Present Weather Detector / Raw Data
The present weather detector data provide NWS weather type and codes and visibility metrics. These data would be helpful to easily detect fog over the barge.
17 WIND ENERGY↗
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Present Weather Detector / Raw Data
The present weather detector data provide NWS weather type and codes and visibility metrics. These data would be helpful to easily detect fog over the barge.
17 WIND ENERGY↗
Present Weather Detector / Processed Data
The present weather detector data provide NWS weather type and codes and visibility metrics. These data would be helpful to easily detect fog over the barge.
17 WIND ENERGY↗
Using Machine Learning Algorithm to Detect Blowing Snow and Fog in Antarctica Based on Ceilometer and Surface Meteorology Systems
Blowing snow is a common weather phenomenon in Antarctica and plays an important role in the water vapor cycle and ice sheet mass balance. Although it has a significant impact on the climate of Antarctica, people do not know much about this process. Fog events are difficult to distinguish from blowing snow events using existing detection algorithms by a ceilometer. In this study, based on ceilometer, the meteorological parameters observed by surface meteorology systems are further combined to detect blowing snow and fog using the AdaBoost algorithm. The weather phenomena recorded by human observers are ‘true’. The dataset is collected from 1 January 2016 to 31 December 2016 at the AWARE site. Among them, three-quarters of the data are used as the training set and the rest of the data as the testing set. The classification accuracy of the proposed algorithm for the testing set is about 94%. Compared with the Loeb method, the proposed algorithm can detect 89.12% of blowing snow events and 76.10% of fog events, while the Loeb method can only identify 64.29% of blowing snow events and 31.87% of fog events.
54 ENVIRONMENTAL SCIENCES↗
Snowmass2021 Cosmic Frontier Dark Matter Direct Detection to the Neutrino Fog
We present a summary of future prospects for direct detection of dark matter within the GeV/c2 to TeV/c2 mass range. This is paired with a new definition of the neutrino fog in order to better quantify the rate of diminishing returns on sensitivity due to irreducible neutrino backgrounds. A survey of dark matter candidates predicted to fall within this mass range demonstrates that fully testing multiple well-motivated theo-ries will require expanding the currently-funded generation of experiments down to and past the neutrino fog. We end with the status and plans for next-generation exper-iments and novel R&D concepts which will get us there.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Recoil imaging for dark matter, neutrinos, and physics beyond the Standard Model
Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Discovering the Higgsino at CTAO-North within the Decade
We demonstrate that higgsino dark matter (DM) could be discovered within the next few years using the Cherenkov Telescope Array Observatory's soon-to-be-operational northern site (CTAO-North). A 1.1 TeV thermal higgsino is a highly motivated yet untested model of DM. Despite its strong theoretical motivation in supersymmetry and beyond, the higgsino is notoriously difficult to detect; it lies deep within the neutrino fog of direct detection experiments and could pose a challenge even for a future muon collider. We show that, in contrast, higgsino detection could be possible within this decade with CTAO-North in La Palma, Spain. The Galactic Center is the region where the dominant DM annihilation signature emerges, but it only barely rises above the horizon at the CTAO-North site. However, we project that this challenge can be overcome with large-zenith-angle observations at the northern site, enabling the conclusive detection of a higgsino signal by 2030 for a range of DM density profiles in the inner Galaxy.
Cosmology and Nongalactic Astrophysics (astro-ph.C↗
Incorporating the effects of objects in an approximate model of light transport in scattering media
A computationally efficient radiative transport model is presented that predicts a camera measurement and accounts for the light reflected and blocked by an object in a scattering medium. The model is in good agreement with experimental data acquired at the Sandia National Laboratory Fog Chamber Facility (SNLFC). The model is applicable in computational imaging to detect, localize, and image objects hidden in scattering media. Here, a statistical approach was implemented to study object detection limits in fog.
42 ENGINEERING↗
Blowing Snow at McMurdo Station, Antarctica During the AWARE Field Campaign: Surface and Ceilometer Observations
Blowing snow (BLSN) is an impactful process in cold climates, affecting regional thermodynamics, radiation properties, and the surface mass balance of snow. Though it has significant climatic impacts, the process is still poorly understood and not widely included in weather and climate models. In 2016, the AWARE Field Campaign saw the deployment of a large suite of in situ and remote sensing instruments to McMurdo Station, Antarctica allowing for investigation of BLSN. A ceilometer–based BLSN detection algorithm used elsewhere in Antarctica is applied to data from AWARE, yielding a BLSN frequency of 14.1% compared to 8.2% as detected by human observers. To increase confidence in detections, the algorithm is updated to have shorter temporal averaging and to include a variety of meteorological thresholds to limit false detections due to fog. Efforts to incorporate a laser disdrometer into the algorithm were unsuccessful. An unphysical dependence of particle size distributions on wind speed is found suggesting observations are problematic at wind speeds greater than 10 m s –1 . The revised algorithm detected a BLSN frequency of 7.4%, increasing agreement with human observations and confidence that the process is actively occurring at the observation site. Furthermore, these observations are put into context of a climatology of human observations of BLSN at McMurdo station from 2002–2018. An annual average of 8.0%–14.0% is estimated, with a total annual range of 3.4%–21.3%. Regardless of whether BLSN is observed by humans or instrument, the majority of cases at this location are associated with ongoing precipitation.
54 ENVIRONMENTAL SCIENCES↗
CROCUS Dual Polarization Ceilometer Data at Northeastern Illinois University Rooftop
This dataset is from the Department of Energy Office of Science funded project, CROCUS Urban Integrated Field Laboratory (https://crocus-urban.org/). The dual-polarization ceilometer (Vaisala CL61) is an autonomous lidar system operating at 910 nm wavelength, providing valuable measurements for understanding atmospheric boundary layer evolution, air quality, and cloud-aerosol interactions. The CL61 measures the backscattered signal intensity alternating between parallel- and cross-polarization signals. The unique depolarization measurement capability improves discrimination between different particle types, such as liquid droplets, ice crystals, and aerosols. The depolarization is highly dependent on the scatterer shape and orientation (spherical vs non-spherical particles), with the linear depolarization ratio providing a measure of dominant backscatter signal component from atmospheric particles at various heights, essentially allowing discrimination between liquid and solid particles. With its efficient optical system, CL61’s improved signal-to-noise ratio compared to traditional ceilometers allows studying detailed vertical profiles of aerosols and clouds up to 15 km height.Datasets are stored in a netCDF data format, and we we encourage users to make use of the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.
54 ENVIRONMENTAL SCIENCES↗
Quality assurance and quality control of the $26~\text {m}^2$ SiPM production for the DarkSide-20k dark matter experiment
DarkSide-20k is a novel liquid argon dark matter detector currently under construction at the Laboratori Nazionali del Gran Sasso (LNGS) of the Istituto Nazionale di Fisica Nucleare (INFN) that will push the sensitivity for Weakly Interacting Massive Particle (WIMP) detection into the neutrino fog. The core of the apparatus is a dual-phase Time Projection Chamber (TPC), filled with 50 tonnes of low radioactivity underground argon (UAr) acting as the WIMP target. NUV-HD-cryo Silicon Photomultipliers (SiPM)s designed by Fondazione Bruno Kessler (FBK) (Trento, Italy) were selected as the photon sensors covering two $10.5~\text {m}^2$ Optical Planes, one at each end of the TPC, and a total of $5~\text {m}^2$ photosensitive surface for the liquid argon veto detectors. This paper describes the Quality Assurance and Quality Control (QA/QC) plan and procedures accompanying the production of FBK NUV-HD-cryo SiPM wafers manufactured by LFoundry s.r.l. (Avezzano, AQ, Italy). SiPM characteristics are measured at 77 K at the wafer level with a custom-designed probe station. As of March 2025, 1314 of the 1400 production wafers (94% of the total) for DarkSide-20k were tested. The wafer yield is $93.2\pm 2.5$%, which exceeds the 80% specification defined in the original DarkSide-20k production plan.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Amazonian fog harbors viable microbes
Fog formation over tropical forests remains poorly characterized, despite its potential role in bioaerosol dispersion and ecosystem processes. Here, we analyzed fog samples collected at the Amazon Tall Tower Observatory using flow cytometry and culture-based techniques to characterize viable microbial communities. Microbial cell concentrations varied over an order of magnitude across 13 fog events, reaching up to 8 × 104 cells per ml of fog water. Flow cytometry consistently detected metabolically active cells, while culturing and mass spectrometry-based identification yielded eight viable bacterial species and seven fungal taxa. The bacteria Serratia marcescens, Ralstonia pickettii and Sphingomonas paucimobilis exhibited seasonal variations in prevalence. The fungal species identified were primarily mesophilic saprophytes and endophytes, commonly associated with soil and plant surfaces. Our findings indicate that fog harbors viable microbes, including Serratia marcescens and Ralstonia pickettii, which may imply a relevance of fog for microbial dispersal, colonization and nutrient cycling in the Amazon rainforest.
Godoi, Ricardo H. (ORCID:0000000247744870)↗
Testing the dark side of neutrino oscillations with the solar neutrino fog at dark matter experiments
The recent detection of the solar neutrino background at dark matter direct detection experiments paves the way to fully explore an important degeneracy in neutrino oscillations in the presence of new interactions, named the LMA-Dark degeneracy. This degeneracy makes it impossible to determine the neutrino mass ordering in oscillation experiments if neutrinos have new vectorial interactions with matter. As the composition of solar neutrinos at the Earth consists of all three neutrino flavors, testing the presence of new neutrino interactions in the muon and tau neutrino sector in scatterings can fully probe the LMA-Dark region for the first time. In this paper we show that current data from XENONnT and PandaX-4T do not yet exclude the LMA-Dark region with equal couplings of a new mediator to muon and tau neutrinos and quarks, and we identify the possible experimental scenarios to do so in the future. We also show that dark matter experiments can distinguish new interactions in the muon or tau sector only from new interactions affecting both sectors.
Particle interactions↗
Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)
Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.
58 GEOSCIENCES↗
Hydroxymethanesulfonate (HMS) Formation during Summertime Fog in an Arctic Oil Field
Hydroxymethanesulfonate (HMS) is produced in the aqueous-phase reaction of formaldehyde (HCHO) and sulfur dioxide (SO 2 ) and has been proposed as a significant contributor to midlatitude wintertime pollution events. In this work, we report HMS detection within submicrometer atmospheric aerosols during frequent late summer, regional fog events in an Arctic oil field. The number fraction of individual particles containing HMS increased during fog periods, consistent with aqueous-phase formation. The single-particle mass spectra showed the primary particle signature (oil field emissions), plus secondary oxidized organics and sulfate, consistent with aqueous-phase processing. HMS mass concentrations ranged from below the ion chromatography limit of detection (0.3 ng/m 3 ) to 1.6 ng/m 3 , with sulfate concentrations of 37-222 ng/m 3 . HCHO and SO 2 measurements suggest that the fog HMS production rate is ~10 times higher in the oil fields than in the upwind Beaufort Sea. Aqueous-phase reactions of local oil field emissions during frequent summertime regional fog events likely have downwind impacts on Arctic aerosol composition. The potential for fog-based HMS production was estimated to be an order of magnitude higher in Fairbanks and Anchorage, AK, than in the oil fields and may explain the missing organosulfate source contributing to Fairbanks air quality.
54 ENVIRONMENTAL SCIENCES↗
Electroweak loop contributions to the direct detection of wino dark matter
Electroweak loop corrections to the matrix elements for the spin-independent scattering of cold dark matter particles on nuclei are generally small, typically below the uncertainty in the local density of cold dark matter. However, as shown in this paper, there are instances in which the electroweak loop corrections are relatively large, and change significantly the spin-independent dark matter scattering rate. An important example occurs when the dark matter particle is a wino, e.g., in anomaly-mediated supersymmetry breaking (AMSB) and pure gravity mediation (PGM) models. We find that the one-loop electroweak corrections to the spin-independent wino LSP scattering cross section generally interfere constructively with the tree-level contribution for AMSB models with negative Higgsino mixing, μ < 0, and in PGM-like models for both signs of μ, lifting the cross section out of the neutrino fog and into a range that is potentially detectable in the next generation of direct searches for cold dark matter scattering.
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