The Southern Ocean mixed layer and its boundary fluxes: fine-scale observational progress and future research priorities.

Interactions between the upper ocean and air-ice-ocean fluxes in the Southern Ocean play a critical role in global climate by impacting the overturning circulation and oceanic heat and carbon uptake. Remote and challenging conditions have led to sparse observational coverage, while ongoing field programmes often fail to collect sufficient information in the right place or at the time-space scales required to constrain the variability occurring in the coupled ocean-atmosphere system. Only within the last 10 years have we been able to directly observe and assess the role of the fine-scale ocean and rapidly evolving atmospheric marine boundary layer on the upper limb of the Southern Ocean's overturning circulation. This review summarizes advances in mechanistic understanding, arising in part from observational programmes using autonomous platforms, of the fine-scale processes (1-100 km, hours-seasons) influencing the Southern Ocean mixed layer and its variability. We also review progress in observing the ocean interior connections and the coupled interactions between the ocean, atmosphere and cryosphere that moderate air-sea fluxes of heat and carbon. Most examples provided are for the ice-free Southern Ocean, while major challenges remain for observing the ice-covered ocean. We attempt to elucidate contemporary research gaps and ongoing/future efforts needed to address them. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'.

Parsing the Kinetic Energy Budget of the Ocean Surface Mixed Layer.

The total rate of work done on the ocean by the wind is of considerable interest for understanding global energy balances, as the energy from the wind drives ocean currents, grows surface waves, and forces vertical mixing. A large but unknown fraction of this atmospheric energy is dissipated by turbulence in the upper ocean. The focus of this work is twofold. First, we describe a framework for evaluating the vertically integrated turbulent kinetic energy (TKE) equation using measurable quantities from a surface mooring, showing the connection to the atmospheric, mean oceanic, and wave energy. Second, we use this framework to evaluate turbulent energetics in the mixed layer using 10 months of mooring data. This evaluation is made possible by recent advances in estimating TKE dissipation rates from long-enduring moorings. We find that surface fluxes are balanced by TKE dissipation rates in the mixed layer to within a factor of two.

Estimation of the Mixed Layer Depth in the Indian Ocean from Surface Parameters: A Clustering-Neural Network Method.

The effective estimation of mixed-layer depth (MLD) plays a significant role in the study of ocean dynamics and global climate change. However, the methods of estimating MLD still have limitations due to the sparse resolution of the observed data. In this study, a hybrid estimation method that combines the K-means clustering algorithm and an artificial neural network (ANN) model was developed using sea-surface parameter data in the Indian Ocean as a case study. The oceanic datasets from January 2012 to December 2019 were obtained via satellite observations, Argo in situ data, and reanalysis data. These datasets were unified to the same spatial and temporal resolution (1° × 1°, monthly). Based on the processed datasets, the K-means classifier was applied to divide the Indian Ocean into four regions with different characteristics. For ANN training and testing in each region, the gridded data of 84 months were used for training, and 12-month data were used for testing. The ANN results show that the optimized NN architecture comprises five input variables, one output variable, and four hidden layers, each of which has 40 neurons. Compared with the multiple linear regression model (MLR) with a root-mean-square error (RMSE) of 5.2248 m and the HYbrid-Coordinate Ocean Model (HYCOM) with an RMSE of 4.8422 m, the RMSE of the model proposed in this study was reduced by 27% and 22%, respectively. Three typical regions with high variability in their MLDs were selected to further evaluate the performance of the ANN model. Our results showed that the model could reveal the seasonal variation trend in each of the selected regions, but the estimation accuracy showed room for improvement. Furthermore, a correlation analysis between the MLD and input variables showed that the surface temperature and salinity were the main influencing factors of the model. The results of this study suggest that the pre-clustering ANN method proposed could be used to estimate and analyze the MLD in the Indian Ocean. Moreover, this method can be further expanded to estimate other internal parameters for typical ocean regions and to provide effective technical support for ocean researchers when studying the variability of these parameters.

Will coral reef sponges be winners in the Anthropocene?

Recent observations have shown that increases in climate change-related coral mortality cause changes in shallow coral reef community structure through phase shifts to alternative taxa. As a result, sponges have emerged as a potential candidate taxon to become a "winner," and therefore a numerically and functionally dominant member of many coral reef communities. But, in order for this to occur, there must be sufficient trophic resources to support larger populations of these active filter-feeding organisms. Globally, climate change is causing an increase in sea surface temperatures (SSTs) and a decrease in salinity, which can lead to an intensification in the stratification of shallow nearshore waters (0-200 m), that affects both the mixed layer depth (MLD) and the strength and duration of internal waves. Specifically, climate change-driven increases in SSTs for tropical waters are predicted to cause increased stratification, and more stabilized surface waters. This causes a shallowing of the MLD which prevents nutrients from reaching the euphotic zone, and is predicted to decrease net primary production (NPP) up to 20% by the end of the century. Lower NPP would subsequently affect multiple trophic levels, including shallow benthic filter-feeding communities, as the coupling between water column productivity and the benthos weakens. We argue here that sponge populations may actually be constrained, rather than promoted, by climate change due to decreases in their primary trophic resources, caused by bottom-up forcing, secondary to physical changes in the water column (i.e., stratification and changes in the MLD resulting in lower nutrients and NPP). As a result, we predict sponge-dominated tropical reefs will be rare, or short-lived, if they occur at all into the future in the Anthropocene.

High-Frequency Variability of Small-Particle Carbon Export Flux in the Northeast Atlantic.

The biological carbon pump exports carbon fixed by photosynthesis out of the surface ocean and transfers it to the deep, mostly in the form of sinking particles. Despite the importance of the pump in regulating the air-sea CO2 balance, the magnitude of global carbon export remains unclear, as do its controlling mechanisms. A possible sinking flux of carbon to the mesopelagic zone may be via the mixed-layer pump: a seasonal net detrainment of particulate organic carbon (POC)-rich surface waters, caused by sequential deepening and shoaling of the mixed layer. In this study, we present a full year of daily small-particle POC concentrations derived from glider optical backscatter data, to study export variability at the Porcupine Abyssal Plain (PAP) sustained observatory in the Northeast Atlantic. We observe a strong seasonality in small-particle transfer efficiency, with a maximum in winter and early spring. By calculating daily POC export driven by mixed-layer variations, we find that the mixed-layer pump supplies an annual flux of at least 3.0 ± 0.9 g POC·m-2·year-1 to the mesopelagic zone, contributing between 5% and 25% of the total annual export flux and likely contributing to closing a gap in the mesopelagic carbon budget found by other studies. These are, to our best knowledge, the first high-frequency observations of export variability over the course of a full year. Our results support the deployment of bio-optical sensors on gliders to improve our understanding of the ocean carbon cycle on temporal scales from daily to annual.

Changes in the upper ocean mixed layer and phytoplankton productivity along the West Antarctic Peninsula.

The West Antarctic Peninsula (WAP) has experienced significant change over the last 50 years. Using a 24 year spatial time series collected by the Palmer Long Term Ecological Research programme, we assessed long-term patterns in the sea ice, upper mixed layer depth (MLD) and phytoplankton productivity. The number of sea ice days steadily declined from the 1980s until a recent reversal that began in 2008. Results show regional differences between the northern and southern regions sampled during regional ship surveys conducted each austral summer. In the southern WAP, upper ocean MLD has shallowed by a factor of 2. Associated with the shallower mixed layer is enhanced phytoplankton carbon fixation. In the north, significant interannual variability resulted in the mixed layer showing no trended change over time and there was no significant increase in the phytoplankton productivity. Associated with the recent increases in sea ice there has been an increase in the photosynthetic efficiency (chlorophyll a-normalized carbon fixation) in the northern and southern regions of the WAP. We hypothesize the increase in sea ice results in increased micronutrient delivery to the continental shelf which in turn leads to enhanced photosynthetic performance.This article is part of the theme issue 'The marine system of the West Antarctic Peninsula: status and strategy for progress in a region of rapid change'.

A mixed layer height parameterization in a 3-D chemical transport model: Implications for gas and aerosol simulations.

Vertical mixing within the planetary boundary layer (PBL) is crucial for determining surface-level pollutant concentrations. However, standard PBL schemes in chemical transport models (CTMs) often fail to adequately define the upper bounds of vertical mixing, particularly at night. This limitation frequently results in overestimated nocturnal concentrations of pollutants near the surface. To address this issue, we propose a parameterization of mixed layer height (MLH) derived from the Yonsei University (YSU) PBL scheme and thoroughly evaluate it by comparing simulations with various observations. We utilized the Weather Research and Forecasting model coupled with GEOS-Chem (WRF-GC) to simulate gas and aerosol distributions over South Korea during the Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) campaign in 2021. The WRF-GC simulations incorporating the MLH parameterization improved the excessive titration of O3 and the overproduction of HNO3 and NO3- in the model. Consequently, the model performances in gaseous and aerosol simulations showed a better agreement with observations, with changes in normalized mean biases (NMBs) of NOX (from 50 % to -27 %), O3 (from -49 % to -28 %), NO3- (from 126 % to 91 %), NH4+ (from 113 % to 85 %), BC (from 322 % to 135 %), and PM2.5 (from 58 % to 28 %).

Global distribution and environmental correlates of marine bioturbation.

The activities of marine sediment-dwelling invertebrates play a fundamental role in mediating major biogeochemical cycles and have profoundly shaped the evolution of marine systems. Yet there remains a paucity of global marine data describing bioturbation intensities and mixed layer depths and interrogating how these vary with multiple environmental and ecological factors at a system scale. We applied an ensemble of tree-based machine learning techniques to resolve a global map and determine the environmental and ecological correlates most closely associated with bioturbation. We find that bioturbation intensity and the depth of the sediment mixed layer each reflect different associations with a consortium of environmental and ecological parameters, and that bioturbation intensities are much more readily predicted than sediment mixed layer depths from these correlates. Furthermore, we find that the bioturbation intensity, the depth of the sediment mixed layer, and their environmental and ecological correlates differ between shallow marine and open-ocean settings. Our findings provide new insights into the importance of potential drivers of ancient sediment mixing recorded by geologic archives. These results also highlight that climate change may, in the near future, drive shifts in bioturbation and reciprocal fundamental changes in benthic functioning.

Ab initio crystal structures and relative phase stabilities for the aleksite series, PbnBi4Te4Sn+2.

Density functional theory methods are applied to crystal structures and stabilities of phases from the aleksite homologous series, PbnBi4Te4Sn+2 (n = homologue number). The seven phases investigated correspond to n = 0 (tetradymite), 2 (aleksite-21R and -42R), 4 (saddlebackite-9H and -18H), 6 (unnamed Pb6Bi4Te4S8), 8 (unnamed Pb8Bi4Te4S10), 10 (hitachiite) and 12 (unnamed Pb12Bi4Te4S14). These seven phases correspond to nine single- or double-module structures, each comprising an odd number of atom layers, 5, 7, (5.9), 9, (7.11), 11, 13, 15 and 17, expressed by the formula: S(MpXp+1)·L(Mp+1Xp+2), where M = Pb, Bi and X = Te, S, p ≥ 2, and S and L = number of short and long modules, respectively. Relaxed structures show a and c values within 1.5% of experimental data; a and the interlayer distance dsub decrease with increasing PbS content. Variable Pb-S bond lengths contrast with constant Pb-S bond lengths in galena. All phases are n-fold superstructures of a rhombohedral subcell with c/3 = dsub*. Electron diffraction patterns show two brightest reflections at the centre of dsub*, described by the modulation vector qF = (i/N) ·â€…dsub*, i = S + L. A second modulation vector, q = γ ·â€…csub*, shows a decrease in γ, from 1.8 to 1.588, across the n = 0 to n = 12 interval. The linear relationship between γ and dsub allows the prediction of any theoretical phases beyond the studied compositional range. The upper PbS-rich limit of the series is postulated as n = 398 (Pb398Bi4Te4S400), a phase with dsub (1.726 Å) identical to that of trigonal PbS within experimental error. The aleksite series is a prime example of mixed layer compounds built with accretional homology principles.

Role of Sea Surface Physical Processes in Mixed-Layer Temperature Changes During Summer Marine Heat Waves in the Chile-Peru Current System.

We identified anomalously warm sea surface temperature (SST) events during 1980-2019 near the major upwelling center at Punta Lavapié in the central Chile-Peru Current System, using the European Centre for Medium-Range Weather Forecasts reanalysis and focusing on time scales of 10 days to 6 months. Extreme warm SST anomalies on these time scales mostly occurred in the austral summer, December through February, and had spatial scales of 1000s of km. By compositing over the 37 most extreme warm events, we estimated terms in a heat budget for the ocean surface mixed layer at the times of strongest warming preceding the events. The net surface heat flux anomaly is too small to explain the anomalous warming, even when allowing for uncertainty in mixed-layer depth. The composite mean anomaly of wind stress, from satellite ocean vector wind swath data, during the 37 anomalous warming periods has a spatial pattern similar to the resulting warm SST anomalies, analogous to previous studies in the California Current System. The weakened surface wind stress suggests reduced entrainment of cold water from below the mixed layer. Within 100-200 km of the coast, the typical upwelling-favorable wind stress curl decreases, suggesting reduced upwelling of cold water. In a 1000-km area of anomalous warming offshore, the typical downwelling-favorable wind stress curl also decreases, implying reduced downward Ekman pumping, which would allow mixed-layer shoaling and amplify the effect of the positive climatological summertime net surface heat flux.

The mixed layer modified radionuclide atmospheric diffusion based on Gaussian model.

Background: Atmospheric diffusion is often accompanied by complex meteorological conditions of inversion temperature. Methods: In response to the emergency needs for rapid consequence assessment of nuclear accidents under these complex meteorological conditions, a Gaussian diffusion-based model of radionuclide is developed with mixed layer modification. The inhibition effect of the inversion temperature on the diffusion of radionuclides is modified in the vertical direction. The intensity of the radionuclide source is modified by the decay constant. Results: The results indicate that the enhancement effect of the mixed layer on the concentration of radionuclides is reflected. The shorter the half-life of the radionuclide, the greater the effect of reducing the diffusion concentration. The Kincaid dataset validation in the Model Validation Kit (MVK) shows that, compared to the non-modified model, predictions of the modified model have an enhancement effect beyond 5 km, modulating the prediction values to be closer to the observation values. Conclusions: This development is consistent with the modification effects of the mixed layer. The statistical indicators show that the criteria of the modified model meet the criteria of the recommended model.

Two Types of Wear Mechanisms Governing Transition between Mild and Severe Wear in Ti-6Al-4V Alloy during Dry Sliding at Temperatures of 20-250 °C.

Dry wear characteristics and wear mechanisms governing mild-severe wear transition of Ti-6Al-4V alloy were studied during sliding against medium carbon chromium steel (50Cr) in an experimental temperature range of 20-250 °C. At each experimental temperature, wear rate was plotted against applied load, and its variation was broken into two stages according to the difference of slope. Morphologies and contents of worn surfaces were examined by scanning electron microscope and energy dispersive X-ray spectrometer, from which the two stages were identified to correspond to mild and severe wear, respectively. Two types of wear mechanisms that dominated mild-severe wear transition were found, i.e., breakdown of mechanically mixed layer at temperatures of 20 and 50 °C, and severe plastic deformation at temperatures of 100-250 °C. Microstructures and hardness were examined in the subsurfaces, from which severe plastic deformation-dominated mild-severe wear transition was identified to be caused by the softening arising from friction heating-induced dynamic recrystallization. A linear relation between mild-severe wear transition load and experimental temperature was discovered. The intercept of experimental temperature axis 450 °C was obtained by linearly fitting, and it was considered as a critical dynamic recrystallzation temperature for mild-severe wear transition within the temperature range of 100-250 °C.

The coastal front modulates the timing and magnitude of spring phytoplankton bloom in the Yellow Sea.

Major seasonal quasi-stationary fronts on shelves play an important role in regulating the spatiotemporal variations in the phytoplankton community. However, knowledge of their effects on the timing and magnitude of spring phytoplankton bloom (SPB) remains limited. Here, based on decadal satellite data (2003-2020), we examine the climatological relationship between the Shandong coastal front (SCF) and SPB in the Yellow Sea. The results show that the onset of SPB occurs either in March (∼56% of the seasons examined) or in April (44%). The peak of SPB most often occurs in April (∼56% of the seasons examined) or is advanced to March (16%) or delayed to May (28%), and that the peak ranges from 1.04 to 2.54 mg Chl-a m-3. The onset of SPB matches with lower turbulence, particularly when the rate of generation of turbulent kinetic energy (TKERT) reaches zero. A higher magnitude of bloom is associated with a greater change in front and a lower TKERT. The in situ observations along the SCF transects in the Yellow Sea indicate that weakened SCF in spring associated with a shallower mixing layer enhances the transport of nutrients from the coastal to the shelf waters. Weakened frontal structure and atmospheric forcing in spring can further increase the water stability and decrease turbulence in the upper waters. The variation in hydrodynamic conditions allows shelf phytoplankton to stay longer in the upper waters with sufficient light and nutrients and consequently generate a Chl-a peak. The results suggest that the seasonal changes in front intensity and structure and turbulence are important prerequisites for initiating SPB on the shelf, and that further determines the magnitude of SPB.

Marine Heatwaves.

Ocean temperature variability is a fundamental component of the Earth's climate system, and extremes in this variability affect the health of marine ecosystems around the world. The study of marine heatwaves has emerged as a rapidly growing field of research, given notable extreme warm-water events that have occurred against a background trend of global ocean warming. This review summarizes the latest physical and statistical understanding of marine heatwaves based on how they are identified, defined, characterized, and monitored through remotely sensed and in situ data sets. We describe the physical mechanisms that cause marine heatwaves, along with their global distribution, variability, and trends. Finally, we discuss current issues in this developing research area, including considerations related to thechoice of climatological baseline periods in defining extremes and how to communicate findings in the context of societal needs.

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth From Dense Satellite and Sparse In Situ Observations.

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal ( < 90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Impacts of Saharan Mineral Dust on Air-Sea Interaction over North Atlantic Ocean Using a Fully Coupled Regional Model.

This study examines the modifications of air-sea coupling processes by dust-radiation-cloud interactions over the North Atlantic Ocean using a high-resolution coupled atmosphere-wave-ocean-dust (AWOD) regional model. The dust-induced mechanisms that are responsible for changes of sea surface temperature (SST) and latent and sensible heat fluxes (LHF/SHF) are also examined. Two 3-month numerical experiments are conducted, and they differ only in the activation and deactivation of dust-radiation-cloud interactions. Model results show that the dust significantly reduces surface downward radiation fluxes (SDRF) over the ocean with the maximum change of 20-30 W m-2. Over the dust plume region, the dust effect creates a low-pressure anomaly and a cyclonic circulation anomaly, which drives a positive wind stress curl anomaly, thereby reducing sea surface height and mixed layer depth. However, the SST change by dust, ranging from -0.5 to 0.5 K, has a great spatial variation which differs from the dust plume shape. Dust cools SST around the West African coast, except under the maximum dust plume ridge, and extends westward asymmetrically along the northern and southern edges of the dust plume. Dust unexpectedly warms SST over a large area of the western tropical North Atlantic and north of the dust plume. These SST changes are controlled by different mechanisms. Unlike the SST change pattern, the LHF and SHF changes are mostly reduced underneath the dust plume region, though they are different in detail due to different dominant factors, and increased south of the dust plume over the tropic.

An exclusive in-situ dataset on physicochemical parameters in the gappy northern Bay of Bengal.

In-situ measurement of physical characteristics of seawater (temperature, salinity, and density) collected with a single fire module CTD (Conductivity, Temperature, Depth) in the northern Bay of Bengal (NBoB), as a part of the Indian Ocean, are given in this article. Due to the scanty of data in the NBoB, such in-situ measurements will certainly play a crucial role in understanding regional oceanic processes. The presented data were collected onboard during two cruises covering 12 stations with high resolution (0.2 m depth) up to 50-meter contour depth from 20.5778 N, 92.3578 E to 21.287 N, 89.696 E. We present raw CTD data as ASCII (.dat) and Comma Separated Value (.csv), and processed CTD data as netCDF (.nc) format in this article. Additionally, the calculated Mixed Layer Depth that was derived from the netCDF (.nc) file was included in the tabular format. This processed in-situ data would be most useful as a baseline for further studies in coastal and offshore physicochemical properties in the NBoB.

The structure and crystal chemistry of vernadite in ferromanganese crusts.

The structure and crystal chemistry of vernadite in ferromanganese crusts from the Magellan Seamount in the north-west Pacific Ocean have been investigated using synchrotron X-ray diffraction (XRD), X-ray pair distribution function (PDF) and high-resolution transmission electron microscopy (TEM). XRD patterns of vernadite mainly show two strong diffraction peaks at 2.42-2.43 Šand 1.41 Šwithout or with a broad (001) diffraction peak, indicating thin layer nanophases along the c-direction. TEM images show flat and curved sheet-like nanocrystals with (001) layer thickness of ∼7.2 Šand ∼9.6 Å, and their interstratified structure. PDF patterns of the vernadite are similar to those from synthetic δ-MnO2 and defective birnessite, suggesting a phyllomanganate framework. Combined XRD/PDF patterns suggest that vernadite in the outer part is associated with a higher density interlayer species at triple-edge sharing sites. The proportion of the 10 Šphase increases from the outer (young) part to the inner (old) part of the Mn crusts due to aging and sorption of Mn, Co and Ni from ambient seawater. This study suggests that this combined method of synchrotron radiation XRD/PDF and high-resolution TEM is a powerful tool to determine atomic structures of poorly crystallized nano-minerals. The mixture model of vernadite structure will help to understand the partitioning and distribution of trace elements in the ferromanganese crusts.

Implementation of a 2D Wavelet Method to Probe Mixed Layer Height Using Lidar Observations.

A new method was developed to estimate mixed layer (ML) height with light detection and ranging (lidar) observations using a 2Dimensional (2D) wavelet method, which can consider the diurnal variation characteristics of ML height. Ideal signals and real lidar observations in Shanghai, China were used to evaluate the new method. The results showed that the new method is insensitive to the type of wavelet filters. The estimated ML heights obtained by the 2D wavelet method agreed well with both of the previous methods developed for the ML height probing using lidar, including the gradient method, the 1D-wavelet method, the standard deviation method, and the conventional radiosonde method. The primary differences among the results obtained via the different lidar methods occurred in the early morning or later afternoon; when the ML is well mixed, very small differences were observed among the different lidar methods. The new method showed better determination skills than other methods when compared to the radiosonde observation results. It also performed well when there were missing profiles or observation errors and it made the new method suitable for operations where data quality control may be missed.

Structure determination and crystal chemistry of large repeat mixed-layer hexaferrites.

Hexaferrites are an important class of magnetic oxides with applications in data storage and electronics. Their crystal structures are highly modular, consisting of Fe- or Ba-rich close-packed blocks that can be stacked in different sequences to form a multitude of unique structures, producing large anisotropic unit cells with lattice parameters typically >100 Šalong the stacking axis. This has limited atomic-resolution structure solutions to relatively simple examples such as Ba2Zn2Fe12O22, whilst longer stacking sequences have been modelled only in terms of block sequences, with no refinement of individual atomic coordinates or occupancies. This paper describes the growth of a series of complex hexaferrite crystals, their atomic-level structure solution by high-resolution synchrotron X-ray diffraction, electron diffraction and imaging methods, and their physical characterization by magnetometry. The structures include a new hexaferrite stacking sequence, with the longest lattice parameter of any hexaferrite with a fully determined structure.