High-resolution Grid Research Articles

Evaluating Uncertainties in Reconstructing the Pre-eutrophic State of the North Sea

The North Sea is affected by eutrophication problems despite the decreasing riverine nutrient fluxes since the late 1980s. Formally, assessment of the eutrophication state of European marine environments is based on their historical state. Model estimates are increasingly used to support monitoring data that often do not encompass such pre-eutrophic conditions. However, various sources of uncertainties emerge when producing these estimates. In this study, we systematically quantify various sources of uncertainties in terms of variability, and assess their importance for the North Sea. For the reconstruction of the historical state, we use two coupled physical-biogeochemical model systems: ECOHAM on a 20-km grid for the European shelf and GPM on a high-resolution (1.5–4.5 km) grid for the Southern North Sea. To gain insights into the impacts due to the uncertainty in riverine loadings, we consider the historical nutrient inputs from two alternative watershed-models (MONERIS and E-HYPE). Overall, the modeled historic state based on E-HYPE shows higher nutrient concentrations compared to the state based on MONERIS, especially in the coastal regions. Assessing the degree of methodological uncertainties by an inter-comparison of different sources and against natural variabilities provides insight into the reliability of the model-based reconstruction of the historical state. We find that in regions influenced by freshwater from major rivers uncertainties owed to riverine loading scenarios exceed the natural sources of variability. For the offshore regions, natural sources of variability dominate over those caused by model- and scenario-related uncertainties. These findings are expected to assist decision makers and researchers in gaining insight into the degree of confidence in evaluating the model results, and prioritizing the need for refinement of models and scenarios for the production of reliable projections.

A nested multi-scale system implemented in the large-eddy simulation model PALM model system 6.0

Abstract. Large-eddy simulation (LES) provides a physically sound approach to study complex turbulent processes within the atmospheric boundary layer including urban boundary layer flows. However, such flow problems often involve a large separation of turbulent scales, requiring a large computational domain and very high grid resolution near the surface features, leading to prohibitive computational costs. To overcome this problem, an online LES–LES nesting scheme is implemented into the PALM model system 6.0. The hereby documented and evaluated nesting method is capable of supporting multiple child domains, which can be nested within their parent domain either in a parallel or recursively cascading configuration. The nesting system is evaluated by first simulating a purely convective boundary layer flow system and then three different neutrally stratified flow scenarios with increasing order of topographic complexity. The results of the nested runs are compared with corresponding non-nested high- and low-resolution results. The results reveal that the solution accuracy within the high-resolution nest domain is clearly improved as the solutions approach the non-nested high-resolution reference results. In obstacle-resolving LES, the two-way coupling becomes problematic as anterpolation introduces a regional discrepancy within the obstacle canopy of the parent domain. This is remedied by introducing canopy-restricted anterpolation where the operation is only performed above the obstacle canopy. The test simulations make evident that this approach is the most suitable coupling strategy for obstacle-resolving LES. The performed simulations testify that nesting can reduce the CPU time up to 80 % compared to the fine-resolution reference runs, while the computational overhead from the nesting operations remained below 16 % for the two-way coupling approach and significantly less for the one-way alternative.

Beyond connecting the dots: A multi-scale, multi-resolution approach to marine habitat mapping

Conflicts of interests between economic and nature conservation stakeholders are increasingly common in coastal seas, inducing a growing need for evidence-based marine spatial planning. This requires accurate, high-resolution habitat maps showing the spatial distribution of benthic assemblages and enabling intersections of habitats and anthropogenic activities. However, such detailed maps are often not available because relevant biological data are scarce or poorly integrated. Instead, physiotope maps, solely based on abiotic variables, are now often used in marine spatial planning. Here, we investigated how pointwise, relatively sparse biological data can be integrated with gridded, high-resolution environmental data into informative habitat maps, using the intensively used southern North Sea as a case-study. We first conducted hierarchical clustering to identify discrete biological assemblages for three faunal groups: demersal fish, epifauna, and endobenthos. Using Random Forest models with high-resolution abiotic predictors, we then interpolated the distribution of these assemblages to high resolution grids. Finally, we quantified different anthropogenic pressures for each habitat. Habitat maps comprised a different number of habitats between faunal groups (6, 13, and 10 for demersal fish, epifauna, and endobenthos respectively) but showed similar spatial patterns for each group. Several of these ‘fauna-inclusive’ habitats resembled physiotopes, but substantial differences were also observed, especially when few (6; demersal fish) or most (13; epifauna) physiotopes were delineated. Demersal fishing and offshore wind farms (OWFs) were clearly associated with specific habitats, resulting in unequal anthropogenic pressure between different habitats. Natura-2000 areas were not specifically associated with demersal fishing, but OWFs were situated mostly inside these protected areas. We thus conclude that habitat maps derived from biological datasets that cover relevant faunal groups should be included more in ecology-inclusive marine spatial planning, instead of only using physiotope maps based on abiotic variables. This allows better balancing of nature conservation and socio-economic interests in continental shelf seas.

Accelerated Time and High-Resolution 3D Modeling of the Flow and Dispersion of Noxious Substances over a Gigantic Urban Area—The EMERGENCIES Project

Accidental or malicious releases in the atmosphere are more likely to occur in built-up areas, where flow and dispersion are complex. The EMERGENCIES project aims to demonstrate the operational feasibility of three-dimensional simulation as a support tool for emergency teams and first responders. The simulation domain covers a gigantic urban area around Paris, France, and uses high-resolution metric grids. It relies on the PMSS modeling system to model the flow and dispersion over this gigantic domain and on the Code_Saturne model to simulate both the close vicinity and the inside of several buildings of interest. The accelerated time is achieved through the parallel algorithms of the models. Calculations rely on a two-step approach: the flow is computed in advance using meteorological forecasts, and then on-demand release scenarios are performed. Results obtained with actual meteorological mesoscale data and realistic releases occurring both inside and outside of buildings are presented and discussed. They prove the feasibility of operational use by emergency teams in cases of atmospheric release of hazardous materials.

Long Characteristics versus Short Characteristics in 3D Radiative Transfer Simulations of Polarized Radiation

Abstract We compare maps of scattering polarization signals obtained from three-dimensional (3D) radiation transfer calculations in a magnetoconvection model of the solar atmosphere using formal solvers based on the “short characteristics” (SC) and the “long characteristics” (LC) methods. The SC method requires less computational work, but it is known to introduce spatial blurring in the emergent radiation for inclined lines of sight. For polarized radiation this effect is generally more severe due to it being a signed quantity and to the sensitivity of the scattering polarization to the model’s inhomogeneities. We study the differences in the polarization signals of the emergent spectral line radiation calculated with such formal solvers. We take as a case study already published results of the scattering polarization in the Sr i 4607 Å line obtained with the SC method, demonstrating that in high-resolution grids it is accurate enough for that type of study. In general, the LC method is the preferred one for accurate calculations of the emergent radiation, which is the reason why it is now one of the options in the public version of the 3D radiative transfer code PORTA.

Augmenting the spatial resolution of climate-change temperature projections for city planners and local decision makers

Before the 2010, studies in climate change (CC) projections embracing scales below 3° were difficult to find. This has changed dramatically over the past ten years, with literature addressing high resolution grids for climate studies, allowing a better understanding and forecasting of CC at finer scales. However, downscaling methods remain poorly explored in urban planning. Research shows that the main difficulties relate to mismatches between data needs and data availability, terminology, constraints of information technology and maps that inform spatial planning decision-making processes. Based on dynamic downscaled maps for RCP 4.5 and RCP 8.5 at 10 km resolution published by Ecuador’s Ministry of Environment and Water (MAAE), we develop a method for augmenting the resolution scale at 30 m. We use digital elevation models and Landsat 4/5/7/8 satellite imagery for land surface temperature (LST) and present a series of steps and equations before applying Stefan Bolzman’s law. We present the necessary equations between the filling-in of LST outliers, and their projection onto air temperature at 2 m height, taking surface emissivity estimates based on (Alves et al 2017 J. Hyperspectral Remote Sens. 7 91–100). We extrapolate the resulting air temperature in time with Fourier’s series, and for the purpose of coherence among scales, we upscale air temperature maps at 30 m to those at 10 km resolution. The resulting CC projection maps are validated with the temporal series of air temperature (max, min, mean) from the meteorological station in the Ecuadorian city of Portoviejo (Student’s t-test) for the period between 1981 and 2005, with Portoviejo city facing temperature increases of up to 2 °C under RCP 4.5 scenario in the period 2011–2040 vs 1981–2005. The final CC maps have an augmented resolution of 30 m, are compatible with those of MAAE, and offer a low-cost procedure for informing land-use and urban planners, as well as local development decision makers, of temperature anomalies due to climate change.

Validation Process for Rooftop Wind Regime CFD Model in Complex Urban Environment Using an Experimental Measurement Campaign

This research presents a validation methodology for computational fluid dynamics (CFD) assessments of rooftop wind regime in urban environments. A case study is carried out at the Donadeo Innovation Centre for Engineering building at the University of Alberta campus. A numerical assessment of rooftop wind regime around buildings of the University of Alberta North campus has been performed by using 3D steady Reynolds-averaged Navier–Stokes equations, on a large-scale high-resolution grid using the ANSYS CFX code. Two methods of standard deviation (SDM) and average (AM) were introduced to compare the numerical results with the corresponding measurements. The standard deviation method showed slightly better agreements between the numerical results and measurements compared to the average method, by showing the average wind speed errors of 10.8% and 17.7%, and wind direction deviation of 8.4° and 12.3°, for incident winds from East and South, respectively. However, the average error between simulated and measured wind speeds of the North and West incidents were 51.2% and 24.6%, respectively. Considering the fact that the upstream geometry was not modeled in detail for the North and West directions, the validation methodology presented in this paper is deemed as acceptable, as good agreement between the numerical and experimental results of East and South incidents were achieved.

Local-inertial shallow water model on unstructured triangular grids

Two-dimensional shallow water models are widely used for flood risk assessment. Application of these models to large-scale urban areas significantly increases the computational cost as it requires high-resolution simulations to capture the complex hydrodynamic processes. Hence, simplified models that are based on local-inertial formulations have been proposed by different researchers. Although these models are successful in simulating floods, their applications are limited by the use of structured grids and instability issues. Structured grids do not have the flexibility of providing different mesh resolutions to model the computational domain. Importantly, in the case of structured grids, the use of a single grid or the combination of finer and coarser grids inevitably increases the overall computational time. To overcome all these problems, an unstructured grid-based local-inertial model is developed. The performance of the model is rigorously evaluated by solving analytical test cases and simulating an urban flood in Glasgow, UK. Finally, the model is applied to simulate a catastrophic flood event that occurred in Chennai, India. The simulated water depths and inundation extents are compared with observed data or full-2D model results. The investigations show that the developed model has the potential for simulating floods on a large-scale with high-resolution grids at a comparatively lower computational cost than its predecessors for a similar range of accuracy.

Efficient Point-in-Polygon Tests by Grids Without the Trouble of Tuning the Grid Resolutions.

The grid-based approach is popular for point-in-polygon tests. However, there is a trade-off between the preprocessing and the inclusion test, which always requires the grid resolutions to be tuned. In this article, we address this challenge by enhancing the grid structure using y-axis-aligned stripes, which are formed by the y-axis-aligned lines passing through the endpoints of the edge segments in the cell, thereby managing the edge segments in each grid cell. Moreover, we precompute the inclusion properties of the x-axis-aligned top borders of the stripes during preprocessing. Therefore, to answer a query point with the ray crossing method, we can emit a ray from the point to propagate upwards until the ray arrives at the top border of a stripe. We thoroughly consider singular cases to guarantee each query point can be answered in the stripe that contains the point. In our method, the computational load can be decreased, as one coordinate of the intersection point between the ray and an edge is known in advance, and parallel computing can be well exploited because the branching operations for determining whether an edge intersects with the ray are saved. Experimental results show that the efficiency of our method does not vary much with respect to the grid resolutions, so the trouble of tuning grid resolutions can be avoided. Ultimately, our method with a low grid resolution can reduce the preprocessing time and still achieve a higher inclusion test efficiency than the existing methods with a high grid resolution, especially on GPUs.

Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions

Abstract. In this study, we improve the representation of global river runoff in the Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) framework, allowing for a more realistic treatment of coastal plume dynamics. We use a suite of experiments to explore the sensitivity of coastal plume regions to runoff forcing, model grid resolution, and grid type. The results show that simulated sea surface salinity (SSS) is reduced as the model grid resolution increases. Compared to Soil Moisture Active Passive (SMAP) observations, simulated SSS is closest to SMAP when using daily, point-source runoff (DPR) and the intermediate-resolution LLC270 grid. The Willmott skill score, which quantifies agreement between models and SMAP, yields up to 0.92 for large rivers such as the Amazon. There was no major difference in SSS for tropical and temperate coastal rivers when the model grid type was changed from the ECCO v4 latitude–longitude–polar-cap grid to the ECCO2 cube–sphere grid. We also found that using DPR forcing and increasing model resolution from the coarse-resolution LLC90 grid to the intermediate-resolution LLC270 grid elevated the river plume area, volume, stabilized the stratification and shoal the mixed layer depth (MLD). Additionally, we find that the impacts of increasing model resolution from the intermediate-resolution LLC270 grid to the high-resolution LLC540 grid are regionally dependent. The Mississippi River Plume is more sensitive than other regions, possibly because the wider and shallower Texas–Louisiana shelf drives a stronger baroclinic effect, as well as relatively weak sub-grid vertical mixing and adjustment in this region. Since rivers deliver large amounts of freshwater and anthropogenic materials to coastal regions, improving the representation of river runoff in global, high-resolution models will advance studies of coastal hypoxia, carbon cycling, and regional weather and climate and will ultimately help to predict land–ocean–atmospheric feedbacks seamlessly in the next generation of Earth system models.

Global shipping soundscapes: A study of the COVID-19 impact

The global ocean soundscape, at frequencies below 400 Hz, is dominated by shipping and at some select frequencies marine mammals and large storms. In this paper, we present a global model of the shipping and wind noise soundscape. The Parabolic Equation (PE) Model is used to compute the propagation loss from a grid of points through the dynamical ocean to a high resolution grid of receivers. Source depths of 5 m are used for ships and 1/4 wavelength are used surface wind. The combined wind/shipping soundscape can then be generated using satellite observations of the shipping positions via Automated Identification Services and the wind speed at 10 m. Both databases were provided by SPIRE Inc. SPIRE provided the shipping AIS for March/April 2018 and March/April 2020. The global shipping soundscape for these two time periods reveals a drop of 3-6 dB depending upon position at 50 Hz from the reduction in surface shipping traffic due to the COVID-19 global shut down.

Historical and future global burned area with changing climate and human demography

Summary Wildfires influence terrestrial carbon cycling and represent a safety risk, and yet a process-based understanding of their frequency and spatial distributions remains elusive. We combine satellite-based observations with an enhanced dynamic global vegetation model to make regionally resolved global assessments of burned area (BA) responses to changing climate, derived from 34 Earth system models and human demographics for 1860–2100. Limited by climate and socioeconomics, recent BA has decreased, especially in central South America and mesic African savannas. However, future simulations predict increasing BA due to changing climate, rapid population density growth, and urbanization. BA increases are especially notable at high latitudes, due to accelerated warming, and over the tropics and subtropics, due to drying and human ignitions. Conversely, rapid urbanization also limits BA via enhanced fire suppression in the immediate vicinity of settlements, offsetting the potential for dramatic future increases, depending on warming extent. Our analysis provides further insight into regional and global BA trends, highlighting the importance of including human demographic change in models for wildfire under changing climate.

Fringe Projection Profilometry in Production Metrology: A Multi-Scale Comparison in Sheet-Bulk Metal Forming.

Fringe projection profilometry in combination with other optical measuring technologies has established itself over the last decades as an essential complement to conventional, tactile measuring devices. The non-contact, holistic reconstruction of complex geometries within fractions of a second in conjunction with the lightweight and transportable sensor design open up many fields of application in production metrology. Furthermore, triangulation-based measuring principles feature good scalability, which has led to 3D scanners for various scale ranges. Innovative and modern production processes, such as sheet-bulk metal forming, thus, utilize fringe projection profilometry in many respects to monitor the process, quantify possible wear and improve production technology. Therefore, it is essential to identify the appropriate 3D scanner for each application and to properly evaluate the acquired data. Through precise knowledge of the measurement volume and the relative uncertainty with respect to the specimen and scanner position, adapted measurement strategies and integrated production concepts can be realized. Although there are extensive industrial standards and guidelines for the quantification of sensor performance, evaluation and tolerancing is mainly global and can, therefore, neither provide assistance in the correct, application-specific positioning and alignment of the sensor nor reflect the local characteristics within the measuring volume. Therefore, this article compares fringe projection systems across various scale ranges by positioning and scanning a calibrated sphere in a high resolution grid.

Large-scale flow simulations using lattice Boltzmann method with AMR following free-surface on multiple GPUs

Free-surface flow simulations require high-resolution grids to capture phenomena at the interface as well as a long computational time. In this paper, we propose a numerical method for realizing large-scale free-surface flow simulations using the lattice Boltzmann method and multiple GPUs. By introducing the adaptive mesh refinement (AMR) method, which adapts high-resolution grids to free surfaces, to the lattice Boltzmann method, the number of lattice points can be greatly reduced. In the calculation of the AMR method, the spatial distribution of a computational load changes with time; therefore, the number of lattice points assigned to each GPU is kept equal by dynamic domain partitioning using a space-filling curve. We measured the weak scalability of our AMR code on the TSUBAME3.0 supercomputer at the Tokyo Institute of Technology. By hiding GPU–GPU communication overheads by the overlapping method, the performance increased 1.29 times that of the naïve implementation, and we achieved the fairly high performance of 14,570 MLUPS using 256 GPUs. We demonstrate large-scale simulations for the dam breaking problem and show a reduction in computational cost with the AMR method.

Aerodynamic Performance of the Three-Dimensional Lumped Flexibility Wing Under Wind Fluctuating Condition

Understanding the effect of fluctuating wind on the aerodynamic performance of the wing is important for designing practical using flapping-wing micro air vehicles (FMAV). This paper aims at providing a systematic synthesis on the fluctuating wind influence on the performance of the three dimensional lumped flexibility wing based on the numerical analysis approach. The fluctuating wind is simplified as a sine type function, and the flexibility of the wing is modeled as the passive pitching motion by connecting a rigid wing to a torsional spring at the root of the wing. The interaction between the fluctuating wind and the lumped flexibility wing is performed on a high-resolution computational grid. The evaluation is based on validation with published experiment data. The results indicate that the fluctuating wind cannot enhance the flexible wings’ propulsive and lifting performance simultaneously, however, it influences the aerodynamic characteristics of the wing greatly. Comparing to the rigid wing, the suppress leading edge vortex and trailing edge vortex are observed of the flexible wing under appropriate fluctuating wind, which leads the flexible wing to not only have better propulsive and lifting performance, but also flight stability performance.

Improving satellite-based estimation of surface ozone across China during 2008–2019 using iterative random forest model and high-resolution grid meteorological data

China is faced with increasing ozone pollution due to rapid economic development and urbanization. Although the ground monitoring network provides continuous real-time ozone measurements, its practical applications are limited due to sparse spatial distribution. The monitoring network coupling with various data and the machine learning algorithms is a promising approach to estimate surface ozone concentrations. However, previous studies on ozone estimation in China are restricted to small study scale, low spatial resolution and low predictive ability. The study aims to 1) improve the accuracy of surface ozone estimates across China using an iterative random forest (RF) model, more recent ground monitoring data and high-resolution grid meteorological data, and 2) estimate the daily max 8-h average ozone concentrations across China during 2008–2019 at a spatial resolution of 0.0625°. The iterative RF model showed that the sample-based and site-based cross-validation (CV) R2 were 0.84 and 0.79, respectively, indicating higher accuracy than the single RF model and previous studies. Daily max 8-h average ozone data product across China was estimated during 2008–2019 with an improved spatial resolution of 0.0625°. The newly generated ozone data product shows great potential in future studies to assess the short-term and long-term health effect of ozone pollution.

An Operational Numerical System for Oil Stranding Risk Assessment in a High-Density Vessel Traffic Area

In the Mediterranean Sea unique environmental characteristics and sensitive assets coexist with intense maritime traffic that is represented by frequent daily passages of vessels along the main waterways. In order to assess the risk of oil stranding in case of at-sea emergencies and provide key products for environmental agencies or policymakers preparedness, a geographically relocatable, operational numerical system is implemented and tested. The system relies on the application of oceanographic and particle tracking models and is able to provide, on a high-resolution and unstructured computational grid, a 3-days forecast of those variables known as the main drivers of oil slicks at sea. The risk of potential oil stranding is computed through a combination of anthropogenic hazard and shoreline vulnerability. The sources of hazard vary on time and space in relation to local maritime vessel traffic. The shoreline vulnerability is based on the current knowledge of slope, main grain size, geology of rocks, and occurrence of manmade structures at coast. The operational system is enriched by a web graphical user interface and includes automatic and on-demand working modes. Its functionality is demonstrated in the Strait of Bonifacio (western Mediterranean Sea), area with a high potential risk of oil stranding due to an intense maritime traffic. Risk assessment is hence computed for a test year, the 2018. Critical values of risk are found in correspondence of long stretches of littoral while many of them are currently characterized by a low anthropogenic pressure. The results emphasize the geomorphological features of the shorelines as reducing or amplifying factors to any potential impact of oil stranding at coast.

Static grid carbon factors – Can we do better?

The average carbon intensity (gCO2e/kWh) of electricity provided by the UK National Grid is decreasing and becoming more time variable. This paper reviews the impact on energy calculations of using various levels of data resolution (half hourly, daily, monthly and annual) and of moving to region specific data. This analysis is in two parts, one focused on the potential impact on Part L assessments and the other on reported carbon emissions for existing buildings. Analysis demonstrated that an increase in calculated emissions of up to 12% is possible when using an emissions calculation methodology employing higher resolution grid carbon intensity data. Regional analysis indicated an even larger calculation discrepancy, with some regions annual emissions increasing by a factor of ten as compared to other regions. This paper proposes a path forward for the industry to improve the accuracy of analysis by using better data sources. The proposed change in calculation methodology is analogous to moving from using an annual average external temperature to using a CIBSE weather profile for a specific city or using a future weather file. Practical application: This paper aims to quantify the inaccuracy of a calculation methodology in common use in the industry and key to building regulations (specifically Building Regulations Part L – Conservation of Fuel and Power) – translating electricity consumption into carbon emissions. It proposes an alternative methodology which improves the accuracy of the calculation based on improved data inputs.

Photoresponsive thin films of well-synthesized azobenzene side-chain liquid crystalline polynorbornenes as command surface for patterned graphic writing

Azobenzene-containing polymers (azopolymers) are a kind of intensively explored fascinating photoresponsive materials, liquid crystalline (LC) azopolymers with excellent film-forming, ordered structure and self-repairing capability are endowed with enhanced photoisomerization and photoalignment characteristics capable of developing into photo-modulated smart surfaces. Here in this work, two azobenzene side-chain LC polynorbornenes of PNB-Azo-n with different DP of n = 50 and 100 have been well synthesized through ring-opening metathesis polymerization (ROMP). The polynorbornene backbone of less flexibility with larger spacing between adjacent azobenzene side groups endows stronger inhibition for H-aggregation and better photoresponsiveness. The high-DP azopolynorbornene of PNB-Azo-100 thin films well behave as command surface for the upper layer nematic LC molecules thanks to their better performance in photoisomerization and photoalignment, together with their good compatibility and dissolution-resistance to the nematic LC mixture of E7. Selectively optically readable LC graphic writings at normal size through various photomasks have been demonstrated, and higher grid resolution up to sub-ten micrometer with a digital micromirror device (DMD) based dynamic photopatterning system has been achieved. Therefore, such kind of LC azopolynorbornenes demonstrate promising applications in LC photoalignment system and photoresponsive devices for potential anti-forgery document security and smart card technology.

Robust deep learning-based multi-image super-resolution using inpainting

Traditional super-resolution techniques are generally presented as optimization problems with variations in the choice of optimization methods and cost functions. Even for the overdetermined cases, the problem is ill-conditioned. The situation is worsened when considering underdetermined cases with unknown regions due to occlusions or lack of data. Deep learning-based methods have shown promise in solving a similar problem. One recent advancement has come in the form of partial convolutions, which were developed to perform infilling of holes in images. When used in an appropriate deep neural network, this particular variant of the convolutional filter has shown great promise in approximating missing spatial information. The method described is formulated as a two-stage process. Lower resolution images are first registered and placed on a high-resolution grid. The problem is then treated as an in-painting task where the missing regions are reconstructed using a deep neural network with partial convolutional filters. We compare our method against deep learning-based single image super-resolution methods and classical multi-image super-resolution techniques using two similarity metrics and show that our method is more robust to occlusions and errors in registration while also producing higher quality outputs.