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DOE OSTI2015

CASSIS: The Cornell atlas of Spitzer/infrared spectrograph sources. II. HIGH-Resolution observations

The Infrared Spectrograph (IRS) on board the Spitzer Space Telescope observed about 15,000 objects during the cryogenic mission lifetime. Observations provided low-resolution (R=λ/Δλ≈60−127) spectra over ≈5−38 μm and high-resolution (R≈600) spectra over 10–37 μm. The Cornell Atlas of Spitzer/IRS Sources (CASSIS) was created to provide publishable quality spectra to the community. Low-resolution spectra have been available in CASSIS since 2011, and here we present the addition of the high-resolution spectra. The high-resolution observations represent approximately one-third of all staring observations performed with the IRS instrument. While low-resolution observations are adapted to faint objects and/or broad spectral features (e.g., dust continuum, molecular bands), high-resolution observations allow more accurate measurements of narrow features (e.g., ionic emission lines) as well as a better sampling of the spectral profile of various features. Given the narrow aperture of the two high-resolution modules, cosmic ray hits and spurious features usually plague the spectra. Our pipeline is designed to minimize these effects through various improvements. A super-sampled point-spread function was created in order to enable the optimal extraction in addition to the full aperture extraction. The pipeline selects the best extraction method based on the spatial extent of the object. For unresolved sources, the optimal extraction provides a significant improvement in signal-to-noise ratio over a full aperture extraction. We have developed several techniques for optimal extraction, including a differential method that eliminates low-level rogue pixels (even when no dedicated background observation was performed). The updated CASSIS repository now includes all the spectra ever taken by the IRS, with the exception of mapping observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Three Photon Excited Image Scanning Microscopy for in-Depth Super-Resolution Studies of Biological Samples

Multiphoton laser scanning microscopy is a powerful tool for deep imaging of thick biological samples. Image scanning microscopy (ISM) has demonstrated significant improvements in the signal-to-noise ratio in confocal laser scanning microscopy, while at the same time improving upon the effectively attainable resolution. Two-photon excitation (2PE), combined with ISM, has been shown to allow for deep tissue imaging with enhanced resolution compared to 2PE microscopy. Three-photon excitation (3PE) has enabled record imaging depth and contrast for multiphoton imaging, due to the superior suppression of out-of-focus signal generation. In this paper, we demonstrate super-resolution 3PE ISM. This is achieved using a single-photon avalanche detector array, and 1040-nm pulses for 3PE of blue fluorescence. This method enables subdiffraction limited resolution imaging of biological samples stained with blue fluorescent markers, such as mouse myocardial and spinal cord tissues stained with 4 ′ , 6 -diamidino-2-phenylindole. Deconvolution improves the resolving power further and allows for imaging with better than λ / 8 resolution with respect to the 3PE wavelength λ . With the ISM pixel reassignment procedure, we demonstrate a resolution enhancement of ∼ 1.6 laterally, compared to the resolution attained using a photomultiplier tube in a non-descanned detection arrangement, and a factor of ∼ 1.8 enhancement in axial resolution. The experimentally measured three-dimensional point spread function volume is shrunk ∼ 4.4 -fold, which is close to the theoretically expected enhancement. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

xMDFF: molecular dynamics flexible fitting of low-resolution X-ray structures

A new real-space refinement method for low-resolution X-ray crystallography is presented. The method is based on the molecular dynamics flexible fitting protocol targeted at addressing large-scale deformations of the search model to achieve refinement with minimal manual intervention. An explanation of the method is provided, augmented by results from the refinement of both synthetic and experimental low-resolution data, including an independent electrophysiological verification of the xMDFF-refined crystal structure of a voltage-sensor protein. X-ray crystallography remains the most dominant method for solving atomic structures. However, for relatively large systems, the availability of only medium-to-low-resolution diffraction data often limits the determination of all-atom details. A new molecular dynamics flexible fitting (MDFF)-based approach, xMDFF, for determining structures from such low-resolution crystallographic data is reported. xMDFF employs a real-space refinement scheme that flexibly fits atomic models into an iteratively updating electron-density map. It addresses significant large-scale deformations of the initial model to fit the low-resolution density, as tested with synthetic low-resolution maps of d-ribose-binding protein. xMDFF has been successfully applied to re-refine six low-resolution protein structures of varying sizes that had already been submitted to the Protein Data Bank. Finally, via systematic refinement of a series of data from 3.6 to 7 Å resolution, xMDFF refinements together with electrophysiology experiments were used to validate the first all-atom structure of the voltage-sensing protein Ci-VSP.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

SU-E-J-197: Investigation of Microsoft Kinect 2.0 Depth Resolution for Patient Motion Tracking

Purpose: Investigate the use of the Kinect 2.0 for patient motion tracking during radiotherapy by studying spatial and depth resolution capabilities. Methods: Using code written in C#, depth map data was abstracted from the Kinect to create an initial depth map template indicative of the initial position of an object to be compared to the depth map of the object over time. To test this process, simple setup was created in which two objects were imaged: a 40 cm × 40 cm board covered in non reflective material and a 15 cm × 26 cm textbook with a slightly reflective, glossy cover. Each object, imaged and measured separately, was placed on a movable platform with object to camera distance measured. The object was then moved a specified amount to ascertain whether the Kinect’s depth camera would visualize the difference in position of the object. Results: Initial investigations have shown the Kinect depth resolution is dependent on the object to camera distance. Measurements indicate that movements as small as 1 mm can be visualized for objects as close as 50 cm away. This depth resolution decreases linearly with object to camera distance. At 4 m, the depth resolution had decreased to observe a minimum movement of 1 cm. Conclusion: The improved resolution and advanced hardware of the Kinect 2.0 allows for increase of depth resolution over the Kinect 1.0. Although obvious that the depth resolution should decrease with increasing distance from an object given the decrease in number of pixels representing said object, the depth resolution at large distances indicates its usefulness in a clinical setting.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Photon-counting hexagonal pixel array CdTe detector: Spatial resolution characteristics for image-guided interventional applications

Purpose: High-resolution, photon-counting, energy-resolved detector with fast-framing capability can facilitate simultaneous acquisition of precontrast and postcontrast images for subtraction angiography without pixel registration artifacts and can facilitate high-resolution real-time imaging during image-guided interventions. Hence, this study was conducted to determine the spatial resolution characteristics of a hexagonal pixel array photon-counting cadmium telluride (CdTe) detector. Methods: A 650 μm thick CdTe Schottky photon-counting detector capable of concurrently acquiring up to two energy-windowed images was operated in a single energy-window mode to include photons of 10 keV or higher. The detector had hexagonal pixels with apothem of 30 μm resulting in pixel pitch of 60 and 51.96 μm along the two orthogonal directions. The detector was characterized at IEC-RQA5 spectral conditions. Linear response of the detector was determined over the air kerma rate relevant to image-guided interventional procedures ranging from 1.3 nGy/frame to 91.4 μGy/frame. Presampled modulation transfer was determined using a tungsten edge test device. The edge-spread function and the finely sampled line spread function accounted for hexagonal sampling, from which the presampled modulation transfer function (MTF) was determined. Since detectors with hexagonal pixels require resampling to square pixels for distortion-free display, the optimal square pixel size was determined by minimizing the root-mean-squared-error of the aperture functions for the square and hexagonal pixels up to the Nyquist limit. Results: At Nyquist frequencies of 8.33 and 9.62 cycles/mm along the apothem and orthogonal to the apothem directions, the modulation factors were 0.397 and 0.228, respectively. For the corresponding axis, the limiting resolution defined as 10% MTF occurred at 13.3 and 12 cycles/mm, respectively. Evaluation of the aperture functions yielded an optimal square pixel size of 54 μm. After resampling to 54 μm square pixels using trilinear interpolation, the presampled MTF at Nyquist frequency of 9.26 cycles/mm was 0.29 and 0.24 along the orthogonal directions and the limiting resolution (10% MTF) occurred at approximately 12 cycles/mm. Visual analysis of a bar pattern image showed the ability to resolve close to 12 line-pairs/mm and qualitative evaluation of a neurovascular nitinol-stent showed the ability to visualize its struts at clinically relevant conditions. Conclusions: Hexagonal pixel array photon-counting CdTe detector provides high spatial resolution in single-photon counting mode. After resampling to optimal square pixel size for distortion-free display, the spatial resolution is preserved. The dual-energy capabilities of the detector could allow for artifact-free subtraction angiography and basis material decomposition. The proposed high-resolution photon-counting detector with energy-resolving capability can be of importance for several image-guided interventional procedures as well as for pediatric applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Resolution and Dynamical Core Dependence of Atmospheric River Frequency in Global Model Simulations

This study examines the sensitivity of atmospheric river (AR) frequency simulated by a global model with different grid resolutions and dynamical cores. Analysis is performed on aquaplanet simulations using version 4 of Community Atmosphere Model (CAM4) at 240, 120, 60 and 30 km model resolutions each with the Model for Prediction Across Scales (MPAS) and High-Order Methods Modeling Environment (HOMME) dynamical cores. The frequency of AR events decreases with model resolution and the HOMME dynamical core produces more AR events than MPAS. Comparing the frequencies determined using absolute and percentile thresholds of large-scale conditions used to define an AR, model sensitivity is found to be related to the overall sensitivity of sub-tropical westerlies, atmospheric precipitable water content and profile and to a lesser extent on extra-tropical Rossby wave activity to model resolution and dynamical core. Real world simulations using MPAS at 120 km and 30 km grid resolutions also exhibit a decrease of AR frequency with increasing resolution over southern East Pacific, but there difference is smaller over northern East Pacific. This inter-hemispheric difference is related to the enhancement of convection in over the tropics with increased resolution. This anomalous convection sets off Rossby wave patterns that weaken the subtropical westerlies over southern East Pacific but have relatively little effect on those over northern East Pacific. In comparison to NCEP2 reanalysis, MPAS real world simulations are found to underestimate AR frequencies at both resolutions likely because of their climatologically drier sub-tropics and poleward shifted jets. This study highlights the important links between model climatology of large-scale conditions and extremes.

atmopheric river frequency↗

NASA NTRS2014

A Spatially Coherent Global Soil Moisture Product with Improved Temporal Resolution

Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11 km. These products are based on internal modules of the Land Parameter Retrieval Model (LPRM), an algorithm that uses the radiative transfer equation to link soil moisture, vegetation optical depth and land surface temperature to observed brightness temperatures. The soil moisture product that is independent of any type of ancillary data uses the internally calculated dielectric constant as a soil moisture proxy. This data product is not influenced by errors associated with coarse-scale global soil property maps or by any other type of forcing (e.g. re-analysis) data and is therefore solely based on satellite microwave observations. The second step builds upon recent developments to increase the spatial resolution of the LPRM retrievals using a smoothing filter downscaling method. With this method we can attain a spatial resolution that can be more useful at the scale of local and regional hydrological studies as well. The steps presented in this paper were applied to observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). The newly derived data sets were validated using ground-based observations from the International Soil Moisture Network (ISMN). The internally calculated dielectric constant product results in significantly more days with valid retrievals than the original soil moisture data products, in particular over arid regions. The dielectric constant product resulted in similar correlations with in situ data as the original soil moisture data product. Together, these findings demonstrate the usefulness of this new dielectric constant product for the hydrological modeling community and climate studies. A case study on the Australian Fitzroy catchment demonstrated that the downscaled data product has a more detailed spatial description of soil moisture, especially during wet and dry conditions with more pronounced dry and wet regions within the catchment. The increased resolution data products could therefore improve runoff predictions and this study demonstrated the potential added value of a transitioning from a spatial resolution of 56 km toward a higher resolution of 11 km. The hydrological implications of these newly developed data records are not only linked to AMSR-E satellite data, but also to the next generation Soil Moisture Active and Passive (SMAP) mission where a 9 km spatial resolution is the target resolution for satellite soil moisture products. The new data products will not replace the current LPRM products, but will be added to the existing array of data products and will become publicly available through our data portals.

spatial↗

DOE OSTI2024

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗

DOE OSTI2021

Super-Resolution Photothermal Patterning in Conductive Polymers Enabled by Thermally Activated Solubility

Doping induced solubility control (DISC) patterning is a recently developed technique which uses the change in polymer solubility upon doping, along with an optical dedoping process, to achieve high resolution optical patterning. DISC patterning is remarkable because the process resolution exceeds the linear Abbe’s diffraction limit, however, no mechanism has been proposed to explain such high resolution. Here, we use diffraction to spatially modulate the light intensity and determine the dissolution rate, revealing a superlinear dependence on light intensity, which yields features that are sharper than the profile of the writing photomask. This rate law is independent of wavelength, indicating that patterning resolution is not dominated by an optical dedoping reaction, as was previously proposed. Instead we show here that the optical patterning mechanism is primarily controlled by the thermal profile generated by the laser. To quantify this effect, the thermal profile and dissolution rate are modeled using a finite-element model and compared against patterned line cross sections as a function of wavelength, laser intensity, and dwell time. Our model reveals that although the laser-generated thermal profile is broadened considerably beyond the lasers resolution, the highly temperature dependent dissolution rate results in selective dissolution near the peak of the thermal profile. Therefore, the key factor in achieving super-resolution patterning is a strongly temperature dependent dissolution rate|a common feature of many polymers. In addition to suggesting several routes to improved resolution, our model also demonstrates that doping is not required for optical patterning of conjugated polymers, as was previously believed. Instead, we demonstrate that superlinear resolution optical patterning is attainable in any conjugated polymer simply by tuning the solvent quality during patterning, thus extending the applicability of our method to a wide class of materials. Here, we demonstrate the generality of photothermal patterning by writing sub-400 nm features into undoped Pff-BT4T-2OD.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Northern Hemisphere Blocking in ~25-km-Resolution E3SM v0.3 Atmosphere-Land Simulations

The fidelity of a prerelease Energy Exascale Earth System Model (E3SM) in reproducing atmospheric blocking is evaluated with ~100- and ~25-km horizontal resolution within ensembles of simulations with Atmospheric Modeling Intercomparison Protocol-type active atmosphere and land surface configurations. Here this evaluation is conducted via a hybrid bidimensional blocking index based on geopotential height. The lower-resolution model correctly reproduces the spatial distribution of blocking frequency maxima over the Northern Hemisphere. However, it overestimates the blocking frequency over western North America, the Pacific Northeast, and Eastern Europe regions and largely underestimates blocking frequency over the North Atlantic. The high-resolution model significantly reduces the bias over the North Pacific region, particularly over western North America, but the biases over the North Atlantic blocking sector mostly persist. A diagnosis of the mean flow reveals that the subtropical jet is displaced poleward in the high-resolution model with a jet core speed that is generally more realistic. A time scale analysis of eddies suggests that synoptic eddies associated with the blocking events are increased in the high-resolution configuration. The discrepancy between the models implies that both synoptic and low-frequency eddies play significant roles in determining North Pacific blocking, whereas North Atlantic blocking is mainly driven by low-frequency eddies. The characteristic time scale associated with blocking events is also investigated, and it shows that both model resolutions produce events that are overly persistent. However, the bias in the high-resolution model is reduced, which reflects more efficient energy dispersion with higher resolution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Machine learning assisted quantum super-resolution microscopy

One of the main characteristics of optical imaging systems is spatial resolution, which is restricted by the diffraction limit to approximately half the wavelength of the incident light. Along with the recently developed classical super-resolution techniques, which aim at breaking the diffraction limit in classical systems, there is a class of quantum super-resolution techniques which leverage the non-classical nature of the optical signals radiated by quantum emitters, the so-called antibunching super-resolution microscopy. This approach can ensure a factor of $\sqrt{n}$ improvement in the spatial resolution by measuring the n -th order autocorrelation function. The main bottleneck of the antibunching super-resolution microscopy is the time-consuming acquisition of multi-photon event histograms. We present a machine learning-assisted approach for the realization of rapid antibunching super-resolution imaging and demonstrate 12 times speed-up compared to conventional, fitting-based autocorrelation measurements. The developed framework paves the way to the practical realization of scalable quantum super-resolution imaging devices that can be compatible with various types of quantum emitters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Molecular-Resolution Electron Imaging of Defects and Dynamics at the Ice-Water Interface

Water crystallization into hexagonal ice (type I h ) is one of the most critical processes relevant to the Earth’s environment and human activities. However, despite recent breakthroughs in imaging non-equilibrium condensed ice structures, the ice-water interface has never been imaged at a molecular resolution. This is primarily due to the low stability of the hydrogen bonds in ice under high-resolution microscopy conditions and a lack of methods to prepare compatible samples. Here, this presentation describes the first molecular-resolution imaging of ice crystallized from liquid water and the ice-water interface using high-resolution transmission electron microscopy (HRTEM). By encapsulating deionized (DI) water between two amorphous carbon (a-C) TEM grids and subsequently freezing it with liquid N 2 on a cryo sample stage, we generated two types of ice: non-equilibrium, condensed ice from the atmosphere and encapsulated ice from the DI water (Fig. 1A). Condensed ice usually shows irregular, spherulitic shapes (Fig. 1B). Selected area electron diffraction (SAED) shows that they are a mixture of cubic and hexagonal crystals (Fig. 1C). On the contrary, encapsulated ice forms thin films that contain large-area single-crystalline regions of hexagonal ice oriented along the [0001] zone axis (Fig. 1D). Differential electron energy-loss spectroscopy (EELS) confirmed the high purity of the encapsulated ice free from organic contaminations that are common in other encapsulation methods for HRTEM such as graphene liquid cells. These single-crystalline areas are robust under the electron beam up to ~100 e/Å 2 s. Aberration-corrected HRTEM imaging in these areas achieved a line resolution of ~1.3 Å (Fig. 1E and F). This platform allows us to study near-equilibrium ice structures and dynamics at an unprecedented spatial resolution (Fig. 2). For example, we discovered subdomain-rich regions near the defective crystal edges despite the structure appearing single-crystalline according to diffraction criteria. These subdomains connect via low-angle grain boundaries with flat energy landscapes as a function of tilt angles (according to simulations), showing the high tolerance of ice to defect structures. When we tuned the sample temperature and electron flux rate, we observed radiolysis-controlled bubble generation and dissolution in ice single crystals near a steady state of bubble dynamics. Furthermore, rich beam-induced melting and recrystallization dynamics were observed at the ice-water interface with lattice resolution. These data represent the first observation of the ice-water phase transformation at the sub-nanometer level. In summary, the methods developed in this work enabled molecular-resolution observations of ice and the ice-water interface and shed light on the microstructures and phase transformation pathways. Finer control on the temperature, electron irradiation profile, and imaging detector could eventually lead to real-time observation of ice nucleation in water and address long-standing questions in the nucleation pathways.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2019

Towards an understanding of the resolution dependence of Core-Collapse Supernova simulations

ABSTRACT Using our new state-of-the-art core-collapse supernova (CCSN) code Fornax, we explore the dependence upon spatial resolution of the outcome and character of three-dimensional (3D) supernova simulations. For the same 19 M⊙ progenitor star, energy and radial binning, neutrino microphysics, and nuclear equation of state, changing only the number of angular bins in the θ and ϕ directions, we witness that our lowest resolution 3D simulation does not explode. However, when jumping progressively up in resolution by factors of two in each angular direction on our spherical-polar grid, models then explode, and explode slightly more vigorously with increasing resolution. This suggests that there can be a qualitative dependence of the outcome of 3D CCSN simulations upon spatial resolution. The critical aspect of higher spatial resolution is the adequate capturing of the physics of neutrino-driven turbulence, in particular its Reynolds stress. The greater numerical viscosity of lower resolution simulations results in greater drag on the turbulent eddies that embody turbulent stress, and, hence, in a diminution of their vigor. Turbulent stress not only pushes the temporarily stalled shock further out, but bootstraps a concomitant increase in the deposited neutrino power. Both effects together lie at the core of the resolution dependence we observe.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

The ecological assembly of bacterial communities in Antarctic wetlands varies across levels of phylogenetic resolution

Summary As functional traits are conserved at different phylogenetic depths, the ability to detect community assembly processes can be conditional on the phylogenetic resolution; yet most previous work quantifying their influence has focused on a single level of phylogenetic resolution. Here, we have studied the ecological assembly of bacterial communities from an Antarctic wetland complex, applying null models across different levels of phylogenetic resolution (i.e. clustering ASVs into OTUs with decreasing sequence identity thresholds). We found that the relative influence of the community assembly processes varies with phylogenetic resolution. More specifically, selection processes seem to impose stronger influence at finer (100% sequence similarity ASV) than at coarser (99%–97% sequence similarity OTUs) resolution. We identified environmental features related with the ecological processes and propose a conceptual model for the bacterial community assembly in this Antarctic ecosystem. Briefly, eco‐evolutionary processes appear to be leading to different but very closely related ASVs in lotic, lentic and terrestrial environments. In all, this study shows that assessing community assembly processes at different phylogenetic resolutions is key to improve our understanding of microbial ecology. More importantly, a failure to detect selection processes at coarser phylogenetic resolution does not imply the absence of such processes at finer resolutions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Interpolating Low Time-Resolution Forecast Data

Methodology that interpolates low time-resolution data (e.g., hourly) to high time-resolution (e.g., minutely) with variability patterns extracted from historical records. Magnitude of the variability inserted into the low time resolution data can be adjusted according to the installed capacity represented by the low time-resolution data compared to that by historical records. This approach enables detailed analysis of the impacts from wind and solar on power system intra-hour operations and balancing reserve requirements even with only hourly data. It also allows convenient creation of high resolution wind or solar generation data with various degree of variability to investigate their operational impacts. The methodology comprises of the following steps: 1. Smooth the historical data (set A) with an appropriate window length l to get its trend (set B); l can be a fraction of an hour (e.g., 15 minutes) or longer than an hour, of which the length of the variability patterns will be; 2. Extract the variable component (set C) of historical data by subtracting the smooth trend from it, i.e. set C = set A - set B 3. For each window length l of the variable component data set, find the average value x (will call it base component) of the corresponding window of the historical data set; 4. Define a series of segments (set D) that the values of data will be grouped into, e.g. (0, 0.1), (0.1, 0.2), ..., (0.9, 1.0) after normalization; Link each variability pattern to a data segment based on its corresponding base component x; after this step, each data segment should be linked to multiple variability patterns after this step; 5. Use spline function to interpolate the low time-resolution forecast data (set E) to become a high time-resolution smooth curve (set F); 6. Based on the window length l , calculate the average value y in each window length of set F; find the data segment that y belongs to; then randomly select one of the variability patterns linked to this data segment; 7. Add the selected variability pattern in each window to set F to get the high time-resolution data (set G) with variability observed from historical data set A; a coefficient k can be multiplied to the selected variability pattern to reflect the potential difference in variability between forecast set E and historical data set A caused by installation capacity and other factors. 8. After set G is constructed, variability statistics can be checked for set A and set G for comparison. Adjust the coefficient k if necessary to achieve desired variability in the reconstructed data.

Lu, Shuai↗

DOE OSTI2014

Exploratory High-Resolution Climate Simulations using the Community Atmosphere Model (CAM)

Extended, high-resolution (0.23° latitude × 0.31° longitude) simulations with Community Atmosphere Model versions 4 and 5 (CAM4 and CAM5) are examined and compared with results from climate simulations conducted at a more typical resolution of 0.9° latitude × 1.25° longitude. Overall, the simulated climate of the high-resolution experiments is not dramatically better than that of their low-resolution counterparts. Improvements appear primarily where topographic effects may be playing a role, including a substantially improved summertime Indian monsoon simulation in CAM4 at high resolution. Significant sensitivity to resolution is found in simulated precipitation over the southeast United States during winter. Some aspects of the simulated seasonal mean precipitation deteriorate notably at high resolution. Prominent among these is an exacerbated Pacific “double ITCZ” bias in both models. Nevertheless, while large-scale seasonal means are not dramatically better at high resolution, realistic tropical cyclone (TC) distributions are obtained. Some skill in reproducing interannual variability in TC statistics also appears.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Effects of Atmosphere and Ocean Horizontal Model Resolution on Tropical Cyclone and Upper-Ocean Response Forecasts in Four Major Hurricanes

A coupled atmosphere–ocean model is necessary for tropical cyclone (TC) prediction to accurately characterize ocean feedback on atmospheric processes within the TC environment. Here, the ECMWF coupled global model is run at horizontal resolutions from 9 to 1.4 km in the atmosphere, as well as 25 and 8 km in the ocean, to identify how resolution impacts forecast accuracy of four observed major TCs in the Atlantic: Irma, Florence, Teddy, and Ida. Most of the resolutions used here are unprecedented for global models. GOES-16 and synthetic aperture radar (SAR) satellite images and best track data are used for atmospheric validation. Salinity and temperature observations from Air-Launched Autonomous Micro-Observer (ALAMO) floats are used to validate modeled upper-ocean response, including mixed layer deepening, sea surface cooling, and near-inertial waves in the wakes of TCs. Increasing atmospheric resolution leads to more realistic TC structure and stronger winds, significantly improving TC intensity forecasts and modestly improving track errors. Ocean resolution impacts the upper-ocean response but does not influence atmospheric forecasts for the fast-moving TCs considered here. Stronger mixing, sea surface cooling, and near-inertial oscillations are found for both higher atmosphere and ocean resolutions, provided the initial upper-ocean state is the same for the two ocean resolutions. Whether this agrees better with the ALAMO observations also depends on the realism of the initial upper-ocean state in the model, emphasizing the importance of ocean initialization for the accurate upper-ocean response. Overall, the model at all resolutions correctly predicts stronger mixing, surface cooling, and near-inertial oscillation amplitudes to the right of a TC center, as observed by ALAMO floats.

Atmosphere-ocean interaction↗

DOE OSTI2019

Near-field Fourier ptychography: super-resolution phase retrieval via speckle illumination

High spatial resolution is the goal of many imaging systems. While designing a high-resolution lens with diffraction-limited performance over a large field of view remains a difficult task, creating a complex speckle pattern with wavelength-limited spatial features is easily accomplished with a simple random diffuser. With this observation and the concept of near-field ptychography, we report a new imaging modality, termed near-field Fourier ptychography, which is to be used for high-resolution imaging challenges in both microscopic and macroscopic imaging settings. 'Near-field' refers to placing the object at a short defocus distance with a large Fresnel number. We predict a speckle pattern with fine spatial features on the object instead of directly resolving the spatial features via a high-resolution lens. We then translate the object (or speckle) to different positions and acquire the corresponding images by using a low-resolution lens. A ptychographic phase retrieval process is used to recover the complex object, the unknown speckle pattern, and the coherent transfer function at the same time. In a microscopic imaging setup, we use a 0.12 numerical aperture (NA) lens to achieve an NA of 0.85 in the reconstruction process. In a macroscale photographic imaging setup, we achieve similar to 7-fold resolution gain by using a photographic lens. The collection optics do not determine the final achievable resolution; rather, the speckle pattern's feature size does. This is similar to our recent demonstration in fluorescence imaging settings (Guo et al., Biomed. Opt. Express , 9(1), 2018). The reported imaging modality can be utilized in light, coherent X-ray, and transmission electron imaging systems to increase resolution and provide quantitative absorption and object phase contrast.

42 ENGINEERING↗