We report on the extraction of deep ocean travel time variations from time-lapse cross-correlations between a hydrophone station and a three-component broadband seismometer. The signals we cross-correlate in this study result from repeated activity by the Monowai seamount, one of the most active submarine volcanoes of the Tonga-Kermadec ridge. In particular, we introduce a specific workflow to exploit repetitive hydroacoustic underwater source activity, which we detail to such extent that it serves as an example (or “cookbook”). For this reason, we have made the source code publicly available. The workflow proposed in this study (i) overcomes differences in instrument sensitivity and sample rates, (ii) involves the selection of eligible cross-correlations based on a source activity criterium as well as slowness analysis, and (iii) extracts the travel time variations in distinct frequency bands. In our case, the two frequency bands are 3-6 Hz and 6-12 Hz. We find that the estimated travel time variations in both frequency bands consist of a complex periodic pattern superimposed on a distinct long-term linear trend. This long-term linear trend is decreasing, which we attribute to increasing water temperatures along the propagation path of the hydroacoustic signals.

Total column measurements of CO2 (XCO2) have been proposed as a possible way to estimate emissions from large urban regions. Using calculations from the Weather Research and Forecasting (WRF) model with a 1km emissions field, we investigate the viability of both real and proposed observing systems consisting of surface and/or column measurements for constraining emission sources of various types and sizes in the San Francisco Bay Area. We find that column observations are best suited for assessing enhancements downwind of very large emissions sources. For smaller sources (such as highways), in situ surface monitors are required to provide sufficient sensitivity. We explore methods for estimating emissions from the real and simulated observations.

Summer ice in the Arctic is diminishing at an alarming rate. Increase in radiative forcing due to the loss of sea ice is contributing to global warming. Artificially enhancing the sea ice albedo could be a possible lever to restoring and rebuilding the Arctic sea ice. Using reflective hollow glass spheres with low environmental impact, Field et al (2018) reported that such a technology could be promising towards restoring Arctic Sea Ice. Here we present the preliminary climate modeling and impact assessment of such a technology both regionally and globally. We seek to answer the scientific question of whether an enhanced sea ice albedo over the whole of Arctic sea ice provides a large enough perturbation to the climate in the Arctic and if so what is its likely impact over the rest of the globe. The study shows that the climate impact of such a method results in more than 1.5°C cooler temperatures over a large part of the Arctic and about 3°C reduction over regions north of Barents and Kara Seas. We also see notable increases in sea ice thickness (20–50 cm Arctic wide) and (>15–20%) increases in sea ice concentration across large parts of the central Arctic. These preliminary results suggest that such a technology may be a viable instrument for restoring Arctic ice. However, practicality dictates that a localized targeted deployment of the technology may be more desirable. We are extending this work to evaluate targeted deployment of materials in key areas and will present the climate modeling results on efficiency of targeted deployment for at least one such targeted area. Reference: Field, L., Ivanova, D., Bhattacharyya, S., Mlaker, V., Sholtz, A., Decca, R., et al.(2018). Increasing Arctic sea ice albedo using localized reversible geoengineering. Earth’s Future, 6. https://doi.org/10.1029/2018EF000820

In the northern Hikurangi margin, aseismic slip events known as slow slip events (SSEs) occur approximately every 18-24 months with a long duration (weeks to months), and have been shown to cause 1 to 3 cm of horizontal surface displacement onshore and 1.5 to 5.4 cm of vertical displacement (uplift) offshore. The discovery of SSEs has expanded our scientific understanding of slip behavior at subduction zones to encompass behaviors beyond earthquake-producing (fast) slip events. Using converted phase seismic signals from local earthquakes in addition to direct P and S arrivals allows us to further analyze the properties of the plate interface along the subduction zone, including its composition, ­topography and heterogeneity. It has been hypothesized that these properties play a role in the process of slow slip, therefore our investigation of converted waves focuses on the area offshore the east coast of the North Island of New Zealand, where dozens of SSEs have been observed in the past twenty years. We examine an earthquake catalog comprised of local slab earthquakes occurring recorded on ocean-bottom seismometers (OBSs) from the one-year-long Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip (HOBITSS) experiment as well as New Zealand’s permanent GeoNet on-land seismic network. Preliminary findings indicate strong secondary arrivals on the vertical component of the land stations which are likely Sp conversions from the plate interface. We aim to identify conversions from the plate interface on the OBSs from the HOBITSS experiment, as these data will help us resolve a part of the plate interface that was not investigated in previous converted wave studies. We will conduct a systematic search for phase-converted arrivals from the plate interface, initially focusing primarily on Sp conversions by examining the vertical component seismograms.

Ultra-high pressure (UHP) metamorphism of the Tso Morari coesite-eclogite during burial in NW Himalaya has been intensively studied over the past several decades. However, amphibolite-facies metamorphism and accompanying metasomatism occurring at lower-crustal depths in the Tso Morari terrane are less well-constrained. In this study, we characterize the eclogite amphibolization and related metasomatic fluids by systematically sampling and analyzing the eclogites at the core of an eclogite boudin and the amphiblolized eclogite (amphibolite) at the rim. Integrated techniques including modal mineralogy, mineral chemistry, whole-rock geochemistry, Mössbauer spectroscopy, and thermodynamic modelling are used to constrain the fluid-induced eclogite amphibolization and associated fluid behaviors. Petrographic observations show that infiltration of an external fluid caused complete amphibolite-facies overprinting of the eclogites at the boudin rim. This is recorded petrographically as increased modal proportions of amphibole, biotite, epidote, plagioclase, and calcite in the amphibolites. The infiltrating fluid caused increased K2O and CO2 concentrations and higher bulk-rock Fe3+/ΣFe ratio for the amphibolites, as well as increased LILE (e.g., K, Rb, Cs, Sr, Ba) and ratios of Ba/Rb and Cs/Rb. Phase equilibria modelling using P–T–M(H2O) pseudosections on the amphibolite and the surrounding gneiss indicate that the fluid infiltration occurred at 9.0–12.5 kbar and ~608 °C with >2.6–3.1 mol % H2O infiltration. The abrupt increase of bulk-rock Fe3+/ΣFe ratio from 0.192 to 0.395 near the boudin rim indicate that this phase of fluid most likely derived from the mixing of dehydrated host orthogneiss and/or metasediments during uplift at the amphibolite-facies zone in the subduction channel. This study also demonstrates the need for using careful petrographic observations and geochemical analysis in parallel with thermodynamic modelling to achieve realistic results.

Downslope and gusty winds in the lee of the Santa Ynez Mountains (SYM) greatly influence the Santa Barbara (SB) coast in California. These winds, known as ‘Sundowners’ due to their typical peak after sunset, are characterized by northerly cross-mountain flow and strong stability at mountaintop level. The National Weather Service (NWS) defines a Sundowner when sustained cross-mountain winds greater or equal to 30 mph or gusts greater or equal to 35 mph are observed at surface stations located downwind of the SYM. In addition to gale-force winds, temperatures above 100°F and relative humidity below 15% are not uncommon during sundowners, and the marine layer influences the spatial extent to which these strong winds may reach. These conditions have led to turbulence which effects aviation at the local airport and the rapid spread of multiple destructive wildfires in the region, including the Jesusita Fire (2009), Sherpa Fire (2016), and Thomas Fire (2017).

Space weather events can impact satellite communications, astronaut health, and the electric power grid. It is thus of utmost importance that we develop efficient, reliable tools to determine when space weather events, such as solar flares, will occur and how strong they will be. The SWx TREC Deep Learning Laboratory has developed several state-of-the-art machine learning projects to improve solar flare prediction through the use of deep learning models, generative adversarial network data augmentation, and explainable artificial intelligence techniques. In particular, we compared two generative adversarial networks (GANs) to super-resolve the Solar and Heliospheric Observatory’s Michelson Doppler Imager (SOHO/MDI) magnetogram data to match the quality of the Solar Dynamics Observatory’s Helioseismic and Magnetic Imager (SDO/HMI) magnetogram data. We find that both GANs are able to preserve key features of the original SOHO/MDI magnetogram data while achieving better resolution to match the SDO/HMI data. In the future, we will use the combined, augmented dataset in a Long Short-Term Memory model for solar flare prediction to see if training on the expanded dataset results in improved predictive power compared to training on the SDO/HMI dataset alone. In addition to data augmentation, we have used Local Interpretable Model-Agnositc Explanations (LIME) on our existing solar flare prediction model to provide more insight into specific predictions. This is an important step in building trust in our model and understanding what features are driving the model’s predictions. In this presentation, we will discuss these recent projects as well as future work that the SWx TREC Deep Learning Laboratory will tackle in order to advance the field of machine learning in space weather, including: improved hardware, better visualization capabilities, cutting edge models, software tools, and community resources.

VirES is a Virtual workspace for Earth-observation Scientists, a service provided by the European Space Agency (ESA). VirES has firstly been established for ESA’s magnetic field mission Swarm as “VirES for Swarm’‘ and has been extended to ESA’s atmospheric dynamics mission Aeolus, which was launched in August 2018. The service is developed by the Austrian IT company EOX in strong collaboration with missions’ scientists. VirES is a web-based service (https://aeolus.services) that enables scientists to discover, visualize, select and download data of Earth-observation (EO) missions through an easy to operate graphical user interface. ”VirES for Aeolus” will provide access to Aeolus L1B, L2A, L2B, L2C products and auxiliary data. The first version 1.0 passed acceptance tests in April 2018 and developments towards Version 1.2 are in progress. The service is planned to be accessible for public use as soon as the mission’s phase E1 is completed and first data products are released by ESA.

Slow slip events were discovered in many subduction zones during the last two decades thanks to recordings of the displacement of Earth’s surface by dense GNSS networks. Slow slip can last from a few days to several years and have a relatively short recurrence time (months to years), compared to the recurrence time of regular earthquakes (up to several hundreds of years), allowing scientists to observe and study many complete event cycles. In many places, tectonic tremor is also observed in relation to slow slip and can be used as a proxy to study slow slip events of moderate magnitude where surface deformation is hidden in GNSS noise. However, in subduction zones where no clear relationship between tremor and slow slip occurrence is observed, these methods cannot be applied, and we need other methods to be able to better detect and quantify slow slip. Wavelets methods such as the Discrete Wavelet Transform (DWT) and the Maximal Overlap Discrete Wavelet Transform (MODWT) are mathematical tools for analyzing time series simultaneously in the time and the frequency domain by observing how weighted averages of a time series vary from one averaging period to the next. In this study, we use wavelet methods to analyze GPS time series and seismic recordings of slow slip events in Cascadia. We use detrended GPS data, apply the MODWT transform and stack the wavelet details over several nearby GPS stations. As an independent check on the timing of slow slip events, we also compute the cumulative number of tremors in the vicinity of the GPS stations, detrend this signal, and apply the MODWT transform. In both time series, we can then see simultaneous waveforms whose timing corresponds to the timing of slow slip events. We assume that there is a slow slip event whenever there is a peak in the wavelet signal. We verify that there is a good correlation between slow slip events detected with only GPS data, and slow slip events detected with only seismic data. The wavelet-based detection method detects all events of magnitude higher than 6 as determined by independent event catalogs (e.g. Michel et al., 2019, Pure Appli. Geophys.).

Two major sources of radiation hazards at commercial aviation altitudes have been known for decades and those are galactic cosmic rays (GCRs) as well as solar energetic particles (SEPs). GCRs are produced outside the solar system in high-energy explosive events and consist mostly of energetic protons slowly modulated by the strength of the Sun’s interplanetary magnetic field (IMF). SEPs come from either solar coronal mass ejections (CMEs) related to flaring events or from IMF shocks. In the latter case fast CMEs plow through a slower solar wind creating a shock front to produce energetic protons. Recently, a third radiation source has been identified that originates from relativistic electron precipitation (REP) associated with the Van Allen radiation belts and have been called radiation clouds although a physical perspective is likely to be flight through a γ-ray beam. This ensemble radiation field creates safety concerns for aviation. Because of this safety hazard, a broad community is seeking to i)define the requirements for real-time monitoring of the charged particle radiation environment to protect the health and safety of crew and passengers during space weather events; ii)define the scope and requirements for a real-time reporting system that conveys situational awareness of the radiation environment to orbital, suborbital, and commercial aviation users during space weather events; and iii)develop or improve models for the real-time assessment of radiation levels at commercial flight altitudes. While benchmarks for ionizing radiation related to aviation have included characterizing an occurrence frequency of 1 in 100 years and an intensity level at the theoretical maximum for radiation events, it is also important to develop a baseline radiation environment for GCRs, SEPs, and REPs against which events can be compared. We describe functional, analytical baselines for describing the ionizing radiation environment for commercial aviation based on observations and modeling as part of the NAIRAS, ARMAS, and RADIAN programs.

Current General Circulation Models (GCMs) are struggling to capture the observed diurnal cycle of precipitation. One major problem is that GCMs usually have difficulties to simulate nocturnal deep convections. Nocturnal deep convections are usually decoupled with the land surface and are controlled by other factors aloft, which have not been fully understood. The Plains Elevated Convection at Night (PECAN) is a multi-institutional collaborated field experiment conducted at the central Great Plains during summertime (1 June to 15 July) 2015 on the purpose of improving the understanding and simulation of the processes that initial and maintain deep convections at night. During the 45-day PECAN period there are 31 intensive operational periods (IOP) of nighttime deep convections, each last for one night. The unique part of PECAN experiment is the use of 6 fixed and 4 mobile PECAN Integrated Sounding Arrays (PISA) to take detailed measurements for each IOP. These detailed measurements of thermodynamics, wind and water vapor profiles in high temporal resolution (typically 90-min) allow the observation of the evolution of boundary layer and propagating features. We will report results from the analysis of these PISAs using a constrained variational analysis method to understand the large-scale environment that control the nighttime deep convections at the central Great Plains.

Soil erosion is a worldwide agricultural and environmental problem that threatens food security and ecosystem viability. In arable environments, the primary cause of soil loss is short and intense storms that are characterized with high spatiotemporal variability. The complex nature of these erosive events imposes a great challenge for erosion modeling and risk analysis. Accurate high-resolution measurement of rain intensity is often lacking or sparsely available. As a result, many studies rely on coarser-resolution rainfall data that often fail to address the impact of intra-storm properties. In this study, based on a novel statistical method, we quantify the discrete and cumulative multiannual impact of rainstorm regime on runoff and soil erosion to better understand the most important rainstorm properties on erosion rate and amount, and, to provide storm-scale risk analyses. Central to our analyses is the coupling of a processes-based crop-land erosion model, Dynamic Water Erosion Prediction Project (DWEPP), with a stochastic rainfall generator that produces localized rainfall statistics at 5-min resolution (CoSMoS). To our knowledge, this is the first study that calibrated DWEPP runoff and sediment at the plot-scale on cropland. The model had an acceptable fit with measured event runoff and sediment data collected in northern Israel (NSE = 0.79 - 0.82). We then generated 300-year stochastic simulations of event-based runoff and sediment yield and used them to estimate erosion risk and calibrate a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. Results indicate that in the study area, high erosion rate events are characterized by intense rain bursts of short duration (shorter than the usually adopted erosivity index of 30-min), and not necessary by events of large volume accumulation or long duration. On these bases, we proposed an optimal rainfall erosivity index that combines intra-storm properties for the study area. As changes in rainstorm properties are expected under a changing climate, we expect our methodology to be a valuable tool for investigating the global concerns about future changes in soil erosion rate.

Airflows over complex geometrical surfaces such as complex terrain and densely built urban districts are highly turbulent and sometimes become a threat under disturbed weather conditions. Among the meteorological disturbances, the landfalls of tropical cyclones cause strong winds and may lead to severe damages in populated urban areas and in mountainous areas. Because gusty winds are primarily a cause for damages, diagnosing and predicting quantitatively wind and turbulent characteristics are critically important. In order to assess strong wind hazards in complex urban areas, this study uses a large-eddy-simulation (LES) model with buildings and structures explicitly resolved at an O(1 m) grid spacing. With such a building-resolving LES model, we have analyzed turbulent airflows in urban districts of Japanese major cities and have found that the LES model is capable of estimating the magnitude of gusty winds and turbulent fluctuations. In order to improve the accuracy in representing the properties of airflows, we have developed a data assimilation method which incorporates observed turbulence. The proposed data assimilation method used a vibration equation which can incorporate turbulence winds toward target mean winds while maintaining small-scale turbulent fluctuations and was applied for airflows in actual urban districts of Kyoto City by incorporating data obtained from meteorological observations located in Kyoto. We have concluded that the data assimilation method using the vibration equation successfully nudges toward the target mean winds while maintaining small-scale turbulent fluctuations well. Our recent LES analyses of airflows in urban districts have been extended to studies related to the impact assessment of and the adaptation to climate change in urban areas. A building-resolving LES model has become a practical tool to more applied side of turbulent airflow analysis.

SE Asia is renowned as a region of complex plate tectonic interactions, both in the present day and throughout its Mesozoic and Cenozoic history. The study of subduction processes in SE Asia has been instrumental in our understanding of how complex subduction systems develop and evolve, including understanding double subduction zones, areas of subduction polarity reversal, and the interaction of subduction and strike-slip systems. This complexity in subduction style makes SE Asia an ideal natural laboratory for studying forearc development in a range of subduction styles across a relatively small area still exposed in the rock record. Here we present a recently studied example of forearc development in a Mesozoic double subduction zone exposed on Natuna Island in the South China Sea, as well as highlighting two other examples of forearc development in SE Asia. These include a Cenozoic subduction polarity reversal event and transform plate boundary in western New Guinea and forearc sedimentation along the Sunda Trench. All three scenarios chronicle histories of forearc accretion, either of deep-water cherts or continental-derived turbidites, whilst also recording the impacts of case-specific tectonic processes (such as ophiolite obduction, arc-continent collision, or strike-slip movement) that have fundamentally impacted their respective forearcs. Comparing these contrasting examples shows that studying forearc development of these complex subduction systems (including their structural styles, geochemistry and timing of associated magmatism, and sedimentation) in SE Asia can be a powerful tool for improving understanding of forearc evolution in other ancient and complex subduction systems.

Multi-frequency acoustic backscatter measurement can be used to observe spatial profiles of suspended sediment. The use of multiple frequencies helps to resolve mean particle size by exploiting the frequency-dependent relationship between scattering intensity and particle size. The AQUAscat acoustic backscatter profiler uses this principle to estimate mean particle size and concentration profiles with spatial resolution between 2.5 mm and 40 mm. The instrument is usually configured to acquire profiles of backscatter amplitude. However, an infrequently used setting on the standard instrument provides direct access to the quadrature sampled backscatter data stream, from which amplitude is normally calculated. By using the in-phase and quadrature sample data, the backscatter phase can also be calculated. The rate of phase change between profiles can then be related to the along-beam velocity of the scatterers. For a vertical beam, in the absence of vertical water motion, this is the settling velocity. This paper evaluates datasets and data processing approaches for estimating particle settling velocity. The experimental data is acquired with various types of laboratory generated suspensions, including glass spheres, sands, and flocculating mud. Besides extracting settling velocity data, the processing aim is to enhance the quality of acoustic backscatter data analysis.

The complexity of induced seismicity mechanisms significantly hampers seismic hazard assessment around injection wells. The largest magnitude events are commonly thought to be controlled by the size of the injection-affected area, but what controls the size of this area and what is the role of the regional geologic setting? Here we explore observations of deep and distant induced earthquakes in Oklahoma and California. Despite wide-spread injection close to seismically active faults, fluid injection-induced seismicity is comparably rare in California hydrocarbon basins. We identified a potential case of injection-induced earthquakes associated with San Ardo oilfield operations, with the largest events occurring in 1955 (ML5.2) and 1985 (Mw4.5) within ∼6 km from the oilfield. We performed an interferometric analysis of SAR images acquired by Sentinel-1A/B satellites between 2016 and 2020, and find surface deformation of up to 1.5 cm/yr, indicating pressure-imbalance in parts of the oilfield. Temporal correlations are observed over more than 40 years, with correlation coefficients of up to 0.71 for seismicity within 24 km of the oilfield. Such large distances have not previously been observed in California but are similar to the large spatial footprint of injection in Oklahoma. The San Ardo seismicity shows anomalous clustering with earthquakes consistently occurring at close spatial proximity but long inter-event times, analogous to induced earthquakes in geothermal reservoirs. The complexity of seismic behavior at San Ardo indicates that multiple processes, such as elastic stress transfer and aseismic slip transients, contribute to the potentially induced earthquakes. The observed power-law distance decay of induced events from the reservoir is in line with observations of stress decay from poroelastic models in which basement faults may be hydraulically isolated from the injection zone. Our model’s resolved fluid/solid stress interactions suggest that shallow injection can 1) activate deep basement faults and 2) lead to spatially extensive induced earthquake sequences. Both of these observations may significantly elevate the seismic hazard associated with fluid injection operations.

Fine sediment dynamics is an important issue in alpine rivers since it impacts both dam management (decrease of the reservoir capacity, flushing strategy) and river management (interaction between fine sediment and vegetation, gravel bar stabilisation, flood risk). Suspended Particle Matter (SPM) is generally assumed to be transported as washload although significant exchanges with the river bed have been detected in several cases. As a consequence but also due to the variable SPM sources and differences in the discharge and sediment wave velocities, one can often observe a hysteresis behaviour during hydrological events that evolves spatially along the system. In this study, we will present results from a network of hydro-sedimentary stations (measuring both water discharge and sediment concentration) along a reach of 120 km starting from the Arvan River at its confluence and the Arc and Isère rivers, that is part of the ZABR (or Rhône Basin Long Term Environmental Research Observatory). The SPM dynamics is analysed for different types of events (large flood, spring flood, flushing event, debris flow). In particular, we focus on the potential of erosion or deposition between each station by calculating the total SPM flux during each event at each station as well as the hysteresis behaviour using a hysteresis index. The evolution of these parameters is related to input parameters such as discharge and sources and grain size characteristics of the suspension. Indeed, most observed sediment exchanges (erosion or deposition) occur on the gravel bars when inundated, and depend on settling characteristics of the SPM. Also the experimental site provides some useful data for estimating advection and dispersion characteristics of various SPM events that could be used to validate numerical models.

In the northeastern Atlantic Ocean, the eastward-flowing Azores Current converges towards the southwestward-flowing Canary Current, following the African coastline and leading the Eastern Boundary Current System of the North Atlantic Subtropical Gyre. Based on satellite altimetry measurements (1992-2006) and in situ observations (1998, 2002), Sangrà et al. (2009) described for the first time the Canary Eddy Corridor in the northeastern Atlantic Ocean (22.1oN - 29.1oN) as a zonal long-lived mesoscale eddy corridor. In this work, we extend the study area and redefine five zonal corridors that expand from 12oN to 40oN. The aim is to assess the potential role of these eddy corridors as zonal conveyors of mass and ocean properties. To ease its identification, we name these corridors following their generation sites: Cape Verde, Cape Blanc, Canary Islands, Madeira, and the Azores Front. We do this using an altimeter-based dataset of global mesoscale ocean eddies (1992-2018). The analyses are performed in terms of the eddy demography and eddy geometric properties. Generally, we find that cyclonic eddies (CEs) are the most frequent type of long-lived eddies (> 6 months) everywhere but in the Cape Verde Corridor and the Azores Front Corridor, where anticyclonic eddies (AEs) and CEs are of similar number. On average, CEs propagate the farthest away due to the combination of longer lifetimes and higher track stabilities, although AEs also reach on occasions as far as 1000 km away from their generation site. Zonally, results agree well with theory and show recurrent patterns about their geometric eddy properties, where both anticyclonic (AEs) and cyclonic (CEs) eddies display significant differences. Both eddy types increase (decrease) its radius and decrease (increase) its amplitude and rotational speeds when their corridor locates at lower (higher) latitudes. Also, observed eddies propagate west at approximately the phase speed of nondispersive baroclinic Rossby waves, according to their latitude. These results highlight the implications of the geographical location (latitude) of the eddy corridors, suggesting that low latitude eddy corridors may generate the best candidates to convey ocean properties to remote places while these candidates are significantly less frequent than eddies of higher latitude corridors.