Significant investments are made in the collection of water quality data. Yet barriers to effective data sharing and reuse hamper the ability to leverage this information to its full potential in research and water management decisions. Because water monitoring data are collected by a wide range of organizations, through programs of varying scope and focus, and often within jurisdictional or institutional silos, it can be difficult to connect this information together in standardized and accessible formats. DataStream is an online open-access platform that was developed by The Gordon Foundation and its partners to address the challenge of water data accessibility in Canada. DataStream is free to use and allows users to query, visualize, and download water quality data aligned with widely-adopted data and metadata standards (e.g., Water Quality eXchange, ISO19115 and schema.org). The path towards DataStream evolving as a collaborative and open data platform has been guided by the FAIR and CARE data principles. To date, over 140 different groups across Canada are using DataStream to publish water monitoring results including watershed groups, Indigenous organizations, researchers and governments at all levels. We will highlight our lessons learned in developing the platform to align with FAIR data principles and the elements we believe have been key to our success including DataStream’s open data schema, clear data licensing and regional partnership model.

Based on satellites monitoring of the X-Rays Precipitations (Solar Flares), Solar Proton Precipitations (Solar Proton Events), and Riometer absorption in association with F region plasma patches formed in the cusp and propagating into the polar cap, we estimate ionospheric D-Layer ionization caused by energetic electrons precipitations based on our Computational Model of D-Region Ion Production. Knowing D-Layer ionization mechanisms will allow us to monitor precipitating electron source rates based on routine ionospheric absorption measurements by the Canadian Geospace Observatory Riometer Network (GO-RIO).

To a first order, the Caribbean plate converges obliquely at ~2 cm/yr toward the North American plate. This transpression is partly accommodated across the island of Hispaniola by the partitioning of motion between a fold-and-thrust belt trending NW-SE, and two E-W left-lateral fault systems located 150 km apart. The southern fault, the Enriquillo-Plantain Garden Fault (EPGF), is morphologically well expressed in western Haiti but its precise geometry in eastern Haiti is debatable. There, Lake Azuei stretches over 20 km in a direction parallel to the fold-and-thrust belt while its southern shoreline strikes EW, parallel to the expected trend of the EPGF. Because of a high sedimentation rate, the history of transpressional deformation should be captured in the lake stratigraphy and, accordingly, we acquired 220 km of multichannel seismic reflection (MCS) profiles across its surface. The survey followed a grid pattern with a spacing of 1.2 km and achieved a penetration of up to 300 m beneath lakebed. Interpretation of the dataset documents two major structures. First, the western side of the lake is occupied by a broad NW-trending monoclinal fold. This fold is cross-cut by a few NW-striking vertical (strike-slip) faults. We propose that this monocline is the surface expression of a SW-dipping blind thrust fault. The progressive steepening of the seismic horizons with depth suggests that it has been continuously active during the deposition of at least 300 m of sediments. The other major structure consists of a ~2 km-wide deformation zone that borders the EW-trending southern shore. This deformation zone is faintly imaged below a shallow gas front. We tentatively propose that it corresponds to a set of fault-propagation folds that are developing ahead of an EW, S-dipping oblique-slip fault. Such a model has been proposed already from three other independent studies involving GPS monitoring, seismological monitoring, and detailed field mapping. It is also supported by CHIRP profiles acquired concurrently with our MCS data and that document folding of the topmost turbidites but a lack of evidence for any stratigraphic offset across faults. Furthermore, a set of en echelon folds in that area are trending EW, while WNW-ESE fold axes would be expected instead above an EW vertical strike-slip fault.

Differential Interferometric Synthetic Aperture Radar (DInSAR) based mapping of surface deformation has proven valuable in a variety of geoscience applications. Conventional approaches to DInSAR analysis require significant expertise and are not suited to addressing the opportunities and challenges presented by the large multi-temporal SAR datasets generated by future radar constellations. As a result, the Canada Centre for Mapping and Earth Observation (CCMEO) developed, in support of Natural Resources Canada and Government of Canada priorities, a system for automatic generation of standard and advanced deformation products based on DInSAR technology from RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) data. Existing RADARSAT-2 processing algorithms were adapted to RCM specifications and novel advanced processing algorithms were developed to address the large data sets resulting from the constellation’s four-day rapid revisit cycle. This permitted expanding the DInSAR functionality across a wide-range of spatial and temporal scales. The system architecture is scalable and can be expanded to serve a large number of clients; it can simultaneously address multiple application areas including natural and anthropogenic hazards, natural resource development, permafrost and glacier monitoring, coastal and environmental change and wetlands mapping.

Electric field measurements are necessary to understand thunderstorm evolution and lightning initiation. However, most existing measurements are made with single instruments carried by weather balloons. It is difficult to interpret such data since a change in observed electric field could be due either to motion of the instrument or charging/discharging currents. In order to decouple these behaviors, it is necessary to make simultaneous measurements at multiple locations. To avoid the complexity of multiple balloon launches, we describe a single balloon instrument with multiple, independent dropsondes to be released at desired time intervals. The dropsondes are designed to rotate and be self stabilizing, enabling them to measure electric fields as they fall. The dropsondes are lightweight, robust, and low-cost, and include a preamplifier, GPS receiver, search coil and accelerometer for orientation sensing, microcontroller, and a telemetry system to transmit data to a ground station. Prototype instruments have been drop-tested to demonstrate aerodynamic stability and rotation and have been calibrated for electric field measurement. A balloon payload set to release a set of such dropsondes via hot-wire release mechanisms can thus accomplish the goal of multi-point measurements of thunderstorm electrical structures.

The increased availability of daily model output in the latest generation of climate models should allow us a greater understanding of, and an improved ability to predict, future trends in short duration extreme temperature events. We examine the changes in 1, 3, and 5 day averaged annual maximum temperature at the levels of global warming highlighted by the 2016 Paris Agreement, and an additional degree of warming. These events are characterised using daily near surface air temperature output from four large ensemble models in the SSP370 scenario of the Coupled Model Intercomparison Project Phase Six (CMIP6). Bootstrapped distributions of ensemble members are fitted to the generalised extreme value distribution and the changes in location, scale and shape parameters examined at the respective warming levels, compared to the last 10 years of historical model runs. Global trends in location parameter indicate increased warming over land relative to oceans while shape and scale parameters show less globally consistent trends but very clear signals of strong changes over the Arctic sea ice. Risk ratios are determined for extreme temperature events with a return value of 10 years in the historical period, compared to future levels of warming, using the calculated GEV distributions. Risk Ratios increase globally with mean temperature change, with greater increases over the tropics, particularly over the oceans. Longer events are also found to have a greater increase in occurrence than shorter duration temperature extremes.

Tomographic analysis of Pn arrivals times—the guided P-wave propagating within the lithospheric mantle—is ideal for studying the structure of the uppermost mantle. While plate-scale seismic images of Pn wave speeds are common beneath the continents, similar scale studies have not been possible within ocean basins due to the sparsity of seismic stations. The Cascadia Initiative (CI) dataset provides the first opportunity to image spatial variations in lithospheric structure across an entire oceanic plate. We measure 2,862 Pn arrivals from local earthquakes recorded by the CI array. Our dataset provides complete coverage of both the Juan de Fuca (JdF) and deforming Gorda plates. We invert the measured arrival times for 3D variations in anisotropic P-wave velocity and hypocentral parameters. Despite surficial evidence of extensive active faulting, the velocity structure of the Gorda uppermost mantle is remarkably consistent with predictions from a conductive cooling model (attached figure). Limited deformation at mantle depths is supported by seismic anisotropy measurements that show the fast-direction of P-wave propagation rotates in concert with the magnetic anomaly lineations. This rotation may be explained by local plate kinematics without internal deformation and hydration of the shallow mantle. In contrast to Gorda, the seismic velocity structure of the JdF plate does not exhibit a clear age dependence. Three pronounced mantle low-velocity zones are found along the southern edge of the JdF plate near the termini of large pseudofaults that contributed to the formation of the Blanco Transform fault. We attribute these velocity reductions to mantle alteration by seawater. We note that within the interior of the JdF plate pseudofaults do not appear as uniformly slow features in our seismic images. Beneath the central and northern JdF plate, P-wave speeds are ~7.7 km/s out to ~4-5 Myr before abruptly increasing to ~7.9 km/s. Curiously, this transition occurs near the onset of mantle downwelling inferred from teleseismic body wave tomography and attenuation suggesting that mantle flow dynamics may influence the structure of young oceanic lithosphere. Lastly, we note that our results do not suggest a relationship between the structure of the uppermost slab mantle and segmentation of the Cascadia megathrust.

For more than 20 years, the work of academic climate scientists and those at groups like the Union of Concerned Scientists has been to analyze, synthesize, and convey the projected and, in recent years, current impacts of climate change. In the earlier years, these impacts were still largely imperceptible and pathways for solving the problem seemed wide and flexible. A key objective of climate science communication during those years was to establish the legitimacy of our work, which faced tremendous public and policy maker scrutiny, as a simultaneous barrage of well-coordinated disinformation had led to unusual skepticism of the science. Now we are clearly seeing the impacts of one degree Celsius of warming, the current and projected climate impacts themselves have grown, and the solutions pathways have become narrow and steep. While the climate context has changed for the worse over those 20 years, scientists have largely soldiered on with the same reticent communication. Visible climate change impacts and alarming projections for future change have far outpaced the growth in experts’ ability to reach people and inspire them to act with urgency. At UCS, we have consciously and deliberately begun to change the tenor of our climate communications in response to the increasingly dire results our own analyses have generated and against a backdrop of accumulating and similarly dire science. In our most recent work on extreme heat, particularly in introducing and concluding our results, we have embraced starkly visceral and impassioned language because, as scientists, we see how dangerous the future looks, how serious this moment is in the arc of climate change, and our own moral obligation to communicate it. In this presentation, we will examine the communications space our climate scientists at UCS—as well as those at other institutions—have leaned into. As sentient humans who see an emergency measured not just by data points in charts and graphs but by the faces of those whose homes have flooded, whose loved ones have lost their lives during heat waves, or whose livelihoods are no longer viable, we can’t “tell it like it is” without letting go of reticence and objectivity. The words we choose may be perceived as dangerous, but they are not as dangerous as the world we are ushering in. The house is objectively on fire. It’s time to shout.

We present a new statistical interpolation method to estimate fire perimeters from Active Fires detection data from satellite-based sensors, such as MODIS, VIIRS, and GOES-16. Active Fires data is available at varying temporal and spatial resolutions (375m and up several times a day, or 2km every 15 minutes), but pixels are often missing due to clouds or incomplete data. The question arises how to fill in the missing pixels, which is useful, e.g., to distinguish in an automated fashion between a single large fire visible as separate clusters of detection pixels because of cloud cover, and separate fires. We process the satellite data into information when was fire first detected at a location, and when was clear ground without fire detected at the location last. We are then looking for the most likely fire arrival time, which satisfies such constraints. Models at various levels of complexity are possible. Our base assumption in the absence of information to the contrary is that the fire keeps progressing without change, which is expressed as the assumption that the gradient of the fire arrival time is approximately constant. The method is then formulated as an optimization problem to minimize the total change in the gradient of the fire arrival time subject to the constraints given by the data. We consider probabilistic interpretations of the method as well as extensions, such as soft constraints to accommodate the uncertainty of the detection and the uncertainty where exactly the fire is within the pixel. This method is statistical in nature and it does not use fuel information or a fire propagation model. The results are demonstrated on satellite observations of large wildfires in the U.S. in summer 2018 and compared with ground and aerial data.

Timing errors are a notorious problem in seismic data acquisition and processing. We present a technique that allows such time shifts to be detected and corrected in a systematic fashion. The technique relies on virtual-source surface-wave responses retrieved through the crosscorrelation of ambient seismic noise. In particular, it relies on the theoretical time-symmetry of these time-averaged receiver-receiver crosscorrelations. By comparing the arrival time of the surface waves at positive time to the arrival time of the surface waves at negative time for a large a number of receiver-receiver pairs, relative timing errors can be determined in a least-squared sense. The time-symmetry of the receiver-receiver crosscorrelations, however, is contingent on a uniform surface-wave (noise) illumination pattern. In practice, the illumination pattern is often not uniform. We therefore show that weighting different receiver-receiver pairs differently in the inversion allows timing errors to be determined more accurately. The weights are based on the susceptibility of different receiver pairs to illumination-related travel-time errors. The proposed methodology is validated using both synthetic data and field data. The field data consists of recordings of ambient seismic noise by an array of stations centered around the tip of the Reykjanes peninsula, southwest Iceland (some of these stations exhibit time shifts of an unknown nature).

The transport effectiveness of a stream flow event of a certain magnitude in carrying a sediment load is defined as the product of the effect of that event and the frequency with which it occurs. This approach is famously known as Magnitude-Frequency Analysis (MFA). MFA has been commonly used to calculate “effective discharge” which is considered as the stream flow that is responsible for transportation of the majority of the sediments from a river basin over a long period of time. In MFA, the stream flow at a location is assumed to follow a continuous probability distribution whereas the sediment transport is described by a rating curve between stream flow and sediment load. Despite the apparent good fit to the data, there are problems using a rating curve to predict sediment load. The sediment load carried through a stream network can be affected by the variability in stream flow occurring during different months or seasons (i.e. time scales) and consequent hysteresis phenomenon. Prediction of sediment load can be improved by constructing separate rating curves for various time scales. In this study, daily stream flow was assumed to follow the log normal distribution, and rating curves (between stream flow and sediment load) have been developed for total, monsoon, individual months data and considering hysteresis phenomenon for total and monsoon data in transport of sediments. Finally, MFA based effective discharges were calculated at 16 stream gauges in the Godavari River basin, India. The results of this study can find use in the effective planning and functioning of dams/reservoirs.

We explore the effects of changing heating parameters in closed coronal loops on the intensity of Atmospheric Imaging Assembly (AIA) observations. Using EBTEL (Enthalpy-Based Thermal Evolution of Loops) hydrodynamic simulations, we produce realizations of coronal loops with a series of heating events randomly drawn from a power law distribution. We repeat this procedure for multiple loop lengths, heating intensities, and characteristic heating frequencies to investigate how each of these parameters individually and in combination influences observable loop properties. We generate AIA intensities from the corona and transition region for each realization. The variations within and between models generated with these different parameters illustrate the sensitivity of narrowband imaging to the details of coronal heating. Using insights from this analysis, we generate images of observed coronal active regions using the GX Simulator SSW IDL package and interpret the causes of discrepancies between the models and observations.

This work investigates small-scale infiltration dynamics in smooth and rough single fractures using a three-dimensional multiphase pairwise-force smoothed particle hydrodynamics (PF-SPH) model. Gravity-driven infiltration instabilities in fractures under unsaturated conditions can significantly influence the arrival time of tracers or contaminants, and the rapid and localized recharge dynamics in fractured-porous aquifer systems. Here, we study the influence of roughness and injection rate on fluid flow modes and flow velocity. Three types of fractures are considered with different degrees of roughness, including a smooth fracture. Both the rough and smooth fractures exhibit flow instabilities, fingering, and intermittent flow regimes for low infiltration rates. In agreement with theoretical predictions, a flat fluid front is achieved when the flux q supplied to a fracture is larger than the gravitationally driven saturated flux (q > kρg/μ cosφ). To characterize the flow instability, we calculate standard deviations of velocity along the fracture width. For the considered infiltration rates, we find that an increase in roughness decreases the flow velocity and increases the standard deviation of velocity. This is caused by a higher likelihood of flow discontinuities in the form of fingering and/or snapping rivulets. To validate our unsaturated flow simulations in fractures, we estimate the scaling of specific discharge with normalized finger velocity and compute the relationship between fingertip length and scaled finger velocity, and find a good agreement with experimental results.

Total electron content (TEC) observations can provide insights into electron density variations in the ionosphere. Such variations are associated with many aspects of ionospheric dynamics, including traveling ionospheric disturbances. In the present work we assimilate observations of TEC and horizontal TEC gradients into the SAMI3 (SAMI3 is Another Model of the Ionosphere 3D) ionosphere model. Assimilation into SAMI3 is accomplished using an ensemble Kalman filter implemented within LightDA, an extensible data assimilation library. Our TEC gradient observations are obtained from the Very Large Array Low-band Ionosphere and Transient Experiment (VLITE) and the TEC measurements are derived from GNSS receiver data. VLITE provides high precision and high spatial resolution TEC gradient observations over a small area, while GNSS observations supplement these with global coverage. By leveraging TEC observations in a physics-based model through data assimilation, we aim to improve our understanding of ionospheric processes and develop tools for improved ionospheric forecasting capabilities.

Two key parameters control the localization of deformation and seismicity along and surrounding crustal faults: the strength and roughness of the preexisting fault surface. Using three-dimensional discrete element method simulations, we investigate how the anisotropy and amplitude of roughness control the mechanical behavior of healed faults within granite blocks during quasi-static triaxial compression. The results show that the localization of fracture development into a damage zone surrounding the initially weak fault zone coincides with the macroscopic failure of the rock. Rougher faults produce more gouge than smoother faults, providing an explanation for the weak influence of roughness on compressive strength. The particles within smoother fault zones slip with higher maximum fault-parallel velocities than rougher faults during the quasi-static loading, likely because the asperities do not impede slip as effectively in the smoother fault zone. The maximum fault-parallel velocity occurs after the peak stress, and falls to a steady state value by the end of the simulation, highlighting the non-constant evolution of slip despite the constant axial strain rate loading conditions. Smoother faults develop stronger correlations between the fault topography and fault slip magnitudes, likely because smoother faults experience higher velocities than rougher faults. Thus, fault surface asperities control slip by acting as speed bumps that hinder fault-plane parallel slip and promote fault-plane normal opening. These numerical models provide insights into the evolution of damage localization, fault roughness, gouge production, asperity abrasion, fault slip and stress concentrations along initially healed faults of varying roughness.

Vehicle-based methane-sensing systems are gaining popularity as tools for monitoring site-level methane emissions from oil and gas (O&G) sites. To measure emissions, vehicles equipped with methane sensors intersect plumes along roads downwind of target sites and acquire measurements in static (parked) or mobile modes. The downwind distance between the emissions source and the measurement location is one of several factors that must be considered in planning these types of surveys. Here we present a method to estimate the suitability of O&G facilities for vehicle-based measurements using downwind distances recommended in OTM 33A and the tracer technique. We present two types of analyses: (1) a historical analysis using weather reanalysis data and (2) an operational analysis using forecast data. The method uses modeled wind direction and geospatial data to identify O&G facilities that have roads between 20 and 200 m downwind for OTM 33A and between 500 m and 3000 m downwind for the tracer technique. We apply the method to O&G facilities in Alberta that will soon require annual or triannual LDAR surveys. For the historical analysis we use ERA-Interim wind data and calculate the vectorial average (resultant) of modeled winds for the period 2009-2018. Of the 35047 O&G facilities examined, we find that 7% are, on average, suitable for OTM 33A and 69% are, on average, suitable for the tracer technique, based solely on downwind distance. We surmise that other factors like landcover, weather conditions (e.g., stability), and topography would likely reduce the candidate pool from these estimates. We demonstrate the operational utility of the method by examining a subset of 100 O&G facilities in southern Alberta and using forecast wind direction from the Canadian High Resolution Deterministic Prediction System (HRDPS), which has a 2.5 km grid spacing. We propose that the method can be used as a screening tool to estimate site suitability for static vehicle-based surveys and that it will likely translate to mobile surveys once the effect of downwind distance is clarified. Other factors can be incorporated in the method once test results are available.

Understanding the exposure of business characteristics like its location, sector, size, age, and owner demographics and structure to building damages from an earthquake can inform business continuity planning and broader community and regional programs and policies for business recovery. A baseline analysis was performed for the HayWired scenario (Wein, Haveman and others, 2019) using business characteristic data from the National Establishment Time Series (NETS) which showed that location and sector are strong differentiators of disruptive building damage risk, while minority ownership, branch ownership structure, and low revenue are other above average differentiators. The HayWired analysis was limited by damage information at the census tract scale for occupancy classes (per the Federal Emergency Management Agency Hazus software). In this study, we expand the analysis to multiple earthquake scenarios and apply machine learning techniques to generate building level assessments instead of census tract level. Association of business characteristics with building damages by location increases the analysis resolution providing more nuanced understanding and analyzing across multiple scenarios shows the variability of business characteristic exposure to different earthquakes for the region and across communities. Anne Wein, Jon Haveman, Cynthia Kroll, Jeff Peters. 2019. Characteristics of Businesses disrupted by Building Damages from the HayWired Scenario Mainshock, in press.

Precise understanding of complex physical mechanisms of mesoscale process require high resolution observations of temperature, moisture, wind, precipitation, clouds. Using all collocated observations of microwave radiometer, wind profilers, electric field mill, weather radars over South-East India an observational analysis is conducted for the first time. Analysis suggests that these systems developed in warm, moist environment associated with large-scale low-level convergence. Passage of system is accompanied by convective regions with intense upward motion and towers extending up to higher levels indicating developing phase and presence of upward/downward motion comprising of heavy precipitation representing mature phase of the system followed by stratiform regions with prominent downdraft motion and less precipitation related to decay phase. Large (small) values of reflectivity and cloud liquid water values represent presence of deep (shallow)convective (stratiform) regions. Cloud to Ground (CG) lightning activity associated with storm electrification processes showed the existence of both +CG and –CG flashes in convective and dominant –CG in stratiform regions. Presence of different sized cloud liquid hydrometers in convective regions resulted in bipolar nature due to their collisions however in stratiform regions their distribution is mostly uniform and resulted in single polarity. Combination of different observations has provided the unique opportunity to examine interrelations of different physical mechanisms in storm environment. Inspection of reflectivity, CG lightning and cloud liquid water measurements have demonstrated the relationship of lightning mechanism with storm dynamics and cloud microphysics. Combined investigation of temperature, moisture and wind measurements have given considerable insight of thetae ridge formations resulting from thermal and moisture advections. Isentropic upgliding and downgliding facilitated the unique way to visualize the vertical transport of temperature and moisture through ascent and descent of air parcel. Blend of observations presented considerable insight of synoptic and complex mesoscale processes and their mutual interactions in the storm environment and provided encouraging results in explaining MCS structure.