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At least 775 records · Page 43

Dependence of Energetic Storm Particle Heavy Ion Peak Intensities and Spectra on Source CME Longitude and Speed

We examine variations in energetic storm particle (ESP) heavy ion peak intensities and energy spectra at CME-driven interplanetary shocks. We focus on their dependence with heliolongitude relative to the source region of their associated CMEs, and with CME speed, for events observed in Solar Cycle 24 at the STEREO-A, STEREO-B, and/or ACE spacecraft. We find that observations of ESP events at 1 au are organized by longitude relative to their CME solar source. The ESP event longitude distribution also showed organization with CME speed. The near-Sun CME speeds (V i ) for these events ranged from ∼560 to 2650 km s −1 while the average CME transit speeds to 1 au were significantly slower. The angular width of the events had a clear threshold at V i of ∼1300 km s −1 , above which events showed significantly larger angular extension compared to events with speeds below. High-speed events also showed larger heavy ion peak intensities near the nose of the shock compared to the flanks while their spectral index was smaller near the nose and larger near the flanks. This organization for events with V i < 1300 km s −1 was not as clear. These ESP events were observed over a narrower range of longitudes though the heavy ion peak intensities still appeared largest near the nose of the shock. Their heavy ion spectra showed no clear organization with longitude. These observations highlight the impact of spacecraft position relative to the CME source longitude and Vi on the properties of ESP events at 1 au.

Solar energetic particles↗

SQuaD: Smart Quantum Detection for Photon Recognition and Dark Count Elimination

Quantum detectors of single photons are an essential component for quantum information processing across computing, communication and networking. Today's quantum detection system, which consists of single photon detectors, timing electronics, control and data processing software, is primarily used for counting the number of single photon detection events. However, it is largely incapable of extracting other rich physical characteristics of the detected photons, such as their wavelengths, polarization states, photon numbers, or temporal waveforms. This work, for the first time, demonstrates a smart quantum detection system, SQuaD, which integrates a field programmable gate array (FPGA) with a neural network model, and is designed to recognize the features of photons and to eliminate detector dark-count. The SQuaD is a fully integrated quantum system with high timing-resolution data acquisition, onboard multi-scale data analysis, intelligent feature recognition and extraction, and feedback-driven system control. Our \name experimentally demonstrates 1) reliable photon counting on par with the state-of-the art commercial systems; 2) high-throughput data processing for each individual detection events; 3) efficient dark count recognition and elimination; 4) up to 100% accurate feature recognition of photon wavelength and polarization. Additionally, we deploy the SQuaD to an atomic (erbium ion) photon emitter source to realize noise-free control and readout of a spin qubit in the telecom band, enabling critical advances in quantum networks and distributed quantum information processing.

Linne, Karl C. [U. Chicago (main)] (ORCID:00090009↗

Simulation of Hurricane Harvey flood event through coupled hydrologic-hydraulic models: Challenges and next steps

Using the 2017 Hurricane Harvey flood event as a test case, this study set up a series of sensitivity analyses to highlight three challenges associated with large-scale flood inundation modeling, including (a) model parameterization, (b) errors in digital elevation models, and (c) effects of reservoir retention. Driven by radar-based hourly rainfall data, a series of hydrologic-hydraulic models including the VIC hydrologic model, RAPID routing model, and Flood2D-GPU hydrodynamic model are set up over Harris County, Texas, to simulate flood inundation and hazards. The results demonstrate the importance of hydrologic parameters in improving flood modeling. For a large flood event such as Hurricane Harvey, the effect of the initial water depths is insignificant. The Manning's n values may increase the peak water depth by ~1%, the flood extents by 65km 2 , and the high danger zone by ~6%. On the contrary, the bathymetry correction factors may reduce the flood extent by ~1.4% and the high-danger zone by ~4%. Reducing the reservoir storage capacity to 1% may increase the flood extent by ~4% and the high-danger zone by ~17%. This study may provide supporting information to guide and prioritize the development of future high-performance computing hydrodynamic large-scale flood simulations.

54 ENVIRONMENTAL SCIENCES↗

Aera-Mip: Emission Pathways, Remaining Budgets, and Carbon Cycle Dynamics Compatible With 1.5 and 2 °C Global Warming Stabilization

While international climate policies now focus on limiting global warming to well below 2 °C or pursuing a 1.5 °C level of global warming, the climate modelling community has not provided an experimental design in which all Earth system models (ESMs) converge and stabilize at the same prescribed global warming levels. This gap hampers accurate estimations based on comprehensive ESMs of the carbon emission pathways and budgets needed to meet such agreed warming levels and of the associated climate impacts under temperature stabilization. Here, we apply the Adaptive Emission Reduction Approach (AERA) with ESMs to provide such simulations in which all models converge at 1.5 and 2.0 °C warming levels by adjusting their emissions over time. These emission-driven simulations provide a wide range of emission pathways and resulting atmospheric CO 2 projections for a given warming level, uncovering uncertainty ranges that were previously missing in the traditional Coupled Model Intercomparison Project (CMIP) scenarios with prescribed greenhouse gas concentration pathways. Meeting the 1.5 °C warming level requires a 40 % (full model range: 7 % to 76 %) reduction in multi-model mean CO 2 -forcing-equivalent (CO 2 -fe) emissions from 2025 to 2030, a 98 % (57 % to 127 %) reduction from 2025 to 2050, and a stabilization at 1.0 (−1.7 to 2.9) PgC yr−1 from 2100 onward after the 1.5 °C global warming level is reached. Meeting the 2.0 °C warming level requires a 47 % (8 % to 92 %) reduction in multi-model mean CO 2 -fe emissions until 2050 and a stabilization at 1.7 (−1.5 to 2.7) PgC yr−1 from 2100 onward. The on-average positive emissions under stabilized global temperatures are the result of a decreasing transient climate response to cumulative CO 2 -fe emissions over time under stabilized global warming. This evolution is consistent with a slightly negative zero emissions commitment – initially assumed to be zero – and leads to an increase in the post-2025 CO 2 -fe emission budget by a factor of 2.2 (−0.8 to 6.9) by 2150 for the 1.5 °C warming level and a factor of 1.4 (0.9 to 2.4) for the 2.0 °C warming level compared to its first estimate in 2025. The median CO 2 -only carbon budget by 2150, relative to 2020, is 800 GtCO 2 for the 1.5 °C warming level and 2250 GtCO 2 for the 2.0 °C warming level. These median values exceed the median IPCC AR6 estimates by 60 % for the 1.5 °C warming level and 67 % for 2.0 °C. Some of the differences may be explained by the choice of the mitigation scenario for non-CO 2 radiative agents. Our simulations highlight shifts in carbon uptake dynamics under stabilized temperature, such as a cessation of the carbon sinks in the North Atlantic and in tropical forests. On the other hand, the Southern Ocean remains a carbon sink centuries after temperatures stabilize. Overall, this new type of warming-level-based emission-driven simulation offers a more coherent assessment across climate models and opens up a wide range of possibilities for studying both the carbon cycle and climate impacts, such as extreme events, under climate stabilization.

Adaptive Emission Reduction Approach↗

Old Faithful Model for Radiolytic Gas-Driven Cryovolcanism at Enceladus

A new model is presented on how chemically driven cryovolcanism might contribute to episodic outgassing at the icy moon Enceladus and potentially elsewhere including Europa and Kuiper Belt Objects. Exposed water ices can become oxidized from radiolytic chemical alteration of near-surface water ice by space environment irradiation. In contact with primordially abundant reductants such as NH3, CH4, and other hydrocarbons, the product oxidants can react exothermically to produce volatile gases driving cryovolcanism via gas-piston forces on any subsurface liquid reservoirs. Radiolytic oxidants such as H2O2 and O2 can continuously accumulate deep in icy regoliths and be conveyed by rheological flows to subsurface chemical reaction zones over million-year time scales indicated by cratering ages for active regions of Enceladus and Europa. Surface blanketing with cryovolcanic plume ejecta would further accelerate regolith burial of radiolytic oxidants. Episodic heating from transient gravitational tides, radioisotope decay, impacts, or other geologic events might occasionally accelerate chemical reaction rates and ignite the exothermic release of cumulative radiolytic oxidant energy. The time history for the suggested "Old Faithful" model of radiolytic gas-driven cryovolcanism at Enceladus and elsewhere therefore consists of long periods of chemical energy accumulation punctuated by much briefer episodes of cryovolcanic activity. The most probable sequence for detection of activity in the current epoch is a long evolutionary phase of slow but continuous oxidant accumulation over billions of years followed by continuous but variable high activity over the past 10(exp 7)-10(exp 8) years. Detectable cryovolcanic activity could then later decline due to near-total oxidation of the rheologically accessible ice crust and depletion the accessible reductant abundances, as may have already occurred for Europa in the more intense radiation environment of Jupiter's magnetosphere. Astrobiological potential of Enceladus could correspondingly be higher than at Europa due to a less extreme state of oxidation and greater residual abundance of organics.

Cooper, John F.↗

Online-compatible unsupervised nonresonant anomaly detection

There is a growing need for anomaly detection methods that can broaden the search for new particles in a model-agnostic manner. Most proposals for new methods focus exclusively on signal sensitivity. However, it is not enough to select anomalous events—there must also be a strategy to provide context to the selected events. In this work, we propose the first complete strategy for unsupervised detection of nonresonant anomalies that includes both signal sensitivity and a data-driven method for background estimation. Our technique is built out of two simultaneously trained autoencoders that are forced to be decorrelated from each other. This method can be deployed off-line for nonresonant anomaly detection and is also the first complete on-line-compatible anomaly detection strategy. We show that our method achieves excellent performance on a variety of signals prepared for the ADC2021 data challenge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observation of Forward Neutron Multiplicity Dependence of Dimuon Acoplanarity in Ultraperipheral Pb-Pb Collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

The first measurement of the dependence of $γγ → μ^+μ^–$ production on the multiplicity of neutrons emitted very close to the beam direction in ultraperipheral heavy ion collisions is reported. Data for lead-lead interactions at $\sqrt{s_{NN}}$ = 5.02 TeV, with an integrated luminosity of approximately 1.5 nb –1 , are collected using the CMS detector at the LHC. The azimuthal correlations between the two muons in the invariant mass region 8 < $m_{μμ}$ < 60 GeV are extracted for events including 0, 1, or at least 2 neutrons detected in the forward pseudorapidity range |η| > 8.3. The back-to-back correlation structure from leading-order photon-photon scattering is found to be significantly broader for events with a larger number of emitted neutrons from each nucleus, corresponding to interactions with a smaller impact parameter. This observation provides a data-driven demonstration that the average transverse momentum of photons emitted from relativistic heavy ions has an impact parameter dependence. These results provide new constraints on models of photon-induced interactions in ultraperipheral collisions. They also provide a baseline to search for possible final-state effects on lepton pairs caused by traversing a quark-gluon plasma produced in hadronic heavy ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Predicting Seafloor Seismic Noise from Sea Surface Wave Heights and Vice Versa

Seismic hazard monitoring and global seismic tomography efforts are improved by recording seismic signals close to sources and at a variety of azimuths surrounding the source. While seismic networks have been deployed at many locations on land, seafloor stations are still sparse. Inclusion of ocean-based data would greatly improve the global coverage of seismic networks. However, the use of seafloor seismic data to complement land-based detection and characterization of events is complicated by the fact that ambient noise on the seafloor is in general much higher than noise levels on land. This noise is driven primarily by sea surface waves and tides. In this project, I define an empirical relationship between wave height and seafloor seismic displacement, and tie this relationship to the microseism noise theory of Longuet-Higgins and Ursell (1948). I find that while there appears to be a linear relationship between wave height and seismic displacement, wave height values can only be used with low confidence to predict seismic displacement and vice versa, and furthermore, factors other than wave height are significant in determining the level of seismic noise at a particular site.

58 GEOSCIENCES↗

Community-Engaged Modeling of Urban Flood Adaptation Pathways

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Spangler, Ava [Pennsylvania State University] (ORC↗

Community-Informed Urban Flood Modeling for Impact Mitigation

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Baltimore MD↗

A new source of suprathermal O(+) ions near the dayside polar cap boundary

A large number of data on suprathermal O(+) ions taken during the retarding ion mass spectrometer (RIMS) experiment aboard the DE 1 satellite are surveyed. Examples are found of low-energy, upflowing O(+) which are consistent with one or more of the proposed ionospheric escape mechanisms. These include transversely accelerated O(+) ions, indicating low-altitude transverse acceleration, and O(+) field-aligned flows which indicate low-altitude parallel acceleration by either ambipolar or current-driven electric fields. However, by far the most common pitch angle distribution of escaping O(+) is found to be a new type of O(+) flow event which provides evidence for both perpendicular and parallel ion acceleration below the satellite and is found exclusively in the lower latitudes of the dayside polar cap. All species of ions are observed to move upward during these events, with an upward heat flux.

Lockwood, M.↗

The geo-control system for station keeping and colocation of geostationary satellites

GeoControl is a compact but powerful and accurate software system for station keeping of single and colocated satellites, which has been developed at the German Space Operations Center. It includes four core modules for orbit determination (including maneuver estimation), maneuver planning, monitoring of proximities between colocated satellites, and interference and event prediction. A simple database containing state vector and maneuver information at selected epochs is maintained as a central interface between the modules. A menu driven shell utilizing form screens for data input serves as the central user interface. The software is written in Ada and FORTRAN and may be used on VAX workstations or mainframes under the VMS operating system.

Montenbruck, O.↗

Dependence of Wave-Breaking Statistics on Wind Stress and Wave Development

Incidence of wave breaking for pure wind driven waves has been studied on Lake Washington at wind speeds up to 8 m/s. Video recordings were employed to identify and categorize the breaking events in terms of micro-scale, spilling and plunging breakers. These events were correlated with the magnitude of the wave spectrum measured with a resistance wire wave gauge and band pass filtered between 6 and 10 Hz. An equivalent percentage of breaking crests were found for spilling and plunging events. Wave forcing as measured by wind stress (or friction velocity, u(sub *), squared) and by inverse wave age, u(sub *)/Cp where Cp is the phase velocity of the waves at the peak of the frequency spectrum, were found to be good prerictors of percentage of breaking crests. When combined in a two parameter regression, those two variables gave small standard deviation and had a high correlation coefficient (66 percent). The combination of u(sub *)(exp 2) and u(sub *)/Cp can be understood in physical terms. Furthermore, for the larger values of u(sub *)(exp 2) the dependence of wave braking and wave age was stronger than at the low end of the values u(sub *)(exp 2) and u(sub *)/Cp. Thus, both the level of wave development as determined by inverse wave age, which we may term relative wind effectiveness for wave forcing and the wind forcing on the water surface determine the incidence of wave breaking. Substituting U(sub 10)(sup 3.75) (which is the dependence of whitecap cover found by Monahan and coworkers) an equivalent correlation was found to the prediction by u(sub *)(exp 2). Slightly better standard deviation value and higher correlation coefficient were found by using a Reynolds number as predictor. A two-parameter regression involving u(sub *)(exp 2) and a Reynold's number proposed by Toba and his colleagues which relates u(sub *)(exp 2) and peak wave frequency, improves the correlation even more but is less easy to interpret in physical terms. The equivalent percentage of breaking crests obtained in our previous study was reported at 8.6 percent for a short record obtained at U(sub 10N) of about 6 m/s. Typical values in the current study for similar conditions are 6 percent, which is consistent with the previous study in view of the scatter. In that study we did not have a video recording system, so the observed breaking may include more of the micro-scaic breaking events, and the value, 8.6 percent, is well within the range of highly probable sampling variability.

Katsaros, Kristina B.↗

Using Black Hole Mergers to Explore Structure Formation

Observations of gravitational waves from massive black hole mergers will open a new window into the era of structure formation in the early universe. Past efforts have concentrated on calculating merger rates using different physical assumptions, resulting in merger rate estimates that span a wide range (0.1 - 1 0A4 mergers/year). We develop a semi-analytical, phenomenological model of massive black hole mergers that includes plausible combinations of several physical parameters, which we then turn around to determine how well observations with the Laser Interferometer Space Antenna (LISA) will be able to enhance our understanding of the universe during the critical z approx. 5 - 30 epoch. Our approach involves generating synthetic LISA observable data (total BH masses, BH mass ratios, redshifts, merger rates), which are then analyzed using a Markov Chain Monte Carlo method, thus finding constraints for the physical parameters of the mergers. We find that our method works well at estimating merger parameters and that the number of merger events is a key discriminant among models, therefore making our method robust against observational uncertainties. Our approach can also be extended to more physically-driven models and more general problems in cosmology.

Alicea-Munoz, E.↗

Using Black Hole Mergers to Explore Structure Formation

Observations of gravitational waves from massive black hole mergers will open a new window into the era of structure formation in the early universe. Past efforts have concentrated on calculating merger rates using different physical assumptions, resulting in merger rate estimates that span a wide range (0.1 - 10(exp 4) mergers/year). We develop a semi-analytical, phenomenological model of massive black hole mergers that includes plausible combinations of several physical parameters, which we then turn around to determine how well observations with the Laser Interferometer Space Antenna (LISA) will be able to enhance our understanding of the universe during the critical z approximately equal to 5-30 epoch. Our approach involves generating synthetic LISA observable data (total BH masses, BH mass ratios, redshifts, merger rates), which are then analyzed using a Markov Chain Monte Carlo method, thus finding constraints for the physical parameters of the mergers. We find that our method works well at estimating merger parameters and that the number of merger events is a key discriminant among models, therefore making our method robust against observational uncertainties. Our approach can also be extended to more physically-driven models and more general problems in cosmology. This work is supported in part by the Cooperative Education Program at NASA/GSFC.

Alicea-Munoz, E.↗

Fine-Scale Features of the Sun's Atmosphere: Spicules and Jets

We present an overview of fine-scale features in the Sun’s atmosphere, with a focus on spicules and jets. We consider older and newer observations and theories for chromospheric spicules and coronal jets. We also consider the connection between these features and some other solar atmospheric phenomena. We then discuss the possibility that there is a continuum of jet-like features ranging from spicules to large-scale CME-producing eruptions, all driven by similar magnetic processes operating on differing corresponding size scales. Future observational and theoretical studies will help clarify further the nature of these solar events, and elucidate possible connections between them.

Sterling, Alphonse C.↗

Tree-Ring Reconstruction of the Atmospheric Ridging Feature that Causes Flash Drought in the Central United States Since 1500

Rapid drought intensification, or flash droughts, is often driven by anomalous atmospheric ridging and can cause severe and complex impacts on water availability and agriculture, but the full range of variability of such events in terms of intensity and frequency is unknown. New tree-ring reconstructions of May–July mid-tropospheric ridging and soil moisture anomalies back to 1500 CE in the central United States — a hotspot for flash drought — suggest that over the last five centuries, anomalies in these two variables combined to indicate flash-drought conditions in ~17% of years and exceptionally severe flash drought in ~4% of years, similar to frequencies in recent decades. However, over one-third of all inferred exceptional flash droughts occurred since 1900, suggesting the 20th century was highly flash-drought prone. These results may guide future work to diagnose the roles of external, oceanic, and land-surface forcing of warm-season atmospheric circulation and hydroclimate over North America.

Flash Drought↗

Volcanic Climate Warming through Radiative and Dynamical Feedbacks of SO2 Emissions

Volcanic flood basalt eruptions have been linked to or are contemporaneous with major climate disruptions, ocean anoxic events, and mass extinctions throughout at least the last 400M years of Earth’s history. Previous studies and recent history have shown that volcanically-driven climate cooling can occur through reflection of sunlight by H2SO4 aerosols, while longer-term climate warming can occur via CO2 emissions. We use the Goddard Earth Observing System Chemistry- Climate Model to simulate a four-year duration volcanic SO2 emission of the scale of the Wapshilla Ridge member of the Columbia River Basalt eruption. Brief cooling from H2SO4 aerosols is outweighed by dynamically and radiatively driven warming of the climate through a three orders of magnitude increase in stratospheric H2O vapor.

Scott D Guzewich↗