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Enero de 2024 Volcano geoengineering is the practice of altering the state of volcanic systems and/or volcanic eruptions to exploit them or mitigate their risk. Although many in the field insist there is little that can be done to mitigate the hazard, past examples of both intentional and inadvertent volcano interventions demonstrate that it is technically feasible to reach volcano plumbing systems or alter atmospheric processes following eruptions. Furthermore, we suggest that economical, political, and environmental pressures may make such interventions more common in the future. If volcano geoengineering ever becomes a discipline, it will need to overcome many safety and ethical concerns, including dealing with uncertainty, deciding on |
philosophical approaches such as a consequentialism or precautionary principle, justice and inequality, military uses, cultural values, and communication. We highlight that while volcano geoengineering has significant potential benefits, the risks and uncertainties are too great to justify its use in the short term. Despite this, because of the potential large benefits to society, we believe there is a strong ethical case to support research into the efficacy and safety of volcano geoengineering for its potential future use. We propose that rigorous governance and regulation of any volcano geoengineering is required to protect against potential risks, to enable potentially valuable and publicly available research (e.g., quantification of efficacy and safety), to ensure that any future policy must be co-created through community engagement, and that volcano geoengineering should only be considered as part of larger mitigation practices. |
Enero de 2024 This study aims to explain the nonuniform earthquake pattern along the Cascadia Subduction Zone. In particular, we investigate the relationship between the tectonic features of the subducting oceanic Juan de Fuca slab and the onshore seismicity pattern. We have integrated multiple geophysical data sets toward three general objectives. The first study intends to study variations in physical properties along three 2-dimensional models through regions of different seismicities that combine public gravity, magnetic, and seismic data sets. These models reveal multiple zones of decreased crustal density that we interpret as |
regions of weaker oceanic crust. The second objective is to delineate major tectonic features by performing spatial analysis of potential fields. The overall methodology comprises gravity and magnetic data filtering, followed by lineaments mapping and cross-referencing interpretation with available seismic reflection data. This process allows delineating zones of crustal weakness by extrapolating outside our three 2-D models. We also map multiple seamounts that appear to cluster along identified zones of weaker crust. Third, we investigate the relationship between the mapped tectonic elements, namely the zones of weak crust with accompanying seamounts, and the observed seismicity trends within the subducted slab. The alignment between those suggests that mapped weak crust zones and associated seamounts may have an influence on the overall subduction process. As more of these structures are heading toward the Washington portion of the margin than to the Oregon portion, more earthquakes are observed in the north than in the south. |
Enero de 2024 In active volcanoes, magmatic fluids rising toward the surface may interact with shallow waters, thereby forming hydrothermal systems that record variations in magma dynamics at depth. Here, we report on a data set comprising the chemical and isotopic composition of thermal waters and dissolved gases from Stromboli Island (Aeolian |
Volcanic Arc, Southern Italy) that spans 14 years (2004–2018) of continuous observations. We show that the shallow thermal aquifer of Stromboli results from variable mixing between meteoric water, seawater and magmatic fluids. Gas-water-rock interactions occur, which induce a large spectrum of variation in both water and gas chemistry. These shallow processes do not affect the 3He/4He of helium dissolved in thermal waters, which records a magmatic signature that varies in response to changes in magma supply at depth. We show that in periods of more intense volcanic activity, the helium isotopic composition of thermal waters approaches that of the gas emitted from the magma residing |
Diciembre de 2023 Latent heat (LH) released from precipitation during the water phase change process is the primary energy source driving atmospheric circulation. Current satellite LH retrieval algorithms are mainly physical-based or lookup table-based. In this study, a fully connected neural network LH algorithm (FCNH) was developed and tested by weather research and forecasting model (WRF) simulations and global precipitation measurement (GPM) satellite observations. FCNH uses three types of modules: feature representation, feature fusion, and regression. Using satellite observable vertical derivation of precipitation rate (urn:x-wiley:2169897X:media:jgrd58973:jgrd58973-math- |
0001) and air temperature (T) as inputs into FCNH achieved the best LH retrieval performance; increasing the number of input variables covering environmental or precipitation characteristics degraded the retrieval accuracy. Compared to the WRF simulated true LH, the FCNH retrieval captured the main features of horizontal and vertical structures with high correlation coefficients and showed improved performance over the associated physical-based LH algorithm on the same inputs. The FCNH algorithm can alleviate the overestimation of cooling near the surface and the overestimation of positive heating in the mixing layer. The LH retrievals from FCNH and the other three algorithms using inputs of GPM observations were compared, and all achieved basically consistent results. This study is the first attempt to use an artificial neural network method for satellite remote sensing of LH inside precipitation clouds. It promotes understanding of the learning efficiency, accuracy, and limitations of using a fully connected neural network to retrieve LH. |
Diciembre de 2023 The emergence of large language models (LLMs), such as ChatGPT, has garnered significant attention, particularly in academic and scientific circles. Researchers, scientists, and instructors hold varying perspectives on the advantages and disadvantages of using ChatGPT for research and teaching purposes. ChatGPT will be used by many scientists going forward for creating content and driving scientific progress. This commentary offers a brief explanation of the fundamental principles |
behind ChatGPT and how it can be applied in the fields of hydrology and other Earth sciences. The article examines the primary applications of this open artificial intelligence tool within these fields, specifically its ability to assist with writing and coding tasks, and highlights both the advantages and concerns associated with using such a model. Moreover, the study brings up some other limitations of the model, and the dangers of potential miss-uses. Finally, we suggest that the academic community adapts its regulations and policies to harness the potential benefits of LLMs while mitigating its pitfalls, including establishing a structure for utilizing LLMs and presenting clear regulations for their implementation. We also outline some specific steps on how to accomplish this structure. |
Diciembre de 2023 The population of Santiago, Chile, experiences air pollution above global health guidelines that is attributable in part to large anthropogenic emissions. This is compounded by geographic features and meteorological conditions that are prone to pollution accumulation as well as secondary pollution production. In recent years, there have been improvements in air quality; however, the future of air pollution in Santiago remains unclear due to its growing population and increased vehicle use. Mitigation efforts can be supported by characterizing sources of air pollution and estimating how changes in emissions could affect air quality in future years. In this study, we conduct simulations using a chemical transport |
model (GEOS-Chem) and perform adjoint calculations to characterize the relationship between health impacts associated with exposure to PM2.5, O3, and NO2 and anthropogenic emissions. We incorporate model updates in a new nested domain simulation over Central South America including local and regional anthropogenic emissions inventories for Chile. We estimate that 2,490 (1,360, 4,060) PM2.5- and O3-related premature deaths and 5,350 (1,320, 11,330) NO2-related new pediatric asthma cases were associated with pollution exposure in Santiago in 2015 and that a majority of these health impacts were attributable to anthropogenic emissions. We identify emissions from transportation, energy generation, and residential combustion as the leading contributors to these health impacts. Additionally, we estimate that Chile's commitment to attain carbon neutrality by 2050 could result in benefits in Santiago of 3,230 (1,240, 7,160) avoided deaths and 2,590 (640, 5,500) avoided pediatric asthma cases in 2050 compared to business-as-usual emissions. |
Diciembre de 2023 The role of lithospheric heterogeneities, presence or absence of melt, local and regional stresses, and gravitational potential energy in strain localization in continental rifts remains debated. We use new seismic and geodetic data to identify the location and orientation of the modern Nubia-Somalia plate boundary in the 300-km-wide zone between the southern Main Ethiopian Rift (MER) and Eastern Rift (ER) across the Mesozoic Anza rift in the Turkana Depression. This region exhibits lithospheric heterogeneity, 45 Ma-Recent magmatism, and more than 1,500 m of base-level elevation change, enabling the assessment of strain localization mechanisms. We relocate 1716 earthquakes using |
a new 1-D velocity model. Using a new local magnitude scaling with station corrections, we find 1 ≤ ML ≤ 4.5, and a b-value of 1.22 ± 0.06. We present 59 first motion and 3 full moment tensor inversions, and invert for opening directions. We use complementary geodetic displacement vectors and strain rates to describe the geodetic strain field. Our seismic and geodetic strain zones demonstrate that only a small part of the 300 km-wide region is currently active; low elevation and high-elevation regions are active, as are areas with and without Holocene magmatism. Variations in the active plate boundary's location, orientation and strain rate appear to correspond to lithospheric heterogeneities. In the MER-ER linkage zone, a belt of seismically fast mantle lithosphere generally lacking Recent magmatism is coincident with diffuse crustal deformation, whereas seismically slow mantle lithosphere and Recent magmatism are characterized by localized crustal strain; lithospheric heterogeneity drives strain localization. |
Diciembre de 2023 In active volcanoes, magmatic fluids rising toward the surface may interact with shallow waters, thereby forming hydrothermal systems that record variations in magma dynamics at depth. Here, we report on a data set comprising the chemical and isotopic composition of thermal waters and dissolved gases from Stromboli Island (Aeolian Volcanic Arc, Southern Italy) that spans 14 years (2004–2018) of continuous observations. We show that the shallow thermal aquifer of Stromboli results |
from variable mixing between meteoric water, seawater and magmatic fluids. Gas-water-rock interactions occur, which induce a large spectrum of variation in both water and gas chemistry. These shallow processes do not affect the 3He/4He of helium dissolved in thermal waters, which records a magmatic signature that varies in response to changes in magma supply at depth. We show that in periods of more intense volcanic activity, the helium isotopic composition of thermal waters approaches that of the gas emitted from the magma residing at 7–10 km depth. Investigation of hydrothermal waters at active volcanoes is a promising tool to examine magmatic fluids and their shallow circulation, as well as to evaluate the state of activity of a volcano, particularly when summit areas are inaccessible. |
Diciembre de 2023 Someday, a great earthquake will erupt from the San Andreas fault, which cuts through Southern California from Los Angeles to San Francisco. Geologic records make it clear. It has happened, and it will happen again. |
violently than official hazard models suggest. The good news for Angelenos stems from five rocks balanced precariously on top of other rocks in Lovejoy Buttes, a place in northern Los Angeles County that sits just 15 kilometers from the fault. By dating when the rocks first became fragile and analyzing their structures to assess the maximum shaking they could withstand, the researchers could test official predictions against thousands of years of earthquakes. Those predictions have been found wanting, says Anna Rood, a seismic hazard scientist at the Global Earthquake Model Foundation who led the work, which is accepted in Seismological Research Letters. “The hazard estimates are totally inconsistent with these precariously balanced rock data..." |
Diciembre de 2023 On 6 February 2023, a local tsunami was recorded in the southeastern Mediterranean Sea following the Mw 7.7 Turkey–Syria inland strike-slip earthquake. Due to the lack of underwater observation, the tsunami generation mechanism remains mysterious. To understand the source mechanisms, we analyzed the tsunami waveforms of four nearby tide gauges and located possible |
sources using a backward tsunami ray tracing approach. We then conducted forward numerical modelings for a range of possible source parameters. We show that there were probably two tsunami sources, inside and outside Iskenderun Bay, which may be related to thick coastal sediments. A source inside the Bay with a characteristic length of 7 km produced dominant periods of 10–30 min with negative initial motion, possibly generated by a landslide. Another source of 6 km length outside the Bay produced dominant periods of 2–10 min with positive initial motions, possibly related with liquefaction. |
Diciembre de 2023 This study proposes to construct a model using random forest method, an efficient machine learning-based method, to predict the spatial structure and temporal evolution of the sea surface temperature (SST) cooling induced by northwest Pacific tropical cyclones (TCs), a process of the so-called wind pump. The predictors in use include 12 |
predictors related to TC characteristics and pre-storm ocean conditions. The model is shown to skillfully predict the spatiotemporal evolutions of the cold wake generated by TCs of different intensity groups, and capture the cross-case variance in the observed SST response. Another model is further built based on the same method to assess the relative importance of the 12 predictors in determining the magnitude of the maximum cooling. Computations of feature scores of those predictors show that TC intensity, translation speed and size, and pre-storm mixed layer depth and SST dominate, depending on the area where the cooling is considered. |
Diciembre de 2023 Co-seismic Ionospheric disturbances (CID, or “ionoquakes”) are disturbances in the electron density or total electron content (TEC) of the ionosphere, produced by the ground motion due to earthquakes. Usually, ionoquakes are detected in the near-epicentral region within 8–10 min after an earthquake onset time. In this work, we present a new methodology that allows to estimate the CID arrival time based on determining the CID peak time |
in TEC measurements with respect to the peak time of seismic waves registered by the nearest seismic station. Our methodology also allows to understand the altitude of GNSS detection that otherwise remains ambiguous. We apply the newly developed techniques to detect CID signatures associated with three large earthquakes: the 2015 Illapel, the 2014 Iquique, and the 2011 Sanriku-Oki. We show that for these events, the CID arrive 250–430 s after the time of the seismic wave peak, or 350–700 s after the earthquake onset time. Our analysis show that the first CID are detected at the altitudes of 150–180 km (the Sanriku earthquake) and of 200–300 km (the Illapel and the Iquique earthquakes). The disturbances represent high-frequency acoustic oscillations that propagate with a horizontal speed faster than 0.75 km/s. |
Diciembre de 2023 Following laboratory experiments and friction theory, slow slip events and seismicity rate accelerations observed before mainshocks are sometimes interpreted as evidence of a nucleation phase. However, such precursory observations still remain scarce and are associated with different time and length scales, raising doubts about their actual preparatory nature. We study the 2017 Valparaiso Mw = 6.9 earthquake, which was preceded by aseismic slip accompanied by an intense seismicity, suspected to reflect its nucleation phase. We complement previous observations, which have focused only on precursory activity, with a continuous investigation of seismic and aseismic processes from the foreshock sequence to the post- |
mainshock phase. By building a high-resolution earthquake catalog and searching for anomalous seismicity rate increases compared to aftershock triggering models, we highlight an over-productive seismicity starting within the foreshock sequence and persisting several days after the mainshock. Using repeating earthquakes and high-rate GPS observations, we highlight a transient aseismic perturbation starting 1-day before the first foreshock and continuing after the mainshock. The estimated slip rate over time is lightly impacted by large magnitude earthquakes and does not accelerate toward the mainshock. Therefore, the unusual seismic and aseismic activity observed during the 2017 Valparaiso sequence might be interpreted as the result of a slow slip event starting before the mainshock and continuing beyond it. Rather than pointing to a possible nucleation phase of the 2017 Valparaiso mainshock, the identified slow slip event acts as an aseismic loading of nearby faults, increasing the seismic activity, and thus the likelihood of a large rupture. |
Noviembre de 2023 For decades, the Epidemic-Type Aftershock Sequence (ETAS) model has been the most popular way of forecasting earthquakes over short time spans (days/weeks). It is formulated mathematically as a point process, a general class of statistical model describing the random occurrence of points in time. Recently the machine learning community have used neural networks to make point processes more expressive and titled them neural point processes. In this study we investigate |
whether a neural point process can compete with the ETAS model. We find that the two models perform similarly on computer simulated data; however, the neural model is much faster with large data sets and is not hindered if there is missing data for smaller earthquakes. Most earthquake catalogs contain missing data due to varying capability in our detection methods, therefore we need models that are robust to this missingness. We then find that the neural model outperforms ETAS on a new catalog for the 2016–2017 Central Apennines earthquake sequence, which through machine learning detection contains thousands of previously undetected small magnitude events. We argue that some of this improvement can in fact be explained by missing data. These results present neural point processes as an encouraging competitor in earthquake forecasting. |
Noviembre de 2023 Co-seismic Ionospheric disturbances (CID, or “ionoquakes”) are disturbances in the electron density or total electron content (TEC) of the ionosphere, produced by the ground motion due to earthquakes. Usually, ionoquakes are detected in the near-epicentral region within 8–10 min after an earthquake onset time. In this work, we present a new methodology that allows to estimate the CID arrival time based on determining the CID peak time |
in TEC measurements with respect to the peak time of seismic waves registered by the nearest seismic station. Our methodology also allows to understand the altitude of GNSS detection that otherwise remains ambiguous. We apply the newly developed techniques to detect CID signatures associated with three large earthquakes: the 2015 Illapel, the 2014 Iquique, and the 2011 Sanriku-Oki. We show that for these events, the CID arrive 250–430 s after the time of the seismic wave peak, or 350–700 s after the earthquake onset time. Our analysis show that the first CID are detected at the altitudes of 150–180 km (the Sanriku earthquake) and of 200–300 km (the Illapel and the Iquique earthquakes). The disturbances represent high-frequency acoustic oscillations that propagate with a horizontal speed faster than 0.75 km/s. |
Octubre de 2023 Tsunami early warning requires the fast and reliable estimation of an earthquake magnitude provided by Earthquake Early Warning (EEW) systems. EEW systems are currently limited by the propagation speed of P-waves, which rely on as natural information carriers. Even more problematic, EEW systems based on the first seismic arrivals tend to saturate with earthquake magnitude, and can become unreliable for magnitudes above 8. The recent discovery of Prompt Elasto-Gravity Signals (PEGS), which comprise gravitational changes |
generated by earthquakes, has raised hope to overcome these limitations because they travel at the speed of light, much faster than P-waves. We use PEGS to re-train the previously developed deep learning model PEGSNet to track the magnitude evolution of big earthquakes in the Chilean subduction zone, historically affected by tsunamis. Given the scarcity of big earthquakes, we simulate signals to train the model using synthetic sources and the seismic stations available in 2010 and 2021, augmented with empirical noise recorded by those stations. PEGSNet tracks the moment release 90 s after the origin time. The performance of PEGSNet is limited by the seismic network configuration, the number of stations and the level of noise in the data, but could be useful for tsunami warning. |
Octubre de 2023 The main earthquake of Mw 7.8 occurred at 01:17:34 UTC and was followed by the three notable (Mw > 5.5) aftershocks within the next 18 min. Then, ∼9 hr later, the biggest aftershock with magnitude Mw 7.5 and a Mw 6.0 earthquake occurred to the north-east from the first main earthquake. In this work, we use data of ground-based Global Navigation Satellite Systems (GNSS) receivers in Turkey, Israel and Cyprus to analyze the ionospheric response to this series of earthquakes. We separate these events in |
two groups: the first sequence of earthquakes (at 01–02 UTC) and the second sequence (at 10–11 UTC). For the first sequence, we observe a clear N-shaped total electron content (TEC) response after the Mw 7.8 mainshock earthquake and Mw 6.7 aftershock, and a smaller TEC disturbance that is, most likely, caused by the Mw 5.6 earthquake. The latter is now the smallest earthquake detected by using ionospheric GNSS data. The co-seismic ionospheric disturbances (CSID) propagated from the epicentral area in the south-west direction with velocities of about 750–830 m/s. For the second sequence, we observed the response to the Mw 7.5 aftershock earthquake and the Mw 6.0 aftershock. The CSID propagated both to the south-west and the north-west to the epicentral area, with velocities of about 950–1,100 m/s. |
Septiembre de 2023 Seismology is witnessing explosive growth in the diversity and scale of earthquake catalogs. A key motivation for this community effort is that more data should translate into better earthquake forecasts. Such improvements are yet to be seen. Here, we introduce the Recurrent Earthquake foreCAST (RECAST), a deep-learning model based on recent developments in neural temporal point processes. |
The model enables access to a greater volume and diversity of earthquake observations, overcoming the theoretical and computational limitations of traditional approaches. We benchmark against a temporal Epidemic Type Aftershock Sequence model. Tests on synthetic data suggest that with a modest-sized data set, RECAST accurately models earthquake-like point processes directly from cataloged data. Tests on earthquake catalogs in Southern California indicate improved fit and forecast accuracy compared to our benchmark when the training set is sufficiently long (>104 events). The basic components in RECAST add flexibility and scalability for earthquake forecasting without sacrificing performance. |
Septiembre de 2023 Maar-diatreme volcanoes are small volcanic structures with a funnel-shaped crater surrounded by a tephra-ring. They are usually formed by the explosive phreatomagmatic eruptions when groundwater comes into the contact with magma. We focus on such a structure in the geodynamically active western Eger Rift (Czech Republic) and present results from multidisciplinary geophysical investigation calibrated by drilling in the newly discovered Pleistocene Bažina maar. We evaluated morphological (LiDAR-based DEM) data and confirmed the existence of a maar-diatreme structure by combined geophysical methods. In the map view, they revealed circular negative gravity anomaly, funnel-shape low-resistivity anomaly, and |
strong magnetic anomaly. These results allowed for the optimal location of two boreholes in the maar crater, which evinced its contact with country rocks and lithologies of the maar-diatreme filling. The drilling revealed coherent volcanic rocks and volcaniclastic deposits, moreover, it revealed a presence of a pyroclastic cone with the olivine nephelinite feeding conduit. Further investigations disclosed maar structure and subsequent pyroclastic cone(s) with several generations of eruptions and systematic decrease of water influence on the eruption style. Different eruption styles suggest a unique evolution of two volcanoes, one inside the other. The age of the Bažina maar eruption, estimated from the reverse polarity of the detected magnetic anomaly, implies that the effusion and solidification of the lava during the eruption must be older than 0.78 Ma (Pleistocene). This points to an active volcanism in the western Eger Rift in a span of 0.5 Ma, where Bažina represents the oldest (maybe opening) phase. |
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