Infrastructure is not truly designed. It evolves. Infrastructure matures and becomes more ubiquitous, accessible, reliable, and transparent as ‘gateways’ begin to connect myriad systems [1]. Often these gateways that facilitate interconnection are ‘standards’ — be they formally defined or tacitly accepted practice. There is a process of convergence where communities begin to agree not only to use a common standard, but to use it in a common way. This presentation examines two case-studies of how standards adoption for data interoperability has progressed over time: The development of an international Arctic data coordination network over the last 15 years and work establishing the Research Data Alliance. Observations suggest that convergence on standards and their implementation is a dynamic process that works to negotiate and interpret multiple, sometimes conflicting, concerns. Standards can be adopted in different ways by different people and organizations and still enable interoperability. An inclusive, ecological methodology to system design is more resilient, adaptive, and responsive to interdisciplinary needs. Overall, maintenance of standards and their community is essential to their adoption and persistence.

Within a year of its launch date, the ATLAS altimeter on board ICESat-2 is already providing a wealth of critical data of interest across and beyond the cryospheric sciences. With the satellite returning nearly 1 TB of raw data per day, traditional practices of individual research groups downloading large granules of data and then subsetting, processing, and storing them locally are ultimately impractical. We are leading the development of icepyx (formerly icesat2py), an open source Python library designed to easily query, filter, download, and pre-process ICESat-2 datasets. The project’s documentation will include interactive Jupyter Notebook examples, providing a starting point for researchers to create and customize workflows to address their research questions. We actively invite contributions from the community to ensure the project develops in a way that meets a wide range of research needs. The project aims to leverage existing libraries that enable easy parallelization and can be run locally or on cloud-based platforms. As a result, researchers will ultimately download and store minimally-sized subsets of ICESat-2 data and have the opportunity to contribute their code to an established open science project. This presentation will serve to introduce icepyx to the cryosphere community and encourage early adoption of the library by researchers with all levels of coding experience.

Recent research showed that machine learning, in particular deep learning, can be applied with great success to a multitude of seismological tasks, e.g. phase picking and earthquake localization. One reason is that neural networks can be used as feature extractors, generating generally applicable representations of complex data. We employ a convolutional network to condense earthquake waveforms from a varying set of stations into a high dimensional vector, which we call event embedding. For each event the embedding is calculated from instrument-corrected waveforms beginning at the first P pick and updated continuously with incoming data. We employ event embeddings for real time magnitude estimation, earthquake localization and ground motion prediction, which are central tasks for early warning and for guiding rapid disaster response. We evaluate our model on the IPOC catalog for Northern Chile, containing ∼100,000 events with low uncertainty hypocenters and magnitude estimates. We split the catalog sequentially into a training and a test set, with the 2014 Iquique event (Mw 8.1) and its fore- and aftershocks contained in the test set. Following preliminary results the system achieves a test RMSE of 0.28 magnitude units (m.u.) and 35 km hypocentral distance 1 s after the first P arrival at the nearest station, which improves to 0.17 m.u. and 22 km after 5 s and 0.11 m.u. and 15 km after 25 s. As applications in the hazard domain require proper uncertainty estimates, we propose a probabilistic model using Gaussian mixture density networks. By analyzing the predictions in terms of their calibration, we show that the model exhibits overconfidence i.e. overly optimistic confidence intervals. We show that deep ensembles substantially improve calibration. To assess the limitations of our model and elucidate the pitfalls of machine learning for early warning in general, we conduct an error analysis and discuss mitigation strategies. Despite the size of our catalog, we observe issues with two kinds of data sparsity. First, we observe increased residuals for the source parameters of the largest events, as training data for these events is scarce. Second, similar inaccuracies occur in areas without events of a certain size in the training catalog. We investigate the impact of these limitations on the Iquique fore- and aftershocks.

It has been four decades since Apollo 16 returned the first wide-field UV imagery of the Earth and revealed the vast extent of exospheric hydrogen (H) atoms around the planet. Since that time, appreciation has grown regarding the significance of this outermost atmospheric layer, whose charge exchange interaction with ambient ions dissipates magnetospheric energy, generates the energetic neutral atoms (ENAs) widely used for remote sensing of the ring current dynamics during geomagnetic storms, and accelerates gravitational escape and thus permanent atmospheric evolution. Despite the importance of Earth’s H exosphere to the solar-terrestrial system, however, current understanding of its global structure and dynamical evolution is insufficient, such that the origin of persistent discrepancies between measurements and models remains unresolved. Remote sensing of UV emission from geocoronal H atoms, generated through resonant scattering of solar radiation at 121.6 nm (Lyman-alpha) is the only empirical means available to investigate the terrestrial exosphere. In this work, we present robust tomographic-based techniques we have developed in recent years to estimate the 3-D, global and time-dependent H-density distributions during quiet and storm-time from observations of its optically thin emission at Lyman-α acquired from the Lyman-alpha detectors onboard the NASA TWINS satellites. Several examples of recent 2D and 3D data analyses will be used to demonstrate the current state-of-the-art, reveal surprising exospheric phenomenon, and motivate future work.

Photoelectrons produced by solar EUV 􀂧uxes are a major contributor to ionospheric heating at high altitudes. Modeling of photoelectron heating relies strongly on their space-energy distribution, which in turn depends on the accuracy of the description of EUV sources and complex photon-electron transport. The source of EUV 􀂧uxes is solar radiation emitted from the whole solar disk and corrected for atmospheric absorption. Measured EUV 􀂧uxes consist of numerous integrated bands and the emission line intensities, which have high (~50%) variability, even for similar levels of solar activity (Heroux, 1972). We analyze the sensitivity of photoelectron production to the EUV sources by comparing results calculated based on a direct EUV 􀂧ux measurement in the wavelength region 1220-52 Å from(Heroux, 1972), and the EUVAC model developed by Phil Richards (Richards et al., 1994). Our preliminary results show that the accuracy of the EUVAC model in the calculation of the photoelectron space-energy distribution is comparable to that based on direct EUV 􀂧ux measurements. Photoelectron production caused by EUV 􀂧ux involves a complex physical process of primary (photons) and secondary (electrons) interactions. It relies on cross-section libraries and tabulated distribution functions for secondary particle production and energy losses, implemented in the MCNP6 general-purpose Monte Carlo solution, and utilized in our coupled photon-electron transport calculations. The solution takes into account all fundamental photoand electro-atomic transport processes, including sub-shell electro-ionization that affects the atomic relaxation process for energies down to one eV. The most signicant improvement is made by including all atomic electron subshells that affect the atomic relaxation process for these energies. Data structures include subshell binding energies, ground-state electron populations, and the number of possible relaxation transitions. Photon transport enhancements are based on a new dataset speci􀂦c to atomic subshells and incorporated into MCNP6, and completion of form factor data for coherent and incoherent scattering. These results will be applied to ionospheric electron temperature measurements from Langmuir probes on board the European Space Agency’s Swarm satellite mission.

Quality metadata and data are critical to advancing science and preserving data for long-term use. The Next Generation Ecosystem Experiments (NGEE) Tropics project funded by the U.S. Department of Energy generates and utilizes ecological, hydrological, and meteorological data from tropical forests for scientific analysis and model parameterization. The project’s data team manages an archive for users to internally curate and publish data with a digital object identifier (DOI). A key focus of our project is to ensure NGEE Tropics data can be interpreted and utilized by current and future research teams. However, the education and participation of project members to prioritize and be involved in data curation is necessary to reach this goal. We have taken an interdisciplinary approach involving domain and data scientists to create a process that makes it easy for scientists to curate high-quality data packages for archival. First, the NGEE Tropics Archive and metadata reporting templates (FRAMES) were designed using user-experience research methods to incorporate user feedback through interviews and surveys. Upon submission of data packages, thorough checks are performed to ensure quality expectations are met. Each dataset is curated individually, and feedback is provided directly to scientists to identify the optimal data organization for their packages. The data team also provides training to project members using presentations, tutorials, and 1:1 training. As a result of our efforts, package and file-level metadata reporting to the NGEE Tropics archive fits within the existing workflow of scientists, establishing data curation as a core aspect of research. By educating the NGEE Tropics team through integration and communication, we have enabled the production of quality data packages that are findable, accessible and usable by any member of the public. This work will enhance the legacy of NGEE Tropics, and provide a lasting resource for the tropical research community.

Our world has been continuously urbanized and is currently accommodating more than half of the human population in cities. Despite that cities cover only less than 3% of the Earth’s land surface area, they emerged as focal points of human activities, and confront numerous environmental challenges as a result of changes in landscapes, hydroclimate, ecosystems, and biodiversity. In particular, the built environment usually experiences exacerbated heat stress induced by global climate and landscape changes, commonly known as the urban heat island effect. Urban irrigation, as a climate adaptation and mitigation strategy, is effective in cooling the built environment, but exhibits large uncertainties in the trade-off between water use and heat mitigation capacity. Here we show the efficiency of cooling effect induced by irrigation of urban vegetation, represented by a novel metric, viz. urban water capacity, analogous to the heat capacity, across the contiguous United States (CONUS) during summertime via numerical simulations. The urban water capacity is calculated as the average irrigation depth per degree of urban temperature reduction; the values are 4.52 ± 0.77 mm day–1 °C–1 and 7.27 ± 1.27 mm day–1 °C–1 (mean ± standard deviation) for surface and near-surface air cooling, respectively, over the CONUS. The robustness of urban water capacity is further exemplified in an extreme heat wave event, during which the warming anomaly is partially offset by the additional cooling from urban irrigation. Estimates of water capacity provide a quantitative metric for evaluating the efficacy of irrigation in urban planning under current heat stress and future warming.

Measuring progress towards achieving the 17 UN Sustainable Development Goals (SDGs) requires the monitoring of indicators developed to assess and quantify changes in the state of natural, social, economic, and environmental systems structures within countries. Aggregated over regions these indicators provide information to decision makers at national, regional and international organizations to support policy actions to ensure the sustainability of available resources. Frequently, the SDG indicators are targeted at specific social or economic subelements; they are not designed to consider the interaction between sectors. Here, we propose an integrated index for the Water-Energy-Food Nexus using a selection of sub-indicators from among the already defined 17 UN Sustainable Development Goals. The use of EO data streams and data assimilation products is proposed as an essential part of the methodology, especially in large parts of the globe where detailed in-situ data are likely to be insufficient or lacking. Once the methodology is validated and tested in a selection of pilot regions, it can be made available to all interested national, regional and international development organizations and programs. Primary Goal: EO/RS WEF-SDG Index to monitor sustainability of natural resources and socio-economic activity.

In the framework of EGS, using hydraulic stimulation increases pore pressure into the existing fracture networks and can be responsible for slip reactivations. In order to predict the seismic or aseismic character of these slips, it is important to determine the influence of the gouge characteristics on the slip behaviour. Lab or in-situ testing can be very helpful, but experience has shown that it is complicated to install local sensors inside a mechanical contact and that some data remains impossible to obtain. In this study, we are focusing on the physics of the contact inside a granular gouge to understand the mechanisms of slip triggering by using numerical modelling. We implement a 2D granular fault gouge with Discrete Element Modelling (DEM). The model involves two rough surfaces representing the rock walls separated by a granular gouge with realistic angular particles created by the wear of previous slips. A displacement-driven model with dry contact is primarily studied to observe the peak of static friction (shape, slope or duration). In order to spotlight the aseismic and seismic patterns, a second model is carried out to add the stiffness of the rocks (or loading apparatus). Dedicated post processing tools are also used in order to analyse the spatial distribution of the solid fraction and the force chains patterns bringing a new understanding of physics from a granular point of view. Representing realistic morphology of particles (angular shapes) brings an additional level of control with respect to most of the simulations reported in the literature using circular grains. Angular grains lead to higher friction coefficients with different global behaviours. The initial solid fraction of the gouge appears to be a good indicator of the friction peak we have at a slip triggering (Fig.). The more compacted the gouge is, the more effort is needed to disturb the initial grains assembly and to reach a steady state regime. With fractal size distribution, we have also studied the mechanical contribution of small particles in the media. Friction coefficient results let us conclude that the presence or not of very small particles is not as influent as the initial solid fraction of the gouge. Finally, adding a stiffness on the upper rock wall provides information on the transition from stable sliding to slow-slip/stick-slip behaviour.

Overlapping areas between Protected Areas and Indigenous peoples’ territories are important spaces for articulating cross-scale governing institutions and augmenting socioecological adaptability in developing countries. However, cooperation hinges on conflicts resolution between local (Indigenous peoples’ authorities) and national institutions (Protected Areas’ federal managers), official recognition of ancestral rights to Indigenous peoples, and the investment of social and financial capital for protecting important natural resources in synchrony with local communities. For this, is necessary to improve our understanding of the impacts of cross-scale interaction on natural resources’ conservation. In this research, we study these interactions on the Orinoco River watershed, one of the most important areas for the conservation of biodiversity in South America. Overlaps between Protected Areas and Indigenous peoples’ territories in this watershed account for 9% of its surface area. To test the effect of different political setups on conservation, we employed conservation indicators that use spatially-defined biophysical attributes. First, we explored differences between governing units (non-overlapping Protected Areas or PA, non-overlapping Indigenous peoples’ territories or IT, and overlapping areas or OV), then, we analyzed different overlapping categories (Partial, Near, None, and Full), finally, we analyzed how the recognition of ancestral rights impacts local governance by comparing Indigenous territories with rights and without rights. We found that conservation measurements were higher where any type of overlap took place, which suggests that the interaction between local and national institutions has a positive effect on the protection of important ecosystem services, furthermore, the proxies used to measure ecosystem services values indicate that areas contiguous to OV (Near overlapping category) have greater benefit than commonly expected. Our results were inconclusive regarding the effect of public recognition to local authorities on the local governance; however, this study contributes to the body of evidence about the contribution of these communities to the conservation of strategic ecosystems. This research highlights the importance of collaborative work for the conservation of natural resources, furthermore, it could support future investments of public funds on the creation and strengthening of cross-scale alliances and coalitions for the conservation and management of strategic ecosystems in the Orinoco River watershed.

Seismic, potential-field, and earthquake data have been collected and modeled across the San Andreas fault (SAF) in a number of locations in southern and central California. In most locations the fault does not have a vertical or steep dip (>85 deg). In at least 3 locations it has a 2-part dip: below 6- to 9- km depth the fault dips moderately (between about 40 and 70 deg), and above that depth interval it is steep. The subsurface geometry of the fault from southeast to northwest is as follows. In two locations in the Coachella Valley, spanning a major bend in the SAF, the deeper segment of the SAF dips moderately northeast and the shallower segment is steep. Through the San Gorgonio Pass and San Bernardino areas, the SAF continues to dip northeast (as gently as 37 deg at one location), but the 2-part dip seen in the Coachella Valley is not resolvable. From Cajon Pass to the western Mojave Desert, spanning the two LARSE seismic profiles, the SAF dips steeply and is approximately planar. Around the Big Bend of the SAF, southwest of Bakerseld, the fault appears to dip moderately southwest, although this dip is constrained only by potential field data, and a 2-part dip cannot be resolved. At Parkfield, the fault dips steeply southwest and is approximately planar. A southwest dip continues to be observed northwestward into the Santa Cruz Mountains where we resolve a 2-part dip for the rupture of the 1989 M 6.9 Loma Prieta earthquake. The deeper segment of the fault dips moderately southwest, whereas the shallower segment is steep and complex. The change in fault dip in the depth interval of 6-9 km, that is observed in at least 3 locations along the SAF in southern and central California, may result in part from a change in rheology in the upper part of the crust. Rheology changes from elastic at greater depths, where earthquakes occur, to non-linear at shallower depths, where earthquakes diminish in number. A steeper dip at shallower depth likely represents a minimum-work configuration for fault rupture. The approach of the fault to the free surface may also play a part in this depth-dependent geometry.

Background: Capillary trapping of gas bubbles and oil blobs within water-saturated media plays an important role for underground gas storage and secondary oil recovery. Wettability and roughness of the surface are elementary properties of a porous medium that determine the trapping efficiency. In previous work [1,2], we demonstrated that glass beads and natural sands display a significant difference (15%) of the trapped gas phase. Here, we carry out a systematic study of the capillary trapping efficiency in dependence of the wettability and surface roughness. Methods: We conducted a series of column experiments to study capillary trapping of gaseous CO2 using both glass beads and natural sands as sediments. Based on the high-resolution non-invasive micro-CT visualization method and subsequent image processing, we quantified capillary trapping efficiency, gas-cluster morphology and gas-cluster size distribution. We used the silanization method for varying degrees of wettability resulting in three different contact angles on microscopic soda lime glass slides: (i) Piranha cleaning (= 7°), (ii) untreated glass (= 30°) and (iii) silanized glass (=100°). Results: We observed that by-pass trapping is the dominant trapping mechanism in glass beads (smooth surfaces). The displacement process is piston-like. For natural sands (rough surface), thick film flow occurs, causing an efficient snap-off trapping mechanism. Our results indicate that the capillary trapping efficiency of natural sands is stronger reduced by a transition from water-wet to CO2-wet 3-phase system (increasing contact angle) when compared to glass beads. [1] H. Geistlinger, I. Ataei-Dadavi, S. Mohammadian, and H.-J. Vogel (2015) The Impact of Pore structure and Surface Roughness on Capillary Trapping for 2D- and 3D-porous media: Comparison with Percolation theory. Special issue: Applications of Percolation theory, Water Resour Res, 51, doi:10.1002/2015WR017852. [2] H. Geistlinger, I. Ataei-Dadavi, and H.-J. Vogel (2016) Impact of Surface Roughness on Capillary Trapping Using 2D-Micromodel Visualization Experiments. Transport in Porous Med., DOI 10.1007/s11242-016-0641-y.

The considerable challenges of accessing unpredictable events at remote seafloor locations make submarine eruptions difficult to study in real time. The serendipitous discovery of two persistently active sites (NW Rota-1 in the Mariana arc, at ~550 m, and West Mata in the NE Lau basin at ~1200 m) resulted in multi-year, multi-parameter studies that included water column plume surveys and direct (ROV) observations. Intense magmatic-hydrothermal plumes rose buoyantly above both sites, while deep particle plume layers, dominated by fine ash and devoid of hydrothermal tracers, were found dispersing laterally on isopycnal surfaces at variable depths below the eruptive vents and above the seafloor. The presence or absence of deep ash plumes was directly correlated with explosive activity or quiescence, respectively. An estimated 0.4-14.6 x 105 m3/yr of fine ash entered the water column surrounding these volcanoes and remained suspended at distances exceeding 10’s of km. We show that deep ash plume layers in the water column are a common feature of explosive submarine eruptions at other sites as well, and that they demonstrate a syn-eruptive mode of transport for fine ash that will result in deposition as “hidden” cryptotephra or fallout deposits in marine sediments at distances greater than previously predicted. Cruise FK171110 extended the time series of observations at West Mata, and resulted in discovery of new lava flows emplaced after September 2012, with one constrained between March 2016 and November 2017. ROV dives confirmed that West Mata was quiescent during this expedition, but widespread deep ash plumes were present. Turbidity in the deep ash plumes decreased by 80% over a 25-day period, with an average loss of 3% (0.15-0.6 g/m2) per day, suggesting the eruption that formed the 2016-2017 eruptive deposits had occurred within 8-121 days prior to the FK171110 expedition. Future studies of submarine volcanic processes will depend on improved exploration and event detection capabilities. In addition to recognizing the characteristic hydrothermal event plumes rising into the water column above actively erupting sites, widespread ash plumes dispersing at depths deeper than eruptive vents can also be diagnostic of ongoing, or very recent, eruptions. We infer the eruptive status at other sites based on these criteria.

Driven by unusually warm air in the Arctic, severe winter weather moves down south to mid-latitude areas, reflecting the complexity in the ways that climate change may affect local weather extremes. Food and agriculture have been identified as central to global efforts to adapt to climate change. However, research is notably lacking in understanding the vulnerability of farming communities to winter storms that are recognized as one of catastrophic events leading to agricultural damage and loss. This study focuses on mapping the interplay of social and physical factors (e.g. building age, farm-related income, education level, access to farming facilities) that differentiate Iowa farming communities with unequal vulnerability. Semi-structured interview was used in this study to identify the determinants of vulnerability of farming communities to winter storms. Incorporating spatial analysis and factor analysis, this study quantified the effects of physical factors on the sensitivity and exposure of winter storms, and prioritized primary livelihood capitals that determine the adaptive capacity to winter storms. Current results have demonstrated the vulnerability patterns of farming communities to winter storms shaped under varying societal-physical environments and weather conditions. This research shows implications in livelihood pathways to transforming adaptations to vulnerability reduction.

Vertical motions of Earth’s surface are used to inform almost all branches of the Earth Sciences, and central role in understanding geological, biological and climatic processes. An important challenge is generating enough information to reliably constrain histories of vertical motion. Significant effort has been expended in generating information about denudation (e.g. from thermochronometry), uplift (e.g. from stable isotopes or drainage analyses) and subsidence patterns. However, a canonical inventory of measurements that determine continental uplift on timescales pertinent to growth and decay of continental topography does not exist. We address this issue using the distribution of unequivocally marine rock recorded in new, detailed, paleobiological inventories. We show that these new compilations of paleobiological and paleoenvironmental data, that were generated to address paleobiological problems, also provide an unprecedented number of self-consistent, high-resolution measurements of continental and ocean island uplift. We focus on the Cretaceous to Recent history, which captures the large-scale marine incursions of the continents. Our results highlight that significant improvements can be made in understanding the histories of the continents in using these measurements of uplift. We present examples from North and South America, southern Africa and Australia to show how this new database can be explored to better understand the processes that generate high topography. They emphasize the importance of large inventories of paleobiological data for understanding long-wavelength uplift and the role tectonic and mantle convective processes play in generating continental topography.

In our current system, research assessment and reward are weighted heavily towards scientific inputs and outputs, and research impact is measured in funding dollars awarded and research articles produced. The value of science, however, extends well beyond contributions to the research activity itself. ‘Project Redefining Recognition’ is a cross-society initiative which seeks to develop a shared future vision and clear set of actions across the Earth, Space, and Environmental Sciences to expand research assessment to explicitly include, recognize, and reward actions that advance open science, broad communication and public engagement.This presentation will look closely at the ways in which Society partners participating in ‘Project Redefining Recognition’ are supporting their communities in sharing and applying their science, and the challenges and opportunities in our current system to recognize and reward those efforts.

The Cabled Observatory Vent Imaging Sonar (COVIS) was initially installed on the Ocean Observatories Initiative’s Cabled Array (OOI-CA) observatory at ASHES hydrothermal vent field on Axial Seamount in July 2018. COVIS recorded the acoustic backscatter from the water-column plumes formed above hydrothermal sources and the seafloor within the sonar’s field-of-view until Oct 2018, when an instrument malfunction suspended regular data-collection procedures. In July 2019, COVIS was redeployed after repairs and has since been collecting data at full capacity. Here, we present a comprehensive analysis of the acoustic backscatter data recorded by COVIS along with the in-situ temperature measurements in 2018 and 2019. The results demonstrate significant influences of ocean tides and bottom currents on diffuse hydrothermal discharge within ASHES. In addition, comparison with local seismicity shows a positive correlation between diffuse hydrothermal venting and the seismic activity in the vicinity of the vent field, which provides evidence for an intimate connection between hydrothermal activity and geological processes during the dynamic period leading up to the next eruption of Axial Seamount. Overall, our results showcase the capabilities of underwater acoustic techniques as remote-sensing tools for long-term, quantitative monitoring of seafloor hydrothermal discharge.

Land use and land cover changes (LULCC) associated with urbanization affect watershed functions and services through fundamental alteration of biogeochemical cycles. Quantifying the potential changes in water, carbon, and energy due to urbanization helps sustainable city planning and integrated watershed management. We hypothesize that ‘impacts of urbanization do not create equal’. We conducted two case studies in the US and China at watershed to national scales to show how urbanization affect watershed hydrology, meteorology, and Gross Primary Productivity (GPP). We used both empirical data and ecohydrological models including WaSSI, SWAT, and MIKE SHE. We used stepwise regression and geographically weighted regression models to assess the variable impacts of urbanization on watershed water and carbon balances across a large disturbance and climatic gradient. We show that LULCC may overwhelm the impacts of climate warming on hydrology and urban microclimate (Urban Heat Island and Urban Dry Island) in the humid southern China. We found that the impacts of urbanization on both water yield and GPP are more pronounced in the area with high precipitation and forest covers. The magnitude of changes in ecosystem functions were influenced by many factors such as the background climate (high precipitation vs. low precipitation), previous land use and cover types and land use and cover changes, and the magnitude of urbanization (change in % impervious surface). We conclude that effective environmental management measures and strategies such as maintaining forest vegetation and wetlands to mitigate the negative effects must be designed to fit local watershed conditions.