Subtropical cyclones (STCs) are characterized by a hybrid structure sharing tropical and extratropical features. The impacts of this kind of cyclones are similar to the generated by tropical storms or even hurricanes, leading to widespread social damage and great economic losses. Carrying out accurate simulations becomes key for a forecast improvement of these extreme events. In this study, several STCs that hit the northeastern Atlantic coasts and experimented a transition into tropical storms (Delta 2005) or even hurricanes (Vince 2005 and Ophelia 2017) are assessed by means of simulations using the high-resolution HARMONIE-AROME model. This model is developed and operated at 2.5 km resolution through the collaboration of the 10 European National Meteorological Services (NMS) that are part of the international research program HIRLAM together with the 16 countries that comprise the ALADIN consortium. The HARMONIE-AROME model has a convection-permitting configuration and uses a non-hydrostatic spectral dynamical core with a semi-Lagrangian and semi-implicit discretization of the equations. In this way, more realistic results are obtained, which allows providing an added value to the study of tropical transitions.

This study uses gravity data to investigate crustal structure in the region of the Galapagos triple junction where the westward propagating Cocos-Nazca rift (CNR) approaches the East Pacific Rise (EPR) and forms the northern boundary of the Galapagos micro plate. Shipboard and global gravity data are analyzed from 104˚W to 96˚W and 0˚ to 4˚N. In May 2018, the high-resolution gravity data were collected along ship tracks that run across the entire width of the Galapagos gore from the tip of the CNR at ~101.7˚W to 98.5˚W. Residual mantle Bouguer anomaly (RMBA) was calculated by removing the effects of water-crust, crust-mantle, and lithospheric cooling from the free-air anomaly (FAA). We also calculated a model of gravity-derived crustal thickness by downward continuation of the RMBA, as well as a model of non-isostatic topography by removing the topographic effects of thermal subsidence and crustal thickness variations. The results reveal several distinctive features in gravity and crustal structure: (1) The eastern flank of the EPR has systematic shallower topography and more negative RMBA than the conjugate western flank, reflecting regional density variations. (2) On the eastern flank of the EPR, the region south of the Galapagos gore is associated with more negative RMBA than the conjugate region to the north, possibly reflecting closer proximity to the Galapagos hotspot in the southern region. (3) The first ~100 km behind the propagating CNR tip (~101.7˚W to 100.8˚W) is associated with more positive RMBA (up to ~35 mGal) than the CNR rift between ~100.8˚W and 98.5˚W, suggesting locally thinner crust (up to ~1.5 – 2 km). East of 98.5˚W along the CNR, RMBA decreases gradually towards the Galapagos hotspot. (4) A region of local high topography on the southern boundary of the Galapagos microplate, where fresh basalts were sampled, is associated with negative RMBA centered at ~101.6˚W and 1.3˚N, indicating local relatively thick crust. (5) Within our study area, the CNR crust shows shallower average off-axis topography and more negative average RMBA than the EPR crust of corresponding age, which is consistent with a model of isostatic compensation of average thicker CNR crust than the surrounding EPR crust, possibly reflecting Galapagos hotspot effects.

The 1755 Lisbon earthquake triggered the largest historical tsunami ever registered in Western Europe. Despite the recent efforts to better understand this event, there are still questions to be answered. Understanding the past tsunami intensity is key to assessing tsunami hazard. Sedimentary imprints are the only evidence in the geological record able to quantify onshore tsunami flow characteristics through inverse modelling. On the other hand, forward numerical modelling is a powerful tool capable of simulating tsunami hydrodynamics and the induced sediment transport. This work presents results from inverse and forward modelling in order to assess tsunami characteristics onshore. The study site is located on the Portuguese southern coast, at Salgados lowland where inverse modelling was performed using TsuSedMod (Jaffe and Gelfenbaum, 2007, Sedimentary Geology) based on four Livingstone sediment cores. Forward modelling including tsunami generation and propagation was performed respectively using the methods of Okada (1985, Bulletin of the Seismological Society of America) and Delft3D-FLOW. Onshore topography was corrected for the 1755 scenario based on extensive deposit thickness data. The tsunami source was chosen based on recent results from the same authors that pointed to a good correlation between modeled and field tsunami data considering Marques de Pombal fault. Results from inverse model show tsunami onshore average speed varying from 7.3 up to 9.3 m/s and shear velocities from 0.52 up to 0.66 m/s. Varying the bottom roughness results in the forward model result in average flow velocities between 7.0 and 8.0 m/s, induced by a 3-meter high tsunami at 50 m depth. The good agreement between forward and inverse model estimates of tsunami velocity highlights the potential of numerical modelling (coupled with geological records) to improve the understanding of historical events. Additional research on correlating modelling and geological data is needed and will likely lead to a better understanding of the effects of similar events and contribute to the ability to assess tsunami hazard and coastal vulnerability. Acknowledgements: Work supported by Instituto Dom Luiz and by project OnOff ‑ PTDC/CTA‑GEO/28941/2017 – financed by FCT

Quantification of sulfur dioxide (SO2) emission flux is a fundamental task in volcanology to have insights of the composition and the spatial evolution of volcanic plumes. The ground based InfraRed hyperspectral imager HyperCam, from Telops Company, was deployed during IMAGETNA campaign in 2015 and provided high spatial and spectral resolution images of Mt Etna plume. The spectral range of the hyperspectral imager is [7.7 - 11.8 µm] and the measured images contained 320 x 64 pixels with a spectral resolution of 2 cm-1. To process hyperspectral images in quasi real-time, a fast and reliable radiative transfer retrieval model is required. The LATMOS Atmospheric Retrieval Algorithm (LARA), used to retrieve the slant column densities of SO2, includes an accurate line-by-line radiative transfer model and an efficient minimization algorithm of the Levenberg-Marquardt type. But the calculation time remains too high to infer near real time (NRT) estimation of SO2 fluxes. As first, to reach NRT target, a classification methodology of the brightness temperature spectra was developed and then applied on each measured sequence to significantly decrease the processing time. One image previously took a week of calculation to be retrieved. The classification of the spectra, which takes a couple of hours, allows the retrieval of a complete measurement sequence of the field campaign (~400 images) in only two days. The accuracy of the methodology was confirmed, by comparing the SO2 slant column density images obtained after classification with the one obtained by the accurate and time expensive pixel by pixel retrieval processing. The LARA model, the spectra classification methodology and a comparison of the results will be presented.

In the subsurface, water content, gas solubility, adsorption on minerals and chemical reactions control gas fluxes between soil and the atmosphere. Because these processes vary in intensity both in time and space, it is very challenging to quantify emissions, specifically when flux measurements are used for detection, identification or monitoring of a subsurface gas source. An experimental setup for gas percolation though soil column experiments under well-controlled conditions was developed and validated at the ECOTRON IleDeFrance research center. Its design included the effect of: i) watering/evaporation cycles, ii) barometric pressure, iii) injection pressure, iv) tracer behaviors and v) plant metabolism. To better understand subsurface processes controlling gas fluxes, we studied transport of multiple tracers across soil columns using long-term and high-resolution monitoring thanks to online low-flow mass-spectrometry. We injected tracer gases into columns containing different porous media, pure sillica sand and zeolite. This set-up allowed us to evaluate the relative contribution of diffusion, solubility and adsorption on various trace gases (SF6, noble gas including Xe). All the experimental data are discussed in conjonction with simulations using the NUFT unsaturated flow and transport code.

With the recent GIEC report about global warming urging humanity to limit the global temperature increase to 2°C maximum, research on the geological storage of carbon dioxide appears more important than ever. However, the injection in geological formations (such as deep saline aquifers and depleted gas/oil fields) of supercritical CO2, stores it in the porosity of the host rock raising legitimate concern about the safety and long-term behavior of such dynamic multiphase hydrosystems. Additionally, the economic and energetic weight of such storage complicates its development at the world scale without strong political incentives. The storage of CO2 in ultramafic formations in some specific contexts appears, on the contrary, as a very appealing technology since it involves the safe mineralization of the carbon by precipitation of carbonates with the major alkaline earth metals (i.e. Mg, Ca…) leached from the formation itself. Moreover, as these rocks contain high amounts of ferrous iron, its oxidation by the water co-injected with CO2 produces dihydrogen, which can be economically valuable rendering the whole process more viable. Large ophiolite formations (Oman, Papua New Guinea, east coast of Adriatic Sea…) are expected to have a storage capacity of several billion tons of CO2 and could produce similar amounts of clean dihydrogen. We present experimental results on the mineral carbonation of natural cores of serpentinites by the continuous percolation of carbon-saturated water. We show that the dimensionless Péclet (relative importance of diffusion and convection processes), and Damköhler (relative importance of convection and chemical processes) numbers as well as the initial geometry of the porosity and permeability control the localization of the silicate dissolution and the carbonate precipitation in the porous medium. We also show that the chemical behavior is principally controlled by the reactivity of calcium-bearing silicates (wollastonite, diopside) and the precipitation of calcite as well as the initial iron content of the different phases. Such results are particularly interesting for the design and the optimization of pilot sites and the development of this technology at industrial scale.

Iron is the fourth most common element found in the earth crust. Although it may not be as important for soil fertility as, e.g., phosphorus, nitrogen and organic matter, its absence would be detrimental to plant growth. At the same time, iron oxides are highly correlated with phosphorus availability. Iron is thus an indicator for soil fertility and the usability of an area for cultivation of crop. A relatively high spectral resolution is needed for mapping iron oxide contents with spectral reflectance data, and remote sensing is the only suitable tool for surveying large areas at a high temporal and spatial interval. Sentinel-2 MSI (MultiSpectral Instrument) is the Landsat-like spatial resolution (10–60 m) super-spectral instrument of the European Space Agency (ESA), aimed at additional data continuity for global land surface monitoring with Landsat and Satellite Pour l’Observation de la Terre (SPOT) missions. Several studies with simulated and real data have been conducted in the last several years to show the potential of Sentinel-2 MSI, including its use for geological remote sensing, mineral mapping in particular. Sentinel-2 has several bands that cover the 0.9 μm iron absorption feature, while space-borne sensors traditionally used for geologic remote sensing, like ASTER and Landsat, had only one band in this feature. In this paper, we show a comparison of Sentinel-2 and AVIRIS to demonstrate the usability of the VNIR bands for mapping the near-infrared iron absorption feature. Next, we present spectral indices for mapping iron minerals that are important in soil fertility and mineral exploration.

The Track Zero Charitable Trust (http://trackzero.nz) was founded in early 2018 with the goal of inspiring action on climate change through engagement with the arts. The main motivation is that artistic expression connects on an emotional level in a way that direct communication of science does not. Also, around 80 percent of New Zealanders engage in some way with the arts, a much larger audience than those who take an active interest in science. This presentation discusses the first major activity of TrackZero, a series of public meetings around New Zealand where scientists partnered with local arts practitioners to interact with audiences on the science, on people’s feelings and concerns, and on ways forward to action on adapting to or mitigating climate change. Different communities had different concerns and the range of conversations was rich and varied. While no formal evaluation has been carried out, we provide some general reflections on impact and engagement, and ideas for future activities.

Inspired by the AAHE Assessment Forum’s Principles for good practice for assessing students’ learning, the author has generated Ten Steps (1992) to Promote a Stronger Emphasis on Student Learning in a Hydrology–Fluid Mechanics Course. Student-Learning must not be focused only about making the connections initially. Instead it should concentrate more about maintaining those connections in the long run. Student learning is fundamentally about a strong bond between the academic establishment and the student citizens of the entire community. Student-Learning is enhanced by the environment. It should take place in the context of a compelling situation that balances curiosity, challenge and opportunity. Student-Learning should have an active search for meaning by the learner – constructing knowledge rather than passively delivering it or receiving it. In other words one should create a Concept Mapping Model instead of a Structured Content Model. Student-Learning is developmental. In other words, it is a cumulative process involving the whole person, who is capable of integrating the new with the old. The settings, the surroundings, the influences of others contribute to successful accomplishments. Student-Learning should be viewed as an effort promoted by individuals who are intrinsically tied to others as social beings, actually interacting as collaborators. Student-Learning is strongly influenced by the educational climate in which learning achievements takes place. Student-Learning requires Action, Communication, Ownership, Reflection and Nurture (ACORN) as suggested by Hawkins and Winter (1997). Student-Learning in reality aims at an educational experience that takes place informally and incidentally, beyond explicit teaching in the lecture hall. Student-Learning is grounded in particular contexts and individual experiences, requiring effort to transfer specific knowledge and skills to other citizens. Student-Learning involves the ability of individuals not only to monitor their own learning, but also be able to enhance learning through collaboration and cooperation. References: Hawkins, P., & Winter, J. (1997). Mastering change: Learning the lessons of the enterprise in higher education initiative. London: Department for Education and Employment.

Western U.S. conifer forests harbor diverse ecological strategies that enable species to persist across a wide range of hydroclimate conditions, along with wildfire and eruptive insect outbreaks. Assessing climate influences on future forest composition and carbon sequestration requires vegetation process models that have sufficient ecological resolution to simulate this range of ecological variability. Here we present progress towards incorporating multiple shade and drought tolerance strategies in a vegetation demographic model parameterized for Western U.S. forests. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) to simulate a mixed conifer forest dominated by ponderosa pine and incense cedar in the Sierra Nevada Mountains of California. FATES resolves plant growth and respiration at the level of cohorts, defined by size and plant functional type. Incense cedar is shade and drought tolerant, while ponderosa pine is shade intolerant and the canopy dominant. We synthesized literature values of plant traits that correspond to important physiological and allometric parameters in FATES and conducted a sensitivity analysis within the observed parameter ranges with respect to carbon and water fluxes. Model output was benchmarked against carbon flux, water flux, and leaf area index measurements from the Critical Zone Observatory/AmeriFlux CZ2 site during 2010-2012. Specific leaf area, Vcmax, rooting distribution, and allometric equations had the most influence on simulated carbon and water fluxes. Final simulated average annual gross primary production (GPP) over 2010-2012 (1156 +- 79.2 gC/m2/yr) was 3.8% lower than observed GPP (1202 +-138.2 gC/m2/yr). Simulated evapotranspiration (ET, 373 +- 25 mm/yr) was 62% lower than measured ET (993 +-158 mm/yr). Simulated leaf area index (LAI, 1.2) was within the range of measured LAI (0.5-1.5). Preliminary analysis indicates underestimation of ET is likely due to an overestimation of soil water drainage. Our final parameter set allows pine and cedar coexistence to emerge from a bare ground initialization, and additional sensitivity testing of parameters important for coexistence are in progress. Clearly, observationally constrained parameters are critical for simulating ecosystem dynamics in Western U.S. forests.

The 2016 Amatrice-Norcia seismic sequence in central Italy activated a system of normal faults in the central Apennines and ruptured the surface along the Monte Vettore normal fault. Due to the complex rupture behavior, including antithetic faults and the proposed reactivation of an old thrust front, the Amatrice-Norcia seismic sequence offers a unique opportunity to study the relationship between fault complexity, surface ruptures, and earthquake source properties. Here, we focus on the first two months of the Amatrice-Norcia seismic sequence, including the 30 October 2016 Mw 6.5 mainshock near Norcia and more than 25000 aftershocks. Using continuous waveform data from 94 seismic stations with epicentral distances of up to ~100 km, we estimate source parameters of all cataloged earthquakes that exceed specific quality control criteria in a time period ranging from 24 October – 29 November 2016. Displacement spectral corner frequency and seismic moment values are fit using individual earthquake spectra, and corner frequency estimates are refined using spectral ratios. Constrained spectral parameters then provide input for static stress drop estimates based on a circular crack model. Preliminary results suggest the majority of earthquakes have static stress drop values between 1 and 10 MPa and self-similar scaling. Due to the high quality and quantity of available data, including precise earthquake locations, manually reviewed phase arrivals, and detailed mapping of surface ruptures, the Amatrice-Norcia earthquake sequence represents an opportunity to link earthquake source parameters to geological structures and surface rupture complexity. Preliminary results show correlations between high stress drop values and areas with increasing fault complexity, such as fault intersections at depth (inferred from precise earthquake hypocenters) or the mapped tip of the Monte Vettore normal fault, relative to other fault patches with fewer intersections or mapped surface trace terminations. Future work will examine whether the correlation of stress drop and fault complexity holds using refined stress drop estimates obtained using spectral ratio approaches.

Automated classification of remote sensing data is an integral tool for earth scientists, and deep learning has proven very successful at solving such problems. However, building deep learning models to process the data requires expert knowledge of machine learning. We introduce DELTA, a software toolkit to bridge this technical gap and make deep learning easily accessible to earth scientists. Visual feature engineering is a critical part of the machine learning lifecycle, and hence is a key area that will be automated by DELTA. Hand-engineered features can perform well, but require a cross functional team with expertise in both machine learning and the specific problem domain, which is costly in both researcher time and labor. The problem is more acute with multispectral satellite imagery, which requires considerable computational resources to process. In order to automate the feature learning process, a neural architecture search samples the space of asymmetric and symmetric autoencoders using evolutionary algorithms. Since denoising autoencoders have been shown to perform well for feature learning, the autoencoders are trained on various levels of noise and the features generated by the best performing autoencoders evaluated according to their performance on image classification tasks. The resulting features are demonstrated to be effective for Landsat-8 flood mapping, as well as benchmark datasets CIFAR10 and SVHN.

Gas leakage through wellbore micro-channels is a major challenging problem for well cementing and integrity. One of the reason that leads to weaker cementing is the drilling fluid contamination within the cement plug, which provides weak parts for the flowing pathways of gas and fluids. The objective of this paper was to experimentally investigate the drilling fluids contamination in terms of liquid and dehydrated drilling fluid on wellbore cement in multiple scale to compare and quantify the impact of the drilling fluids on the cement plug. In the experiment, specific amount of drilling fluid was mixed with wellbore cement. Different level of contamination was introduced for each phase of the drilling fluid. Class H Portland cement slurries were then prepared using API-10 B standard for a density of 16.4 lb/gal (SG=1.97), and the control sample with 0% contamination is referred to as neat Class H cement slurry. The first part of the testing is to quantify the effect of the contamination on core scale. Samples were tested for petrophysical and mechanical properties in terms of porosity, permeability and unconfined compressive strength. Moreover, Microstructural properties and hydration process were evaluated using Optical Microscopy and Scanning Electron Microscope (SEM) on micrometer scale in order to investigate the fundamental mechanism of contamination on properties of cement matrix. The results showed that the presence of mud would highly harm the performance of the cement. Micro-fractures appeared at the interface of the cement/mud through the Optical Microscope. The porosity of the core increased from 30% porosity of the neat cement to approximately 40% porosity of contaminated samples at most. The compressive strength could drop to more than 50% of the original value. Micro-annular channel and irregularities in the structure can be observed which might explain the increased porosity and permeability. The results presented in this paper would lead to safe implementation of cementing, enable safe Oil and Gas exploration in deepwater without risks of environmental contamination, and contribute to improvement in overall wellbore construction and development of robust hydraulic barrier materials.

Glaciers are major contributors to global sea level change and regional freshwater resources. In light of the worldwide societal importance of glacier change, we see a need for accessible glacier-education materials in many languages. We have developed a set of Jupyter notebooks, available in both Spanish and English, that coaches users through basic simulations with the Open Global Glacier Model (edu.oggm.org). The notebooks are freely available via GitHub (github.com/ehultee/CdeC-glaciologia), with no special software installation requirements for users. Participants in a week-long glaciology workshop at Clubes de Ciencia Peru 2019 used our notebooks to study glacier physics and make future projections for mountain glaciers of their choice. Only one participant had previously used Python, and none had experience with numerical modelling of Earth systems in any language. All were able to run the notebooks and explain their findings. Most participants were also able to modify the notebooks to conduct experiments of interest to them. We consider this a particularly successful case of science outreach, in that workshop participants are now equipped to explore their own important questions independently. The notebooks we have developed can support multilingual glaciology outreach; we hope that sharing our experience can support public geoscience more broadly.

Previous studies done for the TROPOMI mission (e.g. Meister et al (2017), Hu et al (2016), Landgraf et al (2016)) has shown that inhomogeneous illumination within the field of view causes distortions in the instrument spectral response function (ISRF). The differences in the distorted ISRF and the ISRF measured in the pre-flight calibration lead to retrieval biases. It is known through laboratory trials that these distortions increase with wavelength and various methods have been employed to mitigate these issues, including continuous within-slit scanning and temporal oversampling. Recently, a hardware solution, called a slit homogenizer, has shown promise in reducing distortions due to inhomogeneous illumination. In this work, we used an instrument model of the Geostationary Carbon Cycle Observatory, GeoCarb, to simulate observations in the 0.76um, 1.6um, 2.05um, and 2.3um spectral bands with varying illuminations. We found that the posterior scatter and bias of Greenhouse Gas retrievals grow linearly with the coefficient of variation of illumination within a footprint. We also found that the ISRF distortion effects of inhomogeneous illumination are significantly reduced through the use of a slit homogenizer, though not completely resolved.

This presentation will show an ongoing freshwater health assessment stemming from a partnership between the National Aeronautical and Space Agency (NASA) and Conservation International (CI) that is dedicated to improving natural resources assessment for conservation and sustainable management. The goal of this work is to develop a calibrated satellite- and hydrologic modeling-based tool to support the assessment of hydrologic environmental health and value natural capital in the Lower Mekong River Basin. Vollmer et al., (2018) have presented the social-ecological framework named the Freshwater Health Index (FHI), which takes account of the interplay between governance, stakeholders, freshwater ecosystems and the ecosystem services they provide. The FHI framework and its accompanying indicators are oriented toward management and stakeholder engagement, and they make a significant contribution by providing a systematic, evidence-based quantitative tool that supports the integration between social and ecological nature of fresh waters at the basin level. Since the FHI is intended to be used iteratively, we leverage multiple data products and hydrological modelling capabilities specifically created to improve decision support in the Lower Mekong basin (Mohammed et al., 2018). Mohammed et al. modelling capabilities enable the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil characteristics, and land cover and land use information to drive watershed model water simulations over the Lower Mekong River Basin. Multiple dam reservoirs scenarios have been envisioned and tested based on stakeholder engagement to enhance the results of the integrative social and ecological nature of fresh waters at the Srepok, Sesan, and Sekong (3S) River Basins of the Lower Mekong. This assessment provides a comprehensive picture of freshwater ecosystem health, the services it provides and the status of its governance at the Lower Mekong.

Wind and solar energy technologies are, by their nature, variable. Variations in resource availability, based on weather patterns, occur on intra-day to inter-annual time scales. Many energy system models optimize over a single year of input weather and electricity demand data. Energy system planners need increased understanding of the variability in generation potential across multiple years and how this could impact model results. A system achieving 100% reliability modeled using Year A data will not necessarily achieve 100% reliability when applied to Year B data unless an overbuild safety margin is added. We demonstrate: 1) model results can vary significantly based on the year of data used, 2) adding wind and solar does not necessarily reduce the predictability of meeting reliability targets year-to-year and can improve predictability in many cases, and 3) we illustrate a method to derive safety margins to predictably meet 100% reliability year after year and find the least-cost option.

Pesticide seed treatments (PST) which contain fungicides and insecticides are commonly used in agriculture; however, little is known about their effect on soil microbial communities and soil health. Neonicotinoids – controversial insecticides which are common in PST – have received criticism due to potential non-target effects. While fungal pathogens need to be moderated, PST have the potential to disturb broader fungal communities which could lead to reduced nutrient cycling and poor soil health. Given the broad use of PST, their effect on soil fungi needs to be studied within the context of other agricultural management practices. For example, tillage regimes can result in distinct fungal communities which may respond differently to PST. An experimental site was established in 2013 with a corn-soy rotation under three tillage treatments: Full-till, Strip-till, and No-till. Since 2016, seeds with or without PST (fungicides and insecticides) were planted under each tillage regime in a fully factorial design. In 2018, bulk soil was collected from within rows while soy was growing. A range of soil physicochemical variables were measured, and soil function was determined with substrate-induced respiration and enzyme assays. DNA was extracted from soil and the ITS region was sequenced to determine fungal community structure and diversity. While tillage significantly affected fungal community structure (p < 0.01), there was no effect of PST on either community structure (p = 0.59) or diversity (p = 0.52). This indicates that PST does not affect bulk soil fungal communities; however, they may have an impact at different temporal or spatial scales than those studied here. Across all treatments, fungal community structure correlated with soil water holding capacity (rs = 0.23, p = 0.04) and electrical conductivity (rs = 0.26, p = 0.01). Despite not finding an effect of PST on fungal communities, we did find that PST increased potentially mineralizable nitrogen under no-till and shifted community level physiological profiles determined by substrate-induced respiration. These results suggest that while PST can affect certain aspects of soil health, there are no clear effects on the soil fungal community.