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At least 721 records · Page 40

Simultaneous UV Images and High-Latitude Particle and Field Measurements During an Auroral Dawn Storm at Jupiter

We present multi-instrument Juno observations on day-of-year 86, 2017 that link particles and fields in Jupiter's polar magnetosphere to transient UV emissions in Jupiter's northern auroral region known as dawn storms. Juno ranged from 42°N to 51°N in magnetic latitude and 5.8–7.8 Jovian radii (1 RJ = 71,492 km) during this period. These dawn storm emissions consisted of two separate, elongated structures which extended into the nightside, rotated with the planet, had enhanced brightness (up to at least 1.4 megaRayleigh) and high color ratios. The color ratio is a proxy for the atmospheric penetration depth and therefore the energy of the electrons that produce the UV emissions. Juno observed electrons and ions on magnetic field lines mapping to these emissions. The electrons were primarily field-aligned, bidirectional, and, at times, exhibited sudden intensity decreases below ∼10 keV coincident with intensity enhancements up to energies of ∼1,000 keV, consistent with the high color ratio observations. The more energetic electron distributions had characteristic energies of ∼160–280 keV and downward energy fluxes (∼70–135 mW m−2) that were a significant fraction needed to produce the UV emissions for this event. Magnetic field perturbations up to ∼0.7% of the local magnetic field showing evidence of upward and downward field-aligned currents, whistler mode waves, and broadband kilometric radio emissions were also observed along Juno's trajectory during this time frame. These high-latitude observations show similarities to those in the equatorial magnetosphere associated with dynamics processes such as interchange events, plasma injections, and/or tail reconnection.

R. W. Ebert↗

Application of Tisserand's Criterion and the Lidov-Kozai Effect to STORM's Trajectory Design

The Solar-Terrestrial Observer for the Response of the Magnetosphere (STORM) concept recently completed its Phase A design funded by NASA's Heliophysics Medium-class Explorers program. The mission design required a lunar gravity assist to insert the single spacecraft into a 30-Earth-radii circular geocentric science orbit inclined 90 degrees to the ecliptic. STORM's trajectory design leveraged several interesting gravitational effects from third bodies. This paper describes our application of Tisserand's criterion for finding feasible transfers and lunar gravity assist trajectories, and the Lidov-Kozai effect to design a maneuver-free science orbit optimization and decommissioning strategy.

tisserand criterion↗

Extreme Poleward Expanding Super Plasma Bubbles Over Asia-Pacific Region Triggered By Tonga Volcano Eruption During the Recovery-Phase of Geomagnetic Storm

The Tonga volcano eruption of 15 January 2022 unleashed a variety of atmospheric perturbations, coinciding with the recovery-phase of a geomagnetic storm. The ensuing thermospheric variations created rare display of extreme poleward-expanding conjugate plasma bubbles seen in the rate of total electron content index over 100–150°E, reaching ∼40°N geographic latitude. This is associated with fluctuations in FORMOSAT-7/COSMIC-2 (F7/C2) ion-density measurements and spread-F in ionograms. Preceding to this, an unusually strong pre-reversal enhancement (PRE) occurred in the global ionospheric specification (GIS) electron density profiles derived from F7/C2 observations. The GIS also revealed a decrease of equatorial ionization anomaly (EIA) crest density due to the storm impact. Reduced E-region conductivity by volcano-induced waves and enhanced F-region wind, further accelerated by reduced ion-drag over the EIA, apparently intensified the PRE. Accompanied with the strong PRE, volcano-induced seed perturbations triggered the super plasma bubble activity.

P. K. Rajesh↗

Thermal Electron Heat Fluxes Associated with Precipitated Auroral Electrons During the Saint Patrick's Days 2013 and 2015 Geomagnetic Storms

The Rice Convection Model-Equilibrium (RCM-E) and SuperThermal Electron Transport (STET) are combined to investigate electron heat flux formation in the region of the diffuse aurora for the geomagnetic storms of 17 March 2013 and 17 March 2015. The primary electron precipitation into the atmosphere resulting from wave particle scattering in the magnetosphere are simulated by the magnetically and electrically RCM-E during these two geomagnetic storms. The primary precipitating electron fluxes are modified by the STET model by taking into account atmospheric backscatter processes. The modified electron energy fluxes and their mean energies are coupled to the STET code to calculate electron thermal fluxes associated with diffuse aurora on a global scale. We use the simulated heat flux to estimate electron temperatures at the upper ionospheric altitudes and compare them with corresponding observations from the Defense Meteorological Satellite Program satellite.

George V. Khazanov↗

THE MAIN PHASE OF GREAT MAGNETIC STORMS

Demonstration that the main phase of great geomagnetic storms is composed of two parts, characterized by different decay rates of the ring current field

MAGNETIC STORM↗

Cross-scale modeling of storm surge, tide, and inundation in Mid-Atlantic Bight and New York City during Hurricane Sandy, 2012

Driven by high-resolution NAM (North America Mesoscale) and ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric fields, a 3-D unstructured grid SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) was applied to simulate total water level in the Mid-Atlantic Bight during Hurricane Sandy in 2012. The simulated storm surge, tide, significant wave height, and wave peak period results compared favorably with NOAA observations along US East Coast, Long Island Sound, and New York Harbor. The maximum total water level at The Battery in the New York Harbor was accurately simulated with an absolute error of less than 0.08 m (out of 2.9 m peak surge) and a timing difference less than 10 min, which includes the effects on the order of 0.1–0.3 m (5–10%) from the coastal setup induced by the surface waves. The scenario comparisons of (1) “NAM” versus “ECMWF”, (2) “2-D” versus “3-D”, and (3) “with” versus “without” wind wave model were examined. The 3-D barotropic model forced by ECMWF including the effects of wind waves performs the best, attributed to wave-induced radiation stress and reduction of bottom stress when the 3-D version is used. Simultaneously, the ELCIRC-Sub model, using a 5-m topography/bathymetry sub-grid and a regular 200-m resolution finite volume computational model grid, was developed to simulate the street-level inundation in New York City. The momentum and mass fluxes calculated by the coarser base grid model were effectively coupled with the sub-grid so that running a full-blown high-resolution base model is not required. The ELCIRC-Sub model uses MPI (Message Passing Interface) parallel computing to enlarge the coverage of the land surface and an efficient non-linear solver to improve the accuracy of the wetting-and-drying processes. The temporal comparisons of modeled water level with NOAA's tidal stations and USGS' rapid-deployed gauges showed overall performance with an average error of 0.1 m. Particularly, ELCIRC-Sub captured the profile of the highest peak surge (3.9 m), which rose 2 m within 3 hour at Kings Point, NY. The spatial comparisons of the modeled peak water level at 80 surveyed locations showed an average error less than 0.13 m. The modeled maximum inundation extent also matched well with an 80% hit rate against FEMA's Hurricane Sandy maximum flooding extent.

54 ENVIRONMENTAL SCIENCES↗

Investigating the Determinants of Household Capabilities Burden During Power Outages: The Case of Winter Storm Uri

Existing research primarily uses census data to identify the vulnerability of communities to hazards. These vulnerability indices provide aggregated data and are not hazard-specific nor well-validated with post-event data. In contrast, our study uses household survey data (n=1065) to understand which Texan households suffered the greatest loss of their capabilities due to power outages and other utility service disruptions during Winter Storm Uri. Inspired by the Capabilities Approach, our measures of burden include the number of household capability types disrupted during the outages (e.g., cooking, heating, refrigeration), the severity of impact for each disrupted capability, and the additional time and financial costs of coping with these disruptions. We perform a clustering analysis, and find two distinct groups in our data, consisting of ‘lesser burden' and ‘heavier burden' households. Results indicate that the households experiencing the heaviest capabilities burden were most likely to experience longer power outages and the loss of water services. They were also more likely to have a Hispanic-Latino household member, lack access to a generator, live in a rented home, have larger households with more young children, fewer adults over 65, lower household incomes, been impacted by the COVID-19 pandemic, and more family characteristics that made life harder. We also fit a logistic regression model to assess the role of outage, household, and community characteristics in predicting differences in capabilities burden. Our results offer insights into enumerating the consequences of utility service disruptions on households, which can inform more targeted and equitable resilience strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Tropical Cirrus in Global Storm-Resolving Models. Part II: Cirrus Life Cycle and Top-of-Atmosphere Radiative Fluxes

Cirrus clouds of various thicknesses and radiative characteristics extend over much of the tropics, especially around deep convection. They are difficult to observe due to their high altitude and sometimes small optical depths. They are also difficult to simulate in conventional global climate models, which have coarse grid spacings and simplified parameterizations of deep convection and cirrus formation. We investigate the representation of tropical cirrus in global storm-resolving models (GSRMs), which have higher spatial resolution and explicit convection and could more accurately represent cirrus cloud processes. This study uses GSRMs from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project. The aggregate life cycle of tropical cirrus is analyzed using joint albedo and outgoing longwave radiation (OLR) histograms to assess the fidelity of models in capturing the observed cirrus cloud populations over representative tropical ocean and land regions. The proportions of optically-thick deep convection, anvils, and cirrus vary across models and are portrayed in the vertical distribution of cloud cover and top-of-atmosphere radiative fluxes. Model differences in cirrus populations, likely driven by subgrid processes such as ice microphysics, dominate over regional differences between convectively-active tropical land and ocean locations.

54 ENVIRONMENTAL SCIENCES↗

Air Pollution Unable to Intensify Storms via Warm‐Phase Invigoration

Abstract According to the hypothesis of aerosol invigoration, the higher concentration of aerosols in polluted air intensifies storms. A leading theory for explaining such a relationship is warm‐phase invigoration, in which cloudy updrafts that are more polluted more readily condense water vapor onto liquid drops, thereby releasing latent heat faster, leading to higher buoyancies and higher updraft speeds. For this mechanism to work, water‐vapor supersaturations well in excess of 1% must be typical of relatively unpolluted cloudy updrafts. Here, the supersaturation is calculated from in situ observations of warm‐phase cloudy updrafts over the Amazon. Instead of values well in excess of 1%, the typical values are found to be around 0.2%. These observations imply that cleaner preindustrial air might have generated supersaturations around 1%, but those are still too low for warm‐phase invigoration to have any practically significant impact on cloud buoyancy and updraft speeds.

54 ENVIRONMENTAL SCIENCES↗

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗

How do deer respiratory epithelial cells weather the initial storm of SARS-CoV-2 WA1/2020 strain?

The potential infectivity of severe acute respiratory syndrome associated coronavirus-2 (SARS-CoV-2) in animals raises a public health and economic concern, particularly the high susceptibility of white-tailed deer (WTD) to SARS-CoV-2. The disparity in the disease outcome between humans and WTD is very intriguing, as the latter are often asymptomatic, subclinical carriers of SARS-CoV-2. To date, no studies have evaluated the innate immune factors responsible for the contrasting SARS-CoV-2-associated disease outcomes in these mammalian species. A comparative transcriptomic analysis in primary respiratory epithelial cells of human (HRECs) and WTD (Deer-RECs) infected with the SARS-CoV-2 WA1/2020 strain was assessed throughout 48 h post inoculation (hpi). Both HRECs and Deer-RECs were susceptible to virus infection, with significantly ( P < 0.001) lower virus replication in Deer-RECs. The number of differentially expressed genes (DEG) gradually increased in Deer-RECs but decreased in HRECs throughout the infection. The ingenuity pathway analysis of DEGs further identified that genes commonly altered during SARS-CoV-2 infection mainly belong to cytokine and chemokine response pathways mediated via interleukin-17 (IL-17) and nuclear factor-κB (NF-κB) signaling pathways. Inhibition of the NF-κB signaling in the Deer-RECs pathway was predicted as early as 6 hpi. The findings from this study could explain the lack of clinical signs reported in WTD in response to SARS-CoV-2 infection as opposed to the severe clinical outcomes reported in humans. IMPORTANCE. This study demonstrated that human and white-tailed deer primary respiratory epithelial cells are susceptible to the SARS-CoV-2 WA1/2020 strain infection. However, the comparative transcriptomic analysis revealed that deer cells could limit viral replication without causing hypercytokinemia by downregulating IL-17 and NF-κB signaling pathways. Identifying differentially expressed genes in human and deer cells that modulate key innate immunity pathways during the early infection will lead to developing targeted therapies toward preventing or mitigating the “cytokine storm” often associated with severe cases of coronavirus disease 19 (COVID-19). Moreover, results from this study will aid in identifying novel prognostic biomarkers in predicting SARS-CoV-2 adaption and transmission in deer and associated cervids.

60 APPLIED LIFE SCIENCES↗