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At least 37 records · Page 2

Revealing the Formation of the <20 MeV Inner Proton Radiation Belt at L ∼ 2 During the 10–11 May 2024 Superstorm

A new proton radiation belt was identified during the geomagnetic superstorm of 10–11 May 2024. To investigate its origin, we use an MHD-test particle simulation to model solar energetic proton (SEP) trapping and the evolution of the initial trapped proton population during the storm. The simulation weights the injected SEP population with interplanetary proton measurements and the initial trapped proton radial profile with energy-resolved Weather System Follow-on-Microwave (WSF-M) proton data, enabling quantitative comparison with observations. Results show that SEP contributions are minimal; the new ∼2–18 MeV belt at L ∼ 2 forms mainly through redistribution and energization of the initial trapped population within hours of the CME shock, driven by subsequent electric field impulses, rather than the initial shock alone. These results provide quantitative evidence based on realistic, plasma-dependent field dynamics and significantly advance understanding of inner radiation belt formation.

79 ASTRONOMY AND ASTROPHYSICS↗

Examination of Radiation Belt Dynamics During Substorm Clusters: Activity Drivers and Dependencies of Trapped Flux Enhancements

Here, dynamical variations of radiation belt trapped electron fluxes are examined to better understand the variability of enhancements linked to substorm clusters. Analysis is undertaken using the Substorm Onsets and Phases from Indices of the Electrojet substorm cluster algorithm for event detection. Observations from low earth orbit are complemented by additional measurements from medium earth orbit to allow a major expansion in the energy range considered, from medium energy energetic electrons up to ultra-relativistic electrons. The number of substorms identified inside a cluster does not depend strongly on solar wind drivers or geomagnetic indices either before, during, or after the cluster start time. Clusters of substorms linked to moderate (100 nT < AE ≤ 300 nT) or strong AE (AE ≥ 300 nT) disturbances are associated with radiation belt flux enhancements, including up to ultra-relativistic energies by the strongest substorms (as measured by strong southward Bz and high AE). These clusters reliably occur during times of high speed solar winds streams with associated increased magnetospheric convection. However, substorm clusters associated with quiet AE disturbances (AE ≤ 100 nT) lead to no significant chorus whistler mode intensity enhancements, or increases in energetic, relativistic, or ultra-relativistic electron flux in the outer radiation belts. In these cases the solar wind speed is low, and the geomagnetic Kp index indicates a lack of magnetospheric convection. Our study clearly indicates that clusters of substorms occurring outside of high speed wind streams are not by themselves sufficient to drive acceleration, which may be due to the lack of pre-cluster convection.

79 ASTRONOMY AND ASTROPHYSICS↗

PreMevE Update: Forecasting Ultra-Relativistic Electrons Inside Earth's Outer Radiation Belt

Energetic electrons inside Earth's Van Allen belts pose a major radiation threat to spaceborne electronics that often play vital roles in modern society. Ultra-relativistic electrons with energies greater than or equal to two megaelectron-volt (MeV) are of particular interest, and thus forecasting these ≥2 MeV electrons has a significant meaning to all space sectors. Here, we update the latest development of the predictive model for MeV electrons in the outer radiation belt. The new version, called PREdictive MEV Electron (PreMevE)-2E, forecasts ultra-relativistic electron flux distributions across the outer belt, with no need for in situ measurements of the trapped MeV electron population except at the geosynchronous orbit (GEO). Model inputs include precipitating electrons observed in low-Earthorbits by NOAA satellites, upstream solar wind speeds and densities from solar wind monitors, as well as ultra-relativistic electrons measured by one Los Alamos GEO satellite. We evaluated 32 supervised machine learning models that fall into four different classes of linear and neural network architectures, and successfully tested ensemble forecasting by using groups of top-performing models. All models are individually trained, validated, and tested by in situ electron data from NASA's Van Allen Probes mission. It is shown that the final ensemble model outperforms individual models at most L-shells, and this PreMevE-2E model can provide 25-h (~1-day) and 50-h (~2-day) forecasts with high mean performance efficiency and correlation values. Our results also suggest that this new model is dominated by nonlinear components at L-shells <~4 for ultra-relativistic electrons, different from the dominance of linear components for 1 MeV electrons as previously discovered.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling the Effects of Drift Orbit Bifurcation on Radiation Belt Electrons

Abstract Drift orbit bifurcation (DOB) has been suggested to play a major role in the loss and transport of radiation belt electrons since it violates the second adiabatic invariants of particles and makes the third invariant undefined. Results from our guiding‐center test particle simulations using the Tsyganenko‐1989c magnetic field model show that the DOB could affect a broad region of the outer radiation belt, which can penetrate inside the geosynchronous orbit at Kp ≥ 3, and its effects are more significant further away from the Earth, at a higher Kp and for higher electron energies. Specifically, the short‐term simulation results after one electron drift show both traditional and nontraditional DOB transport of electrons, with the nontraditional DOB, caused by a third minimum of the magnetic field strength near the equator, reported here for the first time. Moreover, our results show large ballistic jumps in the second invariant and radial distance for electrons at high equatorial pitch angles after one drift. In addition, long‐term DOB transport coefficients of electrons over many drifts are calculated based on our simulation results. We find that the pitch angle and radial diffusion coefficients of electrons due to DOB could be comparable to or even larger than those caused by electron interactions with chorus and Ultra‐Low‐Frequency waves, respectively. In sum, our results demonstrate that DOB could cause effective loss and transport of radiation belt electrons even in the absence of waves.

Astronomy & Astrophysics↗

Oscillating surge wave energy converter using a novel above-water power takeoff with belt-arc speed amplification

We investigate the performance of a novel power takeoff (PTO) featuring belt-arc speed amplification for oscillating surge wave energy converters (OSWECs), aiming to address the challenges of extremely low rotary speed and large torque under the low-frequency ocean wave excitations. The belt-arc design significantly increases the rotary speed of the generator, enabling generator downsizing and decreasing the powertrain friction losses. The design also allows for placing the generator above water, eliminating the need for high Ingress Protection ratings for the generator and powertrain, and potentially leading to substantial reductions in capital and maintenance costs. Using the linear potential wave theory, the dynamics of the integrated system are analyzed, and key parameters are identified. To validate the numerical analysis, a 1:10 scale model is designed, fabricated, and tested in a wave tank. Performance evaluations are conducted under regular and irregular wave conditions, with quantified effects of parameter tuning. The results reveal an optimal wave-to-electric efficiency of 48% under regular wave excitation and 20% under irregular excitation. Furthermore, these findings underscore the effectiveness of the proposed novel PTO design in addressing the challenges of low rotation speed and large torque inherent in OSWECs, demonstrating its ability to efficiently convert wave power into electricity.

16 TIDAL AND WAVE POWER↗

A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ~ 82%) and physiological information (i.e. physiological SIF yield, Φ F , 17% ~ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Φ F indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that Φ F responded to the proxy for physiological stress (partial correlation coefficient, r p = 0.40, p < 0.001) while non-physiological signals of SIF did not respond ( p > 0.1). The field-scale Φ F data showed water deficit stress from the comparison between irrigated and rainfed fields, and Φ F was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r = 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Φ F was more strongly correlated spatially with air temperature and VPD ( r = 0.23 and 0.39) than SIF ( r = 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Φ F reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Φ F is spatially scalable. Utilizing Φ F for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.

54 ENVIRONMENTAL SCIENCES↗

Modeling of the cold electron plasma density for radiation belt physics

This review focusses strictly on existing plasma density models, including ionospheric source models, empirical density models, physics-based and machine-learning density models. This review is framed in the context of radiation belt physics and space weather codes. The review is limited to the most commonly used models or to models recently developed and promising. A great variety of conditions is considered such as the magnetic local time variation, geomagnetic conditions, ionospheric source regions, radial and latitudinal dependence, and collisional vs. collisionless conditions. These models can serve to complement satellite observations of the electron plasma density when data are lacking, are for most of them commonly used in radiation belt physics simulations and can improve our understanding of the plasmasphere dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗

Radiation Belt Response to Fast Reverse Shock at Geosynchronous Orbit

Fast reverse shocks (FRSs) cause the magnetosphere to expand, by contrast to the well-known compressions caused by the impact of fast forward shocks (FFS). Usually, FFSs are more geoeffective than FRSs, and consequently the inner magnetosphere dynamic responses to both shock types can be quite different. In this study, we investigate for the first time the radiation belt response to an FRS impact using multi-satellite observations and numerical simulations. Spacecraft on the dayside observed decreases in magnetic field strength and energetic (~40–475 keV) particle fluxes. Timing analysis shows that the magnetic field signature propagated from the dayside to the nightside magnetosphere. Particles with different energies vary simultaneously at each spacecraft, implying a non-dispersive particle response to the shock. Spacecraft located at lower L-shells did not record any significant signatures. The observations indicate a local time dependence of the response associated with the shock inclination, with the clearest signatures being observed in the dusk–midnight sector. Simulations underestimate the amplitude of the magnetic field variations observed on the nightside. The observed decreases in the electron intensities result from a combination of radial gradient and adiabatic effects. The radial gradients in the spectral index appear to be the dominant contributor to the observed variations of electrons seen on the dayside (near noon and dusk) and on the nightside (near midnight). This work shows that even an FRS can affect the radiation belts significantly and provides an opportunity to understand their dynamic response to a sudden expansion of the magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling the Effects of Drift Orbit Bifurcation on the Magnetopause Shadowing Loss of Radiation Belt Electrons

Abstract Last closed drift shell (LCDS) has been identified as a crucial parameter for investigating the magnetopause shadowing loss of radiation belt electrons. However, drift orbit bifurcation (DOB) effects have not been physically incorporated into the LCDS calculation. Here we calculate event‐specific LCDS using different approaches to dealing with the DOB effects, that is, tracing field lines ignoring DOB, tracing test particles rejecting field lines with DOB, and tracing particles including field lines with DOB, and then incorporate them into a radial diffusion model to simulate the fast electron dropout observed by Van Allen Probes in May 2017. The model effectively captures the fast dropout at high L* and exhibits the best agreement with data when LCDS is calculated by tracing test particles with DOB more physically included. This study represents the first quantitative modeling of the DOB effects on radiation belt magnetopause shadowing loss via a more physical specification of LCDS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simulating Long–Term Dynamics of Radiation Belt Electrons Using DREAM3D Model

Here, we compared the performance of DREAM3D simulations in reproducing the long-term radiation belt dynamics observed by Van Allen Probes over the entire year of 2017 with various boundary conditions (BCs) and model inputs. Specifically, we investigated the effects of three different outer boundary conditions, two different low-energy boundary conditions for seed electrons, four different radial diffusion (RD) coefficients (DLL), four hiss wave models, and two chorus wave models from the literature. Using the outer boundary condition driven by GOES data, our benchmark simulation generally well reproduces the observed radiation belt dynamics inside L* = 6, with a better model performance at lower μ than higher μ, where μ is the first adiabatic invariant. By varying the boundary conditions and inputs, we find that: (a) The data-driven outer boundary condition is critical to the model performance, while adding in the data-driven seed population doesn't further improve the performance. (b) The model shows comparable performance with DLL from Brautigam and Albert (2000, https://doi.org/10.1029/1999ja900344), Ozeke et al. (2014, https://doi.org/10.1002/2013ja019204), and Liu et al. (2016, https://doi.org/10.1002/2015gl067398), while with DLL from Ali et al. (2016, https://doi.org/10.1002/2016ja023002) the model shows less RD compared to data. (c) The model performance is similar with data-based hiss models, but the results show faster loss is still needed inside the plasmasphere. (d) The model performs similarly with the two different chorus models, but better capturing the electron enhancement at higher μ using the Wang et al. (2019, https://doi.org/10.1029/2018ja026183) model due to its stronger wave power, since local heating for higher energy electrons is under-reproduced in the current model.

79 ASTRONOMY AND ASTROPHYSICS↗

Very-Low-Frequency transmitters bifurcate energetic electron belt in near-earth space

Very-Low-Frequency (VLF) transmitters operate worldwide mostly at frequencies of 10–30 kilohertz for submarine communications. While it has been of intense scientific interest and practical importance to understand whether VLF transmitters can affect the natural environment of charged energetic particles, for decades there remained little direct observational evidence that revealed the effects of these VLF transmitters in geospace. Here we report a radially bifurcated electron belt formation at energies of tens of kiloelectron volts (keV) at altitudes of ~0.8–1.5 Earth radii on timescales over 10 days. Using Fokker-Planck diffusion simulations, we provide quantitative evidence that VLF transmitter emissions that leak from the Earth-ionosphere waveguide are primarily responsible for bifurcating the energetic electron belt, which typically exhibits a single-peak radial structure in near-Earth space. Since energetic electrons pose a potential danger to satellite operations, our findings demonstrate the feasibility of mitigation of natural particle radiation environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Upper troposphere dust belt formation processes vary seasonally and spatially in the Northern Hemisphere

Dust aerosols impact global energy balance substantially by acting as efficient ice nuclei to alter cold cloud properties. However, the estimate of dust indirect effect remains uncertain due to simulating dust distributions poorly and lacking reliable dust observations, especially in the upper-troposphere. Here, we characterize and understand upper-troposphere dust sources and transport with an improved dust dataset derived from A-train satellite lidar and radar measurements and an air parcel trajectory model. The distinct upper-troposphere dust belt over the northern hemisphere has seasonally varying base and top heights of 3.65 ± 2.84 and 8.35 ± 1.50 km above mean sea level and its column loading is strongest during spring (March-April-May). The out-of-phase annual cycles of mid-level dust concentration and westerly wind over source regions control the seasonal upper-tropospheric dust loading variations. African deserts contribute the most (46.3%) to the upper-troposphere dust belt in spring and the synoptic trough is the leading (49%) dust lifting mechanism.

54 ENVIRONMENTAL SCIENCES↗

Fabrication of freeform potassium dihydrogen phosphate crystals by belt-on-wheel polishing for spatially tailored polarization control in high-power lasers

Large-aperture (>30 cm) optical components that provide spatially tailored control of the properties of a laser beam, such as phase, polarization, and amplitude, have been the focus of much research and development in recent years. Such optics can improve energy throughput and target implosion efficiency in high-power laser systems conducting inertial confinement fusion research. Here, a method is demonstrated for fabricating freeform surface topographies into the birefringent crystalline material, potassium dihydrogen phosphate (KDP). Belt-on-wheel polishing with an oil-based fluid, developed to mitigate the deliquescent properties of KDP, is used to deterministically polish a freeform topography into KDP, enabling the fabrication of a wave plate with spatially arbitrary retardance. Testing of the laser-induced damage threshold of belt-on-wheel polished KDP was conducted at a wavelength of 351 nm and a pulse duration of 1 ns. The results revealed that the polished surfaces are highly resistant to laser-induced damage, making them suitable for large-aperture, high-power laser applications.

Urban, Nathaniel D. [Univ. of Rochester, NY (Unite↗

Field-scale dynamics of planting dates in the US Corn Belt from 2000 to 2020

Crop planting dates are a dynamic feature of agricultural systems that respond to short- and long-term climate signals, crop and cultivar selection, and technology changes. Planting date records are essential for yield gap analyses, accurate crop modeling, and tracking farmer adaptations to weather and climate change. Although planting dates have high variation at local scales due to heterogeneity in farm resources and decision-making, available long-term data on planting dates is largely restricted to aggregated regional statistics or, at best, satellite-derived datasets with limited spatiotemporal extent and at resolutions unable to distinguish individual fields (> 250 m). Here, we generated retrospective annual field-scale (30 m) planting date maps for both maize and soybeans spanning 2000-2020 across a 12 state region in the United States Corn Belt based on Landsat satellite data and a large ground sample of over 28,000 maize and soybean fields. Using training data from 2015-2020 for model selection, we found that planting date predictions improved with harmonic regression of Landsat data and additional annual weather covariates. The preferred random forests model approximately doubled performance compared to a null model based on state median planting dates, capturing 47% of field-level variation for maize (mean absolute error, MAE = 7.4 days) and 44% for soybeans (MAE = 7.5 days) against held-out ground truth test data for 2008-2014. We also evaluated the full 2000-2020 dataset with state agricultural statistics, finding strong agreement with median planting dates for maize (R 2 = 0.76, MAE = 4.4 days) and slightly lower agreement for soybeans (R 2 = 0.65, MAE = 5.4 days) when aggregated to the state level. We then used this new dataset to analyze environmental determinants of planting dates at a finer-scale than previously possible, controlling for unobserved variation at the sub-state district level. We found that during 2000-2020, each standard deviation increase in rainfall delayed planting by ~ 2.5 days, and fields with higher soil productivity ratings tended to be planted earlier. We did not find meaningful trends over the last two decades in planting dates for maize or soybeans, in contrast to trends towards earlier planting dates late last century and predicted for this period in climate adaptation studies. We hypothesize increases in early season rainfall may have inhibited these shifts towards earlier planting. Remotely sensed planting dates will be a useful tool for yield gap analyses, crop simulation modeling, and ongoing assessment of climate adaptation.

54 ENVIRONMENTAL SCIENCES↗

Inner Belt Electron Decay Timescales: A Comparison of Van Allen Probes and DREAM3D Losses Following the June 2015 Storm

Abstract NASA's Van Allen Probes observed significant, long‐lived fluxes of inner belt electrons up to ∼1 MeV after geomagnetic storms in March and June 2015. Reanalysis of Magnetic Electron Ion Spectrometer (MagEIS) data with improved background correction showed a clearer picture of the relativistic electron population that persisted through 2016 and into 2017 above the Fennell et al. (2015, https://doi.org/10.1002/2014gl062874 ) limit. The intensity and duration of these enhancements allow estimation of decay timescales for comparison with simulated decay rates and theoretical lifetimes. We compare decay timescales from these data and DREAM3D simulations based on them using geomagnetic activity‐dependent pitch angle diffusion coefficients derived from plasmapause‐indexed wave data (Malaspina et al., 2016, https://doi.org/10.1002/2016gl069982 , 2018, https://doi.org/10.1029/2018gl078564 ) and phase space densities derived from MagEIS observations. Simulated decay rates match observed decay rates more closely than the theoretical lifetime due to significantly nonequilibrium pitch angle distributions in simulation and data. We conclude that nonequilibrium effects, rather than a missing diffusion or loss process, account for observed short decay rates.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantifying nitrogen loss hotspots and mitigation potential for individual fields in the US Corn Belt with a metamodeling approach

The high productivity in the US Corn Belt is largely enabled by the consumption of millions of tons of manufactured fertilizer. Excessive application of nitrogen (N) fertilizer has been pervasive in this region, and the unrecovered N eventually escaped from croplands in forms of nitrous oxide (N 2 O) emission and N leaching. Mitigating these negative impacts is hindered by a lack of practical information on where to focus and how much mitigation potential to expect. At a large scale, process-based crop models are the primary tools for predicting variables required by decision making, but their applications are prohibited by expensive computational and data storage costs. To overcome these challenges, we built a series of metamodels to learn the key mechanisms regarding the carbon (C) and N cycle from a well-validated process-based biogeochemical model, ecosys. The trained metamodel captures over 98% of the variability of the ecosys simulated outputs for 99 randomly selected counties in Iowa, Illinois, and Indiana. To identify hotspots with high mitigation potential, we introduce net societal benefit (NSB) as an indicator for synthesizing the loss in yield and social benefits through emissions and pollutants avoided. Our results show that reducing N fertilizer by 10% leads to 9.8% less N 2 O emissions and 9.6% less N leaching at the cost of 4.9% more SOC depletion and 0.6% yield reduction over the study region. The estimated total annual NSB is $\$395$ M (uncertainty ranges from $\$114$ M to $\$1271$ M), including $\$334$ from social benefits (uncertainty ranges from $\$46$ M to $\$1076$ M), $\$100$ M from saving fertilizer (uncertainty ranges from $\$13$ M to $\$455$ M), and –$\$40$ M due to yield changes (uncertainty ranges from –$\$261$ M to $\$69$ M). For the median scenario, we noted that 20% of the study area accounts for nearly 50% of the NSB, and thus represent hotspot locations for targeted mitigation. Although the uncertainty range suggests that developing such a high-resolution framework is not yet settled and the scenario based estimations are not appropriate to inform the management practices for individual farmers, our efforts shed light on the new generation of analytical tools for life cycle assessment.

54 ENVIRONMENTAL SCIENCES↗

Further adoption of conservation tillage can increase maize yields in the western US Corn Belt

Conservation tillage can reduce soil erosion, increase soil health, and decrease labor and fuel input costs. Despite these benefits, potential yield impacts remain an important concern for farmers considering adoption. Previous research suggests that conservation tillage is likely to have the largest yield benefits in more arid conditions, but a lack of field-level analyses across climatic, management and soil conditions limits confidence in such predictions. Satellite imagery provides the opportunity to monitor agricultural lands at sub-field resolution across large spatial scales and wide environmental gradients. Here we investigate the maize yield impacts of conservation tillage in the semi-arid western US Corn Belt, using sub-field resolution datasets on tillage practices and crop yields derived from satellite data spanning four states (Nebraska, Kansas, South Dakota, and North Dakota) between 2008 and 2020. On these datasets, we estimate heterogenous yield outcomes for several thousand maize fields across gradients in climate, soil quality and irrigation status by using a causal forests analysis, an adaptation of the random forests machine-learning algorithm for causal inference on observational data. We find that long-term adoption of conservation tillage increased rainfed maize yields by an average of 9.9% in the region. Impacts on irrigated yields were small and not statistically significant. These results, along with an analysis of variables related to greater than average yield benefits, indicate that improved water infiltration and retention are the primary reasons for conservation tillage benefits. Despite yield benefits, many fields estimated to see increased yields under long term low till have not adopted the practice. Therefore, we identify specific counties likely to benefit most from increased levels of adoption. Our results strengthen the understanding of the impacts of conservation agriculture on crop yields and help define environments and counties most likely to benefit from conservation tillage.

54 ENVIRONMENTAL SCIENCES↗