methodology for extracting the intrinsic particle permittivity from experimentally measured effective permittivity by combining cavity-based measurements with multiscale simulations and machine learning. Further, we develop the first multiscale model of packed-bed microwave reactors that incorporate particle effects (geometric features, random packing, and particle contact). This approach bridges macroscopic observables with mesoscopic physics, enabling analysis of local hotspots, arcing, and contact effects that control reactor performance. Using polymer-based spherical activated carbon (PBSAC) and silicon carbide (SiC) as examples, we demonstrate that the inferred particle permittivity is consistent with independent experimental heating profiles we collect from microwave reactors without adjustable parameters. Finally, this methodology establishes a foundation for predictive, multiscale design of microwave packed-bed reactors that explicitly accounts for particle-scale effects, enabling the estimation of intrinsic permittivity for the first time.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

NASA Tech Briefs, May 2007

Topics include: Noise-Canceling Helmet Audio System; Program Analyzes Spacecraft/Ground Radio Links; Two-Way Communication Using RFID Equipment and Techniques; Six-Message Electromechanical Display System; Scanning Terahertz Heterodyne Imaging Systems; Master Clock and Time-Signal-Distribution System; Synchronous Phase-Resolving Flash Range Imaging; Integrated Radial Probe Transition From MMIC to Waveguide; Bar-Code System for a Microbiological Laboratory; MMIC Amplifier Produces Gain of 10 dB at 235 GHz; Mapping Nearby Terrain in 3D by Use of a Grid of Laser Spots; Digital Beam Deflectors Based Partly on Liquid Crystals; Narrow-Band WGM Optical Filters With Tunable FSRs; Better Finite-Element Analysis of Composite Shell Structures; Computing Spacecraft-Pointing Vectors for Limb Tracking; Enhanced Master Controller Unit Tester; Rover Graphical Simulator; Increasing Durability of Flame-Sprayed Strain Gauges; Multifunctional, High-Temperature Nanocomposites; Multilayer Impregnated Fibrous Thermal Insulation Tiles; Radiation-Shielding Polymer/Soil Composites; Film/Adhesive Processing Module for Fiber-Placement Processing of Composites; Fabrication of Submillimeter Axisymmetric Optical Components; Electrochemical Disposal of Hydrazines in Water; Statistical Model of Evaporating Multicomponent Fuel Drops; Resistively Heated SiC Nozzle for Generating Molecular Beams; Compact Packaging of Photonic Millimeter-Wave Receiver; Diffractive Combiner of Single-Mode Pump Laser-Diode Beams; Wide-Band, High-Quantum-Efficiency Photodetector; A Robustly Stabilizing Model Predictive Control Algorithm; Modeling Evaporation of Drops of Different Kerosenes; Development of Vapor-Phase Catalytic Ammonia Removal System; Several Developments in Space Tethers; Design Concept for a Nuclear Reactor-Powered Mars Rover; Formation-Initialization Algorithm for N Spacecraft; and DNSs of Multicomponent Gaseous and Drop-Laden Mixing Layers Achieving Transition to Turbulence.

Source record↗
DOE OSTI2023

Patterns and rates of soil movement and shallow failures across several small watersheds on the Seward Peninsula, Alaska

Abstract. Thawing permafrost can alter topography, ecosystems, and sediment and carbon fluxes, but predicting landscape evolution of permafrost-influenced watersheds in response to warming and/or hydrological changes remains an unsolved challenge. Sediment flux and slope instability in sloping saturated soils have been commonly predicted from topographic metrics (e.g., slope, drainage area). In addition to topographic factors, cohesion imparted by soil and vegetation and melting ground ice may also control spatial trends in slope stability, but the distribution of ground ice is poorly constrained and hard to predict. To address whether slope stability and surface displacements follow topographic-based predictions, we document recent drivers of permafrost sediment flux present on a landscape in western Alaska that include creep, solifluction, gullying, and catastrophic hillslope failures ranging in size from a few meters to tens of meters, and we find evidence of rapid and substantial landscape change on an annual timescale. We quantify the timing and rate of surface movements using a multi-pronged, multi-scalar dataset including aerial surveys, interannual GPS surveys, synthetic aperture radar interferometry (InSAR), and climate data. Despite clear visual evidence of downslope soil transport of solifluction lobes, we find that the interannual downslope surface displacement of these features does not outpace downslope displacement of soil in locations where lobes are absent (downslope movement means: 7 cm yr−1 for lobes over 2 years vs. 10 cm yr−1 in landscape positions without lobes over 1 year). Annual displacements do not appear related to slope, drainage area, or modeled total solar radiation but are likely related to soil thickness, and volumetric sediment fluxes are high compared to temperate landscapes of comparable bedrock lithology. Time series of InSAR displacements show accelerated movement in late summer, associated with intense rainfall and/or deep thaw. While mapped slope failures do cluster at slope–area thresholds, a simple slope stability model driven with hydraulic conductivities representative of throughflow in mineral and organic soil drastically overpredicts the occurrence of slope failures. This mismatch implies permafrost hillslopes have unaccounted-for cohesion and/or throughflow pathways, perhaps modulated by vegetation, which stabilize slopes against high rainfall. Our results highlight the breadth and complexity of soil transport processes in Arctic landscapes and demonstrate the utility of using a range of synergistic data collection methods to observe multiple scales of landscape change, which can aid in predicting periglacial landscape evolution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Bowles-Tatnall Wake Vortex Encounter Hazard Metric

Wake vortex spacing standards constrict the terminal area throughput and impose severe constraints on the overall capacity and efficiency of the National Airspace System. For more than two decades starting in the early 1990s, the National Aeronautics and Space Administration conducted extensive research on characterizing the formation and evolution of aircraft wakes. This multidisciplinary work included comprehensive field experiments (Pruis et al. 2016), flight tests (Vicroy et al. 1998), and wind tunnel tests (Rossow 1994; Chow et al. 1997). Parametric studies using large eddy simulations (Proctor 1998; Proctor et al. 2006) were conducted in order to develop fast-time models for the prediction of wake transport and decay (Ahmad et al. 2016). Substantial effort was spent on the formulation of acceptable vortex hazard metrics (Tatnall 1995; Hinton and Tatnall 1997). Several wake encounter severity metrics have been suggested in the past, which include the wake circulation strength, vortex-induced rolling moment coefficient (Clv), bank angle, and the roll control ratio (Tatnall 1995; Hinton and Tatnall 1997; Van der Geest 2012). The vortex-induced rolling moment coefficient introduced by Bowles and Tatnall (Tatnall 1995; Gloudemans et al. 2016) has been used extensively for risk and safety analysis of newly proposed air traffic management concepts and procedures. The original method of Bowles and Tatnall assumed a constant wing loading (the wing lift-curve slope, CL is constant), which resulted in an overestimation of the vortexinduced rolling moment coefficient. Bowles (2014) suggested a correction to the original method that provides more accurate values of Clv and which is also consistent with the underlying physics of the problem. The overestimation of Clv in the original method can be corrected by assuming an elliptical lift distribution. Figure 1.1 illustrates the correction in Clv achieved by the modified method.

Joel Malissa↗
NASA NTRSDate not supplied

NASA Langley FUN3D Analyses in Support of the 1st AIAA Stability and Control Prediction Workshop

This work summarizes the results of FUN3D analyses conducted for the 1st AIAA Stability and Control Workshop on behalf of participants from the NASA Langley Research Center. The workshop was created to establish best practices for the prediction of stability and control derivatives using computational fluid dynamics and assess the limitations of these methods when those best practices are applied. The inaugural workshop considered the ONERA version of the NASA/Boeing Common Research Model, which includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. Wind tunnel data at small sideslip angles remain unpublished and served as ‘blind’ data for computational comparisons. The present research generated workshop test case data using the NASA FUN3D code, which is a parallelized, unstructured, node-based, finite-volume discretization, Reynolds-averaged Navier-Stokes flow solver. Steady- state numerical simulations were conducted for workshop test cases investigating the following: grid convergence, Mach number effect on static stability, wind tunnel sting increments, static stability-derivative calculations, and a sideslip angle sweep. Results were generated for two series of unstructured, mixed-element grids, one set provided by the workshop and another set created using the HeldenMesh grid generation software. The results provided include total- and component-level breakdowns of the force and moment coefficients, in addition to sectional pressure distributions for the wing and tail components for comparisons to wind tunnel data.

CFD↗
DOE OSTI2025

Three-Dimensional Pore Networks in Miocene Stevens Sandstone of California: Implications for CO 2 Geologic Storage

The Miocene Stevens Sandstone in the San Joaquin Basin of California is increasingly recognized as a promising candidate for CO 2 geological storage due to the enormous storage capacity, proven sealing, and existing infrastructure. In this study, computed microtomography imaging and pore network modeling were employed to investigate the influence of pore geometry and wettability on the CO 2 injectivity and residual trapping. Image analysis revealed that a significant fraction of the cement and matrix consists of microporous regions. The microporosity can substantially increase the overall pore space, yet its contribution to permeability remains modest, particularly in samples with low permeability. The intrinsic heterogeneity of turbidite reservoirs further complicates the reservoir properties among different layers. Two-phase flow simulations under varying wettability conditions (water-wet, weak water-wet, and neutral-wet) demonstrated that the CO 2 injection is predominantly controlled by macropores. CO 2 invades microporous regions only after these larger pores are filled. The presence of microporosity leads to a decrease in both initial and residual CO 2 saturations, with the magnitude of the reduction being influenced by wettability. Neutral-wet scenarios exhibit higher CO 2 mobility and thus lower residual trapping than water-wet scenarios. The results imply that heterogeneity in pore geometry and cement distribution across different layers can result in stratified CO 2 flow pathways, complicating efforts to predict injection performance. Overall, the Stevens Sandstone shows considerable promise for CO 2 geologic storage, but effective implementation will require detailed characterization of the pore structure as well as the integration of reactive fluid flow to account for potential mineral dissolution and fines migration.

fluids↗
DOE OSTI2023

Modelling galaxy cluster triaxiality in stacked cluster weak lensing analyses

Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude ln (A) is boosted from the lowest to highest orientation bin with a significance of 14σ, while the orientation dependence of the richness-mass slope and intrinsic scatter is minimal. We also find that the weak lensing shear-profile ratios of cluster-associated dark haloes in different orientation bins resemble a ‘bottleneck’ shape that can be quantified with a Cauchy function. We test the correlation of orientation with two other leading systematics in cluster cosmology – miscentering and projection – and find a null correlation. The resulting mass bias predicted from our templates confirms the DES Y1 finding that triaxiality is a leading source of bias in cluster cosmology. However, the richness-dependence of the bias confirms that triaxiality does not fully resolve the tension at low-richness between DES Y1 cluster cosmology and other probes. Our model can be used for quantifying the impact of triaxiality bias on cosmological constraints for upcoming weak lensing surveys of galaxy clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRSDate not supplied

Assimilation of Reconstructed Radiances from IASI Principal Component Scores into the GEOS-ADAS

Hyperspectral Infrared sounders such as IASI, AIRS, and CrIS have long been an integral part of radiance assimilation in numerical weather prediction (NWP), providing vertical profiles of water vapor and temperature information. Principal Component Scores (PCS) are a lossy form of compression that retains most information, such as temperature and moisture, by using a large training set of atmospheric profiles. However, PCS may not well represent profiles which are rare events, such as volcanic eruptions, and drops some sources of random noise. There has been an increased interest in the use of PCS as EUMETSAT plans to distribute future geostationary sounder radiances from MTG-IRS via PCS only. NWP centers use two approaches to deal with PCS: direct assimilation of the PCS by modifying the radiative transfer model to produce PCS and the associated Jacobians, or a simpler approach of decompressing the PCS and reconstructing the radiances back into channel space to allow assimilating radiances without modifications to the data assimilation system. EUMETSAT has developed a PCS product for IASI that has been operational since 2011. We utilize this product opting for the simpler approach, decompressing IASI PCS into channel space, and assimilating those radiances using the GEOS-ADAS. We then compare this with a control using the standard IASI radiance product. Resulting differences in global forecast statistics, differences in Forecast Sensitivity to Observation Impact, along with implications for implementation and quality control are discussed.

Bryan M. Karpowicz↗