Klyuchevskoy Volcano. Bibliography
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Records: 516
Girina O.A., Melnikov D.V., Manevich A.G., Nuzhdaev A.A., Romanova I.M., Loupian E.A., Sorokin A.A. The 2020 Activity of Kamchatkan Volcanoes and Danger to Aviation // EGU General Assembly 2021. 2021. https://doi.org/10.5194/egusphere-egu21-1448.
Girina O.A., Ushakov S.V., Malik N.A., Manevich A.G., Melnikov D.V., Nuzhdaev A.A., Demyanchuk Yu.V., Kotenko L.V. The active volcanoes of Kamchatka and Paramushir Island, North Kurils in 2007 // Journal of Volcanology and Seismology. 2009. Vol. 3. № 1. P. 1-17. https://doi.org/10.1134/S0742046309010011.
Eight strong eruptions of four Kamchatka volcanoes (Bezymyannyi, Klyuchevskoi, Shiveluch, and Karymskii) and Chikurachki Volcano on Paramushir Island, North Kurils took place in 2007. In addition, an explosive event occurred on Mutnovskii Volcano and increased fumarole activity was recorded on Avacha and Gorelyi volcanoes in Kamchatka and Ebeko Volcano on Paramushir Island, North Kurils. Thanks to close cooperation with colleagues involved in the Kamchatkan Volcanic Eruption Response Team (KVERT) project from the Elizovo Airport Meteorological Center and volcanic ash advisory centers in Tokyo, Anchorage, and Washington (Tokyo VAAC, Anchorage VAAC, and Washington VAAC), all necessary precautions were taken for flight safety near Kamchatka.
Global Volcanism Program. Volcanoes of the World, v. 4.11.0 (08 Jun 2022). 2013. doi: 10.5479/si.GVP.VOTW4-2013.
The Volcanoes of the World database is a catalog of Holocene and Pleistocene volcanoes, and eruptions from the past 12,000 years.
Gordeev E.I., Girina O.A., Lupyan E.A., Sorokin A.A., Kramareva L.S., Efremov V.Yu., Kashnitskii A.V., Uvarov I.A., Burtsev M.A., Romanova I.M., Mel’nikov D.V., Manevich A.G., Korolev S.P., Verkhoturov A.L. The VolSatView information system for Monitoring the Volcanic Activity in Kamchatka and on the Kuril Islands // Journal of Volcanology and Seismology. 2016. Vol. 10. № 6. P. 382-394. https://doi.org/10.1134/S074204631606004X.
Kamchatka and the Kuril Islands are home to 36 active volcanoes with yearly explosive eruptions that eject ash to heights of 8 to 15 km above sea level, posing hazards to jet planes. In order to reduce the risk of planes colliding with ash clouds in the north Pacific, the KVERT team affiliated with the Institute of Volcanology and Seismology of the Far East Branch of the Russian Academy of Sciences (IV&S FEB RAS) has conducted daily satellite-based monitoring of Kamchatka volcanoes since 2002. Specialists at the IV&S FEB RAS, Space Research Institute of the Russian Academy of Sciences (SRI RAS), the Computing Center of the Far East Branch of the Russian Academy of Sciences (CC FEB RAS), and the Far East Planeta Center of Space Hydrometeorology Research (FEPC SHR) have developed, introduced into practice, and were continuing to refine the VolSatView information system for Monitoring of Volcanic Activity in Kamchatka and on the Kuril Islands during the 2011–2015 period. This system enables integrated processing of various satellite data, as well as of weather and land-based information for continuous monitoring and investigation of volcanic activity in the Kuril–Kamchatka region. No other information system worldwide offers the abilities that the Vol-SatView has for studies of volcanoes. This paper shows the main abilities of the application of VolSatView for routine monitoring and retrospective analysis of volcanic activity in Kamchatka and on the Kuril Islands.
Gordeev E.I., Girina O.A., Manevich A.G., Melnikov D.V., Nuzhdaev A.A. 2015-2016 Activity of Kamchatkan and Northern Kuriles Volcanoes (Russia) and Danger to Aviation // 9th Biennial Workshop on Japan-Kamchatka-Alaska Subduction Processes (JKASP 2016). Fairbanks, Alaska: UAF. 2016. P. 93-94.
Gordeychik Boris, Churikova Tatiana, Kronz Andreas, Simakin Alexander, Wörner Gerhard First data on magma ascent and residence times retrieved from Fe-Mg and trace element zonation in olivine phenocrysts from Kamchatka basalts // Geophysical Research Abstracts. 2016. Vol. 18. P. EGU2016-12839.
Compositional zonation in olivine phenocrysts and diffusion modelling have been used in the last ten years to estimate magma residence times and the duration of magma ascent. The fundamental assumption is that mixing with newly injected magma into a reservoir triggers diffusional exchange between mafic olivine crystals and more evolved magma and that this magma mixing eventually triggers eruption. If depth of mixing is known, this translates to ascent rates of magmas to the surface. We applied this approach to a series of different arc basalt lavas from Kamchatka to constrain the rates of magma ascent and magma resident in what is one of the most active subduction zones in the world that is also dominated by an abundance of unusually mafic magmas. Our sample collection cover the principal modes of arc magmatism in Kamchatka: from different volcanic complexes (stratovolcano, dikes, summit eruptions, monogenetic cones), of different age (from Late-Pleistocene to Holocene and recent eruptions), from different magmatic regimes (long-lived volcanoes vs. monogenetic eruptions) and different major element composition (from basalt to basaltic andesite of different geochemical character including LILE enrichments). We analyzed and modelled zonation profiles for a range of elements with different diffusivities (e.g. Mg-Fe, Ca, Ni, Mn, Cr) to assess the role of variable diffusivities as a function of major and trace elements in the olivines from different P-T conditions. First data were obtained on samples from the Klyuchevskoy, Shiveluch and Tolbachik, including recent most eruption in 2012/2013. These data show that for some samples the zonation patterns are much more complex than is usually observed: high-Mg olivines at different volcanoes have very different zonation patterns, including normally, reversely zoned grains or even show highly complex repetitive zonation that indicate large compositional changes in the surrounding magma at very short time scales (years). Thus in some Kamchatka basalts, we observe unusual Mg-Fe zonations that are linked to complex mixing, possibly resorption and subsequent crystal growth processes that are generally not preserved due to fast diffusion of Mg-Fe. Based on a first assessment of our measured profiles, the values for diffusion times in Fo-rich olivines (88 to 92% Fo) vary from only a few months to years and thus magma ascent from deep magma sources must have been fast.
Gorelchik V.I., Levina V.I. Space-Time and Dinamic Characteristics of Earthquakes Associated with the 1974 Eruption of Klyuchevskoi // Volcanology and Seismology. 1989. Vol. 7. № 6. P. 943-974.
Gorshkov G.S., Kirsanov I.T. Eruption of Piip Crater (Kamchatka) // Bulletin Volcanologique. 1968. Vol. 32. Vol. 1. P. 269-282. doi: 10.1007/BF02596594.
Guschenko I.I. Volcanoes of the World: Eruption Cycles // Volcanology and Seismology. 1988. Vol. 7. № 3. P. 189-218.
Gusev A.A., Ponomareva V.V., Braitseva O.A., Melekestsev I.V., Sulerzhitsky L.D. Great explosive eruptions on Kamchatka during the last 10,000 years: Self-similar irregularity of the output of volcanic products // Journal of Geophysical Research. 2003. Vol. 108. № B2. doi:10.1029/2001JB000312.
Temporal irregularity of the output of volcanic material is studied for the sequence of large (V ≥ 0.5 km3, N = 29) explosive eruptions on Kamchatka during the last 10,000 years. Informally, volcanic productivity looks episodic, and dates of eruptions cluster. To investigate the probable self-similar clustering behavior of eruption times, we determine correlation dimension Dc. For intervals between events 800 and 10,000 years, Dc ≈ 1 (no self-similar clustering). However, for shorter delays, Dc = 0.71, and the significance level for the hypothesis Dc < 1 is 2.5%. For the temporal structure of the output of volcanic products (i.e., for the sequence of variable-weight points), a self-similar “episodic” behavior holds over the entire range of delays 100–10,000 years, with Dc = 0.67 (Dc < 1 at 3.4% significance). This behavior is produced partly by the mentioned common clustering of event dates, and partly by another specific property of the event sequence, that we call “order clustering”. This kind of clustering is a property of a time-ordered list of eruptions, and is manifested as the tendency of the largest eruptions (as opposed to smaller ones) to be close neighbors in this list. Another statistical technique, of “rescaled range” (R/S), confirms these results. Similar but weaker-expressed behavior was also found for two other data sets: historical Kamchatka eruptions and acid layers in Greenland ice column. The episodic multiscaled mode of the output of volcanic material may be a characteristic property of a sequence of eruptions in an island arc, with important consequences for climate forcing by volcanic aerosol, and volcanic hazard.