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.

Manuscripts based on machine-learning techniques have significantly increased in Space Weather over the past few years. We discuss which manuscripts are within the journal’s scope and emphasize that manuscripts fo-cusing purely on a forecasting technique (rather than on understanding and forecasting a phenomenon) must correspond to a substantial improvement over the current state-of-the-art techniques and present this comparison. All manuscripts shall include information about data preparation, including splitting of data between training, validation and testing sets. The software and/or algorithms used for to develop the machine-learning technique should be included in a repository at the time of submission. Comparison with published results using other methods must be presented, and uncertainties of the forecast results must be discussed.

The Surface Water Ocean Topography (SWOT) mission will launch in 2021 to provide the first global inventory of terrestrial surface water. Although SWOT is primarily a research mission with key science objectives in both the oceanography and hydrology domains, SWOT data is expected to have application potential to address many societal needs. To identify SWOT applications, prepare for the use of SWOT data, and quantify SWOT impacts prior to launch, realistic proxy SWOT observations with representative measurement errors are required. This paper provides a step-by-step description of two methods for deriving proxy SWOT water surface elevations (WSE) from an Observing System Simulation Experiment (OSSE) using the Weather Research and Forecasting hydrological extension package (WRF-Hydro). The first, a basic method, provides a simple and efficient way to sample WRF-Hydro output according to the SWOT orbit and add random white noise to simulate measurement error, similar to many previous approaches. An alternate method using the Centre National d’Etudes Spatiales (CNES) Large-scale SWOT Hydrology Simulator accounts for additional sources of measurement error and produces output in formats comparable to that expected from official SWOT products. The basic method is ideal for river hydrology applications in which a full representation of SWOT measurement errors and spatial resolution are unnecessary, whereas the CNES simulator approach is better-suited for more rigorous scientific studies that require a comprehensive error budget.

Wave energy has received significant attention in both academic and industrial areas during the past few decades. Among all of Wave Energy Devices (WEC) devices, many researchers focus on modeling the point absorber since it can provide a large amount of power in a small simple device when compared with other technologies. In this present work, we developed an efficient Structured Adaptive Mesh Refinement (SAMR) framework to model the interactions between the wave and pointer absorber by directly solving the Naiver-Stokes equation in a conservative manner. In particular, the level set function is used to capture the air-water interface, and re-initialization across different levels is applied. The Discrete Immersed Boundary Method (DIBM) is applied to describe geometry of the pointer absorber and include its effects on the incoming wave, which is generated in the inlet and absorbed by using a sponger layer closed to the outlet. To save computational cost, meshes are only refined near the air-water interface and surface of point absorber. Specially, both non-subcycling, where a uniform time step is employed for all variables on composite levels, and subcycling, in which variables on different levels advance via different time steps, are embedded in the SAMR framework. Cases about wave generation and fluid-structure interaction are obtained to validate the above proposed algorithm. Results show that subcycling takes significantly less CPU hours than non-subcycling to model the wave and pointer absorber interaction. Heave motions under different wave inputs are compared with previous experiments as well as results from potential flow theory, which shows viscous effects are important in this process. Future work including coupling AMR with Turbulent Models (e.g. RANS or LES) are also listed as an extension.

This work presents the results of a paleostress investigation in dated Mio-Pliocene volcanic rocks in the vicinity of the town of Lądek Zdrój in the Rychlebské hory Mts., as a part of the central Sudetic Mts. in the NE Bohemian Massif. Six different paleostress field regimes from the Late Miocene to Quaternary were distinguished. Each stress regime is characterized by the orientation of the principal parameters and is discussed in relation to the known paleostress regimes within the surrounding regions of the Sudetic Mts., Fore-Sudetic block, and European Alpine foreland in Central Europe. The results show switching of tectonic phases with dominant compression, transtension or extension. Moreover, the orientation of theoretical planes with maximum shear stress and with a high tendency to dilate for individual paleostress regimes is defined and compared with the orientation of known faults within the study area suggesting their possible kinematics. The timing of the derived regimes is determined more accurately and is in good accordance with the data reported from different regions in Central Europe, which suggests their broader validity. In addition, one event or shorter events interrupting the main Plio-Quaternary extensional regime and one differently oriented Plio-Quaternary extension regime were discovered and constrained based on several dated phases of the volcanism of the faulted rocks.