We present a new empirical vertical drift model developed using ground-based magnetometer, radar, and satellite data over equatorial latitude regions. We first implement an algorithm relating magnetometer derived equatorial electrojet (EEJ) and vertical ion plasma drift (equivalent to vertical drift within magnetic latitudes of and altitudes of about 400-550 km) from the Communications and Navigation Outage Forecasting System (C/NOFS) satellite at different longitude sectors. The relationship between EEJ and C/NOFS vertical drift is developed separately at different longitudes over the globe at coincidental times when both data sets are available. These relationships are then used to estimate continuous vertical drift at each epoch of EEJ observation over the respective longitude sectors during local daytime. The reconstructed vertical drift data are combined with global C/NOFS vertical drifts and JULIA data set to develop a global vertical drift model. Validation using Ion Velocity Meter (IVM) drifts from ICON satellite for January to August 2022 shows that our model improves vertical drift global modeling by over 20% compared to the current climatology representation.
Ports are major sources of greenhouse gases (GHG) from port activities, area energy, and other heavy industries, and transportation (trucks, trains, vessels, and commuters). The Ports of Los Angeles and Long Beach (the western hemisphere's largest) have planned Port electrification to reduce GHG emissions. In this regard, the Covid19 shutdown provided a real-world test of the expected emissions benefits from electrification, investigated during a series of 10 mobile air quality lab surveys since 2019, including during the Covid19 shutdown. Surveys were conducted by an evolving mobile air pollution lab, SISTER (Standard Instrumentation Suite: Truck Enabled for Response), that continuously measured meteorology, aerosols, 15 trace gases, including methane (CH4), and targeted air samples for laboratory analysis of up to 87 trace gases. In Part 1, oxidant pollutants were investigated. Herein, we report on port-area stationary-source CH4 emissions. In situ survey data are interpreted in terms of port-area typical wind patterns from air quality station meteorology time series and oversampled TROPOMI (TROPOspheric Monitoring Instrument) CH4 satellite observations. Port-area CH4 concentrations did not change significantly during the shutdown. Total CH4 emissions for all (non-mobile) port-area sources were 7.3 f 0.7 Gg CH4 yr-1, primarily from oil production (71 %) and refineries (25 %) with emissions of 5.2 f 1.0 and 1.8 f 0.07 Gg CH4 yr-1, respectively. The Ports' proper CH4 emissions were 0.053 +/- 0.0085 Gg CH4 yr-1 and appeared mostly related to docked vessels. Measured (top-down) refinery CH4 emissions were triple California Air Resources Board's (CARB) bottom-up values; production could not be compared due to reporting differences, preventing a useful comparison of overall port emissions. Discrepancies between satellite anomaly relative strengths and CARB inventories were proposed due to transient releases, characterized in the upper decile in satellite CH4 maps, which likely are not represented in the inventories.
Context. Superluminous supernovae (SLSNe) are a rare class of transients with peak luminosities 10–100 times greater than those of standard core-collapse supernovae (SNe). The mechanisms powering their extreme brightness remain debated, with circumstellar medium (CSM) interaction, or energy injection from a central engine like a magnetar wind nebula being the most plausible scenarios. While the optical properties of SLSNe are extensively studied, their γ-ray signatures remain poorly constrained. Aims. To further constrain the underlying mechanism, we carried out a systematic search for giga-electronvolt γ-ray emission using the Fermi Large Area Telescope (LAT) from a sample of nearby hydrogen-poor (Type I) and hydrogen-rich (Type II) SLSNe over the past 16 years. Our objective is to test predictions from CSM and magnetar models, and to assess the prospects for future detections with the Cherenkov Telescope Array Observatory (CTAO). Methods. For the six targets of this sample, we studied the time variability of a putative γ-ray signal at the optical position of the SLSN on a six-month timescale, and in the case of SN 2017egm, we further investigated variability on 15-day intervals and applied a Bayesian block algorithm to characterize the time variability of the signal. We then compared the temporal evolution and spectral properties to the predictions from a magnetar and CSM interaction model. Results. Among the sample, only SN 2017egm shows significant γ-ray emission, with likelihood test statistic (TS) values of 26–33 (i.e., > 5σ) depending on the adopted time window. The signal arises between 50 and 160 days after explosion and is well described by a power-law spectrum with index Γ = 2.17 ± 0.23. The emission is consistent both in terms of its light curve and its spectrum, with predictions from magnetar models requiring either low nebular magnetization or faster spin-down than dipole losses. The CSM shell interaction scenario can reproduce the observed flux level but not the observed timing of the γ-ray signal. In addition, the observed ratio, Lγ/Lopt ∼ 1, is inconsistent with theoretical expectations and not in line with ratio measurements in other interacting CSM-dominated objects (e.g., novae or SNe) where this ratio is less than 10−2. Conclusions. Our study strongly suggests that a central engine like a magnetar plays a key role in this SLSN and could explain the bulk of the optical and γ-ray light curves properties. In order to explain the observed late-time bumps in the optical light curve of SN 2017egm, we require either: a hybrid picture combining magnetar and multiple CSM shells for the optical bumps or a pure magnetar model with infalling matter on an accretion disk. Finally, simulations of 50 hours of CTAO observations indicate that a SN 2017egm-like event would be detectable up to ∼140 Mpc in the magnetar model but not in the CSM model due to strong γ − γ absorption.
The concept of “just culture” has become important to many industries where mistakes can be deadly, such as aviation and healthcare. In the space mission assurance business, mistakes are rarely deadly, but usually costly, and consequently our approach to risk and failure resembles that of other high-criticality industries. Yet we still hew to an “old way” of looking at failure that hampers our ability to manage risk and improve success. We assume that most failures involve some sort of human error, and we fail to recognize that people behave with local rationality, or ask why their decisions made sense at the time. We overuse procedural and technological tools in an attempt to drive down human error, without recognizing that such tools create their own problems. We don't recognize the hindsight bias in our failure investigations, and consequently engage in backward-looking rather than forward-looking accountability. By shifting our approach to failure and adopting techniques rooted in just culture, space mission assurance practitioners - like airlines and healthcare providers - can improve both human performance and mission success.
