Understanding, predicting, and responding to a rapidly changing Arctic requires sustained observations that capture variability and transformative change of the Arctic systems with all its major components. A key challenge for researchers, Arctic communities, and others tasked with effective responses to such change is to achieve structured coordination of numerous individual observing activities and networks. These have different regional and thematic foci. Many are driven from the bottom-up by research interests, while others are mission-oriented operational networks. The Arctic Observing Summit (AOS) is an effort that seeks to help coordinate such disparate activities and support efforts such as the Sustaining Arctic Observing Networks (SAON) initiative. We report on progress as part of an AOS 2018 working group focused on implementation and optimization of sustained observations. Drawing on the Framework on Ocean Observations, our group identified effective approaches and barriers to integration of different observation requirements and activities/platforms into a coherent observing framework. Case studies for benthic communities, sea ice prediction, and permafrost highlighted the importance of allowing for independently driven activities to coalesce into a uniform framework. This in turn requires clearly defined requirements that ideally serve multiple societal benefits. Such clear definitions also aid private-public partnerships and the development of new observing system business models. Prerequisite to better coordination is a comprehensive, international assessment that describes the current set of systems, community-based networks, sensors, networks, and surveys that are used to observe the Arctic today. Pieces of such an endeavor are starting to emerge, and SAON may serve as a home for integrating and building upon these pieces. Essential to this goal is the development of a knowledge map that collates and connects observing resources to societal benefits, helps identify and prioritize essential variables, data management needs, and critical products and services. The AOS 2018 calls for the launch of an optimization and implementation team of experts that would conduct such an effort under the auspices of SAON. We explore different elements of such a team’s portfolio of tasks.

Extreme floods which overwhelm the capacity of a system of flood control dams may result in overtopping one or more of those structures. Traditional US Army Corps of Engineers analysis of hydrologic hazards isolates the study area to a single dam. However, in watersheds where flood hazard is managed by several dams, the estimate for the annual probability of overtopping a dam may be influenced by the operation of one or more other dams in that system. Evaluation and prioritization of modifications for dam safety in a portfolio of structures requires a sound estimate of overtopping probability for every structure. In an effort to properly characterize the hydrologic hazard for five dams in the Trinity River Basin above Dallas, Texas, synthetic weather generation coupled with hydrologic and reservoir models is applied to extend the stage-frequency curve for each dam beyond the observed record. The synthetic weather model is comprised of processes which typify floods most likely to result in overtopping the study dams: 1) continuous, local-scale precipitation and temperature sampling to characterize antecedent hydrologic conditions, 2) intermittent (inhomogenous Poisson), synoptic-scale precipitation sampling based on regional precipitation-frequency analysis to generate hazardous floods, 3) k-nearest-neighbor resampling of precipitation and temperature spatiotemporal patterns and 4) temporal disaggregation of daily precipitation to hourly using correlated Brownian processes. Interrelations between local-scale precipitation, synoptic-scale precipitation and temperature are preserved using a Gaussian copula. Natural variability in annual maximum reservoir stage is described using a stratified sampling scheme used to disproportionately represent extreme floods in a fixed sample of 1,000 events, resulting in fewer model events required to span the probability space from 0.5 to 10-8 annual exceedance probability. Knowledge uncertainty in model components is estimated using a parametric bootstrap, resulting in multiple realizations of synthetic weather. Each weather realization of 1,000 events generated using varying parameters is routed using hydrologic and reservoir models for the system which produce a posterior distribution of annual overtopping probability for each structure.

The ocean floor broadband seismology has been established based on several practical observations by using broadband ocean bottom seismometer (BBOBS) and its new generation system (BBOBS-NX) in Japan since 1999. The data obtained by our BBOBS and BBOBS-NX is adequate for broadband seismic analyses, especially the BBOBS-NX enables the quality of the horizontal data comparable to land sites in longer periods (10 s –). And, the BBOBS-NX with tilt measurement function, BBOBST-NX, is in practical evaluation for the mobile tilt observation that may realize a dense seafloor geodetic monitoring with low cost. The weak point of the BBOBS-NX system lies in the intrinsic limitation of the submersible in its operation. If this system can be operated alone like as the BBOBS, it should be a true breakthrough of ocean bottom seismology. We call this new autonomous BBOBS-NX as the NX-2G in short. Several problems to realize the NX-2G have been almost cleared through test observations since 2012. The function of the NX-2G system is based on 3 stage operations as shown in the image. The glass float is added to obtain enough buoyancy to extract the sensor unit from the seafloor and also to suppress the oscillating tilt of the system in descending, not to exceed the tilt allowance of the broadband seismic sensor. In Oct. 2016, the first in-situ test of the NX-2G system was performed. The landing of the NX-2G looked well and the maximum tilt in descending was about ±2.5°, that ensured the effective suppression for the oscillating tilt by the glass float. As the final step test of the NX-2G, the one-year-long observation has been started in April 2017 with the BBOBS deployed nearby, to obtain simultaneous data for the noise level evaluation. The free-fall deployment and the transition from the landing stage to the observation stage were completed, those were monitored through the acoustic communication from the ship. This NX-2G was recovered in Oct. 2018 with the ROV, KAIKO Mk-IV, to watch the transition from the observation stage to the recovery stage at the seafloor. All function of the NX-2G at the seafloor was perfect with immediate extraction of the sensor unit. Noise level comparison with the BBOBS shows about 10 dB improvement that is not enough as expected, which may lie in a small tension of the cable between the sensor unit and the recording unit. And, scenes of the landing and the first transition were selfied by the Deep-Sea CAM.

Groundwater occurrence in crystalline basement complex is mainly due to the development of secondary porosity and permeability arising from the weathering and fracturing of the low porosity igneous and metamorphic basement rocks. In this study, geophysical survey involving seismic refraction and 2D electrical resistivity tomography (ERT) was conducted to assess the hydrogeological characteristics of the weathering profile of the crystalline basement rocks in Olomore, Abeokuta, southwestern Nigeria. The 2D ERT survey was conducted along five Traverses using dipole-dipole array with a minimum electrode spacing of 5.0 m in Traverses 1, 2, 3 and 5, and 10.0 m in Traverse 4, and a dipole separation factor of 1 – 4 in all the traverses; the observed apparent resistivity data were inverted using RES2DINV. The seismic refraction survey was conducted along the same traverses using 10 Hz electromagnetic geophones; the refraction data were processed using SeisImager with the first arrival travel times picked using Pickwin module and inverted using Plotrefa to obtain velocity model of the subsurface. A good correlation exists between the 2D ERT images and the seismic refraction velocity models. The effective depth of investigation for both ERT and seismic refraction is approximately 43.0 m in all the traverses except for ERT of Traverse 4 which 66.0 m depth of investigation. Four lithologic layers may be inferred with varying model resistivity and P-wave velocity range of 546-974 m/s, 1456-1877 m/s, 2042-2944 m/s, and 3041-6894 m/s respectively. Both ERT and seismic refraction images indicate that the regolith (collapsed zone and saprolite) is relatively thin (< 10.0 m) and may be unable to support adequate drawdown for good yield. But the weathered and fractured basement is sufficiently thick to support adequate drawdown for high groundwater storativity and yield; depth-to-bedrock is greater than 20.0 m in most part of the study area. The study shows that the combination of ERT and seismic refraction is effective for near-surface characterisation for hydrogeological investigations in crystalline basement complex.

The resonant charge exchange coupling between H+, H, O+ and O is a major driver of H+ and O+ transport between the plasmasphere and topside ionosphere. In this work, we present a new technique to derive model-independent neutral atomic hydrogen density, [H], based on parametric solution of the proton continuity equation including charge-exchange-driven transport. Estimation of [H] using the proton continuity equation incorporates atomic oxygen density [O] derived from the inversion of 135.6 nm OI emission measured by TIMED/GUVI and coincident ionospheric parameter measurements from the Arecibo incoherent scatter radar. Furthermore, by solving both the H+ and O+ continuity equations simultaneously, this work also quantifies the field-aligned vertical transport of protons between the plasmasphere and ionosphere and its effect on maintenance of the nightside and dayside ionospheric composition. Case studies during geomagnetically quiet intervals show that the transport of protons from the plasmasphere during nighttime is sufficient for the maintenance of the observed ionospheric O+ composition through reverse charge-exchange with O. Resulting O+ can diffuse upward or downward away from the source, which leads to observed counter-streaming of H+ and O+. Higher O+ densities on the dayside result in the charge-exchange production of H+, which acts as a source of protons to the plasmasphere. In summary, this work provides an unprecedented, model-independent quantification of diurnal conservation of plasmaspheric protons and its effect on ionospheric variability during quiet-times.

We have developed a suite of computer-based interactive educational activities for introductory sedimentology and stratigraphy courses, called SedEdu. Specifically, SedEdu is a free and open-source Python framework through which any contributor can easily and seamlessly integrate their own “module” into the suite for distribution. In this way, SedEdu is a community-built tool written by sedimentology and stratigraphy educators for sedimentology and stratigraphy educators. The so-called modules are coupled with “activities” that guide students through a concept, incrementally introducing components of the subject, and testing for understanding and retention throughout the activity. For example, one module (“rivers2stratigraphy”) illustrates the concept of the construction of fluvial stratigraphy through a laterally migrating river that leaves behind a channel-sand body, which is subsided into a stratigraphic profile. The module allows students to modulate system properties like water discharge, subsidence rate, and avulsion timescale, and observe changes in the developed stratigraphic record. At one point during an activity accompanying this module, students are guided to decrease the basin subsidence rate, and then to measure (using in-activity tools) the change in sand-body stacking patterns before and after the subsidence change. A small-scale test was conducted, wherein the SedEdu rivers2stratigraphy module was used as a curriculum component. In the test, one section of an undergraduate sedimentology and stratigraphy class was taught using traditional lecture materials, and the other used the module on student computers. The efficacy of this style of technology-enabled active learning was tested through a multivariate assessment of student’s understanding of fluvial stratigraphy construction.

In global climate models, CO2-driven warming causes strong and very widespread mean drying trends in climatic wetness indices like the Palmer Drought Severity Index, Aridity Index and Standardized Precipitation-Evapotranspiration Index. Yet, these same simulations also predict that runoff will not decline over most of Earth’s surface, that root-zone soil moisture and evaporative fraction will decline only regionally, and that vegetation will become broadly greener. Thus, actual drought impacts of warming in these models are far less broad and severe than implied by the drought indices. Here, I probe why this “index-impact gap” occurs, and whether it is a feature of reality as well as models. In particular, I show that the discrepancies are not just limited to simulations which assume a substantial direct CO2 effect on vegetation, but are also large in greenhouse-only simulations, implying that they occur for fundamental climatic reasons rather than via CO2-physiological pathways. I also review key observational evidence that the index-impact gap has also been large over the historical era and was very evident for the last glacial-to-interglacial warming, lending much additional credence to the model output.

Rangelands cover over 50% of the land surface area in the western US, providing important economic, social and environmental benefits. The resilience of western rangelands, however, is threatened by climate change, including altered phenology and precipitation patterns, increased frequency and intensity of drought and forest fires, heightened pressure from invasive plants, and reduced water storage in winter snowpack. Climate adaptation strategies are available to ranchers, yet uptake varies substantially. Rancher decision-making is a complex function of their beliefs, knowledge, skill level, risk perceptions, and the institutions supporting them. Semi-structured interviews, focus groups and workshops will be utilized to examine how ranchers in Idaho, Montana, Wyoming perceive and respond to climate change, and the opportunities and barriers these social processes create for climate change adaptation.

The intraseasonal variation of the Tibetan Plateau summer monsoon (TPSM) during 1979–2011 is investigated. The TPSM shows a dominant quasi-biweekly oscillation (QBWO) in most summer seasons, and its active/break phases are closely related to more/less precipitation over the Tibetan Plateau. We suggest that the TPSM QBWO is associated with a southeastward propagating nonstationary wave train in the middle and upper troposphere. It shows equivalent barotropic vertical structures over the midlatitudes and a baroclinic structure over the eastern Tibetan Plateau. Wave activity flux analysis indicates that it originates from northern Europe, which is an active center of the summertime Arctic Oscillation (AO). The AO also shows significant QBWO signals and leads TPSM QBWO by about 13 days. Phase composite and wave activity flux analyses of AO QBWO confirmed that the wave train influences TPSM QBWO, suggesting that AO plays an important role in the TPSM on a 10- to 20-day timescale.

Over 33,000 flash flood events recorded by the NOAA National Weather Service (NWS) between 2006 and 2017, after polygon warnings replaced county-wide warnings, are analyzed in terms of NEXRAD (Next Generation Weather Radar) radar coverage in two ways. Events are binned in two large categories according to whether the starting point of an event falls inside or outside the range implied by the 6 kft AGL bottom-of-the-beam altitude, accounting for beam clutter and beam obstructions. Separately, events are classified according to the percentage surface area covered under the 6 kft beam height for each NWS Weather Forecast Office (WFO) or state. Emphasis is on unwarned events associated with fatalities, injuries and property damage and their relationship to WFO-area NEXRAD coverage. Significant property damage is defined in terms of the mean damage per event of about $411k. There is parity in the ratio of events warned or unwarned inside the inside/outside distance bins except for injury-event ratios. The linear fits to the traditional metrics of warned ratio (WR), false alarm ratio (FAR) and critical success index (CSI) are statistically significant and improve with more radar coverage. A stronger sensitivity is found for the WR as a function of the total number of events. New metrics are also evaluated, such as the mean flash flood partial event warning (PEW) and the ratios of unwarned to all events per WFO have statistically significant variations with radar coverage, improving with higher coverage. This is unlike the linear fits to the ratios of unwarned fatal-to-all-fatal events, which is marginally significant. Unwarned fatal-to-all-fatal, unwarned injury-to-all events and unwarned significant damage-to-nonzero damage event ratios are both not statistically significant to the 95% level of significance. The large scatter in the data results in very low coefficients of determination, and is interpreted to mean that radar coverage alone is not necessarily the primary driver though there is sensitivity to variations in such coverage.

Throughout Earth history, extensive, sub-aerial, basaltic lava flows associated with continental rifting and hot spots have been contemporaneous with major global warming—the more extensive the flows, the longer the period of eruption, and the greater the warming of air and oceans. Around 251 Ma, basalts covered an area in Siberia of 5 million km2 probably within 670,000 years, causing equatorial oceans to become highly acidic with temperatures >40°C. Approximately 96% of all marine species and 70% of all terrestrial vertebrate species went extinct in an environmental crisis mapped globally as the end of the Paleozoic. The Deccan basalts covered an area of 0.5 million km2 around 66 Ma causing warming and extinctions that formed the end of the Mesozoic. Around 56 Ma, rifting of Norway from Greenland extruded as much basalt as 3000 km3 per km of rift per million years, forming the Paleocene Eocene Thermal Maximum. Hundreds of smaller basalt eruptions punctuate the geologic time scale ending geologic eras, periods, epochs, and even ages. In historic time, the Great Þjórsá Lava, covering 970 km2 of Iceland, led to major warming around 8600 BP. The King’s Bowl and Wapi lava fields covered 700 km2 of the Snake River Plain in southern Idaho around 2250 BP during the Roman Warm Period. The basaltic volcano Eldgjá covered 800 km2 of Iceland around 939 AD, associated with the Medieval Warm Period. The much smaller volcano Bárðarbunga erupted 85 km2 of basalt in 6 months starting in 2014, the largest basalt flow since 1783, contemporaneous with sudden warming in the northern hemisphere of 0.47oC from 2014 to 2016. The rate of flood-basalt areal coverage was 0.5 km2 per day. The Kona eruption has been extruding basalts covering 0.6 to 0.4 km2 per day from May 3 through July 27. If this eruption continues for 6 months, it could affect climate as much as Bárðarbunga. Warming appears caused by ozone depletion, allowing more UV-B than usual to reach Earth. UV-B radiation is hot enough to burn skin and is 48 times hotter than infrared radiation absorbed strongly by CO2. Basaltic eruptions emit especially high volumes of chlorine and bromine, which are observed to cause ozone depletion. The exact chemical path is not yet well understood. Heat waves during the summer of 2018 are associated with a “sharply kinked” jet stream often thought caused by ozone depletion.

Climate change poses uncertain, complex, and emerging risks to local governments across the country, particularly in regions prone to flood and storm hazards. While local governments recognize the importance of finding innovative approaches to climate change adaptation, it remains a challenge for many reasons, including the high cost of policy experimentation, lack of organizational capacity, and uncertainty about the efficacy of potential adaptation strategies. These are not merely challenges of technological innovation, but also of social and policy innovation. It is increasingly recognized that collaboration is required to meet these challenges. Collaborations of various types---referred to broadly as policy networks---give organizations access to information, ideas, and other resources that may be used to adapt to climate change. Certain types of networks are hypothesized to be effective for these purposes, particularly networks that span fragmented communities and integrate different knowledge systems and resources. These types of networks tend to reduce information asymmetries and maximize the diversity of information and resources available to network actors, thus increasing capacity to manage uncertain, emerging, and complex problems. In this paper we characterize the policy network surrounding climate change adaptation in Southeast Florida that includes municipal actors as well as a diverse array of stakeholders in the public, private, and nonprofit sectors. Data are gathered using a survey of organizational representatives in the region, identified though systematic searches of organizational websites as well as nominations by other climate change professionals. Overall this study shows a complex web of collaborations where over 300 diverse actors are exchanging information about climate change and sharing resources to address adaptation. Findings demonstrate that county governments and regional nonprofit organizations, such as the Southeast Florida Regional Climate Change Compact, play a crucial role in linking disparate resources and knowledge systems in the region. These organizations help to stabilize network ties within a complex and rapidly shifting political landscape, making them instrumental for the delivery of climate adaptation services.

Carbon distribution in soil is intricately linked to soil health. However, repeatable measurements of carbon distribution typically require destructive sampling and laboratory analyses. Soil carbon distributions in both natural and managed landscapes significantly vary due to numerous factors related to topography, mineralogy, hydrology, land use history, and vegetation. In order to accurately inventory soil C distributions and dynamics over time, we are developing a new technique that relies on neutron inelastic scattering to measure elemental distribution. This approach can be used to image a volume of approximately 50 cm × 50 cm × 30 cm (depth) with a few centimeters resolution, for example the root zone of a plant. To achieve this, we use neutrons created in a deuterium-tritium fusion reaction. The products of this reaction are an alpha particle and a neutron. Due to momentum conservation, both particles are emitted in opposite directions in the center-of-mass frame. This allows us to measure the neutron direction by detecting the alpha particle with a position sensitive detector. The neutron can then induce an inelastic scattering reaction on a carbon nucleus present in the soil, and this event produces a gamma ray with a characteristic energy for the carbon isotope. Using a gamma detector, we measure these gamma rays, which allows us to perform time-of-flight analysis between arrival times of the alpha and gamma particles. Using the information from both measurements (alpha and gamma), we can reconstruct the spatial distribution of the carbon atoms and other elements in soil. We will report on the design, potential applications, and limitations of the instrument. We will also report on initial results from laboratory experiments and progress towards future field experiments. The information, data, or work presented herein was funded by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Contract No. DE-AC02-05CH11231.

The ice sheet-ocean modeling community is making large strides toward developing coupled models capable of examining the interactions and feedbacks between ice shelves and ocean along the Antarctic margin. We present preliminary results and address some of the challenges that have arisen during the development of a coupled ice sheet-ocean model. The ice sheet model is icepack, a shallow-shelf finite element model written in Python. The ocean model is the Regional Ocean Modelling System (ROMS), a terrain-following vertical (sigma) coordinate model that has been modified to interface with a moving ice shelf. These two models are coupled in an online configuration using the Framework for Ice Sheet Ocean Coupling (FISOC). The use of a model with sigma coordinates for the ocean component introduces a simplification and a complication to modeling a moving ice draft. The sigma coordinate system retains the same number of vertical layers at any depth, eliminating the need to convert grid cells between ice and water, when using a fixed grounding line configuration. However, as the ice shelf draft evolves in time, topographic configurations develop that induce pressure gradient errors in ROMS. We quantify these errors in an idealized set-up with an artificially changing ice draft following the ISOMIP+ geometry. We compare results between an ice draft that is smoothed to meet standard ROMS smoothing criteria (rx0, rx1) and a non-smoothed ice draft. Finally, we present a simple parameterization in a buffer zone near the grounding line that uses interpolated melt rates from the ocean model, allowing us to maintain a steep ice topography in the ice model without inducing pressure gradient errors in the short water column in the ocean model. This model configuration will be applied to Pine Island Glacier and used to examine present and possible future states of the ice sheet-ocean system.

This paper presents a novel approach and algorithm to the problem of magnetic field interference cancellation of time-varying interference using distributed magnetometers and spacecraft telemetry with particular emphasis on the constrained computational and power requirements of CubeSats. The traditional approach to enable space-based low-amplitude and low-noise magnetometry is to develop a spacecraft magnetic cleanliness design and place the magnetometer sensor at the end of a boom far enough away from the bus to minimize remaining stray magnetic fields. In addition, secondary magnetometers are often placed partway along the boom to apply magnetic field gradiometry to clean the data further (e.g., NASA MMS has 8 meter booms with a sensor half-way down and another at the end). We employ a different approach taking advantage of low-cost chip-based magnetometers that can be placed throughout the satellite bus instead of utilizing a boom. The spacecraft magnetic field interference cancellation problem that we solve involves estimation of noise when the number of interfering sources far exceeds the number of sensors required to decouple the noise from the signal. The proposed approach models this as a contextual bandit learning problem and the proposed algorithm learns to identify the optimal low-noise combination of distributed magnetometers based on indirect information gained on spacecraft currents through telemetry. The algorithmic behaviors are tested with synthetically modeled spacecraft data and on real world data generated in a lab-based setting with telemetry and currents collected from the GRIFEX CubeSat and provides a way for accurate magnetic field measurements with CubeSats.

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.

To improve our understanding of the Canoe Reach Geothermal Field in the Rocky Mountain Trench of western Canada, we examine the distribution of local earthquakes using a network of 10 broadband seismometers deployed over a 40 by 60 km area across the trench. The Canoe Reach area exhibits strong cultural noise from communities, roads and trains that makes detecting earthquake signals challenging. We propose detecting earthquakes in the area of the trench by measuring the kurtosis of the seismic signal, which is a statistical moment representing the distribution tail and is insensitive to emerging signals but more sensitive to impulsive earthquake onsets. Examining the kurtosis of the three-component seismograms for four months of data, we identified eight local earthquakes. An earthquake catalog produced by STA/LTA detections found 11 events for the same four-month period, four of which were detected through our kurtosis approach. By further exploring the kurtosis detections, we are refining our catalog to identify the source of discrepancies between it and the STA/LTA catalog. We then estimated locations of our detected events, and the uncertainties of those locations, through nonlinear Bayesian sampling. This method treats the origin times, half-space velocities, and the picking noise for P and S arrivals as unknowns. We employed this parameterization to test whether Bayesian sampling could account for the challenging noise environment. Locating our detected events found that five events occurred outside the seismic network and three events occurred inside. The average horizontal and vertical uncertainty is 28 and 19 km respectively for the outside events. These uncertainties are lower at 7 and 9 km for the inside events. While the inside events exhibit lower spatial uncertainties than the outside events, their uncertainties remain large. We then examined whether the uncertainties could be further improved by jointly locating multiple events. Jointly inverting two of the events from within the array decreased their average horizontal uncertainty from 6.5 to 2.5 km and the vertical from 14 to 7 km. Reducing uncertainties in the locations of the events in this manner will clarify their distribution and all for an improved understanding of the seismicity and structure of the Rocky Mountain Trench.

We propose a new numerical code based on a new multi-species theoretical model to study the mass, momentum and energy exchanges (MMEE) that happen across the magnetospheric boundaries. We use two distinct populations for ions, one cold and one hot (plus one neutralising electron population), to take into account the differences between the properties of the plasmas coming from the magnetosphere and from the solar wind. This approach represents a step forward in the context of the study of coupled large-scale plasma systems being a new and efficient compromise between fluid and kinetic codes in tracing the different plasma contributions during MMEE. Due to the very important role that magnetic reconnection plays in connecting the shocked Solar Wind to the Earth’s magnetosphere, we show and discuss the results we obtained about the simulations of the tearing mode instability occurring across an Earth’s magnetopause that we modelled thanks to our most recents MMS observations [Rezeau 2018]. Rezeau, Belmont, Manuzzo, Aunai, Dargent, 2018, Journal of Geophysical Research: Space Physics, 123, doi: 10.1002/2017JA024526.