The realization that changes within the Arctic have profound impacts on ecosystems and human populations across the globe has motivated greater attention. Yet major gaps remain in our understanding of the feedbacks, response, and resilience of coastal Arctic ecosystems, communities, and natural resources to current and future pressures. Most importantly, the Arctic coastal zone, a vulnerable and complex contiguous landscape of lakes, streams, wetlands, permafrost, rivers, lagoons, estuaries, and coastal seas—all modified by snow and ice—remains poorly understood. To improve our mechanistic understanding and prediction capabilities of land-ice-ocean interactions in the rapidly changing Arctic coastal zone, our team proposed a Field Campaign Scoping Study called Arctic-COLORS (Arctic-COastal Land Ocean inteRactionS) to NASA’s Ocean Biology and Biogeochemistry Program. Arctic-COLORS aims to quantify the response of the Arctic coastal environment to global change and anthropogenic disturbances – an imperative for developing mitigation and adaptation strategies for the region. Arctic-COLORS is unprecedented, as it represents the first attempt to study the nearshore coastal Arctic (from riverine deltas and estuaries out to the coastal sea) as an integrated land-ocean atmosphere-biosphere system. The overarching objective of Arctic-COLORS is to quantify the coupled biogeochemical/ecological response of the Arctic nearshore system to rapidly changing terrestrial fluxes and ice conditions, in the context of environmental (short-term) and climate (long-term) change. The science of our field campaign will focus on three key science themes and several overarching science questions per theme: (1) Effect of land on nearshore Arctic biogeochemistry (2) Effect of ice on nearshore Arctic biogeochemistry (3) Effects of future change (warming land and melting ice) on nearshore Arctic biogeochemistry This field campaign will be composed of an integrative measurement approach utilizing a broad range of proven sampling approaches from a multitude of platforms including autonomous vehicles to achieve sufficient seasonal and spatial coverage to resolve the science questions proposed by the Arctic-COLORS team as well as remote sensing and development of coupled physical-biogeochemical models.

We present a neural network (NN) based algorithm for the retrieval of cloud and aerosol properties from above cloud aerosol (ACA) scenes. The large state space explored in ACA scenes causes traditional retrieval approaches slow and complicated. This is especially true for optimal inversion retrieval approaches, where a growth in the number of dependent variables can drastically complicate and slow the retrieval search. Our NN retrieval is applied to data from the airborne Research Scanning Polarimeter (RSP), which measures both polarized and total reflectance in the spectral range of 410 to 2260 nm, scanning along the flight track at ~150 viewing zenith angles spanning the angular range between -60˚ to 60˚. We apply this algorithm to field campaign data from the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) 2016 and 2017 campaigns and compare to results obtained from other algorithms.

To fully understand the constitutive parameters and the associated mechanism in the velocity-weakening behavior of pyroxene observed in a previous study (He et al., 2013), we employed pure augite (clinopyroxene) as simulated gouge sample to run velocity stepping sliding tests under hydrothermal conditions with temperatures of 101-607 °C, effective normal stress of 200 MPa with 30 MPa pore pressure and axial loading rates of 0.1-1.0 μm/s. From our experiments, we found that: (1) Velocity-strengthening behavior was observed at temperatures of 101-203 °C, the steady-state velocity dependence transitioned to velocity weakening at ~215 °C, and the velocity weakening persisted up to 607 °C, the highest temperature in our experiments. The absolute (b-a) values were revealed to range from 0.0009 to 0.0014, and the inferred average b/a values ranged from 1.15-1.18, both indicating quite weak velocity weakening at temperatures of 303-607 °C. (2) Inferred constitutive parameters through numerical fitting to rate and state friction laws show that the healing effect of friction (b value) has an increasing trend with temperature increase up to 403 °C, indicating an Arrhenius-type thermally-activated creep mechanism behind the healing effect. (3) In addition to microstructural observation of deformed samples that shows remarkable size reduction (crushed grains reduced to scales typically below 1-2 μm) in both intensely sheared regions and moderately sheared regions, ubiquitous precipitated particles (50-100 nm) with platy morphologies were observed to attach to the surfaces of crushed grains, which are typical signatures of intergranular pressure solution process, suggesting that pressure solution was commonly activated at intergranular contacts. (4) No recognizable crystalline plasticity was observed. Our microstructural observation together with the comparison of experimental data with model’s prediction, implies that intergranular pressure solution process at the frictional contacts may be the most likely mechanism operating at the frictional contacts and governing the healing effect for augite.

Increased demand for precision agriculture is reflected by a global rise in greenhouse food production. To maximize crop efficiency and yield, commercial greenhouses require live monitoring of growth conditions. Recent advances in open-source hardware allow for environmental sensing with the potential to rival lab-grade equipment at a fraction of the cost. This study introduces a high-resolution sensor package that costs less than $400. Consisting of microcontrollers and small open-source hardware, the sensor package can be deployed on the HyperRail, a modular conveyance system developed in Oregon State University’s OPEnS Lab. The system can then provide data from multiple sensing locations at the cost of a single package. Sensor data, including CO2, temperature, relative humidity, luminosity and dust/pollen, is saved to a microSD card as the HyperRail-mounted package travels throughout the greenhouse. A wireless GFSK nRF connection to a network hub allows the broadcast of a live stream of environmental conditions online. CO2 monitoring efforts are especially relevant to greenhouse management as artificially elevated levels can significantly increase plant growth. Results from calibration in the lab show that the K30 CO2 sensor ($85) can be calibrated to be accurate within less than 10 ppm of industry standard equipment costing up to $10,000. Our sensor package’s instructions, code, wiring, and 3D-printed enclosures are openly-published on GitHub. Addition of an RFID tag soil moisture sensing system is anticipated. Actuators may also be integrated in the future, allowing the system to automatically adjust greenhouse controls (i.e. CO2, water) in response to sensor readings. The affordability of this package can make precision agriculture more accessible in developing countries where conventional monitoring systems are not feasible. Efficient use of resources and the ability to adapt to local challenges with input from the open-source community has the potential to improve global crop yield.

Seismograms recorded at an array of 10 closely spaced seismometers in the western United States are stacked about the ScP phase and display a complex set of phase arrivals in addition to ScP. One dimensional forward modeling with ultra-low velocity zone structures are unable to match the observed waveform. Forward modeling with core-rigidity zone structures, where S-waves can propagate in a thin layer below the core-mantle boundary, provide reasonable waveform fits to the largest amplitude phases. The basic core-rigidity zone model has thickness of 1.1 km, shear wave velocity of 1.8 km/s, and density decrease of 10%, although tradeoffs in model parameters are observed. Waveform fits are insensitive to small changes in P-wave velocity in the core-rigidity zone. To match trailing smaller amplitude phases, S-wave multiples are modeled in the core-rigidity zone. Cross correlation of ScP waveforms from 392 EarthScope seismometer sites surrounding the small array site shows discrete patches of similarity to the above model. These results point to a spatially large but patchy core-rigidity zone beneath Mexico and adds to the small set of previous core-rigidity zone observations globally.

Stable Ca isotopic composition (δ44/40Ca) of crustal carbonates are typically lighter than that of the bulk silicate Earth value (~1.05 ‰). Hence, δ44/40Ca of mantle-derived rocks can potentially trace recycled crustal carbonates into the mantle. We report the Ca isotopic compositions of globally distributed carbonatites (n = 46), which are unique igneous rocks with more than 50% modal carbonate minerals, with eruption ages ranging from Precambrian until recent. The δ44/40Ca (w.r.t. SRM915a) of these carbonatites show a large range (0.35 ‰ to 1.26 ‰), which is significantly higher than the analytical uncertainty (0.08‰) of the measurements performed using TIMS at CEaS, IISc. These samples are well-characterized in terms of their major and trace element geochemistry as well as Nd, Sr, B, C, and O isotopic compositions for selected samples. No systematic trend is observed between δ44/40Ca of the carbonatites and their eruption ages. Significant variability is observed in δ44/40Ca values in samples from individual provinces including those from the Oka complex in Canada (0.44 ‰ – 1.26 ‰, n= 8), Ambadongar (0.53 ‰ – 1.1 ‰, n= 8) and the Newania complexes (0.44 ‰ – 0.83 ‰, n= 4) in north-west India, the South Indian carbonatites (0.65 ‰ – 0.91 ‰, n= 3) and carbonatites from the Palabora complex in South Africa (0.35 ‰ – 0.84‰, n= 3). The δ44/40Ca of carbonatites from Oka, Newania and the Ambadongar show strong correlations with Ca/Mg, Ca/Fe as well as CaO and MgO contents. The δ44/40Ca of the Oka and Ambadongar carbonatites show correlated variations with their Mg# and K/Rb ratios, respectively. The large variability in δ44/40Ca of global carbonatites is explained in terms of: (1) presence of isotopically lighter ancient subducted carbonates in the mantle-source regions and carbonate metasomatism of the mantle, (2) partial melting and differentiation of the carbonatite magma and (3) heterogeneity in the source-mantle mineralogy of carbonatites.

Airborne allergic pollen is a well known trigger for several cases of public health issues affecting millions of people. The effect is highly prevalent in the temperature region, especially in the North American region and Europe. For example, about 50 million Americans are affected by pollen caused allergy and similarly, studies show quite a significant population of Europe is affected. Contrary to the higher abundance of pollen in rural areas, pollen allergy is severe in urban areas than rural environments. Of all sources, it is the Ambrosia pollen that affects most due to its abundant production, strong allergic potency and its high prevalence near urban areas. Hence estimating the concentration of allergic pollen in the ambient atmosphere and notifying the public is crucial for people with allergies and health professionals who care for them. In this workshop, we present estimation of allergic pollen (particularly Ambrosia pollen) using advanced machine learning methods and input parameters from a suite of sources ranging from land surface to global reanalysis models and NEXRAD weather radar measurements at location of Tulsa, Oklahoma. We will present results of the machine learning model tested using an independent dataset and characterization of each atmospheric and land surface parameters’ importance for the machine learning estimation.

Interferometric synthetic aperture radar (InSAR) measures surface deformation from repeated passes of satellites or aircraft and has become an important tool to study geophysical phenomena such as earthquakes. However, InSAR data analysis is challenging due to atmospheric water vapor that can mimic the effects of Earth deformation and thus lead to wrong interpretations. We present preliminary results on how to differentiate between tropospheric effects and surface deformation from earthquakes using a convolutional neural network. As earthquake training sets are sparse, our approach leverages transfer learning techniques for tropospheric patterns from areas where deformations are known to be mostly absent over short time periods, and classifies specific areas of interferograms to reflect regions that are dominated by deformation or tropospheric noise. The applicability of the training set to a new area may depend on the similarity of the two climates. Examples of tropospheric delays are shown from interferograms constructed from Sentinel-1 data over part of southern California with short temporal baselines, and examples of deformation are taken from interferograms generated using Okada models. Our classifier is tested on data from the 2018 Oaxaca earthquake in Mexico from Sentinel-1. This work is a step towards using neural networks for a fine-granular tile-based validation of interferograms and automatically removing unwanted effects from InSAR signals, as well as towards enhancing the agility of disaster response programs. The open source code is available in the PyInSAR package on GitHub under the MIT license. We acknowledge support from NASA AIST80NSSC17K0125 (PI Pankratius) and NSF ACI1442997 (PI Pankratius).

Europe is covered by various networks of GNSS stations maintained by different agencies with different technical and scientific objectives. The EPOS-IP (European Plate Observing System – Implementation Phase) project aims to harmonize and standardize data collection and processing and to design and establish dedicated products and services that benefit the existence of national and pan-European infra-structures (in particular EUREF), optimized for Solid Earth Research applications.

Sea ice extent in the Bering Sea during the winter of 2017–2018 was the lowest on record with ice cover attaining less than half the long-term average. Mandt’s Black Guillemot (Cepphus grylle mandtii), one of the few Arctic ice-obligate seabirds, typically winters in the Marginal Ice Zone over the Bering Sea shelf, occurring as far south as the shelf break. Adult survival and breeding biology of the species has been studied since 1975 at a breeding colony near Point Barrow, Alaska in the western Beaufort Sea, with nonbreeding distribution and movements monitored since 2011 with light-sensitive geolocators. Preliminary analysis of geolocators retrieved at the start of the 2018 breeding season indicates guillemots wintered further north than in any previous year with most birds remaining near the Bering Strait or in the southern Chukchi Sea. It appears the lack of sea ice in the traditional wintering area and resulting anomalous winter distribution had a major effect on the survival and condition of Mandt’s Black Guillemot in the Western Arctic, although direct causative factors have yet to be determined. Adult overwinter apparent mortality was the highest on record with 32 percent of the birds breeding in 2017 failing to return to the colony, compared to 11 percent apparent overwinter mortality for the period 1976–2013. Of the 70 pairs occupying nest sites in 2018, only 50 pairs produced eggs. Of those 50 nests, nearly one-half had no incubation occur after egg laying. Nonbreeding by established breeders occupying nest sites and abandonment of nests immediately after egg laying were extremely rare in earlier years. The number of breeding birds in 2018 was the lowest in four decades and punctuates a long-term decrease in the population since 1989. Analysis of geolocation and behavioral data from the 2017–2018 nonbreeding period will lend insights into how the anomalous winter sea ice conditions might have contributed to the observed high mortality and poor condition of surviving birds. Decreased prey availability in the Arctic Basin and Bering Strait regions, compared to the southern Bering Sea shelf, could be a factor, as could atypical oceanographic and sea ice conditions in the winter Marginal Ice Zone.

A modified version of the commercially available RheOptiCAD® was developed to examine the conformational changes and break-up of flocs in clay suspensions in microscopic detail, under shearing action. In contrast to the RheOptiCAD®, our device aims to enable the structural observation of suspensions even when coagulation or settling of particles onto the bottom plate of the shear cell occurs. This challenge was met by using an upright modular microscope instead of an inverted one, equipped with a CMOS camera to record the structural evolution of samples as a function of shear. The verification of the design was done by analysing a model system of un-flocculated and flocculated kaolin suspensions. Additional experiments with natural clay (mud) suspensions were performed.

Climate change affects the global water cycle and has the potential to alter water availability for food-energy-water production and the ecosystems services on regional and local scales. In southeastern Brazil, the Cantareira Water Supply System reached unprecedented low levels in January 2015 compromising the water supply for the Metropolitan Region of São Paulo (MRSP). However, there is still few studies investigating the effects of climate change on water availability in this region. Here, we assess the influence of climate change on water availability in the Jaguari Basin, Southeastern Brazil using a modeling approach. This basin covers and area of about 1200 km2 and it is the main source of the Cantareira Water Supply System, responsible for providing water for about 7 million people in the MRSP. To evaluate climate change scenarios, we use the lumped conceptual HYMOD model on daily time step. This model was calibrated and evaluated using daily observed data of precipitation, evapotranspiration, and discharge for the period of 1990 to 2009. To evaluated climate change scenarios, we used data of an ensemble of 17 General Circulation Models (GCMs), downscaled by MarkSim GCM working off a 30 arc-second climate surface spatial resolution forced by two Representative Concentration Pathways (RCP): RCP 4.5 and RCP 8.5. These data were integrated into the HYMOD to projected scenarios (up to 2095) of water discharge. We find values of Nash-Sutcliffe Efficiency Coefficient (NSE) and Coefficient of Determination (R2) greater than 0.80 for the calibration and evaluation period. We also noticed an increase in the peak of runoff and a decrease and baseflow for both scenarios. Such changes reflect in a higher interannual variability, therefore, increasing the risk of drought and flood. In terms of Environmental Flow Requirement, the probability of exceedance Q90, reveal a clear pattern of decreasing, about 23% from 2010 to 2040, and reaching 28% by the end of the century. Our findings indicate that the water discharge could not be enough for the current and future water demand. Our results expose the fragility of the studied basin, presenting a technical and scientific information focusing on guiding the plans and strategies to deal with situations of water scarcity.

The original Evaporometer prototype was designed by the Openly Published Environmental Sensing (OPEnS) Lab at Oregon State University to remotely collect near real-time environmental data, including temperature, humidity, luminosity, and amount of precipitation, and transmit it to a receiver hub, where it can be viewed online by researchers worldwide. This eliminates costly and time-consuming site visits. Deployed during the summer of 2017 in OSU’s HJ Andrew’s Experimental Forest, the prototype failed after three months due to excess moisture entering the enclosure and damaging the hardware. Over its first two months, the prototype performed well, gathered over 90,000 data points, updating every five minutes. To extend the lifespan of the Evaporometer, the enclosure was redesigned to improve weatherproofing, include additional sensors, and improve the accuracy of data readings. These improvements will extend the Evaporometer’s field life, allowing it to reliably gather and transmit data for longer periods of time while the ability to gather albedo measurement expands the device’s sensing capabilities. The upgraded Evaporometer provides researchers with a reliable, low-cost, and open-sourced method of collecting environmental data in locations that may not have previously been feasible.

The Vavilov Ice Cap destabilized in 2013. It reached its highest annual ice loss rate of 4.48 km3/yr between 2015 and 2016, a rate that is more than half of the entire combined ice loss from all the other ice caps in the Russian Arctic. To understand the mechanics of how the surge took place and what will happen in the future, we investigate surface elevation and glacier velocities using the Cryosphere And Remote Sensing Toolkit (CARST), an open-access python toolbox designed for processing temporal changes of high-resolution remote sensing data. We use optical satellite images from WorldView, Landsat, and Sentinel-2 and their derived elevation and velocity products to track the history of the surge between 2010 and the present. We propose that the surge initiated when the ice front overrode weak marine sediments in 2013, leading to a reduction of frontal friction. Velocity time series show that the glacier reached a maximum speed of 25 m/day (9 km/yr) in late 2015, when a piedmont-like ice lobe stretched more than 10 km into the Kara Sea. However, in spring 2017 the glacier slowed down to 7-9 m/day with the development of a new channel inside the piedmont lobe, with new shear margins visible from optical imagery. The channelized flow pushes through the grounded portion of the piedmont glacier, and suggests a further reorganization of resistive forces. The unprecedented evolution of the surge at Vavilov Ice Cap shows a strong connection to the status of the terminus, which might pose general concern for the stability of marine- or lake-terminating glaciers regardless of their locations on Earth.

Numeracy is the ability to understand and interpret numbers. The numeracy skills are required and relevant across all disciplines and especially in STEM majors. The diverse group of underrepresented students from two-year community college was assessed on the knowledge of basic units of measurement and unit conversions in this study. The student performance was assessed in a lesson plan administered during The Numeracy Infusion for College Educators (NICE) Program at Bronx Community College. The students were assessed to identify different units; to be able to perform basic unit conversions; to recognize the scale of bigger and smaller units; and associated vocabulary. The learning goals aimed at developing thinking skills in reading graphs, trends or patterns and develop a habit of comparing the values of measurement in one unit system to another system of units. The students were provided tools to remember the increasing and decreasing trends in the scale of units. The real-life examples were incorporated into the learning process. The assessment was administered at different stages of learning in this lesson plan. This study will present the assessment results of lesson plan administered to a diverse group of underrepresented students from various majors in community college education. The student performance assessment in this lesson plan highlights the urgency to incorporate tools and techniques for numeracy skills across the curriculum in various disciplines of higher education.

Each state and district within the Chesapeake Bay watershed has cooperated with the Chesapeake Bay Program (CBP) to develop local Watershed Implementation Plans (WIPs) that identify the type and quantity of best management practices (BMPs) that, if implemented, are estimated to meet 2025 Total Maximum Daily Load (TMDL) goals for Bay water quality. However, top-down management of large regions, such as the 167,000-km2 Bay catchment, is often necessarily limited by the feasibility of providing implementation plans that are customized by watershed hydro-physiographic characteristics and socio-political considerations. The Bay simulation model divides the catchment into watersheds of approximately 350 km2 each; these watersheds become the Bay model’s smallest overland management unit. We used Bay WIP plans, local information, and a hydrologic model called Topo-SWAT to model three of these smallest-unit watersheds in more local detail. Our smallest management unit became contiguous, similarly managed, cropland areas (i.e., one or several neighboring agricultural fields) and these management units were further divided by the topographic wetness index. Our watersheds represent three distinct hydrological and geochemical regions within the Chesapeake Bay catchment, namely Appalachian Valley and Ridge – karst, Appalachian Valley and Ridge – nonkarst, and Appalachian Piedmont. We modeled three scenarios for each watershed: baseline (pre-WIP), WIP implementation, and “smarter” WIP placement where we targeted BMP placements for cost-effectiveness. We then compared results among scenarios as well as across watersheds. We are interested to see how well the models agree at the watershed outlet, discover cost-effective BMP placements within each watershed that meet WIP goals, and compare our findings across the physiographic regions to determine how they can guide regional planning.

Following the radioactive fall out of the 2011 Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, radiocesium (Cs-137) contaminated soils of forests, uplands, rice paddies and other land uses released contaminated sediments onto neighboring areas and into the creeks and rivers in Iitate Village, Japan. The study used conventional and Cs-137 fingerprinting techniques to determine runoff and suspended sediment discharges to assess the small and large-scale soil redistribution dynamics within contributing areas in two watersheds. Also, we attempted to use Cs-137 fingerprinting to identify spatial and temporal patterns of erosion, transport and sedimentation on hillslopes within those watersheds. Tributaries near the outlet of the 30 km2 Hiso watersheds were simulated at the hillslope and watersheds using the process-based Water Erosion Prediction Project (WEPP) model and the Geospatial Interface for WEPP (GeoWEPP). Besides the simulation of historic soil redistribution events, a particular emphasis was the identification and assessment of various land use and cover changes on the past soil redistribution. Results of the analysis in the post-fallout landscapes enables scientists and farmers as well as natural resources and disaster managers to investigate the consequences of active and passive land use and cover changes on the runoff and sediment dynamics at the plot, hillslope and watershed scales. Especially the behavior of Cs-137 contaminated clay particles in soils and sediments seem to be the key for the success of the measurement, modeling and management techniques. The result of this study has the potential to assist decision and policymaking for stakeholders not only in areas that were impacted by the contamination through radioactive fallout.

In support of our ongoing program to measure coronal magnetic fields using Faraday rotation (the rotation of the plane of polarization when linearly polarized light propagates through a magnetized plasma), we report on measurements of angular broadening of cosmic radio sources as they were occulted by the corona. Angular broadening results from plasma density irregularities elongated along the coronal magnetic field that cause radio wave scattering. In radioastronomical observations, the measured intensity (power per unit area per unit solid angle along the path to the detector) is the convolution of the true radio source intensity with a point spread function (PSF, the effective response of an imaging system to a point-like source). In most radio interferometric applications, the PSF is simply the synthesized beam; however, when observing through a turbulent plasma like the corona, the PSF is the convolution of the synthesized beam with the power pattern of the angular broadening. The angular broadening acts to reduce the measured intensity of a radio source. This can have important consequences for coronal Faraday rotation studies because the error associated with measuring the polarization angle is inversely proportional to the intensity of the linearly polarized light. We made full-polarization observations at 1 – 2 GHz frequencies using the Karl G. Jansky Very Large Array of 21 linearly polarized cosmic radio sources occulted by the solar corona in July and August, 2015. The radio sources were scattered over a range of heliocentric distances; however, sources within a heliocentric distance of 10 solar radii experienced the most pronounced angular broadening. The observed angular broadening is consistent with a 15% - 35% decrease in intensity. We discuss the implications of these angular broadening measurements on the observed coronal Faraday rotation as well as potential methods to correct for this phenomenon in mapping the radio sources.