Mapping Earth's deepest secrets

doi:10.1126/science.abc3134

GSTDTAP > 气候变化

DOI	10.1126/science.abc3134
	Mapping Earth's deepest secrets
	Meghan S. Miller
	2020-06-12
发表期刊	Science
出版年	2020
英文摘要	Deep within Earth's interior, at ∼2900 km beneath the surface, lies the boundary between the solid silicate rock mantle and the liquid iron-nickel alloy core (the core-mantle boundary). Geophysicists have studied the complex thermal and chemical dynamics that take place in this boundary layer. In the early 20th century, Gutenberg investigated the structure of the lowermost region, or base, of the mantle by recording with only a few seismograms from a small number of large-magnitude earthquakes that occurred thousands of kilometers away ([ 1 ][1]). The structure of the rocks just above the core-mantle boundary—designated as D″ by Jeffreys in 1939 ([ 2 ][2])—forms a distinct layer with surprising complexity. Now, on page 1223 of this issue, Kim et al. ([ 3 ][3]) describe new structural heterogeneities in the lowermost mantle with the use of a learning algorithm that does not require any a priori knowledge of Earth. Research over the past ∼100 years has yielded major improvements in scientists' understanding of the lowermost mantle. However, the velocity discontinuities (which represent the boundaries between layers within the deep Earth) detected by the pioneers in seismology with just a small number of measurements remain as fundamental constraints of Earth's structure. Thanks to community experiments such as EarthScope ([ 4 ][4]), the relatively disparate and important observations of the lowermost mantle have increased in number and location with the exponential growth in seismic data collected over the past couple of decades. Seismologists have used seismograms of earthquakes recorded by arrays of distant seismometers to image the deep-mantle structures ([ 5 ][5]). The development of methods, such as those used by Kim et al. , to process and analyze increasingly large datasets are crucial to improving geophysicists' knowledge of Earth's structure, which is central to understanding the evolution of Earth. Global tomographic models at lower mantle depths, such as S40RTS (see the figure) ([ 6 ][6]), were generated from low-resolution (hundred- to thousand-kilometers-cale) images of Earth's structure; such models were hampered by the use of only long-wavelength seismic waves and the type of imaging method. Despite the limitations, these global models illustrate the remarkable complexity of the lowermost mantle, which suggests that this region is one of Earth's most important thermal and structural zones. This part of Earth's interior includes large low-shear-velocity provinces (LLSVPs) and ultralow-velocity zones (ULVZs), which have been linked to hotspot volcanoes and large igneous provinces at Earth's surface ([ 7 ][7], [ 8 ][8]). The extent and edges of structures that cluster primarily at the edges of LLSVPs [such as the African LLSVP ([ 9 ][9]), the Pacific LLSVP ([ 10 ][10]), and in particular the small-scale ULVZs ([ 5 ][5], [ 11 ][11])] traditionally have been mapped by analyzing individual seismic waveforms that sample the deepest mantle. ![Figure][12] Shaking things up at the center of Earth Seismic-wave scattering can pinpoint structures beneath Earth's surface, as shown in this tomographic model of Earth and its lower-mantle depths near the core-mantle boundary (center circle). The red-orange region indicates the Pacific large low-shear-velocity province (LLSVP). Green symbols indicate deep-focus (>150 km depth) earthquakes that occurred between 2000 and 2018 and were recorded at distant seismometers (red symbols). The seismograms were analyzed by Kim et al. ULVZ, ultralow velocity zone. GRAPHIC: ADAPTED BY V. ALTOUNIAN/ SCIENCE FROM NATIONAL COMPUTATIONAL INFRASTRUCTURE AUSTRALIA VIZLAB Only certain seismic phases are sensitive to the LLSVP and ULVZ structures; these include seismic waves that are diffracted off the core-mantle boundary, such as S diff ([ 6 ][6]) and P diff ([ 12 ][13], [ 13 ][14]), or are reflected at the core-mantle boundary, such as ScS or ScP ([ 13 ][14]). The waveform distortion of these seismic phases, paired with arrival-time anomalies relative to a preexisting model, allows for inference about the detailed heterogeneities of the rocks near the core-mantle boundary and provide key information regarding the composition and dynamics of the lower mantle. However, after selecting data on the basis of signal-to-noise ratios and sparse earthquake and seismometer (source-receiver) geometries, the seismic waveforms often are analyzed manually and then compared with either one-dimensional (1D) models or 3D models (from tomographic imaging) of Earth's structure. Although there are millions of earthquake records available from seismic networks across the globe, it remains a challenge to analyze and quantitively assess individual seismic waveform data and extract the desired information. The ability to detect and analyze subtle changes in waveforms is important for providing constraints on the physical parameters of deep Earth. To this end, Kim et al. used a man ifold algorithm called “the Sequencer” to investigate a relatively large S diff waveform dataset; the Sequencer enabled a data-driven analysis of the deep mantle without any expectations or prior knowledge about its structure. This unsupervised, graph-based algorithm orders the waveforms to minimize dissimilarities and can reveal trends without an Earth model. The analysis by Kim et al. detected subtle changes in seismic waveforms from earthquakes that occurred in Asia and Oceania and were recorded in the Americas and mapped their origins across a large geographic region beneath the Pacific Ocean. The new study also identified more broadly distributed ULVZs at the base of the mantle north of Hawaii and a previously undetected anomaly in the deepest mantle beneath the south-central Pacific. This type of analysis could be applied to various seismic phases such as ScS, ScP , and P diff and a range of others that are of higher frequency, which would provide a new, higher-resolution, and more comprehensive mapping of the structural heterogeneity of deep Earth. Knowledge of these physical properties and of inferred chemical and thermal structures is essential to determining whether partial melt of the rocks exists at the core-mantle boundary, whether distinct materials accumulate or stabilize in particular regions, whether some volcanoes have origins in deep Earth, and, last, what the compositional variations are in the lowermost mantle. 1. [↵][15]1. B. Gutenberg , Nachr. Ges. Wiss. Goettingen Math. Phys. Kl. 1914, 125 (1914). [OpenUrl][16] 2. [↵][17]1. H. Jeffreys , Mon. Not. R. Astron. Soc. Geophys. 4 (suppl.), 498 (1939). [OpenUrl][18] 3. [↵][19]1. D. Kim et al ., Science 368, 1223 (2020). [OpenUrl][20][Abstract/FREE Full Text][21] 4. [↵][22]EarthScope Working Group, Eos 81, 122 (2000). [OpenUrl][23] 5. [↵][24]1. S. Yu, 2. E. J. Garnero , Geochem. Geophys. Geosyst. 19, 396 (2018). [OpenUrl][25][CrossRef][26] 6. [↵][27]1. J. Ritsema et al ., Geophys. J. Int. 184, 1223 (2011). [OpenUrl][28][CrossRef][29][GeoRef][30] 7. [↵][31]1. K. 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领域	气候变化 ; 资源环境
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文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/274457
专题	气候变化资源环境科学
推荐引用方式 GB/T 7714	Meghan S. Miller. Mapping Earth's deepest secrets[J]. Science,2020.
APA	Meghan S. Miller.(2020).Mapping Earth's deepest secrets.Science.
MLA	Meghan S. Miller."Mapping Earth's deepest secrets".Science (2020).