Краткосрочный прогноз землетрясения на основе озоновых предвестников для территории Камчатки

This study investigated earthquake occurrences in Nigeria using the Weibull equations. The data employed in this study was the historical and instrumental data recorded from 1933 to 2018. The relationship between intensity scale and Richter magnitude scale given by Gutenberg and Richter
 was used to convert from intensity scale to Richter scale. The Weibull equations were used to compute probabilities and return periods of earthquakes. The findings of the study revealed that the return period for an earthquake of magnitude 6.5 on Richter’s scale is 86 years; an earthquake of magnitude 4.7 is 34.4 years; an earthquake of magnitude 4.2 is 17.2 years and earthquake of magnitudes 2-3.7 is between 5.56-14.3years. This implies that Nigeria may not likely experience any earthquake of magnitude 6.5 till the year 2025 since earthquake of magnitude 6.5 last occurred in 1939 but the probability of occurrence is 1.16% or 0.0116. Earthquakes of highest magnitudes 6.5, 4.7 and 4.2 on Richter’s scale for a 100 year period which indicate the most hazardous in the location with probabilities exceedance of 1.16%, 2.91% and 4.65% were evaluated. It was observed that as the time increases the probability of occurrence of these earthquakes increases with it and vice versa with magnitude 4.2 having (99.1%), magnitude 4.7 having (94.8%) and magnitude 6.5 having (80.07%). But earthquake forecast or prediction is still a complicated issue due to saturation of earthquake magnitudes and variation in seismic data collection by different seismic stations and networks. The implication of this study is that the findings will help Nigeria government to protect its people, infrastructures and the constructions that are going to take place especially earthquake – prone areas like southwestern Nigeria.

Modelling horizontal and vertical concentration profiles of ozone and oxides of nitrogen within high-latitude urban areas

Current models used for earthquake forecasting assume that the magnitude of an earthquake is independent of past earthquakes, i.e., the earthquake magnitudes are uncorrelated. Nevertheless, several studies have challenged this assumption by revealing correlations between the magnitude of subsequent earthquakes in a sequence. These findings could significantly improve earthquake forecasting and help in understanding the physics of the nucleation process.We investigate this phenomenon for the foreshock sequence of the first 2019 Ridgecrest event (Mw6.4) using a high-resolution catalog; choosing this foreshock sequence has been guided by a low b-value (~0.68 ± 0.06 after converting local magnitudes to moment magnitudes) and a significant magnitude correlation, even when considering only earthquakes above the completeness level estimated with different methods. To disregard incomplete events in the b-value estimation, we apply the b-positive approach (van der Elst 2021), i.e., using only positive magnitude differences; those magnitude differences are uncorrelated and we obtain a markedly higher b-value (~0.9 ± 0.1). Apparently, the foreshock sequence contained substantial short-term aftershock incompleteness due to a Mw4.0 event.We observe a similar behaviour for whole Southern California after stacking earthquake sequences. Finally, we generate synthetic catalogs and apply short-term incompleteness to demonstrate that common methods for estimating the completeness level still result in magnitude correlation, indicating hidden incompleteness.Our findings highlight that (i) existing methods for estimating the completeness level have limited statistical power and the remaining incompleteness can significantly bias the b-value estimation; (ii) the magnitude correlation is the most powerful property to detect incompleteness, so it should supplement statistical analyses of earthquake catalogs.

Forecasting earthquakes of various intensities will continue to be an urgent task that has yet to bene resolved. The use of various forecasting methods makes it possible to conduct analysis and warnings more objectively and reliably. Methods of short-term prediction of strong earthquakes based on satellite monitoring of cloudiness anomalies can be used with some success. Based on the research results, it was established that before strong earthquakes, linear cloudiness anomalies are observed over the Earth's deep fault zones, which can be used for short-term earthquake forecasting. The most effective method of studying cloudiness anomalies is the use of satellite methods. As a result of the analysis of linear cloudiness anomalies, a conclusion was made about the possibility of a regional short-term forecast of strong and catastrophic earthquakes with an assessment of the possible magnitude and approximate position of the future earthquake. The reliability of the forecast depends on the tectonic structure of the region and atmospheric conditions. It is important to be able to forecast the magnitude of the future earthquake based on the length of the cloudiness anomaly. It was established that the length of the cloudiness anomaly before a catastrophic earthquake allows one to predict the magnitude, which is very important for forecasting the level of seismic danger in the coming days.

The clustering phenomenon in seismology draws significant attention from geophysicists as well as the public at large. The reason for this is rooted in the fundamental interest of reliable earthquake prediction; or otherwise, if earthquake prediction is possible. The investigations of earthquake spatial-magnitude clustering, especially if earthquake magnitudes are clustering within a controlling geological structure(s), are however, still of active debate. In this paper, we first present several discoveries on the magnitude clustering phenomenon via the interrogation of the laboratory acoustic emission (AE); after that, we shortly display the accompanying instigations on field-scale catalogs intrigued by the laboratory interrogation. In laboratory, the clustering of AE event magnitude can only unconditionally exist under shear stress; the tensile stress will remove the magnitude clustering phenomenon. This confirmation from laboratory interrogation intrigues the field investigation on several natural and anthropogenic catalogs crossing the North American continent. As the consequence that pure tensile stress condition can hardly exist in field-scale, magnitude clustering phenomenon for field-scale catalogs is found to be prominent crossing scales from the scale of hundreds of meters to the scale of hundreds of kilometers. INTRODUCTION The clustering phenomenon in space and time is a well-recognized feature of earthquakes. There are prominent examples of earthquakes as being spatial clustering, i.e. the aftershocks around a mainshock, and temporal clustering, i.e. the Omori-Utsu decay in the temporal productivity after a mainshock (Felzer & Brodsky, 2006; Utsu, Ogata, & Matsu’ura, 1995). However, the existence of clustering in earthquake magnitudes is still a matter of active debate. The earthquake magnitudes were thought to be independent until a set of studies reported magnitude correlations between sequential catalogued earthquakes (A. Corral, 2004; A. Corral, 2006; Lippiello, Godano, & de Arcangelis, 2007). Questions on these results had also been proposed by other researchers as the magnitude clustering observation could be influenced by catalog incompleteness (Davidsen & Green, 2011; Davidsen, Kwiatek, & Dresen, 2012). The reason for the extensive investigations on earthquake clustering phenomenon is rooted in the fundamental interest of reliable earthquake prediction; or otherwise, to address the question if earthquake prediction is really possible (Davidsen & Green, 2011). If magnitude clustering does exist, it can have practical meanings for the short-term earthquake forecasting. For instance, if similar magnitude events are clustered in aftershock sequences (Field et al., 2017; Nandan, Ouillon, & Sornette, 2019; Nichols & Schoenberg, 2014; Spassiani & Sebastiani, 2016). Specifically, contemporary forecasting approaches typically utilize the epidemic-type aftershock sequence (ETAS) methodology for simulating seismicity. This method has incorporated with the spatial and temporal clustering but has not included any form of magnitude clustering (Field et al., 2017; Hardebeck, 2013; Ogata, 1988).

For the past several decades, scientists have been exploring the possibilities of decoding the complex physical mechanism of the earthquake process using satellites and ground-based technologies. In recent years, use of satellite-based technologies has been preferred, since monitoring a broader region and round-the-clock surveillance is possible using geostationary satellites. Using sensors mounted on satellites, it is possible to observe anomalous thermal variations in both the atmosphere and the ground. Measurement of anomalous variations in outgoing longwave radiation (OLR) is one such technology used to identify earthquake preparation zones. Anomalous variations in OLR have been observed in the vicinity of the epicenter, 3 to 30 days prior to impending earthquakes. We have analyzed the OLR scenario for earthquakes with magnitude greater than 7.0 that occurred during April 2016. Analysis has been done to find the relationship between OLR flux variations and the magnitude of the earthquakes. From the analysis, we have found that the recurrence frequency of OLR anomaly and cumulative energy flux of OLR can give us vital clues about the probable magnitude of impending earthquakes.

A short-term tsunami forecast and effective tsunami warning is a key problem of the tsunami service. At present, the conventional method for short-term tsunami forecasting is based on seismological information only (earthquake magnitude, time of the main shock and epicentre location). An earthquake magnitude which exceeds the established threshold value, which is different for different tsunamigenic zones, typically results in the issuing of a tsunami warning (Gusiakov, 2011). This approach, based on the “magnitude-geographical principle”, is straightforward and rather effective: at least it ensures few tsunami omissions. However, this method cannot provide sufficiently accurate estimates of tsunami wave heights, especially for specific coastal areas. Firstly, this is because the dependence of the tsunami intensity on the earthquake magnitude is far from being deterministic (Gusiakov, 2011): strong earthquakes can produce weak tsunamis (or no tsunamis at all) and, vice versa, sometimes destructive tsunamis are induced by relatively weak earthquakes. Secondly, because actual tsunami runups are strongly variable along the coast (c.f. MacInnes et al., 2009), the tsunami alarm can be justified for one coastal site, but false for another. Moreover, the magnitude-geographical warning method does not allow evaluation of the duration of the tsunami alarm or prediction of the arrival time of the largest tsunami wave (not necessarily the first, which is quite typical for tsunami events (c.f. Rabinovich et al., 2008)). Consequently, up to 75% of tsunami warnings turn out to be false (Gusiakov, 2011; Poplavsky et al., 1997). False tsunami warnings cause anxiety among emergency managers, government officials and the business community. These false alarms result in actual financial losses, sometimes significant, including losses due to production downtime and expenses for emergency evacuation procedures and navigation of vessels to the open sea (NOAA Tsunami, 2004).

Цунами являются одними из самых катастрофических природных явлений, приносящих колоссальные разрушения и уносящих большое число человеческих жизней. Причины возникновения цунами могут быть различными: подводные землетрясения, подводные оползни, извержения вулканов. Даже известны случаи возникновения цунами в результате обрушения в море больших оползней и обвалов. Изучением физики возникновения и развития цунами занимались с древности и продолжают заниматься учёные разных стран. Основное направление исследований связано с построением краткосрочного прогноза землетрясений. В настоящее время традиционные методы краткосрочного прогнозирования цунами основаны только на сейсмологической информации (магнитуде землетрясения, времени главного толчка и местоположении эпицентра). Магнитуда землетрясения, превышающая установленное пороговое значение, которое различается для разных цунамигенных зон, обычно приводит к выдаче предупреждения о цунами. Научная значимость и актуальность обозначенной проблемы очень высока, более того, она жизненно необходима для большинства населения планеты, живущего в прибрежных районах. Как показывает история последних десятилетий, особенно события 2004 и 2011 годов и последних лет, эффективность работы службы предупреждений о цунами далека от своего совершенства. Не предсказанные катастрофические цунами, плохая оценка энергии возникающих цунами, объявления ложных тревог приводят к большим экономическим и социальным потерям. Это связано, прежде всего, с отсутствием достоверного краткосрочного прогноза цунами. Работы последних лет, основанные на применении распределённой сети GPS-приёмников, системы DART, спутниковых технологий, направлены на решение данной проблемы, но итоговые результаты этих исследований пока не видны. Мы считаем, что решение задачи краткосрочного прогноза цунами, основанного на дистанционной регистрации деформационных процессов, происходящих в очаговой области места возникновения цунами, является самым перспективным направлением исследований. Tsunamis are one of the most catastrophic phenomena, causing tremendous destruction and claiming a significant number of lives. The causes of tsunamis can be different: water-quake, underwater landslides and volcanic eruptions. Even cases of tsunami are known as a result of the collapse of a huge mass of rocks in the sea. Scientists from different countries since antiquity have been studying the physics of the occurrence and development of tsunamis. The main direction of research is related to the construction of a short-term forecast of earthquakes. Currently, the traditional method of short-term tsunami forecasting is based only on seismological information (earthquake magnitude, main shock time and epicenter location). An earthquake magnitude exceeding a predetermined threshold value that differs between tsunamigenic zones usually results to a tsunami warning. The scientific significance and relevance of this problem is very high, moreover, it is vital for the majority of the world's population living in coastal regions. As the history of recent decades, especially the events of 2004 and 2011, and even recent years, shows, the efficiency of the tsunami service, to put it mildly, is far from perfect. The misses of catastrophic tsunamis, poor estimation of the energy of the arising tsunamis, false alarms, lead to very sad consequences. This is primarily due to the lack of a reliable short-term tsunami forecast. The works of recent years, based on the use of a distributed network of GPS receivers, DART systems, satellite technologies, are aimed at solving this problem, the final results of which are not yet visible. We believe that solving the problem of short-term tsunami forecast based on remote registration of deformational processes occurring in the source area of the tsunami origin is the most promising area of research, which will be partially confirmed in this paper.

Use of a dense monitoring network of low-cost instruments to observe local changes in the diurnal ozone cycles as marine air passes over a geographically isolated urban centre

A strong earthquake is always preceded by groupings of shocks whose identification and understanding constitute a sound method for improving short-term earthquake forecasts. Thanks to a graphical method, we have identified and classified some microsequences and reversed phase repetitive patterns that precede the hazardous events. The seismic microsequences include a series of information useful to know in advance the beginning of energy release and accumulation phases that usually precede and follow a moderate-to-high magnitude earthquake. Their identification and correct interpretation allow us to determine various warning signals. In particular, through the analysis of their shape and position in the seismic sequence we can claim that the strongest earthquakes occur shortly after the formation of some peculiar micro-sequences. The checks carried out on large data sets related to earthquakes occurred in the past have shown that the analysis procedures developed do not depend on the size of the area analyzed while predicting a high percentage of moderate-to-high magnitude earthquakes.

CMAQ predictions of tropospheric ozone in the U.S. southwest: Influence of lateral boundary and synoptic conditions

Aerial ozone concentration during the operation of an atmospheric pressure pencil-type plasma jet, a proto type for biomedical applications, is measured as a function of the distance from the jet nozzle. Ozone concentration is below time weighted average (TWA) allowable concentration of 0.08 ppm for inert gases of (He, Ne, and Ar)-jets in the plasma current of less than 10 mA. However, air–plasma jet of a current 20–40 mA, operated with a higher voltage, generates a higher ozone concentration in the air, which exceeds the TWA limitation. Ozone concentration decreases exponentially; proportional to the distance from the area of discharge cavity, where we presume the ozone concentration to be the order of $10^{2}$ ppm. The solutions of the diffusion equation confirm that the concentration diminishes to below 1 ppm at 20 cm away from the growth area of $10^{2}$ ppm without considering the destruction of ozone during diffusion in the air.

The article is devoted to the analysis of the development and control of the operation of the functional mock-up of the information service for automated monitoring and short-term forecasting of severe earthquakes in the Kamchatka-Sakhalin region. The tasks of the service mock-up concerning the collection, processing of data on earthquake precursors, the forecasting of severe (earthquake magnitude 6 or more) earthquakes in the form of estimates of the times of their onset, coordinates of epicenters (latitude and longitude) and earthquake magnitudes are determined. Taking the geoinformational character of the initial data on the approaching earthquakes as the basis for constructing the mock-up of the service, a geo-integration platform is proposed. This allows the integration of the information resources of the earthquake precursor monitoring systems, the functions of processing monitoring information into earthquake forecasts, the results of generating earthquake forecasts and their presentation to consumers into a single geoinformation environment. The composition of the service mock-up and the functioning of such elements as microservices are considered: collection and processing data from receivers of radio navigation signals of the GPS/GLONASS systems; collection and processing of data on the global distribution of TEC in the ionosphere; collection and processing of data on geomagnetic conditions, the flux of solar radio emission, thermal anomalies, as well as data concerning the atmospheric anomalies over the test site area and a unit for presenting and communicating the results of the operation of the information service mock-up for automated monitoring and short-term forecasting of severe earthquakes. The results of service operation are illustrated with the help of examples of retrospective forecasting of a number of severe earthquakes that occurred over the past 10 years in the Kamchatka-Sakhalin region, according to their precursors.

Five-year measurements of ozone fluxes to a Danish Norway spruce canopy

High ground-level ozone concentrations are typical of Mediterranean climates. Plant exposure to this oxidant is known to reduce carbon assimilation. Ozone damage has been traditionally measured through manipulative experiments that do not consider long-term exposure and propagate large uncertainty by up-scaling leaf-level observations to ecosystem-level interpretations. We analyzed long-term continuous measurements (>9 site-years at 30min resolution) of environmental and eco-physiological parameters at three Mediterranean ecosystems: (i) forest site dominated by Pinus ponderosa in the Sierra Mountains in California, USA; (ii) forest site composed of a mixture of Quercus spp. and P. pinea in the Tyrrhenian sea coast near Rome, Italy; and (iii) orchard site of Citrus sinensis cultivated in the California Central Valley, USA. We hypothesized that higher levels of ozone concentration in the atmosphere result in a decrease in carbon assimilation by trees under field conditions. This hypothesis was tested using time series analysis such as wavelet coherence and spectral Granger causality, and complemented with multivariate linear and nonlinear statistical analyses. We found that reduction in carbon assimilation was more related to stomatal ozone deposition than to ozone concentration. The negative effects of ozone occurred within a day of exposure/uptake. Decoupling between carbon assimilation and stomatal aperture increased with the amount of ozone pollution. Up to 12-19% of the carbon assimilation reduction in P. ponderosa and in the Citrus plantation was explained by higher stomatal ozone deposition. In contrast, the Italian site did not show reductions in gross primary productivity either by ozone concentration or stomatal ozone deposition, mainly due to the lower ozone concentrations in the periurban site over the shorter period of investigation. These results highlight the importance of plant adaptation/sensitivity under field conditions, and the importance of continuous long-term measurements to explain ozone damage to real-world forests and calculate metrics for ozone-risk assessment.