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DOE OSTI2024

Trends and meteorological drivers of extreme daily reservoir evaporation events in the western United States

Extreme daily evaporation from reservoir surfaces can lead to significant short-term water losses, affecting water quality, water supply, and reservoir operation strategies. Historical trends in daily reservoir evaporation events have eluded the scientific and operational communities, largely due to a lack of long-term, consistent data record. This study quantifies trends in extreme daily reservoir evaporation events at 165 major reservoirs located in the western U.S. Here, we use the place-based energy balance and aerodynamic Daily Lake Evaporation Model (DLEM) driven by multiple meteorological data products (RTMA, gridMET, Daymet) to estimate daily evaporation rates at these reservoirs from 1981 to 2022. The results—while are based on different meteorological forcing datasets—consistently indicate that the California, Lower Colorado, and Rio Grande hydrologic regions are more prone to higher daily evaporation extremes. Compared to the rest of western U.S, these three regions also experience a more pronounced increasing trend in the annual maximum daily evaporation rate, at about 0.3 mm day -1 decade -1 during 1981-2022. The results show that heat and dryness are the main drivers to the increasing trend of extreme evaporation, while extreme wind speed is the primary contributor to exceptionally high daily evaporation events across all regions. This phenomenon is particularly prominent in the arid Lower Colorado region, but less significant in the cold and humid Pacific Northwest region. We also find that the correlation between extreme wind speed and extreme evaporation degrades as the time scale increases from daily, to monthly and seasonal. Our findings have strong implications for the pattern and distribution of extreme evaporation events at the western U.S. reservoirs, and illustrate how various drivers influence extreme evaporation across different time scales.

13 HYDRO ENERGY↗

DOE OSTI2026

Implementation of a Three-Dimensional Planetary Boundary Layer Parameterization in a Coupled Modeling System and Evaluation of "Gray Zone" Simulations of a Wind-Wave Event Off the US California Coast Using Observations

A three-dimensional (3D) planetary boundary layer (PBL) parameterization was added to the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) model and the first coupled atmosphere/wave "gray zone" simulations were carried out using the 3D PBL parameterization. A case study of a significant wind-wave event from 4-8 November 2020 off the US west coast was examined, with a focus on the impacts of the event within an approximate 280x280 km central California coastal region covering the Bureau of Ocean Energy Management Morro Bay wind energy lease area. Simulations with both one-dimensional (1D; Yonsei University) and 3D PBL parameterizations were examined in this nest with ..delta..x=400 m. Two-way coupling was active, with near-surface winds feeding back to the wave model and bulk wave statistics feeding back to the atmospheric model. Both simulations compared favorably with buoy observations in capturing the timing and magnitude of wind speed, temperature, dewpoint, and significant wave height, as the front associated with the maritime weather system moved southward across coastal California. However, wind speed errors over land were larger. Time series of the vertical profile of winds below z=250 m from the simulations compared favorably with observations from the US Dept. of Energy Morro Bay Doppler lidar buoy. Differences between the coupled 1D and 3D PBL simulations were minor. The most notable difference was that the simulation using the 3D PBL parameterization had approximately 10 % weaker winds at the peak of the event causing 10 % lower significant wave heights. This difference was shown to be mostly due to differences in the vertical mixing treatment between the parameterizations, in particular the nonlocal downward mixing of higher momentum air in the 1D Yonsei University parameterization in convective conditions. Overall, this work demonstrates that the 3D PBL parameterization can be used in a coupled atmosphere/wave modeling framework with similar behaviors as traditional PBL parameterizations that do not provide horizontal turbulent variances and fluxes.

16 TIDAL AND WAVE POWER↗

NASA NTRS2024

Central California Disasters: Incorporating Satellite-Derived Precipitation and Soil Moisture Products into Flood Preparedness and Emergency Management in California

Atmospheric rivers are a major contributor to extreme precipitation events and flooding in California. This study assessed the feasibility of using Earth observation data to monitor precipitation, soil moisture, and flooding from atmospheric rivers in the Salinas River Watershed in central California during the winter of 2022-2023. The team analyzed satellite derived precipitation estimates from the Global Precipitation Measurement mission, soil moisture data from the Soil Moisture Active Passive radiometer, and synthetic aperture radar imagery from Sentinel-1 to detect flood inundation. Global Precipitation Measurement precipitation estimates were found to underestimate rainfall by 33% to 52% compared to rain gauge data. The team found the Soil Moisture Active Passive dataset to be a valuable flooding indicator that they could visualize through various graphical representations, although its accuracy still needs verification with in situ flood maps. Sentinel-1 synthetic aperture radar imagery provided mapping of flood inundation extent along the Salinas River and surrounding areas and the Blue Spot model appears to be a good predictor of pluvial flood zones. The findings suggest Earth observations can enhance precipitation and flooding monitoring by the California Department of Water Resources, though further verification is needed. Integration of these datasets with vulnerability indices highlighted communities at highest risk during the 2022-2023 flooding events.

Abhinav Banthiya↗

NASA NTRS2012

Future Gamma-Ray Imaging of Solar Eruptive Events

Solar eruptive events, the combination of large solar flares and coronal mass ejections (CMEs), accelerate ions to tens of Gev and electrons to hundreds of MeV. The energy in accelerated particles can be a significant fraction (up to tens of percent) of the released energy and is roughly equipartitioned between ions and electrons. Observations of the gamma-ray signatures produced by these particles interacting with the ambient solar atmosphere probes the distribution and composition of the accelerated population, as well as the atmospheric parameters and abundances of the atmosphere, ultimately revealing information about the underlying physics. Gamma-ray imaging provided by RHESSI showed that the interacting approx.20 MeV/nucleon ions are confined to flare magnetic loops rather than precipitating from a large CME-associated shock. Furthermore, RHESSI images show a surprising, significant spatial separation between the locations where accelerated ions and electrons are interacting, thus indicating a difference in acceleration or transport processes for the two types of particles. Future gamma-ray imaging observations, with higher sensitivity and greater angular resolution, can investigate more deeply the nature of ion acceleration. The technologies being proven on the Gamma-Ray Imager/Polarimeter for Solar flares (GRIPS), a NASA balloon instrument, are possible approaches for future instrumentation. We discuss the GRIPS instrument and the future of studying this aspect of solar eruptive events.

Shih, Albert↗

NASA NTRS1984

The 19 March 1982 Eruption and Lahar at Mount Saint Helens: Implications for Martian Outlfow Channels?

A small explosive eruption of Mount St. Helens set into motion an unusually complex series of geomorphic and hydrologic processes that had not previously been described in the literature. This event was unusual in that a laterally-directed eruption dislodged and mobilized a thick snowpack from the surrounding crater floor and walls, resulting in the formation of a temporary lake. Catastrophic release of this self-impounded lake spawned a series of destructive debris avalanches and debris flows that moved rapidly down the volcano's north flank and into the North Toutle River valley. Catastrophic release of volatiles mobilized by volcanic activity has been discussed as a possible mechanism to explain a class of outflow channels on Mars. The eruption of Mount St. Helens provides a unique opportunity to study the deposits and landforms created by such an event; a more detailed field study and examination of Viking photographs of martian outflow channels is underway.

Beach, G. L.↗

DOE OSTI2024

Modification of charged-particle jets in event-shape engineered Pb–Pb collisions at $\sqrt{S_{NN}}$ = 5.02 TeV

Charged-particle jet yields have been measured in semicentral Pb–Pb collisions at center-of-mass energy per nucleon–nucleon collision $\sqrt{S_{NN}}$ = 5.02 TeV with the ALICE detector at the LHC. These yields are reported as a function of the jet transverse momentum, and further classified by their angle with respect to the event plane and the event shape, characterized by ellipticity, in an effort to study the path-length dependence of jet quenching. Jets were reconstructed at midrapidity from charged-particle tracks using the anti-k T algorithm with resolution parameters R = 0.2 and 0.4, with event-plane angle and event-shape values determined using information from forward scintillating detectors. The results presented in this letter show that, in semicentral Pb–Pb collisions, there is no significant difference between jet yields in predominantly isotropic and elliptical events. However, out-of-plane jets are observed to be more suppressed than in-plane jets. Further, this relative suppression is greater for low transverse momentum (< 50 GeV/c) R = 0.2 jets produced in elliptical events, with out-of-plane to in-plane jet-yield ratios varying up to 5.2σ between different event-shape classes. These results agree with previous studies indicating that jets experience azimuthally anisotropic suppression when traversing the QGP medium, and can provide additional constraints on the path-length dependence of jet energy loss.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

The Next-Generation Ecosystem Experiment Arctic Rainfall Simulator: a tool to understand the effects of changing rainfall patterns in the Arctic

Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R 2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Stellar flares from blended and neighbouring stars in Kepler short cadence observations

ABSTRACT We present the results of a search for stellar flares from stars neighbouring the target sources in the Kepler short cadence data. These flares have been discarded as contaminants in previous surveys and therefore provide an unexplored resource of flare events, in particular high-energy events from faint stars. We have measured M dwarf flare energies up to 1.5 × 1035 erg, pushing the limit for flare energies measured using Kepler data. We have used our sample to study the flaring activity of wide binaries, finding that the lower mass counterpart in a wide binary flares more often at a given energy. Of the 4430 flares detected in our original search, 298 came from a neighbouring star, a rate of 6.7 ± 0.4 per cent for the Kepler short cadence light curves. We have used our sample to estimate a 5.8 ± 0.1 per cent rate of false positive flare events in studies using Transiting Exoplanet Survey Satellite short cadence data.

Jackman, James A. G.↗

DOE OSTI2023

Integrated deep learning framework for unstable event identification and disruption prediction of tokamak plasmas

Abstract The ability to identify underlying disruption precursors is key to disruption avoidance. In this paper, we present an integrated deep learning (DL) based model that combines disruption prediction with the identification of several disruption precursors like rotating modes, locked modes, H-to-L back transitions and radiative collapses. The first part of our study demonstrates that the DL-based unstable event identifier trained on 160 manually labeled DIII-D shots can achieve, on average, 84% event identification rate of various frequent unstable events (like H-L back transition, locked mode, radiative collapse, rotating MHD mode, large sawtooth crash), and the trained identifier can be adapted to label unseen discharges, thus expanding the original manually labeled database. Based on these results, the integrated DL-based framework is developed using a combined database of manually labeled and automatically labeled DIII-D data, and it shows state-of-the-art (AUC = 0.940) disruption prediction and event identification abilities on DIII-D. Through cross-machine numerical disruption prediction studies using this new integrated model and leveraging the C-Mod, DIII-D, and EAST disruption warning databases, we demonstrate the improved cross-machine disruption prediction ability and extended warning time of the new model compared with a baseline predictor. In addition, the trained integrated model shows qualitatively good cross-machine event identification ability. Given a labeled dataset, the strategy presented in this paper, i.e. one that combines a disruption predictor with an event identifier module, can be applied to upgrade any neural network based disruption predictor. The results presented here inform possible development strategies of machine learning based disruption avoidance algorithms for future tokamaks and highlight the importance of building comprehensive databases with unstable event information on current machines.

plasma instabilities↗

NASA NTRS2018

Validation of the Nasa Integrated Medical Model: a Space Flight Medical Risk Prediction Tool

The Human Research Program funded the development of the Integrated Medical Model (IMM) to quantify the medical component of overall mission risk. The IMM uses Monte Carlo simulation methodology, incorporating space flight and ground medical data, to estimate the probability of mission medical outcomes and resource utilization. To determine the credibility of IMM output, the IMM project team completed two validation studies that compared IMM predicted output to observed medical events from a selection of Shuttle Transportation System (STS) and International Space Station (ISS) missions. The validation study results showed that the IMM underpredicted the occurrence of ~10% of the modeled medical conditions for the STS missions and overpredicted ~20% of the modeled medical conditions for the ISS missions. These findings imply that the strength of IMM predictions to inform decisions depends on simulated mission specifications including length. This discrepancy could result from medical recording differences between ISS and STS that possibly influence observed incidence rates, IMM combining all "mission type" data as constant occurrence rate or fixed proportion across both mission types, misspecification of symptoms to conditions, and gaps in the literature informing the model. Some of these issues will be alleviated by updating the IMM source data through incorporation of the observed validation data.

medical equipment↗

NASA NTRS2018

Validation of the NASA Integrated Medical Model: a Space Flight Medical Risk Prediction Tool

risk assessment↗

DOE OSTI2023

Climate science to inform adaptation policy: Heat waves over India in the 1.5°C and 2°C warmer worlds

Developing a better scientific understanding of anthropogenic climate change and climate variability, especially the prediction/projection of climate futures with useful temporal and geographical resolution and quantified uncertainties, and using that knowledge to inform adaptation planning and action will become crucially important in the coming years. Generating such policy-relevant knowledge may be particularly important for developing countries such as India. It is with this backdrop that, in this paper, we analyze future heat waves in India by using observations and a large number of model simulations of historical, + 1.5 °C, and + 2.0 °C warmer worlds. In both the future scenarios, there is an increased probability of heat waves during June and July when the Indian monsoon is in full swing and humidity is high, which makes the heat events even more of a health risk. While the highest temperatures in heat waves may not increase much in future climates, the duration and areal extent of the heat waves will most likely increase, leading to the emergence of new heat wave-prone zones in India. The results indicate that the joint frequencies of the longest duration and large area events could be nearly threefold greater in the + 1.5 °C and fivefold greater in the + 2.0 °C future scenarios compared to historical simulations. Thus, overall, the study indicates a substantial increase in the risk of heat events that typically elicit warnings from forecasters. The likely widespread and persistent nature of heat wave events in the future, as revealed by this study, will require planning and adaptation measures beyond the short-term disaster planning frameworks currently in place. Exploring what these measures might look like is beyond the scope of this study, but it underlines the importance of developing climate knowledge with high temporal and geographical resolution capable of informing adaptation policy and planning.

+1.5 °C and +2.0 °C↗

DOE OSTI2025

Evidence of medium response to hard probes using correlations of Z bosons with hadrons in heavy ion collisions

The first measurement of pseudorapidity and azimuthal angle distributions relative to the momentum vector of a Z boson for low transverse momentum ($p_\mathrm{T}$) charged hadrons in lead-lead (PbPb) collisions is presented. By studying the hadrons produced in an event with a high-$p_\mathrm{T}$ Z boson (40 $\lt$ $p_\mathrm{T}$ $\lt$ 350 GeV), the analysis probes how the quark-gluon plasma (QGP) medium created in these collisions affects the parton recoiling opposite to the Z boson. Utilizing PbPb data at a nucleon-nucleon center-of-mass energy $\sqrt{s_{_\mathrm{NN}}}$ = 5.02 TeV from 2018 with an integrated luminosity of 1.67 nb$^{-1}$ and proton-proton (pp) data at the same energy from 2017 with 301 pb$^{-1}$, the distributions are examined in bins of charged-hadron $p_\mathrm{T}$. A significant modification of the distributions for charged hadrons in the range 1 $\lt$ $p_\mathrm{T}$ $\lt$ 2 GeV in PbPb collisions is observed when compared to reference measurements from pp collisions. The data provide new information about the correlation between hard and soft particles in heavy ion collisions, which can be used to test predictions of various jet quenching models. The results are consistent with expectations of a hydrodynamic wake created when the QGP is depleted of energy by the parton propagating through it. Based on comparisons of PbPb data with pp references and predictions from theoretical models, this Letter presents the first evidence of medium-recoil and medium-hole effects caused by a hard probe.

CMS↗

DOE OSTI2023

Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the estimated performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant to aspects of detector design including particle identification, charge information, and minimum transverse momentum capabilities. Additionally, we study the impact of using full event information instead of using only information associated with the identified jet. These methods can be deployed either on suitably accurate Monte Carlo event generators, or, for several applications, directly on experimental data. We provide an outlook for ultimately connecting these machine learning-based methods with first principles calculations in quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

The resilience value of residential solar + storage systems in the continental U.S.

Abstract Behind the meter rooftop solar plus storage (PVESS) has the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Whereas the bill reduction and environmental benefits of PVESS are well studied, its monetary resilience benefits are less understood. The increasing trend of power interruptions driven by extreme weather events heightens the need to understand these benefits. This study leverages various publicly available datasets to perform a cost benefit analysis of adding to determine the resilience value of PVESS for a typical single family home in each county in the continental U.S. We find that PVESS is very effective to technically mitigate interruptions across the country. However, the monetary benefits in the base case only cover about 14% of battery costs, with no county exceeding 60%. This is somewhat expected, given that PVESS provide other monetary benefits that are not part of this analysis. Through sensitivities, we find that higher frequency of extreme weather events roughly triples the resilience value of PVESS and that higher values of lost load double the same metric. Our sensitivity analysis shows that the benefit cost ratio of PVESS for customers living in areas with higher-than-average frequency of long duration interruptions and value of lost load is already above one even without considering other value streams. We conclude with recommendations that regulators and utilities could implement to enable customers to calculate and capture the resilience value of PVESS more efficiently.

Baik, Sunhee↗

DOE OSTI2020

Pitch Angle Dependence of Electron and Ion Flux Changes During Local Magnetic Dipolarization Inside Geosynchronous Orbit

In this study we have statistically examined flux changes of 1–1,000-keV electrons, and hydrogen, helium, and oxygen ions during local magnetic dipolarization inside geosynchronous orbit, with a focus on their pitch angle dependence. Here, using 144 dipolarization events that were selected in a previous study with Van Allen Probes observations in 2012–2016, we have performed a superposed epoch analysis of differential flux changes after the dipolarization onset for each species. On average the electron flux increases primarily around pitch angle (α) = 90° at >80 keV and almost isotropically at 10–50 keV. The electron flux at <5 keV increases at α = 0° and 180° but slightly decreases (or remains unchanged) at α = 90°. On the other hand, the ion flux at >80 keV increases around α = 90°, while at <30 keV it decreases nearly independent of pitch angle. Only the low-energy (<5 keV) helium and oxygen ion flux changes indicate a strong field-aligned enhancement, which could be attributed to their outflows from the topside ionosphere. After the dipolarization onset, >5-keV electron and >30-keV ion fluxes exhibit a perpendicular anisotropy, which is most pronounced for 50–200-keV electrons. Both distributions become more isotropic with decreasing energy. A noticeable field-aligned anisotropy is seen for <5-keV ion fluxes. These statistical pitch angle-dependent electron and ion properties during dipolarizations may be explained by combining various processes, including adiabatic acceleration and/or transport, wave-particle interactions, and ion outflow.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Coherent $\mathrm{J}/\psi $ and ψ photoproduction at midrapidity in ultra-peripheral Pb–Pb collisions at $\sqrt{s_{\mathrm {NN}}}~=~5.02$ TeV

The coherent photoproduction of J/ψ and ψ' mesons was measured in ultra-peripheral Pb–Pb collisions at a center-of-mass energy $\sqrt{s_{\mathrm {NN}}}~=~5.02$ TeV with the ALICE detector. Charmonia are detected in the central rapidity region for events where the hadronic interactions are strongly suppressed. The J/ψ is reconstructed using the dilepton (l + l - ) and proton–antiproton decay channels, while for the ψ' the dilepton and the l + l - π + π - decay channels are studied. The analysis is based on an event sample corresponding to an integrated luminosity of about 233 μb -1 . The results are compared with theoretical models for coherent J/ψ and ψ' photoproduction. The coherent cross section is found to be in a good agreement with models incorporating moderate nuclear gluon shadowing of about 0.64 at a Bjorken-x of around 6×10 -4 , such as the EPS09 parametrization, however none of the models is able to fully describe the rapidity dependence of the coherent J/ψ cross section including ALICE measurements at forward rapidity. The ratio of ψ' to J/ψ coherent photoproduction cross sections was also measured and found to be consistent with the one for photoproduction off protons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2022

A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across U.S. lakes

Cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state’s risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the Cyanobacteria Index (CI(cyano)). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CI(cyano) detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CI(cyano) was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater (r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.

remote sensing↗