bluuebunny/crossref_metadata_2025_split huggingface dataset:
Network‐Based Detection and Classification of Seismovolcanic Tremors: Example From the Klyuchevskoy Volcanic Group in Kamchatka
Authors: Soubestre Jean , Shapiro Nikolai M. , Seydoux Léonard , de Rosny Julien , Droznin Dmitry V. , Droznina Svetlana Ya. , Senyukov Sergey L. , Gordeev Evgeniy I. 
Published: January 2018

AbstractWe develop a network‐based method for detecting and classifying seismovolcanic tremors. The proposed approach exploits the coherence of tremor signals across the network that is estimated from the array covariance matrix. The method is applied to four and a half years of continuous seismic data recorded by 19 permanent seismic stations in the vicinity of the Klyuchevskoy volcanic group in Kamchatka (Russia), where five volcanoes were erupting during the considered time period. We compute and analyze daily covariance matrices together with their eigenvalues and eigenvectors. As a first step, most coherent signals corresponding to dominating tremor sources are detected based on the width of the covariance matrix eigenvalues distribution. Thus, volcanic tremors of the two volcanoes known as most active during the considered period, Klyuchevskoy and Tolbachik, are efficiently detected. As a next step, we consider the daily array covariance matrix's first eigenvector. Our main hypothesis is that these eigenvectors represent the principal components of the daily seismic wavefield and, for days with tremor activity, characterize dominant tremor sources. Those daily first eigenvectors, which can be used as network‐based fingerprints of tremor sources, are then grouped into clusters using correlation coefficient as a measure of the vector similarity. As a result, we identify seven clusters associated with different periods of activity of four volcanoes: Tolbachik, Klyuchevskoy, Shiveluch, and Kizimen. The developed method does not require a priori knowledge and is fully automatic; and the database of the network‐based tremor fingerprints can be continuously enriched with newly available data.
Inverse Problems in Geodynamics Using Machine Learning Algorithms
Authors: Shahnas M. H. , Yuen D. A. , Pysklywec R. N. 
Published: January 2018

AbstractDuring the past few decades numerical studies have been widely employed to explore the style of circulation and mixing in the mantle of Earth and other planets. However, in geodynamical studies there are many properties from mineral physics, geochemistry, and petrology in these numerical models. Machine learning, as a computational statistic‐related technique and a subfield of artificial intelligence, has rapidly emerged recently in many fields of sciences and engineering. We focus here on the application of supervised machine learning (SML) algorithms in predictions of mantle flow processes. Specifically, we emphasize on estimating mantle properties by employing machine learning techniques in solving an inverse problem. Using snapshots of numerical convection models as training samples, we enable machine learning models to determine the magnitude of the spin transition‐induced density anomalies that can cause flow stagnation at midmantle depths. Employing support vector machine algorithms, we show that SML techniques can successfully predict the magnitude of mantle density anomalies and can also be used in characterizing mantle flow patterns. The technique can be extended to more complex geodynamic problems in mantle dynamics by employing deep learning algorithms for putting constraints on properties such as viscosity, elastic parameters, and the nature of thermal and chemical anomalies.
The Dallas‐Fort Worth Airport Earthquake Sequence: Seismicity Beyond Injection Period
Authors: Ogwari Paul O. , DeShon Heather R. , Hornbach Matthew J. 
Published: January 2018

AbstractThe 2008 Dallas‐Fort Worth Airport earthquakes mark the beginning of seismicity rate changes linked to oil and gas operations in the central United States. We assess the spatial and temporal evolution of the sequence through December 2015 using template‐based waveform correlation and relative location methods. We locate ~400 earthquakes spanning 2008–2015 along a basement fault mapped as the Airport fault. The sequence exhibits temporally variable b values, and small‐magnitude (m < 3.4) earthquakes spread northeast along strike over time. Pore pressure diffusion models indicate that the high‐volume brine injection well located within 1 km of the 2008 earthquakes, although only operating from September 2008 to August 2009, contributes most significantly to long‐term pressure perturbations, and hence stress changes, along the fault; a second long‐operating, low‐volume injector located 10 km north causes insufficient pressure changes. High‐volume injection for a short time period near a critically stressed fault can induce long‐lasting seismicity.
Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations
Authors: Hutter Nils , Losch Martin , Menemenlis Dimitris 
Published: January 2018

AbstractSea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.
Flow Patterns in the Eastern Chukchi Sea: 2010–2015
Authors: Stabeno Phyllis , Kachel Nancy , Ladd Carol , Woodgate Rebecca 
Published: January 2018

AbstractFrom 2010 to 2015, moorings were deployed on the northern Chukchi Sea at nine sites. Deployment duration varied from 5 years at a site off Icy Cape to 1 year at a site north of Hanna Shoal. In addition, 39 satellite‐tracked drifters (drogue depth 25–30 m) were deployed in the region during 2012–2015. The goals of this manuscript are to describe currents in the Chukchi Sea and their relationship to ice and winds. The north‐south pressure gradient results in, on average, a northward flow over the Chukchi shelf, which is modified by local winds. The volume transport near Icy Cape (∼0.4 Sv) was ∼40% of flow through Bering Strait and varied seasonally, accounting for >50% of summer and ∼20% of winter transport in Bering Strait. Current direction was strongly influenced by bathymetry, with northward flow through the Central Channel and eastward flow south of Hanna Shoal. The latter joined the coastal flow exiting the shelf via Barrow Canyon. Drifter trajectories indicated the transit from Bering Strait to the mouth of Barrow Canyon took ∼90 days during the ice‐free season. Most (∼70%) of the drifters turned westward at the mouth of Barrow Canyon and continued westward in the Chukchi Slope Current. This slope flow was largely confined to the upper 300 m, and although it existed year‐round, it was strongest in spring and summer. Drifter trajectories indicated that the Chukchi Slope Current extends as far west as the mouth of Herald Canyon. The remaining ∼30% of the drifters turned eastward or were intercepted by sea ice.
Surface Connectivity and Interocean Exchanges From Drifter‐Based Transition Matrices
Authors: McAdam Ronan , van Sebille Erik 
Published: January 2018

AbstractGlobal surface transport in the ocean can be represented by using the observed trajectories of drifters to calculate probability distribution functions. The oceanographic applications of the Markov Chain approach to modeling include tracking of floating debris and water masses, globally and on yearly‐to‐centennial time scales. Here we analyze the error inherent with mapping trajectories onto a grid and the consequences for ocean transport modeling and detection of accumulation structures. A sensitivity analysis of Markov Chain parameters is performed in an idealized Stommel gyre and western boundary current as well as with observed ocean drifters, complementing previous studies on widespread floating debris accumulation. Focusing on two key areas of interocean exchange—the Agulhas system and the North Atlantic intergyre transport barrier—we assess the capacity of the Markov Chain methodology to detect surface connectivity and dynamic transport barriers. Finally, we extend the methodology's functionality to separate the geostrophic and nongeostrophic contributions to interocean exchange in these key regions.
Retrieving Temperature Anomaly in the Global Subsurface and Deeper Ocean From Satellite Observations
Authors: Su Hua , Li Wene , Yan Xiao‐Hai 
Published: January 2018

AbstractRetrieving the subsurface and deeper ocean (SDO) dynamic parameters from satellite observations is crucial for effectively understanding ocean interior anomalies and dynamic processes, but it is challenging to accurately estimate the subsurface thermal structure over the global scale from sea surface parameters. This study proposes a new approach based on Random Forest (RF) machine learning to retrieve subsurface temperature anomaly (STA) in the global ocean from multisource satellite observations including sea surface height anomaly (SSHA), sea surface temperature anomaly (SSTA), sea surface salinity anomaly (SSSA), and sea surface wind anomaly (SSWA) via in situ Argo data for RF training and testing. RF machine‐learning approach can accurately retrieve the STA in the global ocean from satellite observations of sea surface parameters (SSHA, SSTA, SSSA, SSWA). The Argo STA data were used to validate the accuracy and reliability of the results from the RF model. The results indicated that SSHA, SSTA, SSSA, and SSWA together are useful parameters for detecting SDO thermal information and obtaining accurate STA estimations. The proposed method also outperformed support vector regression (SVR) in global STA estimation. It will be a useful technique for studying SDO thermal variability and its role in global climate system from global‐scale satellite observations.
Decadal Shift in West China Autumn Precipitation and its Association With Sea Surface Temperature
Authors: Wei Ting , He Shengping , Yan Qing , Dong Wenjie , Wen Xiaohang 
Published: January 2018

AbstractWest China autumn precipitation (WCAP) is the final stage of the rainy season in mainland China and is characterized as the secondary peak in annual cycle of precipitation in West China. This study reveals that WCAP experienced a significant interdecadal shift around the mid‐1980s, with greatly reduced precipitation after this shift. Features related to the decrease in WCAP include the weakening of warm, wet southerlies prevailing from the oceans to inland China, the weakened Eurasian pattern, and the southward displacement of the East Asian jet stream (EAJS). Further analysis indicates that the interdecadal changes in WCAP may be attributed to the interdecadal increasing of sea surface temperature (SST) in the Indo‐Pacific warm pool (SSTIOP), North Pacific (SSTNP), and central equatorial Pacific (SSTCEP) after the 1980s. The warmer SSTIOP contributes to a weaker meridional land‐sea thermal contrast, which inducts an anomalous local meridional circulation and northerly. The warmer SSTNP stimulates a Rossby wave train that leads to weakened West Pacific subtropical high and accompanying cyclonic circulation anomaly, hindering the transport of water vapor inland from the oceans. The increased SSTCEP leads to the southward displacement of the EAJS and its secondary circulation, generating an anomalous descending branch and reduced WCAP. Numerical simulations further support the conclusions derived from the diagnostic analysis that the decadal warming of the SSTIOP, SSTNP, and SSTCEP synergistically contributes to the reduction of WCAP after the 1980s.
Distinct Contributions of Ice Nucleation, Large‐Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5
Authors: Wang Yong , Zhang Damao , Liu Xiaohong , Wang Zhien 
Published: January 2018

AbstractMixed‐phase clouds containing both liquid droplets and ice particles occur frequently at high latitudes and in the midlatitude storm track regions. Simulations of the cloud phase partitioning between liquid and ice hydrometeors in state‐of‐the‐art global climate models are still associated with large biases. In this study, the phase partitioning in terms of liquid mass phase ratio (MPRliq, defined as the ratio of liquid mass to total condensed water mass) simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against the observational data from A‐Train satellite remote sensors. Modeled MPRliq is significantly lower than observations on the global scale, especially in the Southern Hemisphere (e.g., Southern Ocean and the Antarctic). Sensitivity tests with CAM5 are conducted to investigate the distinct contributions of heterogeneous ice nucleation, shallow cumulus detrainment, and large‐scale environment (e.g., winds, temperature, and water vapor) to the low MPRliq biases. Our results show that an aerosol‐aware ice nucleation parameterization increases the MPRliq especially at temperatures colder than −20°C and significantly improves the model agreements with observations in the Polar regions in summer. The decrease of threshold temperature over which all detrained cloud water is liquid from 268 to 253 K enhances the MPRliq and improves the MPRliq mostly over the Southern Ocean. By constraining water vapor in CAM5 toward reanalysis, modeled low biases in many geographical regions are largely reduced through a significant decrease of cloud ice mass mixing ratio.
An Evaluation of the Shortwave Direct Aerosol Radiative Forcing Using CALIOP and MODIS Observations
Authors: Oikawa Eiji , Nakajima Teruyuki , Winker David 
Published: January 2018

AbstractIn this study, all‐sky ShortWave Direct Aerosol Radiative Forcing (SWDARF) at the top of atmosphere is estimated using the method of Oikawa et al. (2013) applied to two generations of Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Level 2 products, i.e., version 2 (V2) and version 3 (V3), and the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product. The estimated SWDARF in Oikawa et al. (2013) was based on CALIPSO V2 product, which contained significant errors in cloud clearing and low‐altitude aerosols. This error was corrected in V3, resulting in greatly improved and significantly different aerosol and cloud distributions. In clear‐sky conditions, the magnitude of aerosol optical thickness underestimation becomes smaller and SWDARF becomes more negative using the V3 product. In addition, above‐cloud aerosols, which cause positive SWDARF, are less frequently detected and below‐cloud aerosols are more frequently detected in the V3 product than in the V2 product, so that cloudy‐sky SWDARF becomes more negative using the V3 product. From these results, clear‐sky, cloudy‐sky, and all‐sky SWDARFs become more negative using the V3 product than the V2 product. The magnitude of negative SWDARF using the V3 product is more than twice as large as the V2 product under all‐sky conditions due to V3 improvements in the lidar retrieval algorithms. Considering the uncertainties of aerosol and cloud measurements, annual zonal averages of clear‐sky, cloudy‐sky, and all‐sky SWDARFs from 60°S to 60°N are estimated as −4.0 ± 0.2, −1.1 ± 0.3, and −2.1 ± 0.2 Wm−2 from the V3 product.
Isolating the Liquid Cloud Response to Recent Arctic Sea Ice Variability Using Spaceborne Lidar Observations
Authors: Morrison A. L. , Kay J. E. , Chepfer H. , Guzman R. , Yettella V. 
Published: January 2018

AbstractWhile the radiative influence of clouds on Arctic sea ice is known, the influence of sea ice cover on Arctic clouds is challenging to detect, separate from atmospheric circulation, and attribute to human activities. Providing observational constraints on the two‐way relationship between sea ice cover and Arctic clouds is important for predicting the rate of future sea ice loss. Here we use 8 years of CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations from 2008 to 2015 to analyze Arctic cloud profiles over sea ice and over open water. Using a novel surface mask to restrict our analysis to where sea ice concentration varies, we isolate the influence of sea ice cover on Arctic Ocean clouds. The study focuses on clouds containing liquid water because liquid‐containing clouds are the most important cloud type for radiative fluxes and therefore for sea ice melt and growth. Summer is the only season with no observed cloud response to sea ice cover variability: liquid cloud profiles are nearly identical over sea ice and over open water. These results suggest that shortwave summer cloud feedbacks do not slow long‐term summer sea ice loss. In contrast, more liquid clouds are observed over open water than over sea ice in the winter, spring, and fall in the 8 year mean and in each individual year. Observed fall sea ice loss cannot be explained by natural variability alone, which suggests that observed increases in fall Arctic cloud cover over newly open water are linked to human activities.
Key Role of Nitrate in Phase Transitions of Urban Particles: Implications of Important Reactive Surfaces for Secondary Aerosol Formation
Authors: Sun Jiaxing , Liu Lei , Xu Liang , Wang Yuanyuan , Wu Zhijun , Hu Min , Shi Zongbo , Li Yongjie , Zhang Xiaoye , Chen Jianmin , Li Weijun 
Published: January 2018

AbstractAmmonium sulfate (AS) and ammonium nitrate (AN) are key components of urban fine particles. Both field and model studies showed that heterogeneous reactions of SO2, NO2, and NH3 on wet aerosols accelerated the haze formation in northern China. However, little is known on phase transitions of AS‐AN containing haze particles. Here hygroscopic properties of laboratory‐generated AS‐AN particles and individual particles collected during haze events in an urban site were investigated using an individual particle hygroscopicity system. AS‐AN particles showed a two‐stage deliquescence at mutual deliquescence relative humidity (MDRH) and full deliquescence relative humidity (DRH) and three physical states: solid before MDRH, solid‐aqueous between MDRH and DRH, and aqueous after DRH. During hydration, urban haze particles displayed a solid core and aqueous shell at RH = 60–80% and aqueous phase at RH > 80%. Most particles were in aqueous phase at RH > 50% during dehydration. Our results show that AS content in individual particles determines their DRH and AN content determines their MDRH. AN content increase can reduce MDRH, which indicates occurrence of aqueous shell at lower RH. The humidity‐dependent phase transitions of nitrate‐abundant urban particles are important to provide reactive surfaces of secondary aerosol formation in the polluted air.
Observations and Explicit Modeling of Summertime Carbonyl Formation in Beijing: Identification of Key Precursor Species and Their Impact on Atmospheric Oxidation Chemistry
Authors: Yang Xue , Xue Likun , Wang Tao , Wang Xinfeng , Gao Jian , Lee Shuncheng , Blake Donald R. , Chai Fahe , Wang Wenxing 
Published: January 2018

AbstractCarbonyls are an important group of volatile organic compounds (VOCs) that play critical roles in tropospheric chemistry. To better understand the formation mechanisms of carbonyl compounds, extensive measurements of carbonyls and related parameters were conducted in Beijing in summer 2008. Formaldehyde (11.17 ± 5.32 ppbv), acetone (6.98 ± 3.01 ppbv), and acetaldehyde (5.27 ± 2.24 ppbv) were the most abundant carbonyl species. Two dicarbonyls, glyoxal (0.68 ± 0.26 ppbv) and methylglyoxal (MGLY; 1.10 ± 0.44 ppbv), were also present in relatively high concentrations. An observation‐based chemical box model was used to simulate the in situ production of formaldehyde, acetaldehyde, glyoxal, and MGLY and quantify their contributions to ozone formation and ROx budget. All four carbonyls showed similar formation mechanisms but exhibited different precursor distributions. Alkenes (mainly isoprene and ethene) were the dominant precursors of formaldehyde, while both alkenes (e.g., propene, i‐butene, and cis‐2‐pentene) and alkanes (mainly i‐pentane) were major precursors of acetaldehyde. For dicarbonyls, both isoprene and aromatic VOCs were the dominant parent hydrocarbons of glyoxal and MGLY. Photolysis of oxygenated VOCs was the dominant source of ROx radicals (approximately >80% for HO2 and approximately >70% for RO2) in Beijing. Ozone production occurred under a mixed‐control regime with carbonyls being the key VOC species. Overall, this study provides some new insights into the formation mechanisms of carbonyls, especially their parent hydrocarbon species, and underlines the important role of carbonyls in radical chemistry and ozone pollution in Beijing. Reducing the emissions of alkenes and aromatics would be an effective way to mitigate photochemical pollution in Beijing.
Decoupling of Climatic Drying and Asian Dust Export During the Holocene
Authors: Xu Bing , Wang Luo , Gu Zhaoyan , Hao Qingzhen , Wang Haizhi , Chu Guoqiang , Jiang Dabang , Liu Qiang , Qin Xiaoguang 
Published: January 2018

AbstractBoth paleoclimatic records and models suggest that the dust accumulation in ice cores and marine sediments, which is often regarded as a direct record of changing atmospheric dust loading and used to estimate its climatic impact, is strongly coupled to the aridity of dust source regions. However, the underlying association of this couple has not been tested directly because of the lack of continuous and well‐dated independent records of eolian activity in dust source regions. Here we present a high‐resolution multiproxy record of the Holocene eolian activity and climate changes from Lake Xiarinur in north China, a major Asian dust source region. Our data, together with the records of Asian dust accumulation in downwind areas, including the North Pacific Ocean and Greenland, suggest a decoupling between long‐distant Asian dust export and climatic drying in the Holocene. Although the climate was humid and the eolian activity was weak in the source region during the early Holocene, the dust accumulation in the North Pacific Ocean and Greenland was relatively high. Similarly, while climatic drying and strong eolian activity occurred in north China during the late Holocene, the rate of dust accumulation in the downwind areas was low. The long‐distant export of Asian dust is closely correlated with the strength of the Siberian High rather than the westerlies as widely believed before. The rate of dust accumulation in the GISP2 Greenland ice core is comparable in patterns with the intensity of the Siberian High forced eolian activity on both millennial and centennial time scales.