bluuebunny/crossref_metadata_2025 huggingface dataset:
Big data analysis and achievements of global Petroleum exploration
Authors: Mi shiyun , Wu Zhenzhen , Zhang Qian
Published: March 2020

Through applying the data mining analysis techniques of cluster analysis and correlation analysis, as well as spatial analysis and data visualization analysis techniques closely combined with GIS technology, based on IHS’s global exploratory well data, global oil and gas field data,  the data and its classification schemes of 468 petroliferous basins identified by the Oil and Gas Resources Evaluation Project Team of PetroChina, this paper conducted topological analysis, spatial overlay analysis and spatial statistical analysis research in the system of ArcGISn. For the first time, it completed the globally big data mining and analysis of various basin drilling exploration. Meanwhile, it applied small patches technique to analyze the heat of global oil and gas drilling exploration, obtained some new understandings of the global oil and gas exploration activity routines, which is considered to be significant in guiding the optimization of new exploration projects worldwide, and indicated the good application prospect of the big data analysis technology in the oil and gas industry.The new findings are as follows. (1) The prospects with high degree of exploration globally mainly concentrate in Tethyan tectonic domain. (2) In the history of petroleum industry, the active period was distinct with basin types. Specifically, it was in 1910-1920 for for-arc basins, 1950-1980 for foreland basins, and 1980-1990 for continental rift basins. (3) The global success ratio of exploratory wells is 28.8% on the average, and the success ratio does not differ greatly for various types of basins. Generally, the ratio is relatively higher for passive continental margin basins, but relatively lower for for-arc basins. (4) Through estimating the average well-controllable reserves to denote the exploration efficiency in a specific basin type, it is illustrated that the exploration efficiency was the highest in passive continental margin basins, followed by continental rift basins and foreland basins, and the lowest in fore-arc basins.
Identifying and mapping very small mountain glaciers on coarse to high-resolution imagery
Authors: Leigh Joshua , Stokes Chris , Carr Rachel , Evans Ian , Andreassen Liss , Evans David
Published: March 2020

Small mountain glaciers are an important part of the cryosphere and tend to respond rapidly to climate warming. Historically, mapping very small glaciers (generally considered to be <0.5 km2) using satellite imagery has often been subjective due to the difficulty in differentiating them from perennial snowpatches. For this reason, most scientists implement minimum size-thresholds (typically 0.01–0.05 km2). However, when mapping on high-resolution imagery (<1 m) with minimal seasonal snow cover, glaciers <0.05 km2 and even <0.01 km2 are readily identifiable and using a minimum threshold may be inappropriate. For these cases, we have developed a set of criteria to enable the identification of very small glaciers and classify them as certain, probable, or possible. Our identification criteria are based on detailed ice surface structures (e.g. evidence of flow banding and crevasses) and diagnostic glacial landforms (e.g. moraines). Implementation of this scoring system should facilitate a more consistent and objective approach to identifying and mapping very small glaciers on high-resolution imagery, helping to produce more comprehensive and accurate glacier inventories.
Realtime detection and location of very local seismicity using SeisComp3
Authors: Bianchi Marcelo , Schirbel Lucas , Ausgusto Alexandre
Published: March 2020

We put SeisComp3 to test by using it to analyze a very dense (9 squared kilometers) local network of 712, four components sensors (stations). Each station had a 3-component accelerometer and a pressure sensor deployed at the ocean bottom, close to the Brazilian platform near an oil exploration field. Noise levels were extreme. During the two months of the operation time, the network recorded an earthquake swarm sequence, and later analysis indicated more than 1000 earthquakes detected in a one-hour interval employing a coherency stacking method. While still not a common practice, real-time earthquake detection and location in this situation would be beneficial since this could support decisions while drilling or oil recovering is in place. Traditional tools as SeisComp3 are routinely used and allows for real-time detection and location along with the rapid revision of regional and teleseismic events, but are not widely adapted to work in a very local environment. Our experience so far showed that SeisComp3 efficiently handled the data volume (4 components at 500 samples per second times 712 stations) with a modern average workstation. Traditional SEG-Y data can be routinely converted and fed in real-time to SeedLink FIFO using ObsPy. Still, data must be correctly rotated since SeisComp3 needs at least a vertical component. Processing workflow included parallel picking using scautopick with STA/LTA, nucleation of origins using scautoloc, and location using Locsat and Hypo71 tools. In this harsh environment, the optimal window size for STA is about the size of the P-wave (0.05-0.1 s) and, LTA is about 30-60 times the S-P times (60-120 s). Using those parameters, SeisComp3 managed to generate from 400-1200 readings per data channel. We fed all picks into scautoloc that handled origin nucleation and location. Despite parameters supplied to scautoloc, the tool has many limits and relations hardcoded that inhibit it from respecting maximum requested residuals. In other words, its nucleation algorithm is adapted to work on the teleseismic and regional scale. Actual results indicate that we were able to nucleate and locate only 10-20% of known origins. Due to the flexibility of the tool, we also developed a pipeline using S-waves only. S-waves had a higher SNR for the events of interest and, due to lower velocities, presents a larger moveout on the small array easing the location. Manually picked and relocated detections returned an RMS lower as 0.04 s. Additional tests performed using the Scanloc module (GEMPA closed source nucleator) showed a higher performance during the nucleation of new origins. In this case, Hypo71 was the used locator. We did not observe any clear difference between LocSat and Hypo71 performance once the earthquake source is nucleated, and a proper velocity model is supplied.
Determining Sub-Catchment Contributions to the Suspended Sediment load of the Tsitsa River, Eastern Cape, South Africa
Authors: Bannatyne Laura , Foster Ian , Meiklejohn Ian , van der Waal Bennie
Published: March 2020

In South Africa, as in many developing countries, the suspended sediment (SS) data required to support catchment scale hillslope restoration and rehabilitation programmes are typically scarce or absent, leading to a reliance on modelled SS loads and yields that are generally not validated by measured SS data. An exception is the Tsitsa River catchment in the Eastern Cape Province, where modelled SS yields were high (21 – 50 t/ha/yr), leading to the establishment of a Citizen Technician-based monitoring programme (2015 – 2019) that has provided flood-focused, sub-catchment scale SS data at sub-daily timestep for 11 sites throughout the 4000 km2 catchment.

A confluence-based SS fingerprinting and tracing exercise was undertaken in the catchment (2018). Analysis of the distinctive physicochemical properties of resuspended fine sediment sampled above and below major confluences allowed the percentage of SS contributed by each tributary to be apportioned, and compared with findings from both the SS monitoring campaign and from existing models.
Limitation by iron and manganese on phytoplankton communities in the Drake Passage. 
Authors: Balaguer Jenna , Koch Florian , Trimborn Scarlett
Published: March 2020

The Southern Ocean (SO) accounts for over 40% of anthropogenically derived CO2 uptake. It is the world’s largest High-Nutrient Low-Chlorophyll (HNLC) region and the scarcity of trace metals such as iron (Fe) drives phytoplankton composition and biomass build up. Besides Fe, manganese (Mn) is the second most abundant trace metal since it is present in the thylakoids. As dissolved manganese (dMn) concentrations in the Atlantic sector of the SO are very low (0.04 nM), phytoplankton growth may not only be limited by Fe but also by Mn availability, a theory previously described by Martin et al. (1990). However, mechanistic studies investigating the effects of multiple trace metals limiting or co-limiting on growth and photosynthesis are lacking. This study focuses on the identification of the Fe-Mn co-limitation of natural phytoplankton assemblages to elucidate the impact of different Fe and Mn additions on species composition. To this end, two shipboard Fe-Mn addition bottle incubation experiments were conducted during the ‘RV Polarstern’ expedition PS97 in the Western and Eastern Drake Passage (DP) in 2016. This study highlights the importance of Mn in the otherwise Fe-limited Drake Passage. From microscopy samples, the addition of Fe and Mn together triggered the highest abundance of the genus Fragilariopsis sp. in the Western DP. In the Eastern DP, the nanophytoplankton fraction, detected by flow cytometry, reached the highest abundance only when both trace elements were provided, confirmed by highest chlorophyll-a build up. Moreover, the distinct response of Mn depletion relative to the Fe depletion support the findings that Fe and Mn do not substitute to each other. This experimental study highlights that both trace elements act as drivers of the ecology across the Drake Passage.
River corridors as global hotspots of microplastic pollution
Authors: Krause Stefan , Drummond Jennifer , Nel Holly , Gomez-Velez Jesus , Lynch Iseult , Sambrook Smith Greg
Published: March 2020

The total production of plastics is estimated to be~ 10 billion metric tons, half of which is thought to have ended up as waste in the environment. However, the total mass of plastic found in the world’s ocean garbage patches has been calculated as less than 1 million metric tons, a paradox that leaves the whereabouts of the majority (>99.9%) of plastic waste produced so far unexplained.

 

Recent research suggests that the accumulation of plastic (in particular microplastic < 5mm in size) in river corridors may be even greater than that  in the world’s oceans. Our model-based quantifications reveal that rivers do not solely function as pure conduits for plastics travelling to the oceans, but also represent long-term sinks, with in particular microplastics being buried in streambeds and floodplain sediments. This includes the development of pronounced hotspots of long-term plastic accumulation, evidencing that these emerging pollutants have already developed a pollution legacy that will affect generations to come.

 

The principles that govern the spatially and temporally dynamic inputs of plastics into river corridors as well as the fate and transport mechanisms that explain how plastics are transported and where they accumulate are still poorly understood. Experimental evidence of microplastic pollution in river corridors is hampered by the absence of unified sampling, extraction and analysis approaches, inhibiting a comprehensive investigation of global source distributions and fate pathways. We have therefore initiated the 100 Plastic Rivers programme to provide a global baseline of microplastic pollution in rivers, their drivers and controls in order to develop mechanistic understanding of their fate and transport dynamics and create predictive capacity by informing the parameterisation of global plastic transport models. Preliminary results evidence the suitability of the 100 Plastic Rivers approach and help validate our predictions of global plastic storage in river corridors.
Wave activities during different phase of solar cycle : Cassini observations on Saturn
Authors: Pan Dongxiao , Yao Zhonghua
Published: March 2020

Low frequency quasiperiodic (QP) magnetic field fluctuations are commonly observed in terrestrial and planetary magnetosphere.  At Earth,  these magnetohydrodynamic (MHD) waves are often observed in ultralow frequency (ULF) band (~1 mHz to 1 Hz), which could be generated by solar wind buffeting, Kelvin-Helmholtz instability and/or wave-particle interactions inside the Earth's magnetosphere. At giant planets (Saturn or Jupiter), their enormous magnetospheres often produce QP fluctuations with frequencies lower than the terrestrial ULF waves. In this study, we use Cassini spacecraft observations to analysis waves at period of 10 min to 60 min in Saturnian magnetosphere. We compare wave activities during different solar activities.
Spectroscopic retrieval of above-ground crop nitrogen content with a hybrid machine learning regression method
Authors: Berger Katja , Camps-Valls Gustau , Verrelst Jochem , Féret Jean-Baptiste , Wocher Matthias , Hank Tobias
Published: March 2020

Proteins are the major nitrogen-containing biochemical constituents of plants. Since nitrogen (N) cannot be measured directly using remote sensing data, leaf protein content constitutes a valid proxy for this main limiting plant nutrient. In the past, mainly linear parametric algorithms, such as vegetation indices, have been employed to retrieve this non-state variable from optical reflectance data. Moreover, most studies solely relied on the relationship of chlorophyll content with nitrogen. In contrast, our study presents a hybrid model inversion scheme of a physically-based approach via protein retrieval combined with advanced machine learning regression. The leaf optical properties PROSPECT-PRO model, including the newly calibrated specific absorption coefficients (SAC) of proteins, was coupled with the canopy reflectance model 4SAIL to PROSAIL-PRO. A generic synthetic database of model input parameters with corresponding reflectance was simulated and used for training two different machine learning regression methods: a standard homoscedastic Gaussian Process (GP) and a variational heteroscedastic GP regression that accounts for signal-to-noise correlations. Both GP methods have the interesting feature of providing confidence intervals for the estimates. As part of multiple field campaigns, carried out in the scientific preparation framework of the Environmental Mapping and Analysis Program (EnMAP), spectra of maize and winter wheat were acquired to simulate EnMAP data and plant-organ-specific nitrogen measurements were destructively collected for validation. Both GP models yielded excellent performance in learning the nonlinear relationship between specific protein absorption bands and area-based above-ground N. They also performed similar or even outperformed other nonlinear nonparametric approaches. Physical validation of the estimates against in situ nitrogen measurements from leaves plus stalks yielded a root mean square error (RMSE) of 2.5 g/m². The variational heteroscedastic GP provided a more differentiated pattern of uncertainty with tighter confidence intervals within low-value regimes compared to the standard GP. The inclusion of fruit nitrogen content for validation deteriorated the results of all models, which can be explained by the inability of radiation in the optical domain to penetrate the thick tissues of maize cobs and wheat ears. Following some further validation exercises, we aim to implement GP-based algorithms for global agricultural monitoring of above-ground N derived from future satellite imaging spectroscopy data.
On the Relation between Filament Chirality, Rotation Direction, and Morphology
Authors: Zhou Zhenjun , Liu Rui , Cheng Xing , Jiang Chaowei , Wang Yuming , Liu Lijuan , Wang Guoqiang , Zhang Tielong , Cui Jun
Published: March 2020

Coronal mass ejections (CMEs) with enhanced south-component of the magnetic field are susceptible to producing geomagnetic storms. Filament chirality, rotation direction, and morphology are responsible for CMEs’ magnetic orientation and they are manifestations of magnetic helicity. However, different models predict different relations among them. In this paper, taking advantage of stereoscopic observations and a new method of determining the chirality of erupting filaments, we analyze 12 filaments that present a clear rotation during the eruption. The results based on the small sample support the argument that the filaments with for sinistral (dextral) chirality, they rotate clockwise (counterclock-wise), indicating the transformation of twist into writhe. Moreover, we also inspect soft X-ray and EUV hot temperature images and find that, the associated sigmoids are consistent with filaments prior to the eruption morphologically. However, once starting to rise up, the erupting filaments reverse their shapes from forward S-shaped to inversed S-shaped and vice versa.
Characteristics of North European winter lightning related to a high positive North Atlantic Oscillation index
Authors: Kolmašová Ivana , Rosická Kateřina , Santolík Ondřej
Published: March 2020

The variability of winter climate in the North Atlantic region is predominantly driven by a large scale alternation of atmospheric masses between the Icelandic Low and Azores High pressure systems called the North Atlantic Oscillation (NAO) and characterized by the NAO index. The calculation of the NAO index is based on the difference between sea-level pressure strengths of the Azores High and the Icelandic Low. Unusually high positive values of the NAO index were observed to manifest themselves by above-average precipitation and severe winter storms over British Isles and other parts of northwestern and northern Europe.

In the last two decades, the winter season 2014/2015 exhibited the highest positive monthly NAO indexes. During this winter, newspapers in the UK, Germany, Poland, and Scandinavia reported extremely strong storms which caused huge power outages, damages of buildings, and collapses of traffic which paralyzed the daily life. As winter thunderstorms are also characterized by a higher production of very energetic lightning, we use the World Wide Lightning Location Network (WWLLN) data and investigate properties of lightning which occurred in the north European region from October 2014 to March 2015.  The dataset consists of more than 90 thousand lightning detections. We focus on spatial and temporal distribution of lightning strokes, their energies and multiplicity.

We have found that the diurnal distribution of lightning was random from November till February, while the afternoon peak typical for summer storms was noticeable only in October and March. The median energy of lightning strokes observed in October, November and March reached only about 10-20% of the median energy of strokes detected in December, January and February. The most energetic strokes were concentrated above the ocean close to the western coastal areas and appeared exclusively at night and in the morning hours.
Salt tectonics in the Eastern Mediterranean: Chronology, kinematics, and driving forces
Authors: Zucker Elchanan , Ben Zeev Yechiel , Enzel Yehouda , Gvirtzman Zohar
Published: March 2020

In the Late 1970’s, a slope-parallel normal fault system has been recognized offshore Israel. ~25 years later, a system of folds and thrust faults was recognized farther west in the deep Levant Basin. Initially, this combination of updip extension and downdip contraction seemed to fit the classic paradigm known from other salt basins around the world in which sediments overriding salt glide basinward and produce extension upslope and contraction in the deep basin. However, later studies in the Levant Basin showed that the shapes of the updip extension system and the downdip contractional system do not match; the updip normal faults are trending to the NNE, whereas the deep basin folds are trending to the NW and even to the WNW.

We propose that while extension of the Levant continental slope expresses basinward gliding, the deep basin shortening belongs to the circum-Nile deformation belt (CNDB) that was previously interpreted as an expression of salt squeezing-out from under the Nile Delta.

However, careful mapping of the salt-overburden thicknesses around the Nile delta and its submarine cone clearly shows that in the majority of the study area salt squeeze-out cannot be the dominant driving force, because the thick delta load (nearshore) does not reach the thick basin salt (distal basin). The dominating driving force in the western side of the Nile Delta towards the Herodotus Basin, as well as along the Levant continental margin, is simply the elevation gradient towards the lowest place leading to downslope gliding of the sediment-salt sequence.

Only in the easternmost side of the delta, towards the Levant Basin, does the squeeze-out model work. Here, the delta front covers a thick salt layer and differential loading promotes basinward salt flow. Particularly interesting is the southeast corner of the Mediterranean where the CNDB, driven by differential loading (salt squeezing), is pushed against the Levant margin belt, driven by downslope gliding. By improving the chrono-stratigraphy of the Levant Basin we show that during the first 2.5 my after salt deposition only minor deformation occurred. Then, tilting of the Levant margin (inland uplift) initiated downward gliding and rapid extension; and only ~1 my later the CNDB reached the Levant Basin and started suppressing the downward gliding.

In a wider perspective our analysis shows that the role of salt squeezing by differential loading was previously overestimated in the Eastern Mediterranean and raises the need to carefully map the boundary of the salt basins prior to any interpretation. This conclusion is especially relevant to young basins where deltas and shelves have not propagated far enough into the basin.
Ex-hurricane Ophelia and air quality impacts over Europe in CAMS forecast systems
Authors: Akritidis Dimitris , Katragkou Eleni , Georgoulias Aristeidis K. , Zanis Prodromos , Kartsios Stergios , Flemming Johannes , Inness Antje , Eskes Henk
Published: March 2020

Within the framework of the Copernicus Atmosphere Monitoring Service (CAMS) element CAMS-84 (Global and regional a posteriori evaluation and quality assurance), we analyze and evaluate the performance of CAMS forecast systems during the passage of ex-hurricane Ophelia in mid-October 2017, carrying Saharan dust and Iberian fire smoke over several Western European regions. To this end, day-1 forecasts from CAMS-global (ECMWF Integrated Forecast System; IFS) and CAMS-regional (ensemble of seven regional air quality models) products are compared against satellite retrievals (MODIS/Terra and Aqua, CALIPSO) and ground-based measurements. The analysis indicates that dust and smoke are injected into the warm sector of Ophelia, lying in the vicinity of the warm and cold front, respectively, gradually affecting the air quality and atmospheric composition over France, the Netherlands and Great Britain. The distinct pattern of enhanced aerosol optical depth (AOD) over Western coastal Europe seen in satellite retrievals is well reproduced by the CAMS near-real time forecast. The observed implications for air quality (PM10 and PM2.5) are satisfactorily forecasted in qualitative terms by both CAMS-global and CAMS-regional systems, while in quantitative terms, the CAMS-regional system exhibits a better performance in predicting surface PM concentrations (higher correlation and lower bias) compared to the global.
DTM-based landslide detection using deep learning: A case study in Hong Kong
Authors: Wang Haojie , Zhang Limin
Published: March 2020

Landslide detection is an essential component of landslide risk assessment and hazard mitigation. It can be used to produce landslide inventories which are considered as one of the fundamental auxiliary data for regional landslide susceptibility analysis. In order to achieve high landslide interpretation accuracy, visual interpretation is frequently used, but suffers in time efficiency and labour demand. Hence, an automatic landslide detection method utilizing deep learning techniques is implemented in this work to conduct high-accuracy and fast landslide interpretation. As the ground characteristics and terrain features can precisely capture the three-dimensional space form of landslides, high-resolution digital terrain model (DTM) is taken as the data source for landslide detection. A case study in Hong Kong, China is conducted to validate the applicability of deep learning techniques in landslide detection. The case study takes multiple data layers derived from the DTM (e.g., elevation, slope gradient, aspect, etc.) and a local landslide inventory named enhanced natural terrain landslide inventory (ENTLI) as its data sources, and integrates them into a database for learning. Then, a deep learning technique (e.g., convolutional neural network) is used to train models on the database and perform landslide detection. Results of the case study show great performance and capacity of the applied deep learning techniques, which provides valuable references for advancing landslide detection.
Estimating the macroscopic capillary length using steady state infiltration
Authors: Di Prima Simone , Stewart Ryan D. , Castellini Mirko , Bagarello Vincenzo , Abou Najm Majdi R. , Pirastru Mario , Giadrossich Filippo , Iovino Massimo , Angulo-Jaramillo Rafael , Lassabatere Laurent
Published: March 2020

The macroscopic capillary length is a critical parameter for the modeling of infiltration in single-ring experiments. Current methods to quantify this parameter either require multiple infiltration experiments, thus increasing effort and potential for error, or laboratory characterization that does not reflect field condition. We propose a simple field method for the estimation of the macroscopic capillary length, λc, from Beerkan runs (single-ring infiltration experiment with measurements of initial and saturated soil water contents). In the proposed method, we use the final portion of the cumulative infiltration, corresponding to the steady state of the water infiltration, to develop a reliable predictor of λc. The proposed model was validated using analytically generated data along with an experimental database that included 433 Beerkan runs from a wide range of conditions and types of soils. The analytical validation demonstrated the reliability of the proposed λc estimates for different soil textures and initial soil water contents. Altogether, the proposed method constitutes a simple solution for estimating λc, and it can improve our ability to estimate Ks in the field.
Transport ratios of the kinetic Alfvén mode in space plasmas
Authors: Narita Yasuhito , Vörös Zoltan , Roberts Owen Wyn , Hoshino Masahiro
Published: March 2020

Electric field properties of the kinetic Alfvén mode are analytically studied by constructing the dielectric tensor of the plasma using the linear Vlasov theory and reducing (and identifying) the tensor elements into that of the fluid picture such as the polarization drift, the Hall current, and the diamagnetic current. Off-diagonal dielectric responses do not primarly contribute to the dispersion relation of the kinetic Alfvén mode, but play an important role in the electric field polarization (field rotation sense around the mean magnetic field) and parallel component of the field. The polarization becomes more circular and the parallel component enhances at larger perpendicular wavenumbers. Analytic expression of fluctuation sense serves as a tool to identify the kinetic Alfvén mode in space plasma observations.
The occurrence of drought amplified yield loss risk for maize production in China
Authors: Liu Shengli , Wu Wenbin
Published: March 2020

Increasing drought event is one of the major threats to yield stability and crop production. However, the precise quantification of crop response to such extreme weather is still in lack. Unlike the deterministic researches of drought effects, we propose an insightful probabilistic perspective to quantify drought impacts on maize yield across China. The county-specific combination of annual maize yield anomaly and standardized precipitation evapotranspiration index (SPEI) across its growing season during 1981-2010 was utilized to build a copula-based probabilistic diagram, for the purpose to predict yield loss risk under different drought types. The results reveal that, when compared with the expected long-term yield, the reduction of maize yield and its uncertainty was in line with the drought severity across the growth season, with yield reduced by -5.14%, -8.05% and -3.94% under moderately dry, severely dry, and extremely dry, respectively. Despite the spatial pattern of SPEI existed varying timescales in determining yield anomaly across different counties, the number of counties where maize experienced drought with a response time starts from June and July accounted for 55.28% of counties across China, and that drought with one month duration occupied 50.29%. A considerable gap in the likelihood of maize yield reduction was detected under drought and under non-drought conditions, which further confirmed the negative impacts of drought on maize yield. Moreover, the conditional estimation revealed that the semi-arid region was more susceptible to the drought-induced yield loss risk of maize in comparison to other regions. The probability of yield loss for maize amplified according to the drought severity along with the significant differences (P < 0.05) among the extreme, severely and moderately drought conditions across all of these sub-regions. Our results highlight the improving knowledge of drought on crop yield anomaly and consequent adaptation was essential for the decision making in coping with extreme weather in agricultural production.
Preliminary results from teleseismic tomography of the upper mantle beneath northern Borneo
Authors: Pilia Simone , Rawlinson Nick , Tongkul Felix , Gilligan Amy , Cornwell Dave
Published: March 2020

We present preliminary P-wave tomographic images of the upper mantle beneath northern Borneo (Sabah) using teleseismic earthquake data. Sabah underwent diachronous double-polarity subduction, one dipping to the southeast (terminated in the early Miocene) and the other to the northwest (terminated 5-6 Ma). With the goal of better understanding post-subduction processes in Sabah, 24 permanent seismic stations of MetMalaysia were augmented by the deployment of 46 temporary stations of the nBOSS network, which ran from March 2018 to January 2020. Relative P-wave traveltime residuals from nearly a thousand teleseismic events have been extracted from the continuous records using an adaptive stacking technique, which uses the coherency of global phases across the entire network. Using a grid-based eikonal solver and a subspace inversion technique implemented in FMTOMO, relative arrival time residuals are mapped as 3-D P-wave perturbations.

The most intriguing feature of the final tomographic model is a north-east trending lithospheric structure running across northern Borneo and separating relatively low to high wavespeeds to the west and east, respectively. This structure possibly indicates the suture between pre-Cenozoic lithosphere to the east and the Cenozoic accreted material to the west.

Results from receiver function analysis (i.e., crustal thickness) and crustal velocities from ambient noise tomography will be in the future incorporated in the tomographic inversion in order to obtain an integrated view of the crust-mantle system beneath Sabah.
Uncovering the diverging factors that control microbial carbon sequestration and respiration in soils exposed to moisture fluctuations
Authors: Brangarí Albert C. , Manzoni Stefano , Rousk Johannes
Published: March 2020

Soils are continuously exposed to recurrent cycles of drying and rewetting, for instance, when extended periods of drought are followed by rainfall events. For nearly a century it has been known that the balance of the soil C budget is affected by these moisture fluctuations, which is characterized by very large mineralization losses when dry soils are rewetted. In some ecosystems, the soil C losses resulting from this phenomenon (“the Birch effect”) even represent a dominant fraction of the annual C-transfer from soils to the atmosphere. However, to balance the soil C budget, the microbial control of C input to the soil during these events also needs to be known. It was recently discovered that the growth of microorganisms, driving C stabilization in soils, has a far slower response to rewetting than does respiration. This results in a pronounced and dynamic disconnection between the mechanisms controlling microbial respiration and growth. Despite the significance of this decoupling for the C budget and the long-term balance of soil C stocks, this feature has so far been entirely overlooked by biogeochemical models, potentially leading to a failure to capture the capacity of soils to mitigate the effects of climate change.

To close this knowledge gap, we developed a new process-based soil microbial model that includes a wide range of physical, chemical and biological mechanisms to explore the nature of soil C dynamics induced by moisture changes. The model was validated using respiration data from soils exposed to repeated cycles of drying and rewetting which has been frequently studied (Miller et al., 2005, Soil Biol Biochem) and compared to other models existing in the literature. The proposed model was able to capture, at once and for the first time, the respiration data and the decoupled behaviour of growth. Simulation results identified the drought-legacy effects on C use efficiency and microbial physiology as the main mechanisms controlling the soil responses to moisture fluctuations. This represents a critical step towards unravelling the C sequestration capacity of soils, its drivers and feedback on climate.
Radiative forcing of anthropogenic aerosols on cirrus clouds using a hybrid ice nucleation scheme
Authors: Zhu Jialei , Penner Joyce E.
Published: March 2020

Anthropogenic aerosols impact cirrus clouds through ice nucleation, thereby changing the Earth’s radiation budget. However, the magnitude and sign of anthropogenic forcing on cirrus clouds are still very uncertain depending on the treatments for ice nucleating particles (INPs) and the ice nucleation scheme. In this study, a new ice nucleation scheme (hereafter the HYBRID scheme) is developed to combine the best features of two previous ice nucleation schemes, so that the global model is able to calculate the ice number concentration in both the updrafts and downdrafts associated with gravity waves and has a robust sensitivity to the change of aerosol number. The ice number concentrations calculated using the HYBRID scheme are overestimated somewhat but are in reasonable agreement with an adiabatic parcel model and observations. The forcing and cloud changes associated with changes in aircraft soot, sulfur emission and all anthropogenic emissions between the preindustrial period (PI) and the present day (PD) are examined using a global model with the HYBRID scheme. Aircraft soot emissions decrease the global average ice number concentration (Ni) by -1.0±2.4×107 m-2 due to the inhibition of homogeneous nucleation and lead to a radiative forcing of -0.14±0.07 W m-2, while the increase in the sulfur emissions increases the global average Ni by 7.3±2.9×107 m-2 due to the increase in homogeneous nucleation and leads to a radiative forcing of -0.02±0.06 W m-2. The possible effects of aerosol and cloud feedbacks to the meteorological state in remote regions partly contribute to reduce the forcing and the change in Ni due to anthropogenic emissions. The radiative forcing due to all increased anthropogenic emissions from PI to PD is estimated to be -0.20±0.05 W m-2. If newly formed secondary organic aerosols (SOA) acts an INP and inhibit homogeneous nucleation, the Ni formed from heterogeneous nucleation is increased. As a result, the inclusion of INPs from SOA increases the change in Ni to 12.0±2.3×107 m-2 and increases (makes less negative) the anthropogenic forcing on cirrus clouds to -0.04±0.08 W m-2 from PI to PD.
Delineating monitoring Network in Biodiversity Hotspot based on Land Surface Phenology. The case of Tropical Montane Cloud Forest
Authors: Aragones David , Rodriguez-Galiano Victor F. , Caparros-Santiago Jose A. , Espinoza-Guzman Marco A.
Published: March 2020

Land Surface Phenology (LSP) is the study of the phenology through satellite sensors. It integrates phenological patterns (mainly spatial) and processes (mainly temporal) within heterogeneous biophysical environments across multiple scales. It is a very useful tool for the characterization and monitoring of forests. Tropical montane cloud forest is the most diverse type of vegetation per unit area, since it occupies less than 1% of Mexico but harbours 10% of the country’s plant biodiversity. It is a critical priority for biodiversity conservation, its permanence in the medium and long term is threatened by habitat destruction and climate change. A regional conservation approach, which values all fragments of this type of forest as contributing to regional biodiversity, will be required to conserve plant biodiversity in central Veracruz. This area is one of the Rare forest ecoregions within biodiversity hotspots. Our primary aim was to identify priority zones for stablishing a Tropical montane cloud forest monitoring network in Central Veracruz based on its phenological responses at multiples scales. Our methodology can be applied in other tropical biodiversity zones, even in the absence of adequate cartography. We start from homogeneous and reliable pixels and automatically calculate the number of pheno-regions that exist within this type of vegetation in the study area, based on different LSP pheno-metrics extracted from different MODIS vegetation index time-series (NDVI & EVI) with Timesat and BFAST algorithm. We extract Fraction cover subpixels homogeneus from MODIS and Sentinel 2 LC map with Random Forest classification and success rate analysis curve ensures the reliability of the LC map. We identify 4 statistically different representative pheno-regions through cluster analysis in this type of forest within the study area and we obtained 351 priority areas where a phenological monitoring network could be located.
Interpretation of a Network-Scale Tracer Experiment in Fractured Rock
Authors: Howroyd Matthew , Novakowski Kent
Published: March 2020

The presence of fractures in consolidated media allows for rapid transport of aqueous contaminants through convoluted pathways and for diffusion into the rock matrix adjacent to the fracture, which significantly complicates our ability to make transport predictions. Despite the need to predict transport in fractures over substantive distances, very few tracer experiments have been conducted at large scale (>50m) due to experimental difficulty and cost associated with such experiments.  Even where these studies have been conducted, the results have often been difficult to model accurately without the use of extra fitting parameters. The objective of this study is to improve our understanding of key transport processes in complex large-scale fracture networks in carbonate rock by simulating the results of a tracer experiment conducted at a network scale. The tracer experiment used for this study was conducted previously by injecting a conservative dye tracer into an isolated 10 m section of a well and with breakthrough in six downstream observation wells open over a similar depth range. These observation points were located at distances of up to 245 m from the injection well. Measurement of the tracer breakthrough was conducted using a downhole fluorometer, allowing for observation of the full concentration profile in each well over time. To simulate the results, a DFN approach with a control-volume finite element model is used, which allows for irregular grid blocks and maintenance of the mass balance within the simulation domain. Because of the measurement of full concentration profiles, simulating transport inside the observation wells is also a focus of this study. In order to achieve a fit between the simulated and measured data, combinations of various fracture network geometries with aperture and matrix porosity heterogeneity are examined.
Release of old carbon from the deep South Pacific during the last deglaciation
Authors: Dai Yuhao , Yu Jimin , Rafter Patrick
Published: March 2020

The release of old carbon via the Southern Ocean has been thought to contribute to the last deglacial atmospheric CO2 rise, but underlying processes are not fully understood, in part, due to insufficient high-fidelity radiocarbon (Δ14C) reconstructions minimally complicated by age models and release of “dead carbon”. Here, we present a new deep-water Δ14C record for a core located at 3.3 km water depth from the Southwest Pacific, based on a robust age model using planktonic Mg/Ca along with co-existing benthic 14C measurements. Our results confirm previous records that suggest enhanced ventilation in the Southern Ocean during Heinrich Stadial 1 and the Younger Dryas. For the first time, our data show a large Δ14C decline during the Antarctic Cold Reversal, indicating strengthened stratification in the deep South Pacific. Our results strongly support that the deep ocean supplied old carbon to the atmosphere during the last deglaciation.
Finding solutions in an interdisciplinary environment
Authors: Bryndum-Buchholz Andrea , Corbalan Ana , Shajahan Najeem
Published: March 2020

Our rapidly changing world is facing challenges that increasingly demand strong interdisciplinary components in academic projects to find the solutions we need. Successful interdisciplinary research can enhance knowledge and hence lead to new discoveries and innovation. In order to successfully work together in projects that span multiple disciplines, it is important to fully understand the challenges these projects face. We revisit the meaning of interdisciplinarity and evaluate why it has often proven very challenging. For example, one of the greatest challenges is finding a common ground when framing key research questions. We analyze and present an ideal scenario, where challenges and limitations are acknowledged but overcome, and suggest some techniques that can be used to plan and successfully undertake interdisciplinary projects.  

 
Mineralogical and chemical variability of soils across a tropical ocean island climate gradient, San Cristóbal, Galápagos
Authors: Percy Madelyn , Benninger Larry
Published: March 2020

Little data currently exist on the chemistry of soils on the island of San Cristóbal, Galápagos, despite the importance of this data in understanding how the island has weathered through time. We sought to resolve this lack of data by surveying soils from different elevations and in different climate zones across the island. We collected soil samples from transects and sites across a precipitation-gradient in order to describe the mineralogy and chemistry of the soils, and to understand how soils have weathered in different precipitation regimes across the island. We used a mass balance approach, coupled with chemical weathering indices, to understand profile-scale to site-scale differences in weathering.

Climate-dependent shifts in soil characteristics are apparent: at the wettest sites, the soils have the lowest pH, the highest percentage of amorphous material, and the highest loss on ignition values. We compared the saprolite, the basal material from the soil pits in which the basalt bedrock’s texture was still apparent but the material was extremely friable, and previously reported unweathered bedrock data, showing that the saprolite was highly weathered relative to the unweathered bedrock. Using the mass balance approach, we show that while base cations have been lost from soils relative to the parent material underlying the profiles, aluminum and iron concentrations have remained the same or have increased.

 We used chemical indices of weathering as evidence for the relationship between weathering intensity and precipitation, with greater weathering intensity observed in the very humid highlands compared to the less intense weathering that has occurred in the arid lowlands. The windward side of the island shows higher intensities of weathering than the leeward side. Our findings conform with other soil chemistry studies on the islands of Santa Cruz and Isabela, also in the Galápagos archipelago, showing that more intense weathering, accompanied by a greater loss of mobile elements, is observed at wetter sites.
Comparison of Madden–Julian Oscillation Modulation on tropical-cyclone genesis over the South China Sea and Western North Pacific under different El Niño Southern Oscillation conditions
Authors: Ye Chengyao , Deng Liping , Huang Wan-Ru , Chen Jinghua
Published: March 2020

This paper explores the modulation by Madden–Julian Oscillation (MJO) on tropical-cyclone (TC; hereafter, MJO TC) genesis over the Western North Pacific (WNP) and the South China Sea (SCS) under different El Niño Southern Oscillation (ENSO) conditions. Analyses used Joint Typhoon Warning Center (JTWC) Best Track data, the Real-Time Multivariate MJO (RMM) index, and European Center for Medium-Range Weather Forecasts (ECMWF) Interim (ERA-Interim) reanalysis data. Results showed that MJO has significant modulation on both SCS and WNP TC genesis in neutral years, with more (fewer) TCs forming during active (inactive) MJO phases. However, during El Niño and La Niña years, modulation over the two regions differs. Over the SCS, the modulation of TC genesis is strong in La Niña years, while it becomes weak in El Niño years. Over the WNP, MJO has stronger influence on TC genesis in El Niño years compared to that in La Niña years. Related Genesis Potential Index (GPI) analysis suggests that midlevel moisture is the primary factor for MJO modulation on SCS TC genesis in La Niña years, and vorticity is the secondary factor. Over the WNP, midlevel moisture is the dominant factor for MJO TC genesis modulation during El Niño years. The main reason is increased water-vapor transport from the Bay of Bengal associated with the active MJO phase related westerly wind anomalies; these features are a significant presence over the SCS during La Niña years, and over the WNP during El Niño years.
Electron Bernstein Waves driven by Electron Crescents near the Electron Diffusion Region
Authors: Li Wenya , Graham Daniel , Tang Binbin , Vaivads Andris , Andre Mats , Min Kyungguk , Liu Kaijun , Fujimoto Keizo , Lindqvist Per Arne , Dokgo Kyunghwan , Wang Chi , Burch James
Published: March 2020

The Magnetospheric Multiscale spacecraft encounter an electron diffusion region (EDR) of asymmetric magnetic reconnection at Earth's magnetopause. The EDR is characterized by agyrotropic electron velocity distributions on both sides of the neutral line. Various types of plasma waves are produced by the magnetic reconnection in and near the EDR. Here we report large-amplitude electron Bernstein waves (EBWs) at the electron-scale boundary of the Hall current reversal. The finite gyroradius effect of the outflow electrons generates the crescent-shaped agyrotropic electron distributions, which drive the EBWs. The EBWs propagate toward the central EDR. The amplitude of the EBWs is sufficiently large to thermalize and diffuse electrons around the EDR. Our analysis shows that the EBWs contribute to the cross-field diffusion of the electron-scale boundary of the Hall current reversal near the EDR.