CUMULOS is a tiny three-camera VIS/SWIR/LWIR sensor system flying as a hosted payload on the NASA/JPL ISARA mission, a 3U CubeSat. The CUMULOS sensors provide a small-aperture, large field-of-view, remote sensing payload suitable for testing the performance of passively-cooled commercial sensors for weather and environmental monitoring missions. The CUMULOS consists of a 0.4-0.9 µm visible CMOS camera, a 0.9 -1.7 µm short-wave infrared InGaAs CMOS camera, and a 7.5-13.5 long-wave infrared VOx microbolometer camera. All three cameras and associated electronics fit into less than 1U of spacecraft volume and were accommodated on the ISARA mission on a non-interference basis. CUMULOS is designed for point-and-stare imaging and acquires almost simultaneous 3-band coverage of regions approximately 200 x 150 kilometers in size, at ground sample distances from 130 to 400 meters from an orbital altitude of 450km, 52° inclination. Remote sensing applications being investigated include: hotspot detection (including fires, gas flares, and volcanic activity), detection of nighttime lights, cloud cover detection, surface temperature characterization, and airglow phenomenology. Operational since June 2018, the sensors have taken sample daytime and nighttime cloud imagery including, notably, the detection of airglow-illuminated clouds by the SWIR camera operating in high-sensitivity mode. The LWIR microbolometer camera provides useful single-band cloud and earth surface thermal imagery. The visible camera can provide daytime pictures as well as high-sensitivity nightlights imagery. The combination of all three cameras working together has proven quite successful for characterizing nightlights and thermal hotspots in manner similar to the much larger VIIRS payload that flies on JPSS, and for researching compact sensor nighttime weather imaging possibilities. We present example results on nightlights mapping of urban areas and road networks, detection of gas flares and other industrial heat sources, detection of urban heat islands, and demonstrate how the combination of sensors work together to map light and thermal features of rapidly developing urban areas. CubeSats sensors, such as CUMULOS, can complement existing of larger space sensors, such as VIIRS, by acting as testbeds for new spectral bands, imaging at higher resolutions over smaller fields of view, and flying in different orbits to measure nightlights signatures at different times during the night. The CUMULOS is also an engineering test bed for developing techniques for the calibration of small sensors in space, demonstrating a calibration and georegistration data pipeline, and automating CubeSat remote sensing data collection. These experiences, lessons and procedures will be described as well.

In this study, we use a doubly stochastic model to develop a short-term eruption forecasting method based on precursory signals. The method enhances the Failure Forecast Method (FFM) equation, which represents the potential cascading of signals leading to failure. The reliability of such forecasts is affected by uncertainty in data and volcanic system behavior and, sometimes, a classical approach poorly predicts the time of failure. To address this, we introduce stochastic noise into the original ordinary differential equation, converting it into a stochastic differential equation, and systematically characterize the uncertainty. Embedding noise in the model can enable us to have greater forecasting skill by focusing on averages and moments. In our model, the prediction is thus perturbed inside a range that can be tuned, producing probabilistic forecasts. Furthermore, our doubly stochastic formulation is particularly powerful in that it provides a complete posterior probability distribution, allowing users to determine a worst-case scenario with a specified level of confidence. We verify the new method on simple historical datasets of precursory signals already studied with the classical FFM. The results show the increased forecasting skill of our doubly stochastic formulation. We then present a preliminary application of the method to more recent and complex monitoring signals.

The ability to access time series data with one API would significantly enhance science data interoperability. The Heliophysics Application Programmers Interface (HAPI) is a simple, standardized mechanism for exposing time series data through a service. HAPI is being adopted by data centers within the Planetary and Heliophysics communities, especially for plasma, particle and field datasets. At the recent COSPAR meeting, the Panel on Space Weather passed a resolution encouraging data providers to have at minimum a HAPI server to deliver time series data. The COSPAR is now considering the resolution for full organizational endorsement. HAPI standardizes the two key parts of a data service: the request interface and the result format. The request interface is very simple and captures the common features of many existing data access services. For result formats, the HAPI specification allows several options, all of them streaming. Servers must provide a Comma Separated Value (CSV) result format, but may optionally provide a JSON or binary stream as well. The details of the request and result formats are described in the current version of the specification document, which is available at GitHub: https://github.com/hapi-server/data-specification. Several institutions have recently added HAPI-compliant access. These include the large Heliophysics archive at Goddard’s Coordinated Data Analysis Web (CDAWeb), as well as the Planetary Plasma Interactions node of the Planetary Data System, the Laboratory for Atmospheric and Space Physics at CU Boulder, the University of Iowa, George Mason University, and the Johns Hopkins University Applied Physics Lab. Multiple client options are available for accessing HAPI data from the growing number of servers. Autoplot (Faden, et al, 2010) and SPEDAS (http://spedas.org/wiki) both read HAPI data, and other clients (Java, Python, Matlab, IDL) can be downloaded from the HAPI Github project. The ease with which various providers have adapted existing servers to create a HAPI-compliant capability shows that it does capture a useful way to represent time series data. Because clients for reading HAPI data are also easy to create, we anticipate significant growth and interest in this emerging standard. Faden, et al, Earth Sci Inform (2010) 3:41–49, DOI 10.1007/s12145-010-0049-0

Pressure ridges are deformation features within the sea ice pack created through the collision of sea ice floes. Pressure ridges play an important role in ice drift and influence the mass and energy budgets of the Arctic Ocean. Over the past decade annual airborne surveys over Arctic sea ice have been conducted in late winter (March and April) by NASA’s Operation IceBridge (OIB) mission. A total of 74 OIB flights between 2010 and 2018 surveyed tens of thousands of kilometers of sea ice, providing observations of pressure ridges at a higher spatial and temporal resolution than previous airborne studies. Here we utilize Digital Mapping System (DMS) imagery to identify shadows cast by pressure ridge sails and, then, use these shadows to derive sail height. Over 64,000 DMS images were analyzed, allowing for more than 33 million individual sail height measurements to be calculated. We present the full sail-height distributions of new pressure ridges recently formed across a range of ice conditions on first-year (FYI) and multiyear ice (MYI), and we assess year-to-year variability. We find distinct characteristics depending on the ice type in which the pressure ridge formed. The mean and standard deviation of sail heights on FYI is ~20-30 cm lower than those formed on MYI. Maximum sail heights on FYI are ~1.5 m lower on average. Arctic sea ice is getting younger, shifting from predominantly MYI to predominantly FYI. Our results may inform new model parameterizations of pressure ridges on sea ice in the changing Arctic, thereby supporting advances in sea ice forecasting.

Multiple generations of ductile and brittle deformation recorded in the Obsidian Dome lava, California, inform on the rheological complexities of silicic lava emplacement. Understanding the non-linear rheological evolution of advancing lava is key to improving understanding of the durations, extents, and explosive hazards of future eruptions. Numerous studies of silicic lavas, at Obsidian Dome in particular, have focused on micro-scale textures and features interpreted to record flow within the conduit, primarily. How the lava flowed as a growing mass outside the conduit is largely unconstrained. Field observations at Obsidian Dome identify cycles of ductile flow followed by brittle fracturing, followed by relaxation and continued flow. Mode 1 vertical fractures often served as conduits for tephra venting, presumably following spontaneous exsolution-driven vesiculation and volume expansion deeper in the lava. Tephra, often tack-welded to the fracture surfaces, are preserved in many fractures that clearly closed-up on relaxation of the obsidian. Therefore, crossing the glass transition was likely strain rate driven, rather than cooling- or exsolution-driven that would have inhibited relaxation after the stress was released. The interplay between flow and fracturing is also evident in the ubiquity of crease structures at decimeter to decameter scales over all of Obsidian Dome. Unraveling the complexities of flow and fracturing in obsidian lavas will require and enable improved understanding of similarly non-linear rheological evolutions in ice, salt, the mid crust, and the asthenosphere.

Spectrometer/Telescope for Imaging X-rays is one of the instruments on-board the Solar Orbiter mission. It will be launched in 2020 into heliocentric orbit, with perihelion distance ~0.3 AU. The instrument is a Fourier X-ray imager operating within a range of 4-150 keV. The heliocentric orbit of the spacecraft can be highly affected by streams of solar energetic particle. This will affect the instrument operation by distorting obtained spectra and will complicate image reconstruction. Therefore we performed Geant4 simulation of particles interaction with the instrument, assuming realistic scenarios SEP events. We calculated direct detectors hits as well as secondary radiation from instrumental parts. We have found that the latter may highly influence measured X-ray spectra and reconstructed images, and have to be taken into account during data reduction.

Extension and rifting of the lithosphere is fundamental to the evolution of the continents, but the mechanism by which the lithosphere thins remains enigmatic. Using new dense magnetotelluric array data collected within the rifted margin and adjacent areas of Southeast China, we resolve the three-dimensional electrical structure of the lithosphere to constrain the process of rifting and thinning. Our measurements discover a brittle-ductile transition zone featuring low electrical resistivity and low seismic velocity in the Cathaysia Block. A southeast-directed dip is resolved for the Jiangshan-Shaoxing Fault that documents the Neoproterozoic suturing of the Yangtze and Cathaysia Blocks, and has been reactivated by the Early Paleozoic and Early Mesozoic intracontinental orogenies. It acted as a low-angle detachment fault during the Mesozoic-Cenozoic extension and rifting. Given the asymmetries of topography, electrical resistivity, Bouguer gravity anomaly and Mesozoic volcanism across the Gan-Hang Rift, an asymmetric simple shear extension model is proposed for the South China Mesozoic-Cenozoic rift system. Water content of up to 0.1 wt% and melt fraction of up to 1% are estimated at 70 km depth beneath the central Wuyi Mountains, suggesting hydration of the mantle lithosphere. The hydration weakening of the mantle lithosphere promoted both the gravitational instability and convective removal of the lowermost lithosphere in South China.

The application of a physics-based earthquake simulation algorithm to the central Apennines region, where the 24 August 2016 Amatrice earthquake (Mw6.2) occurred, allowed the compilation of a synthetic seismic catalog lasting 100,000 years, and containing more than 300,000 M ≥ 4.0 events, without the limitations that real catalogs suffer in terms of completeness, homogeneity and time duration. The seismogenic model upon which we applied the simulator code, was derived from the DISS 3.2.1 database (http://diss.rm.ingv.it/diss/), selecting all the fault systems that are recognized in the central Apennines region, with a total of 54 fault rectangular segments. The physical model on which the last version of our simulation algorithm is based includes, besides tectonic stress loading and static stress transfer as in the previous versions, also the Rate & State constitutive law. The resulting synthetic catalog exhibits typical magnitude, space and time features, which are comparable with those of real observations. These features include (i) an earthquake magnitude distribution departing from the linear Gutenberg-Richter distribution in the moderate and higher magnitude range, (ii) long–term pseudo-periodicity of strong earthquakes and (iii) short- and medium-term earthquake clustering. We found in our synthetic catalog a clear trend of long-term acceleration of seismic activity preceding M ≥ 6.0 earthquakes and quiescence following those earthquakes. A typical aspect of the observed seismicity in Italy and of the Central Apennines region in particular, is the occurrence of multiple events of M ≥ 5.5 earthquakes close to each other in space and time. A special attention was devoted to verify if the synthetic catalog includes this feature. On this purpose, we applied a specific code written in “Mathematica” to count the number of multiple events contained in a seismic catalog under a quantitative definition, finding that the synthetic catalog contains a large number of multiple events but not as frequently as in the real catalog. Lastly, as an example of a possible use of synthetic catalogs, a ground motion prediction equation was applied to all the events reported in the synthetic catalog for the production of PSHA maps (in terms of PGA).

The projected response of the atmospheric circulation to changes driven by increasing greenhouse gas concentrations is highly uncertain. One of the primary reasons for this is that the state-of-the-art models we employ to investigate these responses struggle to represent basic features of the midlatitude circulation such as storm tracks, jets and blocking. Biases also have detrimental effects on predictive skill for dynamically driven fields at climate prediction time scales of seasons to decades. Despite this, physical understanding of the controls on these features and the drivers of their biases is still limited. Here we investigate a hierarchy of large ensemble climate reanalysis and hindcast simulations performed by the Norwegian Earth System Model (NorESM). Each ensemble is 30 members and was run from 1985-2010. For the reanalysis runs various data-assimilation strategies were employed. These are: SST only, SST plus hydrographic profiles, SST plus hydrographic profiles plus sea-ice concentration. The assimilation was performed monthly after which the model runs freely. These are compared to both free runs and AMIP-style simulations with ERA-Interim serving as ground truth. We evaluate the North Pacific and North Atlantic jets in winter and summer. We also identify where the observations lie within the predictive distribution of the ensemble. Results show that the North Atlantic jet is too zonal, extends too far into Europe and is shifted northwards. Virtually the entire North Atlantic sector lies outside the predictive distribution of the ensemble and performance actually degrades in the simulations with tighter constraints on the assimilation. By contrast the North Pacific jet is rather better represented in all aspects both with respect to pattern as well as magnitude of the biases. This is likely due to the better-represented teleconnections between the tropical and extratropical Pacific. Comparison of these ensembles with AMIP simulations suggests that the errors in the midlatitude circulation reside in the atmospheric component of the model. We also present results from hindcast simulations where NorCPM was initialized at different times of the year and then run forward 12 months. Implications and causes of the varying behavior among the ensembles are discussed as well as prospects for the future.

Sedimentary records provide an invaluable background for understanding of complex phenomena that vary within multiple spatio--temporal scales, such as climate and the seismic cycle. Understanding the latter in southern Chile has yielded motivation to develop new tools to deal with such records, in order to build a comprehensive peleoseismic catalog from them. The region inherited an extensive chain of lakes from the pleistocene glaciations, and a strong tephrochronological framework has been developed during the last two decades. Lake deposits have been extensively studied and shown to contain an incredibly sensitive paleoseismic record in the form of lacustrine turbidites. The task is thus to build the best possible chronology making use of all available data. Age--depth modeling is now routinely done by means of bayesian techniques, by using a sedimentation model as prior information and a set of age determinations as data. This approach provides the best results for any single record, but not necessarily for a set of records taken together. This is the goal of the shared chronologies approach, to build the tools for estimating the best chronologies for a set of sedimentary records given some chronological data for each and a set of shared events or stratigraphic markers. We use for this purpose the fact that two or more of such layers should yield age differences close to zero, within the general age uncertainty. This fact is incorporated to the model as prior information, along with the sedimentation model. The idea is clearly usable in a wide range of contexts, and for this reason we would like to share the implementation in a very early stage of development in order to incorporate feedback into design decisions that could affect extensibility and modularity, and to forge collaboration. This contribution shares an early experiment against a simulated data set, as well as the current R implementation and future plans.

Coral reefs are one of the most diverse ecosystems on Earth and provide significant ecological, economic, and societal benefits valued at approximately $9.8 trillion U.S. dollars per year. Since 1997, NOAA’s Coral Reef Watch (CRW) has used near real-time satellite monitoring to provide ecological nowcasting of the ocean heat stress that can cause mass coral bleaching. While this benefitted coral reef managers, scientists, and other stakeholders, our users desired longer-range forecasts. In 2012, CRW launched its probabilistic, global Four-Month Coral Bleaching Outlook system based on NOAA’s operational Climate Forecast System (now CFSv2). The Outlook proved accurate in local bleaching events over the following two years. Subsequently, June 2014-May 2017 brought the longest, most widespread, and probably most damaging coral bleaching event on record. As this global event greatly threatened all tropical coral reefs, the Outlook system proved critical in helping users worldwide prepare for and respond to bleaching – including actions to reduce damage from these intense marine heatwaves. This presentation will introduce CRW’s ecoforecasting tools and focus on four “use cases” of CRW’s Outlook system during the 2014-17 global coral bleaching event. In 2015, concern over bleaching forecasted by CRW’s Outlooks prompted two actions by the State of Hawaii. First, the “Eyes of the Reef” volunteer network organized numerous training sessions and its first state-wide Bleach Watch “Bleachapalooza” event to monitor bleaching across the state. Second, State scientists collected specimens of rare corals to preserve them in onshore nurseries. One of these species is now locally extinct on Hawaii’s reefs, and these rescued specimens are being prepared for re-introduction. Next, as CRW predicted bleaching would persist for several months in the Northern Line Islands, NOAA mounted a special cruise to monitor these remote coral reefs. The record heat stress killed over 98% of the corals at Jarvis Island. Finally, in 2016, prior to peak bleaching, Thailand used CRW’s prediction of severe heat stress to close ten heavily used coral reefs to tourism as a way to reduce further stress to the reefs. These actions show the value of ecoforecasts to prepare resource managers for further climate change impacts.

Over 270 major dams have been constructed in the Southeastern United States (SEUS) during the past century, changing natural flow patterns and affecting stream temperatures. Projected increases in air temperature combined with changes in precipitation may result in water scarcity and affect maximum stream temperatures during the summer for some regions in the SEUS. Currently existing reservoirs mitigate water shortages during drought by releasing more water but reducing residence time, the ratio of reservoir volume to inflow. Regulating stream temperature in the summer can be done by either increasing residence time or releasing more water. In this study, we investigate the extent to which the current reservoir infrastructure can be used to mitigate the impacts of climate change under current reservoir regulations as well as the range of operating rules that could minimize climate change impacts on both streamflow and river temperature. We use the Variable Infiltration Capacity (VIC) hydrological model to simulate runoff, which is then used as input to a large-scale river routing-reservoir model (MOSART-WM) to simulate reservoir operations and produce regulated streamflow. VIC and MOSART-WM outputs are then used as input to a stream temperature model that accounts for thermal stratification in reservoirs (RBM-res). Climate change projections are based on two representative concentration pathways (RCPs) and multiple global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We compare modeled changes with those from a model implementation that does not include any reservoirs and which therefore lacks any flow regulation (VIC->MOSART-RBM) to evaluate the resilience of current reservoir infrastructures. We also evaluate different reservoir operating rules (residence time versus low flow mitigation) to investigate the extent to which the current reservoir system can be used to mitigate the impacts of climate changes on both streamflow and stream temperature.

We developed a new experimental system with which anelasticity of a rock analogue sample (polycrystalline borneol) can be measured in situ during dislocation creep. We attached a piezo-electric actuator to a triaxial deformation apparatus, to add a small cyclic load to a large constant load. We also attached a load cell and two laser displacement meters to measure the small cyclic load and displacement accurately. Using this new system, we deformed a polycrystalline borneol sample under diffusion creep (σ = 0.27 MPa) for about 1 day, intermediate creep (σ ≈ 1.1 MPa) for about 0.5 day and dislocation creep (σ ≈ 2.2 MPa) for about 1 day continuously, and performed an in-situ measurement of Young’s modulus and attenuation at frequencies of 2.5 and 1.0 Hz. During the first diffusion creep, Young’s modulus increased, probably due to the improved contact between the sample and the piston, and reached a constant value. Although the modulus did not change during the second intermediate creep, it gradually decreased during the third dislocation creep. The final modulus reduction was about 20%. The present result supports our previous result obtained from the anelasticity measurement of a pre-deformed sample (Sasaki et al., 2017, AGU fall meeting; Sasaki et al., 2019, submitted to JGR). In the previous study, we showed that detailed form of the dislocation creep curves can be explained well by considering a gradual increase in dislocation density during the dislocation creep. Also, reduction of Young’s modulus by about 10% was observed after the dislocation creep under the similar condition to this study. The gradual decrease in Young’s modulus observed in this present study provides a supporting evidence for these previous results. Frequency dependence of the dislocation-induced anelasticity obtained from our previous study is a peak at much higher frequency than the grain boundary-induced anelasticity (Sasaki et al., 2017, AGU fall meeting; Sasaki et al., 2019, submitted to JGR). In contrast, dislocation-induced anelasticity obtained from single crystal forsterite or polycrystalline olivine is a broad absorption band (Guéguen et al., 1989; Farla et al., 2012). It is important to clarify the reason for this discrepancy.

Wetlands are the most important natural source of methane (CH4) to the atmosphere. When present, plant efflux is often the dominant pathway for methane emissions from the anoxic wetland sediments, however, they are rarely considered in chamber measurement campaigns of CH4 flux in wetlands. While studies have focused on the mechanisms that govern transport through plant structures, none have addressed how CH4 emissions relate with carbon uptake or how this relationship may vary among plants. Understanding this relationship has important implications for linking carbon flux at the ecosystem level to wetland CH4 emission predictions, and ultimately, to help improve current carbon budget and greenhouse gas models of wetlands. This study presents simultaneous measurements of CH4 and CO2 fluxes in three macrophyte species of different cosmopolitan genera: Typha (emergent), Nelumbo, and Nymphaea (floating attached). These measurements were conducted using the Picarro GasScouter G4301 fitted with custom-designed leaf chambers. Chamber measurements were performed three times during a day (morning, noon and afternoon), in three separate months. Results indicate significant negative correlations between CH4 flux and carbon uptake in Nelumbo and Nymphaea species and a non-significant positive correlation in Typha sp. We term the rate of CH4 flux per unit CO2 uptake – CH4 flux efficiency. We found that in Nymphaea CH4 flux efficiency is almost double that of Nelumbo. These results suggest the dependence of CH4 efflux in stomatal conductance in the floating attached macrophytes, while in the Typha CH4 flux is primarily through other pores, probably aerenchyma, not regulated by stomata. Our results emphasize the importance of species-specific knowledge and considering the growth type of different wetland macrophytes (e.g. emergent vs floating attached) in scaling of bottom-up observations and ecosystem models.

One third of all coastlines worldwide consist of permafrost. Many of these permafrost coasts are presently exposed to greater environmental forcing as a consequence of climate change, such as a lengthening of the open water season, intensified storms, and higher water and air temperatures. As a result, increasing erosion rates are currently reported from various sites across the Arctic. It is crucial to synthetize these data on Arctic shoreline dynamics in order to improve our understanding on present coastal dynamics on the pan-Arctic scale. A first synthesis product was released in form of the Arctic Coastal Dynamics databse in 2012, which included data published until 2009 (Lantuit et al., 2012). Since then, numerous publications and data products were published on short and long term changes of Arctic coasts across a wide range of study sites. We made an extensive literature review of publications released within the last 10 years and updated the shoreline change data section in the Arctic Coastal Dynamics database. While in 2009 for one percent of the Arctic shoreline data on coastal dynamics was available, the addition of new data leads to a broader data coverage, which is mainly the effect of the greater availability of remotely sensed products for analyses conducted in these remote regions. Further, the additional data allow us to update the current mean rate of Arctic shoreline change.

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.

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.

Mongolia has a complex tectonic history. The lithosphere was formed from multiple plate collisions in the Neoproterozoic - Early Paleozoic associated with the Central Asian Orogenic Belt. The region has since been modified by Mesozoic rifting, Cenozoic magmatism, and major strike-slip faulting along terrane boundaries and sutures. Central and Western Mongolia are part of the larger high elevation, low-relief Mongolian Plateau. To gain deeper understanding of modern deformation within the Hangay Dome in Central Mongolia, two years of teleseismic, regional, and local seismicity, recorded by a dense array of 72 temporary broadband seismic stations, was used to determine the distribution of seismicity and crustal structure. Results from receiver function analysis indicate the Hangay Dome has a crustal thickness ranging from 41-59 km. The thickest crust resides under areas of high topography and generally thins to the east. Average Vp/Vs ratios range from 1.77-1.8. We located the 7680 events detected by the array using a local 1D velocity model. Many events outline the Bulnay and Bogd faults, where historic Mw 8 earthquakes have occurred. Considerable seismicity is observed on the South Hangay – Bayan Hongor Fault System, including a Mw 4.6 earthquake. Seismicity is also observed along the Egiin Davaa and Mogod Faults. Preliminary results from a joint tomographic inversion for earthquake location and 3D velocity structure show a relatively uniform crust, where P-wave velocities in the uppermost crust range from 5.8-6 km/s. In these preliminary inversions, large portions of the region show Vp exceeds 7.0 km/s in the lower 10-15 km of the crust. The depth to the Moho is consistent with results from the receiver function analysis. Lateral velocity variations generally align with terrane boundaries and faults, such as the South Hangay - Bayan Hongor Fault System. Seismicity relocated in the inversion outline the South Hangay, Egiin Davaa, and Bulnay Faults. In addition, a cluster of seismicity locates between the Egiin Davaa and Hag Nuur faults, where no fault has previously been mapped. Seismicity in the Hangay Dome is generally confined to the upper 20 km, suggesting a rheological transition from brittle to ductile at this depth.