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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 235 records · Page 13
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NASA NTRS2015

Testing Secondary Models for the Origin of Radio Mini-Halos in Galaxy Clusters

We present an MHD simulation of the emergence of a radio minihalo in a galaxy cluster core in a "secondary" model, where the source of the synchrotron-emitting electrons is hadronic interactions between cosmic-ray protons with the thermal intracluster gas, an alternative to the "reacceleration model" where the cosmic ray electrons are reaccelerated by turbulence induced by core sloshing, which we discussed in an earlier work. We follow the evolution of cosmic-ray electron spectra and their radio emission using passive tracer particles, taking into account the time-dependent injection of electrons from hadronic interactions and their energy losses. We find that secondary electrons in a sloshing cluster core can generate diffuse synchrotron emission with luminosity and extent similar to observed radio minihalos. However, we also find important differences with our previous work. We find that the drop in radio emission at cold fronts is less prominent than that in our reacceleration-based simulations, indicating that in this flavor of the secondary model the emission is more spatially extended than in some observed minihalos. We also explore the effect of rapid changes in the magnetic field on the radio spectrum. While the resulting spectra in some regions are steeper than expected from stationary conditions, the change is marginal, with differences in the synchrotron spectral index of delta(spectral index) less than approximately 0.15-0.25, depending on the frequency band. This is a much narrower range than claimed in the best-observed minihalos and produced in the reacceleration model. Our results provide important suggestions to constrain these models with future observations.

clusters: general aEuro" magnetohydrodynamics (MHD↗
DOE OSTI2025

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗
NASA NTRS1974

Modulation of cosmic-ray protons and helium nuclei near solar maximum

Balloon observations of proton and helium spectra in 1970, 1971 and 1972, reveal a factor of approximately 1.85 deviation from a single valued regression at low rigidities. This deviation decreases with increasing rigidity for both species. The period 1969-1970 is unique because time variations at low and high energies were anti-correlated. When satellite observations are used to extend the balloon observations to energies below 100 MeV/Nucleon, the proton spectrum showed a steeper slope in 1970 and 1972 than the characteristic J = AT spectrum observed during 1965-1969. The slope of the helium spectrum became continuously flatter during the same period (1970-1972). Computer generated spectra based on simple two parameter modulation models describe the basic features of the observations if one of the variable parameters is used to characterize the rigidity dependence of the diffusion coefficient. Models which do not allow such a variation are not consistent with the observations.

Rygg, T. A.↗
NASA NTRS1978

Automatic phase control in solar power satellite systems

Various approaches to the problem of generating, maintaining and distributing a coherent, reference phase signal over a large area are suggested, mathematically modeled and analyzed with respect to their ability to minimize: phase build-up, beam diffusion and beam steering phase jitter, cable length, and maximize power transfer efficiency. In addition, phase control configurations are suggested which alleviate the need for layout symmetry.

Lindsey, W. C.↗
NASA NTRS1990

One-dimensional cloud fluid model for propagating star formation

The aim of this project was to study the propagation of star formation (SF) with a self-consistent deterministic model for the interstellar gas. The questions of under what conditions does star formation propagate in this model and what are the mechanisms of the propagation are explored. Here, researchers used the deterministic Oort-type cloud fluid model of Scalo and Struck-Marcell (1984, also see the review of Struck-Marcell, Scalo and Appleton 1987). This cloud fluid approach includes simple models for the effects of cloud collisional coalescence or disruption, collisional energy dissipation, and cloud disruption and acceleration as the result of young star winds, HII regions and supernovae. An extensive one-zone parameter study is presented in Struck-Marcell and Scalo (1987). To answer the questions above, researchers carried out one-dimensional calculations for an annulus within a galactic disk, like the so-called solar neighborhood of the galactic chemical evolution. In the calculations the left-hand boundary is set equal to the right hand boundary. The calculation is obviously idealized; however, it is computationally convenient to study the first order effects of propagating star formation. The annulus was treated as if it were at rest, i.e., in the local rotating frame. This assumption may remove some interesting effects of a supersonic gas flow, but was necessary to maintain a numerical stability in the annulus. The results on the one-dimensional propagation of SF in the Oort cloud fluid model follow: (1) SF is propagated by means of hydrodynamic waves, which can be generated by external forces or by the pressure generated by local bursts. SF is not effectively propagated via diffusion or variation in cloud interaction rates without corresponding density and velocity changes. (2) The propagation and long-range effects of SF depend on how close the gas density is to the critical threshold value, i.e., on the susceptibility of the medium.

Titus, Timothy N.↗
NASA NTRS1991

'Self-consistent' production of ion conics on return current region auroral field lines - A time-dependent, semi-kinetic model

We describe initial results from a time-dependent, semi-kinetic model of plasma outflow incorporating wave-particle interactions along current-carrying auroral field lines. Electrostatic waves are generated by the current driven ion cyclotron instability (CDICI), causing perpendicular velocity diffusion of ions plus electron heating via anomalous resistivity when and where the relative drift between electrons and ions exceeds certain critical velocities. Using the local bulk parameters we calculate these critical velocities, and so are able to self-consistently switch on and off the heating of the various particle species. Due to the dependence of these critical velocities on the bulk parameters of the species the heating effects exhibit quite complex spatial and temporal variations. A wide range of ion distribution functions are observed in these simulations, including conics with energies of a few electron volts and 'ring' distributions. The rings are seen to be a natural result of transverse heating and velocity filter effects and do not require coherent acceleration processes. We also observe the formation of a density depletion in hydrogen and enhanced oxygen densities at high altitudes.

Brown, David G.↗
NASA NTRSDate not supplied

Predicting Thermal Response in a Li-ion Cell on a UAV Fight Profile

As the energy storage devices continue to "pack" more energy in a small space, any damage, battery component failure, manufacturing defect, or electrically abusing the battery can lead to catastrophic thermal runaway events. A catastrophic thermal event in a cell leads to high temperature, in some instances spewing of battery materials due to gas development from side reactions initiated due to high internal temperatures. Also, a thermal runaway event can propagate from a single "failed" cell to the pack in a battery pack, leading to a more significant event. Mitigating a thermal runaway event is important in the commercial and automotive sectors. However, preventing such events in an electric aircraft (or air taxis) is paramount due to the lack of alternatives in the event of a failure. Battery prognostics algorithms allow the prediction of state-of-charge (SOC) and end-of-life (EOL) of a Li-ion battery in a UAV (unmanned air vehicle) [1]. For this presentation, we will extend this two-level battery predictive algorithm to predict SOC, EOL, and estimated maximum temperature during a simulated flight. The model is extended by integrating a lumped physics-driven thermal model for high current densities [2]. The parameters used to control SOC and EOL are maximum storable charge, time constant for Li-ion diffusivity in the carbon particles, and internal cell resistance. Cycling leads to an increase in the heat generated by an aged Li-ion cell with a LiyCoO2 (LCO) cathode and a LixC6 (MCMB) anode. The aging of a cell leads to increase in SEI layer thickness, the diffusion time for the lithium ions inside the electrodes, and the local reaction rates, in addition to the thermodynamic abuse caused by fixed cycling voltages controlled by a Battery Management System. As the battery ages, the cell resistance increases, while the onset temperature of the thermal runaway decreases (depends on the cell chemistry and cell abuse history). Any large deviation of the cell temperature from the estimated (expected) value can identify a faulty cell. Since SEI decomposition has the lowest onset temperature in the series of reactions leading to thermal runaway, the model considers the self-heating rate of the SEI decomposition as onset temperature (similar to Ref. [3]). The parameters in the Arrhenius equation for the SEI heating rate depend on the number of cycles, the cell's operating temperature, and the cell's abuse history [4,5]. Coupling the electrochemical, thermal, and aging model allow the prognostic algorithm to estimate a typical cell voltage and temperature as a function of age (cycling and calendar), whose departure from measured values from the BMS is used to identify a safety event. In addition, we will present the results from two simulated flight scenarios for a UAV: typical and extreme, since the power requirements vary significantly during take-off, landing, and changing altitudes, while the power requirements remain low during the cruise. For this presentation, the power requirement for a battery pack in a UAV is scaled to a single cell. This cell is cycled through a simulated profile, and the data is collected and used to predict a safety event.

Li-ion↗
DOE OSTI2025

An Optimization-Based Coupling of Reduced Order Models with an Efficient Reduced Adjoint Basis Generation Approach

Optimization-based coupling (OBC) is an attractive alternative to traditional Lagrange multiplier approaches in multiple modeling and simulation contexts. However, application of OBC to time-dependent problems has been hindered by the computational cost of finding the stationary points of the associated Lagrangian, which requires primal and adjoint solves. This issue can be mitigated by using OBC in conjunction with computationally efficient reduced order models (ROMs). To demonstrate the potential of this combination, in this paper, we develop an optimization-based ROM-ROM coupling for a transient advection-diffusion transmission problem. We pursue the “optimize-then-reduce” path toward solving the minimization problem at each time step and solve reduced space adjoint system of equations, where the main challenge in this formulation is the generation of adjoint snapshots and reduced bases for the adjoint systems required by the optimizer. One of the main contributions of the paper is a new technique for an efficient adjoint snapshot collection for gradient-based optimizers in the context of optimization-based ROM-ROM couplings. In conclusion, we present numerical studies demonstrating the accuracy of the approach along with comparison between various approaches for selecting a reduced order basis for the adjoint systems, including decay of snapshot energy, average iteration counts, and timings.

coupled problems↗
NASA NTRS1988

Fatigue life prediction modeling for turbine hot section materials

This paper presents a summary of the life prediction methods developed under the NASA Lewis Research Center's Hot Section Technology (HOST) program. A major objective of the fatigue and fracture efforts under the HOST program was to significantly improve the analytic life prediction tools used by the aeronautical gas turbine engine industry. This has been achieved in the areas of high-temperature thermal and mechanical fatigue of bare and coated high-temperature superalloys. Such technical improvements will eventually reduce life cycle costs. The cyclic crack initiation and propagation resistance of nominally isotropic polycrystalline alloys and highly anisotropic single crystal alloys has been addressed. A sizeable data base has been generated for three alloys [cast PWA 1455 (B-1900 + Hf), wrought Inconel 718, and cast single crystal PWA 1480] in bare and coated conditions. Two coatings systems, diffusion aluminide (PWA 273) and plasma sprayed MCrAIY overlay (PWA 286) were employed. Life prediction modeling efforts were devoted to creep-fatigue interaction, oxidation, coatings interactions, multiaxiality of stress-strain states, mean stress effects, cumulative damage, and thermomechanical fatigue. The fatigue crack initiation life models developed to date include the Cyclic Damage Accumulation (CDA) Model of Pratt & Whitney and the Total Strain Version of Strainrange Partitioning (TS-SRP) of NASA Lewis for nominally isotropic materials, and the Tensile Hysteretic Energy Model of Pratt & Whitney for anisotropic superalloys. The fatigue model being developed by the General Electric Company is based upon the concepts of Path-lndependent Integrals (PII) for describing cyclic crack growth under complex nonlinear response at the crack tip due to thermomechanical loading conditions. A micromechanistic oxidation crack extension model has been derived by researchers at Syracuse University. The models are described and discussed in the paper. Only limited verification has been achieved to-date as several of the technical programs are still in progress and the verification tasks are scheduled, quite naturally, near the conclusion of the program. To-date, efforts have concentrated on development of independent models for cyclic constitutive behavior, cyclic crack initiation, and cyclic crack propagation. The transition between crack initiation and crack propagation has not been thoroughly researched as yet, and the integration of these models into a unified life prediction method has not been addressed.

Metal fatigue↗
DOE OSTI2025

From clutter to clarity: Emergent neural operators via questionnaire metrics

Real-world datasets in chemical engineering and bioengineering processes—such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials—can often be unlabeled or disorganized, rendering the training of existing supervised learning models ineffective at learning the underlying dynamics. To salvage these datasets for decision-making, we first seek to obtain clarity from the cluttered data. Here, we present a framework for developing “structural” generative models, discovering emergent equations, and constructing efficient emulators from scrambled datasets by integrating unsupervised organizational learning techniques (Questionnaires) with advanced deep learning architectures (Deep Hidden Physics Models and Deep Operator Networks). Our approach is demonstrated on two illustrative model systems: (a) a 1D advection–diffusion partial differential equation representing a winding underground pipe and (b) an ensemble of Stuart–Landau oscillators, an agent-based system of coupled ordinary differential equations. In both cases, we successfully reconstruct meaningful spatial, temporal, and parameter embeddings from scrambled data, enabling good predictions of system dynamics. As a result, we highlight the framework’s potential for broader applications, enabling data-driven system identification in fields with inherently disorganized or hidden parameter spaces.

42 ENGINEERING↗
DOE OSTI2025

From disorganized data to emergent dynamic models: Questionnaires to partial differential equations

Starting with sets of disorganized observations of spatially varying and temporally evolving systems, obtained at different (also disorganized) sets of parameters, we demonstrate the data-driven derivation of parameter dependent, evolutionary partial differential equation (PDE) models capable of generating the data. This tensor type of data is reminiscent of shuffled (multidimensional) puzzle tiles. The independent variables for the evolution equations (their “space” and “time”) as well as their effective parameters are all emergent , i.e. determined in a data-driven way from our disorganized observations of behavior in them. We use a diffusion map based questionnaire approach to build a smooth parametrization of our emergent space/time/parameter space for the data. This approach iteratively processes the data by successively observing them on the “space,” the “time” and the “parameter” axes of a tensor. Once the data become organized, we use machine learning (here, neural networks) to approximate the operators governing the evolution equations in this emergent space. Our illustrative examples are based (i) on a simple advection–diffusion model; (ii) on a previously developed vertex-plus-signaling model of Drosophila embryonic development; and (iii) on two complex dynamic network models (one neuronal and one coupled oscillator model) for which no obvious smooth embedding geometry is known a priori. This allows us to discuss features of the process like symmetry breaking, translational invariance, and autonomousness of the emergent PDE model, as well as its interpretability.

generative models↗
NASA NTRS1993

A two-dimensional model with coupled dynamics, radiation, and photochemistry. 1: Simulation of the middle atmosphere

Spatial and seasonal distribution of ozone and other trace gases are simulated using a interactive two-dimensional model of the stratosphere updated to include full gas phase chemistry. The model consists of a primitive equation dynamics module, a full radiative transfer scheme, and a comprehensive gas phase chemistry module. The circulation is derived from heating rates in the stratosphere that are calculated using model-generated ozone. In the troposphere, parameterized heating rates are adopted. The eddy momentum flux divergence in the zonal mean momentum equation is given by the eddy fluxes of potential vorticity. Eddy fluxes of potential vorticity and tracers are parameterized using a set of predetermined diffusion coefficients. The adopted values for K(sub yy), show a hemispherical asymmetry in that the values in the lower stratosphere are consistently smaller in the southern hemisphere. The asymmetry in K(sub yy) and in the parameterization of the tropospheric heating rate results in an asymmetry in the circulation giving rise to unique signatures in the trace gas distributions. The model successfully simulates the observed asymmetry in the column abundance of the springtime ozone maxima between northern and southern hemisphere. Results for other trace gases are in agreement with the gross observed features although specific differences exist.

Ko, Malcolm K. W.↗
NASA NTRS1974

Modulation of cosmic ray protons and helium nuclei near solar maximum

Balloon observations of proton and helium spectra in 1970, 1971, and 1972, which extend previous work for the period 1965-1969, reveal a factor of about 1.85 deviation from a single-valued regression at low rigidities. This deviation decreases with increasing rigidity for both species. The period 1969-197 is unique, because time variations at low and high energies were anticorrelated. When satellite observations are used to extend the balloon observations to energies below 100 MeV/nucleon, the proton spectrum shows a steeper slope in 1970 and 1972 than the characteristic J = AT spectrum observed during 1965-1969. The slope of the helium spectrum became continuously flatter during the same period (1970-1972). Computer-generated spectra based on simple two-parameter modulation models describe the basic features of the observations, if one of the variable parameters is used to characterize the rigidity dependence of the diffusion coefficient. On the other hand, models that do not allow such a variation are not consistent with the observations.

Rygg, T. A.↗
NASA NTRS1991

What maintains the zonal circulation in planetary atmospheres?

The latest Voyager observations have shown large zonal velocities in Neptune's atmosphere, with some indication of alternating jets. Similar wind velocities have also been observed on Venus and are characteristic of planetary atmospheres in general, which is remarkable considering that the available solar or internal heating varies by more than a factor of 1000. A simplified model of the planetary circulation which provides some qualitative understanding is discussed. The basic assumption is that the source driving the circulation is also generating the dissipating eddies which are simulated by diffusion. Thus, the magnitude and structure of the zonal circulation are independent both of the source and the dissipation rate. The zonal velocities are related to the speed of sound and are of comparable magnitude in different atmospheres; although the available heating varies by a large factor, and the planetary parameters vary over a wide range. The alternating jets are described by a convective eigenmode which develops when energy transport out of the planetary interior is important, as is the case on Jupiter, Neptune, and Saturn.

Mayr, H. G.↗
DOE OSTI2025

Equilibrium Fe isotope fractionation between olivine, pyroxene, spinel and MORB glass: Implications for mantle partial melting to generate MORBs

Primitive mid-ocean ridge basalts (MORBs) exhibit Fe isotopic compositions heavier than the upper mantle by +0.074 ± 0.028 ‰ for δ 56 Fe. The processes responsible for this isotopic difference remain unclear. Modeling of Fe isotope fractionation during mantle partial melting requires reliable equilibrium Fe isotope fractionation factors between minerals and melts, for which consistent data are still lacking. Here, in this study, we used Nuclear Resonant Inelastic X-ray Scattering (NRIXS) technique to measure Fe force constants for a MORB glass (ALV 519-4-1) and natural mantle minerals (olivine, orthopyroxene, clinopyroxene, and spinel) to determine the equilibrium Fe isotope fractionation factors between them. The force constants determined in this study, in increasing order, are 167 ± 26 N/m for spinel, 175 ± 17 N/m for olivine, 176 ± 20 N/m for MORB glass, 205 ± 26 N/m for clinopyroxene, and 219 ± 36 N/m for orthopyroxene. We evaluated the previously proposed mechanisms for the heavy Fe isotopic composition of MORBs, including (i) mantle partial melting, (ii) mantle lithological heterogeneity, with pyroxenite in the source, (iii) mantle metasomatism by low-degree melts, and (iv) fractional crystallization of olivine from melts. For (i), we used the pMELTS program to simulate adiabatic decompression melting of mantle peridotites, and calculated Fe isotope fractionation based on Fe 3+ –Fe 2+ equilibrium-controlled fractionation, where Fe 3+ forms stronger bonds and is more incompatible than Fe 2+ . At 10 wt% peridotite melting, corresponding to MORB generation, only +0.03 ‰ Fe isotope fractionation between the melt and the original bulk composition (Δ 56 Fe = δ 56 Fe melt - δ 56 Fe 0 ) was produced, insufficient to account for the observed MORB-upper mantle difference. For (ii), melting of pyroxenites yields smaller Fe isotope fractionation than melting of peridotites, making it unlikely the cause for the MORB-upper mantle isotopic difference. For (iii), both the Fe 3+ /ΣFe ratio and the δ 56 Fe of melts increase with the degree of partial melting, indicating that low-degree melts are not isotopically heavy enough to significantly alter the isotopic composition of lithospheric mantle through metasomatism. For (iv), equilibrium isotope fractionation between olivine and melt is near zero. These results suggest that equilibrium Fe isotope fractionation alone cannot explain the MORB isotopic signature, highlighting the potential role of kinetic isotope fractionation. Using a diffusion model, we calculated kinetic Fe and Mg isotope fractionations associated with (iv) olivine crystallization from a melt, and found that the predicted Fe and Mg isotope fractionations were inconsistent with observations in MORBs. Qualitatively, two processes could have induced kinetic Fe isotope fractionation during MORB generation: (a) Fe-Mg interdiffusion between melt and solid during melt migration and (b) reactive melt-rock interactions during melt focusing. However, a quantitative understanding of their role in modifying the melt isotopic composition remains limited and requires further investigation.

Fe isotopes↗
NASA NTRS2003

First Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Foreground Emission

The WMAP mission has mapped the full sky to determine the geometry, content, and evolution of the universe. Full sky maps are made in five microwave frequency bands to separate the temperature anisotropy of the cosmic microwave background (CMB) from foreground emission, including diffuse Galactic emission and Galactic and extragalactic point sources. We define masks that excise regions of high foreground emission, so CMB analyses can became out with minimal foreground contamination. We also present maps and spectra of the individual emission components, leading to an improved understanding of Galactic astrophysical processes. The effectiveness of template fits to remove foreground emission from the WMAP data is also examined. These efforts result in a CMB map with minimal contamination and a demonstration that the WMAP CMB power spectrum is insensitive to residual foreground emission. We use a Maximum Entropy Method to construct a model of the Galactic emission components. The observed total Galactic emission matches the model to less than 1% and the individual model components are accurate to a few percent. We find that the Milky Way resembles other normal spiral galaxies between 408 MHz and 23 GHz, with a synchrotron spectral index that is flattest (beta(sub s) approx. -2.5) near star-forming regions, especially in the plane, and steepest (beta(sub s) approx. -3) in the halo. This is consistent with a picture of relativistic cosmic ray electron generation in star-forming regions and diffusion and convection within the plane. The significant synchrotron index steepening out of the plane suggests a diffusion process in which the halo electrons are trapped in the Galactic potential long enough to suffer synchrotron and inverse Compton energy losses and hence a spectral steepening. The synchrotron index is steeper in the WMAP bands than in lower frequency radio surveys, with a spectral break near 20 GHz to beta(sub s) less than -3. The modeled thermal dust spectral index is also steep in the WMAP bands, with beta(sub d) approx. = 2.2. Our model is driven to these conclusions by the low level of total foreground contamination at approx. 60 GHz. Microwave and Ha measurements of the ionized gas agree well with one another at about the expected levels. Spinning dust emission is limited to less than 5% of the Ka-band foreground emission. A catalog of 208 point sources is presented. The reliability of the catalog is 98%, i.e., we expect five of the 208 sources to be statistically spurious. The mean spectral index of the point sources is alpha approx. 0(beta approx. -2). Derived source counts suggest a contribution to the anisotropy power from unresolved sources of (15.0 +/- 1.4) x 10(exp -3)micro sq K sr at Q-band and negligible levels at V-band and W-band. The Sunyaev-Zeldovich effect is shown to be a negligible "contamination" to the maps.

Bennett, C. L.↗
DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗
NASA NTRS1998

Transport Between the Tropical and Midlatitude Lower Stratosphere: Implications for Ozone Response to High Speed Civil Transport Emissions

Several recent studies have quantified the air exchange rate between the tropics and midlatitudes in the lower stratosphere using airborne and satellite measurements of chemical species. It is found that the midlatitude air is mixed into the tropical lower stratosphere with a replacement timescale of 13.5 months (with 20% uncertainty) for the region from the tropopause to 21 km and at least 18 months for the region of 20-28 km. These estimates are used to adjust the horizontal eddy diffusion coefficients, K(sub yy), in a two-dimensional chemistry transport model. The value of K(sub yy) previously used to simulate the subtropical barrier, 0.03 x 10(exp 6)sq m/s, generates an exchange time of about 4 years, and the model without subtropical barrier (K(sub yy) = 0.3 x 10(exp 6)sq m/s) has an exchange time of 5 months. Adjusting the K(sub yy) to 0.13 x 10(exp 6) sq m/s from the tropopause to 21 km and 0.07 x 10(exp 6)sq m/s above 21 km produces the exchange timescales which match the estimates deduced from the measurements. The subtropical barrier prevents the engine emissions of the high-speed civil transport (HSCT) aircraft from being transported into the tropics and subsequently lifted into the upper atmosphere or mixed into the southern hemisphere. The model results show that the calculated ozone response to HSCT aircraft emissions using the K(sub yy), adjusted to observed mixing rates is substantially smaller than that simulated without the subtropical barrier.

Shia, R.-L.↗