The Blue Nile Basin, Ethiopia, whose inter-annual variability in local precipitation has resulted in droughts and floods that lead to economic and food insecurity, is the area of interest for our NSF-PIRE project, which aims to develop novel forecast technologies to mitigate the stresses to local communities. As part of the PIRE project, a Citizen Science Initiative (PIRE CSI) was established in June 2017, a project that trains high school students in hydrologic data collection under the guidance of classroom teachers and graduate students and professors from Bahir Dar University in four watersheds of interest, located south of Lake Tana, Ethiopia. Four MSc graduate students were selected from Bahir Dar University and trained nine high school students who were nominated taking into account gender and the proximity of their schools to the watersheds. High school students are currently collecting soil moisture data using TDR, river stage measurements using optical levels and groundwater levels using shallow water level meters. The data collection is supported by an app (B-WING), developed specifically for the needs of the project. College-ready activities are being planned for the high school students, i.e. inviting them to Bahir Dar University to analyze some of the data, present their work at a workshop, and familiarize themselves with the university experience. Recently, the PIRE CSI was extended to involve local farmers as “citizen scientists”, collecting soil moisture data using low-cost, soil moisture sensors developed in-house at the University of Connecticut, that have been installed in 12 locations and two soil depths (20 cm and 40 cm). The collected data will be used for the initialization and validation of the hydrological models developed in the region. The PIRE CSI promotes the empowerment of local communities and establishes long-lasting partnerships between scientists and stakeholders. It is believed that the co-generation of knowledge may contribute to higher rates of forecast adaption by the local farmers and may trigger the student’s interest in STEM and encourage their uptake of scientific careers. Acknowledgment: This material is based upon work supported by the National Science Foundation under Grant No. 1545874.

Continuous evolution of Global Navigation Satellite Systems (GNSS) provides the opportunity of using observations from multi-GNSS constellations for geodetic applications. It is a well-known fact that the use of multi-GNSS observations improves the robustness and reliability of the position estimates while providing enhanced spatial coverage due to increased number of available satellites. The combined use of the ground-based observations from GPS and GLONASS, for example, significantly adds to the coverage in both azimuth and elevation of the ground-based stations. The aim of this study is, firstly, to assess the geographical variations in the improvement (of position estimates) offered by the use of multi-GNSS observations, and secondly, to assess implications of multi-GNSS position estimates for improvements and robustness of the terrestrial reference frame. A GPS-only double-differenced positioning solution for a global network of stations will be used as a reference in this study. Furthermore, two precise point positioning (PPP) solutions i.e. one with GPS-only and one with GPS+GLONASS observations, will be computed and compared to the reference solution. To study the geographical variation, the differences between the simulated and reference North/East/Up components will be analyzed as a function of latitude. Eventually, the various positioning solutions will be analyzed in terms of their application in terrestrial reference frame definition.

Harmful algal blooms (HAB; Karenia brevis) occurrences have been reported from the coastal waters of Charlotte County in southwest Florida. We developed multivariate regression models that relate reported (January 2010 to October 2017) bloom occurrences to observations extracted from archival remote sensing data (Moderate Resolution Imaging Spectroradiometer [MODIS]) to accomplish the following: (1) identify factors controlling HAB propagation, (2) predict algal bloom distribution (same day, and 1, 2, and 3 days in advance), and (3) develop fully automated system for data distribution via a web-based GIS platform. These tasks were accomplished through three main steps: (1) automatic downloading and processing of daily MODIS products using SeaDAS software to extract relevant remote sensing variables (euphotic depth, wind direction, ocean chlorophyll three-band algorithm for MODIS [Chlorophyll a OC3M], wind speed, chlorophyll a Generalized Inherent Optical Property [GIOP], Fluorescence Line Height [Flh], diffused attenuation coefficient for downwelling irradiance at 490 nanometer [Kd_490], chlorophyll a Garver-Siegel- Maritorena [GSM], Turbidity index, Particulate backscattering coefficient at 547 nm [bbp_547_giop] and sea surface temperature [SST]), (2) development and calibration of multivariate regression models using relevant remote sensing and static variable (distance from river mouth, bathymetry) inputs for same day mapping and forecasting of HAB occurrences, and (3) automated posting of model outputs on a web-based GIS (http://mgs.geology.wmich.edu/bloom/). Findings include: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, sea surface temperature [SST], chlorophyll a [OC3M] and distance from the river mouth, and (2) the model predictions were successful at 90% for same day mapping and 65%, 72% and 71% for the one, two and three days in advance predictions, respectively.

Preventing leakage of CO2 along wellbore cement sheaths is a key factor for ensuring success of geologic carbon storage (GCS) operations. Here, we examine a potential alternative cementing material, engineered cementitious composites (ECC), for use in GCS wellbore cementing applications. ECC is a novel fiber-reinforced cementitious composite that exhibits strain hardening and improved tensile ductility in comparison to conventional cement. Improved ductility may prevent wellbore damage caused by CO2 injection pressures and casing expansion/contraction associated with thermal swings. Earlier work examining physical alterations of ECC exposed to CO2 at 10 MPa and 50°C found that damage to ECC was limited to microcracks with apertures less than 60 µm after several weeks of reaction. However, microstructural analysis revealed densification of the fiber/matrix interphase due to calcite precipitation, which could alter the engineered bonding properties between the matrix and fibers. Such alteration following carbonation could negatively impact the long-term ductility of ECC used for GCS wellbore cementing applications. This presentation will discuss recent results from static batch studies investigating the impact of CO2-acidified water on tensile ductility of ECC. Several ECC and ordinary Portland cement (OPC) coupons were exposed to CO2-saturated water under temperature and pressure conditions of 50oC and 10 MPa, respectively, and samples were retrieved after 2, 7, 14, and 28 days. Four-point flexural test and micro-CT analysis were carried out to investigate the impact of carbonation on the ductility and microstructural properties of ECC. Replicate experiments were also conducted under the same conditions but with a N2 headspace to isolate impacts associated with CO­2 exposure. While the samples exposed to N2 continued to exhibit a multiple microcracking behavior with no observable change in tensile ductility, the ductility of the composite exposed to CO2-acidified water showed an increase in the ultimate flexural strength and significant decrease in ductility as the duration of reaction increased. OPC coupons exhibited brittle behaviors under all test conditions. This suggests that the densification of the fiber matrix interface after exposure to CO2 can compromise ECC’s overall ductility.

Fracture dissolution in carbonate rocks is of great interest for the applications of CO2 geological storage and formation of conduits and caves in karst reservoirs. Taking into account the fracture roughness and interporosity fluid exchange between the fracture and the porous host rock, the classical cubic law for parallel-plate channels or Poiseuille's flow for tubes cannot describe the flow within the fracture's opening. The Reynolds number increases along the fracture as a result of the influx crossing the fracture walls. The wavy, irregular, nonparallel-plate shape of the boundaries affects the overall flow regime and the average flow model. The velocity field on the fracture boundaries possesses a slip and a normal component. The nonzero fluid velocity maintains the concentration gradient near the porous host rock and provides a fresh source of the solvent that facilitates dissolution. The aim of this work is to point out the role of fracture roughness and the influx of fluid from the porous host rock on fracture dissolution. The effective model of flow in a single fracture with permeable wavy walls is coupled to transport of dissolved calcite. The asymptotic solutions of the steady-state Navier-Stokes equations with slip boundary condition are used to determine the velocity field in the fracture opening. Two cases of axisymmetric and parallel-plate wavy fractures are considered. The inflow through the walls increases the Reynolds number along the fracture and results in local flow instabilities and formation of reverse flow. The local instabilities arise in relatively higher Reynolds numbers in parallel-plate wavy fractures than in cylindrical wavy fractures. The averaged pressure drop along the fracture is represented as quadratic and cubic corrections to the linear law. The corrections result from the effect of the inflow through the walls and the irregular geometry of channel. Asymptotic solutions to the reactive transport of the dissolved calcite in the acidified brine are derived for rate-limited reactions with a low Damkohler number and high Peclet number. The role of the fracture's walls corrugations, fractures aspect ratio, porous host rock permeability, and the interporosity fluid exchange between the fracture and host rock on the fracture dissolution is investigated.

Relationships between climate variability and climate sensitivity are to be expected where the damping of a climatic anomaly is due to a change in the energy balance of the planet, such that the Fluctuation-Dissipation theorem heuristically applies [Leith, 1975]. A recent attempt to relate Equilibrium Climate Sensitivity (ECS) to global temperature variability over the historical period suggested a surprisingly tight emergent constraint on ECS [Cox et al., 2018]. However, the sensitivity-variability relationship in that study was partially hidden by anthropogenic forcing over the historical period. Here we examine instead CMIP5 control runs. These runs have no external forcing and therefore provide a much cleaner test of proposed links between internal variability and sensitivity. It has been noted before that there is a positive correlation between decadal temperature variability and climate sensitivity across climate models [Colman & Power, 2018]. Questions remained however as to how robust this relationship is across different model ensembles, what mechanisms are responsible for it, and whether it can be used as an emergent constraint on climate sensitivity. We examine the relationship between decadal variability and ECS using models of varying complexity, including CMIP5 control runs and a range of conceptual energy balance models for which analytical solutions are presented. Based on these results, a general mechanism becomes apparent and the shape of the relationship is determined to be more quadratic than linear. The nonlinearity has implications for using this relationship as an emergent constraint, where an incorrect assumption of linearity might lead to biased estimates. A further surprising implication of the study is that a slowdown in global warming does not necessarily imply that climate sensitivity is lower than previously estimated. Models with a higher sensitivity, but which broadly reproduce the long-term record of global warming, are actually more likely to have slow-down periods than models with lower sensitivity.

We present an interdisciplinary study of observations of pre-earthquake processes associated with major earthquakes based on integrating space and ground- data. Recent large magnitude earthquakes in Asia and Europe have emphasized the various observations of multiple types of pre-earthquake signals recorded either on the ground or from space. Four physical parameters were measured from ground and satellite and used in our simulation models: 1) Ground Radon variation; 2) Outgoing Long-Wavelength Radiation (OLR) obtained from NPOES, NASA/AQUA) on top of the atmosphere (TOA); 3) Atmospheric Chemical Potential (ACP) obtained from NASA assimilation models and; 4) electron density variations in the ionosphere via GPS Total Electron Content (GPS/TEC). For this analysis we selected six large earthquakes from the last decade with differing geographic and seismo-tectonics regions: (1) M9.3, Off the West Coast of Northern Sumatra, Dec 26, 2004; (2) M9.0 Great Tohoku Earthquake, Japan, March 11, 2011; (3) and (4) M7.8 and M7.3 Gorkha, Nepal, 2015; (5); M8.2 Tehuantepec, Mexico, September 8, 2017 and; (6) M7.1, Puebla central Mexico earthquakes, September 19, 2017. Our preliminary results indicate an enhancements of radon (about a week to ten days prior) coincident (with some delay) with an increase in the atmospheric chemical potential measured near the epicenter from both satellite and subsequently with an increase of outgoing infrared radiation (OLR) observed on the TOA from NOAA/NASA (a week in advance). Finally GPS/TEC data indicate an increase of electron concentration 1-4 days before the earthquakes. Although the radon variations and some of satellite OLR anomalies were observed far (>2000km) from the epicenter areas the anomalies were always inside the estimates of the Dobrovolsky-Bowman area of preparation. We examined the possible correlation between magnitude and the spatial size of earthquake preparation zone in the framework of the Lithosphere –Atmosphere -Ionosphere Coupling hypothesis. The reliable detection of pre-earthquake signals for both sea and land earthquakes was possible only by integrating satellite and ground observations. A detail summary of our approach to this study of pre-earthquake research has just been published as AGU/Wiley Geophysical Monograph Series No. 234.

In 1988, the Center for Operational Oceanographic Products and Services (CO-OPS), an office of NOAA’s National Ocean Service, began to record continuous 6-minute water temperature data with thermistors at the coastal stations of the National Water Level Observation Network. Today, 140 of the stations have accumulated at least 15 years of archived data. We performed extensive quality control of the daily-averaged water temperatures by excluding periods of suspect data revealed through inter-station comparison. All quality-controlled series have 15-25 years of daily means that, when aggregated, produce an average seasonal cycle for 365 days of the year. Residual temperature series obtained after subtracting the average seasonal cycle from the daily mean temperature depict the inter-annual variations. A threshold for defining an extreme residual water temperature was selected to highlight periods of anomalously warm or cold coastal water conditions. This type of climate information should prove valuable to users in the fields of ecology and fisheries management for quantifying anomalous temperature effects on coastal ecosystems (such as fisheries, corals, sea grasses, harmful algal blooms, etc). Knowledge of average seasonal water temperature cycles are also useful for validating coastal hydrodynamic models. Extended periods from weeks to months of high or low coastal sea levels can be correlated with coastal water temperature anomalies.

WindNinja is a high-resolution diagnostic wind model developed for use by operational wildland fire management. The original version of WindNinja employed a numerical solver to enforce conservation of mass (COM). Because the COM solver is fast-running, requires little technical experience to run, and predicts ridgetop speed up and channeling effects well, it is widely used by the operational fire community. The COM solver has limitations, however, in regions where momentum effects dominate the flow, such as in regions of flow separation, which can occur on the lee-side of terrain obstacles. Recently, a second solver has been incorporated into WindNinja which enforces conservation of mass and momentum using computational fluid dynamics (CFD) techniques based on the Reynolds-Averaged Navier-Stokes (RANS) equations. In this work we compare simulations from the CFD solver to measurements made during three field campaigns (Askervein Hill, Bolund Hill, and Big Southern Butte) as well as to simulations from the COM solver and an LES model. Evaluations focus on near-surface winds during high-wind periods, which are of particular interest to wildland fire managers.

The Mw 7.2 Sarez strike-slip earthquake occurred on Dec 7, 2015 in the Pamir region at the North-West of the Tibetan Plateau. We used Sentinel-1A/B Interferometric Synthetic Aperture Radar (InSAR) data to investigate postseismic deformation due to the Mw 7.2 Sarez earthquake. We analyzed 2.5 years of post-earthquake acquisitions from the ascending track 100 and the descending track 005. Despite challenging surface conditions (that include rugged topography and snow cover), we were able to derive time series of line of sight (LOS) displacements within 150 km from the earthquake rupture. We used stacks of interferograms covering snow-free months, as well as persistent scatterers to detect possible deformation transients. Preliminary results indicate no postseismic relaxation signals above the noise level (10-20 mm/yr for average LOS velocities). We do observe coseismic deformation due to two M>6 earthquakes that occurred ~100 km to the North-East from the epicenter of the Sarez earthquake. We use constraints on the maximum amplitude of surface displacements provided by the InSAR data to provide bounds on the effective rheologic structure of the lower crust and upper mantle beneath Pamir.

Evidence for asymmetric plate growth, variable crustal thickness, and non-uniform spreading rates is ubiquitous on the seafloor. However, conventional numerical modeling approaches are often incapable of explaining the non-uniform growth of oceanic lithosphere. Noting that plate-boundary forces can dynamically determine plate speed by finding a balance against the resistance to extension at ridge axes, we introduce plate-boundary tractions instead of kinematics to drive plate motions in numerical models for mid-ocean ridges. We construct such models using FLAC, an open-source finite element code for geodynamic simulations. Our preliminary two-dimensional models for slow-spreading ridges have constant tractions on the boundary far from the ridge. Applying periodic variations in thermal states or magmatic accretion rates at the spreading center, we monitor how plate speed, crustal thickness, faulting styles and fault offset change in time. We also compare the model results to the temporal variations found in the bathymetry and seismic reflection data along a 1500 km-long transect across the slow-spreading South Atlantic seafloor, which were acquired in the 2017 CREST (Crustal Reflectivity Experiment Southern Transect) expedition.

On decadal timescales, the greenhouse gas methane (CH4) is ~100 times more potent than carbon dioxide. Its abundance is increasing, many of its sources are temperature dependent. The Arctic is the site of the fastest warming globally. Feed-backs between Arctic temperature and CH4 emissions and concentrations need investigation. Unfortunately, available Arctic in situ data are extremely sparse with no marine observations outside summer. Satellite instruments measuring solar radiation reflected from the surface are ineffective in the Arctic. Thus, we leverage satellite data from AIRS, IASI-1, and IASI-2 Thermal Infrared (TIR) spectrometers, which provide year-round, day/night CH4 observations. Available in situ high latitude NOAA/ESRL surface coastal (50-85°N) flask atmospheric CH4 concentrations were compared with satellite data. We find: 1) remote sensing data revealed 150% (IASI-1, mid-upper troposphere) and 80% (surface data for Arctic stations) increases in atmospheric CH4 concentration growth rates between 2010-2014 and 2014-2017 time spans. Global NOAA/ESRL surface concentration rates increased by 90% for the same period; 2) maximum CH4 seasonal emission from the Arctic land occurs in boreal summer, while that from the Barents Kara Sea (BKS) occurs in boreal winter (Nov–Mar). Total annual Arctic Ocean CH4 emissions are preliminary estimated as ~40% of all land emissions North of 50°N; 3) marine emissions are concentrated in shelf areas within ~100 km of the coasts of major Arctic BKS lands; 4) CH4 anomalies over BKS, defined as surplus over its concentration at the North Atlantic area, grew after 2014; 5) the strongest SST increase was observed every year in the southeast Barents Sea in June due to strengthening of the warm Murman Currents and in the south Kara Sea in Sept. Direct in situ CH4 flux measurements during polar night over sea are necessary to test the satellite results.

Tides influence the allocation of river discharge to distributary channels interconnected by tidal junctions. Geometrical properties of distributary channels and nearshore coastal morphology might also play a significant role in tidal propagation, and hence control river discharge division and tidal energy transport at tidal junctions. Model simulations reveal how under different river discharge regimes, the discharge division is controlled by the tidal behavior at the junctions. Furthermore, analysis of tidal energy at the junctions indicates that the side distributaries drain or add tidal energy to the main river channel depending on the upstream discharge condition.

This study aims to give a brief overview of an ensemble of regional climate model (RCM) simulations with bias correction for daily precipitation for the Carpathian Region located in Central/Eastern Europe. Within the international initiation called the COordinated Regional Downscaling Experiment (CORDEX) EURO-CORDEX and Med-CORDEX provide RCM simulations targeting Europe as a whole or in a part at the grid resolutions of 0.44o (~50 km) and 0.11o (~12 km). The ensemble of RCMs provides a huge amount of data, which are however prone to biases compared to high resolution observations. Percentile-based bias corrections of the daily precipitation output of EURO-CORDEX and Med-CORDEX RCM ensemble at a common 0.11o × 0.11o horizontal grid resolution are performed based on the high-resolution, high-quality observational dataset: CARPATCLIM. The region covered by the CARPATCLIM dataset can be considered as the Carpathian Region for which the RCM ensemble (consisting of total six members at 0.11o resolution) of a historical period (1976-2005) and under the Representative Concentration Pathway 8.5 over two future time slices (2021-2050 and 2070-2099) are assessed. The present study focuses on precipitation climate indices over the entire Carpathian Region and two subregions representing high- and lowlands within the target region. The analyzed indices are: frequency of rainy days (RR1, days with a total rainfall of at least 1 mm), heavy precipitation days (RR10, days with a total rainfall of at least 10 mm), highest daily precipitation (RX1), maximum consecutive dry days (CDD, the duration of the longest period with < 1 mm total daily precipitation), maximum consecutive wet periods (CWD, the duration of the longest period with > 1 mm total daily precipitation). The key findings are as follows: (1) the influence of orography on seasonal precipitation change is evident throughout the analyzed periods, (2) precipitation change holds an unequivocal seasonality as most models estimate significant winter (DJF) precipitation increase (~30%), while in general drier (~20%) summers (JJA) are projected over most part of the Carpathian Region by the end of the 21st century, (3) over the subregions RR10 shows a clear signal of increase in all seasons (10-50%), except summer (~-15%), while RX1 shows increase in all seasons.

Explosive, ash-producing volcanic eruptions are a significant natural hazard with the potential for loss of life, economy, and infrastructure. Turrialba is an active stratovolcano located in the Central Cordillera of Costa Rica. The edifice is located only 35 km east-northeast of Costa Rica's capital city and poses a threat to its central valley, the social and economic hub where more than half of the population resides. The most recent eruption took place in 2016-2017, consisting of four eruption phases. Preliminary observations using SEM show significant morphological differences between the various eruption phases, including the amount of dust and crystals that are present. The morphology of volcanic ash is fundamental to our understanding of magma fragmentation, and in transport modeling of volcanic plumes and clouds. The chemistry of the ash particles produced by fragmenting magmatic foams may affect their evolving morphology throughout the various stages of eruption. In addition, eruption energetics may play a role in ash morphology. Separating the roles of chemical heterogeneity and evolving energetics requires careful examination of ash morphology and its relation to composition. In this way, we take some initial steps in closing the knowledge gap between eruption mechanisms and how and why these mechanisms are exhibited in the morphology of ash during explosive eruptions.

Deep carbon is terrestrial carbon that is not in the atmosphere or oceans or on the surface. We have a great deal of knowledge about the properties of near surface carbon, but relatively little is known about the deep carbon cycle. The Deep Carbon Observatory, was founded in 2009, to address major questions about deep carbon. Where are the reservoirs of carbon? Is there significant carbon flux between the deep interior and the surface? What is deep microbial life? Did deep organic chemistry have a role in the origin of life? This project is directed toward documenting and describing of the history of deep carbon science. The narrative begins in 1601, when William Gilbert suggested that Earth's interior behaves like a giant bar magnet. We trace across three centuries the slow evolution of thought that led to the establishment of the interdisciplinary field of Earth System Science. The concept and then development of the deep carbon cycle of burial and exhumation dates back at least two hundred years. We identify and document the key discoveries of deep carbon science, and assess the impact of this new knowledge on geochemistry, geodynamics, and geobiology. A History of Deep Carbon Science is in preparation for publication by Cambridge University Press in 2019. Its illuminating narrative highlights the engaging human stories of many remarkable researchers who have discovered the complexity and dynamics of Earth's interior.

In this study, we detail a new prediction-oriented procedure aimed at volcanic hazard assessment based on geophysical mass flow models with heterogeneous and poorly constrained output information. Our method is based on an itemized application of the empirical falsification principle over an arbitrarily wide envelope of possible input conditions. In particular, instead of fully calibrating input data on past observations, we create and explore input values under more general requirements of consistency, and then we separately use each piece of empirical data to remove those input values that are not compatible with it, hence defining partial solutions to the inversion problem. This has several advantages compared to a traditionally posed inverse problem: (i) the potentially non-empty intersection of the input spaces of partial solutions fully contains solutions to the inverse problem; (ii) the partial solutions can provide hazard estimates under weaker constraints potentially including extreme cases that are important for hazard analysis; (iii) if multiple models are applicable, specific performance scores against each piece of empirical information can be calculated. We apply our procedure to the case study of the Atenquique volcaniclastic debris flow, which occurred in the State of Jalisco (MX), 1955. We adopt and compare three depth averaged models currently implemented in the TITAN2D solver, available from vhub.org. The associated inverse problem is not well-posed if approached in a traditional way. However, we show that our procedure can extract valuable information for hazard assessment, allowing the exploration of the impact of model flows that are similar to those which occurred in the past, but differ in plausible ways.

The NASA’s Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR) mission was launched on February 11, 2015 to the Sun-Earth Lagrangian L1 point where it began to collect radiance data of the entire sunlit Earth every 65 to 110 min in June 2015. It provides imageries in near backscattering directions at ten ultraviolet to near infrared narrow spectral bands. The DSCOVR EPIC science product suite includes vegetation Earth System Data Record (VESDR) that provides leaf area index (LAI) and diurnal courses of normalized difference vegetation index (NDVI), sunlit LAI (SLAI), fraction of incident photosynthetically active radiation (FPAR) and Directional Area Scattering Function (DASF). The parameters at 10 km sinusoidal grid and 65 to 110 minute temporal frequency generated from the upstream DSCOVR EPIC BRF product are available from the NASA Langley Atmospheric Science Data Center. Whereas LAI is a standard product of many satellite missions, global diurnal courses of NDVI, FPAR, SLAI and DASF are new satellite derived products. Sunlit and shaded leaves exhibit different radiative response to incident Photosynthetically Active Radiation (400-700 nm), which in turn triggers various physiological and physical processes required for the functioning of plants. LAI, SLAI and FPAR are key state parameters in most ecosystem productivity models and carbon/nitrogen cycle. DASF provides information critical to accounting for structural contributions to measurements of leaf biochemistry from remote sensing. This poster provides an overview of the EPIC VESDR research. This includes a description of the algorithm and its performance, details of the product, initial assessment of its quality and obtaining new information on vegetation properties from the VESDR product.