NSF NCAR Computational & Information Systems Laboratory

Asteroseismology with the Kepler space telescope is providing not only an improved characterization of exoplanets and their host stars, but also a new window on stellar structure and evolution for the large sample of solar-type stars in the field. We perform a uniform analysis of 22 of the brightest asteroseismic targets with the highest signal-to-noise ratio observed for 1 month each during the first year of the mission, and we quantify the precision and relative accuracy of asteroseismic determinations of the stellar radius, mass, and age that are possible using various methods. We present the properties of each star in the sample derived from an automated analysis of the individual oscillation frequencies and other observational constraints using the Asteroseismic Modeling Portal (AMP), and we compare them to the results of model-grid-based methods that fit the global oscillation properties. We find that fitting the individual frequencies typically yields asteroseismic radii and masses to \sim1% precision, and ages to \sim2.5% precision (respectively 2, 5, and 8 times better than fitting the global oscillation properties). The absolute level of agreement between the results from different approaches is also encouraging, with model-grid-based methods yielding slightly smaller estimates of the radius and mass and slightly older values for the stellar age relative to AMP, which computes a large number of dedicated models for each star. The sample of targets for which this type of analysis is possible will grow as longer data sets are obtained during the remainder of the mission.

The evolved solar-type stars 16 Cyg A and B have long been studied as solar analogs, yielding a glimpse into the future of our own Sun. The orbital period of the binary system is too long to provide meaningful dynamical constraints on the stellar properties, but asteroseismology can help because the stars are among the brightest in the Kepler field. We present an analysis of three months of nearly uninterrupted photometry of 16 Cyg A and B from the Kepler space telescope. We extract a total of 46 and 41 oscillation frequencies for the two components, respectively, including a clear detection of octupole (l = 3) modes in both stars. We derive the properties of each star independently using the Asteroseismic Modeling Portal, fitting the individual oscillation frequencies and other observational constraints simultaneously. We evaluate the systematic uncertainties from an ensemble of results generated by a variety of stellar evolution codes and fitting methods. The optimal models derived by fitting each component individually yield a common age (t = 6.8 0.4 Gyr) and initial composition (Z i = 0.024 0.002, Y i = 0.25 0.01) within the uncertainties, as expected for the components of a binary system, bolstering our confidence in the reliability of asteroseismic techniques. The longer data sets that will ultimately become available will allow future studies of differential rotation, convection zone depths, and long-term changes due to stellar activity cycles.

Recently the number of main-sequence and subgiant stars exhibiting solar-like oscillations that are resolved into individual mode frequencies has increased dramatically. While only a few such data sets were available for detailed modeling just a decade ago, the Kepler mission has produced suitable observations for hundreds of new targets. This rapid expansion in observational capacity has been accompanied by a shift in analysis and modeling strategies to yield uniform sets of derived stellar properties more quickly and easily. We use previously published asteroseismic and spectroscopic data sets to provide a uniform analysis of 42 solar-type Kepler targets from the Asteroseismic Modeling Portal. We find that fitting the individual frequencies typically doubles the precision of the asteroseismic radius, mass, and age compared to grid-based modeling of the global oscillation properties, and improves the precision of the radius and mass by about a factor of three over empirical scaling relations. We demonstrate the utility of the derived properties with several applications.

Abstract We present a nonlinear magnetohydrodynamic shallow-water model for the solar tachocline (MHD-SWT) that generates quasi-periodic tachocline nonlinear oscillations (TNOs) that can be identified with the recently discovered solar “seasons.” We discuss the properties of the hydrodynamic and magnetohydrodynamic Rossby waves that interact with the differential rotation and toroidal fields to sustain these oscillations, which occur due to back-and-forth energy exchanges among potential, kinetic, and magnetic energies. We perform model simulations for a few years, for selected example cases, in both hydrodynamic and magnetohydrodynamic regimes and show that the TNOs are robust features of the MHD-SWT model, occurring with periods of 2–20 months. We find that in certain cases multiple unstable shallow-water modes govern the dynamics, and TNO periods vary with time. In hydrodynamically governed TNOs, the energy exchange mechanism is simple, occurring between the Rossby waves and differential rotation. But in MHD cases, energy exchange becomes much more complex, involving energy flow among six energy reservoirs by means of eight different energy conversion processes. For toroidal magnetic bands of 5 and 35 kG peak amplitudes, both placed at 45° latitude and oppositely directed in north and south hemispheres, we show that the energy transfers responsible for TNO, as well as westward phase propagation, are evident in synoptic maps of the flow, magnetic field, and tachocline top-surface deformations. Nonlinear mode–mode interaction is particularly dramatic in the strong-field case. We also find that the TNO period increases with a decrease in rotation rate, implying that the younger Sun had more frequent seasons.

The ocean and the atmosphere, and hence the climate, are governed at large scale by interactions between pressure gradient and Coriolis and buoyancy forces. This leads to a quasigeostrophic balance in which, in a two-dimensional-like fashion, the energy injected by solar radiation, winds, or tides goes to large scales in what is known as an inverse cascade. Yet, except for Ekman friction, energy dissipation and turbulent mixing occur at a small scale implying the formation of such scales associated with breaking of geostrophic dynamics through wave-eddy interactions or frontogenesis, in opposition to the inverse cascade. Can it be both at the same time? We exemplify here this dual behavior of energy with the help of three-dimensional direct numerical simulations of rotating stratified Boussinesq turbulence. We show that efficient small-scale mixing and large-scale coherence develop simultaneously in such geophysical and astrophysical flows, both with constant flux as required by theoretical arguments, thereby clearly resolving the aforementioned contradiction.

The occurrence and nature of a nonlinear energy cascade within the intermediate scales of solar wind Alfvenic turbulence represents an important open issue. Using in situ measurements of fast, high latitude solar wind taken by the Ulysses spacecraft at solar minima, it is possible to show that a nonlinear energy cascade of imbalanced turbulence is only observed when the solar wind owns peculiar properties. These are the reduction of the local correlation between velocity and magnetic field (weak cross-helicity); the presence of large-scale velocity shears; and the steepening and extension down to low frequencies of the turbulent spectra. Our observations suggest the important role of both large-scale velocity and Alfvenicity of the field fluctuations for the validation of the Yaglom law in solar wind turbulence.

We present results from two 15363 direct numerical simulations of rotating turbulence where both energy and helicity are injected into the flow by an external forcing. The dual cascade of energy and helicity toward smaller scales observed in isotropic and homogeneous turbulence is broken in the presence of rotation, with the development of an inverse cascade of energy now coexisting with direct cascades of energy and helicity. In the direct cascade range, the flux of helicity dominates over that of energy at low Rossby number. These cascades have several consequences for the statistics of the flow. The evolution of global quantities and of the energy and helicity spectra is studied, and comparisons with simulations at different Reynolds and Rossby numbers at lower resolution are done to identify scaling laws.

The Kepler space telescope yielded unprecedented data for the study of solar-like oscillations in other stars. The large samples of multi-year observations posed an enormous data analysis challenge that has only recently been surmounted. Asteroseismic modeling has become more sophisticated over time, with better methods gradually developing alongside the extended observations and improved data analysis techniques. We apply the latest version of the Asteroseismic Modeling Portal (AMP) to the full-length Kepler data sets for 57 stars, comprising planetary hosts, binaries, solar-analogs, active stars, and for validation purposes, the Sun. From an analysis of the derived stellar properties for the full sample, we identify a variation of the mixing-length parameter with atmospheric properties. We also derive a linear relation between the stellar age and a characteristic frequency separation ratio. In addition, we find that the empirical correction for surface effects suggested by Kjeldsen and coworkers is adequate for solar-type stars that are not much hotter ( T eff ≲6200 K) or significantly more evolved (log g ≳4.2, ⟨ Δ ν ⟩≳80 μ Hz) than the Sun. Precise parallaxes from the Gaia mission and future observations from TESS and PLATO promise to improve the reliability of stellar properties derived from asteroseismology.

We present results from two 15363 direct numerical simulations of rotating turbulence where both energy and helicity are injected into the flow by an external forcing. The dual cascade of energy and helicity toward smaller scales observed in isotropic and homogeneous turbulence is broken in the presence of rotation, with the development of an inverse cascade of energy now coexisting with direct cascades of energy and helicity. In the direct cascade range, the flux of helicity dominates over that of energy at low Rossby number. These cascades have several consequences for the statistics of the flow. The evolution of global quantities and of the energy and helicity spectra is studied, and comparisons with simulations at different Reynolds and Rossby numbers at lower resolution are done to identify scaling laws. © 2010 American Institute of Physics.

In this paper, we describe how inverse space-filling curve partitioning is used to increase the simulation rate of a global ocean model. Space-filling curve partitioning allows for the elimination of load imbalance in the computational grid due to land points. Improved load balance combined with code modifications within the conjugate gradient solver significantly increase the simulation rate of the parallel ocean program at high resolution. The simulation rate for a high resolution model nearly doubled from 4.0 to 7.9 simulated years per day on 28,972 IBM Blue Gene/L processors. We also demonstrate that our techniques increase the simulation rate on 7545 Cray XT3 processors from 6.3 to 8.1 simulated years per day. Our results demonstrate how minor code modifications can have significant impact on resulting performance for very large processor counts.

We study the intermittency properties of the energy and helicity cascades in two 15363 direct numerical simulations of helical rotating turbulence. Symmetric and antisymmetric velocity increments are examinedas well as probability density functions of the velocity field and of the helicity density. It is found that the direct cascade of energy to small scales is scale invariant and nonintermittentwhereas the direct cascade of helicity is highly intermittent. Furthermorethe study of structure functions of different orders allows us to identify a recovery of isotropy of strong events at very small scales in the flow. Finallywe observe the juxtaposition in space of strong laminar and persistent helical columns next to time-varying vortex tanglesthe former being associated with the self-similarity of energy and the latter with the intermittency of helicity. © 2010 American Institute of Physics.

We study the intermittency properties of the energy and helicity cascades in two 15363 direct numerical simulations of helical rotating turbulence. Symmetric and antisymmetric velocity increments are examined, as well as probability density functions of the velocity field and of the helicity density. It is found that the direct cascade of energy to small scales is scale invariant and nonintermittent, whereas the direct cascade of helicity is highly intermittent. Furthermore, the study of structure functions of different orders allows us to identify a recovery of isotropy of strong events at very small scales in the flow. Finally, we observe the juxtaposition in space of strong laminar and persistent helical columns next to time-varying vortex tangles, the former being associated with the self-similarity of energy and the latter with the intermittency of helicity.

Selection protocols such as SELEX, where molecules are selected over multiple rounds for their ability to bind to a target of interest, are popular methods for obtaining binders for diagnostic and therapeutic purposes. We show that Restricted Boltzmann Machines (RBMs), an unsupervised two-layer neural network architecture, can successfully be trained on sequence ensembles from single rounds of SELEX experiments for thrombin aptamers. RBMs assign scores to sequences that can be directly related to their fitnesses estimated through experimental enrichment ratios. Hence, RBMs trained from sequence data at a given round can be used to predict the effects of selection at later rounds. Moreover, the parameters of the trained RBMs are interpretable and identify functional features contributing most to sequence fitness. To exploit the generative capabilities of RBMs, we introduce two different training protocols: one taking into account sequence counts, capable of identifying the few best binders, and another based on unique sequences only, generating more diverse binders. We then use RBMs model to generate novel aptamers with putative disruptive mutations or good binding properties, and validate the generated sequences with gel shift assay experiments. Finally, we compare the RBM's performance with different supervised learning approaches that include random forests and several deep neural network architectures.

Abstract. Predicting major floods during extreme rainfall events remains an important challenge. Rapid changes in flows over short timescales, combined with multiple sources of model error, makes it difficult to accurately simulate intense floods. This study presents a general data assimilation framework that aims to improve flood predictions in channel routing models. Hurricane Florence, which caused catastrophic flooding and damages in the Carolinas in September 2018, is used as a case study. The National Water Model (NWM) configuration of the WRF-Hydro modeling framework is interfaced with the Data Assimilation Research Testbed (DART) to produce ensemble streamflow forecasts and analyses. Instantaneous streamflow observations from 107 United States Geological Survey (USGS) gauges are assimilated for a period of 1 month. The data assimilation (DA) system developed in this paper explores two novel contributions, namely (1) along-the-stream (ATS) covariance localization and (2) spatially and temporally varying adaptive covariance inflation. ATS localization aims to mitigate not only spurious correlations, due to limited ensemble size, but also physically incorrect correlations between unconnected and indirectly connected state variables in the river network. We demonstrate that ATS localization provides improved information propagation during the model update. Adaptive prior inflation is used to tackle errors in the prior, including large model biases which often occur in flooding situations. Analysis errors incurred during the update are addressed using posterior inflation. Results show that ATS localization is a crucial ingredient of our hydrologic DA system, providing at least 40 % more accurate (root mean square error) streamflow estimates than regular, Euclidean distance-based localization. An assessment of hydrographs indicates that adaptive inflation is extremely useful and perhaps indispensable for improving the forecast skill during flooding events with significant model errors. We argue that adaptive prior inflation is able to serve as a vigorous bias correction scheme which varies both spatially and temporally. Major improvements over the model's severely underestimated streamflow estimates are suggested along the Pee Dee River in South Carolina, and many other locations in the domain, where inflation is able to avoid filter divergence and, thereby, assimilate significantly more observations.

We investigate the ideal and incompressible magnetohydrodynamic (MHD) equations in three space dimensions for the development of potentially singular structures. The methodology consists in implementing the fourfold symmetries of the Taylor-Green vortex generalized to MHD, leading to substantial computer time and memory savings at a given resolution; we also use a regridding method that allows for lower-resolution runs at early times, with no loss of spectral accuracy. One magnetic configuration is examined at an equivalent resolution of 6144(3) points and three different configurations on grids of 4096(3) points. At the highest resolution, two different current and vorticity sheet systems are found to collide, producing two successive accelerations in the development of small scales. At the latest time, a convergence of magnetic field lines to the location of maximum current is probably leading locally to a strong bending and directional variability of such lines. A novel analytical method, based on sharp analysis inequalities, is used to assess the validity of the finite-time singularity scenario. This method allows one to rule out spurious singularities by evaluating the rate at which the logarithmic decrement of the analyticity-strip method goes to zero. The result is that the finite-time singularity scenario cannot be ruled out, and the singularity time could be somewhere between t=2.33 and t=2.70. More robust conclusions will require higher resolution runs and grid-point interpolation measurements of maximum current and vorticity.

A posteriori error estimation is an important tool for reliable and efficient Galerkin boundary element computations. For hypersingular integral equations in 2D with a positive-order Sobolev space, we analyse the mathematical relation between the (h − h/2)-error estimator from [S. Ferraz-Leite and D. Praetorius, Simple a posteriori error estimators for the h-version of the boundary element method, Computing 83 (2008), pp. 135–162], the two-level error estimator from [M. Maischak, P. Mund, and E. Stephan, Adaptive multilevel BEM for acoustic scattering, 585 Comput. Methods Appl. Mech. Eng. 150 (1997), pp. 351–367], and the averaging error estimator from [C. Carstensen and D. Praetorius, Averaging techniques for the a posteriori bem error control for a hypersingular integral equation in two dimensions, SIAM J. Sci. Comput. 29 (2007), pp. 782–810]. All of these a posteriori error estimators are simple in the following sense: first, the numerical analysis can be done within the same mathematical framework, namely localization techniques for the energy norm. Second, there is almost no implementational overhead for the realization.

We first summarize briefly several properties concerning the dynamics of two-dimensional (2D) turbulence, with an emphasis on the inverse cascade of energy to the largest accessible scale of the system. In order to study a similar phenomenon in 3D turbulence undergoing strong solid-body rotation, we test a previously developed large eddy simulation (LES) model against a high-resolution direct numerical simulation of rotating turbulence on a grid of 3072 3 points. We then describe new numerical results on the inverse energy cascade in rotating flows using this LES model and contrast the case of 2D versus 3D forcing, as well as non-helical forcing (i.e. with weak overall alignment between velocity and vorticity) versus the fully helical Beltrami case, for both deterministic and random forcing. The different scaling laws for the inverse energy cascade can be attributed to the dimensionality of the forcing, with either a k -3 or a k -5/3 energy spectrum of slow modes at large scales, k referring to a direction perpendicular to that of rotation. We finally invoke the role of shear in the case of a strongly anisotropic deterministic forcing, using the so-called ABC flow; in that case, a k -5/3 is again observed for the slow modes, together with a k -1 spectrum for the total energy associated with enhanced shear at a large scale

Improving the precision and function of encapsulating three-dimensional (3D) DNA nanostructures via curved geometries could have transformative impacts on areas such as molecular transport, drug delivery, and nanofabrication. However, the addition of non-rasterized curvature escalates design complexity without algorithmic regularity, and these challenges have limited the ad hoc development and usage of previously unknown shapes. In this work, we develop and automate the application of a set of previously unknown design principles that now includes a multilayer design for closed and curved DNA nanostructures to resolve past obstacles in shape selection, yield, mechanical rigidity, and accessibility. We design, analyze, and experimentally demonstrate a set of diverse 3D curved nanoarchitectures, showing planar asymmetry and examining partial multilayer designs. Our automated design tool implements a combined algorithmic and numerical approximation strategy for scaffold routing and crossover placement, which may enable wider applications of general DNA nanostructure design for nonregular or oblique shapes.

Abstract. Assimilation of atmospheric composition retrievals presents computational challenges due to their high data volume and often sparse information density. Assimilation of compact phase space retrievals (CPSRs) meets those challenges and offers a promising alternative to assimilation of raw retrievals at reduced computational cost (Mizzi et al., 2016). This paper compares analysis and forecast results from assimilation of Terra/Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) CPSRs with independent observations. We use MetOp-A/Infrared Atmospheric Sounding Interferometer (IASI) CO retrievals and Measurement of OZone, water vapor, carbon monoxide, and nitrogen oxides by in-service AIrbus airCraft (MOZAIC) in situ CO profiles for our independent observation comparisons. Generally, the results confirm that assimilation of MOPITT CPSRs improves the Weather Research and Forecasting model with chemistry coupled to the ensemble Kalman filter data assimilation from the Data Assimilation Research Testbed (WRF-Chem/DART) analysis fit and forecast skill at a reduced computational cost compared to assimilation of raw retrievals. Comparison with the independent observations shows that assimilation of MOPITT CO generally improved the analysis fit and forecast skill in the lower troposphere but degraded it in the upper troposphere. We attribute that degradation to assimilation of MOPITT CO retrievals with a possible bias of ∼ 14 % above 300 hPa. To discard the biased retrievals, in this paper, we also extend CPSRs to assimilation of truncated retrieval profiles (as opposed to assimilation of full retrieval profiles). Those results show that not assimilating the biased retrievals (i) resolves the upper tropospheric analysis fit degradation issue and (ii) reduces the impact of assimilating the remaining unbiased retrievals because the total information content and vertical sensitivities are changed.

We examine long-time properties of the ideal dynamics of three-dimensional flows, in the presence or not of an imposed solid-body rotation and with or without helicity (velocity-vorticity correlation). In all cases, the results agree with the isotropic predictions stemming from statistical mechanics. No accumulation of excitation occurs in the large scales, although, in the dissipative rotating case, anisotropy and accumulation, in the form of an inverse cascade of energy, are known to occur. We attribute this latter discrepancy to the linearity of the term responsible for the emergence of inertial waves. At intermediate times, inertial energy spectra emerge that differ somewhat from classical wave-turbulence expectations and with a trace of large-scale excitation that goes away for long times. These results are discussed in the context of partial two dimensionalization of the flow undergoing strong rotation as advocated by several authors.