High-resolution Simulations Research Articles

Turbulent Ice–Ocean Boundary Layers in the Well-Mixed Regime: Insights from Direct Numerical Simulations

Abstract The meltwater mixing line (MML) model provides a theoretical prediction of near-ice water mass properties that is useful to compare with observations. If oceanographic measurements reported in a temperature–salinity diagram overlap with the MML prediction, then it is usually concluded that the local dynamics are dominated by the turbulent mixing of an ambient water mass with near-ice meltwater. While the MML model is consistent with numerous observations, it is built on an assumption that is difficult to test with field measurements, especially near the ice boundary, namely, that the effective (turbulent and molecular) salt and temperature diffusivities are equal. In this paper, this assumption is tested via direct numerical simulations of a canonical model for externally forced ice–ocean boundary layers in a uniform ambient. We focus on the well-mixed regime by considering an ambient temperature close to freezing and run the simulations until a statistical steady state is reached. The results validate the assumption of equal effective diffusivities across most of the boundary layer. Importantly, the validity of the MML model implies a linear correlation between the mean salinity and temperature profiles normal to the interface that can be leveraged to construct a reduced ice–ocean boundary layer model based on a single scalar variable called thermal driving. We demonstrate that the bulk dynamics predicted by the reduced thermal driving model are in good agreement with the bulk dynamics predicted by the full temperature–salinity model. Then, we show how the results from the thermal driving model can be used to estimate the interfacial heat and salt fluxes and the melt rate. Significance Statement We investigate the turbulent dynamics and thermodynamical properties of water masses below ice shelves using new data from high-resolution simulations. This is important because there are currently too few observations of ice–ocean boundary layer dynamics to construct reliable models of ice-shelf melting as a function of ocean conditions. Our results demonstrate that the turbulent diffusivities of salt and temperature are approximately equal in the well-mixed regime. This implies a linear correlation between the mean temperature and salinity profiles, consistent with the meltwater mixing line prediction that is often used to interpret polar observations. We take advantage of this correlation to propose a reduced model of ice–ocean boundary layers that can predict ice-shelf melt rates at relatively low computational cost.

HYACINTH: HYdrogen And Carbon chemistry in the INTerstellar medium in Hydro simulations

Aims. We present a new sub-grid model, HYACINTH – HYdrogen And Carbon chemistry in the INTerstellar medium in Hydro simulations – for computing the non-equilibrium abundances of H2 and its carbon-based tracers, namely CO, C, and C+, in cosmological simulations of galaxy formation. Methods. The model accounts for the unresolved density structure in simulations using a variable probability distribution function of sub-grid densities and a temperature-density relation. Included is a simplified chemical network that has been tailored for hydrogen and carbon chemistry within molecular clouds and easily integrated into large-scale simulations with minimal computational overhead. As an example, we applied HYACINTH to a simulated galaxy at redshift z ~ 2.5 in post-processing and compared the resulting abundances with observations. Results. The chemical predictions from HYACINTH are in reasonable agreement with high-resolution molecular-cloud simulations at different metallicities. By post-processing a galaxy simulation with HYACINTH, we reproduced the H I − H2 transition as a function of the hydrogen column density NH for both Milky-Way-like and Large-Magellanic-Cloud-like conditions. We also matched the NCO versus NH2 relation inferred from absorption measurements towards Milky-Way molecular clouds, although most of our post-processed regions occupy the same region as (optically) dark molecular clouds in the NCO – NH2 plane. Column density maps reveal that CO is concentrated in the peaks of the H2 distribution, while atomic carbon more broadly traces the bulk of H2 in our post-processed galaxy. Based on both the column density maps and the surface density profiles oŕ the different gas species in the post-processed galaxy, we find that C+ maintains a substantially high surŕace density out to ~10 kpc as opposed to other components that exhibit a higher central concentration. This is similar to the extended [C II] emission ŕound in some recent observations at high redshifts.

The clustering of Lyman Alpha Emitting galaxies at 𝗓=2–3

We measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs at z = 2.45 and 3.1 in 9 sq.deg. centered on the COSMOS field with median Lyα fluxes of ≈ 10-16 erg s-1 cm-2. Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length of r 0 = 3.0 ± 0.2 h-1 Mpc. Within our fiducial cosmology these correspond to 3D number densities of ≈ 10-3 h3 Mpc-3 and, from our mock catalogs, biases of 1.7 and 2.0 at z = 2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology.

Field-split preconditioned active-set reduced-space algorithm for complex black oil reservoir simulation at large-scale

Accurate black oil reservoir simulation is important for the understanding of underground resources in hydrology and petroleum reservoir engineering. The success of fast prediction relies on a robust and scalable black oil simulator, which can handle the complex subsurface fluid dynamics with coupling several different physical processes, and meanwhile run efficiently on distributed memory parallel computers. In this work, we introduce a highly parallel simulator to accurately compute the reservoir flow coupling with wells, including some adaptive fully implicit schemes for the temporal discretization, the improved active-set reduced-space algorithm for the nonlinear algebraic system, and several types of field-split methods for preconditioning. This parallel simulator is applied on the domain decomposition framework, which is designed to overcome the computational issues of traditional simulators implemented for personal computers or small workstations. High-resolution reservoir simulation results on the Society of Petroleum Engineers (SPE) comparative solution project or real-field cases are obtained and analyzed, and the parallel performance of the algorithm is studied on a supercomputer with scaling up to 27440 processor cores. The numerical experiments indicate that the proposed black oil simulator is capable of accurately predicting the highly complex physical processes and interactions between wells and the reservoir for full field scale simulation.

Concurrent Accretion and Migration of Giant Planets in Their Natal Disks with Consistent Accretion Torque

Migration commonly occurs during the epoch of planet formation. For emerging gas giant planets, it proceeds concurrently with their growth through the accretion of gas from their natal protoplanetary disks. A similar migration process should also be applied to the stellar-mass black holes embedded in active galactic nucleus disks. In this work, we perform high-resolution 3D and 2D numerical hydrodynamical simulations to study the migration dynamics for accreting embedded objects over the disk viscous timescales in a self-consistent manner. We find that an accreting planet embedded in a predominantly viscous disk has a tendency to migrate outward, in contrast to the inward orbital decay of nonaccreting planets. 3D and 2D simulations find the consistent outward migration results for the accreting planets. Under this circumstance, the accreting planet’s outward migration is mainly due to the asymmetric spiral arms feeding from the global disk into the Hill radius. This is analogous to the unsaturated corotation torque although the imbalance is due to material accretion within the libration timescale rather than diffusion onto the inner disk. In a disk with a relatively small viscosity, the accreting planets clear deep gaps near their orbits. The tendency of inward migration is recovered, albeit with suppressed rates. By performing a parameter survey with a range of disks’ viscosity, we find that the transition from outward to inward migration occurs with the effective viscous efficiency factor α ∼ 0.003 for Jupiter-mass planets.

Sparsity and mixing effects in deep learning predictions of temperature and humidity

Developing deep learning models for predicting environmental data is a powerful tool that can significantly enhance equipment design, optimize the implementation of engineering systems, and deepen our understanding of the limitations imposed by flow physics. This study unequivocally demonstrates the accuracy of forecasting models based on popular deep learning algorithms, such as the long-short-term memory model, in turbulent mixing regions associated with flow physics arising from ventilation. This accuracy is contingent on two essential conditions. First, the sparsity of the sampling data is consistent with the model's accuracy overall. Second, the data sparsity ensures reasonable accuracy in the turbulent mixing regions. The investigation combines high-resolution flow simulation data with deep learning predictions of velocity, temperature, and relative humidity in a ventilated confined space. The results of this study, with their high accuracy, not only help to understand the mixing arising from flow circulation but also pave the way for developing predictive capabilities for environmental data.

Measuring the Conditional Luminosity and Stellar Mass Functions of Galaxies by Combining the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 Data

In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r- and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ∼109 h −2 L ⊙ (or h −2 M ⊙) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function.

Toward Parameterizing Eddy-Mediated Transport of Warm Deep Water across the Weddell Sea Continental Slope

Abstract The transport of warm deep water (WDW) onto the Weddell Sea continental shelf is associated with heat flux and strongly contributes to the melting of Antarctic ice shelves. The small radius of deformation at high latitudes makes it difficult to accurately represent the eddy-driven component of onshore WDW transport in coarse-resolution ocean models so that parameterization becomes necessary. The Gent and McWilliams/Redi (GM/Redi) scheme was designed to parameterize mesoscale eddies in the open ocean. Here, it is assessed to what extent the GM/Redi scheme can generate a realistic transport of WDW across the Weddell Sea continental slope. To this end, the eddy parameterization is applied to a coarse-resolution idealized model of the Weddell Sea continental shelf and slope, and its performance is evaluated against a high-resolution reference simulation. With the GM/Redi parameterization applied, the coarse model simulates a shoreward WDW transport with a heat transport that matches the high-resolution reference and both the hydrographic mean fields and the mean slopes of the isopycnals are improved. A successful application of the GM/Redi parameterization is only possible by reducing the GM diffusivity over the continental slope by an order of magnitude compared to the open ocean value to account for the eddy-suppressing effect of the topographic slope. When the influence of topography on the GM diffusivity is neglected, the coarse model with the parameterization either under- or overestimates the shoreward heat flux. These results motivate the incorporation of slope-aware eddy parameterizations into regional and global ocean models. Significance Statement Mesoscale eddies drive warm water across the continental slope and onto the continental shelf of the Weddell Sea, where it melts the adjacent Antarctic ice shelves. This process is not resolved in ocean models employing a coarse horizontal resolution akin to state-of-the-art climate models. This work addresses this issue by modifying and applying a well-established eddy parameterization to this specific case. The parameterization works particularly well when it accounts for the effect of sloping topography, over which eddy transports are weaker. We expect this modification also to be of benefit to regional and global models.

Strong Bow Shocks: Turbulence and an Exact Self-similar Asymptotic

We show that strong bow shocks are turbulent and nonuniversal near the head but asymptote to a universal, steady, self-similar, and analytically solvable flow in the downstream. The turbulence is essentially 3D and has been confirmed by a 3D simulation. The asymptotic behavior is confirmed with high-resolution 2D and 3D simulations of a cold uniform wind encountering both a solid spherical obstacle and stellar wind. This solution is relevant in the context of (i) probing the kinematic properties of observed high-velocity compact bodies—e.g., runaway stars and/or supernova ejecta blobs—flying through the interstellar medium; and (ii) constraining stellar bow shock luminosities invoked by some quasiperiodic eruption models.

Resolution analysis of magnetically arrested disc simulations

ABSTRACT Polarization measurements by the Event Horizon Telescope from M87* and Sgr A* suggest that there is a dynamically strong, ordered magnetic field, typical of what is expected of a magnetically arrested accretion disc (MAD). In such discs, the strong poloidal magnetic field can suppress the accretion flow and cause episodic flux eruptions. Recent work shows that general relativistic magnetohydrodynamic (GRMHD) MAD simulations feature dynamics of turbulence and mixing instabilities that are becoming resolved at higher resolutions. We perform a convergence study of MAD states exceeding the status quo by an order of magnitude in resolution. We use existing 3D simulations performed with the H-AMR code, up to a resolution of 5376 × 2304 × 2304 in a logarithmic spherical-polar grid. We find consistent time-averaged disc properties across all resolutions. However, higher resolutions reveal signs of inward angular momentum transport attributed to turbulent convection, particularly evident when mixing instabilities occur at the surfaces of flux tubes during flux eruptions. Additionally, we see wave-like features in the jet sheath, which become more prominent at higher resolutions, that may induce mixing between the jet and disc. At higher resolutions, we observe the sheath to be thinner, resulting in increased temperature, reduced magnetization, and greater variability. Those differences could affect the dissipation of energy, which would eventually result in distinct observable radiative emission from high-resolution simulations. With higher resolutions, we can delve into crucial questions about horizon-scale physics and its impact on the dynamics and emission properties of larger-scale jets.

A Critical Evaluation and Future Projection of Extreme Precipitation Over South Korea in Observation-Based Products and a High-Resolution Model Simulation

A Critical Evaluation and Future Projection of Extreme Precipitation Over South Korea in Observation-Based Products and a High-Resolution Model Simulation

A more quiescent deep ocean under global warming

The ocean is a magnificent reservoir of kinetic energy possessed by currents at diverse spatio-temporal scales. These currents transport heat and material, regulating the regional and global climate. It is generally thought that large-scale ocean circulations should become more energetic under global warming, especially in the ocean’s upper layer. However, using high-resolution global climate simulations, here we demonstrate that the total ocean kinetic energy is projected to be significantly reduced in a warming climate, despite overall acceleration of large-scale ocean circulations in the upper layer. This reduction is primarily attributed to weakened ocean mesoscale eddies in the deep ocean. Enhanced vertical stratification under global warming reduces the available potential energy stored in large-scale ocean circulations, diminishing its conversion into eddy kinetic energy. Our findings reveal a more quiescent deep ocean under global warming and suggest a crucial role of mesoscale eddies in determining the anthropogenic change of total ocean kinetic energy.

Thermal vortex ring: vortex-dynamics analysis of a high-resolution simulation

A high-resolution simulation of a thermal vortex ring is analysed from the point of view of the vortex dynamics. A power-spectrum analysis of vortex-ring sections suggests that the simulated flows are overall ‘two dimensional’ in the large-scale limit, being dominated by axisymmetric components, but with a substantial contribution from the non-axisymmetric component at small scales. Contribution of the non-axisymmetric components is negligible in budgets of volume integrals of the vorticity and potential vorticity as well as the impulse (moments of the vorticity weighted by $s^n$ with $n=-1$ , 0, 1, where $s$ is the distance from the vertical axis of the vortex ring). A concise description of the dynamics is obtained as a function of geometrical factors together with these three integral variables. Analysis shows that the geometrical factors are fairly close to constant with time, and thus, a redundant closed description of the system is obtained in the similarity regime after spin up of the vortex ring. This redundancy leads to a constraint on the geometrical factors, which is reasonably satisfied by the simulation. A closed description is also obtained over the initial spin-up period of the vortex ring by adding a phenomenologically derived prognostic equation for the source for the volume integral of the potential vorticity (with $n=-1$ ). Analysis of the budget supports this description.

Data-driven constitutive meta-modeling of nonlinear rheology via multifidelity neural networks

Predicting the response of complex fluids to different flow conditions has been the focal point of rheology and is generally done via constitutive relations. There are, nonetheless, scenarios in which not much is known from the material mathematically, while data collection from samples is elusive, resource-intensive, or both. In such cases, meta-modeling of observables using a parametric surrogate model called multi-fidelity neural networks (MFNNs) may obviate the constitutive equation development step by leveraging only a handful of high-fidelity (Hi-Fi) data collected from experiments (or high-resolution simulations) and an abundance of low-fidelity (Lo-Fi) data generated synthetically to compensate for Hi-Fi data scarcity. To this end, MFNNs are employed to meta-model the material responses of a thermo-viscoelastic (TVE) fluid, consumer product Johnson’s® Baby Shampoo, under four flow protocols: steady shear, step growth, oscillatory, and small/large amplitude oscillatory shear (S/LAOS). In addition, the time–temperature superposition (TTS) of the material response and MFNN predictions are explored. By applying simple linear regression (without induction of any constitutive equation) on log-spaced Hi-Fi data, a series of Lo-Fi data were generated and found sufficient to obtain accurate material response recovery in terms of either interpolation or extrapolation for all flow protocols except for S/LAOS. This insufficiency is resolved by informing the MFNN platform with a linear constitutive model (Maxwell viscoelastic) resulting in simultaneous interpolation and extrapolation capabilities in S/LAOS material response recovery. The roles of data volume, flow type, and deformation range are discussed in detail, providing a practical pathway to multifidelity meta-modeling of different complex fluids.

No Catch-22 for fuzzy dark matter: testing substructure counts and core sizes via high-resolution cosmological simulations

ABSTRACT Fuzzy dark matter (FDM) has recently emerged as an interesting alternative model to the standard cold dark matter (CDM). In this model, dark matter consists of very light bosonic particles with wave-like behaviour on galactic scales. Using the N-body code ax-gadget, we perform cosmological simulations of FDM that fully model the dynamical effects of the quantum potential throughout cosmic evolution. Through the combined analysis of FDM volume and high-resolution zoom-in simulations of different FDM particle masses ($m_{\chi }$$\sim$$10^{-23}\!-\!10^{-21}$ eV c−2), we study how FDM impacts the abundance of substructure and the inner density profiles of dark matter haloes. For the first time, using our FDM volume simulations, we provide a fitting formula for the FDM-to-CDM subhalo abundance ratio as a function of the FDM mass. More importantly, our simulations clearly demonstrate that there exists an extended FDM particle mass interval able to reproduce the observed substructure counts and, at the same time, create substantial cores ($r_{c} \sim 1$ kpc) in the density profile of dwarf galaxies ($\approx 10^{9}\!-\!10^{10}$ M$_{\odot }$), which stands in stark contrast with CDM predictions even with baryonic effects taken into account. The dark matter distribution in the faintest galaxies offers then a clear way to discriminate between FDM and CDM.

Metallicity distributions of halo stars: do they trace the Galactic accretion history?

The standard cosmological scenario predicts a hierarchical formation for galaxies. Many substructures have been found in the Galactic halo, usually identified as clumps in kinematic spaces, like the energy-angular momentum space ($E-L_z$), under the hypothesis that these quantities should be conserved during the interaction. If these clumps also feature different chemical abundances, such as the metallicity distribution function (MDF), these two arguments together (different kinematic and chemical properties) are often used to motivate their association with distinct and independent merger debris. The aim of this study is to explore to what extent we can couple kinematic characteristics and metallicities of stars in the Galactic halo to reconstruct the accretion history of the Milky Way (MW). In particular, we want to understand whether different clumps in the $E-L_z$ space with different MDFs should be associated with distinct merger debris. We analysed dissipationless, self-consistent, high-resolution N-body simulations of a MW-type galaxy accreting a satellite with a mass ratio of 1:10, with different orbital parameters and different metallicity gradients, which were assigned a posteriori. We confirm that accreted stars from a sim 1:10 mass ratio merger event redistribute in a wide range of $E$ and $L_z$, due to the dynamical friction process, and are thus not associated with a single region. Because satellite stars with different metallicities can be deposited in different regions of the $E-L_z$ space (on average the more metal-rich ones end up more gravitationally bound to the MW), this implies that a single accretion of sim 1:10 can manifest with different MDFs, in different regions of the $E-L_z$ space. Groups of stars with different $E$, $L_z$, and metallicities may be interpreted as originating from different satellite galaxies, but our analysis shows that these interpretations are not physically motivated. In fact, as we show, the coupling of kinematic information with MDFs to reconstruct the accretion history of the MW can bias the reconstructed merger tree towards increasing the number of past accretions and decreasing the masses of the progenitor galaxies.

Chemo-dynamical Evolution of Simulated Satellites for a Milky Way–like Galaxy

The chemical abundances of Milky Way’s (MW's) satellites reflect their star formation histories (SFHs), yet, due to the difficulty of determining the ages of old stars, the SFHs of most satellites are poorly measured. Ongoing and upcoming surveys will obtain around 10 times more medium-resolution spectra for stars in satellites than are currently available. To correctly extract SFHs from large samples of chemical abundances, the relationship between chemical abundances and SFHs needs to be clarified. Here, we perform a high-resolution cosmological zoom-in simulation of a MW-like galaxy with detailed models of star formation, supernova (SN) feedback, and metal diffusion. We quantify SFHs, metallicity distribution functions, and the α-element (Mg, Ca, and Si) abundances in satellites of the host galaxy. We find that star formation in most simulated satellites is quenched before infalling to their host. Star formation episodes in simulated satellites are separated by a few hundred Myr owing to SN feedback; each star formation event produces groups of stars with similar [α/Fe] and [Fe/H]. We then perform a mock observation of the upcoming Subaru Prime Focus Spectrograph (PFS) observations. We find that Subaru PFS will be able to detect distinct groups of stars in [α/Fe] versus [Fe/H] space, produced by episodic star formation. This result means that episodic SFHs can be estimated from the chemical abundances of ≳1000 stars determined with medium-resolution spectroscopy.

Reconstructing Younger Dryas ground temperature and snow thickness from cave deposits

Abstract. The Younger Dryas stadial was characterised by a rapid shift towards cold-climate conditions in the North Atlantic realm during the last deglaciation. While some climate parameters including atmospheric temperature and glacier extent are widely studied, empirical constraints on permafrost temperature and snow thickness are limited. To address this, we present a regional dataset of cryogenic cave carbonates (CCCs) from three caves in Great Britain that formed at temperatures between −2 and 0 °C. Our CCC record indicates that these permafrost temperatures persisted for most of the Younger Dryas. By combining ground temperatures with surface temperatures from high-resolution ground-truthed model simulations, we demonstrate that ground temperatures were approximately 6.6 ± 2.3 °C warmer than the mean annual air temperature. Our results suggest that the observed temperature offset between permafrost and the atmosphere can be explained by an average snow thickness between 0.2 and 0.9 m, which persisted for 233 ± 54 d per year. By identifying modern analogues from climate reanalysis data, we demonstrate that the inferred temperature and snow cover characteristics for the British Isles during the Younger Dryas are best explained by extreme temperature seasonality, comparable to continental parts of today's Arctic Archipelago. Such a climate for the British Isles necessitates a winter sea ice margin at approximately 45° N in the North Atlantic Ocean.

From nutrients to fish: Impacts of mesoscale processes in a global CESM-FEISTY eddying ocean model framework

The ocean sustains ecosystems that are essential for human livelihood and habitability of the planet. The ocean holds an enormous amount of carbon, and serves as a critical source of nutrition for human societies worldwide. Climate variability and change impact marine biogeochemistry and ecosystems. Thus, having state-of-the-art simulations of the ocean, which include marine biogeochemistry and ecosystems, is critical for understanding the role of climate variability and change on the ocean biosphere. Here we present a novel global eddy-resolving (0.1° horizontal resolution) simulation of the ocean and sea ice, including ocean biogeochemistry, performed with the Community Earth System Model (CESM). The simulation is forced by the atmospheric dataset based on the Japanese Reanalysis (JRA-55) product over the 1958–2021 period. We present a novel configuration of the CESM marine ecosystem model in this simulation which includes two zooplankton classes: microzooplankton and mesozooplankton. This novel planktonic food web structure facilitates “offline” coupling with the Fisheries Size and Functional Type (FEISTY) model. FEISTY is a size- and trait-based model of fish functional types contributing to fisheries. We present an evaluation of the ocean biogeochemistry, marine ecosystem (including fish types), and sea ice in this high resolution simulation compared to available observations and a corresponding low resolution (nominal 1°) simulation. Our analysis offers insights into environmental controls on trophodynamics within the ocean. We find that this high resolution simulation provides a realistic reconstruction of nutrients, oxygen, sea ice, plankton and fish distributions over the global ocean. On global and large regional scales the high resolution simulation is comparable to the standard 1° simulation, but on smaller scales, explicitly resolving the mesoscale dynamics is shown to be important for accurately capturing trophodynamic structuring, especially in coastal ecosystems. We show that fine-scale ocean features leave imprints on ocean ecosystems, from plankton to fish, from the tropics to polar regions. This simulation also offers insights on ocean acidification over the past 64 years, as well as how large-scale climate variations may impact upper trophic levels. The data generated by the simulations are publicly available and will be a fruitful community resource for a large variety of oceanographic science questions.

Solute transport in unsaturated porous media with spatially correlated disorder

Solute transport in unsaturated porous media is of interest in many engineering and environmental applications. The interplay between small-scale, local forces and the porous microstructure exerts a strong control on the transport of fluids and solutes at the larger, macroscopic scales. Heterogeneity in pore geometry is intrinsic to natural materials across a large range of scales. This multiscale nature, and the intricate links between two-phase flow and solute transport, remain far from well understood, by and large. Here, we use high-resolution direct simulation to quantify solute mixing and dispersion behavior within correlated porous media during drainage under an unfavorable viscosity ratio. Through analysis of flow and transport at multiple realizations, we find that increasing spatial correlations in pore sizes increase the size of the required Representative Elementary Volume (REV). We show that increasing the correlation length enhances solute dispersivity through its impact on the spatial distribution of low-velocity (diffusion-dominated) and high-velocity (advection-dominated) regions. Fluid saturation is shown to directly affect diffusive mass flux among high- and low-velocity zones. Another indirect effect of correlated heterogeneity on solute transport is through its control of the drainage patterns via repeated alteration in the connectivity of flowing pathways. Our findings improve quantitative understanding of solute mixing and dispersion under two-phase conditions, highly relevant to some of our most urgent environmental problems.