bluuebunny/crossref_metadata_2025 huggingface dataset:
Attenuation and amplification effects of seismic translational and rotational components in shallow media
Authors: Li Wei , Zhang Yi , Wang Yun
Published: March 2024

In a three-dimensional Cartesian coordinate system, the deformation of the medium around a particle includes strain, translation, and rotation. Rotational motion is an important aspect of current seismological research. Seismologists have recognized the importance of rotational motion in dynamic response and damage of structures caused by certain earthquakes, through investigations into earthquake damage. In rapid earthquake intensity reports, it is essential to not only consider factors such as earthquake location, source depth, magnitude, and fault rupture model, but also to emphasize the analysis of the amplification effect of shallow media. We discuss the attenuation characteristics and difference between seismic translational and rotational components by medium viscoelasticity through two-dimensional numerical simulation, analyze the amplification effect of shallow viscoelastic low-velocity layer on ground motion by the reference site spectral ratio (RSSR), and discuss the difference of the amplification caused by different low-velocity layer factors. The results show that the seismic primary frequency decreases more with increasing viscoelasticity, and the energy of rotational component attenuates more significantly than that of translational component. The elastic low-velocity layer amplifies high-frequency signals of body waves greater than the viscoelastic low-velocity layer, especially in rotational component. When shallow low-velocity layers consist of multilayered sediments compared to a single sediment, the amplification of surface wave is stronger, particularly in rotation. We follow the research method used for seismic translation to discuss the amplification effect of shallow viscoelastic medium on seismic rotation, which is important for performance-based seismic design and earthquake damage analysis.
Permeability evolution of localised failure sandstone
Authors: Nguyen Nhan , Nguyen Giang , Bui Ha , Bennett Terry
Published: March 2024

Permeability, a crucial factor in assessing porous reservoir rock quality, can be influenced by localised deformation such as fractures, shear bands, or compaction bands. Considering the arbitrary occurrence of these bands and the need to investigate the permeability difference between the overall specimen and within the localised zone, existing literature lacks a quantitative measure for such complexity. This study proposes a numerical concept that focuses on the permeability-stress connection across multiple levels from macroscopic to grain-scale bridging via the localised band, referred to as mesoscale. This framework integrates breakage mechanics into a dual-scale continuum model, tracking the permeability evolution of Bentheim sandstone under triaxial compression. The key feature lies in the link from stress to grain size distribution, due to breakage mechanics, that governs the constitutive responses, including macro, inside and outside of the localisation zone, produced from the dual-scale model following traction equilibrium condition. The successful outcome should capture the permeability inside the localisation band that is significantly lower compared to that of the outer bulk. The achievement provides insight into how important a correct mechanism of small details can influence the overall material behaviour while opening possible studies on many other material quantities while respecting the fundamental mechanics at multiple scales.
Quantifying city-scale methane emissions based on ground-site, mobile, and satellite observations: an observing system simulation experiment (OSSE)
Authors: Wang Xinlu , Zhang Yuzhong , Wang Rui , Zhao Shuang
Published: March 2024

As a hotspot for greenhouse gas emissions, cities also represent a major opportunity for mitigating greenhouse gases including methane. However, city-scale methane emissions are often inadequately resolved in most of existing global/national “bottom-up” inventories, because of coarse-resolution and biased activity data or proxies used for constructing these inventories. The observation-based “top-down” inversion method provides an alternative approach to detect and quantify city-scale methane emissions, but it is often limited by the availability of useful city observations. Here, we construct a city-scale inversion system using a high-resolution (4 km) WRF-GHG transport model for a megacity, Hangzhou, in the densely populated Yangtze River Delta of China. We perform an observing system simulation (OSSE) to assess the ability of different observation systems (including ground-site, mobile, satellite observations, and their combinations) to constrain and resolve methane emissions from Hangzhou. The construction of “true” observations in OSSE accounts for main characteristics of different observations systems, e.g., temporally continuous but spatially sparse ground-site observations, spatially continuous but temporally sparse mobile observations, and coarse-resolution and low-precision satellite column observations. The results show that ground-level observations (including ground sites and mobile observations), though taken within the city, largely reflect signals from up-wind adjacent regions with large methane emission. The small local signals in the sparse ground-level observations have little constraining in the inference city posterior emissions and lead to large uncertainties. Joint inversion of ground and satellite observations with a wider modeling domain leads to a more accurate posterior emission of the targeted city, as it better captures and distinguish the contribution from surrounding regions. This result also underscores the accuracy of model transport for the city-scale emission estimation.
Non-point source pollution control in farmland by source-reduction strategies coupled with wetland treatment
Authors: Huang Cih-Jin , Fan Chihhao
Published: March 2024

In recent years, intensive agricultural practices have been adopted to enhance crop yields for food production. Therefore, the issue of agricultural non-point source pollution attracts attention due to the increasing use of fertilizer. The non-point source pollution control is diverse and difficult to manage because of the physical landscape and agricultural practices (e.g., topography, soil texture, farming, and irrigation). In addition, excessive fertilizer used to enhance crop yields would lead to land degradation. During a rainfall event, nitrogen and phosphorus from fertilizers would be washed into surface water and infiltrated into groundwater, resulting in the degradation of the aquatic environment.In this study, the use of slow-release fertilizer, compared to the reference of conventional chemical fertilizer, and a constructed wetland were adopted at a pilot-scale study. During a 40-day growing cycle, Brassica Chinensis L.(Pak-Choi) was chosen as the model crop, and two types (i.e., chemical fertilizer and slow-release fertilizer) of fertilizers were applied under pre-designed conditions. Two simulated intense rainfalls were operated on the 26th and 33rd days, and the surface runoff was introduced to the constructed wetland for further nutrient removal. The soil and water samples from the soil and wetland were analyzed for nutrient concentration variation, and the nutrient distribution and removal efficiency were assessed. The results showed that the chemical fertilizer has a higher nutrient loss rate. The nitrogen (N), phosphorus (P), and potassium (K) contents in the soil increased rapidly after top dressing and decreased significantly after the simulated rainfall. In contrast, slow-release fertilizer has a relatively steady nutrient loss rate during the growing cycle. Meanwhile, the chemical fertilizer has a higher total N, P, and K loss via infiltration and runoff than slow-release fertilizer. For the wetland treatment, the N removal for chemical fertilizer and slow-release fertilizer after 15 days was 24.4 % (i.e., from 19.99 ppm to 15.11 ppm) and 29.5 % (i.e., from 20.81 ppm to 14.68 ppm), the P removal amount was 38.1 % (i.e., from 0.21 ppm to 0.13 ppm) and 87.5 % (i.e., from 0.08 ppm to 0.01 ppm), respectively. Opposing to the conventional chemical fertilizers, the use of slow-release fertilizers could reduce nutrient loss. The constructed wetland demonstrated a positive effect on removing the nutrients in neighboring water, which reduced the impact of agricultural non-point source pollution.Keywords: Conventional farming, Best management practices, Slow-release fertilizer, Constructed wetlands
Winter Convective Mixing Mediating Coupling of N-gain and -loss in the Arabian Sea
Authors: Singh Arvind , Saxena Himanshu , Sahoo Deepika , Nazirahmed Sipai , Sharma Niharika , Rai Deepak Kumar , Kumar Sanjeev
Published: March 2024

Marine dinitrogen (N2) fixation fuels primary production and thereby influences the Earth’s climate. Yet, its geographical distribution and controlling environmental parameters remain debatable. We measured N2 fixation rates from the two spatially and physicochemically contrasting regions of the Arabian Sea during the winter monsoon: (a) the colder and nutrient-rich waters in the northern region owing to winter convection and (b) the warmer and nutrient-poor waters in the southern region unaffected by winter convection. We found higher N2 fixation rates at the surface of northern region due to convective mixing driven supply of phosphate (intuitively iron also) from the underlying suboxic waters, whereas the lower rates in the southern region are attributable to the limited supply of iron. N2 fixation was favoured by high nutrients concentration in the euphotic waters, whereas remained unaffected by nutrients availability in the aphotic waters. We conclude that diazotrophs dwelling in the euphotic zone chose phosphate and iron over fixed nitrogen-poor waters. However, we found that among oligotrophic waters, anticyclonic eddy extremes the barrier of fixed nitrogen supply and thereby elevates N2 fixation. While the Arabian Sea loses about 20 to 40% of the global ocean fixed nitrogen, we estimate that N2 fixation in the Arabian Sea offsets only up to 42% of its fixed nitrogen-loss by denitrification, but this offset could be higher if diazotrophic activity is further examined up to the deeper depths of the Arabian Sea.
Early Detection of Coal Fire inside the Coal Stock Pile by 4D ERT Monitoring
Authors: Yi Myeong Jong , Jeong Soocheol , Shin Seungwook
Published: March 2024

Coal-fired power plant requires huge storage of coal. During the storage of coal, heat is accumulated inside the stock piles and eventually results in the self-combustion or coal fire, which is a very serious problem in the fuel management and environmental aspect of the power plant facilities. To detect and forecast the coal fire, various methods had been suggested but there are no proven early warning technology until today. Since the resistivity of the coal is strongly affected by temperature, we suggested the ERT (Electrical Resistivity Tomography) monitoring technology to identify the heat accumulation inside the coal stock pile, which can eventually provide an early warning method of coal fire in the power plant facilities. To prove the technology, we prepared a small scale coal stock pile and electrodes were placed on the bottom of the stock pile. In the inside of the coal pile, temperature was continuously increased by using heating tools and ERT monitoring data were acquired for a few days until real coal fire take place on site. The whole ERT monitoring data were processed and we tried the 4D inversion to obtain changes of 3D resistivity distribution with temperature changes. In the 4D inversion results, we could identify the systematic change of resistivity values due to the heating process. Although resistivity is increased in the very early heating stage, increased resistivity is evident with the increase of coal temperature until self-combustion of coal. Therefore, we could prove that 4D ERT monitoring technology is a very promising method to detect and forecast the coal fire in the power plant facility.
Comparisons of Temporal Resolution of Atmospheric De-aliasing Products for the Analysis of Gravity Field Estimation
Authors: Bai Yinglun , Chen Qiujie , Shen Yunzhong
Published: March 2024

Despite the increasing accuracies of GRACE/GRACE-FO gravity field models through worldwide endeavors, the temporal aliasing effect caused by the imperfect background models used in gravity field modelling is still a crucial factor that degrades the quality of gravity field solutions. Recognizing the significant impact of temporal resolution in atmospheric de-aliasing models, this study specifically explores its influence on gravity field modeling across frequency, spectral, and spatial domains. Analysis indicates that elevating the temporal resolution from 3 hours to 1 hour has a negligible impact on gravity solutions in both frequency and spectral domains, and this effect is smaller than the variations caused by employing different atmospheric datasets. Nevertheless, in the spatial domain, increasing temporal resolution proves effective in mitigating LRI range-rate residuals, particularly in specific regions of the Southern Hemisphere at mid- and high-latitudes. Mass changes, expressed in Equivalent Water Height (EWH) and derived through P4M6 filtering, reveal that the maximum RMS value of spatial differences resulting from enhanced temporal resolution in atmospheric de-aliasing models can reach ~13.4mm in the sub-region of the Congo River Basin. However, using different atmospheric datasets can lead to a maximum difference of ~16.5mm. For the Amazon River Basin, the corresponding maximum discrepancy is ~18.1mm, and that caused by improving temporal resolution is ~9.4mm. Subsequently, the Congo River Basin is divided into several sub-regions using a lat-lon regular grid with a spatial resolution of 3 degrees. The subsequent time series results of mass changes reveal that the maximum contribution of temporal resolution and changes in the atmospheric datasets can reach 11.09% and 21.24%, respectively. These findings underscore the importance of accounting for temporal resolution in de-aliasing products when investigating mass changes at a regional scale.
Exploring How Machines Model Water Flow: Predicting Small-Scale Watershed Behavior in a Distributed Setting
Authors: Kim Dongkyun
Published: March 2024

This research created a deep neural network (DNN)-based hydrologic model for an urban watershed in South Korea using multiple LSTM (long short-term memory) units and a fully connected layer. The model utilized 10-minute intervals of radar-gauge composite precipitation and temperature data across 239 grid cells, each 1 km in resolution, to simulate watershed flow discharge every 10 minutes. It showed high accuracy during both the calibration (2013–2016) and validation (2017–2019) periods, with Nash–Sutcliffe efficiency coefficient values of 0.99 and 0.67, respectively. Key findings include: 1) the DNN model's runoff–precipitation ratio map closely matched the imperviousness ratio map from land cover data, demonstrating the model's ability to learn precipitation partitioning without prior hydrological information; 2) it effectively mimicked soil moisture-dependent runoff processes, crucial for continuous hydrologic models; and 3) the LSTM units displayed varying temporal responses to precipitation, with units near the watershed outlet responding faster, indicating the model's capability to differentiate between hydrological components like direct runoff and groundwater-driven baseflow.
Volcanic Debris Avalanche Deposits in the Coastal Range, Eastern Taiwan: Implications for Sedimentation and Tectonics of Arc-Continent Collision
Authors: Song Sheng-Rong , Lu Yi-Chia
Published: March 2024

The Coastal Range of eastern Taiwan is located at the plate boundary of Philippine Sea and Eurasia plates, which is the arc-continent collision zone. Abundant huge blocks, especially in Wushihpi area, which are predominantly composed of the volcanic rocks, are interbedded in the Paliwan Formation. Based on the field surveys, different occurrences of volcanic lithofacies have been recognized in outcrops. They are pillow breccias with and without white vesicle fillings, hyaloclastites, peperites rich and poor in zeolite fillings, lahars, lava flows with columnar structures, weathered brownish and reddish blocks in tuffaceous conglomerates and limestones. Those lithofacies can be grouped into three volcanic facies, the shallow marine, transitional from submarine to subaerial facies and subaerial facies. Those facies occur together chaotically and contact sharply. It infers that the volcanic rocks occurred in Wushihpi of Coastal Range is debris avalanche deposits and the source may come from different volcanic sequences of the Tulunshan volcanics, the major eruption products of Luzon Arc. Meanwhile, similar occurrences of debris avalanche deposits as huge blocks are also widely distributed in whole Coastal Range from the north to the south and Lutao. Those observations suggest that the sedimentation of debris avalanche and tectonics of slope failures may play major roles for denudation of volcanic arc during Taiwan arc-continent collision.   
Hydrodynamic responses of the Caspian Sea and Black Sea to greenhouse warming in a high-resolution ocean-atmosphere coupled climate model
Authors: Huang Lei , Timmermann Axel , Lee Sun-Seon
Published: March 2024

The Caspian Sea and Black Sea are the two earth's largest inland seas. Projections of their temperature, circulation and water balance responses to greenhouse warming remain largely uncertain. We investigated hydrodynamic changes of the two water bodies in a high-resolution CESM1 simulation, in which both the Caspian Sea and Black Sea are simulated by the ocean model (POP2). It turns out the mean surface water temperature of the two seas will increase by about 2.5°C in response to CO2 doubling in the atmosphere. Meanwhile, reduction of wind stress curl will lead to a spin-down of the main gyre circulations particularly in the Black Sea, which was also evidenced by a two-dimensional ocean model with joint effect of baroclinicity and bottom relief being considered. Our results also show that future evaporation enhancement due to surface warming will lead to a negative water balance for both seas, which is equivalent to a mean sea level trend of -0.1 m/year when CO2 concentration in the atmosphere doubles. These hydrodynamic changes are likely to exert large impacts on the aquatic ecosystems, fisheries, and human societies in the coastal areas.
Deep learning for X-band radar quantitative precipitation estimation using polarimetric measurements
Authors: Zhou Ruiyang , Gong Aofan , Li Bu , Qi Youcun , Ni Guangheng
Published: March 2024

Accurate estimation of surface precipitation with high spatial and temporal resolution is crucial for disaster weather detection and decision-making regarding water resources management. Polarimetric weather radar is an important instrument for quantitative precipitation estimation (QPE). Conventional parametric approaches, such as the radar reflectivity (Z) and rain rate (R) relations, cannot fully represent the spatial and temporal variability of clouds and precipitation due to parameterization errors and dependence on raindrop size distribution (DSD). Furthermore, these relations estimate rainfall on a grid-by-grid basis, preventing the incorporation of spatial information into precipitation estimation.In recent years, machine learning has made rapid advancements in non-linear fitting and feature extracting. Since 2020, multiple studies constructed MLP or CNN-based QPE models that used polarimetric radar observations to retrieve precipitation. These researches have consistently demonstrated that machine learning algorithms perform better than traditional parametric methods in different regions and climatic conditions(Chen & Chandrasekar, 2021; Li et al., 2023; Osborne et al., 2023; Tian et al., 2020; Zhang et al., 2021; Zhou et al., 2023).The aforementioned studies have highlighted the immense potential of deep learning for radar QPE, but they are based on S-band radar data. Because X-band radar has a shorter wavelength, the electromagnetic scattering characteristics of hydrometeors differ from those of S-band radar, especially for specific differential phase (kdp), which is closely related to rainfall. Furthermore, X-band radars have different spatial resolutions from S-band radars, which indicates that directly applying a model trained with S-band radar data to X-band radar data may introduce biases. Therefore, we develop a CNN-based QPE model using polarimetric measurements from X-band radars and compare its performance against traditional parametric methods. The input data for the CNN model is a matrix with dimensions (6, 9, 9). The matrix is composed of two matrices of size (3, 9, 9), which is the polarimetric measurements from the two lowest scan elevation angles and 9*9 surrounding range gates. This allows the input data to capture the spatial and physical characteristics of the precipitation field. The results reveal that the CNN-based model not only enhances the accuracy of radar QPE with a diminished bias but also provides a more precise depiction of the spatial distribution of precipitation in comparison to conventional methods.
An adaptive mapping framework for the management of peat soils: a new Irish Peat Soils Map.
Authors: Gilet Louis , Morley Terry , Flynn Raymond , Connolly John
Published: March 2024

Accurate mapping is necessary for effective management of peat soils to help reduce GHG emissions and improve environmental quality. However, mapping peat soils remains a major challenge: definitions of peat soils vary substantially, field data are sparse and difficult to produce, and remote sensing of limited use for converted peatlands. Using an Adaptive Mapping Framework developed for the Derived Irish Peat Map, this study describes our work to update the map with refined and new datasets. These include incorporation of areas considered to be underlain by shallow peat soils (≥ 10 cm and ≥ 8.6 % Organic Matter content), and augmentation of the overall test dataset with an additional ~ 20,000 points.The workflow for map generation employed 20 Decision Tree Output Maps (DTOMs), aggregated into 33 Map Combinations (MCs). The MC selected for the update had the highest accuracy metrics (≥ 80 %), consisting of DTOMs with a user accuracy ≥ 60 % and assessed over a minimum number of test points ≥ 50. The resulting map reveals peat to underlie 1.66 M ha of Ireland (~ 23.3 % of the country), with an overall accuracy of 84 % and a F1 score for peat areas of 85 %. This extent is 13.2 % larger than that delineated in previous versions and at least 18.8 % larger than areas presented in other previous maps. The methodology also allows transparency from which data sources the different peat layers of the new map are coming from and to distinguish different peat thickness ranges (≥ 10 cm, ≥ 30-40 cm).We demonstrate the utility of the mapping framework to facilitate the production of a more reliable peat map than previous mapping attempts. This approach has potential relevance for peat mapping elsewhere, in areas containing disparate datasets (e.g., land cover, soil map, etc.), covering different time periods, or employing different production methods. The accuracy metrics generated also suggest that the approach can be used as a basis for implementing or updating European and national regulations concerning carbon-rich soils in comparable settings to those encountered in Ireland.
Identifying potential drivers of land-atmosphere coupling variation under climate change by explainable artificial intelligence
Authors: Huang Feini , Shangguan Wei , Jiang Shijie
Published: March 2024

Land-atmosphere coupling (LAC) involves a variety of interactions between the land surface and the atmospheric boundary layer that are critical to are critical to understanding hydrological partitioning and cycling. As climate change continues to affect these interactions, identifying the specific drivers of LAC variability has become increasingly important. However, due to the complexity of the coupling mechanism, a quantitative understanding of the potential drivers is still lacking. Recently, deep learning has been considered as an effective approach to capture nonlinear relationships within the data, which provides a useful window into complex climatic processes. In this study, we will explore the LAC variability under climate change and its potential drivers by using Convolutional Long Short-term Memory (ConvLSTM) together with explainable AI techniques for attribution analysis. Specifically, the variability of the LAC, defined here as a two-legged index, is used as the modeling target, and variables representing meteorological forcing, land use, irrigation, soil properties, gross primary production, ecosystem respiration, and net ecosystem exchange are the inputs. Our analysis covers global land with a spatial resolution of 0.1° × 0.1° every one day during the period 1979–2019. Overall, the study demonstrates how interpretable machine learning would help us understand the complex dynamics of LAC under changing climatic conditions. We expect the results to facilitate the understanding of terrestrial hydroclimate interactions and hopefully provide multiple lines of evidence to support future water management.
Vivianite verified in early Cambrian strata in northwestern China: Implications for phosphorus recycling in ancient anoxic oceans
Authors: Cao Xuyang , Ju Pengcheng , Han Yigui , Lu Lihui , Shao Dong
Published: March 2024

In modern low sulfate and anoxic (euxinic) waters, the precipitation of mineral vivianite (an easily oxidized hydrated ferrous-iron phosphate) has played a crucial role in restraining the limiting nutrient element phosphorus (P) recycling back to the water column and consequently decreasing primary productivity. Although such low sulfate and anoxic conditions were widespread in ancient coastal oceans, vivianite has not been directly discovered in the paleo-sediments, which hampers the understanding of P cycling in ancient anoxic environments. Here, we combined techniques of scanning electron microscopy-energy dispersive X-ray spectroscopy, focused ion beam-transmission electron microscopy and P K-edge X-ray absorption near edge structure spectroscopy to analyze samples of P-bearing siliceous rocks and shales from the early Cambrian Yurtus Formation in the Tarim Craton, northwest China. Our results have demonstrated that micron- to nano-scale vivianite crystals are well preserved in the rocks and the vivianite dominates the P phase in some samples. The cherty matrix of the rocks most likely increased the chances of preservation of the oxidation-sensitive vivianite. In light of recent advances, we suggest that vivianite was a crucial P phase in ancient continental margin sediments, spanning most time from the Neoarchean to the early Cambrian. During this interval, the precipitation of vivianite was likely aided by the prevalent dynamic ocean euxinic conditions linked with the seawater sulfate reservoir and the flux of organic matter settling. We propose a negative feedback mechanism in which vivianite precipitation from ancient euxinic waters restricted P availability for biota, reduced marine primary productivity, and possibly abated the rate of Earth's oxygenation and associated evolution of life. This work was financially supported by NSFC projects (grants 42072264, 41730213) and Hong Kong RGC GRF (17307918).
Integrated Prediction Model for Cadmium Toxicity in Oxidized Freshwater Sediment: Emphasis on the Role of Fe Oxides and Validation with Hyalella azteca
Authors: Jeong Buyun , Shim Gunwoo , An Jinsung , Nam Kyoungphile
Published: March 2024

The evaluation of metal toxicity in sediment has traditionally involved measuring sulfide concentrations and considering organic carbon content through the sediment biotic ligand model. This model operates on the assumption that the predominant formation of insoluble metal sulfides (MeS) renders the metals unavailable for uptake by benthic organisms. Specifically, in cases where the quantity of metals exceeds that of sulfides, the model postulates that the surplus metals will partition to organic carbon. It holds relevance in anoxic environments where sulfides and organic carbon play pivotal roles in metal binding. However, heavy metals susceptible to redox changes may be released from both MeS and organic carbon, particularly in oxidized sediments. Literature indicates elevated concentrations of dissolved Cadmium under oxidizing conditions compared to reduced sediments. Such liberated metals subsequently re-adsorb onto Fe oxides, another significant phase for metal binding.To enhance cadmium toxicity prediction, we propose an advanced model that considers contributions from both Fe oxides and organic carbon, in addition to sulfide, in oxidized sediment. Partition coefficients (Kd) for both phases were determined using the Windermere Humic Aqueous Model, version 7 (UK Centre for Ecology and Hydrology, 2012), and the relationship with pH was derived through curve fitting to optimize data fitting. Previous studies' data align well with the predicted Kd values. A comprehensive model equation for determining a total Kd, incorporating these Kd values of Fe oxides and organic carbon contents, was formulated. Upon comparison with experimental data from sediment samples collected from 21 different regions in South Korea, the model exhibited accurate predictions within one order of magnitude.To validate the proposed model, a toxicity test was conducted using a benthic invertebrate, Hyalella azteca, with the same sediment samples. While the previous model predicted toxicity, the observed mortality was less than 24%, indicating non-toxicity to the organism. The new model accurately assessed toxicity and serves as a valuable tool for predicting cadmium toxicity in oxidized sediment.
Typhoon precipitation forecasting based on Satellite Imagery Sequencing and Generative Adversarial Networks
Authors: Yang Nan , Li Xiaofeng
Published: March 2024

Precipitation forecasting with Typhoons (especially nowcasting), a short-term (up to two hours) high-resolution forecasting, is arguably one of the most demanding tasks. Traditional forecasting methods contain 1) Ensemble numerical weather prediction (NWP) systems and 2) advect precipitation fields with radar-based wind estimates via optical flow techniques. The former simulates coupled physical equations of the atmosphere to generate multiple precipitation forecasts. In the latter methods, motion fields are estimated by optical flow, smoothness penalties are used to approximate an advection forecast, and stochastic perturbations are added to the motion field and intensity model. However, these methods either do not meet the requirement on time or rely on the advection equation. These drawbacks limit the performance of precipitation forecasting. Satellite imagery benefits from machine learning technologies, e.g., deep learning, which can be regarded as video frames and is expected to be a promising approach to solving precipitation nowcasting tasks.Convolutional neural networks (CNN), recurrent neural networks (RNN), and their combination are used to generate future frames with the previous context frames. In general, CNN is employed to capture spatial dependencies, while RNN aims to capture temporal dependencies. However, CNN suffers from inductive bias (i.e., translation invariance and locality), which cannot capture location-variant information (i.e., natural motion and transformation) and fails to extract long-range dependencies. As for RNN, the process of long back-propagation is time-consuming because of its recurrent structure. Therefore, the above drawbacks lack these methods’ operational utility and can not provide skillful precipitation forecasting.This work proposes a fire-new artificial intelligence model to achieve skillful precipitation forecasting with Typhoons. The satellite Imagery containing precipitation is made into a series of sequences, each containing multiple frames over time. We re-design the traditional CNN-RNN-based architecture that can solve the problem of information loss/forgetting and provide skillful precipitation forecasting. Furthermore, we introduce the generative adversarial strategy and propose a novel random-patch loss function. It ensures that the model can generate high-fidelity precipitation forecasting. In summary, our proposed model simplifies the complex TC precipitation forecasting into a video prediction problem, greatly avoiding many uncertainties in the physical process and facilitating a fully data-driven artificial intelligence paradigm using deep learning and satellite image sequencing for discovering insights for weather forecasting-related sciences.
The impact of converting open-field cultivation to greenhouse cultivation on the accumulation of organic carbon in coastal soil
Authors: Tian Yu , Liu Jing Jing , Lu Shenggao
Published: March 2024

The conversion of open fields to greenhouse cultivation leads to an increase in the amount and frequency of fertilization, as well as an increase in tillage intensity, which significantly affects soil organic carbon turnover and sequestration. In this study, four types of soils were selected in the coastal area of southeast China based on a sequence of greenhouse cultivation years of 0, 8, 18, and 36. The study fractionated the soil into four organic fractions: free mineral-associated organic carbon (f-MAOC), occluded mineral-associated organic carbon (o-MAOC), free particulate organic carbon (f-POC), occluded particulate organic carbon (o-POC), using particle size and density separation. The organic carbon content and natural abundance of 13C were measured for each of these fractions, as well as for the bulk soil. Key findings include a significant increase in bulk soil organic carbon with extended greenhouse cultivation, although differences between 18 and 36 years were not significant (27.4 g kg-1 and 31.7 g kg-1 respectively). o-MAOC and o-POC contents increased initially, then declined after 18 years. Notably, f-POC content significantly rose after 36 years, reaching 9.91 g kg-1. The δ13C values for f-MAOC, o-MAOC, and f-POC showed similar increasing trends, peaking after 18 years. The carbon flow analysis revealed the main carbon turnover pathway from f-POC to o-MAOC, with reverse transfers occurring after 18 and 36 years. It highlighted a saturation limit in the sequestration capacity of occluded organic carbon and significant accumulation of labile organic carbon due to long-term greenhouse cultivation. These findings offer new insights into carbon management in agricultural soils.
Global marine ecosystem response to a strong AMOC weakening under low and high emission scenarios
Authors: Boot Amber A. , Steenbeek Jeroen , Coll Marta , von der Heydt Anna S. , Dijkstra Henk A.
Published: March 2024

Marine ecosystems provide several important services for the Earth System and society in the form of, for example, carbon export, food and income. These ecosystems, and the functions they provide, are under threat from anthropogenic climate change, pollution and overfishing.  Besides being a large risk for marine ecosystems, anthropogenic climate change might also lead to passing tipping points in the Earth System, leading to relatively fast and strong additional changes to the climate system.  A tipping element in the Earth System is the Atlantic Meridional Overturning Circulation (AMOC). Tipping of the AMOC will disrupt the climate system and lead to changes in temperature, precipitation, wind fields, ocean circulation and the carbon cycle. In this study, we look at the effect of a strong AMOC weakening on global marine ecosystems. We do this by forcing a state-of-the-art model, the Community Earth System Model v2 (CESM2), with low (SSP1-2.6) and high (SSP5-8.5) emission scenarios, and with an additional freshwater flux in the North Atlantic from 2015 to 2100. Since the ecosystem component of the CESM2 is limited, we use the CESM2 output in a marine ecosystem model, EcoOcean v2. EcoOcean simulates 52 functional groups including mammals, birds, zooplankton, benthic species and fish on a 1° horizontal grid, and reconciles food web dynamics with a dynamic niche model. EcoOcean is forced with phytoplankton biomass and temperature fields from the CESM2 simulations and this enables us to determine the effect of the AMOC weakening in CESM2 on marine ecosystems. In CESM2, the weakening of the AMOC has a large impact on phytoplankton biomass and temperature fields through various mechanisms including changes in stratification and mixed layer depth, changes in sea-ice cover, and changes in upwelling velocities. Through these mechanisms, the three dimensional distribution of nutrients in the ocean is altered which directly affects the primary producers in CESM2. In EcoOcean, we see that almost all functional groups are negatively impacted by an AMOC weakening. The strongest net effect is seen in the high emission scenario, but the relative effect of the AMOC weakening is larger in the low emission scenario.  There are some functional groups, e.g. pinnipeds, that show a strong decrease that closely follows the AMOC weakening. These results show that marine ecosystems will be under increased threat if the AMOC strongly weakens. Furthermore, the results show how tipping in the climate system can negatively impact marine ecosystems and thereby put an additional stress on socio-economic systems that are dependent on fishery industries as a food and income source.  
Short-period (400 kyr) pulsation of the Réunion plume
Authors: Famin Vincent , Quidelleur Xavier , Michon Laurent
Published: March 2024

Many hotspots worldwide display evidence of fluctuating magmatic emplacement rates in their history, at periods of 1-20 Myr, indicative of changing melt production within underlying mantle plumes. Here we report unprecedentedly short fluctuations of magmatic activity in the Réunion hotspot, emblematic because it started with the Deccan traps suspected to have caused the Cretaceous-Paleogene mass extinction. Using K-Ar geochronology, field observations, and geomorphology, we reconstructed the volcanic history of La Réunion and Mauritius islands, the two latest manifestations of the Réunion hotspot. Our reconstruction reveals coeval magmatic activity pulses and rest intervals for the two islands over the past 4 Ma. The period of these pulses, of ~400 kyr, is an order of magnitude shorter than any fluctuation found on other hotspots. Given the distance between La Réunion and Mauritius (~230 km), this synchronous short-period pulsation of the Réunion hotspot cannot stem from the lithosphere (≤70 km thick), and must be attributed to deeper plume processes. Moreover, this ~400 kyr periodicity coincides with the recurrence time of magmatic phases in the Deccan traps, suggesting that the pulsation began with the initiation of the hotspot. We propose that the Réunion plume is regularly pulsing with a periodicity of ~400 kyr, possibly since the Cretaceous-Paleogene transition, thus delivering extremely short-period waves of magma to the surface, synchronous over hundreds of kilometers. Understanding the geodynamic causes of this superfast beat of the Réunion plume is the objective of the four-year project “Plum-BeatR”, funded by the Agence Nationale de la Recherche (ANR- 23-CE49-0009), starting in 2024.
Machine learning for reconstructing the primary carbon contents of mid-ocean ridge basalts
Authors: Lei Tian-Ting , Liu Jia , Xia Qun-Ke
Published: March 2024

One of the primary locations of mafic magma production on Earth is the global mid-ocean ridge system, with basalts erupted from these ridges serving as valuable probes for assessing the compositional variability of the upper mantle and exploring the deep carbon cycle. However, directly measuring carbon contents in mid-ocean ridge basalts (MORBs) has proven challenging due to degassing during magma ascent. Early investigations indicate that some incompatible-trace-element- depleted and -enriched MORBs avoid heavy degassing, and show a narrow range of CO2/Ba ratios, which was generally applied to reconstruct the primitive CO2 content of global MORBs. However, increasing studies reveal significant variability in the CO2/Ba ratios of MORBs. Here, we compiled a dataset including the geochemical compositions of MORB glasses and melt inclusions for which studies supported no significant degassing. Based on it, we constructed a supervised machine learning (ML) model capable of accurately predicting CO2 contents in individual samples using the selected elemental contents. Applying our model to a global MORB database reveals that CO2 contents and CO2/Ba ratios of global MORBs are highly variable, highlighting the significance of mantle heterogeneity, which can be attributed to the interactions with deep-sourced plume, or the recycled components associated with the big subduction zone. Our findings underscore the potential of ML as a powerful tool for uncovering hidden structural patterns in complex geological data, shedding light on the intricate interplay between carbon, mantle composition, and Earth's long-term geological processes.
Observation of positive Narrow Bipolar Events in the Mediterranean region
Authors: Kolmašová Ivana , Santolík Ondřej , Soula Serge , Defer Eric , Zhu Yanan , Lán Radek , Pedeboy Stéphane , Kolínská Andrea
Published: March 2024

Narrow Bipolar Events (NBEs) are brief intracloud (IC) discharge processes that generate powerful radiation in the HF and VHF radio bands. NBEs typically occur in isolation, but they have also been identified as initial events in IC lightning flashes. Their incidence is statistically correlated with the strength of convection. NBEs can exhibit both polarities and usually occur in the upper regions of the thundercloud.We present, for the first time, properties of NBEs detected in the Mediterranean region. The dataset comprises 37 events recorded by broadband magnetic loops located at two sites in France. The events were identified using the list of NBEs from 2022 provided by the Earth Network. The frequency range of our broadband sensors enabled us to obtain detailed shapes of NBE pulses. We calculated rise times, full width at half maximum times, and zero-crossing times of NBE pulses to facilitate comparisons with observations of NBEs in other parts of the world. The majority of NBE pulses observed in the Mediterranean region were isolated events occurring above the land and displaying a simple bipolar waveform with an overshoot peak of the opposite polarity. For two events, we supplemented our observation with the data from the SAETTA (Suivi de l’Activité Electrique Tridimensionnelle Totale de l’Atmosphère) lightning mapping array. Additionally, we estimated the altitude of the NBE events and placed our observations in the meteorological contexts to determine why NBE occurrences in the Mediterranean region have been overlooked until now. 
Geophysical Understanding of Coupled Thermal-Hydro-Mechanical Dynamics in Rock Salt During Heating
Authors: Wu Yuxin , Wang Jiannan , Chen Hang , Luo Linqing , Otto Shawn , Kuhlman Kristopher , Zheng Liange , Birkholzer Jens
Published: March 2024

The distinctive properties of salt, such as low permeability, high thermal conductivity, and self-sealing features, make it a suitable medium for storing heat-generating radioactive waste. Understanding the thermal, hydrological, and mechanical (THM) processes, including permeability evolution and brine migration around the heat source, is crucial for safety. The Brine Availability Tests in Salt (BATS) at the Waste Isolation Pilot Plant were conducted to investigate these processes, employing an array of sensors and techniques like electrical resistivity tomography (ERT), fiber optic distributed temperature sensing (DTS), and strain sensing (DSS). These techniques monitored temperature changes, brine movement, and stress conditions in the salt.This presentation highlights the results from ERT, DTS, and DSS in controlled heating experiments, focusing on the response differences across various heating events. The analysis, augmented by Discrete Element Models (DEM) simulations, showed that resistivity changes were sensitive to temperature and brine movement. A significant decrease in resistivity, especially beyond temperature effects, indicated brine migration or permeability changes. The DTS and DSS data captured the evolving thermal and mechanical responses of the salt to heating and cooling cycles, including salt deformation, and creeping towards the drift wall.Joint analysis of ERT, DTS, and DSS data provided an integrated understanding of THM processes in salt during heating. Consistent heating and brine migration patterns were observed across different events. Ongoing work aims to combine all monitoring data for a deeper insight into the coupled behaviors in salt formations, offering valuable calibration and benchmarking for numerical models.
From Dome to Duplex: An Intriguing Case of Convergent Gravitational Collapse in Central Australia
Authors: Rey Patrice , Ibrahim Youseph , Whitney Donna , Teyssier Christian , Roger Françoise , Bosse Valérie , Cenki Bénédicte
Published: March 2024

Defying traditional plate tectonics, the Alice Springs Orogeny (ASO) developed between 450 to 300 Ma deep within the interior of the Australian continent, at significant distances from any plate boundaries. The region NE of the Amadeus basin presents a surprising geological association of the Entia gneiss dome, exhuming high-grade Paleoproterozoic gneisses alongside a nappe complex comprising high-grade rocks of the Harts Range Metamorphic Complex and Paradise Nappes and their lower-grade Neoproterozoic covers. These isoclinally folded nappes were thrust onto the lower-grade Ruby Gap duplex and White Range duplex, which consist of Amadeus basin sequences, overlapping the Amadeus basin. Collectively, these nappes constitute the Arltunga Nappe Complex. Understanding of the regional geology took a transformative turn when detrital zircon data revealed that the HRMC, into which the Entia dome was emplaced, did not belong to the Paleoproterozoic basement. Instead, these gneisses are the metamorphic equivalent of Neoproterozoic to Palaeozoic marine siliciclastic and limestone sediments of the Amadeus Basin. A transect from the Entia Dome to the Ruby Gap duplex reveals conformable structures that juxtapose a high-grade extensional domain (the Entia dome), and a low-grade contractional domain (the Ruby Gap and White Range duplexes), across a transitional zone containing the Bruna décollement zone and the Illogwa shear zone. Exhumation of the Entia Dome and shearing and thrusting of the Arltunga Nappe Complex are age-bracketed between ~345 and ~310 Ma. The structural continuity and geochronology suggest that these features are synchronous and interrelated. Numerical experiments support a tectonic model in which the dome and nappe complex formed synchronously because of the convergent gravitational collapse of the Paleozoic Harts Range Rift basin. In this model, the Entia dome was emplaced into the 30-40 km deep Harts Range Rift basin, the base of which reached granulite facies metamorphism and melting at ~470 Ma. The density contrast between the Neoproterozoic to Paleozoic sedimentary basin infill and the metamorphic Paleoproterozoic basement created a strong horizontal pressure gradient, leading to significant gravitational stresses acting laterally towards the basin. As the geotherm in the basin reached melting conditions, these gravitational forces may have overcome viscous strength to drive centripetal flow, forcing the exhumation of the Entia Dome and the development of gravity nappes at the Earth’s surface.