Sedimentary basins beneath many Antarctic ice streams host substantial volumes of groundwater, which can be exchanged with a "shallow" subglacial hydrological system of till and channelised water. This exchange contributes substantially to basal water budgets, which in turn modulate the flow of ice streams. The geometry of these sedimentary basins is known to be complex, and the groundwater therein has been observed to vary in salinity due to historic seawater intrusion. However, little is known about the hydraulic properties of subglacial sedimentary basins, and the factors controlling groundwater exfiltration and infiltration. We develop a mathematical model for two-dimensional groundwater flow beneath a marine-terminating ice stream on geological timescales, taking into account the effect of seawater intrusion. We find that seawater may become "trapped" in subglacial sedimentary basins, through cycles of grounding line advance and retreat or through "pockets" arising from basin geometry. In addition, we estimate the sedimentary basin permeability which reproduces field observations of groundwater salinity profiles from beneath Whillans Ice Stream in West Antarctica. Exchange of groundwater with the shallow hydrological system is primarily controlled by basin geometry, with groundwater being exfiltrated where the basin becomes shallower and re-infiltrating where it becomes deeper. However, seawater intrusion also has non-negligible effects on this exchange.
{"title":"Groundwater dynamics beneath a marine ice sheet","authors":"Gabriel Cairns, Graham Benham, Ian Hewitt","doi":"arxiv-2409.11848","DOIUrl":"https://doi.org/arxiv-2409.11848","url":null,"abstract":"Sedimentary basins beneath many Antarctic ice streams host substantial\u0000volumes of groundwater, which can be exchanged with a \"shallow\" subglacial\u0000hydrological system of till and channelised water. This exchange contributes\u0000substantially to basal water budgets, which in turn modulate the flow of ice\u0000streams. The geometry of these sedimentary basins is known to be complex, and\u0000the groundwater therein has been observed to vary in salinity due to historic\u0000seawater intrusion. However, little is known about the hydraulic properties of\u0000subglacial sedimentary basins, and the factors controlling groundwater\u0000exfiltration and infiltration. We develop a mathematical model for\u0000two-dimensional groundwater flow beneath a marine-terminating ice stream on\u0000geological timescales, taking into account the effect of seawater intrusion. We\u0000find that seawater may become \"trapped\" in subglacial sedimentary basins,\u0000through cycles of grounding line advance and retreat or through \"pockets\"\u0000arising from basin geometry. In addition, we estimate the sedimentary basin\u0000permeability which reproduces field observations of groundwater salinity\u0000profiles from beneath Whillans Ice Stream in West Antarctica. Exchange of\u0000groundwater with the shallow hydrological system is primarily controlled by\u0000basin geometry, with groundwater being exfiltrated where the basin becomes\u0000shallower and re-infiltrating where it becomes deeper. However, seawater\u0000intrusion also has non-negligible effects on this exchange.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seth Bassetti, Brian Hutchinson, Claudia Tebaldi, Ben Kravitz
Earth System Models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.
{"title":"DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models with 3D Diffusion Models","authors":"Seth Bassetti, Brian Hutchinson, Claudia Tebaldi, Ben Kravitz","doi":"arxiv-2409.11601","DOIUrl":"https://doi.org/arxiv-2409.11601","url":null,"abstract":"Earth System Models (ESMs) are essential for understanding the interaction\u0000between human activities and the Earth's climate. However, the computational\u0000demands of ESMs often limit the number of simulations that can be run,\u0000hindering the robust analysis of risks associated with extreme weather events.\u0000While low-cost climate emulators have emerged as an alternative to emulate ESMs\u0000and enable rapid analysis of future climate, many of these emulators only\u0000provide output on at most a monthly frequency. This temporal resolution is\u0000insufficient for analyzing events that require daily characterization, such as\u0000heat waves or heavy precipitation. We propose using diffusion models, a class\u0000of generative deep learning models, to effectively downscale ESM output from a\u0000monthly to a daily frequency. Trained on a handful of ESM realizations,\u0000reflecting a wide range of radiative forcings, our DiffESM model takes monthly\u0000mean precipitation or temperature as input, and is capable of producing daily\u0000values with statistical characteristics close to ESM output. Combined with a\u0000low-cost emulator providing monthly means, this approach requires only a small\u0000fraction of the computational resources needed to run a large ensemble. We\u0000evaluate model behavior using a number of extreme metrics, showing that DiffESM\u0000closely matches the spatio-temporal behavior of the ESM output it emulates in\u0000terms of the frequency and spatial characteristics of phenomena such as heat\u0000waves, dry spells, or rainfall intensity.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Catastrophic failures have momentous impact in many scientific and technological fields but remain challenging to understand and predict. One key difficulty lies in the burstiness of rupture phenomena, which typically involve a series of progressively shorter quiescent phases punctuated by sudden bursts, rather than a smooth continuous progression. This seemingly erratic pattern challenges the conventional power law assumption of continuous scale invariance. Here, we propose a generalized material failure law based on the log-periodic power law, which better captures the discrete scale invariance inherent in intermittent rupture dynamics. Our method's superiority is demonstrated through testing on 109 historical geohazard events, including landslides, rockbursts, glacier breakoffs, and volcanic eruptions. The results indicate that our method is general and robust, offering significant potential to forecast catastrophic failures.
{"title":"Generalized failure law for landslides, rockbursts, glacier breakoffs, and volcanic eruptions","authors":"Qinghua Lei, Didier Sornette","doi":"arxiv-2409.11455","DOIUrl":"https://doi.org/arxiv-2409.11455","url":null,"abstract":"Catastrophic failures have momentous impact in many scientific and\u0000technological fields but remain challenging to understand and predict. One key\u0000difficulty lies in the burstiness of rupture phenomena, which typically involve\u0000a series of progressively shorter quiescent phases punctuated by sudden bursts,\u0000rather than a smooth continuous progression. This seemingly erratic pattern\u0000challenges the conventional power law assumption of continuous scale\u0000invariance. Here, we propose a generalized material failure law based on the\u0000log-periodic power law, which better captures the discrete scale invariance\u0000inherent in intermittent rupture dynamics. Our method's superiority is\u0000demonstrated through testing on 109 historical geohazard events, including\u0000landslides, rockbursts, glacier breakoffs, and volcanic eruptions. The results\u0000indicate that our method is general and robust, offering significant potential\u0000to forecast catastrophic failures.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"192 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meteorites trace planet formation in the Sun's protoplanetary disk, but they also record the influence of the Sun's birth environment. Whether the Sun formed in a region like Taurus-Auriga with ~10^2 stars, or a region like the Carina Nebula with ~10^6 stars, matters for how large the Sun's disk was, for how long and from how far away it accreted gas from the molecular cloud, and how it acquired radionuclides like 26Al. To provide context for the interpretation of meteoritic data, we review what is known about the Sun's birth environment. Based on an inferred gas disk outer radius ~50-90 AU, radial transport in the disk, and the abundances of noble gases in Jupiter's atmosphere, the Sun's molecular cloud and protoplanetary disk were exposed to an ultraviolet flux G0 ~30-3000 during its birth and first ~10 Myr of evolution. Based on the orbits of Kuiper Belt objects, the Solar System was subsequently exposed to a stellar density ~100 Msol/pc^3 for ~100 Myr, strongly implying formation in a bound cluster. These facts suggest formation in a region like the outskirts of the Orion Nebula, perhaps 2 pc from the center. The protoplanetary disk might have accreted gas for many Myr, but a few x10^5 yr seems more likely. It probably inherited radionuclides from its molecular cloud, enriched by inputs from supernovae and especially Wolf-Rayet star winds, and acquired a typical amount of 26Al.
{"title":"The Sun's Birth Environment: Context for Meteoritics","authors":"Steve Desch, Núria Miret-Roig","doi":"arxiv-2409.10638","DOIUrl":"https://doi.org/arxiv-2409.10638","url":null,"abstract":"Meteorites trace planet formation in the Sun's protoplanetary disk, but they\u0000also record the influence of the Sun's birth environment. Whether the Sun\u0000formed in a region like Taurus-Auriga with ~10^2 stars, or a region like the\u0000Carina Nebula with ~10^6 stars, matters for how large the Sun's disk was, for\u0000how long and from how far away it accreted gas from the molecular cloud, and\u0000how it acquired radionuclides like 26Al. To provide context for the\u0000interpretation of meteoritic data, we review what is known about the Sun's\u0000birth environment. Based on an inferred gas disk outer radius ~50-90 AU, radial\u0000transport in the disk, and the abundances of noble gases in Jupiter's\u0000atmosphere, the Sun's molecular cloud and protoplanetary disk were exposed to\u0000an ultraviolet flux G0 ~30-3000 during its birth and first ~10 Myr of\u0000evolution. Based on the orbits of Kuiper Belt objects, the Solar System was\u0000subsequently exposed to a stellar density ~100 Msol/pc^3 for ~100 Myr, strongly\u0000implying formation in a bound cluster. These facts suggest formation in a\u0000region like the outskirts of the Orion Nebula, perhaps 2 pc from the center.\u0000The protoplanetary disk might have accreted gas for many Myr, but a few x10^5\u0000yr seems more likely. It probably inherited radionuclides from its molecular\u0000cloud, enriched by inputs from supernovae and especially Wolf-Rayet star winds,\u0000and acquired a typical amount of 26Al.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"187 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seamus L. Anderson, Gretchen K. Benedix, Belinda Godel, Romain M. L. Alosius, Daniela Krietsch, Henner Busemann, Colin Maden, Jon M. Friedrich, Lara R. McMonigal, Kees C. Welten, Marc W. Caffee, Robert J. Macke, Seán Cadogan, Dominic H. Ryan, Fred Jourdan, Celia Mayers, Matthias Laubenstein, Richard C. Greenwood, Malcom P. Roberts, Hadrien A. R. Devillepoix, Eleanor K. Sansom, Martin C. Towner, Martin Cupák, Philip A. Bland, Lucy V. Forman, John H. Fairweather, Ashley F. Rogers, Nicholas E. Timms
Over the Nullarbor Plain in South Australia, the Desert Fireball Network detected a fireball on the night of 1 June 2019 (7:30 pm local time), and six weeks later recovered a single meteorite (42 g) named Arpu Kuilpu. This meteorite was then distributed to a consortium of collaborating institutions to be measured and analyzed by a number of methodologies including: SEM-EDS, EPMA, ICP-MS, gamma-ray spectrometry, ideal gas pycnometry, magnetic susceptibility measurement, {mu}CT, optical microscopy, and accelerator and noble gas mass spectrometry techniques. These analyses revealed that Arpu Kuilpu is an unbrecciated H5 ordinary chondrite, with minimal weathering (W0-1) and minimal shock (S2). The olivine and pyroxene mineral compositions (in mol%) are Fa: 19.2 +- 0.2, and Fs: 16.8 +- 0.2, further supporting the H5 type and class. The measured oxygen isotopes are also consistent with an H chondrite ({delta}17O = 2.904 +- 0.177; {delta}18O = 4.163 +- 0.336; {Delta}17O = 0.740 +- 0.002). Ideal gas pycnometry measured bulk and grain densities of 3.66 +- 0.02 and 3.77 +- 0.02 g cm-3, respectively, yielding a porosity of 3.0 % +- 0.7. The magnetic susceptibility of this meteorite is log X = 5.16 +- 0.08. The most recent impact-related heating event experienced by Arpu Kuilpu was measured by 40Ar/39Ar chronology to be 4467 +- 16 Ma, while the cosmic ray exposure age is estimated to be between 6-8 Ma. The noble gas isotopes, radionuclides, and fireball observations all indicate that Arpu Kuilpu's meteoroid was quite small (maximum radius of 10 cm, though more likely between 1-5 cm). Although this meteorite is a rather ordinary ordinary chondrite, its prior orbit resembled that of a Jupiter Family Comet (JFC) further lending support to the assertion that many cm- to m-sized objects on JFC orbits are asteroidal rather than cometary in origin.
{"title":"The Arpu Kuilpu Meteorite: In-depth characterization of an H5 chondrite delivered from a Jupiter Family Comet orbit","authors":"Seamus L. Anderson, Gretchen K. Benedix, Belinda Godel, Romain M. L. Alosius, Daniela Krietsch, Henner Busemann, Colin Maden, Jon M. Friedrich, Lara R. McMonigal, Kees C. Welten, Marc W. Caffee, Robert J. Macke, Seán Cadogan, Dominic H. Ryan, Fred Jourdan, Celia Mayers, Matthias Laubenstein, Richard C. Greenwood, Malcom P. Roberts, Hadrien A. R. Devillepoix, Eleanor K. Sansom, Martin C. Towner, Martin Cupák, Philip A. Bland, Lucy V. Forman, John H. Fairweather, Ashley F. Rogers, Nicholas E. Timms","doi":"arxiv-2409.10382","DOIUrl":"https://doi.org/arxiv-2409.10382","url":null,"abstract":"Over the Nullarbor Plain in South Australia, the Desert Fireball Network\u0000detected a fireball on the night of 1 June 2019 (7:30 pm local time), and six\u0000weeks later recovered a single meteorite (42 g) named Arpu Kuilpu. This\u0000meteorite was then distributed to a consortium of collaborating institutions to\u0000be measured and analyzed by a number of methodologies including: SEM-EDS, EPMA,\u0000ICP-MS, gamma-ray spectrometry, ideal gas pycnometry, magnetic susceptibility\u0000measurement, {mu}CT, optical microscopy, and accelerator and noble gas mass\u0000spectrometry techniques. These analyses revealed that Arpu Kuilpu is an\u0000unbrecciated H5 ordinary chondrite, with minimal weathering (W0-1) and minimal\u0000shock (S2). The olivine and pyroxene mineral compositions (in mol%) are Fa:\u000019.2 +- 0.2, and Fs: 16.8 +- 0.2, further supporting the H5 type and class. The\u0000measured oxygen isotopes are also consistent with an H chondrite ({delta}17O =\u00002.904 +- 0.177; {delta}18O = 4.163 +- 0.336; {Delta}17O = 0.740 +- 0.002).\u0000Ideal gas pycnometry measured bulk and grain densities of 3.66 +- 0.02 and 3.77\u0000+- 0.02 g cm-3, respectively, yielding a porosity of 3.0 % +- 0.7. The magnetic\u0000susceptibility of this meteorite is log X = 5.16 +- 0.08. The most recent\u0000impact-related heating event experienced by Arpu Kuilpu was measured by\u000040Ar/39Ar chronology to be 4467 +- 16 Ma, while the cosmic ray exposure age is\u0000estimated to be between 6-8 Ma. The noble gas isotopes, radionuclides, and\u0000fireball observations all indicate that Arpu Kuilpu's meteoroid was quite small\u0000(maximum radius of 10 cm, though more likely between 1-5 cm). Although this\u0000meteorite is a rather ordinary ordinary chondrite, its prior orbit resembled\u0000that of a Jupiter Family Comet (JFC) further lending support to the assertion\u0000that many cm- to m-sized objects on JFC orbits are asteroidal rather than\u0000cometary in origin.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spatially 3-dimensional seismic full waveform inversion (3D FWI) is a highly nonlinear and computationally demanding inverse problem that constructs 3D subsurface seismic velocity structures using seismic waveform data. To characterise non-uniqueness in the solutions we demonstrate Bayesian 3D FWI using an efficient method called physically structured variational inference applied to 3D acoustic Bayesian FWI. The results provide reasonable posterior uncertainty estimates, at a computational cost that is only an order of magnitude greater than that of standard, deterministic FWI. Furthermore, we deploy variational prior replacement to calculate Bayesian solutions corresponding to different classes of prior information at low additional cost, and analyse those prior hypotheses by constructing Bayesian L-curves. This reveals the sensitivity of the inversion process to different prior assumptions. Thus we show that fully probabilistic 3D FWI can be performed at a cost that may be practical in small FWI problems, and can be used to test different prior hypotheses.
空间三维地震全波形反演（3D FWI）是一个高度非线性和计算要求极高的反演问题，它利用地震波形数据构建三维次表层地震速度结构。为了描述解的非唯一性，我们演示了贝叶斯三维 FWI，将一种称为物理结构变异推理的高效方法应用于三维声学贝叶斯 FWI。结果提供了合理的后验不确定性估计，计算成本仅比标准的确定性 FWI 高一个数量级。此外，我们还采用变异先验替换法，以较低的额外成本计算出与不同类别先验信息相对应的贝叶斯解，并通过构建贝叶斯 L 曲线对这些先验假设进行分析。这揭示了反演过程对不同先验假设的敏感性。因此，我们证明了全概率三维全维反演可以在小型全维反演问题中以实用的成本进行，并可用于测试不同的先验假设。
{"title":"Efficient 3D Bayesian Full Waveform Inversion and Analysis of Prior Hypotheses","authors":"Xuebin Zhao, Andrew Curtis","doi":"arxiv-2409.09746","DOIUrl":"https://doi.org/arxiv-2409.09746","url":null,"abstract":"Spatially 3-dimensional seismic full waveform inversion (3D FWI) is a highly\u0000nonlinear and computationally demanding inverse problem that constructs 3D\u0000subsurface seismic velocity structures using seismic waveform data. To\u0000characterise non-uniqueness in the solutions we demonstrate Bayesian 3D FWI\u0000using an efficient method called physically structured variational inference\u0000applied to 3D acoustic Bayesian FWI. The results provide reasonable posterior\u0000uncertainty estimates, at a computational cost that is only an order of\u0000magnitude greater than that of standard, deterministic FWI. Furthermore, we\u0000deploy variational prior replacement to calculate Bayesian solutions\u0000corresponding to different classes of prior information at low additional cost,\u0000and analyse those prior hypotheses by constructing Bayesian L-curves. This\u0000reveals the sensitivity of the inversion process to different prior\u0000assumptions. Thus we show that fully probabilistic 3D FWI can be performed at a\u0000cost that may be practical in small FWI problems, and can be used to test\u0000different prior hypotheses.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jean-Baptiste Boulé, Jean de Bremond d'Ars, Vincent Courtillot, Marc Gèze, Dominique Gibert, Jean-Louis Le Mouël, Fernando Lopes, Alexis Maineult, Pierpaolo Zuddas
What is certain is that surface temperatures around the globe vary considerably, regardless of the time scales or underlying causes. Since 1850, we have observed an average increase in global surface temperature anomalies of 1.2$^{circ}$ and a median increase of 0.7$^{circ}$: this overall difference masks significant regional differences. Nearly 60% of the world's population now lives in urban areas, where vegetation cover has been significantly reduced, despite the paradoxical fact that vegetation plays an important role in regulating the thermal environment (textit{eg} through the shading provided by tree canopies). Continuous electrical and thermal measurements of trees in a Parisian grove (France) show and quantify that canopies are not the only protectors against heat waves; we must also consider the role of tree trunks. It is clear that these trunks probably regulate themselves, possibly by modulating the uptake of groundwater, whose geothermal stability is well established at a depth of just one meter. This quantitative observation should not be overlooked in the urban planning of our cities.
{"title":"On the mechanism of thermal self-regulation of trees: a kind of homeothermic observation","authors":"Jean-Baptiste Boulé, Jean de Bremond d'Ars, Vincent Courtillot, Marc Gèze, Dominique Gibert, Jean-Louis Le Mouël, Fernando Lopes, Alexis Maineult, Pierpaolo Zuddas","doi":"arxiv-2409.09765","DOIUrl":"https://doi.org/arxiv-2409.09765","url":null,"abstract":"What is certain is that surface temperatures around the globe vary\u0000considerably, regardless of the time scales or underlying causes. Since 1850,\u0000we have observed an average increase in global surface temperature anomalies of\u00001.2$^{circ}$ and a median increase of 0.7$^{circ}$: this overall difference\u0000masks significant regional differences. Nearly 60% of the world's population\u0000now lives in urban areas, where vegetation cover has been significantly\u0000reduced, despite the paradoxical fact that vegetation plays an important role\u0000in regulating the thermal environment (textit{eg} through the shading provided\u0000by tree canopies). Continuous electrical and thermal measurements of trees in a\u0000Parisian grove (France) show and quantify that canopies are not the only\u0000protectors against heat waves; we must also consider the role of tree trunks.\u0000It is clear that these trunks probably regulate themselves, possibly by\u0000modulating the uptake of groundwater, whose geothermal stability is well\u0000established at a depth of just one meter. This quantitative observation should\u0000not be overlooked in the urban planning of our cities.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jing Sun, Song Hou, Vetle Vinje, Gordon Poole, Leiv-J Gelius
To streamline fast-track processing of large data volumes, we have developed a deep learning approach to deblend seismic data in the shot domain based on a practical strategy for generating high-quality training data along with a list of data conditioning techniques to improve performance of the data-driven model. We make use of unblended shot gathers acquired at the end of each sail line, to which the access requires no additional time or labor costs beyond the blended acquisition. By manually blending these data we obtain training data with good control of the ground truth and fully adapted to the given survey. Furthermore, we train a deep neural network using multi-channel inputs that include adjacent blended shot gathers as additional channels. The prediction of the blending noise is added in as a related and auxiliary task with the main task of the network being the prediction of the primary-source events. Blending noise in the ground truth is scaled down during the training and validation process due to its excessively strong amplitudes. As part of the process, the to-be-deblended shot gathers are aligned by the blending noise. Implementation on field blended-by-acquisition data demonstrates that introducing the suggested data conditioning steps can considerably reduce the leakage of primary-source events in the deep part of the blended section. The complete proposed approach performs almost as well as a conventional algorithm in the shallow section and shows great advantage in efficiency. It performs slightly worse for larger traveltimes, but still removes the blending noise efficiently.
{"title":"Deep learning-based shot-domain seismic deblending","authors":"Jing Sun, Song Hou, Vetle Vinje, Gordon Poole, Leiv-J Gelius","doi":"arxiv-2409.08602","DOIUrl":"https://doi.org/arxiv-2409.08602","url":null,"abstract":"To streamline fast-track processing of large data volumes, we have developed\u0000a deep learning approach to deblend seismic data in the shot domain based on a\u0000practical strategy for generating high-quality training data along with a list\u0000of data conditioning techniques to improve performance of the data-driven\u0000model. We make use of unblended shot gathers acquired at the end of each sail\u0000line, to which the access requires no additional time or labor costs beyond the\u0000blended acquisition. By manually blending these data we obtain training data\u0000with good control of the ground truth and fully adapted to the given survey.\u0000Furthermore, we train a deep neural network using multi-channel inputs that\u0000include adjacent blended shot gathers as additional channels. The prediction of\u0000the blending noise is added in as a related and auxiliary task with the main\u0000task of the network being the prediction of the primary-source events. Blending\u0000noise in the ground truth is scaled down during the training and validation\u0000process due to its excessively strong amplitudes. As part of the process, the\u0000to-be-deblended shot gathers are aligned by the blending noise. Implementation\u0000on field blended-by-acquisition data demonstrates that introducing the\u0000suggested data conditioning steps can considerably reduce the leakage of\u0000primary-source events in the deep part of the blended section. The complete\u0000proposed approach performs almost as well as a conventional algorithm in the\u0000shallow section and shows great advantage in efficiency. It performs slightly\u0000worse for larger traveltimes, but still removes the blending noise efficiently.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sigmund Slang, Jing Sun, Thomas Elboth, Steven McDonald, Leiv-J. Gelius
Processing marine seismic data is computationally demanding and consists of multiple time-consuming steps. Neural network based processing can, in theory, significantly reduce processing time and has the potential to change the way seismic processing is done. In this paper we are using deep convolutional neural networks (CNNs) to remove seismic interference noise and to deblend seismic data. To train such networks, a significant amount of computational memory is needed since a single shot gather consists of more than 106 data samples. Preliminary results are promising both for denoising and deblending. However, we also observed that the results are affected by the signal-to-noise ratio (SnR). Moving to common channel domain is a way of breaking the coherency of the noise while also reducing the input volume size. This makes it easier for the network to distinguish between signal and noise. It also increases the efficiency of the GPU memory usage by enabling better utilization of multi core processing. Deblending in common channel domain with the use of a CNN yields relatively good results and is an improvement compared to shot domain.
{"title":"Using Convolutional Neural Networks for Denoising and Deblending of Marine Seismic Data","authors":"Sigmund Slang, Jing Sun, Thomas Elboth, Steven McDonald, Leiv-J. Gelius","doi":"arxiv-2409.08603","DOIUrl":"https://doi.org/arxiv-2409.08603","url":null,"abstract":"Processing marine seismic data is computationally demanding and consists of\u0000multiple time-consuming steps. Neural network based processing can, in theory,\u0000significantly reduce processing time and has the potential to change the way\u0000seismic processing is done. In this paper we are using deep convolutional\u0000neural networks (CNNs) to remove seismic interference noise and to deblend\u0000seismic data. To train such networks, a significant amount of computational\u0000memory is needed since a single shot gather consists of more than 106 data\u0000samples. Preliminary results are promising both for denoising and deblending.\u0000However, we also observed that the results are affected by the signal-to-noise\u0000ratio (SnR). Moving to common channel domain is a way of breaking the coherency\u0000of the noise while also reducing the input volume size. This makes it easier\u0000for the network to distinguish between signal and noise. It also increases the\u0000efficiency of the GPU memory usage by enabling better utilization of multi core\u0000processing. Deblending in common channel domain with the use of a CNN yields\u0000relatively good results and is an improvement compared to shot domain.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elishevah van Kooten, Adrian Brearley, Denton Ebel, Conel Alexander, Marina Gemma, Dominik Hezel
Chondritic components such as chondrules and matrix are the key time capsules that can help us understand the evolution and dynamics of the protoplanetary disk from which the Solar System originated. Knowledge of where and how these components formed and to what extent they were transported in the gaseous disk provides major constraints to astrophysical models that investigate planet formation. Here, we explore whether chondrules and matrix are genetically related to each other and formed from single reservoirs per chondrite group or if every chondrite represents a unique proportion of components transported from a small number of formation reservoirs in the disk. These static versus dynamic disk interpretations of cosmochemical data have profound implications for the accretion history of the planets in the Solar System. To fully understand the relationship between chondrules and matrix and their potential complementarity, we dive into the petrological nature and origin of matrix, the chemical and isotopic compositions of chondrules and matrix and evaluate these data considering the effect of secondary alteration observed in chondrites and the potential complexity of chondrule formation. Even though we, the authors, have used different datasets and arrived at differing interpretations of chondrule-matrix relationships in the past, this review provides clarity on the existing data and has given us new directions towards future research that can resolve the complementarity debate.
{"title":"Is there a genetic relationship between chondrules and matrix?","authors":"Elishevah van Kooten, Adrian Brearley, Denton Ebel, Conel Alexander, Marina Gemma, Dominik Hezel","doi":"arxiv-2409.08662","DOIUrl":"https://doi.org/arxiv-2409.08662","url":null,"abstract":"Chondritic components such as chondrules and matrix are the key time capsules\u0000that can help us understand the evolution and dynamics of the protoplanetary\u0000disk from which the Solar System originated. Knowledge of where and how these\u0000components formed and to what extent they were transported in the gaseous disk\u0000provides major constraints to astrophysical models that investigate planet\u0000formation. Here, we explore whether chondrules and matrix are genetically\u0000related to each other and formed from single reservoirs per chondrite group or\u0000if every chondrite represents a unique proportion of components transported\u0000from a small number of formation reservoirs in the disk. These static versus\u0000dynamic disk interpretations of cosmochemical data have profound implications\u0000for the accretion history of the planets in the Solar System. To fully\u0000understand the relationship between chondrules and matrix and their potential\u0000complementarity, we dive into the petrological nature and origin of matrix, the\u0000chemical and isotopic compositions of chondrules and matrix and evaluate these\u0000data considering the effect of secondary alteration observed in chondrites and\u0000the potential complexity of chondrule formation. Even though we, the authors,\u0000have used different datasets and arrived at differing interpretations of\u0000chondrule-matrix relationships in the past, this review provides clarity on the\u0000existing data and has given us new directions towards future research that can\u0000resolve the complementarity debate.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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