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At least 361 records · Page 20

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↗

Optimizing invader suppression to restore native species: Leveraging species traits to overcome collateral damage

Strategies to control ongoing biological invasions are often developed by modelling the invasive species' population and aiming to reduce its abundance. However, if the ultimate objective is to protect and restore native species, focussing solely on the invader may not be optimal because it does not account for (i) species interactions that can cause the invader's impacts to depend nonlinearly on its abundance, (ii) collateral damages to native species incurred due to nonspecific removal methods or (iii) native-invader trait differences. Here, to identify an invader suppression strategy that maximizes average native population size, we applied optimal control theory to a two-species model of a native species threatened by an invasive competitor. We examined trade-offs between iterative physical removals that selectively target invaders and intensifiable chemical control that is nonselective but has higher efficacy. We found that while iterative removals were capable of supporting large native populations when applied continuously, cost could be prohibitively high. In contrast, when favourable native-invader trait differences enabled native species to re-establish more quickly than invaders, intensifiable methods could achieve substantial restoration benefits at lower cost by focussing removal effort into periodic, high-efficacy events. In a metapopulation, removals that rotated among spatial patches were optimal when the native species had higher dispersal, whereas synchronous removals were preferred when native recovery was initiated locally and the invader could disperse. For a case study in Hawaiian streams, we compared how effective two alternative methods of removing invasive live-bearing fishes (poeciliids) might be at restoring the endemic freshwater goby Sicyopterus stimpsoni. We found that rotenone (a piscicidal chemical) offered superior benefits when the control budget was small and efficacy was high, but that electrofishing (use of electricity to manually collect target fish) was better with larger budgets and in many lower-efficacy scenarios. Synthesis and applications. Our findings demonstrate that, by accounting for species interactions and collateral damage, invasive species control strategies can be optimized in light of species traits. Choices about the timing, locations and types of removal events present opportunities to increase the efficiency with which invasive species suppression benefits native species.

54 ENVIRONMENTAL SCIENCES↗

GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.

Mach, Douglas M.↗

[Columbia Sensor Diagrams]

A two dimensional graphical event sequence of the time history of relevant sensor information located in the left wing and wheel well areas of the Space Shuttle Columbia Orbiter is presented. Information contained in this graphical event sequence include: 1) Sensor location on orbiter and its associated wire bindle in X-Y plane; 2) Wire bundle routing; 3) Description of each anomalous sensor event; 4) Time annotation by (a) GMT, (b) time relative to LOS, (c) time history bar, and (d) ground track; and 5) Graphical display of temperature rise (based on delta temperature from point it is determined to be anomalous).

Source record↗

Exploration Mission Benefits From Logistics Reduction Technologies

Technologies that reduce logistical mass, volume, and the crew time dedicated to logistics management become more important as exploration missions extend further from the Earth. Even modest reductions in logistical mass can have a significant impact because it also reduces the packaging burden. NASA's Advanced Exploration Systems' Logistics Reduction Project is developing technologies that can directly reduce the mass and volume of crew clothing and metabolic waste collection. Also, cargo bags have been developed that can be reconfigured for crew outfitting, and trash processing technologies are under development to increase habitable volume and improve protection against solar storm events. Additionally, Mars class missions are sufficiently distant that even logistics management without resupply can be problematic due to the communication time delay with Earth. Although exploration vehicles are launched with all consumables and logistics in a defined configuration, the configuration continually changes as the mission progresses. Traditionally significant ground and crew time has been required to understand the evolving configuration and to help locate misplaced items. For key mission events and unplanned contingencies, the crew will not be able to rely on the ground for logistics localization assistance. NASA has been developing a radio-frequency-identification autonomous logistics management system to reduce crew time for general inventory and enable greater crew self-response to unplanned events when a wide range of items may need to be located in a very short time period. This paper provides a status of the technologies being developed and their mission benefits for exploration missions.

Broyan, James Lee, Jr.↗

Exploration Mission Benefits From Logistics Reduction Technologies

Technologies that reduce logistical mass, volume, and the crew time dedicated to logistics management become more important as exploration missions extend further from the Earth. Even modest reductions in logical mass can have a significant impact because it also reduces the packing burden. NASA's Advanced Exploration Systems' Logistics Reduction Project is developing technologies that can directly reduce the mass and volume of crew clothing and metabolic waste collection. Also, cargo bags have been developed that can be reconfigured for crew outfitting and trash processing technologies to increase habitable volume and improve protection against solar storm events are under development. Additionally, Mars class missions are sufficiently distant that even logistics management without resupply can be problematic due to the communication time delay with Earth. Although exploration vehicles are launched with all consumables and logistics in a defined configuration, the configuration continually changes as the mission progresses. Traditionally significant ground and crew time has been required to understand the evolving configuration and locate misplaced items. For key mission events and unplanned contingencies, the crew will not be able to rely on the ground for logistics localization assistance. NASA has been developing a radio frequency identification autonomous logistics management system to reduce crew time for general inventory and enable greater crew self-response to unplanned events when a wide range of items may need to be located in a very short time period. This paper provides a status of the technologies being developed and there mission benefits for exploration missions.

Broyan, James Lee, Jr.↗

Concerning the Motion and Orientation of Flux Transfer Events Produced by Component and Antiparallel Reconnection

We employ the Cooling et al. (2001) model to predict the location, orientation, motion, and signatures of flux transfer events (FTEs) generated at the solstices and equinoxes along extended subsolar component and high ]latitude antiparallel reconnection curves for typical solar wind plasma conditions and various interplanetary magnetic field (IMF) strengths and directions. In general, events generated by the two mechanisms maintain the strikingly different orientations they begin with as they move toward the terminator in opposite pairs of magnetopause quadrants. The curves along which events generated by component reconnection form bow toward the winter cusp. Events generated by antiparallel reconnection form on the equatorial magnetopause during intervals of strongly southward IMF orientation during the equinoxes, form in the winter hemisphere and only reach the dayside equatorial magnetopause during the solstices when the IMF strength is very large and the IMF points strongly southward, never reach the equatorial dayside magnetopause when the IMF has a substantial dawnward or duskward component, and never reach the equatorial flank magnetopause during intervals of northward and dawnward or duskward IMF orientation. Magnetosheath magnetic fields typically have strong components transverse to events generated by component reconnection but only weak components transverse to the axes of events generated by antiparallel reconnection. As a result, much stronger bipolar magnetic field signatures normal to the nominal magnetopause should accompany events generated by component reconnection. The results presented in this paper suggest that events generated by component reconnection predominate on the dayside equatorial and flank magnetopause for most solar wind conditions.

Sibeck, D. G.↗

Source location measurements of terrestrial kilometric radiation obtained from lunar orbit

Two-dimensional source locations of individual terrestrial kilometric radiation (TKR) events have been measured by the Radio Astronomy Explorer-2 (RAE-2) spacecraft in lunar orbit. Although the average source location at 250 kHz is above the polar regions near the earth (r nearly 2-3 earth radii), approximately 10% of the events occur at a distance larger than 7 earth radii from the earth. Furthermore, there is considerable evidence for multiple sources and source motion over the time scale of tens of minutes. Recent TKR mechanism theories which assume that the emission occurs at or near the local electron plasma or gyrofrequency would predict generation much closer to the earth's surface. Alternative emission mechanisms or special propagation conditions are required to explain many TKR events.

Kaiser, M. L.↗

Vertical distribution of boundary layer new particle formation and implications for nanoparticle growth mechanisms (Final Report)

New particles can form high above ground in the atmosphere before such formation events are observed by ground-based instruments. Once formed, these particles can take up significant amounts of water vapor, which has implications on the mechanisms by which nanoparticles grow and, ultimately, impact cloud formation processes. These observations motivated the research performed in this project using a combination of modeling, laboratory experiments, and the analysis of field observations. We hypothesized is that ground-based measurements do not always accurately represent the location and timing of new particle formation events, nor do they adequately characterize the dominant physical and chemical processes that are responsible for the subsequent growth of newly formed particles. Essentially, we wanted to study the new particle formation process under conditions that we expect may be more relevant to the actual location in the atmosphere where such events take place, which are often characterized by higher relative humidities, lower temperatures, and a broader range of precursors and oxidants compared to those observed at ground level. This project had two main objectives, each of which directly addressed our hypothesis. Our first is to investigate the timing, distribution, meteorological conditions, and nanoparticle properties associated with boundary layer new particle formation through the analysis of ARM field campaigns such as HI-SCALE and long-term observations and observations performed in other locales such as in China and India where atmospheric conditions could play a crucial role in determining the mechanisms of new particle formation. This activity provided a comprehensive description, both in time and in space, of the gases and nanoparticle properties that are responsible for these events. We also performed modeling studies to explore the vertical profile and timing of new particle formation events from these campaigns. Our second objective was to perform laboratory and process-level modeling studies to investigate the role that conditions such as low ambient temperature, high relative humidity, and different oxidants such as nitrate radical play in determining unique chemical pathways for nanoparticle growth. In doing so, we revisited the representation of nanoparticle growth in global models and updated assumptions of formation and growth based on the findings of the field, laboratory, and process-level-model work. Our research provides crucial insights into the most important regions of the atmospheric boundary layer for future observational and modeling studies. It also identifies the most relevant environmental conditions, precursors, and oxidants that are responsible for nanoparticle growth, which will aid in the design of laboratory studies and process-level model experiments. The unique pathways that we discovered can be incorporated into regional and global models, thereby improving predictions and attribution of the role of new particle formation in, e.g., air pollution formation and cloud properties.

54 ENVIRONMENTAL SCIENCES↗

Discovery of photosynthesis genes through whole-genome sequencing of acetate-requiring mutants of Chlamydomonas reinhardtii

Large-scale mutant libraries have been indispensable for genetic studies, and the development of next-generation genome sequencing technologies has greatly advanced efforts to analyze mutants. In this work, we sequenced the genomes of 660 Chlamydomonas reinhardtii acetate-requiring mutants, part of a larger photosynthesis mutant collection previously generated by insertional mutagenesis with a linearized plasmid. We identified 554 insertion events from 509 mutants by mapping the plasmid insertion sites through paired-end sequences, in which one end aligned to the plasmid and the other to a chromosomal location. Nearly all (96%) of the events were associated with deletions, duplications, or more complex rearrangements of genomic DNA at the sites of plasmid insertion, and together with deletions that were unassociated with a plasmid insertion, 1470 genes were identified to be affected. Functional annotations of these genes were enriched in those related to photosynthesis, signaling, and tetrapyrrole synthesis as would be expected from a library enriched for photosynthesis mutants. Systematic manual analysis of the disrupted genes for each mutant generated a list of 253 higher-confidence candidate photosynthesis genes, and we experimentally validated two genes that are essential for photoautotrophic growth, CrLPA3 and CrPSBP4 . The inventory of candidate genes includes 53 genes from a phylogenomically defined set of conserved genes in green algae and plants. Altogether, 70 candidate genes encode proteins with previously characterized functions in photosynthesis in Chlamydomonas , land plants, and/or cyanobacteria; 14 genes encode proteins previously shown to have functions unrelated to photosynthesis. Among the remaining 169 uncharacterized genes, 38 genes encode proteins without any functional annotation, signifying that our results connect a function related to photosynthesis to these previously unknown proteins. This mutant library, with genome sequences that reveal the molecular extent of the chromosomal lesions and resulting higher-confidence candidate genes, will aid in advancing gene discovery and protein functional analysis in photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗

Sterile neutrinos and the global reactor antineutrino dataset

We present results from global fits to the available reactor antineutrino dataset, as of Fall 2019, to determine the global preference for a fourth, sterile neutrino. We have separately considered experiments that measure the integrated inverse-beta decay (IBD) rate from those that measure the energy spectrum of IBD events at one or more locations. The evidence that we infer from rate measurements varies between ≲ 3σ and negligible depending on the reactor antineutrino flux model employed. Moreover, we find that spectral ratios ostensibly imply ≳ 3σ evidence, consistent with previous work, though these measurements are known to be plagued by issues related to statistical interpretation; these results should therefore be viewed cautiously. The software used is the newly developed GLoBESfit tool set which is based on the publicly available GLoBES framework and will be released as open-source software.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Parameter estimation with maximal updated densities

A recently developed measure-theoretic framework solves a stochastic inverse problem (SIP) for models where uncertainties in model output data are predominantly due to aleatoric (i.e., irreducible) uncertainties in model inputs (i.e., parameters). The subsequent inferential target is a distribution on parameters. Another type of inverse problem is to quantify uncertainties in estimates of “true” parameter values under the assumption that such uncertainties should be reduced as more data are incorporated into the problem, i.e., the uncertainty is considered epistemic. A major contribution of this work is the formulation and solution of such a parameter identification problem (PIP) within the measure-theoretic framework developed for the SIP. The approach is novel in that it utilizes a solution to a stochastic forward problem (SFP) to update an initial density only in the parameter directions informed by the model output data. In other words, this method performs “selective regularization” only in the parameter directions not informed by data. Further, the solution is defined by a maximal updated density (MUD) point where the updated density defines the measure-theoretic solution to the PIP. Another significant contribution of this work is the full theory of existence and uniqueness of MUD points for linear maps with Gaussian distributions. Data-constructed Quantity of Interest (QoI) maps are also presented and analyzed for solving the PIP within this measure-theoretic framework as a means of reducing uncertainties in the MUD estimate. We conclude with a demonstration of the general applicability of the method on two problems involving either spatial or temporal data for estimating uncertain model parameters. The first problem utilizes spatial data from a stationary partial differential equation to produce a MUD estimate of an uncertain boundary condition. The second problem utilizes temporal data obtained from the state-of-the-art ADvanced CIRCulation (ADCIRC) model to obtain a MUD estimate of uncertain wind drag coefficients for a simulated extreme weather event near the Shinnecock Inlet located in the Outer Barrier of Long Island, NY, USA.

42 ENGINEERING↗

Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed

The 1997 New Year’s flood was among the most devastating floods in the Truckee River watershed located in western Nevada. This event resulted from complex interactions of flood drivers, such as extreme precipitation, wet antecedent watershed conditions, warm temperatures and rapid snowmelt. We leveraged simulated forcings from the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) and a process-based hydrological model to recreate the 1997 New Year’s flood for the Truckee River watershed across four climate warming levels ranging from the current temperatures to + 4° C. For each scenario, we conducted ensemble simulations with the same forcing but with 100 different seasonal watershed antecedent conditions, which were randomly sampled from long-term hydrological simulations. The results show that the 1997 New Year’s flood can be reproduced or exceeded consistently only when the antecedent watershed conditions are wet, specifically when streamflows are above the 75th percentile of the climatological value. There is negligible change in ensemble mean peakflows for Truckee River near Reno; however, there are increases of 18% and 14% under the warming levels of + 3° C and + 4° C, respectively. The increases in peakflows under future climate warming are attributed to wetter antecedent watershed conditions and enhanced snowmelt. Furthermore, the largest increases in peakflows occur at small, high-elevation headwater basins along the Sierra Nevada crest. This study highlights that changes in extreme flood events will result from the complex interplay of multiple flood drivers. It also demonstrates the potential of storyline approaches to analyze future realizations of these extreme events under different climate scenarios.

Climate change impact study↗

The polarization sensitivity of GRETINA

Compton polarimeters have played an important role in the study of nuclear structure physics, but have often been limited in their applications because of relatively low -ray detection efficiency. With the advent of -ray tracking detector arrays, which feature nearly solid angle coverage and the ability to identify the location of Compton-scattering events to within a few millimeters, this limitation can be overcome. Here we present a characterization of the performance of the Gamma Ray Energy Tracking In-beam Nuclear Array (GRETINA) as a Compton polarimeter using the 24 Mg(p,p') reaction at 2.45 MeV proton energy. We also discuss a new capability added to the simulation package UCGretina to simulate the emission of polarized photons, and compare it to the measured data. Lastly, we use these simulations to predict the performance of the Gamma Ray Energy Tracking Array (GRETA).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Tidal disruption events and dark matter scatterings with neutrinos and photons

Stars can be tidally disrupted when passing near a black hole, and the debris can induce a flux of high-energy neutrinos. It has been discussed that there are hints in IceCube data of high-energy neutrinos produced in Tidal Disruption Events. The emitting region of neutrinos and photons in these astrophysical events is likely to be located in the vicinity of the central black hole, where the dark matter density might be significantly larger than in the outer regions of the galaxy. We explore the potential attenuation of the emitted neutrino and photon fluxes due to interactions with dark matter particles around the supermassive black hole of the host galaxies of AT2019dsg, AT2019fdr and AT2019aalc, and study the implications for some well-motivated models of dark matter-neutrino and dark matter-photon interactions. Furthermore, we discuss the complementarity of our constraints with values of the dark matter-neutrino scattering cross section proven to alleviate some cosmological tensions.

Fujiwara, Motoko↗

Cubic-meter scale laboratory fault re-activation experiments to improve the understanding of induced seismicity risks

Abstract To understand fluid induced seismicity, we have designed a large-scale laboratory experiment consisting of a one-cubic-meter sandstone with an artificial fault cut and fluid-injection boreholes. The sandstone block is assembled in a true triaxial loading frame and equipped with 38 piezoelectric sensors to locate and characterise acoustic emission events. The differential stress on the artificial fault is increased in stages to bring it towards a critically stressed state. After each stage of differential stress increase, fluids are injected at low pressures through boreholes to test the potential of fault re-activation. In addition, a high-pressure injection was conducted that created a hydraulic fracture from the injection borehole towards the artificial fault. The newly generated fluid pathway resulted in an activation of the complete block through a stick–slip movement. We compare acoustic emission measurements from the laboratory experiment with seismicity observations from the field-scale CO 2 injection at Decatur, Illinois, U.S., and conclude that the existence of fluid pathways plays a decisive role for the potential of induced seismicity.

47 OTHER INSTRUMENTATION↗

A Comprehensive Model for Analyzing the Effects of Power Outages on Customers

Power outages can cause significant inconveniences to critical services and substantial economic losses. Therefore, it is crucial to systematically analyze the impact on customers during power outages caused by various factors, such as severe thunderstorms, floods, vegetation, or mechanical problems, and to plan for reliable operation and control under such events. Power outages in different locations may exhibit varying characteristics regarding customer impact. In this paper, we present a mathematical model that captures the essential characteristics of customer impact during power outages. The parameters of our model include impact duration, recovery duration, maximum impact level, increase curve parameter, and decrease curve parameter. We demonstrate how historical power outage data can be fitted to our model, enabling a systematic comparison of outages caused by different factors in various locations.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗