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•Investigated resolution-SNR trade-off in diffusion MRI of the brain at 7T using EPI, partial Fourier EPI, and spiral.•NMR field probes were used to minimize artifacts due to eddy currents and field non-uniformities.•For matched nominal resolutions, EPI has the highest effective resolution, specificity, and sharpening due to T2* decay.•For matched effective resolutions, spirals offer highest SNR efficiency.•Spiral trajectories are optimal for high-resolution diffusion MRI at 7T. Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various multi-shot acquisition strategies have been developed to achieve sub-millimeter resolution, but they require long scan times which can be restricting for patient scans. Alternatively, the SNR of single-shot acquisitions can be increased by using a spiral readout trajectory to minimize the sequence echo time. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* of brain tissue and the greater field non-uniformities at UHFs will degrade image quality, causing image blurring, distortions, and signal loss. In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral trajectories, over a range of dMRI resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6–1.8 mm. In-vivo partial brain scans at a nominal resolution of 1.5 mm isotropic were acquired using the three readout trajectories to validate the simulation results. Field probes were used to measure dynamic magnetic fields offline up to the 3rd order of spherical harmonics. Image reconstruction was performed using static ΔB0 field maps and the measured trajectories to correct image distortions and artifacts, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps calculated from a multi-shell dataset with b-values of 300, 1000, and 2000 s/mm2 in 5, 16, and 48 directions, respectively. In-vivo scans at nominal resolutions of 1, 1.2, and 1.5 mm were acquired and the SNR of the different trajectories calculated using the multiple replica method to investigate the SNR. Finally, in-vivo whole brain scans with an effective resolution of 1.5 mm isotropic were acquired to explore the SNR and efficiency of different trajectories at a matching effective resolution. FA and intra-cellular volume fraction (ICVF) maps calculated using neurite orientation dispersion and density imaging (NODDI) were used for the comparison. The simulations and in vivo imaging results showed that for matching nominal resolutions, EPI trajectories had the highest specificity and effective resolution with maximum image sharpening effect. However, spirals have a significantly higher SNR, in particular at higher resolutions and even when the effective image resolutions are matched. Overall, this work shows that the higher SNR of single-shot spiral trajectories at 7T allows us to achieve higher effective resolutions compared to EPI and PF-EPI to map the microstructure and connectivity of small brain structures.

ERA5 represents the state of the art for atmospheric reanalyses and is widely used in meteorological and climatological research. In this work, this dataset is evaluated using the wind kinetic energy spectrum. Seasonal climatologies are generated for 30° latitudinal bands in the Northern Hemisphere (periodic domain) and over the North Atlantic area (limited-area domain). The spectra are also assessed to determine the effective resolution of the reanalysis. The results present notable differences between the latitudinal domains, indicating that ERA5 is properly capturing the synoptic conditions. The seasonal variability is adequate too, being winter the most energetic, and summer the least energetic season. The limited area domain results introduce a larger energy density and range. Despite the good results for the synoptic scales, the reanalysis’ spectra are not able to properly reproduce the dissipation rates at mesoscale. This is a source of uncertainties which needs to be taken into account when using the dataset. Finally, a cyclone tropical transition is presented as a case study. The spectrum generated shows a clear difference in energy density at every wavelength, as expected for a highly-energetic status of the atmosphere.

Previous studies have shown that atmospheric models with a spectral element grid can benefit from putting physics calculations on a relatively coarse finite volume grid. Here we demonstrate an alternative high‐order, element‐based mapping approach used to implement a quasi‐equal‐area, finite volume physics grid in E3SM. Unlike similar methods, the new method in E3SM requires topology data purely local to each spectral element, which trivially allows for regional mesh refinement. Simulations with physics grids defined by 2 × 2, 3 × 3, and 4 × 4 divisions of each element are shown to verify that the alternative physics grid does not qualitatively alter the model solution. The model performance is substantially affected by the reduction of physics columns when using the 2 × 2 grid, which can increase the throughput of physics calculations by roughly 60%–120% depending on whether the computational resources are configured to maximize throughput or efficiency. A pair of regionally refined cases are also shown to highlight the refinement capability. Plain Language Summary Most atmospheric models use the same grid for dynamics (e.g., advection) and physics (e.g., clouds). For spectral element models the grid uses irregularly spaced points and the treatment of element edges can lead to grid imprinting bias. Previous studies have shown that using a regularly spaced physics grid in a spectral element model can alleviate the grid imprinting biases. This alternative physics grid can also reduce the computational cost of the model if the physics grid is coarser than the dynamics grid. This study presents a new approach for using a regularly spaced physics grid in a global spectral element model that additionally allows mesh refinement for regionally focused simulations. The use of a relatively coarse physics grid is shown to make the model faster without qualitatively degrading the simulated climate. Key Points A method is presented for defining a finite volume physics grid in a spectral element model that allows for regional refinement The new method is shown to qualitatively preserve the model solution and effective resolution A relatively coarse physics grid increases the speed of physics by roughly 60%–120% depending on how the computational resources are configured

Higher spatial resolution imaging data are considered desirable in many Earth observation applications. In this work, we propose and demonstrate the TARSGAN (learning Terrestrial image deblurring using Adaptive weighted dense Residual Super-resolution Generative Adversarial Network) system for Super-resolution Restoration (SRR) of 10 m/pixel Sentinel-2 “true” colour images as well as all the other multispectral bands. In parallel, the ELF (automated image Edge detection and measurements of edge spread function, Line spread function, and Full width at half maximum) system is proposed to achieve automated and precise assessments of the effective resolutions of the input and SRR images. Subsequent ELF measurements of the TARSGAN SRR results suggest an averaged effective resolution enhancement factor of about 2.91 times (equivalent to ~3.44 m/pixel for the 10 m/pixel bands) given a nominal SRR upscaling factor of 4 times. Several examples are provided for different types of scenes from urban landscapes to agricultural scenes and sea-ice floes.

A satellite altimeter measures sea surface height (SSH) along the nadir track. Multiple satellite altimeters have been in orbit, and the measurements been merged for mapping mesoscale eddies of ~100 km in size in the oceans. The capability of the mapped SSH for resolving mesoscale eddies depends on mapping algorithms. A two-dimensional variational (2DVAR) algorithm was implemented to generate mapped SSH at a grid size of 1/12° in the South China Sea. A range of comparisons were performed between the mapped SSH and the commonly used AVISO (Archiving, Validation, and Interpretation of Satellite Oceanographic satellite data) mapped SSH data product at a grid size of 1/8° and 1/4°. The effective resolution, which represents the spatial scale that the data can resolve, was examined. The effective resolution of the mapped SSH using the 2DVAR algorithm is approximately 100 km, while it is 250 km with the 1/8° and 1/4° AVISO data products. The difference in the effective resolution results from the difference in the background state and thus the background error. The result suggests that the effective resolution of the mapped data could be increased by choosing a background state so that the associated errors could have a smaller decorrelation length scale.

With the increasing number of satellite altimeters in orbit, the effective resolution of merged multiple satellite altimetry data can be improved. We implement a two-dimensional variational (2-DVar) method to merge multiple satellite altimetry data and produce a daily gridded absolute dynamic topography (ADT) dataset with a grid size of 0.08 degrees. We conduct an observing system simulation experiment (OSSE), and the results show that the merged ADT dataset has an effective resolution of about 210 km. Compared with an independent sea surface temperature (SST) data, fine-scale structures can also be observed in the geostrophic flow of the new dataset. A relationship between effective resolution and the radius of a detected eddy is established and used for eddy analysis in the East China Sea (ECS) region. We observe that eddies in the open ocean are more numerous, have larger radii and live longer than those in other areas.

It is generally accepted that increased horizontal resolution improves the representation of atmospheric circulation in global weather and climate models. Understanding which processes contribute toward this improvement can help to focus future model development efforts. In this study, a set of 10‐day global weather forecasts, performed with different atmospheric and orographic resolutions ranging from 180 to 9 km, are used to examine the impacts of resolving increasingly smaller orographic scales on the forecast skill of the Northern Hemisphere winter circulation. These experiments aim to answer two main questions: What is the relative contribution from increases in atmospheric versus orographic resolution to the overall improvement in the Northern Hemisphere winter medium‐range forecast skill obtained when increasing the horizontal resolution? and How do different orographic scales affect different scales of the atmospheric flow? For experiments in which the subgrid‐scale orography parametrizations are turned off, increases in orographic resolution are responsible for almost all of the increase in skill within the troposphere. In the stratosphere, higher atmospheric resolution also contributes to skill improvements, likely due to a better representation of gravity wave propagation and breaking. All scales of orography considered here are found to be important for the obtained changes in the circulation and appear to rapidly affect all considered scales of the flow. In experiments in which the subgrid‐scale orography parametrizations are turned on, the benefits of increasing the horizontal resolution decrease, but do not entirely disappear, suggesting that these parametrizations are not perfect substitutes for the unresolved orography. Plain Language Summary The skill of global weather forecasts has dramatically improved over the past decades. This is in part due to the fact that the resolution of global numerical weather prediction models has increased over time, from hundreds of kilometers to approximately 10 km. Here we demonstrated that during winter in the Northern Hemisphere, weather forecasts improve when the horizontal resolution is increased across this resolution range mostly because the impacts of orography on the atmospheric circulation are better resolved. In the troposphere, the increases in forecast skill obtained when increasing the model resolution are largely due to increases in orographic resolution, and little forecast skill can be gained by increasing the atmospheric resolution alone. We also showed that even approximately 10‐km scales of orography can affect the largest scales of the atmospheric flow. Finally, we demonstrated that the parametrizations used in models to mimic effects of orographic features with scales smaller than the model grid box do not perfectly capture these unresolved effects and need to be improved. Key Points Orography is the main driver of the Northern Hemisphere winter large‐scale circulation All orographic scales commensurately affect all scales of atmospheric flow Orographic drag parametrizations are not a perfect substitute of unresolved orographic effects

Terrestrial Laser Scanning (TLS) greatly facilitates the acquisition of detailed and accurate 3D measurements of remote rock outcrops, at an operational range from several meters to a few kilometres. Reliable, quantitative measures of rock discontinuity roughness are necessary to characterize and evaluate the mechanical and hydraulic behavior of the rock mass. The aim of this research is to investigate the TLS potential and limitations for a reliable estimation of small scale roughness. TLS data noise and resolution define the level of extractable morphological detail, and therefore need to be known and associated with roughness value. The stationary variant of Discrete Wavelet Transform (SWT) was applied to estimate TLS noise level and perform wavelet denoising in direction of range measurements. Denoised TLS data were compared to reference surfaces of decreasing resolution (reference grids) in order to define the size of extractable surface detail. Noise and resolution effect on rock surface roughness, wavelet denoising success and extractable roughness scale were investigated with comparative analyses of TLS and reference surfaces. The developed methodology enabled reasonable TLS noise estimation, improved capabilities of TLS for modelling fine features of an irregular rock surface, and indicated the surface scale that can be reliably extracted from the TLS data.

The goal of efficient and effective real-world image super-resolution (Real-ISR) is to recover the high-resolution image from the given low-resolution image with unknown degradation by limited computation resources. Prior research has attempted to design a fully degradation-adaptive network, where the entire backbone is a nonlinear combination of several sub-networks which can handle different degradation subspaces. However, these methods heavily rely on expensive dynamic convolution operations and are inefficient in super-resolving images of different degradation levels. To address this issue, we propose an efficient and effective real-world image super-resolution network (E2-RealSR) based on partial degradation modulation, which is consisted of a small regression and a lightweight super-resolution network. The former accurately predicts the individual degradation parameters of input images, while the latter only modulates its partial parameters based on the degradation information. The extensive experiments validate that our proposed method is capable of recovering the rich details in real-world images with varying degradation levels. Moreover, our approach also has an advantage in terms of efficiency, compared to state-of-the-art methods. Our method shows improved performance while only using 20% of the parameters and 60% of the FLOPs of DASR. The relevant code is made available on this link as open source.

Bank resolution is key to avoiding a repetition of the global financial crisis, where failing financial institutions had to be bailed out with taxpayers’ money. It permits recapitalizing banks or alternatively winding them down in an orderly fashion without creating systemic risk. Resolution measures, however, suffer from structural weakness. They are taken by States with territorially limited powers, yet they concern entities or groups with global activities and assets in many countries. Under traditional rules of private international law, these activities and assets are governed by the law of other States, which is beyond the remit of the State undertaking the resolution. This paper illustrates the conflict between resolution and private international law by taking the example of the European Union, where the limitations of cross-border issues are most acute. It explains the techniques and mechanisms provided in the Bank Resolution and Recovery Directive (BRRD) and the Single Resolution Mechanism (SRM) Regulation to make resolution measures effective in intra-Eurozone cases, in intra-EU conflicts with non-Euro Member States and in relation to third States. However, it also shows divergences in the BRRD's transposition into national law and flaws that have been uncovered through first cases decided by national courts. A brief overview of third country regimes furthermore highlights the problems in obtaining recognition of EU resolution measures abroad. This article argues that regulatory cooperation alone is insufficient to overcome these shortcomings. It stresses that the effectiveness of resolution will ultimately depend on the courts. Therefore, mere soft law principles of regulatory cooperation are insufficient. A more stable and uniform text on resolution is required, which could take the form of a legislative guide or, ideally, of a model law. It is submitted that such a text could pave the way for greater effectiveness of cross-border resolution.