bluuebunny/crossref_metadata_2025 huggingface dataset:
Using pyroclastic textures as an index for understanding the impact edifice collapse has on the subvolcanic plumbing system. 
Authors: Mills Shannen , Procter Jonathan , Zernack Anke , Mead Stuart , Schipper Ian , Stevenson Andrew , Arhatatari Benedicta , Thompson Darren , Fleming Joseph
Published: March 2024

Depressurisation from edifice collapse events can impact the subvolcanic plumbing system as a propagation wave moves down through the system shifting the fragmentation zone. Understanding how this influences the eruptive behaviour at a volcano is important for understanding changes in hazards following a large edifice collapse event. Mt. Taranaki has experienced at least 16 collapse events within its > 200 kyr history. Two of the largest collapse events the 27.3 ka Ngaere and 24.8 ka Pungarehu debris avalanches occurred in close succession and were encompassed by the Poto and Paetahi tephra formations, made up of 28 subplinian eruptions over ~ 4,000 years. This eruptive period provides a unique opportunity to examine and understand the influence that edifice collapse events have on the subvolcanic plumbing system. Using 3D Micro-Computed Tomography at the Australian Synchrotron bubble textural analysis was undertaken to investigate the changes in pyroclastic textures from large explosive eruptions and how these change following an edifice collapse event. The high-resolution 3D scans indicate that the eruptive products from the Poto and Paetahi Formations are dominated by small bubbles (2.7 x 10-7 mm3) with high bubble number densities ranging from 2.56 x 1015 cm-3 to 1.74 x 1016 cm-3. Bubble size distributions for the Poto and Paetahi Formations indicate a range of bubble nucleation and growth processes occurring within the subvolcanic plumbing system below Mt. Taranaki initiating at different depths. Early onset of bubble nucleation and periods of magma stalling are indicated by the presence of large, coalesced bubbles within the eruptive products, while the dominance of smaller bubbles indicates a fast ascent of magma within the system with nucleation occurring higher up in the system. Changes are seen in the textural characteristics of pyroclasts produced following the 27.3 ka 5.85 km3 Ngaere collapse which depressurized the shallow magmatic system and shifted the fragmentation zone. Following the 24.8 ka 7.5 km3 Pungarehu collapse ~2,500 years later the same influence is not seen, due to the cone not having enough time to rebuild between edifice collapse events. The results from this study show that the depressurisation and subsequent propagation wave are dependent on the height above the plumbing system not just the mass removed and therefore two major collapses in close proximity do not show the same systematic impact on the fragmentation zone.
Algorithmic optimisation of key parameters of OpenIFS. Implications on ensemble forecasts
Authors: Tuppi Lauri , Ekblom Madeleine , Köhler Daniel , Ollinaho Pirkka , Järvinen Heikki
Published: March 2024

Numerical weather prediction models contain physical parameters describing various small-scale phenomena as a part of parameterization schemes. These parameters are uncertain and can be tuned manually, or more efficiently, using algorithmic methods. Algorithmic tuning is an appealing approach to increase transparency and repeatability of the tuning process. Often, the focus of model tuning is on deterministic forecasts and the effect of model tuning on ensemble forecasts receives little to no attention. This presentation exemplifies how a superficially justifiable choice of activating initial state perturbations in algorithmic tuning of model parameters can have a systematic (and potentially detrimental) effect on the spread-skill relationship of ensemble forecasts.This presentation continues directly from the poster presented last year in EGU2023 (Tuppi et al. 2023). This time, the objective is to understand how algorithmic optimization of a weather model affects the skill of ensemble forecasts. This presentation focuses on ensemble forecasting-based verification of the tuned model versions using root-mean squared error/spread relationship, continuous ranked probability score, and filter likelihood score. The headline results show that ensemble forecasts run with tuned model parameters experience a significant reduction of spread when initial state perturbations are active during the tuning of the parameters. However, both choices of tuning the model with initial state perturbations activated and deactivated lead to optimal deterministic forecasts. This behavior likely arises from conflicting interests between the method to generate initial state perturbations and the method of determining goodness of the parameter values during tuning.Tuppi, L., Ekblom, M., Ollinaho, P., and Järvinen, H.: Algorithmic optimisation of key parameters of OpenIFS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4817, https://doi.org/10.5194/egusphere-egu23-4817, 2023.
Tidal influence on heat exchange and temperature dynamics in salt marshes
Authors: Xu Xinghua , Yu Xiayang , Xin Pei
Published: March 2024

Soil temperature has a marked effect on ecological processes in salt marshes and is significantly affected by tidal fluctuations. Periodic tidal inundation modifies the heat exchange between marsh sediments and the atmosphere, and also induces additional heat exchange between the sediments and tidal water. Tide-driven porewater flow further modulates heat transfer within the sediment, a process complicated by seasonal variations in atmospheric and tidal temperatures. In addition, macropores such as crab burrows are common in salt marsh sediments, and they are expected to regulate heat exchange and temperature distribution within the salt marshes by altering water movements. This study aims to explore how spring-neap tides and atmospheric conditions collectively influence heat exchange and temperature dynamics in salt marshes. We developed a marsh-creek model incorporating sediment-atmosphere/water heat exchange and validated it against laboratory experiments. Extending the model to the field scale, we analyzed temperature dynamics across the marsh and heat fluxes at the sediment-atmosphere/water interfaces over an annual cycle. We also compared simulation outcomes of water and heat dynamics in scenarios with and without macropores. Finally, we discussed the implications of our findings for accurately assessing tidal and atmospheric heat exchange and the associated temperature variations.
Exploring the impacts of changes in solar radiation on ecohydrological variables
Authors: Wang Yiran , Meili Naika , Fatichi Simone
Published: March 2024

Several geoengineering projects are designed to modify solar radiation to limit global warming. These changes in solar radiation can have impacts on ecohydrological systems which are poorly quantified. In this study, CMIP6 outputs were used to calculate sensitivities of global and local near-surface meteorological variables to solar radiation changes. These sensitivities were applied to the currently observed climate to perturb meteorological variables in response to changes in solar radiation. These new conditions were used as inputs to a mechanistic ecohydrological model (T&C) to analyze the partitioning and changes in energy and water fluxes and the response of vegetation productivity in different biomes and climates. Specifically, we run two simulation scenarios to understand the solar radiation impacts on ecohydrological systems. The first scenario focuses only on changes in solar radiation, while the second scenario considers the combined effects of solar radiation changes and its climate feedback. The results show that, in the absence of climate feedback, changes in solar radiation are mainly reflected in changes in sensible heat, with less impact on the hydrological cycle, and vegetation productivity is positively and linearly correlated with changes in solar radiation. When climate feedback is included, the effects on latent heat and hydrologic variables are more pronounced, and the response of vegetation productivity to negative and positive solar radiation changes tend to be asymmetric. These results provide a basis for how land-surface processes could respond to regional brightening and dimming and future solar geoengineering programs.
Indian Summer Monsoon Rainfall trends over 1979-2022 driven by ocean warming and anomalous wind patterns.
Authors: Joseph Ligin , Skliris Nikolaos , Dey Dipanjan , Marsh Robert
Published: March 2024

India receives 80% of its annual rainfall during the Indian Summer Monsoon (ISM) season from June to September. The climate model simulations of Coupled Model Intercomparison Project 6 (CMIP6) robustly indicate a strengthening of the Indian summer monsoon rainfall in a warming climate, despite a reduced land-sea thermal contrast. In this study, we analysed the ISM precipitation trend over India from 1979 to 2022 using rain gauge, satellite-derived, and atmospheric re-analysis data. The results show a broad-scale increasing precipitation trend over major parts of India. However, there is strong spatial variability, with a pronounced precipitation increase over Western India and decreasing precipitation in parts of north-eastern India. The precipitation trend pattern is associated with sea surface temperature (SST) and wind anomalies over the Indian Ocean. Observations indicate a basin-scale warming of the Indian Ocean (IO) that is more prominent in the west equatorial region and Arabian Sea (AS), altering the east-west SST gradient over this period, which is associated with increased equatorial winds during the summer monsoon period. Evaporation correspondingly increases over the Indian Ocean, with widespread increases along the typical atmospheric moisture transport pathway over the western Indian Ocean during the summer monsoon, driven by both ocean surface warming and increasing winds. Increased evaporation results in more moisture being available in the atmosphere over the western Indian Ocean, which subsequently feeds ISM precipitation. Furthermore, a strong correlation between the AS moisture transport and the ISM rainfall has been noticed over the central and western parts of India, where increased precipitation trends exist. A moisture budget trend analysis over Western India suggests that the large increase in moisture convergence in this area is driven by increased moisture entering from the AS concomitant with strongly reduced outgoing moisture transport through the eastern and northern boundaries. A detailed analysis shows that the increased moisture convergence in Western India is predominantly attributed to changes in the wind pattern driven by anomalously reduced winds in the northern part of the peninsula. In addition, the teleconnections between ISM rainfall and large-scale natural climate variability modes such as ENSO and IOD were also shown to modulate precipitation variations over India during the considered period at inter-annual to multi-decadal scales. 
Extracting planes from sparse 3D LiDAR data with measurement noise model
Authors: He Linkun , Li Bofeng
Published: March 2024

Global Navigation Satellite System (GNSS) can provide accurate absolute position but requires fine observational conditions. In urban canyons and indoor scenes, GNSS suffers from severe performance degradation and is even unavailable. Thereby, to provide ubiquitous positioning solutions, it is very necessary to incorporate other complementary sensors. A popular option is the 3D LiDAR sensor, which emits its own light and thus is robust to illumination variation. 3D LiDAR sensors can efficiently capture plentiful point patterns of the ambient environment. Besides perception tasks, the obtained point clouds are also used for relative localization in a registration fashion, known as the LiDAR odometry (LO). Generally, LO is based on structural information, where edge and planar features are extensively exploited.In this work, we propose a novel method aiming to efficiently extract planes from the sparse and noisy 3D LiDAR point clouds. To fully exploit the scanning pattern of this sensor, our method follows a framework of point-to-line-to-plane. The point cloud is firstly projected onto a range image by investigating the azimuth and elevation of each point. In the point-to-line stage, consecutive flat points in a column are grouped into line segments, where a new flat point detector is introduced. In the line-to-plane stage, we extend the classical line extraction method, i.e., Douglas-Peucker algorithm, to find planes in line segments. Considering the over-segmentation caused by occlusion and deformation, we finally conduct region growing and merging to acquire more complete results. Most importantly, we bridge the measurement noise model and the parameter uncertainty via error propagation to determine reasonable thresholds throughout our method.We test the proposed method on datasets collected by various LiDAR sensors. The experiments are conducted in indoor scenes and urban scenes, which contains abundant planar objects such as walls and building facades. Three point-level metrics, namely positive predictive value (PPV), true positive rate (TPR) and F1 score, are employed for quantitative evaluation. The average PPV, TPR, F1 of the proposed method are 89.92%, 86.38% and 88.11%, respectively. The results show that the proposed method is able to recover the dominant planar structure, which is valuable to LO. Moreover, compared to the rotation rate of the LiDAR sensor, which is generally set to 10 Hz, the average runtime of the proposed method is 15.6 ms/frame, so it is qualified for online operation.
Insights into the genesis and geological significance of iron-manganese precipitates in the Baltic Sea, Gulf of Finland seafloor
Authors: Liira Martin , Ojap Johanna Maria , Lepland Aivo , Suuroja Sten , Ausmeel Markus , Szymczycha Beata , Hong Wei-Li , Böttcher Michael E. , Virtasalo Joonas , Mikenberg Hannah , Heinsalu Atko , Roopõld Krete
Published: March 2024

This study investigates the distribution and geological implications of iron-manganese (Fe-Mn) oxyhydroxide precipitates on the seafloor of the Gulf of Finland, with a particular focus on associated pockmarks and Fe-Mn concretions. The formations occur in regions devoid of modern sediment deposition, revealing exposure of late glacial glacio-lacustrine varved clays, glacial tills, or bedrock. Pockmarks, up to 3 m deep and 30-60 m wide, coexist with Fe-Mn concretions, exhibiting sub-vertical walls and microbial colonies, suggesting active seepage of chemically reduced fluids from underlying strata.Globally occurring Fe-Mn concretions, sedimentary bodies primarily composed of iron and manganese compounds, exhibiting round or crust-like shapes formed through redox-driven processes in seabed environments. Microbial activity accelerates necessary redox reactions, influencing the growth of these concretions. The study delves into the morphological, chemical, and mineralogical characteristics of Fe-Mn concretions in the Gulf of Finland, identifying two distinct types—concentric and crust-like—with varied compositions, hinting at diverse formation mechanisms.Elevated concentrations of precious and rare earth metals in these concretions raise interest for potential industrial applications. Fe-Mn concretions also serve as valuable indicators of sedimentary processes' geological history, exposing environmental changes over time, including anthropogenic pollution. Despite advancements, the genetic types of Fe-Mn concretions in Estonian sea areas remain elusive, emphasizing the need for further research.The study integrates findings from three recent international expeditions to the central Gulf of Finland, aiming to comprehensively understand the relationships between fluid seepage, Fe-Mn concretions, and seafloor features. These expeditions collect representative materials, focusing on the timing and controls of groundwater discharge, mineral precipitation, and associated seafloor microbial processes. The preliminary results provide insights into the intricate geological processes underlying the observed seafloor features.In conclusion, this collaborative effort contributes valuable information about the distribution and genetic characteristics of Fe-Mn precipitates and associated features in the Gulf of Finland. The simultaneous investigation of pockmarks and Fe-Mn concretions, along with their geological implications, enhances our understanding of these complex marine environments. Further research is essential to unravel the exact genetic types of Fe-Mn concretions in Estonian sea areas and to refine our knowledge of the dynamic interactions between fluid seepage, mineral precipitation, and microbial processes on the seafloor.
Improvements in fog predictions via a modified reconstruction of moisture distribution using the Weather Research and Forecasting(WRF) model
Authors: Kim Eunji , Park Soon-Young , You Jung-Woo , Lee Soon-Hwan
Published: March 2024

Since fog is an important weather phenomenon affecting the traffic safety, accurate fog forecasting should be attained to minimize meteorological disasters. Most fog forecasts determine only the presence or absence of fog based on less visibility than 1 km, which is known as the visibility diagnostic method. During this process, fog could be predicted by the visibility calculated in the numerical weather prediction (NWP) model using the cloud liquid water content (LWC) near the surface. In this study, we investigated to increase the accuracy of fog forecast by optimizing the reconstruction of moisture distribution method, which can simulate the intensity of fog as well as the presence or absence of fog. The performances of the fog simulations were examined by modifying the relative humidity threshold at a height of 2 m and the stability parameters which affect turbulence and also one of the important criteria for fog occurrence. When we applied the optimize parameters to fog prediction in the winter seasons, the probability of detection (POD) has been increased significantly from 0.21 to 0.54. These improvements were attributed to the corrected relative humidity threshold and the stability parameters. Although the false alarm rate (FAR) remained almost unchanged, the critical success index (CSI) has been improved slightly lesser than those of the POD. When we analyzed the life cycle of fog, it takes time for the NWP model to simulate water droplets in the fog-developing stage. Therefore, the accuracy of the fog simulation is intimately related to the reconstruction of moisture distribution. The NWP model, however, showed a better performance in the process of fog dissipation than the reconstruction of moisture distribution method that was sensitive to temperature and turbulence. In conclusion, the reconstruction of moisture distribution led to a considerable improvement of the fog prediction in the generation and development stage since we used the optimized humidity threshold. It is also expected that accurate fog prediction could be achieved in the future by considering the aerosol effects, which is another importance factor for the fog generation.
Earthworm-microbe interactions: what can we learn from controlled earthworm introduction into boreal forest soil?
Authors: Garamszegi Péter , Clemmensen Karina E. , Keller Thomas , Lindahl Björn D. , Krab Eveline J.
Published: March 2024

Earthworms are considered ecosystem engineers due to their remarkable influence on the soil system. While creating the drilosphere in the soil, they interact with microorganisms both directly and indirectly and thereby greatly affecting soil carbon and nutrient cycling. Earthworm activity may reshape soil microbial communities in several ways. Amongst others, earthworms may cause shifts in microbial communities and activities/processes by damaging hyphal networks, selectively feeding on substrates hosting certain bacteria and fungi, and by redistributing nutrients in the litter-soil continuum of the soil. However, interactions between earthworms and soil microbes, especially fungi, are poorly understood, and the mechanisms by which earthworms affect microorganisms are challenging to study. First, given the widespread presence of earthworms, finding soils that have not been previously affected by earthworms is difficult. Second, controlled laboratory incubation experiments generally exclude certain functionally important groups of fungi such as plant-associated ectomycorrhizal (EcM) fungi. In our recently initiated project, we aim to study earthworm influence on soil fungal communities and associated soil biogeochemical processes by introducing soil-dwelling earthworms into to date yet uncolonised northern forest soils. Therefore, we established mesocosm boxes filled with soil turfs including tree saplings from northern boreal forests and placed them in an experimental forest in southern Sweden. Later on, we will introduce earthworms (Aporrectodea and Lumbricus spp) into the mesocosms and measure (depth specific) changes in microbial communities and genes using RNA and DNA sequencing. Potential microbial changes will be related to measurements of carbon and nitrogen cycling, such as carbon-dioxide flux measurements and soil mineral nitrogen content analysis in the growing season after earthworm introduction.
Deep learning-based earthquake catalogs extracted from threebroadband/nodal seismic arrays with different apertures in Taiwan bySeisBlue
Authors: Pan Sheng-Yan , Sun Wei-Fang , Huang Chun-Ming , Kuo-Chen Hao
Published: March 2024

SeisBlue, a deep-learning-based earthquake monitoring system, is one of the solutions to deal with massive continuous waveform data and create earthquake catalogs. The SeisBlue workflow contains waveform data preprocessing, phase arrival detection by AI modules, phase associator, earthquake locating, earthquake catalog generation, and data visualization. The whole process can be done automatically and efficiently reduces the labor and time costs. In this study, SeisBlue is applied to three different regional seismic networks: the Formosa Array for the observation of magma chamber beneath the Tatun volcanic area, Taiwan (aperture ~80 km with 148 broadband stations and station spacing 5 km), the Chihshang seismic network (CSN) for monitoring micro-seismicity of Chihshang, Taiwan (aperture ~150 km with 14 broadband stations and station spacing 20 km), and the temporary dense nodal array for capturing the aftershock sequence of the 18 th Sep. 2022 Mw6.9 Chihshang earthquake, Taiwan (aperture ~70 km with 46 nodal stations and station spacing 3 km). The 2020 annual SeisBlue catalog of the Formosa Array contains 2,201 earthquakes, as background seismicity, compare to the 1,467 earthquakes listed in the standard catalog of the Central Weather Administration (CWA), Taiwan. The two-month SeisBlue catalog of the 2022 Mw6.9 Chihshang earthquake sequence, September to October, contains 14,276 earthquakes using the CSN dataset; however, the CWA standard catalog only lists 1,247 earthquakes during the same time period. By using waveform data of 18 th Sep. to 25 th Oct. 2022, SeisBlue detects 34,630 and 12,458 earthquakes extracted from the datasets of the dense nodal array and CSN, respectively. SeisBlue can effectively detects both background and aftershock seismicity and extracts small earthquakes via dense arrays.Keywords: AI earthquake monitoring system, deep learning, AI earthquake catalog, SeisBlue, automatic waveform picking
Exploring Drought Monitoring in Morocco: A Review of Remote Sensing and Machine Learning Techniques
Authors: El Goumi Said , Namous Mustapha , Elaloui Abdenbi , Krimissa Samira , El-alaouy Nafia
Published: March 2024

The challenges of climate change and water scarcity in Morocco highlight the need for Remote Sensing (RS) and Machine Learning (ML) for drought monitoring. Droughts pose socio-economic and environmental challenges and have significant impacts on the country's agriculture-based economy and water management strategies. This study provides a comprehensive review of advanced RS technologies and ML algorithms, with a focus on their effectiveness in monitoring and forecasting drought conditions. RS provides extensive spatial coverage and captures important data on factors such as vegetation health, soil moisture, and precipitation trends, which are crucial for early detection and response to droughts. Incorporating ML algorithms significantly improves the precision and efficiency of drought prediction models, aiding in the development of comprehensive drought indices and forecasting models for agricultural planning and effective water resource management.The study evaluates various RS methods utilized in Morocco, including the analysis of satellite imagery and vegetation indices such as NDVI, and assesses ML techniques like support vector machines (SVM) and artificial neural networks (ANN) for predicting drought-induced agricultural impacts. The combined use of these technologies provides a holistic approach to drought monitoring, enabling timely interventions to assist communities affected by drought. However, the study also highlights challenges in areas such as data availability, model validation, and associated costs. To effectively manage drought risks, the paper recommends that Moroccan policymakers and stakeholders leverage these technological advancements while emphasizing the importance of continuing research, interdisciplinary collaboration, and capacity building in these areas.Key words: Drought,remote sensing, machine learning, climate change, Morocco
Unlocking the dynamics of extreme wind speeds of North Atlantic storms
Authors: Son Jun-Hyeok , Franzke Christian L.E. , Son Seok-Woo
Published: March 2024

North Atlantic extra-tropical storms are some of the most severe weather systems, causing enormous economic damages and threatening human lives. In general, these storms are characterized by strong cyclonic convergent surface winds, upward vertical flow, and precipitation. In specific confined areas inside the storm where downward flows occur with clear sky, extreme surface wind speeds are observed. Such a horizontal variation of vertical wind direction and surface wind speed can cause severe and damaging impacts; however, the underlying key dynamics are not understood. Here we show the dynamical and thermodynamical linkage between the horizontal wind impinging on the frontal surface at the lower troposphere, downward flow, and very intense surface wind speeds inside the storm. The anti-clockwise cyclonic wind into the cold frontal area is mainly responsible for generating the downward flow, which transports the high-altitude horizontal momentum to the surface layer causing intense surface wind speeds. About half of North Atlantic storms accompany the downward wind, and that downward flow is more frequently observed in the southern and western part of the storm center. Overall results illuminated in this paper have a far-reaching impact in multiple ways to enhance forecasting skills for devastating weather events associated with extra-tropical storms.
Research on the major factor of hyperspectral image measurement method for tree leaves
Authors: Chang Hanna , Jeong Su Gyeong , Je Sun Mi
Published: March 2024

Street trees are exposed to various stresses, thus the detection and management of stresses is significant for street tree vitality. Hyperspectral imaging is one of the non-destructive techniques to detect stress responses and vitality of trees. The spectral reflectance of leaves could change as the method for hyperspectral image measurement. We aimed to research the effect of distance and angle between the hyperspectral camera and leaves to recognize the factors for the optical method at the leaf scale. The target is tree seedlings for three major street tree species (Ginkgo biloba L., Chionanthus retusus Lindl. & Paxton and Prunus × yedoensis Matsum.). The hyperspectral images were collected at various distances (30cm and 80cm) and angles (90° (top), 60°, 30°) between the camera and leaves. When measuring, the halogen light was located at the same height as the camera and maintained a 45° angle with leaves. Also, hyperspectral images were collected at various light intensities (low, medium, high) with an 80cm distance and 90° angle between the camera and leaves. We analyze the change in reflectance in the spectral range of 400nm~1000nm as the various measurement methods. For all species, the effects of measurement methods on spectral reflectance were similar. The reflectance near infrared region increased at 30cm distance compared to 80cm distance. Also, the difference in spectral reflectance between 30cm and 80cm distance was continuously increased at over 800nm. However, there were no changes in the spectral response pattern among the light intensities. It means that the reflectance changes due to the distance between the camera and leaves might result from the physical distance, not the light intensity that can increase as the distance gets closer. Meanwhile, the reflectance value could change slightly, but the spectral response patterns were similar among angles between the camera and leaves. The wavelength in which the reflectance value changed differed for species. Therefore, the distance between the camera and leaves might be the major factor in setting the method. We select the distance between the camera and leaves as 80cm to measure the whole seedling crown. Then, we treated the salt stress (three times of 5% CaCl2 500ml with 2-3 days intervals) for G. biloba L. and C. retusus Lindl. & Paxton seedlings. The hyperspectral images were measured before and 7 days after salt treatment with an 80cm distance and 90° angle between the camera and leaves. The changes in the spectral index (R900/800) by the treatment compared between control and salt treatment. The stress responses were detected with the set measurement method; the spectral index increased higher in salt treatment than in the control.
Machine Learning-Based Quantification of Archean Crustal Thickness (Moho Depth)
Authors: Zhang Yu , Liu He , Sun Wei-dong
Published: March 2024

The Earth's crust, an incredibly thin layer of rock encompassing the planet's outermost solid shell, plays a crucial role in sustaining human existence by housing vital natural resources. Moreover, actively engaged in a multitude of geological processes such as plate tectonics, volcanic activities, and erosion, it significantly molds landscapes and influences natural phenomena, thereby serving as a cornerstone in maintaining Earth's habitable conditions. However, substantial debate persists regarding the mechanisms governing the growth of continental crust, and the broader implications of its role within Earth's tectonic framework remain elusive. In this study, we sought to predict the historical evolution of crustal thickness during the Archean era using machine learning based on global geochemical data of igneous rocks. The model predicted that crustal thickness decreased progressively from approximately ~35km during the Paleoarchean period to a nadir of roughly ~33km in the Early Mesoarchean era. Subsequently, there was a trend of thickening observed from the Early Mesoarchean to the Neoarchean period. Our findings reveal a dynamic history of Archean crustal thickness characterized by an initial phase of thinning followed by subsequent thickening from the Paleoarchean to the Neoarchean. These fluctuations align cohesively with the transition from a pre-plate tectonic to a regime of sustained plate tectonics. The observed phenomena were attributed to the initiation of ultrathick primary crust formation, accompanied by a tectonic regime primarily influenced by Rayleigh–Taylor instabilities. The instabilities arising from an excessive buildup of primary crust likely played a pivotal role in causing the subsequent thinning of the continental crust, marking the transition phase towards a predominantly modern-style subduction.
Reactivity of hydrogen sulfide toward organic compounds with sulfur-sulfur bonds
Authors: Zweig Irina , Kamyshny Alexey
Published: March 2024

The presence of organic molecules containing sulfur-sulfur bonds was identified in both water columns and sediments of natural aquatic systems. While processes leading to formation of these compounds were intensively studied during recent decades, the kinetics and mechanisms of reactions responsible for their decomposition remain poorly understood. This study focuses on the kinetics and products of the reactions of dimethyl disulfide, dimethyl trisulfide, and cyclic polysulfide lenthionine (1,2,3,5,6-pentathiepane) with hydrogen sulfide at the pH and temperature ranges typical of environmental conditions. The findings reveal that under environmental conditions (pH≥5), the overall reaction rates are primarily controlled by the reaction of bisulfide anion (HS-) rather than hydrogen sulfide. The activation energy and the order of the reaction with respect to bisulfide anion is dimethyl disulfide < dimethyl trisulfide < lenthionine, while the order of the reaction with respect to organosulfur compounds is lenthionine < dimethyl trisulfide < dimethyl disulfide. The rates of the reactions between linear dimethyl polysulfides with bisulfide anion were found to be higher than the rates of their reactions with cyanide and hydroxyl anions, but lower than the rates of their photodecomposition. These results suggest that rapid decomposition of organosulfur compounds in sulfidic aphotic natural aquatic systems should be controlled by HS- decomposition pathway. Products of the decomposition of dimethyl disulfide and dimethyl trisulfide include methanethiol, higher dimethyl polysulfides, and inorganic polysulfides. The cyclic polysulfides were shown to be more stable than their linear analogs, resulting in their preferential preservation during the maturation process.
Thermodynamic modelling of the outgassing chemistry of Super Earths and sub-Neptunes: applications to secondary and hybrid atmospheres
Authors: Tian Meng , Heng Kevin
Published: March 2024

Hydrogen- and helium-rich primordial atmospheres of small rocky planets, formed as a result of planetary accretion, are subject to subsequent modifications of geochemical outgassing. Two outcomes are possible: a secondary atmosphere forms if the outgassing completely replaces the primordial atmosphere, or a hybrid atmosphere results if the primordial atmosphere undergoes a partial loss with its leftover reacting with the newly outgassed species. We constructed a zero-dimensional thermodynamic model where both scenarios can be consistently simulated. The model assumes chemical equilibrium and admits input parameters of oxidation and sulfidation states of the mantle, melt temperature, atmospheric nitrogen content, surface pressure (for secondary atmosphere models), and hydrogen partial pressure (for hybrid atmosphere models). It computes the chemical compositions of outgassing, namely, the volume mixing ratios of various gaseous species. Non-ideal gas behaviors are accounted for in the model and the calculated secondary and hybrid atmospheres both exhibit a vast chemical diversity. For example, hydrogen-rich atmospheres, conventionally deemed of primordial origin, can also stem from interior outgassing. By Monte Carlo sampling in the possible ranges of the input parameters, we found that outgassed methane-dominated atmospheres, regardless of secondary or hybrid, require rather specific conditions: (1) a reduced rocky mantle; (2) relatively low melt temperatures in comparison to those of basaltic or peridotitic melts; (3) relatively high atmosphere pressures (> c.a. 10 bar) on the rocky surface. Moreover, we found that the abundance ratio of CO2 and CO can serve as a powerful diagnostic of oxygen fugacity of rocky mantles, which could potentially be constrained by future James Webb Space Telescope spectra. The current model does not consider atmospheric escape, chemical kinetics or photochemistry, which awaits to be incorporated in future works.
Changes in Solar and Wind Power Generation Potentials over South Korea under Future Global Warming.
Authors: Kim Seon Tae
Published: March 2024

This study presents the impact of climate change on the wind and solar power generation potentials over South Korea considering ensemble projections from downscaled high-resolution bias-corrected future climate change scenario data. Under future global warming, solar power potentials over South Korea are projected to decrease in spring (March-May) and winter (December-February) seasons relative to present climate in the late 21st century (2081-2100), particularly showing a relatively large decrease in the northern part of South Korea. The decrease tendency is more significant and larger in the high-CO2 emission scenario (SSP5-8.5) than the low-CO2 emission scenario (SSP2-4.5). The projected decrease in solar power potential in spring is mainly due to increased air temperature by future global warming and the decrease in winter is attributable to the projected increase in the air temperature and the decrease in solar radiation at the surface. Wind power potentials which are estimated with the wind energy density is generally projected to decrease with future global warming in all seasons except for summer. This decrease tendency is also larger in the late 21st century of the SSP5-8.5 scenario, especially over the southern part of South Korea in winter and spring and over the northern part in fall. These results may help optimize the regional renewable energy generation system development and plans
High-resolution mapping of surface water dynamics using restricted random forest: A case study in the Yellow River Basin
Authors: Wang Xian , Zhang Yongqiang
Published: March 2024

Numerous datasets revealing locations and alterations of water bodies have been produced from field investigations and remote sensing imagery. However, measuring surface water changes with high resolution remains a challenge. Here, a high-precision random forest (RF) model constrained by the annual maximum remote sensing indices was developed. Validation result from visual inspection shows that the accuracy of the model has reached 99.46%. Based on the improved RF model, monthly surface water variations in the Yellow River Basin over the past 10 years were quantified at 30-meter resolution using Landsat 8 and Sentinel 2 satellite images. The variations of water bodies including when water was presented, where occurrence changed and what form changes took in terms of seasonality and persistence were obtained. It is found that between 2014 and 2023, there are evident variations of permanent water bodies including formation and disappearance of surface permanent water bodies in the Yellow River Basin. Further research can be conducted on the intricate impact of climate and human activity on water bodies using the high-resolution surface water dataset provided.
Present-day quantification of seismic coupling along the décollement level beneath the Potwar Plateau region in Pakistan western Himalaya
Authors: Meyer Pauline , Jouanne Francois , Doin Marie-Pierre , Ahmed Awais , Alam Awan Adnan , Mugnier Jean-Louis
Published: March 2024

The northwestern syntax of the Himalaya is a very rapidly deforming area at the edge of the India-Asia collision zone. Therefore, we quantify the current velocity field of the Potwar Plateau – Salt Range fold-and-thrust belt using GNSS horizontal surface velocities and Sentinel-1 interferometry line-of-sight velocities. From this velocity field which indicates a creep of the Potwar Plateau along the Main Himalayan Thrust, we infer a weak subhorizontal décollement level formed by a massive Precambrian salt layer. South of the Plateau, the Salt Range is uplifted along the Salt Range Thrust up to 5 mm/yr. The Kalabagh Fault, which forms the western boundary of the Salt Range and the Potwar Plateau, exhibits a creep rate along fault of 3.3 mm/yr. To characterize the slip distribution and coupling along the faults, we use numerical modelling with a set of dislocations in an elastic half-space. The preferred model shows the presence of a large asperity along the décollement level beneath the Potwar Plateau and several smaller asperities along the eastern basal thrust. These observations are consistent with the occurrence of the 2029 Mirpur earthquake of Mw 5.9 along the eastern part of the décollement level. Along the southern and superficial parts of the Salt Range Thrust, the model indicates a slip rate of 20 mm/yr which is greater than the 14 mm/yr slip rate along the Main Himalayan Thrust at depth. This observation suggests the existence of an internal southward flow of the massive salt layer along the upper part of the Salt Range Thrust. For the Kalabagh strike slip fault, an alternation of coupled and decoupled zones is observed, meaning that this fault can be characterised by creep and asperities where earthquakes and/or slow slip events can occur. Considering the lack of instrumental and historical large magnitude earthquakes in the area since the AD 25 Taxila earthquake, it can be concluded that the Main Himalayan Thrust and the Kalabagh Fault are likely to be affected by large magnitude earthquakes.
Evaluating Flood Adaptation Effectiveness through Economic Analysis: A Case Study of Surat, India
Authors: Kumar Ashish , Bhatia Udit
Published: March 2024

Floods are among the most costly natural disasters globally and are projected to increase in frequency and magnitude with a warming climate. To confront increasing flood risks, flood managers need the most cost-effective adaptation actions to reduce economic damage to floodplain infrastructures. Recent research advancements have explored the physical aspects of flood adaptation strategies such as levees, diversions, and barrages. However, implementing adaptation actions requires comprehensive economic analysis before execution due to the substantial capital investment involved. Here, we develop a 1D-2D coupled hydrodynamic flood model in the MIKE+ platform, considering river flow to generate flood inundation maps for various hydraulic inland scenarios. We generate inundation maps for 10-, 50-, 100-, and 200-year return periods of design discharge, considering flood adaptation strategies. Subsequently, we utilize available flood depth-damage functions to calculate expected flood damage and conduct a cost-benefit analysis of the proposed adaptation strategies. We demonstrated the proposed framework for the coastal city of Surat, India. Our results provide the decision matrix to select adaptation strategies based on design standard objectives. The initial assessment highlights that a combination of levee and barrage is more effective than individual levee, barrage, and diversion strategies, particularly in terms of cost-effectiveness in reducing flood damage. Our framework would be beneficial in selecting effective planning strategies for reducing flood damage.
The Precipitation Retrieval and Profiling Scheme for the Special Sensor Microwave Imager/Sounder
Authors: Niedorf Anja , Kidd Christopher , Konrad Hannes , Fennig Karsten , Schröder Marc
Published: March 2024

The Special Sensor Microwave Imager/Sounder (SSMIS) of the US Defense Meteorological Satellite Program (DMSP) has been the mainstay of observations used for precipitation retrievals over the last 20 years. The sensor, building upon the heritage of the DMSP Special Sensor Microwave/Imager (SSMI) series that operated between 1987 and 2020, provides precipitation-capable frequencies from 18-183 GHz at resolutions up to 15x13 km. The longevity of the SSMIS and the SSMI satellite series makes these sensors extremely important for the retrieval of precipitation at the climate-scale. The adaptation of the Precipitation Retrieval and Profiling Scheme (PRPS), originally developed for passive microwave sounders, to the SSMIS aims to provide model-free precipitation retrievals that can be incorporated into the Global Interpolated Rainfall Estimation (GIRAFE) product developed by EUMETSATs Satellite Application Facility on Climate Monitoring (CM SAF). Fundamental to the PRPS is the avoidance of external dynamic data sets, such as model information, to ensure that the retrieval scheme is purely a satellite-based observational product. The scheme relies upon the generation of observational databases, based upon co-temporal and co-located observations made by the satellite sensor(s) and observations of precipitation made by either satellite-based precipitation radar or surface radars. For the PRPS-SSMIS, the databases have been generated using observations from SSMIS sensors on the F16, F17, F18 satellites matched against the precipitation estimates provided by the NASA/JAXA Dual frequency Precipitation Radar (DPR) on the NASA/JAXA Global Precipitation Measurement mission (GPM) core observatory. The orbits of the SSMIS and GPM provide about 20,000 crossing points per satellite between 2016 and 2022, and generate about 30M co-located (
Millennial-scale Northern Hemisphere ice sheet growth controlled by stadial-versus-interstadial duration
Authors: Zhang Yu'ao , Zhang Xu
Published: March 2024

Global sea-level changes are significantly associated with variations in Northern Hemisphere ice sheets (NHISs) during the last glacial cycle. However, their responses to glacial millennial-scale climate variability (also known as Dansgaard - Oeschger (DO) cycles), especially during the Marine Isotope Stage 3 (MIS3, ~30-65ka), remains poorly studied, in addition to the contrast lines of geological evidence regarding paleo-sea level changes. Instead of applying Glacial Index Method which overlooks potential tempo-spatial heterogeneity of temperature and precipitation in the northern high latitudes, in this study, we conducted transient PISM ice sheet modeling by imposing full climate forcing derived from fully coupled climate model experiments which are characterized by spontaneous millennial variability. Our results show that control factors of ice volume changes in Laurentide and Eurasian ice sheets are different due to spatially heterogenous climate forcing. During stadial periods, North American Ice sheets is growing because of increased precipitation especially along the margins of the ice sheets, despite spatially heterogenous but trivial changes in the surface air temperature. Meanwhile, dramatic cooling on the southern regions of Eurasian Ice sheets effectively reduces ice loss and hence promote the overall ice growth. In brief, NHIS ice volume grows during stadials while declines during interstadials. We hence propose that stadial-to-interstadial duration ratio is the key to the net change in NHIS volume in a signal DO cycle, providing dynamic understanding of accelerated sea level drop during 40-30ka.