Ubinas volcano has produced moderate explosive eruptions during the last ~500 years. With 26 eruptive periods, this composite cone is the most active volcano in Peru. The 2006–2009 and 2013–2017 eruptions impacted people, agriculture, and livestock within 15 km of the vent. On 24 June 2019 a new eruptive cycle started with minor emissions of tephra and aerosols. Activity increased on July 19 with an explosion beginning at 2:30 AM (local time). At that time, seismicity also increased with a predominance of LP-type signals. Two clearly differentiated and wind-controlled volcanic plumes were observed. Initially, the plume reached 6500 m above the summit and the main dispersion axis was ESE, dispersing ash as far as 300 km away to the villages of Jesús de Machaca and Catacora, Bolivia, where ash fall disrupted people’s daily activities. While the first plume was still active, a 1200-m-high secondary plume developed and was dispersed to the SE, reaching more than 200 km away into the Tacna region (Peru). After July 19, the SO2 emission rate increased reaching 9600 TN/day on July 23. The tephra fall on July 19 and gas emissions forced Civil Defense authorities to subsequently evacuate residents living in the valleys around Ubinas within 15 km of the volcano. Just after the tephra fall on July 19, deposit thickness was measured along the secondary dispersion axis, where the nearest populated and most impacted areas are located. The accumulation of lapilli and ash during the July 19 eruption reached 7 mm in the village of Ubinas, 5 mm in Tonohaya, 4 mm in San Miguel, 3 mm in Escacha and Huatagua, 2 mm in Huarina and 1 mm in Matalaque, ~20 km away. Fine ash accumulation was also reported at the Quellaveco mine, 90 km to the SE. Samples collected at 3.2 and 6 km from the vent allowed three types of juvenile clasts to be differentiated; dark- and light-gray scoria and dense, dark-gray lithics. Some juvenile clasts have bands of dark and light material, suggesting a partial mixing (mingling) of compositionally different magmas, which might have triggered the eruption. Based on the variety of juvenile clasts and unprecedented SO2 emission rates compared to the two past eruptive periods, we expect stronger eruptive activity or at least a long-lasting eruptive cycle.

Considering that the instrumental climate record covers a period of about a century, it becomes necessary to use paleoclimatic records/models to explore the stability of the climatic variability and investigate the robustness of the teleconnections of the past. It is important to identify if the observed patterns in the current period persist over the last millennium when the changes in the orbital induced climate variations are negligible. In several studies on climatic causality crosscorrelation functions are used and the analysis is based on the relationship between atmospheric structures in pairs, a procedure that has several limitations in the elucidation of the network of possible connections. To mitigate these barriers, this work uses Partial Directed Coherence (PDC) and kernel nonlinear Partial Directed Coherence (knPDC) to allow the inference of the linear or nonlinear couplings between the climatological patterns, respectively. Connections between the two groups of climatic indicators in the last millennium were observed from 850 to 1850. The first group comprises the El Nino-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Atlantic Interhemispheric SST Gradient (GTA) and the second, Antarctic Oscillation (AAO), El Nino-Southern Oscillation (ENSO), Pacific-South American (PSA1, EOF2) and QuasiBiennial Oscillation (QBO). The climate indices were computed from a weighted average set of climate model simulations of PMIP3, which represent simulations oriented to the past climate in the climate projection models of CMIP5. For the first group, no significant results were observed on the low-frequency band, observing only linear relationships between the Pacific and Atlantic Oceans. For the second group, the causal analysis point to linear relationships between ENSO↔AAO, and nonlinear between ENSO↔PSA in the low and high band and QBO↔AAO, QBO↔ENSO and QBO↔PSA in the low-frequency band. In summary, the results indicate a higher nonlinear connection between low-frequency phenomena.

The GEOICE project was a collaborative instrumentation development effort funded by NSF and undertaken by Central Washington University, New Mexico Tech, and the Incorporated Research Institutions for Seismology (IRIS). Born out of a desire to facilitate additional seismic exploration of polar regions, the GEOICE project developed a multi-modal pool of seismic equipment for deployments in harsh polar environments, with the signature capability of recording the seismic wavefield with minimal aliasing. The completed instrumentation set is available as a community resource which expands on the IRIS PASSCAL Polar instrument pool. A significant amount of effort was put into testing the new equipment pool by the staff at the IRIS PASSCAL Instrument Center. Over the past several years this included both testing at the facility, as well as field testing of sensors, data loggers, and power systems in Alaska and Antarctica. The final equipment pool consists of 10 posthole polar-rated broadbands, 55 compact posthole polar-rated broadbands, 65 next-generation polar-rated dataloggers, and 200 all-in-one nodal-style high-frequency seismometers. Through a combination of design and form-factor, this pool will expand on and improve the instrumentation needed to perform high-quality seismic investigations of Earth’s ice-covered regions with reduced logistics and power requirements, while enabling spatially dense observations over a very wide frequency range. This new instrumentation can be used to study a variety of phenomena in ice-covered regions, recording signals from the solid Earth, glacier movement, liquid water flow and other relevant signals. Thus, these instruments will be a key tool for making observations of the interaction of the solid Earth with the cryosphere and atmosphere to better understand how drivers such as climate change impacts these systems.

The LASP Interactive Solar IRradiance Datacenter (LISIRD), lasp.colorado.edu/lisird, is a website where researchers can discover, visualize, and download solar data from a variety of space missions, instruments, models, and laboratories. LISIRD focuses on making heliophysics research as effortless as possible by making solar data openly available and easy to analyze through an intuitive user interface, detailed metadata, interactive plotting capabilities, and a catalog of over 75 datasets. This poster will discuss how LISIRD currently demonstrates, and aspires to better comply with, the TRUST Principles (Transparency, Responsibility, User Community, Sustainability, and Technology). Topics will include metadata efforts to improve dataset transparency, usability testing to further understand the needs of user communities, and how we designed our current technology stack to make development and maintenance easier and more sustainable.

Finding quality solar data can be difficult, if not cumbersome at best, especially for students and early career researchers. The trend of having static files in an obscure format served in a hidden directory on some seemingly random server certainly doesn’t help the situation, not to mention the datasets that are only accessible via a researcher’s hard drive. The LASP Interactive Solar IRradiance Datacenter (LISIRD), lasp.colorado.edu/lisird, seeks to alleviate many of these pains. LISIRD is a website where students and researchers can discover, visualize, and download solar data from a variety of space missions, instruments, models, and laboratories. LISIRD focuses on making heliophysics research as effortless as possible by making solar data openly available and easy to analyze through an intuitive user interface, detailed metadata, interactive plotting capabilities, and a catalog of over 75 datasets. This poster will demonstrate the key features of LISIRD, provide details on the datasets it serves, outline future plans for improvement and growth, and discuss how it can be used as a valuable resource in space physics curricula.

Changing characteristics of precipitation extremes have been reported mainly using parameters like the frequency of occurrence and the magnitude. As climate changes, the spatio-temporal characteristics of rainfall extremes are also likely to get modified. Though there exist studies noting the changing the temporal distribution, the spatial extent of extreme rainfall events has received less attention. We show that 31% of the fractional increase in the number of rainfall extremes of the Indian summer monsoon from 1951 to 2015 is size-change related. We find that the average size of rainfall extreme is significantly increasing after 1980. Depending on the number of connected grids experiencing simultaneous extreme rainfall, we classify them as small, medium and large events. 90 % of large events have occurred after 1980 and these have the strongest rainfall intensity among all types. They are more likely to cause floods, hence important. These events are invariably associated with a monsoon low-pressure system (LPS) and occur in the southwest sector of an LPS within 400 km from its centre. Strong surface pressure anomalies that persist for more than a week are present in different parts of the globe when these events occur, suggesting preferred planetary-scale conditions that favour their formation. Thus giving hopes of their advanced prediction and facilitating flood hazard mitigation.

The recent discovery of thousands of protoplanetary disks and exoplanets has revealed that planet formation is a very efficient process in nature. There have been several theories to describe the many steps along this process, but it remains difficult to discover planets surrounding young stars. Thanks to its unprecedented angular resolution and sensitivity at radio wavelengths where the emission from the circumstellar material is optically thin, the future ngVLA telescope has the potential to transform our understanding of planet formation. In this presentation I will highlight the unprecedented imaging capabilities of the ngVLA using theoretical models of protoplanetary disks with varying planet and stellar masses. These theoretical models showcase the temporal evolution of the separation of gas and dust that in turn forms gaps and rings within the protoplanetary disk. These images will help shed light on how planets interact with disks and young stars, as well as on the properties of forming exoplanetary systems. Our findings suggest that the ngVLA would be capable of detecting the signatures in the disk of terrestrial planets at few astronomical units from the host star.

Blue carbon ecosystems such as mangroves and seagrass meadows (coastal marine ecosystems dominated by halophytic vascular plants) are regarded as a global carbon dioxide (CO2) sink supported by high net community production. A part of the excess organic carbon (OC) production by these ecosystems is stored for a long term as persistent OC in underlying sediments, while the rest is exported to outside the system (open ocean) without being remineralized. In order to properly assess the role of blue carbon ecosystems in the global carbon cycle, the fate of exported OC must be elucidated. A part of the OC exported to the open ocean may be decomposed and remineralized quickly while in the ocean surface and return to the atmosphere as CO2. In such a case, the export production cannot be regarded as a long-term carbon sink. On the other hand, the exported OC may either be (1) stored for a long term in the offshore sediment as detrital OC, (2) stored as refractory dissolved organic carbon (RDOC) in seawater, or (3) settled down in the bathypelagic layer and subsequently remineralized into CO2 there. In these cases, carbon does not return to the atmosphere in the short term and can be included in net CO2 sequestration. It is obvious that carbon pools corresponding to these three processes exits in the ocean. However, it is technically extremely difficult to clarify whether and to what extent carbon derived from the blue carbon ecosystems is contained in these pools. The purpose of this study is to demonstrate by using environmental DNA techniques that OC derived from the blue carbon ecosystems can be transported to and stored in open ocean sediments. As a case study, coastal area off the west coast of Busuanga Island, Philippines, was set as study site, where natural coral reefs, seagrass beds, and mangroves are relatively well preserved. DNA probes for MatK sequences (part of chloroplast DNA) of two mangrove species (Rhizophora mucronata, Sonneratia alba) and two seagrass species (Enhalus acoroides, Thalassia hemprichii) as well as ITS sequence (part of nuclear DNA) of R. mucronata were designed. Then, the DNA copy numbers of respective sequences contained in extracts from surface sediment samples were quantified by the qPCR method. In addition, the organic and inorganic carbon concentrations and the specific surface area of the surface sediment samples were determined, and the origin of the sediment OC was assessed using a carbon stable isotope mixing model. During sample collection, seismic profiling with a sub-bottom profiler was also conducted to evaluate thickness of sediment accumulated in the studied area. In this presentation, we summarize the results of these surveys to evaluate the areal extent to which seagrass- and mangrove-derived OC is transported and stored in relatively intact state, and identify environmental conditions that influence the accumulation in open ocean sediments of OC derived from blue carbon ecosystems. Difficulties in conve

PTFO 8-8695 (CVSO 30) is a star in the 7-10 million year old Orion-OB1a cluster that shows brightness dips that resemble planetary transits. Although strong evidence against the planet hypothesis for this system has been presented, the possibility remains debated in the literature. To obtain further clues, we inspected data from the NASA TESS and the ESA Gaia missions. The Gaia data suggest that PTFO 8-8695 is a binary: the photometric data show it to be over-luminous with respect to members of its kinematic group, and the astrometric data are inconsistent with a single star. The TESS light curve shows two different photometric periods. The variability is dominated by a sinusoidal signal with a period of 11.98 hr, probably caused by stellar rotation. Also present is a 10.76 hr signal consisting of a not-quite sinusoid interrupted by hour-long dips, the type of signal previously interpreted as planetary transits. The phase of the dips is nearly 180° away from the phase of the originally reported dips. This makes the dips difficult to explain as planetary transits. Instead, we believe that PTFO 8-8695 is a pair of young and rapidly rotating M dwarfs, one of which shows the same “transient-dip” behavior that has been seen in at least 5 other cases. The origin of these transient dips is still unknown but likely involves circumstellar material. Combined with recent counter-arguments against the planetary nature of CI Tau b and V830 Tau b, the rejection of the planetary hypothesis for PTFO 8-8695b suggests that the number of known hot Jupiters younger than 100 Myr is approximately zero.

An NSF EarthCube-funded project supported a field-based workshop designed to evaluate and refine the sedimentology/stratigraphy portion of the StraboSpot digital data management system. Eleven academics attended the workshop, representing a spectrum of career levels and specialties. The participants teach classes in sedimentology and conduct sedimentary research, but had not used any previous digital mobile apps in the field. The field component focused on learning the basic functionality of the StraboSpot app as a method of collecting digital data in the field. On the first day, teams of 2-3 participants measured a stratigraphic section in a highly visited locality of the well-studied Book Cliffs of central Utah. Teams saw how the vocabulary and spot functionality worked to collect sedimentary field data and to generate stratigraphic columns. The second day was spent measuring a more complex mixed carbonate-clastic sequence in the San Rafael Swell (Utah). Half of the third day was spent in discussion on major issues with workflow/vocabulary and getting feedback on how to simplify and streamline descriptive data collection functions (stratal attributes), and reviewing the more challenging interpretation functions (processes, depositional environments, and architecture). A major discussion point was how best to handle data collection and stratigraphic plotting of ‘interbedded’ intervals. As a result of the workshop, we streamlined workflow options and refined portions of the vocabulary. This field testing followed up on two previous workshops that solicited expert advice to develop the program categories and basic vocabulary for the sedimentary community. Overall, workshop participants were enthusiastic about the potential of digital data systems, and the ability to link annotated photographs and sketches to georeferenced localities. All participants indicated they were inclined to use StraboSpot in both teaching and research, particularly with versatile and customizable options.

Episodic volcanic eruptions are often either not considered in future climate projections, or represented in terms of a constant volcanic forcing. This conventional representation of volcanic eruptions in climate models does not account for how climate change might affect the dynamics of volcanic plumes and the stratospheric sulfate aerosol lifecycle and, ultimately, volcanic radiative forcing. The height of eruptive plumes is indeed sensitive to atmospheric conditions such as stratification and the strength of wind. In addition, climate change will affect tropopause height, the Brewer Dobson circulation and stratospheric temperatures which all govern volcanic sulfate aerosol cycle. A recent study showed that for tropical eruptions, these changes would either lead to a dampening or an amplification of volcanic forcing depending on the eruption intensity. In this study, to account for volcano-climate interactions in future climate projections, we present a new modelling approach through coupling a 1-D plume-rise model (Plumeria) with an Earth System model (UKESM). In this approach, each time a volcanic eruption of prescribed intensity (i.e., mass eruption rate) and SO2 mass occur, atmospheric conditions simulated by UKESM are passed interactively to Plumeria which then computes the corresponding height of eruptive plumes. Volcanic SO2 is then injected at the same height in UKESM stratospheric aerosol module. With this new methodology, plume heights are consistent with the climate conditions simulated by UKESM. Our study thus represents a first attempt to consider the impacts of climate change on volcanic eruptions in an Earth System model, which allows us to better evaluate the climate impacts of volcanoes under global warming.

An accurate assessment of hydrometeorological variables/ observations over an urban area is crucial to policy-makers and civic bodies to address an extensive range of water resources and environmental problems for informed decision-making related to the water distribution system and drainage networks. This necessitates the establishment of hydrometeorological monitoring networks that can efficiently obtain consistent and reliable information about the spatiotemporal variability of multiple hydrometeorological observations while being economically sustainable. However, the urban catchments especially in underdeveloped and developing countries are often subjected to spatial, environmental as well as monetary limitations which hinders the application of conventional approaches followed to set up the hydrometeorological networks. With this context, we propose a novel rationalization framework to record numerous hydrometeorological variables and acquire maximum information at an optimal cost. We have attempted to combine a multivariate statistical technique, Principal Component Analysis (PCA) with a multi-attribute decision-making method, Technique for Order of Preference by Similarity to Ideal Solutions (TOPSIS) to rank the significant hydrometeorological stations of an existing Automatic Weather Stations (AWS) network. It is observed that the set of rationalized AWS network obtained from this framework can capture the spatiotemporal information of the hydrometeorological variables considered in this study as efficiently as the entire AWS network. Additionally, the comparison of flood inundation and hazard maps derived from a 3-way coupled hydrodynamic flood modeling framework for the rationalized and original network also reflects its credibility to capture the flooding characteristics for the catchment. This proposed framework has been applied over Mumbai city, India, a major flood-prone area, and is characterized by high spatiotemporal variability of hydro-meteorological observations and space constraints due to dense population. This framework is generic and can be employed to reevaluate the prevailing hydro-meteorological networks in other catchments and help in the reduction of the maintenance cost while efficiently capturing the variability of observations.

Geologic carbon storage (GCS) is part of a process known as carbon capture, utilization, and storage (CCUS); being adopted to mollify extreme weather events (global warming) as a result of CO2 emissions and improve energy production. Previous studies have shown promising potentials of permanent CO2 storage in depleted shale reservoirs. In this study, we experimentally and analytically investigate the impact of microbially-altered mechanical properties on carbon storage in the Niobrara shale reservoir, using a cultured solution and shale samples from Niobrara formation. Firstly, we obtained the properties of the untreated samples. Secondly, we treated and cultivated the samples with the cultured solution at specific conditions. Further, we obtained the new properties of the treated shale rocks. Lastly, we show the impact of the altered properties on CO2 storage integrity in unconventional shale reservoirs. Our results suggest that in shale reservoirs, biogeomechanical alterations can enhance the long-term integrity of geological sequestration of atmospheric CO2, by mitigating any deep subsurface potential leakage to the atmosphere.

Nowadays, it is so important in saving our economic activity and evading the disasters caused by terrestrial electromagnetic effects to predict both temporal and spatial scales of the geomagnetic disturbances based on in-situ solar wind observations. Recently, Neural Network (NN) is one of the notable techniques for the predictions of the magnetospheric activities. However, NN has a problem referred to as ‘black box’, which is difficult to extract which solar wind parameters are the most important for prediction. In this study, we examine a significant relationship between Kp index, which represents the magnetospheric activity, and the solar wind conditions based on an interpretable neural network: ‘Potential Learning (PL)’. A feature of the PL is to make a network that can understand the input variables by learning the “input potentialities”, which are indices calculated using the variances of the solar wind parameters as input variables. In this study, we investigate the magnetospheric activity profile when the Interplanetary Magnetic Field (IMF) oriented southward (Bz < 0). As the input solar wind data, we utilize the two components of the magnetic field (Bx, By) in GSE, and solar wind flow speed, and number density during 20 years between 1999 and 2018. Furthermore, we divide the associated values of Kp into two groups (targets): ‘Kp = 6- to 9 (positive target)’ and ‘Kp = 0 to 1+ (negative target)’. Because the data number of positive target was smaller than that of negative target, the negative target samples are randomly selected so that the data numbers of both targets become equal. Based on the PL neural network, we obtain two important results; 1) the solar wind plasma flow speed might have the most influential in the increase of the Kp index, and 2) as the secondary influential parameter for the Kp increase, the solar wind proton density is considered. In the presentation, we will discuss feasibility of the application to the prediction of the magnetospheric activity based on the solar wind parameters.

Traditional crop irrigation relies on farmers’ knowledge on plant, soil, and weather. Irrigation system is one of the key facilities in Nebraska to supply sufficient water resource to farming activities. However, in large scale farming, it is not rare to see plant get over irrigated while the marginal economic benefit of irrigation decreases significantly. The WaterSmart system combines various data sources to provide irrigation guidance to help farmers making better irrigation decision. To support the WaterSmart system, a semantic irrigation ontology is developed to understand these Agro-Geoinformatics data with local planting knowledge such as water usage during different crop stages. Local knowledge on crop irrigation has already been studied and published by Institute of Agriculture and Natural Resources, Nebraska Extension at the University of Nebraska-Lincoln. The ontology is built using Webprotégé with using HermiT as the reasoner. The ontology focuses on two main crops in Nebraska: corn and soybean. Final product is released on GitHub repository and registered with w3id thru persistent uniform resource locator (PURL). All software and tools were used to develop the ontology are open source. The ontology is used to represent irrigation knowledge and host concepts in the irrigation decision making portal.

Purpose:Flooding following heavy rains precipitated by hurricanes/tropical storms has previously been shown to increase fecal-oral diseases, vector-borne disease transmission and pregnancy complications during or following inundation. Remote sensing can be used to spatio-temporally resolve inundation extents for subsequent analysis of risks associated with flooding at a finer scale. Here we combined earth observations of the flooding caused by Hurricane Harvey in 2017 with Emergency Department (ED) visit data to evaluate health outcomes associated with flooding.Methods:Our study area included 1073 flooded and 1809 non-flooded census tracts in Texas which were categorized using the inundation maps from Dartmouth Flood Observatory. These maps were created using Sentinel and MODIS satellite imagery captured between 28th Aug - 4th Sep 2017 following the landfall of the hurricane. ED visits in the study area were obtained from Texas Department of State Health Services. A controlled interrupted time series design was employed using ED visits from non-flooded tracts as the control series and ED visits before a week of the landfall and through 2018 as control period. Poisson regression using generalized estimating equation with census tracts as the group variable was used to estimate the relative risk of the health outcomes associated with flooding during and following the flooded days, adjusting for the age, ethnicity, race, sex of the patient, day of week, month and year trends. Results:Flooding was associated with a 35% (95% CI: 22%-48%) increase in risk for insect stings and 24% (17%-31%) increase in risk of pregnancy complications during the flood period. Similarly, relative risks were also elevated (>1) for drowning, hypothermia, and intestinal infectious diseases in the flooded tracts. Also, in the months following the flood period, the relative risk was still elevated (>1) for pregnancy complications and insect stings while asthma and acute respiratory infections showed decreased risks. Conclusion: Earth observations have helped in understanding the health risks that are related to flooding. These earth observations can in turn be used to identify specific communities with increased health risks during and following flooding events.

One of the prominent effects of space weather is the variation of electric currents in the magnetosphere and ionosphere, which give rise to rapid geomagnetic field variations on the surface of the Earth. These Geomagnetic Disturbances (GMDs) can be highly localized and large amplitude. Because the causes of localized GMDs are unresolved, we seek to identify the physical drivers of these localized dB/dt spikes measured by ground magnetometers. We use the Space Weather Modeling Framework (SWMF) models to simulate the magnetosphere and reproduce these small-scale spikes. We use the operational Geospace configuration, which couples a global magnetohydrodynamic model to a height-integrated ionospheric electrodynamics solver and a kinetic ring current model. We run a series of simulations with increasingly higher spatial resolution to resolve small scale dB/dt dynamics. We quantify the success of the model against observation using Regional Station Difference (RSD), a metric calculated using dB/dt or geoelectric field to pinpoint when a single magnetometer station records a significantly different value than others within a given radius. We discuss future work to improve the model’s accuracy and our understanding of these small-scale structures.

MagIC (earthref.org/MagIC (https://www2.earthref.org/MagIC)) is an organization dedicated to improving research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock and paleomagnetic data with portals that allow scientists and others to access to archive, search, visualize, download, and combine versioned datasets. A recent focus of MagIC has been to make our data more accessible, discoverable, and interoperable to further this goal. In collaboration with the GeoCodes/P418 group, we have continued to add more schema.org metadata fields to our data sets which allows for more detailed and deep automated searches. We are involved with the Earth Science Information Partners (ESIP) schema.org cluster which is working on extending the schema.org schema to the sciences. MagIC has been focusing on geo- science issues such as standards for describing deep time. We are also collaborating with the European Plate Observing System (EPOS)’s Thematic Core Service Multi-scale laboratories (TCS MSL). MagIC is sending its contributions’ metadata to TCS MSL via DataCite records for representation in the EPOS system. This collaboration should allow European scientists to use MagIC as an official repository for European rock and paleomagnetic data and help prevent the fragmenting of the global paleomagnetic and rock data into many separate data repositories. By having our data well described by an EarthCube supported standard (schema.org/JSON-LD), we will be able to more easily share data with other EarthCube projects in the future.