Accurate sub-seasonal to seasonal (S2S) weather forecast between 2 weeks and several months is crucial to making informed decisions regarding changes in the risk of extreme weather events, resource management, agriculture, forestry, public health, energy, etc. However, significant gaps exist between the needs of society and what forecasters can produce, especially over longer lead times. Using three goodness-of-fit metrics, this study examined the ability of the SOMs-generated CFSv2 to forecast the correct (observed) circulation pattern, as opposed to the actual observed gridded field over a 90-day forecast period. Mean sea-level pressure (MSLP), near-surface wind (wnd10m), 850-mb temperature (t850), and 700-mb geopotential heights (z700) from the North American Regional Reanalysis were used to categorize the synoptic-scale circulation for three regions (East, West, and Gulf) across North America from January 1979 – December 2016. Expectedly, forecast skill generally decreased from the first day down to the skill of climatology (after 10 -15 days) and also varied regionally, seasonally, and between variables. The forecasts for the winter and summer seasons outperformed others, while t850 and z700 forecasts outperformed wnd10m, except in the west region. More importantly, this study found that the SOMs-generated CFSv2 forecasts improve upon the skill of the raw CFSv2 forecast near the one 1 – 2 weeks lead time. This study thus demonstrates the potential utility of a SOMs-based forecasting method in medium-range weather forecasts.

To investigate the mechanisms involved during semi-brittle flow, we deformed Carrara marble over a confining pressure (Pc) range of 10-300 MPa and room temperature to ≈10% strain. We apply triaxial loading to intact Carrara marble and collect mechanical, ultrasound pulsing, and acoustic emission (AE) data during pressurization and deformation stages. The pulsing and AE waveforms are recorded using a pair of piezoelectric sensors. At lower Pc, microcracking is the dominant deformation mechanism, whereas at higher Pc, crystal-plastic mechanisms such as twinning and dislocation glide are favored. These changes in the activity of defect populations are manifested in changes in mechanical properties, velocity variations, and AE characteristics. Samples at higher Pc exhibit higher strength and require more work for fault-development. Transition from localized faulting to distributed barreling is observed between 50 and 100 MPa Pc. We track precise velocity variations from the pulsing waveforms using correlation-based methods. During the pressurization stage, the velocity increases logarithmically with Pc between 0-100 MPa, followed by a linear increase at higher pressures. During the deformation stage, the compressional wave velocity initially increases before the yield point due to closing of crevices, and then decreases exponentially after the yield point. The rate of this velocity decay is smaller as Pc increases, owing to reduced microcracking with very little change at Pc ≥ 200 MPa. AE data show that individual defect types emit characteristic patterns. Twinning produces repetitive patterns of low amplitude, short signals localized in frequency space whereas microcracks are more energetic, emit over a much broader frequency range, and show more variation in signal shape and duration. The AE spectra shift from ≈ 500 kHz to ≈15 MHz mean frequency as Pc increases, which is associated with increasing twinning activity. This acoustic data agree with microstructural observations of microcracks and crystal-plastic deformation in the samples. By joint-analyzing the stress-strain and velocity evolutions with AE observations, we obtain detailed changes in the micro-mechanisms accommodating strain in the Carrara marble and constrain the deformation modes as it goes through the brittle-plastic transition.

On January 2017, a snow avalanche devastated a Resort-hotel in the municipality of Rigopiano in Abruzzo (Central Italy), unfortunately, burying alive 40 people. In a dramatic rescue operation only 11 people could be recovered. Due to the bad weather conditions, no visual observation was made, thus making it impossible to determine the exact moment of the avalanche and to report necessary observations of the dramatic event. Many are the questions and hypotheses around this tragic event. On-site inspections revealed that the hotel was horizontally cut by shear forces and dislocated by 48 m in 70°deg;N direction, once the increasing avalanche pressure exceeded the structural shear strength of the building. Analyses of phone calls revealed that the avalanche struck sometime before 16:40, when the first emergency call was received, while the last phone call from Hotel Rigopiano before the avalanche was taken at 15:30. Subsequent inspections of the victims’ mobile phones indicates the latest possible event time as 15:54 (all times in UTC). Within this eligible 24 min time window, we scanned regional seismograms for any “suspicious” signal that could have been generated by the avalanche and found three weak seismic transients, starting at 15:42:38 UTC, recorded by the nearest operating station GIGS located in the Gran Sasso underground laboratory at a distance of approximately 17 km from Rigopiano. Particle motion analysis of the strongest seismic avalanche signal, as well as of the synthetic seismograms match best when assuming a single force seismic source, attacking in direction of 120°deg;N. Hundreds of simulations of the avalanche dynamics – calculated by using a 2D rapid mass movement simulator – indicate that the seismic signals were rather generated as the avalanche flowed through a narrow and twisting canyon directly above the hotel. Once the avalanche enters the canyon it is travelling at maximum velocity (37 m/s) and is twice strongly deflected by the rock sidewalls. These impacts created a distinct linearly polarized seismic “avalanche transient”; that can be used to time the destruction of the hotel. Our results demonstrate that seismic recordings combined with simulations of mass movements are indispensable to remotely monitor snow avalanches.

Space weather forecasting remains a national priority in the United States due to the impacts of events like solar flares to life on Earth. High energy bursts of radiation originating from solar flares have the potential to disrupt critical infrastructure systems, including the power grid and GPS and radio communications. The rise of machine learning and the development of higher-quality instruments has greatly improved solar flare prediction models over the past decade. However, the magnetogram data used for solar flare forecasting—taken by the Solar and Heliospheric Observatory/Michelson Doppler Interferometer (SOHO/MDI) and the NASA Solar Dynamic Observatory/Helioseismic and Magnetic Imager (SDO/HMI) instruments—are incompatible due to differences in the cadence, resolution, and size of the data. Furthermore, many studies only focus on data from a single instrument which disregards decades worth of potential training data that is necessary to understand solar cycles. In this work, we show Generative Adversarial Networks (GANs) can be used to super-resolve the historic lower-quality SOHO/MDI data set to match SDO/HMI quality to create a standardized magnetogram data set. The implementation of a Pix2Pix GAN produced some undesirable artifacts in the synthetic image while image translation methods CycleGAN and CUT preserved solar features present in the data more accurately, even in the absence of paired data. The resulting combined, higher-quality data set will be used to improve the predictive power of current solar flare forecasting models.

Global atmospheric ‘storm-resolving’ models with horizontal grid spacing of less than 5~km resolve deep cumulus convection and flow in complex terrain. They promise to be reference models that could be used to improve computationally affordable coarse-grid global climate models across a range of climates, reducing uncertainties in regional precipitation and temperature trends. Here, machine learning of nudging tendencies as functions of column state is used to correct the physical parameterization tendencies of temperature, humidity, and optionally winds, in a real-geography coarse-grid model (FV3GFS with a 200 km grid) to be closer to those of a 40-day reference simulation using X-SHiELD, a modified version of FV3GFS with a 3 km grid. Both simulations specify the same historical sea-surface temperature fields. This methodology builds on a prior study using a global observational analysis as the reference. The coarse-grid model without machine learning corrections has too little cloud, causing too much daytime heating of land surfaces that creates excessive surface latent heat flux and rainfall. This bias is avoided by learning downwelling radiative flux from the fine-grid model. The best configuration uses learned nudging tendencies for temperature and humidity but not winds. Neural nets slightly outperform random forests. Forecasts of 850 hPa temperature gain 18 hours of skill at 3-7 day leads and time-mean precipitation patterns are improved 30% by applying the ML correction. Adding machine-learned wind tendencies improves 500 hPa height skill for the first five days of forecasts but degrades time-mean upper tropospheric temperature and zonal wind patterns thereafter. The figure shows maps of 30-day time-mean precipitation pattern difference from the fine-grid reference for prognostic simulations: (a) 200 km baseline(no machine learning correction) (b) Using random forest correction and (c) neural net correction for temperature. humidity and surface radiation corrections. RMSE is the root mean squared precipitation difference from the reference, which is 30% less for the two machine-learning corrected simulations compared to the baseline. (d) Bar charts of the land-mean, ocean-mean and global-mean precipitation biases for these three configurations, showing the machine-learning corrected simulations remove a high bias of land surface precipitation in the baseline simulation.

PVGeo is an open-source Python package for geoscientific visualization and analysis harnessing an already powerful software platform: the Visualization Toolkit (VTK) and its front-end application, ParaView. The VTK software platform is well-maintained, contains an expansive set of native functionality, and provides a robust foundation for scientific visualization, yet the development of tools compatible for geoscience data and models has been very limited. As a software extension package to VTK and ParaView, PVGeo addresses the lack of geoscientific compatibility by creating a framework for geo-visualization. This framework is a set of tools for visually integrating geoscience data and models directly within ParaView’s graphical user interface, simplifying the required routines to make compelling visualizations of geoscientific datasets. The PVGeo package is available for download on PyPI (pip install PVGeo), documented online (http://pvgeo.org), and open-source on GitHub (https://github.com/OpenGeoVis/PVGeo) for community-driven developments.

Hydrodynamic flood modeling is computationally complex and data-intensive. The accuracy of the flood model outputs is extremely sensitive towards the quality of input parameters. These input parameters are static (mostly geomorphic) and dynamic (mostly hydrometeorological). Sensitivity analysis helps to identify the importance of each input and subsequently improves model accuracy. In various past studies, the sensitivity of only dynamic input parameters was highlighted. Moreover, the sensitivity analysis was limited to flooding of the channel (1D) or floodplain (2D) but never coupled. The present study focuses on developing a framework for global sensitivity analysis of static input parameters in a 1D-2D coupled hydrodynamic flood model, based on HEC-RAS, an open-source flood modeler developed by the U.S. Army Corps of Engineers. A set of numerical experiments was conducted in the model by perturbing the static input parameters from their standard or surveyed values to generate flow hydrographs. The Kullback-Leibler entropy was used as a metric to quantify sensitivity and was calculated by comparing non-parametric probability density functions (PDFs) of the river discharge at different locations. A Gaussian kernel PDF is found most appropriate in a goodness of fit test than other distributions. A highly flood-prone and densely populated river catchment of the Ganges basin in India, which suffers economic and life losses every monsoon, was selected to demonstrate the proposed framework. This study is the first attempt at a global sensitivity analysis in a 1D-2D coupled flood modeling system, concluding that the sensitivity of static input parameters is highly dynamic, and their importance varies spatially from u/s to d/s of the river. However, the channel roughness and land use classes were found significantly sensitive throughout the river. It is suggested that a flood modeling exercise should accompany a global sensitivity analysis, which will guide flood modelers to identify the sensitive input parameters that one should emphasize during data collection and application. Such effort ensures improved accuracy of the static input parameters resulting in better accuracy of the outputs. The proposed framework is generic and can be implemented for any river catchment prior to flood hazard and risk analyses.

Current methods of root sampling typically only obtain small or incomplete sections of root systems and do not capture their true complexity. To facilitate the visualization and analysis of entire, full sized root systems of crop plants, mesocosm growth containers were developed with an internal volume of 45 ft3 (1.27 m3). Mesocosms allow for unconstrained root growth, excavation and preservation of 3-dimensional RSA, and modularity that facilitates the use of a variety of sensors. Sensors arrays monitoring matric potential, temperature and CO2 levels are buried in a grid formation at depths of 1.25, 2.75, & 4.25 ft to assess environmental fluxes at regular intervals. Additionally, 3-dimensional water availability can be measured using ERT inside of root mesocosms. Methods of 3D data visualization of fluxes were developed to allow for comparison with root architectural traits. Following harvest, the recovered root system can be digitally reconstructed through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. Initial metrics inferred from the 3D models include root system biomass (occupied voxels), volume, flatness, convex hull volume and solidity with depth. Root systems are finally dissected and biomass measurements are made in a 3-dimensional matrix of the growth zone, while the crown is saved for X-ray CT analysis.

There is a growing need to address water security issues in Canada in relation to global warming effects and water management issues. Stable water isotopes (𝛿2H and 𝛿18O) have become a popular tool to investigate regional and country level public water distribution systems to identify regional water resource issues and their underlying causes. In this study, we built the first national level maps of isotopic values in tap water across Canada using 576 tap water samples that were collected during the summer season. Observed isotopic values in tap water follow similar patterns as precipitation with highest isotopic values in the coastal and Great Lakes regions and a progressive decrease as continentality increases with lowest values found in the Rocky Mountains. We classified the tap water samples based on their supply sources including groundwater, river and lake. The isotopic values of tap water sourced from groundwater and river are well-predicted by those of local annual precipitation whereas those sourced from lakes are poorly predicted. To explain this difference, we constructed a series of water balance models to predict the 𝛿2H and 𝛿18O variability of surface water across Canada. We used a digital elevation model to accumulate the isotopic composition of local precipitation weighed by precipitation (total or effective) either monthly, seasonally or annually. These water balance models strongly improved the predictability of isotopic values of tap waters sourced from rivers and lakes (particularly the annual average and monthly weighted summer models, with or without accounting for evapotranspiration). Conversely, these models did not improve predictability of the isotopic values in tap water sourced from groundwater. We argue that isotope values of tap water sourced from surface water reflect the accumulation and evapotranspiration of precipitation in catchments whereas groundwater represents an annual average of the isotopic composition of local precipitation. Regionally, we find that winter precipitation and snow melt and glaciers melt from the Rockies contribute to a large part of tap water sources around the Rockies making them vulnerable to water balance changes with ongoing climate warming. In eastern Canada water management processes appear to create some significant evaporative water losses whereas in central Canada dry continental climate causes significant evaporative water loss. Our study highlights the cycling of water from precipitation to tap water across Canada for different tap water supply with implications for water managements, contamination risks and vulnerability to climate change. Our models and databases also provide an isotopic baseline for regionally important water resources monitoring as well as for human forensic cases.

Computational geoscience courses often combine domain science, math, programming, and hardware instrumentation. Ensuring students master all those skills can be daunting for professors, as well as for students who tackle these hybrid classes. Through a series of 3-day in-person workshops, faculty across the geoscience disciplines and allied science fields have collaborated to produce on-line teaching resources and a community of peers to support these multi-faceted but essential Geoscience courses. These resources support Geoscience and Science educators seeking to update their curriculum and even create whole new courses. Topics addressed include approaches to teaching, best practices for working group design, empowering students to self-advocate, building computational skills optimally, and coordinating curriculum across a department and even cross-departments. This e-lightning talk will show the resources available to educators – teaching activities including MATLAB code, presentations on teaching approaches, and course curriculum, among others. It will also highlight relevant MathWorks tools for learning and teaching, from online videos, to free, interactive MATLAB tutorials (MATLAB Onramp and more), to autograding software for MATLAB code (MATLAB Grader), with associated publicly available homework problem sets. Attendees will learn where and how to access these online resources, share their teaching challenges, and participate in future workshops.

Wildland fire smoke exposure affects a broad proportion of the U.S. population and is increasing due to climate change, settlement patterns and fire seclusion. Significant public health questions surrounding its effects remain, including the impact on cardiovascular disease and maternal health. Using atmospheric chemical transport modeling, we examined general air quality with and without wildland fire smoke PM2.5. The 24-hour average concentration of PM2.5 from all sources in 12-km gridded output from all sources in California (2007–2013) was 4.91 μg/m3. The average concentration of fire-PM2.5 in California by year was 1.22 μg/m3 (~25% of total PM2.5). The fire-PM2.5 daily mean was estimated at 4.40 μg/m3 in a high fire year (2008). Based on the model-derived fire-PM2.5 data, 97.4% of California’s population lived in a county that experienced at least one episode of high smoke exposure (“smokewave”) from 2007–2013. Photochemical model predictions of wildfire impacts on daily average PM2.5 carbon (organic and elemental) compared to rural monitors in California compared well for most years but tended to over-estimate wildfire impacts for 2008 (2.0 µg/m3 bias) and 2013 (1.6 µg/m3 bias) while underestimating for 2009 (−2.1 µg/m3 bias). The modeling system isolated wildfire and PM2.5 from other sources at monitored and unmonitored locations, which is important for understanding population exposure in health studies. Further work is needed to refine model predictions of wildland fire impacts on air quality in order to increase confidence in the model for future assessments. Atmospheric modeling can be a useful tool to assess broad geographic scale exposure for epidemiologic studies and to examine scenario-based health impacts.

Fronts, at both mesoscale and submesoscales, are generally hypothesized to play a significant role in mediating the transfer of tracers from the surface boundary layer into the interior. With the advent of computational capabilities numerous high resolution modeling studies have shown the enhancement of of vertical velocities with increasing horizontal resolution. In a carefully designed setup of an idealized channel partially blocked by meridional topography and forced by steady forcing, idealization of the Antarctic Circumpolar Current, we vary the horizontal resolution as the control parameter, and analyze the impact of enhanced vertical velocities on tracer subduction. It is found that the submesoscale-permitting simulations flux far more tracer downward than the lower resolution simulations, the 1km simulation takes up 50\% more tracer compared to the 20km simulation, despite the increased restratifying influence of the resolved submesoscale processes. A spectral decomposition of the flow and fluxes illuminated the relative importance of scales, and the inefficiency of inertia-gravity waves in influencing tracer transport. To further understand the physical dynamics in these simulations we diagnosed how energy was being transferred between the mean and eddy kinetic and potential energy reservoirs (Lorenz energy cycles), and if changing the resolution influenced this exchange. In particular we focussed on separating the dynamics of the energy cycles that are active in the interior of the water column and those that are trapped near the surface. We also analyzed the inter-lengthscale exchange of energy to understand the detailed spectral dynamics of the turbulence that is resolved. Lastly, and probably most relevant to SWOT, we looked at the energy budgets in terms of velocity and pressure structure functions, to assess the potential for the future SWOT mission to directly measure the inter-scale energy transfers at the ocean surface.

Remediation of contaminated soil sites is important to our environment and the growing population that interacts with these resources. Contamination of soil due to leaks, spills and seepage is a worldwide problem usually diagnosed by costly and time-consuming methods primarily using wet chemistry. Problems in remediation efforts involve finding technologies that are less time-consuming and more cost effective over time. Field portable spectrometers that cover key spectral ranges in the ultraviolet, visible and near infrared regions provide a solution for fast and easy identification of contaminants in soil. Using a field portable spectrometer to measure Petroleum Hydrocarbons (TPH) in soil is a fast and nondestructive method of analysis. Applying UV-VIS-NIR technology to these samples hydrocarbon spectra can potentially be characterized by four main absorption features at 1180nm, 1380, 1730nm, and 2310nm. This presentation aims to highlight the utility of field portable NIR technology for researchers in addressing potentially contaminated environments.

Eastern Africa contains a well-preserved pedogenic carbonate record, useful for contextualizing the paleoenvironment associated with key fossil and archeological evidence. One significant paleoanthropological discovery from the Turkana Basin in Kenya was Nariokotome Boy, one of the most complete examples of Homo erectus discovered to date. This site is directly associated with a paleo-Vertisol and the Natoo tuff, enabling stratigraphic correlation into outcrop records. Leveraging this opportunity, we analyzed stable isotopes of pedogenic carbonates (n=74) to study the paleoenvironmental conditions in the Turkana Basin for three time slices between 1.9 and 1.2 Ma. We interpret that the narrow range of δ18O values implies the presence of one main water source throughout the time interval. Variation in δ13C, with a standard deviation of 1.5‰ and range of 6.9‰, can thus be considered a function of landscape heterogeneity rather than changing water source. Woody cover estimates from the paleosols within this study interval suggest this area was a wooded grassland despite a significant first-order paleoenvironmental change from a marginal lacustrine environment to a fluvially-dominated one. While our record cannot resolve variability on a millennial scale, the lack of significant long term trends in percent woody cover suggest that Nariokotome Boy and other hominin communities inhabited a paleoenvironment which was relatively stable in terms of vegetation composition despite a major lacustrine regression.

The unprecedented spatiotemporal resolution of the sixty-four dual electron and ion spectrometers comprising the Fast Plasma Investigation (FPI) onboard the four Magnetospheric Multiscale (MMS) spacecraft enables us to compute terms of the Vlasov equation and thus compare MMS measurements directly to kinetic theory. Here we discuss our techniques for determining spatial and velocity-space gradients of the ion and electron distribution function from the skymaps provided by FPI. We present initial results validating and comparing the contributions from ∂f/∂t, v·∇f, and a·∇vf for a variety of kinetic plasma contexts including both reconnection and non-reconnection events, such as electron diffusion regions (EDRs), magnetic holes, and thin electron-scale current sheets. The ability to resolve gradients of the distribution function motivates comparison of MMS observations to predictions from gyro-kinetic theory and particle-in-cell (PIC) simulations as an approach for determining which physical mechanism is responsible for generating ion and electron crescent distributions observed in association with EDRs and thin boundary layers.

“Water as hazard and water as heritage” was an international workshop funded by the European Geosciences Union and run in frame of the “Spazi aperti” international event of the Romanian Academy in Rome, along with other cultural events. The “Spazi aperti” (open spaces) event is an international exhibition inviting the scholars in arts and humanities at other foreign academies in Rome, an international city. The convener of the workshop, the first author, was Vasile Pârvan fellow at that time in Rome, on a topic about water, and volunteered to the “Spazi aperti” event, whose curator was Roxana Mihaly. Fellows from different academies contributed to the book. Participation was multidisciplinary, from geosciences to archeology, art history, architecture and urban and landscape planning. Participation was also international, from Romania, Italy, the USA, the UK and Germany. In 2018 the report was published, with support of the Marie Curie Alumni Association, which also supports participation to present the book at the EGU GA in 2019. Marie Curie Alumni contributed to the book. Working on the report has been supported by two short term scientific missions in frame of the COST action TD1406 (“Intelligent management of heritage buildings”), both under the mentorship of Alex Dill, co-editor of the book, a conference stay in Karlsruhe funded by the Marie Curie Alumni Association and a mobility project of the Romanian science authority (PN-III-P1-1.1-MC2017-1334), all leading to Karslruhe, Germany. The book has also been presented at the Romanian Architecture Biennale 2018, an event in frame of the European Year of Cultural Heritage of the European Commission. The book has also been announced on platforms such as the Hungarian Academy of Sciences and CORDIS of the European Union (https://cordis.europa.eu/news/rcn/129019_de.html). A contact has been established to present also on the EGU blog. The book contains an overview of the event (both the Spazi aperti exhibition and the workshop, including its webpage) and the abstracts of the presentations, along with images and the CVs of the presenters. The presentations include: symbols of water in the work of Carlo Scarpa, water as hazard in case of earthquakes, postwar riverfront reconstruction, water in the arts, waterways across Europe, water and archaeology (architecture and archaeology, Roman baths, virtual museums), water sketching, waterscapes, precipitation estimation, water and natural risks in smart cities, pastoralism and water, new forms of water in landscape. The countries covered are in Europe and beyond (near East), including different countries in Europe than those of the authors (such as Danemark and the Balkans for example). The contributions display the dual character of water, between hazard (geoscience) and heritage (arts), and thus link to previous contributions of the first author to the EGU, co(convening) since 2002 the session on natural hazards’ impact on urban areas and infrastructure.

We perform a statistical study of 3-s ultra-low frequency (ULF) waves using MMS observations in the Earth’s foreshock region. The average phase velocity in the plasma rest frame is determined to be anti-sunward, and the intrinsic polarization is right-handed. We further examine the linear instability conditions based on drift-bi-Maxwellian distribution functions according to observed plasma conditions. The resulting instability is a solution to the common dispersion equation of the ion/ion right-hand non-resonant and left-hand resonant instabilities. The predicted wave propagation is also predominantly anti-sunward. The cyclotron resonant conditions of the solar wind and backstreaming beam ions are evaluated, and we find that in some cases, the anti-sunward propagating waves can be resonant with beam ions, which was overlooked in previous studies. The result suggests that the dispersion equation provides the 3-s ULF waves a fundamental explanation that unifies a rich variety of resonant conditions. In the later stage, the 3s ULF waves could further develop into Short Large Amplitude Magnetic Structures, contributing to the turbulence in the foreshock region.

A variety of measurements of methane in the Martian atmosphere have been made over the past 15 years, showing wildly varying indications of methane abundance, location and lifetime in the Martian atmosphere. Attempts have been made to use numerical tools such as general circulation models (GCMs) to identify source locations and timing of methane releases, but these remain inconclusive under the current approach of forward-trajectory plume modeling. Here we present results using a novel, complementary method of localizing methane surface sources by modeling passive tracer trajectories backwards in time from the locations where observations of atmospheric methane have been made. Such back-trajectory modeling employs both GCM modeled winds and a Lagrangian particle dispersion model to isolate potential upwind sources of the observed signals. This approach avoids many of the pitfalls inherent in forward-trajectory modeling approaches such as numerical diffusion and subgrid-scale motion which cannot be captured in the Eulerian framework of a GCM. We have chosen to focus on localization of the detection of methane by the Planetary Fourier Spectrometer near Gale crater around Ls=336° in MY 31. This observation is consistent with a near-coincident enhanced methane ‘spike’ observed by the Mars Science Laboratory TLS instrument. We have chosen to use the Stochastic Time-Inverted Lagrangian Transport (STILT) particle dispersion model in conjunction with the Mars Weather Research and Forecasting (MarsWRF) GCM for our back-trajectory modeling. To date, we have combined MarsWRF output with a more basic trajectory model, which advects particles based on bulk winds, and have found areas of enhanced tracer density to the north of Gale crater at prior times. Incorporation of turbulent processes in the planetary boundary layer will subject these preliminary results into test. And geological context will also be used to constrain the likelihood of these methane source locations.