Abstract. Here we propose a methodology for Earthquake Early Warning able issuing the alert based on the real-time estimation of the epicentral area where a ground Intensity measure is expected to exceed a user-set ground shaking level. The method provides in output a P-wave-based, time-evolutive “early” shake map. The P-wave displacement, velocity and acceleration amplitudes are jointly measured on a progressively expanded time window while the earthquake location and magnitude are evaluated using data at near source stations. A retrospective analysis of the 2016, Mw 6.5 Central Italy earthquake records shows that the method naturally accounts for effects related to the earthquake rupture directivity and spatial variability of strong ground motion related to source and path and site effects. Five seconds after the origin time the simulated performance of the system in predicting the event impact is very high: in the 40 km-radius area that suffered an Intensity MCS VIII-IX, 41 over 42 strong-motion instrumented sites would have been successfully alerted, with only one false alert. Even considering the 15-km-radius blind-zone, a 15-55 km wide annular area would have received the alert 2-14.5 sec before the occurrence of the strong ground shaking.The proposed EEW method evolves with time in a way that it minimizes the missed alarms while increasing successful alarms and to a lesser extent false alarms, so it is necessary for the end-user to accept these eventualities and account for them in a probabilistic decision scheme depending on the specific safety actuation measure to be undertaken in real-time

Localized frictional sliding on faults in the continental crust transitions at depth to distributed deformation in viscous shear zones. This brittle-ductile transition (BDT), and/or the transition from velocity-weakening (VW) to velocity-strengthening (VS) friction, are controlled by the lithospheric thermal structure and composition. Here we investigate these transitions, and their effect on the depth extent of earthquakes, using 2D antiplane shear simulations of a strike-slip fault with rate-and-state friction. The off-fault material is viscoelastic, with temperature-dependent dislocation creep. We solve the heat equation for temperature, accounting for frictional and viscous shear heating that creates a thermal anomaly relative to the ambient geotherm which reduces viscosity and facilitates viscous flow. We explore several geotherms and effective normal stress distributions (by changing pore pressure), quantifying the thermal anomaly, seismic and aseismic slip, and the transition from frictional sliding to viscous flow. The thermal anomaly can reach several hundred degrees below the seismogenic zone in models with hydrostatic pressure, but is smaller for higher pressure (and these high-pressure models are most consistent with San Andreas Fault heat flow constraints). Shear heating raises the BDT, sometimes to where it limits rupture depth rather than the frictional VW-to-VS transition. Our thermomechanical modeling framework can be used to evaluate lithospheric rheology and thermal models through predictions of earthquake ruptures, postseismic and interseismic crustal deformation, heat flow, and the geological structures that reflect the complex deformation beneath faults.

Brittleness index (BI) has been considered as a key geomechanical parameter in evaluating fracturability of the shale formation for optimal extraction of hydrocarbon. BI is commonly used to quantitatively classify the brittle-ductile zones in thick shale reservoir and is considered as completion quality index. There are different methods for determining BI. In the present study, mineralogy based BI estimation method has been followed to identify brittle zones of Cambay Shale of Jambusar-Broach block, Cambay basin, India. Mineralogical composition is having a very significant role in controlling brittleness of a rock. Advanced geochemical logs like the Elemental Capture Spectroscopy (ECS) / Litho Scanner were utilized to get the continuous estimation of mineralogical composition of the Cambay Shale formation. XRD and SEM-EDS techniques are also used for mineralogical analysis of selected core samples taken from different depths. Analysis from XRD and SEM-EDS techniques reveals that the shale is composed of kaolinite, chlorite, quartz, siderite, pyrite and other minerals. Good match has been observed between the BI estimated using mineralogical composition from geochemical log and XRD analysis of core samples. Along with BI, another parameter namely fracability index (FI) has been also used for hydro-fracture evaluation. FI has been estimated continuously, combining normalized brittleness index and normalized Young’s modulus. In addition to BI and FI, type of clay minerals present has some controlling role during hydro-fracture. Mineralogical analysis reveals that for hydro-fracture operation, Cambay Shale has the advantage of having kaolinite and chlorite as dominant clay minerals which are comparatively less susceptible to swelling and plastic behaviour than other clay minerals like illite. An integrated analysis of BI, FI, mineralogy, petrophysical and geochemical properties will be helpful for identification of potential target zones within thick shale. Acknowledgement The authors would like to thank Oil and Natural Gas Corporation Limited, India for providing the requisite dataset and core samples to carry out the present study.

Recent studies have shown that ocean-bottom pressure gauges (OBPs) can record seismic waves in addition to tsunamis and seafloor permanent displacements, even if they are installed inside the focal area where the signals are extremely large. We developed a method to extract dynamic ground motion waveforms from near-field OBP data consisting of a complex mixture of various signals, based on an inversion analysis along with a theory of tsunami generation. We applied this method to the OBP data of the 2011 Tohoku-Oki earthquake. We successfully extracted the low-frequency vertical seismograms inside the focal area (f < ~0.05 Hz), although those of the Mw ~9.0 megathrust earthquake had never previously been reported. The seismograms suggested two dominant energy releases around the hypocenter. The seismic wave signals recorded by the near-field OBP will be important not only to reveal earthquake ruptures and tsunami generation processes but also to conduct real-time tsunami forecasts.

Significant advancements have been made over the past four decades in understanding and quantifying the stocks and flows of carbon between the reservoirs. However, knowledge of the complex oceanic processes influencing the carbon cycle has been largely compartmentalized into physico-chemical and biological studies. The connections between coastal and open-ocean carbon processes have also been understudied. To fully appreciate the ocean carbon cycle, and its anticipated changes in the future, a holistic and integrated approach to ocean carbon cycle research is needed. In particular, a greater quantitative understanding of how biological processes interact with the physical and chemical drivers in the open ocean and in coastal waters is needed. Moreover, the carbon cycle needs to be understood in the current socio-economic context and large anticipated changes in the next decades. To address these issues, the Integrated Ocean Carbon Research (IOC-R), a formal IOC working group, was formed in 2018. The working group is a response to the UN Decade of Ocean Science for Sustainable Development 2021-2030, “the Decade”. The IOC-R will contribute to the science elements of an overarching Implementation Plan for the Decade. The Implementation Plan is a high-level framework to guide actions by which ocean science can more effectively deliver its contribution to achieving the societal outcomes outlined for the Decade. The IOC-R focusses the ocean carbon cycle component of the Implementation Plan by addressing key issues in ocean carbon research through a combined strategy of research and observational goals. The research will be framed by four key questions that were formulated at the inaugural Expert Workshop on Integrated Ocean Carbon Research at the IOC-UNESCO Headquarters in Paris, France on Oct. 28-30, 2019: 1) Will the ocean uptake of anthropogenic carbon dioxide (CO2) continue as primarily an abiotic process? 2) What is the role of biology in the ocean carbon cycle? 3) What are the exchanges of carbon between the land-ocean continuum and how are they evolving over time? 4) How are humans altering the ocean carbon cycle, and what are the feedbacks?

The land-sea connection of nutrients via rivers is an essential component in the global nutrient biogeochemistry. Rivers alone transport approximately 80% of the dissolved nutrients from land to ocean and play a vital role in nourishing riverine, coastal and oceanic ecosystems. During the past decades, global scale investigations have estimated the riverine nutrient flux to the oceans along with the significant drivers. However, most of the previous estimations are based on nutrient discharge by a few major rivers. Despite being large in number and high yields, the tropical coastal/mountainous rivers have received less attention. To fill the gap, we have investigated 70 west-flowing coastal rivers, draining the Western Ghats (WG), for their Dissolved Inorganic Nutrient (DIN) transport characteristics and influencing factors. Previous studies in the selected estuaries along the WG coast are combined to update the land-sea fluxes estimation to understand the spatial pattern of DIN over the WG rivers-the Arabian sea coast continuum. Altogether, the DIN fluxes from entire WG (including non-sampled rivers) region to the estuaries are 664, 241 and 6277 Tg yr-1 for Nitrate (N), Phosphate (P) and Silicate (DSi) respectively. The natural factors, such as discharge, cropland, and forest cover each explain 30–85% of the spatial variation in DIN levels at the basin scales. DIN concentrations of rivers reduces to ~ 90% after reaching the respective estuaries. Based on Redfield ratio of C:N:P (106:16:1), annual export of 66.4 Tg of dissolved inorganic N from the WG rivers would support 439.9 Tg of new carbon production in the Arabian Sea coast. The humid tropical climate and high population density (> 300 people per km2 among the bio-diversity hotspots) of the WG region favour the high DIN export, thus, making the Arabian sea coast highly productive among the global coastal regions. Keywords: Dissolved Inorganic Nutrients; Rivers-Coast Continuum; Influencing Factors; Small Mountainous Rivers; Western Ghats.

Seasonal and diurnal variations in the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) version 06B final run and TRMM Multi-satellite Precipitation Analysis (TMPA) 3B42 products were accessed from April 2014 to March 2019. Systematic annual mean differences between IMERG and TMPA data over the oceans were smaller for IMERG version 06B than for earlier IMERG versions, possibly because of updated calibration processes. The mean differences between the IMERG version 06B and TMPA data for tropical oceans were relatively small, but differences between two datasets for the tropical Pacific for all four seasons were not. The diurnal amplitude of the IMERG was smaller than that of the TMPA over most continents, and the differences increased with mean diurnal amplitude. The diurnal amplitude of the IMERG were larger than that of the TMPA data over the oceans. The differences between the phases of the precipitation diurnal harmonics in the IMERG and TMPA datasets varied widely in all four seasons, but the mean phases were almost the same over both the oceans and the land. The sources of the differences in diurnal precipitation amplitudes in the Bay of Bengal and along the west coast of Central America, which showed large diurnal ranges and rather different diur-nal amplitudes, were assessed. Differences in seasonal means caused differences in diurnal amplitudes in the Bay of Bengal, but for Central America differences in diurnal amplitudes were associated with seasonal mean diurnal amplitudes.

The spatial variation of azimuthal S-wave phase velocity anisotropies caused by differential horizontal stress along the subducting plate at the Nankai Trough was analyzed to understand the stress state of the overhung block of the forearc region, off Kii Peninsula, Japan. We conducted controlled-source seismic surveys along the circumference of a 3 km diameter circle centered at each seismometer of a cabled earthquake observatory installed on the seafloor above the Kumano basin of the Nankai Trough subduction zone. We applied an anisotropy semblance method to estimate the orientation of fast and slow S-wave velocities of both shallow sediments and deep accretionary prism using the multi-azimuth seismic dataset acquired at each seismometer location. The estimated orientations of fast S-wave velocity are parallel to the convergent direction of the subducting place beneath the Kumano basin in the deeper accretionary prism while perpendicular to the convergent direction in the shallow sediments inside the Kumano basin. The orientations of these fast S-wave polarization show good agreement with those of horizontal maximum stress orientations estimated in situ borehole measurements in the observation area Then differential horizontal stress field in the Nankai Trough region was estimated from obtained S-wave anisotropy using a simple crack model. The azimuths of fast S-wave polarization and the derived differential stresses could be explained well by the tectonics of the Nankai Trough subduction zone. These results strongly suggested that the S-wave azimuthal anisotropy measurements could be used to monitor the subsurface stress field as a function of time.

Methane plays an important role in determining the atmosphere’s climate and chemistry. Fluxes of methane from an ecosystem are often measured using eddy covariance flux towers; however, there are disadvantages with this method. Flux towers are expensive to purchase and have high demands with respect to maintenance and cost of operation, especially in remote locations, making replication across the landscape a challenge. Using sensors mounted on a unmanned aerial vehicle (UAV), also known as a drone, would allow replication of flux measurements across a landscape as well as enable scientists to measure methane at locations where towers are not practical (i.e. sites that are ephemeral in nature, immediately after a disturbance, etc.). In this work, we test the ability of a UAV equipped with a highly accurate methane sensor to calculate ecosystem flux using the mass balance method. This method uses data collected with curtains (transects at various heights) flown both upwind and downwind of the area of interest. The concentration of methane within these curtains is then estimated using kriging techniques. The difference in calculated amounts of methane between the upwind and downwind curtains is processed to obtain an estimate of flux. Flights in wetlands that also have eddy covariance towers, providing corroborating flux values, have been flown in Alaska and California. We calculated UAV-based flux for the Alaskan flights using a bootstrap approach from multiple randomly subsampled data points within each full curtain of data. We compare these calculations to the traditional mass balance technique. We tested if these different approaches improve the accuracy of our results, as well as the uncertainty bounds for the small fluxes emitted from these ecosystems.

Join us in an exploration of the climate of Northland, a world where the entire northern hemisphere is covered by a continent, and the entire southern hemisphere is covered by an ocean! On the continent, we will visit the seasonally moist tropics, the subtropical desert, and the Great Northern Swamp. We explore the interplay between water, energy, land, ocean, and atmosphere in this idealized climate model study. We find that the presence of a continent greatly increases the poleward extend of the ITCZ over both the land and ocean hemispheres compared to an aquaplanet, as a result of hemispheric energy imbalances introduced by (a) the small heat capacity of land and (b) large reductions in atmospheric water vapor (and thus reduced longwave trapping) over the continent. A combination of moisture transport from the tropics and local water recycling results in a polar swamp over the continent. We explore how the climate state responds to changes in the albedo and evaporative resistance of the continent. While making the land surface darker leads to warming, we find that decreasing evaporation from the land surface leads to global-scale cooling. This is in contrast to past studies, where reduced terrestrial evaporation leads to warming as a result of suppressed evaporative cooling of the land surface. In the case of Northland, the lack of an ocean to provide water to the northern hemisphere means that decreasing land evaporation leads to large reductions in water vapor over the northern hemisphere, in turn reducing strength of the greenhouse effect, resulting in cooling of near-surface air temperatures. This cooling signal is strongest over the continent, but cools air temperatures over the ocean hemisphere as well. We hypothesize that a threshold exists in the temperature response to reduced terrestrial evaporation: for small decreases in evaporation, reduced latent cooling dominates and near-surface temperatures warm, while for large decreases in evaporation, reduced longwave trapping from reduced atmospheric water vapor dominate, cooling near-surface temperatures. Through this idealized study of a hypothetical, Earth-like planet, we gain valuable insight into the connections between water, energy, land surface properties, and continental distribution in controlling global-scale climate.

To understand the overall features of the history of magmatic activities and surface environment on Mars, I used a numerical model of magmatism in the convecting mantle that is nominally anhydrous and internally heated. Magmatism occurs as an upward permeable flow of basaltic magma generated by decompression melting through matrix. The modeled mantle evolves in four stages. In Stage I, high initial temperature in the uppermost mantle causes an extensive magmatism intensified by two types of positive feedback that operate between magmatism and mantle upwelling flow, the MMUb and MMUc feedback: the buoyancy and volume change of matrix, respectively, caused by migrating magma that a mantle upwelling flow generates intensify the flow itself to generate more magma. The stratification suppresses mantle convection and magmatism for the next tens to hundreds of millions of years, allowing heat to build up in the mantle by internal heating (Stage II). Eventually, magma is generated at depth, and the MMUb feedback operates to cause an episodic plume magmatism that releases water from the interior of Mars (Stage III). The plume magmatism also stirs the mantle to make it more homogeneous and extracts heat producing elements from the deep mantle to let the magmatism itself wane and cease. In the final stage IV, mantle convection becomes more like a thermal convection. The episodic magmatism and water outgassing in Stage III account for the magmatism and clement surface environment observed for early Mars.

The Antarctic Ice Sheet remains one of the greatest sources of uncertainty for improving predictions of sea level rise, and constraining this uncertainty has long been a difficult challenge within glaciology and climate science. Cryoseismology, paired with the meteoric rise of data science applications within the geosciences, has emerged as a promising field well suited to answering these challenges as the improvement of sampling technology and access have resulted in a proliferation of Antarctic seismic data. Ice flow dynamics in Antarctica are significantly influenced by features and processes at the bed, and basal microseismicity from tremors as ice moves across the bed can yield valuable information for resolving the glacier subsurface. We deployed high-frequency (up to 1000 Hz) geophone arrays at Rutford Ice Stream over the 2018-2019 austral summer to monitor the natural source seismicity from the base of the ice and generate an event catalog. To efficiently process the enormous volumes of cryoseismic data to locate events, we used the Python package QuakeMigrate which utilizes a parallelized waveform stacking algorithm to detect coherent seismic phase arrivals across our network. Over three months of data, we located over 1,700,000 seismic events (majority which were microseismic) within a 4 km x 4 km square grid around our 13-station, ~3.25 km2 area array. The detection and location of icequakes at this resolution provides a unique opportunity to investigate the temporal, location, and size relations between events, and we present the findings from our data mined event catalog and document the QuakeMigrate parameter tuning to optimize event location. The significant amounts of data collected of the region over the past decades mean that the literature and documentation of conditions at Rutford is more complete relative to most of Antarctica, and our work aims to contribute towards a comprehensive survey of an Antarctic region.

Many current research efforts undertake the solar flare classification task using the Space-weather HMI Active Region Patch (SHARP) parameters as the predictors. The SHARP parameters are scalar quantities based on spatial average or integration of physical quantities derived from the vector magnetic field, which loses information of the two-dimensional spatial distribution of the field and related quantities. In this paper, we construct two new sets of spatial features to expand the feature set used for the flare classification task. The first set uses the idea of topological data analysis to summarize the geometric information of the distributions of various SHARP parameters. The second set utilizes tools coming from spatial statistics to analyze the vertical magnetic field component Br and summarize its spatial variations and clustering patterns. All features are constructed within regions near the polarity inversion lines (PILs) and classification performances using the new features are compared against the SHARP parameters (also along PIL). We found that using the new features can improve the skill of the flare classification model and new features tend to have higher feature importance, especially the spatial statistics features. This potentially suggests that even using a single channel Br, instead of all SHARP parameters, one can still derive strongly predictive features for flare classification.

A globally interactive geo-socioeconomic revolution will be necessary in order to sustainably resource our continued our ways of life and be able to expand beyond to the next giant leap of human progression and evolution. Applied comprehensive integrated changes coupled with a global collaboration invested in over-reaching environmental goals incorporating both the public and private sectors are at the crux of properly upgrading infrastructures and societies. Positive non-biased re-engineering of our societies and their governing laws, policies and economies must include two underlying principles- transparency and environmental transformation. These two founding principles are the Great Green Reset’s scaffolding meant to address a lexicon of constantly revolving and evolving socioeconomic, political, and environmental issues. By integrating environmental sustainability and reclamation in conjunction with promoting biodiversity, We, being a socially accepting, fair, safe and healthy Peoples, can progress confidently into the Fourth Industrial Revolution knowing that at this juncture in human history and time, “We actively took a global stance choosing to make the correct decisions for the successful continuation and advancement of our species and its way of life so our future generations may experience the same lush biodiversity on Earth that we so heavily rely on for our existence”. To gain the public trust, transparency and environmental transformation are the core underlying principles that create a scaffolding of sound, logical, common-sense science policies that legislative decisions are built around. Along with developing national and international science policy frameworks centered around a healthier, greener, smarter future, legislators should reap the deep benefits of having a highly qualified transdisciplinary science team dedicated to consulting with indigenous peoples, local communities, and key experts to provide unbiased opportunity to re-imagine and re-engineer science policy promoting fair socioeconomic equitable equality at all levels of interaction on local, national, and international framework scales. All this must be envisioned within a circular economy.

Land cover information is fundamental in numerical weather prediction and climate modelling because of its impact on the land surface heat, momentum, and moisture fluxes. A new land cover (LC) dataset for the European region is introduced here for the WRF (Weather Research and Forecasting) model coupled with the Noah-MP surface scheme. As part of the Copernicus program the satellite-based Coordination of Information on the Environment (CORINE) LC dataset is available for most of the European continent at high resolution (100 m). This dataset provides a more detailed land cover classification compared to the default WRF LC database over Europe. Its potential applications range from urban numerical studies to regional climate modelling. The CORINE dataset is incorporated into WRF at two different resolutions of 0.00208333° and 0.00416666°. Furthermore, the original 44-category CORINE LC for the WRF model is converted to the USGS LC categories for applications where less detailed but still up-to-date information is desired. It is shown that the application of the CORINE LC dataset not only affects near-surface temperatures (by ≈1 °C on average and ≈3-6 °C over urban areas) but precipitation, snow cover, and wind speed as well.

At Mars, charge exchange between solar wind protons and neutral exospheric hydrogen produces energetic neutral atoms (ENAs) that can penetrate into the collisional atmosphere, where they can be converted through collisions into H+ and H–. The Mars Atmosphere and Volatile EvolutioN (MAVEN) mission observed a population of negatively charged particles at low altitudes, whose energies, angular distribution, and dependence on the upstream solar wind were consistent with H–originating in the solar wind. The highest fluxes of H– were observed near perihelion and the southern summer solstice. We calculated an average ratio of ~4% between H– density and H+ density, implying a slightly smaller relative abundance than reported previously (~10%). We found that the fraction of H ENAs converted to H– increases with the solar wind energy, in agreement with laboratory measurements of the H–CO2 electron capture cross section.

Understanding the seismic precursors is essential for deciphering earthquake rupture physics and can aid earthquake probabilistic forecasting. With regional dense seismic arrays, we identify seismic precursors of 527 0.9 ≤ M ≤ 5.4 events of the 2019 Ridgecrest earthquake sequence, including 48 earthquakes with series of precursors. These precursors are likely immediate-foreshocks that are adjacent to the earthquakes. Their corresponding precursory signals share high resemblances with the earthquake P-waves and occur within 100 s of the P-waves. However, attributes of the immediate-foreshocks, including the amplitudes and preceding times, do not clearly scale with the eventual earthquake magnitudes. Our observations suggest that earthquake rupture may initiate in a universal fashion but evolves stochastically. This indicates that earthquake rupture development is likely controlled by fine-scale fault heterogeneities in the Ridgecrest fault system, and the final magnitude is the only difference between small and large earthquakes.

Spatial variation in landscape attributes can account for much of the variability in water quality compared to land use factors. Spatial variability arises from gradients in topographic, edaphic, and geologic landscape attributes that govern the four dominant processes (atmospheric, hydrological, microbially mediated redox, physical and chemical weathering) that generate, store, attenuate, and transport contaminants. This manuscript extends the application of Process Attribute Mapping (PoAM), a hydrochemically guided landscape classification system for modelling spatial variation in multiple water quality indices, using New Zealand (268,021 km²) as an example. Twelve geospatial datasets and >10,000 ground and surface water samples from 2,921 monitoring sites guided the development of 16 process-attribute gradients (PAG) within a geographic information system. Hydrochemical tracers were used to test the ability of PAG to replicate each dominant process (cross validated R2 of 0.96 to 0.54). For water quality, land use intensity was incorporated and the performance of PAG was evaluated using an independent dataset of 811 long-term surface water quality monitoring sites (R2 values for total nitrogen of 0.90 - 0.71 (median = 0.78), nitrate-nitrite nitrogen 0.83 - 0.71 (0.79), total phosphorus 0.85 - 0.63 (0.73), dissolved reactive phosphorus 0.76 - 0.57 (0.73), turbidity 0.92 - 0.48 (0.69), clarity 0.89 - 0.50 (0.62) and E. coli 0.75 - 0.59 (0.74)). The PAGs retain significant regional variation, with relative sensitivities related to variable geological and climatic histories. Numerical models or policies that do not consider landscape variation likely produce outputs or rule frameworks that may not support improved water quality.