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Within the family of two-dimensional dielectrics, rhombohedral boron nitride (rBN) is considerably promising owing to having not only the superior properties of hexagonal boron nitride 1 – 4 —including low permittivity and dissipation, strong electrical insulation, good chemical stability, high thermal conductivity and atomic flatness without dangling bonds—but also useful optical nonlinearity and interfacial ferroelectricity originating from the broken in-plane and out-of-plane centrosymmetry 5 – 23 . However, the preparation of large-sized single-crystal rBN layers remains a challenge 24 – 26 , owing to the requisite unprecedented growth controls to coordinate the lattice orientation of each layer and the sliding vector of every interface. Here we report a facile methodology using bevel-edge epitaxy to prepare centimetre-sized single-crystal rBN layers with exact interlayer ABC stacking on a vicinal nickel surface. We realized successful accurate fabrication over a single-crystal nickel substrate with bunched step edges of the terrace facet (100) at the bevel facet (110), which simultaneously guided the consistent boron–nitrogen bond orientation in each BN layer and the rhombohedral stacking of BN layers via nucleation near each bevel facet. The pure rhombohedral phase of the as-grown BN layers was verified, and consequently showed robust, homogeneous and switchable ferroelectricity with a high Curie temperature. Our work provides an effective route for accurate stacking-controlled growth of single-crystal two-dimensional layers and presents a foundation for applicable multifunctional devices based on stacked two-dimensional materials.  Centimetre-sized single-crystal rhombohedral boron nitride layers are achieved through bevel-edge epitaxy, and the resulting material exhibits robust, homogeneous and switchable ferroelectricity with a high Curie temperature.

The assimilated ozone product from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), produced at NASA’s Global Modeling and Assimilation Office (GMAO) spanning the time period from 1980 to the present is described herein, and its quality is assessed. MERRA-2 assimilates partial column ozone retrievals from a series of Solar Backscatter Ultraviolet Radiometer (SBUV) instruments on NASA and NOAA spacecraft between January 1980 and September 2004: starting in October 2004, retrieved ozone profiles from the Microwave Limb Sounder (MLS) and total column ozone from the Ozone Monitoring Instrument on NASA’s EOS Aura satellite are assimilated. The MERRA-2 ozone is compared with independent satellite and ozonesonde data, focusing on the representation of the spatial and temporal variability of stratospheric and upper-tropospheric ozone and on implications of the change in the observing system from SBUV to EOS Aura. The comparisons show agreement within 10% (standard deviation of the difference) between MERRA-2 profiles and independent satellite data in most of the stratosphere. The agreement improves after 2004, when EOS Aura data are assimilated. The standard deviation of the differences between the lower-stratospheric and upper-tropospheric MERRA-2 ozone and ozonesondes is 11.2% and 24.5%, respectively, with correlations of 0.8 and above, indicative of a realistic representation of the near-tropopause ozone variability in MERRA-2. The agreement improves significantly in the EOS Aura period; however, MERRA-2 is biased low in the upper troposphere with respect to the ozonesondes. Caution is recommended when using MERRA-2 ozone for decadal changes and trend studies.

Ferromanganese deposits in the South China Sea (SCS) hold significant strategic metal resources, yet their distribution remains poorly understood. To address this gap, we conducted an integrated study across 6,600 km2 in the central basin of the SCS, combining sampling, seafloor video, and multi‐beam backscatter acoustic surveys. A high‐backscatter zone of 1.21 km2 on the Jiaolong seamount was identified as a ferromanganese nodule‐rich area, contrasting with the abyssal basin. The ferromanganese nodules exhibit high vernadite contents and atypical hydrogenesis characteristics, including high Fe/Mn and Fe/Co ratios, and elevated Pb and rare earth element contents. These features suggest that marginal seas are more effective in supplying short‐life cycle elements. Seamounts in the central basin may enhance circulation efficiency, facilitating sediment removal and dissolved oxygen recharge, thereby promoting ferromanganese deposit formation in certain areas. This study contributes to the further exploration of ferromanganese deposits in the SCS. Plain Language Summary Despite geological sampling revealing significant ferromanganese deposits in the South China Sea (SCS), their spatial distribution remains poorly constrained. In this study, multi‐beam backscatter acoustic surveys were used to find high‐reflectivity zones across 6,600 km2 in the central basin of the SCS, and the ferromanganese nodule‐enriched areas and their boundaries were then successively confirmed by geological sampling and seafloor video. A high‐backscatter zone of 1.21 km2 on the Jiaolong seamount was identified as a nodule‐rich area, contrasting with the abyssal basin. We collected 117.8 kg of ferromanganese nodules, which had high vernadite and low todorokite contents, suggesting an oxidized formation environment. Geochemically, these nodules exhibit atypical hydrogenetic characteristics, with high Fe/Mn and Fe/Co ratios, elevated rare earth elements and yttrium (mean 1,969 ppm), and unique elemental signatures (e.g., low Co and high Pb contents). This finding indicates that marginal seas are better at supplying short‐life cycle elements. Seamounts in the central basin may enhance circulation efficiency, facilitating sediment removal, and dissolved oxygen recharge, thereby promoting ferromanganese deposit formation in certain areas. We have modeled the metallogenesis of the ferromanganese nodules and mapped 72,000 km2 of prospective resources, guiding future exploration in the central basin of the SCS. Key Points A high‐backscatter zone spanning 1.21 km2 was proven to be a ferromanganese nodule‐rich area via sampling and seafloor video Ferromanganese deposits in the central basin of the South China Sea are distributed in topographic highlands, not in abyssal basins Atypical hydrogenetic ferromanganese nodule metallogenesis in marginal seas with low Co contents and high Fe/Co ratios is modeled

Seasonal snow is an essential water resource in many mountain regions. However, the spatio-temporal variability in mountain snow depth or snow water equivalent (SWE) at regional to global scales is not well understood due to the lack of high-resolution satellite observations and robust retrieval algorithms. We investigate the ability of the Sentinel-1 mission to monitor snow depth at sub-kilometer (100 m, 500 m, and 1 km) resolutions over the European Alps for 2017–2019. The Sentinel-1 backscatter observations, especially in cross-polarization, show a high correlation with regional model simulations of snow depth over Austria and Switzerland. The observed changes in radar backscatter with the accumulation or ablation of snow are used in an empirical change detection algorithm to retrieve snow depth. The algorithm includes the detection of dry and wet snow conditions. Compared to in situ measurements at 743 sites in the European Alps, dry snow depth retrievals at 500 m and 1 km resolution have a spatio-temporal correlation of 0.89. The mean absolute error equals 20 %–30 % of the measured values for snow depths between 1.5 and 3 m. The performance slightly degrades for retrievals at the finer 100 m spatial resolution as well as for retrievals of shallower and deeper snow. The results demonstrate the ability of Sentinel-1 to provide snow estimates in mountainous regions where satellite-based estimates of snow mass are currently lacking. The retrievals can improve our knowledge of seasonal snow mass in areas with complex topography and benefit a number of applications, such as water resource management, flood forecasting, and numerical weather prediction. However, future research is recommended to further investigate the physical basis of the sensitivity of Sentinel-1 backscatter observations to snow accumulation.

We report on updated trends using different merged zonal mean total ozone datasets from satellite and ground-based observations for the period from 1979 to 2020. This work is an update of the trends reported in Weber et al. (2018) using the same datasets up to 2016. Merged datasets used in this study include NASA MOD v8.7 and NOAA Cohesive Data (COH) v8.6, both based on data from the series of Solar Backscatter Ultraviolet (SBUV), SBUV-2, and Ozone Mapping and Profiler Suite (OMPS) satellite instruments (1978–present), as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone – Essential Climate Variable (GTO-ECV) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (both 1995–present), mainly comprising satellite data from GOME, SCIAMACHY, OMI, GOME-2A, GOME-2B, and TROPOMI. The fifth dataset consists of the annual mean zonal mean data from ground-based measurements collected at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. The addition of 4 more years consolidated the fact that total ozone is indeed slowly recovering in both hemispheres as a result of phasing out ozone-depleting substances (ODSs) as mandated by the Montreal Protocol. The near-global (60° S–60° N) ODS-related ozone trend of the median of all datasets after 1995 was 0.4 ± 0.2 (2σ) %/decade, which is roughly a third of the decreasing rate of 1.5 ± 0.6 %/decade from 1978 until 1995. The ratio of decline and increase is nearly identical to that of the EESC (equivalent effective stratospheric chlorine or stratospheric halogen) change rates before and after 1995, confirming the success of the Montreal Protocol. The observed total ozone time series are also in very good agreement with the median of 17 chemistry climate models from CCMI-1 (Chemistry-Climate Model Initiative Phase 1) with current ODS and GHG (greenhouse gas) scenarios (REF-C2 scenario). The positive ODS-related trends in the Northern Hemisphere (NH) after 1995 are only obtained with a sufficient number of terms in the MLR accounting properly for dynamical ozone changes (Brewer–Dobson circulation, Arctic Oscillation (AO), and Antarctic Oscillation (AAO)). A standard MLR (limited to solar, Quasi-Biennial Oscillation (QBO), volcanic, and El Niño–Southern Oscillation (ENSO)) leads to zero trends, showing that the small positive ODS-related trends have been balanced by negative trend contributions from atmospheric dynamics, resulting in nearly constant total ozone levels since 2000.

Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and biological tissues. QUS techniques extract fundamental physical properties of tissues based on interactions between ultrasound waves and tissue microstructure. These techniques provide quantitative information on sub-resolution properties that are not visible on grayscale (B-mode) imaging. Quantitative data may be represented either as a global measurement or as parametric maps overlaid on B-mode images. Recently, major ultrasound manufacturers have released speed of sound, attenuation, and backscatter packages for tissue characterization and imaging. Established and emerging clinical applications are currently limited and include liver fibrosis staging, liver steatosis grading, and breast cancer characterization. On the other hand, most biological tissues have been studied using experimental QUS methods, and quantitative datasets are available in the literature. This educational review addresses the general topic of biological soft tissue characterization using QUS, with a focus on disseminating technical concepts for clinicians and specialized QUS materials for medical physicists. Advanced but simplified technical descriptions are also provided in separate subsections identified as such. To understand QUS methods, this article reviews types of ultrasound waves, basic concepts of ultrasound wave propagation, ultrasound image formation, point spread function, constructive and destructive wave interferences, radiofrequency data processing, and a summary of different imaging modes. For each major QUS technique, topics include: concept, illustrations, clinical examples, pitfalls, and future directions.

We report on updated trends using different merged datasets from satellite and ground-based observations for the period from 1979 to 2016. Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. Merged datasets used here include NASA MOD v8.6 and National Oceanic and Atmospheric Administration (NOAA) merge v8.6, both based on data from the series of Solar Backscatter UltraViolet (SBUV) and SBUV-2 satellite instruments (1978–present) as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone (GTO) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (1995-present), mainly comprising satellite data from GOME, the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and GOME-2A. The fifth dataset consists of the monthly mean zonal mean data from ground-based measurements collected at World Ozone and UV Data Center (WOUDC). The addition of four more years of data since the last World Meteorological Organization (WMO) ozone assessment (2013-2016) shows that for most datasets and regions the trends since the stratospheric halogen reached its maximum (approximately 1996 globally and approximately 2000 in polar regions) are mostly not significantly different from zero. However, for some latitudes, in particular the Southern Hemisphere extratropics and Northern Hemisphere subtropics, several datasets show small positive trends of slightly below +1 percent decade(exp. -1) that are barely statistically significant at the 2 Sigma uncertainty level. In the tropics, only two datasets show significant trends of +0.5 to +0.8 percent(exp.-1), while the others show near-zero trends. Positive trends since 2000 have been observed over Antarctica in September, but near-zero trends are found in October as well as in March over the Arctic. Uncertainties due to possible drifts between the datasets, from the merging procedure used to combine satellite datasets and related to the low sampling of ground-based data, are not accounted for in the trend analysis. Consequently, the retrieved trends can be only considered to be at the brink of becoming significant, but there are indications that we are about to emerge into the expected recovery phase. However, the recent trends are still considerably masked by the observed large year-to-year dynamical variability in total ozone.

For the first time, a closure study of the relationship between the ice-nucleating particle concentration (INP; INPC) and ice crystal number concentration (ICNC) in altocumulus and cirrus layers, solely based on ground-based active remote sensing, is presented. Such aerosol–cloud closure experiments are required (a) to better understand aerosol–cloud interaction in the case of mixed-phase clouds, (b) to explore to what extent heterogeneous ice nucleation can contribute to cirrus formation, which is usually controlled by homogeneous freezing, and (c) to check the usefulness of available INPC parameterization schemes, applied to lidar profiles of aerosol optical and microphysical properties up to the tropopause level. The INPC–ICNC closure studies were conducted in Cyprus (Limassol and Nicosia) during a 6-week field campaign in March–April 2015 and during the 17-month CyCARE (Cyprus Clouds Aerosol and Rain Experiment) campaign. The focus was on altocumulus and cirrus layers which developed in pronounced Saharan dust layers at heights from 5 to 11 km. As a highlight, a long-lasting cirrus event was studied which was linked to the development of a very strong dust-infused baroclinic storm (DIBS) over Algeria. The DIBS was associated with strong convective cloud development and lifted large amounts of Saharan dust into the upper troposphere, where the dust influenced the evolution of an unusually large anvil cirrus shield and the subsequent transformation into an cirrus uncinus cloud system extending from the eastern Mediterranean to central Asia, and thus over more than 3500 km. Cloud top temperatures of the three discussed closure study cases ranged from −20 to −57 ∘C. The INPC was estimated from polarization/Raman lidar observations in combination with published INPC parameterization schemes, whereas the ICNC was retrieved from combined Doppler lidar, aerosol lidar, and cloud radar observations of the terminal velocity of falling ice crystals, radar reflectivity, and lidar backscatter in combination with the modeling of backscattering at the 532 and 8.5 mm wavelengths. A good-to-acceptable agreement between INPC (observed before and after the occurrence of the cloud layer under investigation) and ICNC values was found in the discussed three proof-of-concept closure experiments. In these case studies, INPC and ICNC values matched within an order of magnitude (i.e., within the uncertainty ranges of the INPC and ICNC estimates), and they ranged from 0.1 to 10 L−1 in the altocumulus layers and 1 to 50 L−1 in the cirrus layers observed between 8 and 11 km height. The successful closure experiments corroborate the important role of heterogeneous ice nucleation in atmospheric ice formation processes when mineral dust is present. The observed long-lasting cirrus event could be fully explained by the presence of dust, i.e., without the need for homogeneous ice nucleation processes.

Using global Sentinel-1 radar backscatter data, we systematically map the locations of glaciers with surge-type activity during 2017–22. Patterns of pronounced increases or decreases in the strongest backscatter between two winter seasons often indicate large changes in glacier crevassing, which we treat here as a sign of surge-type activity. Validations against velocity time series, terminus advances and crevassing found in optical satellite images confirm the robustness of this approach. We find 115 surge-type events globally between 2017 and 2022, around 100 of which on glaciers already know as surge-type. Our data reveal a pronounced spatial clustering in three regions, (i) Karakoram, Pamirs and Western Kunlun Shan (~50 surges), (ii) Svalbard (~25) and (iii) Yukon/Alaska (~9), with only a few other scattered surges elsewhere. This spatial clustering is significantly more pronounced than the overall global clustering of known surge-type glaciers. The 2017–22 clustering may point to climatic forcing of surge initiation.

Electron backscatter diffraction (EBSD) is one of the primary tools for crystal structure determination. However, this method requires human input to select potential phases for Hough-based or dictionary pattern matching and is not well suited for phase identification. Automated phase identification is the first step in making EBSD into a high-throughput technique. We used a machine learning–based approach and developed a general methodology for rapid and autonomous identification of the crystal symmetry from EBSD patterns. We evaluated our algorithm with diffraction patterns from materials outside the training set. The neural network assigned importance to the same symmetry features that a crystallographer would use for structure identification.