We analysed variations in signal metrics and the diurnal amplitude of VLF radiowaves from four propagation paths during intervals of 4 geomagnetic storms on 17, 26 September, 25 October and 1 November 2011. Three propagation paths are located at mid-latitude in the Northern Hemisphere, and one crossing the equatorial ionospheric anomaly (EIA) crests and magnetic equator. Our results show significant reduction in the mean amplitude before sunrise (MBSR), the daytime mean amplitude (DTMA) and the mean amplitude after sunset (MASS) signal strength in majority of the cases analysed. The ratio of the storm day signal-decrease (SDSD) to the total number of points (TNoPs) considered are 0.7692, 0.9231 and 0.6923 for MBSR, DTMA and MASS, respectively, while the respective ratio of storm day signal-increase (SDSI) to the TNoPs are 0.1538, 0.0769 and 0.3846. Of the four propagation paths, the DHO-A118 path (in the mid-latitude European sector) showed the largest decrease especially during strong storms (that are associated with solar particle events (SPEs)). We also observed distinct anomaly (large signal fluctuation) in NAA-ROI propagation path signal in South-American region (Brazil). We further investigated the state of the ionosphere over the VLF radiowaves propagation paths using the total election content (TEC) obtained from multiple stations near the transmitters and receivers, to understand these propagation characteristics. Data showed larger enhancement of electron density profiles near the DHO transmitter and ROI receiver, suggesting the large signal strength decrease and fluctuation may be related to markedly perturbed ionosphere along the DHO-A118 and NAA-ROI propagation paths.

Projected changes in extreme climate are occasionally predicted through multi-model ensemble methods using a weighted averaging that combines predictions from individual simulation models. To predict future changes in precipitation extremes, observed data and 21 of the Coupled Model Inter-comparison Project Phase 6 (CMIP6) models are examined for 46 grids over the Korean peninsula. We apply the generalized extreme value distribution (GEVD) to the series of annual maximum daily precipitation (AMP1) data. Simulation data under three shared socioeconomic pathway (SSP) scenarios, namely, SSP2-4.5, SSP3-7.0, and SSP5-8.5, are used. A multivariate bias correction technique that considers the spatial dependency between nearby grids is applied to these simulation data. In addition, a model weighting approach that accounts for both performance and independence (PI-weighting) is employed. In this study, we estimate the future changes in precipitation extremes in the Korean peninsula using the multiple CMIP6 models and PI-weighting method. In applying the PI-weighting, we suggest simple ways for selecting two shape 1 parameters based on the chi-square statistic and entropy. Variance decomposition with the interaction term between the CMIP6 model and the SSP scenario is applied to quantify the uncertainty of projecting the future AMP1. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1973-2014), are estimated for three future overlapping periods, namely, period 1 (2021-2050), period 2 (2046-2075), and period 3 (2071-2100). From these analyses, we estimate that relative increases in the observations for the spatial median 20-year (50-year) return level will be approximately 16.4% (16.5%) in the SSP2-4.5, 22.9% (22.8%) in the SSP3-7.0, and 37.6% (35.4%) in the SSP5-8.5 scenarios, respectively, by the end of the 21st century. The expected frequency of the reoccurring years, particularly for the AMP1 from 150 mm to 300 mm under the SSP5-8.5 scenario, are projected to increase by approximately 1.4 times that of the past 30 years for period 1, approximately 2.3 times that for period 2, and approximately 3.5 times that for period 3. From the analysis based on latitude, severe rainfall was found to be more prominent in the southern and central parts of the Korean peninsula.

The presence, spatial extent and persistence of low-level clouds (LLCs) largely impact on the diurnal surface radiation and energy balance, as well as, the regional climate. Notwithstanding, there is limited understanding on their evolution and processes, particularly in southern West Africa. This paper assesses the development of LLCs and their dominant formative factors, as well as, their relationship with radiation and energy balance. Firstly, ceilometer and radiosondes deployed during the DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) field campaign were used in identifying the LLC. Afterwards, the cloud fraction was employed to characterize different LLC phases. Averagely, break-up, dissipation and build-up of LLC were marked at 0900 GMT, 1200 GMT and 2200 GMT respectively. Moreover, composites of LLC diurnal evolution and their relationship with net radiation, energy storage and surface stability showed that LLCs significantly impact on net radiation flux, by reducing downwelling shortwave radiation. Additionally, LLC onsets were characterized by a near-steady state in net radiation flux, whereas the rate of energy storage within the lower layers marginally oscillated about equilibrium. Finally, with observations from selected intensive observation periods (IOPs), the dominant factors influencing LLC development were evaluated. Horizontal cold air advection, with enhancement by nocturnal low-level jets, was observed to primarily influence the development of LLCs for the study period. Findings of this paper are necessary for improving the understanding of LLC characteristics, formation and interactions with surface properties, particularly over southern West Africa.

For many universities, the emergency transition to remote learning in March 2020 has evolved into full or partial remote teaching for the foreseeable future. Decades of research show that university classrooms, particularly in STEM (science, technology, engineering, and mathematics), are inequitable and non-inclusive spaces for underrepresented students. Without deliberate action from teachers, the transition to remote learning will exacerbate this issue. As STEM graduate students invested in our learning outcomes and dismantling systemic injustices, we propose specific strategies to create more equitable and inclusive remote graduate STEM learning environments through the revaluation of communication methods and classroom structures.

Observations from rifted margins reveal that significant structural and crustal heterogeneity develops through the process of continental extension and breakup. While a clear link exists between distinct margin structural domains and specific phases of rifting, the origin of strong segmentation along the length of margins remains relatively enigmatic and may reflect multiple competing factors. Given that rifting frequently initiates on complex tectonics sutures, structural inheritance is frequently invoked as an origin of margin segmentation, although to date no studies have clearly elucidated the link between inheritance and 3D rifted margin geometries. Here, we use recent observations from the Labrador Sea and thermal-mechanical simulations of continental rifting to constrain the effects of inherited variable lithospheric properties on margin segmentation. The modelling results demonstrate that N-S variations in lithospheric thickness, crustal structure, and rheology within the pre-rift Canadian Shield produce sharp gradients in rifted margin width and the timing of breakup, leading to strong margin segmentation across a range of geophysically-constrained rift parameters.

Climate communication involves deep community engagement and multiple parallel behavior interventions for a wide array of audiences. Images include large amounts of culturally nuanced details that can improve the social uptake of community climate interventions. Image specificity grounds information within subgroups improving the relatability and accuracy of emerging regional interventions. We experimented with using ArcGIS to collect and sort regionally and topically sorted climate mitigation and resilience behaviors. We'll review how our team set up a feedback loop in Survey123 and ArcGIS and how this might be useful in future climate messaging.

We describe Ziggy, an infrastructure for pipelines that process large volumes of science data. Ziggy is based on the pipeline infrastructure software that was developed to process flight data for the Kepler and TESS exoplanet missions. In this latter capacity, multiple terabytes of data are processed every month. Ziggy provides execution control, logging, exception management, marshaling, and persistence, and data accountability record management for user-defined sequences of processing steps. Users define a pipeline via a set of XML files that specify the order in which processing algorithms are applied (including optional branching, in which one step is followed by multiple algorithms that run simultaneously), inputs, outputs, and any instrument models or control parameters that are required for each step. Ziggy supports heterogeneous pipelines: each processing algorithm can be in any supported language, and each step can run locally on a server or remotely on a supercomputer or cloud computing facility. Ziggy is sufficiently lightweight to run on a laptop and sufficiently robust to run on a supercomputer; builds on Mac OS X and Linux are supported. Ziggy is currently in use as the pipeline infrastructure tool for reprocessing the full data volume of the EO-1/Hyperion mission data and is a candidate for use in the upcoming Surface Biology and Geology (SBG) mission of the Earth System Observatory (ESO). Ziggy contains no proprietary or sensitive/controlled software or algorithms, and approval for its release as a NASA Open Source Software Project is underway.

Through the NESDIS Cloud Archive Project (NCAP), NESDIS is building on previous cloud pilot efforts and making significant progress on delivering an end-to-end cloud archive prototype in late 2021 and operational cloud archive capability in 2022. Critical to the overall design is a clear mapping between the features being designed and the functional requirements driven by National Archives and Records Administration (NARA), the Open Archival Information System Reference Model (OAIS-RM), and the NESDIS vision for a consolidated cloud archive workflow. The mapping between these drivers and the features being developed using Agile methodologies will be reviewed, and a technical summary of NESDIS’ plans to implement data archiving using commercial cloud services will be provided.

The Xiaojiang Fault (XJF) Zone locates in the southeastern of Tibetan Plateau and defines the boundary between the South China and Sichuan-Yunnan blocks. Historical large earthquakes were hosted on the XJF, though its seismic hazard in the near future is under debate. In this study, we utilize portable broad-band seismic network to unravel the microseismic activities along XJF, and to further investigate the fault structures and their properties. Adopting PALM, a newly developed earthquake detection algorithm, we obtained ~13,000 relocated events. The micro-seismicity reveals widespread off-fault structures showing conjugate geometry, while the major faults present low seismicity. The fault branches conjugate to the main-fault present intensive microseismicity, which hosts repeating events and presents high b-value. Regional GPS stations reflect slips are mostly concentrated along the XJF, while the slip rate on off-fault branches correlates with seismic activities on these structures. Combining with other recent seismological and magnetotellurics evidences, we suggest a low strength on these off-fault structures, which may partially release tectonic stress loading and serve as a barrier for future big earthquakes. On the XJF, the microseismic events are clustered on the fault junctions with low b-value. A special set of clusters between 25°N to 25.5°N show an along-strike variation of depth from 10 to 25-km, imaging the boundary between creeping and locked fault portions. We revisit the seismic hazard problem of XJF, and conclude that XJF is at the late stage of inter-seismic period.

We report the interaction between non-spherical swimmers and a long-standing flow structure, Lagrangian coherent structures (LCSs), in a weakly turbulent two-dimensional flow. Using a hybrid experimental-numerical model, we show that rod-like swimmers have a much stronger and more robust preferential alignment with attracting LCSs than with repelling LCSs. Tracing the swimmers’ Lagrangian trajectories, we reveal that the preferential alignment is the consequence of the competition between the intrinsic mobility of the swimmers and the reorientation ability of the strain rate near the attracting LCSs. The strong preferential alignment with attracting LCSs further leads to a strong clustering near the attracting LCSs. Moreover, we show the self-similarity of this clustering, which reduces the intricate interaction to only one control parameter. Our results generically elucidate the interaction between active and non-spherical swimmers with LCSs and, thus, can be widely applied to many natural and engineered fluids including ocean flow.

The NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project provides an extensive data set of aircraft in-situ meteorological, aerosol, and total water heavy isotope ratio measurements in the southeast Atlantic (SEA) lower troposphere over the months of Sept. 2016, Aug. 2017, and Oct. 2018. These months are during southern hemisphere spring, which is the agricultural burning season in subtropical southern Africa. During this season, biomass burning aerosol (BBA) loaded air in the African planetary boundary layer is carried out over the SEA by lower troposphere easterly flow. The goal of ORACLES was to study the effects of aerosol loading in the lower troposphere and as they mix into the semi-permanent cloud deck over the SEA. During ORACLES, water isotope ratio measurements D/H and 18O/16O were taken using Picarro brand cavity ring-down spectroscopic analyzers integrated into our Water Isotope System for Precipitation and Entrainment Research (WISPER). With over 300 hrs (~140,000 linear km at the typical aircraft speed) of 1 Hz sampling between 22°S to the equator and from 70 m to 6 km, this is a large and vertically resolved isotope dataset. In this presentation, we first use the coupled measurements of total water concentration and its heavy isotope ratio D/H to distinguish BBA plumes which have experienced prior precipitation vs those which have not. The findings are supported with lagrangian back-trajectories, MERRA surface temperatures and moisture, and isoCAM surface isotope values, which are combined to constrain simple isotope models. We find that BBA air sampled in 2016 experienced almost no precipitation, while BBA air and moisture in 2017 follow a model of convective outflow and most of the moisture loss is due to precipitation. Finally, we show the strong agreement between D/H evidence of precipitation amount and an indicator of aerosol removal via precipitation: the ratio of black carbon to carbon monoxide. In contrast, no correlation between total water concentration and aerosol removal is found, demonstrating the additional information contained in the isotope ratio measurements. This also provides an example of isotope ratio measurements supplementing other variables during a multifaceted field project to address science questions.

Air containing ~100 ppm H2 gas is venting about 8 hours a day from multiple locations on the periphery of 550m-diameter barren-of-vegetation depression in the Sao Francisco Basin in Brazil. Atmospheric pressure tides modulate the hydrogen venting in accordion fashion and explain the daily cycle. Modeling indicates that for hydrogen concentrations to change as observed, a substantial, permeable, subsurface reservoir must be tapped by fractures of limited volume. The fractures must have 1/1000th the volume of the accessed gas reservoir. For the phase of H2 venting to match the phase of the atmospheric pressure changes, the subsurface reservoir must be terminated by barriers such that the volume decompressed is about 25% of that which could be decompressed. How simple models can probe observations to obtain these conclusions will be the subject of the presentation.

We present a study of the potential impact of deepening the Corpus Christi Ship Channel through Aransas Pass; in particular, we study the effect on the transport of red drum fish larvae due to the change in channel depth. The study is conducted by high resolution simulation of the circulation of the seawater entering and exiting the pass for the current and proposed Ship Channel depths. The computer model incorporates tides and meteorological forcing and includes the entire Gulf of Mexico and the North American Atlantic coast. The corresponding transport of larvae modeled as passive particles due to the sea water circulation is established by releasing particles in the nearshore region outside Aransas Pass and subsequently tracking their trajectories. Both models are implemented in supercomputers at the Texas Advanced Computing Center (TACC). Accuracy of the circulation model computations is validated through comparisons to data collected from tidal gauges in the fall of 2020. We compare the difference in the number of larvae that successfully reach appropriate nursery grounds inside Aransas Pass for four distinctive initial larvae positions in the nearshore region. Our results indicate that the change in channel depth does not significantly alter the number of red drum larvae that reach suitable see a net increase of 0.5%.

Observations of Planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multi-spectral thermal infrared imager to meet a range of needs. First, and perhaps, foremost, it will be the premier integrated observatory for observing the emerging impacts of climate change . It will characterize the diversity of plant life by resolving chemical and physiological signatures. It will address wildfire, observing pre-fire risk, fire behavior and post-fire recovery. It will inform responses to hazards and disasters guiding responses to a wide range of events, including oil spills, toxic minerals in minelands, harmful algal blooms, landslides and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal and spectral resolution, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. The Research and Applications team examined available algorithms, calibration and validation and societal applications and used end-to-end modeling to assess uncertainty. The team also identified valuable opportunities for international collaboration to increase the frequency of revisit through data sharing, adding value for all partners. Analysis of the science, applications, architecture and partnerships led to a clear measurement strategy and a well-defined observing system architecture.

The Van Allen Probes Mission consists of two identical spacecraft flying in highly elliptical orbits, with perigee altitudes originally near 600 km. During the low altitude periods of the orbits, the spacecrafts are immersed in a region of high-density atomic Oxygen. Atomic Oxygen is known to change and degrade the properties of spacecraft surfaces, such as those of the Van Allen Probes Electric Field and Waves (EFW) instrument. The consistency of the sensor surfaces in EFW is important because the mechanisms used to ensure the collection of high quality electric field measurements requires that the photoemission properties of each sensor are uniform and stable. Oxidation or erosion of the sensor surfaces could limit the instrument’s ability to balance the currents produced by both the plasma electrons and the controlled bias current applied to the sensors, and thus to properly operate the device. We have modeled the atomic Oxygen exposure to the spacecraft to help determine the impact it has had on the sensors. We have calculated the fluence (time integrated flux) of atomic Oxygen particles that have collided with the spacecrafts over the entire course of the mission. We have also looked at the distribution of atomic Oxygen flux over time to further analyze malfunctions in the sensor readings at different points along the course of the mission. Additionally, we have investigated how different surfaces of the spacecraft are affected differently due to their orientation with respect to the spacecraft’s motion.

We describe a novel particle telescope, the Advanced enerGetic Ion eLectron tElescope (AGILE), which utilizes full pulse shape discrimination to identify solar energetic particles (SEP), and characterizes their spectra from about 2 to 200 MeV/nuc for most species from H to Fe. AGILE is a compact, low mass, and low-power particle telescope suitable for CubeSat platforms that enable multi-point measurements in interplanetary space. AGILE will employ high heritage solid state detectors, a state-of-art high-speed sampling ASIC, as well as novel algorithms to characterize SEP to advance the understanding of charged particle energization, loss, and transport throughout the heliosphere. AGILE will resolve ion isotopes (e.g. $^3$He vs. $^4$He) with high robustness and reliability. Currently, a prototype of the instrument is being built and will be part of science payload on the GenSat-1 CubeSat. GenSat-1 is expected be launched early 2022 into a high inclination low earth orbit, with AGILE collecting data over the polar regions, i.e., the open field line regions accessed by SEP.

The main ionospheric trough (MIT) is a salient density feature in the mid-latitude ionosphere and characterizing its structure is important for understanding GPS and HF signal propagation, and identifying geospace phenomena such as the plasmapause boundary layer. While a number of previous studies have statistically investigated the properties of the MIT utilizing low-altitude satellite observations, they have been limited to latitudinal cross sections, and have not considered the inherent two-dimensional structure of the trough. In this work, we develop a regularized inversion method for identifying the two dimensional structure of the trough in Total Electron Content (TEC) maps. Because no ground truth labels exist for the MIT, we extensively characterize the behavior of the algorithm by comparing it to the method developed by \citeA{aa-2020}. We show that statistics computed on the resulting labels are robust to our choice of algorithm parameters and that we are able to match the results of \citeA{aa-2020} with a particular selection of the parameters. Without ground truth, these two properties provide much stronger verification than a comparison using a single parameter setting. In addition to enabling fundamentally different studies, our MIT labels are able to provide statistical MIT properties with higher resolution.

Accurate mapping of urban infrastructure, specifically buildings, and extent is a high priority in addressing environmental and socioeconomic problems. Importantly, such mapping must account for the three-dimensionality (3D) of the urban environment that has traditionally been lacking (e.g., land cover and land use change—LCLUC—analyses often utilize two-dimensional satellite imagery). Undoubtedly, considerable development and change in urban areas takes place in the vertical dimension. Light detection and ranging (lidar) data provide the ability to map in 3D, but systematic data coverage both spatially and temporally is direly insufficient globally. Previous works have successfully implemented spaceborne radar data such as 1-km QuikSCAT data in lieu of lidar data to assess 3D urban build-up. Higher spatial resolution is required, though, to examine urban characteristics in detail. In this study, we test whether Sentinel-1 C-band Synthetic Aperture Radar (SAR) data can monitor 3D urban build-up in high spatial resolution (i.e. 40-m) in Detroit, Michigan, USA, 2015. Findings confirm, through comparison with aggregated 1-m lidar data, the utility of high spatial resolution SAR data for examination of urban built-up volume. Correlation and regression results show a strong linear relationship between SAR backscatter and lidar volume citywide. Moreover, SAR data, unlike coarser resolution radar data, can detect 3D anomalies over time (e.g., new building construction, building demolitions, etc.) further attesting to their utility for comprehensive 3D urban analyses a lower cost and higher repeatability over a much more extensive coverage compared to lidar data.