Ecosystem dynamic models have been widely used to estimate terrestrial carbon flux and to project ecosystem structure and composition over time and space, because of their efficiency over direct field measurements and easy applicability to broader spatial coverage. However, such models have also been associated with internal uncertainties, as well as complexities arising from distinct qualities of the ecosystem being analyzed. The widespread sagebrush-steppe ecosystem (dominated by Artemisia spp.) in Western North America holds high ecological and social significance, but is threatened by anthropogenic forcing factors, including impacts from invasive species, climate change, and altered fire regimes. To restore the ecosystem, land managers have focused on reducing flammable vegetation and seeding native species. However, the collective effects of restoration activities, fire, climate change, and invasive species on ecosystem dynamics are poorly understood. We applied the Ecosystem Demography (ED2) model to analyze its effectiveness in predicting plant function type (PFT) composition and ecosystem fluxes, parameterized and validated using empirical datasets for different carbon, vegetation and fire scenarios at Reynolds Creek Experimental Watershed (RCEW), Idaho, USA. We initialized ED2 with 20 x 40 grids of 1 km resolution representing and allowed PFTs to grow for 20 years to reach an equilibrium state. Results showed shrubs dominating C3 grass in a few years of time, sooner for increased CO2 and initial ecosystem condition. A separate scenario with potential fire showed significant loss in biomass within eight years of time. Results from this modeling study can improve our understanding of broad-scale ecosystem processes in sagebrush-steppe landscapes and inform land management and restoration strategies.

The Lithium Nevada Corp. Thacker Pass Project has a measured resource of 242M tonnes at 0.29% Li (~0.7M tonnes Li). The deposit is the southernmost of five known lenses hosted within intracaldera tuffaceous sediments along the west side of the McDermitt caldera, which formed by eruption of 16.4 Ma peralkaline-metaluminous tuff. Analyses of 9880 core samples (~1.5-m thick) give a mean of ~ 2500 ppm Li, with some >8800 ppm. Entire sedimentary sections in the southern and western parts of the caldera basin have high Li (1500+ ppm). Pre-caldera rocks, the McDermitt Tuff, late caldera volcanics, and unaltered tuffaceous sediments have relatively low Li (5 -140 ppm). Sediment deposition was mainly subaqueous in the closed caldera basin. Li-rich fill may have been deposited from airborne sources. Claystone comprises most of the Thacker Pass deposit and dominates Li-rich intervals. The rest is mostly feldspar-rich ash. X-ray diffraction (XRD) data from six core holes across the deposit show consistent lateral mineral zoning. A Li-rich zone (mean >4,000 ppm) mainly contains illitic clay and underlies a zone of lower Li with smectite + analcime. Based on XRD peak locations and chemistry, the closest analogs to the illitic clay are Li micas (e.g. tainiolite). Montmorillonitic clay and a basal silicified zone underlie the illitic zone. Some transitional rock of mixed-layer clay between the illite and smectite zones also has high Li. All clay has similar optical properties but SEM images show illite forms tiny hexagonal plates and smectite has no resolvable crystallinity. Calcite, albite, K-feldspar, and quartz occur in all zones, dolomite and fluorite near the top of the illite zone, and pyrite and bitumen in unoxidized rock. The Li-rich zone has relatively high K, Rb, Mo, As, and Sb. Secondary Kspar in the Li-rich zone gave an 40Ar/39Ar age of 14.87±0.05 Ma. No origin fully explains known characteristics. The presence of illite suggests a moderate temperature hydrothermal system. Release of Li from tuffaceous sediments and transport by alkaline groundwater are consistent with most mineralogy (characteristic of closed hydrologic system diagenesis) and with the Kspar date that long postdates caldera magmatism. Release of 10 ppm Li from the likely 50-200 km3 of intracaldera sediments would contribute ~1-4M tonnes Li.

During the last few years, the debate over the changes in the global average temperature has been one of the most important political issues. A better understanding of the effects of the temperature increase on other variables is one of the main challenges in climate. In the last IPCC report, due in part to the limited rainfall data in the tropics, there is no reliable conclusion about the observed and expected long-term precipitation changes in association with the global temperature increase. Since water resources are essential for energy generation and food production in the Department of Antioquia, Colombia, a better understanding of changes in rainfall in the long term becomes a vital tool for decision making. This research presents an assessment of rain variability at different temporal and spatial scales over Colombia, and more specifically over Antioquia. The data used was corresponds to long-term records of 86 rain gauges, in addition to 9 temperature stations, and TRMM precipitation products. The use of in-situ rain gauge information allows focusing on a spatial scale useful not only for a general understanding of precipitation changes but also for engineering and other practical applications. Analyses reveal that while there are no long-term trends in precipitation at the monthly or longer timescales, relatively short-lived extreme events show long-term changes in intensity and frequency. Results show that the shorter the duration of the intense events, the higher the magnitude of the increasing intensity trend. Similarly, for more intense events, the trends are also larger and more significant from a statistical point of view. Analysis of temperatures shows a clear relationship with extreme precipitation events with scaling features explained via the Clausius-Clapeyron relation, controlling the intensification of precipitation. The long-term rainfall trends are compared with modeling results from the different scenarios of a small set of CMIP runs given that most models do not adequately represent Colombia´s precipitation climatology. The results indicate a substantial reduction of return period of extreme events with implications in engineering: the current hydraulic designs would be obsolete in less than 50 years if the increment in the frequency of intense events is not considered in the design.

Over the past decades, Arctic sea ice has declined in thickness and extent and is shifting towards a seasonal ice regime, with accelerated ice drift and an increase in the seasonal ice zone. The changing Arctic ice cover will impact the trans-border exchange of sea ice between the Exclusive Economic Zones (EEZs) of the Arctic nations, with important implications for ice-rafted contaminant transport. To investigate projected changes to transnational ice exchange, we use the Lagrangian Ice Tracking System (LITS) to follow ice floes from the location of their formation to where they ultimately melt. We apply this tool to output from two ensembles of the Community Earth System Model (CESM): the CESM Large Ensemble, which uses a high emission scenario (RCP8.5) that leads to over 4°C global warming by 2100, and the CESM Low Warming ensemble, with reduced emissions that lead to a stabilized warming of 2°C by 2060. We also use the National Snow and Ice Data Center Polar Pathfinder and Climate Data Record products to evaluate the fidelity of the CESM present-day tracking simulations. Transnational ice exchange is well represented in CESM except for ice traveling from Russia to Norway, with twice as much ice following this pathway compared to observations. Initial results suggest this might be due to a combination of internal variability and speed biases in the observational data. The CESM projects that by mid-century, transnational ice exchange will expand, with a large increase in the fraction of transnational ice originating from Russia and the Central Arctic. As the seasonal ice zone grows, ice floes accelerate and transit times decrease, eventually cutting off ice exchange between longer pathways. By the end of the 21st century, we see a large impact of the emission scenario on ice exchange: consistent ice-free summers under the high emission scenario act to reduce the total fraction of transnational ice exchange compared to mid-century. The low emission scenario on the other hand continues to see an increase in transnational ice exchange by 2100. Under both scenarios, all pathways have decreased to average transit times of less than 2 years, compared to a maximum of 6 years under present-day conditions and 3 years by mid-century, effectively bringing the Arctic nations closer together.

Climate models at high resolution (~25 km horizontal grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus promising the investigation of these high-impact extreme events under present and future climates. On the global scale, simulations with the Community Atmosphere Model version 5 (CAM5) present a reasonable TC climatology under prescribed present-day (1980-2005) sea surface temperature (SST) and greenhouse gas (GHG) forcing. However, for the disaster-prone western North Pacific (WNP) region, biases in TC genesis frequency and location persist across various configurations. The biases under-represent the basin’s share in global TC climatology, complicating the fidelity of future projections. This study addresses these model biases in WNP by evaluating the large-scale environmental controls of TC genesis in CAM5 with two aerosol configurations. Across the two configurations, the lack of mid-level moisture is consistently identified as the leading cause of the deficit in simulated WNP TC genesis. This lack of mid-level moisture in WNP TC main develop region is potentially linked to previously identified deficits in Pacific warm pool precipitation at high horizontal resolution in CAM5, as well as biases in the East Asian Summer Monsoon circulation and moisture transport. Additional CAM5 simulation experiments will explore the effect of moisture nudging on the large-scale environment and subsequent TC genesis, tracks, and intensity development. For a chosen year, simulations covering WNP peak TC season (July - October) under otherwise identical forcing (SST, GHG etc.) will be run with and without nudging the specific humidity field towards MERRA-2 reanalysis. The insight into the biases of basin-scale TC simulation under the present climate and potential improvements will help reduce the uncertainty in future-climate projections, in the interest of disaster risk management.

Machine learning algorithms have become a powerful tool in different areas of seismology, such as phase picking/earthquake detection, earthquake early warning and focal mechanism determination. Previously convolutional neural networks (CNN) have been applied to continuous seismic waveform recordings to perform efficient phase picking and event detection with good accuracy [Zhu et al., 2018]. However, the off-line training of current CNN requires at least a few thousands of accurately picked seismic phases, which makes it difficult to be applied to regions without sufficient picked phases. In this work, we will validate the transfer learning among different geographic regions. Our tests show that the phase picker trained on manually-labeled data acquired from Sichuan, China following the 2008 M7.9 Wenchuan earthquake [Zhu et al., 2018] works equally well on the continuous waveform acquired from Oklahoma, US [Zhu et al., 2018]. Specifically, using the CNN trained on the Wenchuan dataset, together with 895 local/regional catalog events recorded in central Oklahoma, we refine part of the networks to pick the arrival times of the local seismicity in Oklahoma. The refined CNN results are compatible with the matched filter results using the same catalog events as templates. Our next step is to extend our test to waveforms from different tectonic regions to demonstrate the generality of CNN-based phase picker. We plan to further use a New Zealand seismic dataset that includes more than 20 GeoNet stations in the North Island, where the matched-filter detected results are available to be compared with (Yao et al., 2018). Alternatively dataset include a subset of events in the waveform relocated catalog in Southern California. Updated results will be presented at the meeting.

Human activities have been changing deposition rate of the atmospheric reactive N over the last decades. The understanding of the process that rules the accumulation and deposition of reactive nitrogen in the environment still faces major gaps mainly in regions with lack of data as South America. In this work, we evaluated the atmospheric dry deposition of reactive nitrogen (Nr) using concentration measurements of different chemical species, in six sampling sites with different environmental characteristics in the state of São Paulo, Brazil, for a sampling period of approximately 24 months (2015-2017). We used the sampling system DELTA (Sampler for Atmospheric Sampling of Long Term), and ion chromatography method to determine the concentration of gaseous (NH3 and HNO3), and particulate (NH4+ and NO3-) chemical species in the atmosphere. The N-NH3 (gaseous) was the dominant form of Nr in the atmosphere at all sampling sites. The highest N-NH3 mean value was found near the urban area of the municipality of São Paulo (SP, 1.58 ± 0.73 μgN m-3) and the lowest mean value in the most eastern sampling site (0.26 ± 0.26 μgN m-3). The high values in the SP sampling site is related to the intense traffic in the metropolitan area and, also to waste management, industrial NH3, and human emissions as observed in other urban areas around the world. The particulate N-NH4+ is the second most common form of Nr in the São Paulo state atmosphere. The other forms of Nr in the atmosphere, the gaseous HNO3 and particulate NO3, represent only about 10% of the total Nr in the atmosphere each. The total gaseous Nr concentration was a factor of 1.7 larger than particulate Nr. The Nr deposition varied throughout the years. We did not observe a pattern of variation linked to meteorological characteristics of dry and wet season, as observed in other regions of the globe. However, we found good correlation with wind speed higher than 3.5 m s-1 and humidity. Our results provide the first spatial analysis of Nr deposition using in situ data in a Latin American region and will contribute to the understanding of nitrogen balance and to improve Nr deposition modelling approaches. This study was supported by the project Nitrogen cycling in Latin America: drivers, impacts and vulnerabilities (Nnet, IAI/CRN3005 and FAPESP 2012/06416-1), PCI Program of the MCTIC, and collaborators.

Reliable, accurate, and affordable linear motion systems for agricultural applications are currently not easily accessible due to their elevated cost. Most systems available to the public have price tags in the thousands and their dimensions cannot be easily customized. Current systems have a max length of about ten meters and for a typical greenhouse application, the length may not be sufficient. The price of the system increases with an increase in length and with a base price in the thousands it becomes almost impractical to buy a system for such application. The HyperRail is a modular linear motion system with a repeatability of 2mm and current top speed of 100mm/s. An advantage this system has is its ability to increase or decrease the length of system with minimum effort and nominal increase in price. The HyperRail can be mounted on a set of tripods or directly on the structure of a building such as a greenhouse. The base price for a three-meter system, on tripods, is US$240 and an additional US$45 for each additional one-and-a-half meter. The HyperRail was designed for the use of hyperspectral imaging but can be adapted for other sensor systems. We report on a nine-meter study over pine seedlings infected with a virus. A push-broom hyperspectral camera (Headwall Nano) was mounted on the carriage of the system imaging the seedlings. The rail is currently being adapted to an environmental sensor suite that will monitor CO2, luminosity, humidity, temperature, and the concentration of dust. The HyperRail also includes bidirectional-wireless communication between the drive and the carriage; this means that the sensor suite can operate autonomously and communicate to the HyperRail drive to move to a specific location and take measurements. This system includes a graphical user interface for users who are unfamiliar with programming but could also be used through a command line interface for individuals that want to work the code and see the effects of the changes immediately. This system was developed at Oregon State University’s OPEnS Lab, here is a link to the project page for more detailed information. URL for project page: http://www.open-sensing.org/hyper-rail/

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.

Lava tubes can offer protection for human crews and their equipment on other solar system bodies, in particular from radiation threats and extreme surface temperatures. Developing strategies to survey regions of other terrestrial bodies (such as the Moon or Mars) for tubes suitable for potential habitation will likely become an important part in planning future space exploration projects. A variety of surface geophysical techniques, such as ground penetrating radar (GPR) have the potential to help recognize and map tubes. GPR shows promise for providing high resolution information on tube geometries. To investigate GPR’s capacity and limitations, we use GPR, as well as comparative methods of seismic and magnetic surveys, in conjunction with LiDAR mapping of tube interiors at the Lava Beds National Monument (LBNM) in California, USA. LBNM offers a wide variety of tube geometries and textures. We have collected 2D GPR profiles and small 3D GPR grids (of parallel 2D lines) with antenna frequencies of 100 and 200 MHz on four lava tubes with different geometries, textures and at different depths. Challenges in recovering tube geometries include wave scattering in fractured rock covering tubes, irregular and “drippy” ceilings and walls, and blocky floors. Our primary results show that the top of the LBNM tubes can generally be resolved in the GPR data, while resolving the bottom is more challenging. The utility of various GPR processing techniques can be directly assessed by comparing resolved GPR images against the LiDAR-measured tube geometries.

Over the past three years Stone Aerospace has developed a novel ice penetrating technology known as a Direct Laser Penetration (DLP). DLP uses laser light carried by an optical fiber to a vertically descending ice penetrator and emitted from the nose to melt the ice in front of it at extremely high power levels and melt rates. A penetrator can be made with an onboard fiber spool connected to a surface-based laser, allowing the hole to re-freeze behind, drastically increasing efficiency and providing isolation from the surface. A parallel spool can pay out a communications fiber to carry information from imagers, fiber-based sensors (e.g. temperature, pressure, seismic), and other optical sensors (e.g. fluorescence or Raman). Laser power levels of up to 100 kW (continuous) at 1070 nm wavelength are now available and can be coupled to these probes. Successful laboratory test results at Antarctic ice temperatures show that this approach could lead to the fastest ice penetration rate available to terrestrial targets, with access to any Antarctic sub-glacial lake in under 16 hours. In this way, DLP offers an alternative to traditional, logistically intense ice drilling: a small footprint system that is fast and can deploy sensor strings through the deepest ice in a short period of time. DLP also shows promise in addressing the ‘starting problem’ for extraterrestrial targets such as Europa or Mars where low pressures prevent the formation of water at the surface and thus heat transfer for traditional melt probe architectures. In order to test the effectiveness of this concept, a Europa environment ‘cryovac’ test facility has been built at Stone Aerospace in Austin, Texas. We will discuss quantitative results from initial lab and chamber tests of the DLP concept, including in an ice column at 100 K temperature subjected to vacuum.

A planetary surface’s thermal infrared (TIR) emissions provide insight into the surface’s composition. Different minerals can be identified by their characteristic TIR spectral signatures. Therefore one can retrieve surface mineral composition by comparing TIR observations of a planetary surface against a library of known mineral TIR spectra measured on Earth. However for airless bodies such as the Moon, creating such a spectral library poses a challenge: minerals exhibit different TIR characteristics when measured in typical terrestrial conditions versus in lunar surface-like environments. We work to overcome this challenge by measuring TIR emission spectra of mineral samples in a chamber that simulates the lunar environment. The Simulated Airless Body Emission Laboratory (SABEL) chamber heats particulate samples under vacuum to generate a thermal gradient akin to that found in the upper regolith (i.e. epiregolith) of airless bodies. The presence of this thermal gradient—modeled to be as steep as ~60K/100 μm for the Moon—is due to airless bodies lacking the convective heat transfer provided by an atmosphere. This thermal gradient is responsible for the altered TIR spectral emission characteristics of the lunar surface, so simulating it in SABEL allows us to measure TIR spectra that are directly comparable to remotely sensed TIR observations from the Diviner Lunar Radiometer (Diviner) instrument aboard the Lunar Reconnaissance Orbiter (LRO). The work presented here focuses on one particular application of SABEL: characterizing the TIR emission spectra of silicate mineral mixtures with the endmembers plagioclase, pyroxene, and olivine. These endmembers bound the typical mineral compositions of the lunar surface. By understanding the TIR characteristics of these endmembers’ mixtures, and in particular how the wavelength position of the Christiansen feature—an emissivity maximum sensed by Diviner—changes for different mixtures, we can better interpret TIR data and their implications for surface composition.

The climatology of upwelling in the tropical tropopause layer (TTL) in current climate simulations and in future climate projections is examined using models participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Large intermodel differences in upwelling in the TTL appear in the current climate simulations. Model composite analysis and upwelling diagnosis based on the zonal momentum budget indicate that the intermodel differences in upwelling are controlled by meridional eddy momentum fluxes associated with tropical planetary waves and midlatitude synoptic waves. Future climate simulations indicate that upwelling changes in the TTL are significantly correlated with the upwelling in current climate simulations. Models with strong (weak) TTL upwelling in the current climate simulations tend to project strong (weak) upwelling enhancement in the future climate. The intermodel differences in the upwelling change arise from the same dynamical factors as the current climate cases. The contribution of sea surface temperature (SST) to the intermodel upwelling differences is examined by SST-prescribed simulations in CMIP5. The contribution of intermodel SST differences to the upwelling is smaller than that of intrinsic atmospheric intermodel differences. The significant correlation of the tropical upwelling between the current climate simulations and the future changes appears to be independent of the target latitude range.

We are at a unique time in the study of our place in space. On one hand, we operate in the same paradigm that has guided the study of space science for the past couple of decades, and on the other a rising dependence of our economic and social well-being on space demands a shift. Everywhere in our society ‘big data’ (defined by four V’s: volume, variety, veracity, and velocity) and the advent of sophisticated and efficient methods to explore these data (i.e., data science) present new opportunities for discovery, and the time is ripe for these methods to shift how we study the physics of space. We will first discuss the meaning of data science in the context of space science, and then demonstrate the potential for new discovery through a power use case: leveraging Global Navigation Satellite Systems (GNSS) signals for space weather prediction. In this use case, we take advantage of a large volume of data from GNSS signals, data science-driven technologies, and a machine learning algorithm known as the Support Vector Machine (SVM) to develop a novel predictive model for high-latitude ionospheric phase scintillation. This talk will conclude with a perspective on opportunities in space science through ‘big data’ and creating new scientific discovery at the intersection of traditional approaches and data science-driven innovation.

The formation of crystal clusters may influence the mechanical behaviour of magmas. However whether clusters form largely from physical contact in a mobile state during sedimentation and stirring, or require residence in a crystal mush is not well understood. We use discrete-element fluid dynamics numerical experiments to illuminate the potential for clustering from both sedimentation and open-system mixing in a model olivine basalt reservoir for three different initial solid volume fractions. Crystal clustering is quantified using both bulk measures of clustering such as the R index and Ripley’s L(r) and g(r) functions and with a variable scale technique called Voronoi tessellations, which also provide orientation data. Probability density functions for the likelihood of crystal clustering under freely circulating conditions indicates that there is nearly an equal likelihood for clustering and non-clustered textures in natural examples. A crystal cargo in igneous rock suites exhibiting a dominance of crystal clusters may be largely sampling magmatic materials formed in a crystal mush.

We seek to calibrate the flow law for polythermal ice through shear strain analysis. In a warming climate, increased melting of glaciers and ice caps play a big role in sea level rise. Approximately 60% of the current contribution to sea level rise from ice loss is attributed to glaciers and ice caps, raising the urgency of sharpening mass balance change predictions in regions of streaming flow. Polythermal glaciers constitute a significant portion of these contributing glaciers, though our knowledge of their flow dynamics is incomplete. Thermally complex polythermal glaciers have both warm and cold ice which lead to weak wet-based beds, with significant amounts of basal sliding and deformable till. Consequently, polythermal glaciers experience significant shear strain as their lateral shear margins sustain the majority of the resisting stress. Most in-situ and in-lab studies of natural ice over recent years have focused on bodies of ice with frozen beds that experience minimal shear strain downglacier and across vertical planes (with depth) relative to the bed. The lack of studies on wet-based polythermal glaciers causes uncertainties in the flow law, as differences in flow law factors between polythermal ice and bodies of ice with frozen beds have the potential to induce more than an order of magnitude difference in ice velocity. To improve calibration of the flow law for polythermal ice, we seek to improve our understanding of their shear strain regimes. We developed and deployed tilt sensor systems on the polythermal Jarvis Glacier in Alaska, where we drilled multiple boreholes close to Jarvis’ shear margin and installed three boreholes with our tilt sensor systems. The tilt sensors measure gravity, magnetic and temperature data, and each system consists of multiple sensors connected along a cable and serially communicating along a common data bus with a datalogger. We have recently retrieved a year of Jarvis tilt sensor data and calculated the at-depth shear strain rates in the boreholes, allowing evaluation of the at-depth shear strain rate regimes of polythermal ice against theoretical models developed using Glen’s flow law. We present the development of our data collection methodology and the results of our shear strain analysis, with suggestions for potential calibrations of the flow law for polythermal ice.

Terrestrial water storage (TWS) plays a key role in land-surface interaction and the hydrological cycle. Changes in the variability of its components, including surface storage, soil moisture and groundwater can lead to significant changes in local climate, water supply sources and agricultural production. In this study, we assess the impacts of climate variability and change in surface and subsurface hydrological variables over the Magdalena-Cauca basin (Colombia) using a distributed conceptual hydrological model (WMF) driven by precipitation and temperature from four GCMs (general circulation models). WMF is calibrated using daily precipitation products from the Tropical Rainfall Measuring Mission (TRMM). Monthly mean anomalies of surface and groundwater storage outputs show consistency with Gravity Recovery and Climate Experiment (GRACE) data. Past (1970-2001) and future (2021-2050 and 2071-2100) precipitation from GCMs are statistically downscaled using a quantile mapping method to a spatial resolution of 0.25 by 0.25 degrees. Mean precipitation projections over the country are highly dependent on the selected GCMs, but the evidence shows agreement in a decrease towards the lower part of the basin; these projections are also present in surface runoff simulations. Annual mean streamflow follows the sign of the mean rainfall change over the basin. On the other hand, soil properties, topography, and geomorphological characteristics condition the patterns of subsurface and groundwater storage change (magnitude and localization), with the upper part of the Colombian Andes and the river mouth presenting the greatest changes. Results also show that mean soil moisture decrease in all scenarios, associated with changes in precipitation, but also due to the influence of temperature and evapotranspiration. The latter could lead to changes in the soil-atmosphere interaction, energetic conditions of the ecosystems and the need for agricultural mitigation strategies.

According to the concept of the seismic cycle, earthquakes result from the strain accumulation over a variable decade to millennial period, i.e., the interseismic stage, followed by a sudden stress release, i.e., the coseismic stage, eventually evolving in the postseismic stage. Common analytical and numerical approaches simulate interseismic, coseismic and postseismic stages independently. Often, coseismic models constrain the slip of single or multiple planar sources to fit the available geodetic and InSAR measurements to reproduce fault geometry, slip and regional deformation, regardless the origin of the interseismic forces. We developed a numerical model linking the ongoing interseismic viscous deformation at depth with the coseismic brittle episodic behavior of the upper crust. Our model assumes a brittle upper crust where the fault is locked, and a ductile lower crust, where the fault is steadily shearing. This approach is developed to model typical extensional and compressional earthquakes in Italy including the forces acting during the interseismic period, i.e., the lithostatic load and the horizontal stress field. We adjusted the setup of our model to simulate the interseismic, coseismic and postseismic phases of three seismic events in Italy, two extensional (2009 L’Aquila Mw 6.1 and 2016 Amatrice-Norcia Mw 6.5) and one contractional (2012 Emilia Mw 6). The results of our analysis, compared with the available geodetic and InSAR data, show that the proposed numerical model can reproduce the seismic cycle associated with the investigated events. The modeling provides evidence of interseismic dilatancy above the brittle-ductile transition at the bottom of the locked fault plane in the extensional tectonic setting; coseismic fault motion is triggered by the hangingwall gravitational collapse that recovers most of the interseismic dilatancy formed almost orthogonal to the fault. Vice versa, in contractional tectonic settings, the interseismic horizontal stress accumulates elastic energy in the crustal volume above the bottom of the locked fault; coseismic deformation recovers the elastic energy stored in the hangingwall. The two different settings generate a deformation in favor of gravity in extensional tectonic environments and against gravity in contractional tectonic environments.