bluuebunny/crossref_metadata_2025 huggingface dataset:
Preserving coastal agriculture: Nature-based solutions for the mitigation of soil salinization 
Authors: Tarolli Paolo , Park Edward , Luo Jian , Masin Roberta
Published: March 2024

Soil salinization significantly threatens agriculture and food security, leading to profound soil degradation and desertification, negatively impacting ecosystems. The accumulation of excessive salts has negative effects on soil structure, fertility, plant growth, crop yield, and microorganisms. This phenomenon is attributed to natural factors, such as dry climates and high evaporation rates, and human-induced factors, including not optimal irrigation practices, inadequate drainage systems, and excessive fertilizer use. The increased frequency of weather extremes driven by climate change exacerbates this global issue, especially along coastal areas where millions of people live. Here, the sea-level rise, and recently also drought, are causing, especially in river deltas, a progressive land degradation, which negatively impacts the sustainable development of coastal agriculture. The lack of rainfall leads to scarce river discharge and consequently favours marine water inland flow intrusion. Anthropogenic activities (e.g., dams, mining) are exacerbating the phenomenon. Urgent mitigation strategies are therefore necessary. This study explores the potential of Nature-based Solutions (NbS) as sustainable and resilient response to soil salinization, offering benefits to agriculture through revitalizing ecosystem services. In detail, we addressed the challenges and limitations of implementing natural barriers, wetlands, buffer zones, conversion to aquaculture, straw incorporation, microbial-based solutions, organic fertilizers, and low impact water storage facilities. In detail, we should start re-introducing, where possible, wetlands through renaturalisation strategies, aiming to create a virtuous ecological equilibrium in agricultural landscapes. Indeed, wetlands can offer a natural barrier to saltwater intrusion. Soil remediation of degraded areas, especially for those interested in sand mining or oil refineries, is necessary to make soils more resilient and reestablish missed ecosystems. Agriculture must be sustainable and adopt conservation practices to keep and improve soil organic carbon content (SOC). Soils rich in SOC can retain more water and are more resilient; thus, they are more prepared for prolonged pressure given by water scarcity and soil salinization.
Process-landform relationships at variable spatio-temporal scales in the Southern Chaco fluvial megafans (Argentina) 
Authors: Kroehling Daniela
Published: March 2024

The Chaco Plain (South America) is an aggradational lowland (40-600 m asl) with divergent drainage patterns, at present under a tropical–subtropical climate. Late Quaternary coalescent fluvial megafans constitute the most extensive depositional system of the Central Andean foreland basin. A complex assemblage of macro- and mesoscale landforms of the Southern Chaco plain (22°–31°S) was analyzed at variable spatio-temporal scales, based on remote-sensing data coupled with ﬁeld and sedimentological datasets. The Pilcomayo, Bermejo, Salado-Juramento and Dulce River megafans are between the largest distributive fluvial systems (DFS) in modern landscapes of Earth. The surface covered by these megafans reaches ca. 5,5 million km2, deeply advancing basinward and achieving megafan radii of 600/750 km, most of these to the axial fluvial trunk (Paraná).  They are characterized by highly dynamic fluvial processes related to flooding and partial avulsions. A process-based geomorphological research focusing on Late Quaternary-Present fluvial and wetland dynamics from fluvial valley scale to DFS scale is presented. The spatio-temporal pattern of fluvial aggradation and progradation on these megafans is related to climatic and neotectonic forcings. The influence of the South American Summer Monsoon System during the Late Quaternary produced high seasonal ﬂuctuations in the discharge in their Andean rivers, associated with the high sediment input and short-term sedimentation of the formative rivers. Fluvial distributive channels, alluvial ridges, aggradational lobes and crevasse and terminal splays are the typical landscape elements of the megafans. Foreland basin configuration determined the landscape patterns along these megafans. The mosaic of the Late Pleistocene and Holocene landforms influences the present hydro-geomorphological dynamic of each megafan. Extensive permanent to temporary wetlands were developed in the middle/distal reaches of these DFS, which are characterized by surfaces of extremely low gradients (0.03°–0.18°). These wetlands functioned as sediment sinks. Late Pleistocene (MIS 5/3) wetland sedimentary facies and hydromorphic palaeosols were analyzed from cores obtained from research boreholes in distal areas, considering the lack of exposed stratigraphy across the extensive and ﬂat megafan surfaces. Partial avulsions are frequent in the Holocene river belts in middle/distal areas of the megafans, where large, ﬂoodplain-ﬁlling splays dominate (overbank processes).  The accelerated expansion in deforestation and agricultural land use on the Chaco megafans enhanced their flood vulnerability under climate change. Hence, understanding the landscape dynamics of the Chaco Plain is fundamental to risk mitigation strategies.
Visualization of DDE-Outcrop 3D to Promote Public Education in Natural History Museums
Authors: Guo Yao
Published: March 2024

The DDE-Outcrop3D plays an important role in the digitization of geological resources. By digitally preserving, presenting, and reconstructing classic geological outcrops worldwide, the DDE-Outcrop3D Project broadens the user’s fieldwork visions and perspectives, allowing convenient access to fieldwork data, and helping users alleviate constraints imposed by time, distance, and financial resources. This project enables users to partake in immersive, online scientific explorations and educational endeavors, which has significance for public education in natural history museums. Firstly, digital outcrops provide scientific and reliable references for the exhibition scene designing of museum galleries related to geological environments and natural ecology. Secondly, digital outcrops visualize geological knowledge in multimedia forms within museum exhibits, enhancing interactivity with visitors and improving the knowledge density and display efficiency per unit area. Lastly, digital outcrops extend beyond museum confines, supporting museum-school collaborative scientific curricula aimed at cultivating autonomous geological research skills among K-12 students. This paper provides an in-depth example of the DDE-Outcrops3D application at the Chengdu Museum of Natural History (also known as the Museum of Chengdu University of Technology), offering a detailed exposition of the technology’s substantial value in public education for natural science museums.
Impact of Uncertainties in Land Surface Processes on Subseasonal Predictability of Heat Waves Onset Over the Yangtze River Valley
Authors: Zhang Qiyu , Mu Mu , Sun Guodong , Dai Guokun
Published: March 2024

Land surface processes are strongly associated with heat waves (HWs). However, how the uncertainties in land surface processes owing to inaccurate physical parameters influence subseasonal HW predictions has rarely been explored. To examine the impact of parameter errors of land surface processes on the uncertainty of subseasonal HW predictions, five strong and long-lasting HW events over the middle and lower reaches of the Yangtze River (MLYR) are investigated. Based on the Weather Research and Forecasting (WRF) model, the conditional nonlinear optimal perturbation related to parameters (CNOP-P) approach is employed to address the aforementioned issues.Numerical results demonstrate that the CNOP-P type errors of physical parameters cause large prediction errors for five HW event onsets. Two types of CNOP-Ps are obtained for HW events, called the type-1 CNOP-P and the type-2 CNOP-P. The type-1 (type-2) CNOP-P causes an approximately 3 °C (2 °C) warm (cold) bias during the HW period. Surface sensible and latent heat flux errors, especially flux exchange between vegetation canopy and canopy air, provide considerable uncertainty in subseasonal HW predictions. The type-1 (type-2) CNOP-P exhibits an underestimation (overestimation) of transpiration. Furthermore, it should be noted that the type-1 CNOP-P results in a substantial difference in soil moisture, a phenomenon that is demonstrated to be challenging to observe in the type-2 CNOP-P. The results indicate that understanding vegetation-atmosphere dynamics is crucial for improving subseasonal HW predictions. Jointly lowering soil-atmosphere and vegetation-atmosphere uncertainty can notably improve subseasonal HW prediction skills.
New insights into the sources of atmospheric organic aerosols in East China: a comparison of online molecule-level and bulk measurements
Authors: Ge Dafeng , Nie Wei , Liu Yuliang , Huang Dandan , Yan Chao , Wang Jinbo , Li Yuanyuan , Liu Chong , Wang Lei , Wang Jiaping , Chi Xuguang , Ding Aijun
Published: March 2024

Organic aerosols (OA) are of great concern because they contribute to haze pollution, threaten human health and affect the radiation balance. However, tracking OA evolution in real time at the molecular level is still limited, hindering a comprehensive understanding of their origins and behaviors. In this study, we investigated wintertime OA in a megacity in East China by combining simultaneous measurements from an extractive electrospray time-of-flight mass spectrometer (EESI-TOF) and a high-resolution time-of-flight aerosol mass spectrometer (HR-TOF-AMS). AMS results show that the OA mass concentration account for about 27% of non-refractory submicron particulate matters (NR-PM1) on average during the measurement. Speciated-organic data from EESI-TOF further reveals that CxHyOz and CxHyN1-2Oz are the predominant components of OA, contributing over 70% and 20%, respectively. By performing factorization analysis of data obtained from both instruments, we found that traffic, cooking and biomass burning are major primary sources of OA, but most of OA (>70% for EESI-TOF, >55% for AMS) come from secondary production. Compared to AMS, EESI-TOF misses hydrocarbon-like OA but owns advances in providing molecular information on oxygenated OA, revealing that aromatics and aliphatics are important precursors. Specifically, EESI-TOF further splits the less oxidized secondary organic aerosols (SOA) into two factors with distinct molecular compositions, possibly resulted from diverse source regions. Importantly, EESI-TOF additionally identifies two factors based on the tracer molecules, one possibly related to plasticizers and the other representing the SOA formation from the oxidation of monoterpenes by NO3 radicals. In conclusion, our findings suggest that EESI-TOF is highly complementary to the widely used AMS, providing valuable molecular information that aids in uncovering chemical processes underlying the formation of OA, especially in the highly complex urban environment.
Reconciling East Asia's mid-Holocene temperature discrepancy through vegetation-climate feedback
Authors: Chen Jie
Published: March 2024

The Holocene temperature conundrum, marked by inconsistencies between proxy-based reconstructions and transient model simulations, challenges our understanding of Holocene temperature evolution. Reconstructions suggest a cooling trend after the Holocene Thermal Maximum, while model simulations indicate a consistent warming trend due to ice-sheet retreat and rising greenhouse gas concentrations. Various factors, such as seasonal biases and overlooked feedback processes, have been proposed as potential causes for this discrepancy. In this study, we found the impact of vegetation-climate feedback on temperature anomaly patterns in East Asia during the mid-Holocene (6000 BP). By utilizing the fully coupled Earth system model EC-Earth and performing simulations with and without coupled dynamic vegetation, we aim to isolate the influence of vegetation changes on regional temperature patterns. Our findings reveal that vegetation-climate feedback contributed to warming across most of East Asia, resulting in spatially diverse temperature changes during the mid-Holocene and significantly enhanced the model-data agreement. These results highlight the crucial role of vegetation-climate feedback in addressing the Holocene temperature conundrum and emphasize its importance for simulating accurate climate scenarios.
Deep learning forecasting of induced earthquakes through the analysis of precursory signals
Authors: Convertito Vincenzo , Giampaolo Fabio , Amoroso Ortensia , Piccialli Francesco
Published: March 2024

The current limited knowledge about Earth system prevents deterministic earthquake prediction. This will probably continue for the foreseeable future. However, the improved capability of identifying reliable precursory phenomena can allow geoscientists to comprehend if the monitored system is evolving toward an unstable state. Among the premonitory phenomena preceding earthquakes, foreshocks represent the most promising candidate. Physically, two hand-member mechanisms have been proposed to interpret foreshocks. The first considers the failing of populations of small patches of fault that eventually but not necessarily become large earthquakes whereas the second assumes that foreshocks are a part of the nucleation process which ultimately leads to the mainshock. The prompt identification of foreshocks with respect to background seismicity is an issue and the task is worsened when dealing with low-magnitude earthquakes. However, the use of Artificial Intelligence (AI) can help real-time seismology to effectively discriminate precursory signals.In the present study, we propose a deep learning method named PreD-Net (Precursor Detection Network) to address the precursory signal identification of induced earthquakes through the analysis of several statistical features. PreD-Net has been trained on data related to two induced seismicity areas, namely The Geysers, located in California, USA, and Hengill in Iceland. Notably, the network shows a suitable model generalization, providing considerable results on samples that were excluded from the training dataset of all the sites. The performed tests on related samples of induced relatively large events demonstrate the possibility of setting up a real-time warning strategy to be used to avoid adverse consequences during field operations.This work is supported by project D.I.R.E.C.T.I.O.N.S. - Deep learning aIded foReshock deteCTIOn Of iNduced mainShocks, project code: P20229KB4F - - Next Generation EU (PRIN-PNRR 2022, CUP D53D23022800001)
Chinese Wisdom: Investigating Future Patterns of Extreme Precipitation Based on the Twenty-Four Solar Terms
Authors: Xu Yichao , Jiang Zhiqiang , Dai Yanpeng , Li Zhijin
Published: March 2024

The Twenty-Four Solar Terms are an ancient and unique Chinese contribution, developed by agrarian laborers for the convenience of agricultural scheduling. Historically, each Solar Term has exhibited a significant correlation with climate change. Our study revisits and validates the Solar Terms’ sensitivity to regular precipitation metrics over the past half-century. We assessed the reliability of this temporal framework by comparing 30-day cumulative precipitation and the number of effective rainfall days around typical Solar Terms, along with the correlation of China’s Standardized Precipitation Index (SPI) with the Heihe-Tengchong Line, known as the Hu Line, during various Solar Terms. The research further investigates the correspondence between multiple scenarios of future extreme precipitation events, including Event-based Extreme Precipitation (EEP), and the Solar Terms. This study focuses on identifying which Solar Terms have historically been, and are likely to continue being, prone to extreme precipitation, as well as their spatial distribution patterns across China. The result indicates that under four different socio-economic pathways in future scenarios, over 55.2% of the regions in China will witness a concentration of extreme precipitation events during the Minor Heat and Major Heat Solar Terms. These events are predominantly expected to occur in the Qinghai-Tibet region, averaging over 10 instances every five years that exceed the 95th percentile for extreme rainfall, showing an increasing risk trend over time. This study not only enhances the cultural depth of our research but also fosters a profounder understanding of the cyclical patterns of extreme precipitation and the related flood risks it entails, offering a novel perspective for guiding flood prevention efforts and the study of extreme precipitation patterns.
Risk Mapping and Evacuation Analysis of Vulnerable Population under Climate Change - a Case Study in New Taipei City, Taiwan.
Authors: Ke Kai Yuan , Chang Hsiang Kuan , Li Ching Ling , Cheng Yu Fen
Published: March 2024

The objective of this study is to investigate the flooding effect on the evacuation safety of vulnerable populations in the context of disaster response and climate change impact. The case study of New Taipei City, Taiwan, is introduced. Initially, we establish an urban flood drainage model, NTU-2DFIM, which includes a watershed rainfall-runoff model, a one-dimensional hydraulic model for regional drainage and stormwater sewers, and a two-dimensional surface flood model. After calibration and validation, the IPCC AR6 RCP8.5 climate change scenario is applied to simulate the flooding. Regarding vulnerable groups, which include the elderly (65 years and above), children (5 years and below), low to middle-income households, people with disabilities, solitary elderly individuals, and individuals with no formal education, a spatial autocorrelation analysis is conducted using the Basic Statistical Area to identify hotspots of vulnerable populations. Subsequently, in these hotspot areas, together with nearby evacuation shelters, service coverage analysis is performed. Additionally, road network analysis is conducted by considering flood-induced obstacles to determine optimal evacuation routes. With the above risk mapping process, the results can guide individuals in formulating emergency response plans for household and community, as well as providing public authorities with insights for adjusting shelter locations and planning transportation for the evacuation of vulnerable groups.
Strain fringes in Hiriyur Formation of rocks, Chitradurga greenstone belt, Karnataka: Implications with ore formation 
Authors: Sati Manju , Krishnamurthi Rajagopal , Chinnasamy Sakthi Saravanan
Published: March 2024

Paramanahalli gold prospect lies in the Chitrdurga greenstone belt, India; the mineralization found in altered rocks characterized by the mineral assemblage of chamosite (Fe-rich chlorite) + annite (Fe-biotite) + ankerite + quartz + pyrite + gold ± chalcopyrite ± pyrrhotite ± magnetite. Strain fringes are developed with the pyrite and magnetite of the Banded Iron Formation and phyllite of the study area. Strain fringes are indicators of the low-pressure zones parallel to the least compressive stress. These features are massive and monomineralic adjacent to a rigid object (pyrite, magnetite) and are usually composed of a different material than the rigid object. Pyrite and magnetite are euhedral in shape and medium-coarse-grained (20-80 µm) in size. Fringes contain information on flow and style of deformation in their internal and external shape and are helpful kinematic indicators in the mineralized zone. The Hiriyur Formation rocks metamorphosed up to greenschist facies that can retain the pre-deformed shapes. This study illustrates the variety of strain fringes, studied in detail to understand deformation patterns and gold-sulfide mineralization in the research area. Fringe-1 is face-controlled, uneven, made up of fibrous quartz, and associated with rigid magnetite. The uneven nature of extended fringes infers simple shear. Fringe-2 is a face-controlled, variable extended fiber made up of quartz. Fringe-3 is a displacement-controlled fringe consisting of quartz that is similar on both sides and shows typical wing-type features. These stain fringes indicate a sense of rotation after the hydrothermal fluid precipitates ore minerals (pyrite/ magnetite). The presence of strain fringes with pyrite (± gold) infers the remobilization and recrystallization of sulfides during/after a deformation event at Paramanahalli prospect, Karnataka. The current work points toward a strong link between the development of microstructures and ore formation. Based on petrological and microstructural evidence, it is proposed that there was a syn-ore formation / main mineralization event responsible for the precipitation of sulfides, later affected with deformation that leads to the formation of such features.
Development of seasonal ozone maximum reactivity scales for Beijing, China
Authors: Zhou Houhua , Gong Yuanjun , Lu Keding
Published: March 2024

We present an incremental reactivity (IR) scale for 41 conventional volatile organic compounds (VOCs) in Beijing and elucidate their application in calculating ozone (O3) formation potential (OFP) in China. We explore the effects of updating the representative urban atmosphere used for ozone reactivity calculations by updating the meteorology, emission rates, concentration of initial conditions, concentration of background species, and composition of volatile organic compound profiles. Two sets of model inputs (emission-based and observation-based) are designed to localize the IR scale in Beijing using a master chemical mechanism (MCM) box model and compared with the US model. Based on a good fit to actual atmospheric scenarios, the two input models differ in the way the main pollutants are entered, one based on emission data and the other on observed pollutant levels, and there are differences in the maximum incremental reactivity (MIR) derived from them. Significant seasonal characteristics of MIR exist in different months of the year because of differences in meteorological conditions as well as emission scenarios. This study provides recommendations for the application of the MIR scale, serving as a reference for volatile organic compound control strategies in China and other ozone-polluted countries.
Magnetic field and ion velocity spectra in the solar wind from inertial to kinetic scales
Authors: Safrankova Jana , Nemecek Zdenek , Pitna Alexander , Nemec Frantisek , Franci Luca
Published: March 2024

The paper analyzes the power spectra of solar wind velocity and magnetic field fluctuations that are computed in the frequency range around the break between inertial and kinetic scales. The study uses measurements of the Bright Monitor of the Solar Wind (BMSW) on board Spektr-R with a time resolution of 32 ms complemented with 10 Hz magnetic field observations from Wind propagated to the Spektr-R location and compare them with observations of Solar Orbiter and Parker Solar Probe closer to the Sun. We concentrate on the ion kinetic scale and investigate statistically the role of parameters like the fluctuation amplitudes of parallel and perpendicular magnetic field components, collisional age, temperature anisotropy or ion and electron beta. Our discussion encompasses the interplay of magnetic field and plasma fluctuations that characterize this dynamic environment and reveals that although the ion beta controls a position of the spectral break between the inertial and kinetic ranges, other mentioned parameters determine the steepness of the kinetic range spectrum of both quantities. We are showing that these statistical results are in line with theoretical considerations.
New Arctic quality metrics based on oceanic transports for CMIP
Authors: Winkelbauer Susanna , Mayer Michael , Haimberger Leopold
Published: March 2024

Oceanic transports of heat, volume and salinity are an integral part of the Earth's energy and mass budgets and play a key role in regulating the Earth's climate. Changes in the ocean’s transport patterns may affect regional as well as global climates. Accurate monitoring is critical and there are several regional measuring lines like the RAPID 26N and OSNAP (Overturning in the Subpolar North Atlantic Program) array, as well as measuring lines across Arctic water straits, which are equipped with moorings and other advanced measuring systems. It is desirable to compare the transports calculated by these instruments with ocean reanalyses and climate models. However, this is challenging because the moorings are not aligned with the model grids, and the ocean model grids get complicated especially towards more northern latitudes.To address this challenge, we introduce StraitFlux (https://pypi.org/project/straitflux/), a versatile tool enabling precise and mass-consistent calculation of volume, heat, and salinity transports across any oceanic section. We have used StraitFlux to calculate transports from reanalyses and climate models (CMIP6) in the Arctic region and to compare them to available observations. While we find some biases, especially in straits that are narrow and bathymetrically complicated, the results generally show that reanalyses capture the main current patterns quite well. Climate models on the other hand exhibit larger and often systematic deviations from the mooring and reanalysis output. The spread among climate models is 3-5 times larger than the spread between observation-based transports and reanalyses or among reanalyses, and it cannot be explained by natural variability. The large spread in flux quantities is related to mean-state biases in relevant state quantities. It helps to quantify and understand the strong connections between lateral OHT and the mean state as well as changes in the Arctic Ocean and sea ice.Expanding on our methodology, we develop physically based metrics tailored to the Arctic, to detect outliers from the CMIP6 model ensemble and constrain model projections using a weighting approach incorporating the models’ performance and independence. This effectively reduces the spread of future projections of Arctic change. Further, using StraitFlux, we investigate constrained changes in Arctic volume, heat, and salinity transports for the main SSP scenarios. We examine cross-sections of the main Arctic gateways to assess future changes in the structures and strengths of the main currents and their effects on the Arctic system.
Towards understanding the interplay between tectonics, magmatism, and sedimentation in the Timok Magmatic Complex (TMC) basin of the Serbian Carpathians
Authors: Stojadinovic Uros , Toljić Marinko , Trivić Branislav , Pantović Radoje , Srećković-Batoćanin Danica , Krstekanić Nemanja , Kostić Bojan , Velojić Miloš , Stefanović Jelena , Randjelović Nikola , Maleš Maja
Published: March 2024

Among the many examples observed worldwide, the Timok Magmatic Complex (TMC) basin of the Serbian Carpathians represents an excellent area for a process-oriented study on the interplay between tectonics, sedimentation, and magmatism in continental back-arc basins above evolving subducted slabs. The TMC is a segment of the larger Late Cretaceous Apuseni-Banat-Timok-Srednogorie (ABTS) magmatic belt, formed in response to the subduction of the Mesozoic Neotethys oceanic lithosphere beneath the Carpatho-Balkanides of south-eastern Europe. However, despite many qualitative studies, the quantitative link between the subducted slab's mechanics and the overlying basins' evolution is less understood. Within the scope of the newly funded TMCmod project, supported by the Science Fund of the Republic of Serbia (GRANT No TF C1389-YF/PROJECT No 7461), coupled field and laboratory kinematic and petrological investigations will be focused on creating a conceptual definition of the TMC geodynamic evolution, by combining near-surface observations with the known evolution of the subduction system. This definition will be subsequently validated through analogue modelling and integrated into a coherent geodynamic model of tectonic switching in basins driven by the evolution of subducted slabs. The new geodynamic model coupling the TMC basin with its Neotethys subduction driver will quantitatively advance the strategy of prospecting and exploration of world-class porphyry copper-gold deposits, which have been actively exploited in this region for more than a century. Furthermore, reconstructed regional kinematic evolution will improve seismic hazard assessment during industrial and societal infrastructure planning and construction.
Formation of spinel-bearing layered gabbros by the reaction between the basaltic crystal mush and high-Mg andesitic melts in the lower oceanic crust, East Pacific Rise (IODP Exp. 345 U1415P) 
Authors: Hoshide Takashi , Kondo Keita
Published: March 2024

Petrographic studies of the multi-textured layered gabbro series of the lower crustal section recovered from U1415P were conducted to determine the mechanism of orthopyroxene formation in lower crustal gabbros drilled in the Hess Deep rift near the East Pacific Rise. In a particular horizon of the series (U1415P 6R-1 to 6R-2), homogeneous medium-grained troctolite and fine-grained spinel-bearing heterogeneous olivine gabbro occur in proximity.The samples from the Hole1415P 6R are divided into homogeneous troctolite parts with medium-grained equigranular textures and spinel-bearing heterogeneous olivine gabbro parts with poikilitic textures (irregularly shaped fine-grained plagioclase characrysts enclosed in Ol-oikocrysts and Cpx-oikocrysts). The wide variation in TiO2 content against nearly constant Mg# and Cr2O3 of clinopyroxene in these rocks is quite different from the compositional trend of clinopyroxene in layered mafic intrusions explained by the fractional crystallization of magma.Recently, Yang et al. (2019) conducted a reaction experiment between MORB melts and troctolite and reported microtextures and mineral chemical compositions of the experimental products. In the experiment, fine-grained plagioclase was found to be poikilitically enclosed in olivine and clinopyroxene in the melt infiltration zone within troctolite near the boundary between troctolite and melt. The poikilitic textures and the oikocristic clinopyroxene compositional variations in the Hess Deep spinel-bearing olivine gabbro are very similar to those in the reaction experiment by Yang et al. (2019). These indicate that the heterogeneous olivine gabbro of the Hess Deep was formed by a melt-rock (or crystal mush) reaction.              In addition, the multiphase solid inclusions of Cpx-Pl assemblage with basaltic magma composition and Opx-bearing multiphase solid inclusions with composition of high-Mg basaltic-andesite to andesite are enclosed in Cr-spinel from the spinel-bearing heterogeneous olivine gabbro. The presence of Opx-bearing multiphase solid inclusions indicate that the injection of SiO2-rich melt different in composition from the troctolite-forming magma has occurred. The SiO2-rich melt reacted with the troctolite to form spinel-bearing heterogeneous olivine gabbro. Our results may suggest that the sheeted sills model, in which magma of various compositions intrudes into the crust, is a more appropriate mechanism for the formation of the lower oceanic crust.
Comparing ML retrieved and invisible ship tracks to probe the meteorological dependence of cloud susceptibility to aerosol
Authors: Manshausen Peter , Watson-Parris Duncan , Stier Philip
Published: March 2024

Aerosol-cloud interactions continue to resist reliable quantification, partly owing to their strong dependence on cloud and weather regimes. For a long time, opportunistic experiments such as ship tracks have been used to overcome issues of confounding. Recent advances leverage (i) Machine Learning (ML) to drastically enlarge ship track data bases, and (ii) ‘invisible ship tracks’, found by advecting ship emissions, to overcome selection biases in ship track studies. Here, we combine both approaches, to advance our understanding of how meteorology controls cloud responses to aerosol emissions. Firstly, we show that even though the ML dataset is much larger than previous hand-logged data sets, it still contains only a fraction of less than 1% of the cloud regions polluted by shipping. This means less than 1% of ship tracks are visible. Secondly, we find that this fraction varies strongly with location and season, with the Southern Hemisphere winter leading to most visible tracks in the Stratocumulus regions of the SE Pacific and SE Atlantic. Thirdly, we identify meteorological regimes favourable to the visibility of tracks, using ML methods such as Random Forests and Explainable AI, alongside traditional methodsThe regime favourable to visible tracks is defined by a stable lower troposphere and little vertical movement, low sea surface temperatures, high cloud cover, and low boundary layer heights. Lastly, we quantify the link between ship track visibility and albedo change in polluted clouds, establishing to what extent days with visible tracks are those when cloud albedo is most susceptible to aerosol. Building on this relationship, a predictive model like our Random Forest has applications in deliberate Marine Cloud Brightening by predicting the days that are most susceptible to aerosol perturbations.
Evaluating the thermal effects of peatland restoration using UAV monitoring
Authors: Langhammer Jakub , Lendzioch Theodora , Hordiienko Oleksandr
Published: March 2024

Mid-latitude montane peatlands have undergone extensive anthropogenic modifications in past decades. Projects aimed at their restoration represent critical ecological interventions, reinstating their hydrological regime, preserving biodiversity, and mitigating the effects of climate change.This research aims to investigate the effect of mid-latitude montane peatland restoration on the responses in land surface temperature (LST) and wetness using multispectral and thermal UAVs supported by instrumental monitoring. We aimed to test the hypothesis that peatland restoration should have a cooling effect on LST due to increased wetness, enhanced evapotranspiration, and latent heat flux.Multispectral and thermal UAV monitoring, coupled with in-situ instrumental monitoring, was used to acquire data on spatial, quantitative, and qualitative changes in peatland response to restoration aimed at plugging the drains built in the past decades. In particular, we investigated: (i) the change in total surface water extent after peatland restoration, (ii) the LST response of restoration dikes, and (iii) the distribution of LST in restored peatlands.The study was conducted in the montane peat bog of Rokytka in the Šumava Mountains, one of Central Europe's largest montane peatland complexes. The monitoring covered the vegetation seasons from 2018 to 2023, a period of extensive restoration activities in the peatland headwaters, allowing assessment of both pre-and post-restoration conditions.The very high spatial resolution of the spatial data allowed us to analyze changes in peatland area in terms of canopy structure, wetness, and thermal response. The results showed a significant expansion of the waterlogged surface of the peatland due to the clogging of the former drains. However, the land surface temperature analysis indicates that the newly constructed dike systems have only a limited cooling effect compared to the thermal regime of the natural peatland vegetation. Furthermore, the analysis of new and old dike systems showed a continuous decrease of their positive effect.The study proved that UAV monitoring is a unique monitoring technique that allows obtaining objective information on the thermal effects of peatland restoration, separating their effects from the properties of the surrounding environment, and objectively assessing their impact on the peatland thermal regime.
Towards global monitoring and seasonal forecasting of wildfire hazards based on a global hydrological model
Authors: Trautmann Tina , Doell Petra
Published: March 2024

Over the last decades, the frequency and magnitude of wildfires increased worldwide, posing a risk not only for people and infrastructure, but also for the environment. To enable preventive and protective measures it is crucial to monitor and forecast wildfire hazards. Existing systems derive wildfire indices from meteorological data or include remote-sensing-based observations, such as soil moisture anomalies and the state of vegetation health. However, their ability to forecast wildfire hazards into the future is very limited.Therefore, we here suggest utilizing the potential of a global hydrological model to not only monitor, but also provide seasonal forecasts of wildfire hazards globally. To do so, we force the global water resources and use model WaterGAP by meteorological data from ERA5 reanalysis and SEAS5 seasonal ensemble forecasts. Model output, including for example soil moisture anomalies, are combined with meteorological data to derive indicators for wildfire hazards at a global scale. We assess the capability of such indicators to reflect spatio-temporal pattern of wildfire hazards during the year 2018 by performing a regional analysis.Eventually, derived wildfire hazard indicators can be made available for stakeholders via the operational multi-sectoral global drought monitoring and seasonal forecasting system (OUTLAST) on WMO’s HydroSOS web portal.
A time-dependent three-dimensional magnetopause model based on quasi-elastodynamic theory
Authors: Gu Yaxin , Wang Yi , Wei Fengsi , Feng Xueshang , Samsonov Andrey , Song Xiaojian , Chen Yalan , Wang Boyi , Zuo Pingbing , Jiang Chaowei
Published: March 2024

The interaction between the solar wind and the Earth’s magnetosphere is one of the most important research topics in space weather and space plasma physics. The finding of the exact magnetopause position significantly enhances our knowledge of magnetospheric response to solar wind variations. While numerous magnetopause models have been constructed in the past decades, a substantial portion of them remains time-independent models, posing limitations in elucidating the dynamic movement of the magnetopause under varying solar wind conditions. This study pioneers the establishment of a time-dependent three-dimensional magnetopause model grounded in the quasi-elastodynamic pressure theory, named the POS (Position, Overall oscillation and Surface wave like-structure) model. In contrast to the existing time-dependent magnetopause models (except for numerical simulations), the POS model transcends the one-dimensional framework, providing a real-time depiction of magnetopause position and shape alterations. The model's validity is substantiated through comparisons with satellite observation. Based on an extensive dataset of satellite magnetopause crossings (exceeding 40,000 magnetopause crossing events), the POS model exhibits superior predictive accuracy (as evaluated by root-mean-square error) compared to six widely employed magnetopause models. Remarkably, the POS model demonstrates heightened efficacy under highly disturbed solar wind conditions as well as in high-latitude and flank region of magnetopause and it possesses characteristics as predictive accuracy, concise formulation, and fast computational speed. The introduction of a time-dependent three-dimensional dynamic magnetopause model not only advances our comprehension of the physical processes in space plasma and enhances our predictive capabilities for space weather on the Earth but also provides valuable insights into the dynamic processes in the magnetospheres of other planets. 
Autoregressive extensions of EMOS with application to surface temperature ensemble postprocessing
Authors: Möller Annette , Jobst David , Groß Jürgen
Published: March 2024

Two extensions of the autoregressive EMOS (AR-EMOS) which are based on the idea of smooth EMOS (SEMOS) model are proposed: The de-seasonalized EMOS (DAR-SEMOS) approach models time series behavior in the mean and variance of the predictive distribution separately, the standardized AR-SEMOS (SAR-SEMOS) method attempts to incorporate both effects jointly by fitting a time series model to the standardized forecast errors. The proposed modifications both allow to incorporate seasonal and trend effects as well as autoregressive behavior into the mean and variance parameter of the predictive distribution. Due to this explicit modelling of seasonal and trend behavior a rolling training period is not required anymore, and a longer (static) training period can be utilized for model fitting. The extended models can postprocess ensemble forecasts with arbitrary forecast horizons. In a case study for 2m surface temperature the extensions DAR- and SAR-SEMOS yield substantial improvements over AR-EMOS and SEMOS, for all considered forecast horizons and at the majority of observations stations. Overall, the SAR-SEMOS model yields the most noticeable improvements. At the same time its seamless approach of jointly modelling the time series behavior in the mean and variance parameter makes it appealing for practical and possibly operational use.
Cryptotephra quantification in lake sediments: Two workflows developed for sites with distant Laacher See tephra fallout
Authors: Meier Verena , Hrstka Tomáš , Ohser Joachim , Brandstätter Bianca , Kletetschka Gunther , Vondrák Daniel
Published: March 2024

Cryptotephra research has emerged as a major tool for determination of the age of sediments and unraveling the relationship between past volcanic events and their environmental impacts. Lacustrine deposits are particularly important for continental tephra research. Lakes provide relatively stable environments conducive to the long-term preservation of (crypto)tephra layers, forming valuable continental cryptotephra archives. While studies on fingerprinting of marine tephras and peat samples are more common, the identification and quantification of cryptotephra within lacustrine records remains an underexplored area.    In this study, we introduce innovative workflows for the quantification of cryptotephra, particularly in lake sediments with distant Laacher See tephra fallout, which represents the most important stratigraphic marker in late-glacial deposits in Central Europe. Our approach initiates with the identification of potential cryptotephra positions and thickness of the deposits, accomplished through the integration of magnetic susceptibility (MS), X-ray fluorescence (XRF), and computer tomography (medical- and micro-CT) to precisely delineate the extent of the cryptotephra layer within the sediments. The subsequent step evaluates presence and identifies the source of the present cryptotephra layer. This is accomplished using scanning electron microscopy (SEM) and polarizing microscopy to visually confirm the presence of cryptotephra and investigate its geochemical fingerprint, enabling linkage to a specific volcanic eruption.    The key element of our study are methods for quantifying cryptotephra glass shards within sedimentary records. Shard extraction using stepwise flotation with heavy liquids and quantification using standardized markers and a polarizing microscope provides a robust, straightforward laboratory-based technique. Additionally, we offer an innovative, software-based alternative that combines TIMA analysis on thin sections with customized image analysis to study the area fraction of the glass phase, its depth-dependent variation, particle density with a focus on clustering behavior, depth-dependent particle count, total particle count, and particle size distribution within the glass phase.    The significance of both methods lies in the efficiency and precision of cryptotephra quantification, enabling a deeper understanding of shard concentration, depth-dependent shard distribution, as well as multi-site comparison of shard influx within continental cryptotephra deposits.
Spatio-temporal variability of hydrological connectivity through interflow
Authors: Klaus Julian , Schultze Philipp , Jackson Rhett
Published: March 2024

Interflow is lateral subsurface flow in hillslopes during and after precipitation events moving above a restrictive layer of lower hydraulic conductivity soil and rock. Interflow thus becomes more important in steeper hillslopes with a high contrast between the hydraulic conductivities of the layers that impede vertical water movement. However, the travel distance of a water parcel downslope in a perched water body is limited due to potential percolation of water through the impeding layer. This potential travel distance of interflow can be described with the concept of "Downslope Travel Distance" (DTD) that applies to temporary, perched groundwater in hillslopes. The determination of this downslope travel distance in catchments is possible with available topographic and subsurface data. Yet, how this interflow connects to the catchment outlet is poorly understood and depends on the spatio-temporal extension and contraction of the stream network. This presentation introduces the concept of DTD and employs calculations based on published data from various catchments and landscapes. In these catchments, DTDs ranged from about just one meter to over several hundred meters. Yet, the DTDs on must hillslopes with data are less than 50 m and less than 30% of the hillslope length showing that most shallow perched water percolates through the impeding layer before contributing to valley water or streamflow via interflow. In a subsequent step, we illustrate the spatial and temporal variability of the area connecting to the catchment outlet via interflow and thus contributing to discharge in different catchments. While soil properties and topographic characteristics generally remain stable over short periods, the wetted stream network undergoes notable changes both in the short and long term. Consequently, the pronounced variability of the area connecting to the catchment outlet via interflow is observable and characteristic for individual catchments. Lastly, we emphasize the present significant constraints of experimental studies and data concerning hillslopes in different landscapes, underscoring the necessity for revisiting research on runoff generation at the hillslope scale.
Harnessing Heterogeneous Sources of Data and Artificial Intelligence for Hydrologic Monitoring
Authors: Goharian Erfan , Erfani Seyed Mohammad Hassan , Hatami Goloujeh Mehdi
Published: March 2024

The persistent global threat of water-related challenges, particularly floods, necessitates a paradigm shift towards harnessing new technologies, heterogeneous sources of data, and novel techniques to enhance data availability and innovative sensing techniques in hydrology. Emerging data sources, including ground-based cameras, smart hydrologic monitoring systems, citizen observatories, and crowdsourcing, along with innovative techniques like Artificial Intelligence (AI), provide diverse yet novel data sources for more effective monitoring, modeling, and management. This research contributes to this transformative journey by exploring the integration of real-time imagery data from different tools and sources into hydrologic monitoring. Highlighting our efforts is the development of ATLANTIS, the first comprehensive image dataset for semantic segmentation of water bodies and associated objects. We introduce AQUANet, a state-of-the-art deep neural network crafted for precise waterbody segmentation, addressing challenges such as flood detection and inundation mapping. The study further demonstrates flood modeling using cutting-edge deep learning networks, including PSPNet, TransUNet, and SegFormer. Rigorous comparisons against reference data collected through field instruments and sensors underscore the superior performance of SegFormer, achieving an impressive 99.55% Intersection over Union (IoU) and 99.81% accuracy in hydrological monitoring, specifically in water level estimation at our testbed rivers and channels. In conclusion, this presentation not only showcases achievements in flood monitoring using innovative AI techniques and diverse data sources but also discusses how future studies can contribute to the ongoing discourse on the application of advanced technology in hydrologic monitoring systems, paving the way for further innovation and improvements in flood management.