bluuebunny/crossref_metadata_2025 huggingface dataset:
A Stochastic Approach to Quantifying Uncertainty in Soil Organic Carbon
Authors: Inforsato Leonardo , Rosso Pablo , Raza Ahsan , Main-Knorn Magdalena , Nendel Claas
Published: March 2024

Soil organic carbon (SOC) is a key driver of soil hydraulic properties like, field capacity and wilting point, necessary for in-field scale yield prediction using tipping bucket models. However, the labor-intensive nature of obtaining spatially distributed SOC often leads to its extrapolation using satellite imagery, resulting in significant inaccuracies in SOC prediction. In this study, we propose a Monte Carlo-based (MC) procedure to quantify the propagation of SOC error to simulated yield estimates. This procedure stochastically generates data, considering both uncorrelated and correlated data. For uncorrelated data, each SOC value is generated following an independent normal distribution. For correlated data, covariances are considered, accounting for the spatial correlation of in-field SOC variability. The autocorrelation between each pair of pixels is calculated, building a correlation matrix, which is submitted to the Cholesky decomposition, resulting in a lower triangular matrix. This matrix is then used to generate correlated SOC values for each pixel, maintaining the shape of the SOC clusters while varying the SOC value in each pixel according to its error. We validated our methodology using synthetic data, then used the methodology to assist error propagation of SOC with true data in a field located in Booßen, Germany. We generated 5000 SOC images, each with approximately 6000 pixels, and simulated the yield for each pixel. The results were analyzed by the field as a whole and each pixel across different images, by generating probability distributions for both. Another comparison was made by direct measurement between measured and simulated yields. Our results confirm the consistency of our method. In the specific scenario analyzed, preliminary results show that the SOC uncertainty was sufficient to explain the entire difference between the true and estimated crop yield, highlighting the importance of accurately assessing SOC uncertainty in yield prediction models.
Balancing-oriented hydropower operation makes the clean energy transition more affordable and simultaneously boosts water security
Authors: He Xiaogang , Liu Zhanwei
Published: March 2024

Reservoir hydropower offers a compelling combination of stability and flexibility services for modern water and power grids. However, its operating flexibility is poorly characterized in energy system planning, missing opportunities to cost-effectively uptake variable renewable energy (VRE) for a clean energy transition. In this study, we have developed a fully coupled reservoir operation and energy expansion model to quantify the economic and environmental benefits attained from adaptive hydropower operation in a high VRE future. Our case study of the China Southern Power Grid reveals that, in a 2050 net-zero grid, simply adapting hydropower operations to balance VRE can reduce 2018–2050 total system costs by 7% (that is, US$28.2 billion) and simultaneously save 123.8 km3 of water each year (that is, more than three times the reservoir capacity of the Three Gorges Dam). These vast, yet overlooked, cost- and water-saving potentials highlight the importance of incorporating balancing-oriented hydropower operation into future pathways to jointly decarbonize and secure power and water grids.
A coupled O2-CO2 model to understand CO2 source partitioning in flowing freshwaters
Authors: Diamond Jacob , Bertuzzo Enrico
Published: March 2024

The freshwater riverine carbon budget has an unexplained imbalance (~1.5 Pg-C y−1) between estimates of terrestrial C lateral imports and freshwater emissions. This imbalance may be resolved by investigating the source of freshwater CO2 emissions. That is, what proportion of the excess CO2 in rivers comes from lateral CO2 inputs (external, allochthonous sources) versus from riverine respiration of organic matter (internal, autochthonous sources)? We address this question by developing a model to estimate the reach-scale dissolved inorganic carbon (DIC) mass balance using sub-daily time series of dissolved O2 and CO2. The approach extends the classical single station model for the estimation of stream metabolism based on O2 observation by coupling the mass balance of DIC with the lateral input of water, O2 and DIC, and the mass balance of total alkalinity. Here, we present the results of the model application to several study sites across varying discharge and carbonate chemistries. We further show the model's utility in estimating magnitudes of river metabolism, lateral DIC concentration, photosynthetic and respiratory quotients, and carbon flux to the atmosphere.
Mapping gas seeps with multibeam water column data in the Norwegian offshore – Challenges and way forward
Authors: Chand Shyam , Schimel Alexandre C. G. , Thorsnes Terje , Bellec Valérie
Published: March 2024

Seepage of gases from natural sources of subsurface hydrocarbon accumulations escaping through the seafloor to the water column is recorded in many parts of the world’s oceans. These occurrences can be acoustically and visually observed using various sensors onboard various platforms. This is particularly common when carrying out bathymetric surveys of large areas using multibeam echosounder systems with the capability of recording the whole water column acoustic backscattering. The so-called “water-column data” that these systems produce can then be inspected for acoustic anomalies that are characteristic of gas seepages (i.e. acoustic “gas flares”), and those instances and their attributes (e.g. strength, confidence, height, etc.) can be recorded in a database. The Geological Survey of Norway has been building such a database for the Norwegian offshore since 2010. To date, this database includes over 5,000 flares of varying magnitudes and sizes, detected in an area of >140,000 km2. The water-column data used for this task mainly originates from the many multibeam surveys carried out since 2005 over large areas of the Norwegian offshore for the MAREANO program, which is aimed at mapping habitats, but also from datasets acquired in associated projects and sources.We present the results from these comprehensive surveys and discuss the various challenges faced in making such a database. Our main challenges are the very large size of the datasets and our reliance on visual interpretation, which necessitate dedicated software, high-performance processing systems, storage solutions of very large capacity and fast access, considerable interpretation time, and procedures of cross-validation between different interpreters. Another challenge is the variety of the data and its quality due to various acquisition parameters, weather conditions, and water depths, but also from the use of various systems, models, generations, and frequencies. This variety impacts the visual aspect of acoustic gas flares and thus affects the ability of the interpreters to consistently estimate flare magnitude and size. However, this variety also presents research opportunities. For example, we possess several instances of acoustic gas flares that were imaged with a range of frequencies, allowing for frequency dependence analysis. Finally, we will discuss future possibilities for interpreting water-column data in more time-efficient and interpreter-independent manners.
Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
Authors: Lu Bin , Zhao Ze , Han Luyu , Gan Xiaoying , Zhou Yuntao , Zhou Lei , Fu Luoyi , Wang Xinbing , Zhang Jing , Zhou Chenghu
Published: March 2024

Oxygen is fundamentally essential for all life. Unfortunately, recent research has shown that global ocean deoxygenation has significantly increased over the past 50 years, and the stock of dissolved oxygen (DO) in the ocean has been continuously decreasing. Breathless ocean has led to large-scale death of fish, seriously affecting the marine ecosystem. Moreover, global warming and human activities have further intensified the expansion of dead zones (low-oxygen area) in the ocean.Hence, it is of vital importance to quantitatively understand and predict the trend of global ocean deoxygenation. However, despite of the accumulation of in-situ DO observation in recent years, global and long-term observation data is still severely sparse, leading to a critical challenge in reconstructing global ocean deoxygenation over a century. Existing works can be categorized into two ways: (1) Physics-informed numerical models. These methods simulate the DO concentration based on climate models without utilizing in-situ observations, e.g., Coupled Model Intercomparison Project Phase 6 (CMIP6). However, these models fail to adjust biased simulation results based on temporal DO observations and cause error propagation. (2) Spatial interpolation methods. These methods reconstruct the global deoxygenation through available observations by geostatistical regression, Kriging, etc. But these ways are unable to capture the complex spatiotemporal heterogeneity and physical-biogeochemical properties, showing inconsistent performance in different areas.To this end, we propose a knowledge-infused deep graph learning method called 4D Spatio-Temporal Graph HyperNetwork (4D-STGHN) to reconstruct four-dimensional (including time, latitude, longitude, and depth) global ocean deoxygenation from 1920 till now. To capture the spatio-temporal heterogeneity in different regions, 4D-STGHN utilize hypernetwork to generate non-shared parameters by fusing 4D geographic information and observations. Moreover, we design a chemistry-informed gradient norm mechanism as the loss function by integrating the observation of nitrate and phosphate, hereby further improving the performance of DO reconstruction. 4D-STGHN shows promising reconstruction with mean absolute percentage error (MAPE) of only 5.39%, largely outperforming three CMIP6 experiments (CESM2-omip1, CESM2-omip2 and GFDL-ESM4-historical) on dissolved oxygen and other machine learning methods. Further analysis on the global oxygen minimum zones, as well as regional analysis are conducted to evaluate the effectiveness of our proposed methods.
A mechanistic reproduction of particle transformation via fragmentation and diel vertical migration 
Authors: Naidoo-Bagwell Aaron , Monteiro Fanny , Visser Andre , Henson Stephanie
Published: March 2024

The export efficiency of the biological carbon pump depends on a multitude of processes that can affect the sinking speed of particulate organic matter (POC). The uncertainty surrounding factors that promote particle aggregation (e.g. through transparent exopolymer particles – TEP), remineralization (e.g. via microbes) and zooplankton consumption and fragmentation (e.g. coprophagy) has led to inconsistent estimates and future predictions for global export flux amongst earth system models. Two of the most unaccounted-for and least understood processes for constraining these simulations of POC flux are fragmentation and diel vertical migration (DVM) by zooplankton, with the majority of CMIP6 model omitting these from their frameworks. Fragmentation rates can be physically-mediated (e.g. turbulent shear) or biologically-mediated (e.g. “sloppy feeding” by zooplankton) and drive remineralization and thus flux attenuation. Another zooplankton activity, DVM, also contributes to export flux. the resulting export flux. DVM, where organisms nocturnally migrate to surface waters to feed and descend during the day, has great implications for biogeochemical fluxes of nutrients and provides a mechanism for POC to bypass potential transformation via fecal pellet production at depth. Here, we use a 1-dimensional particle model (SISSOMA) that includes mechanistic descriptions of key particle transformation processes (aggregation, remineralization, fragmentation etc.) to explore the potential consequences of fragmentation and DVM. SISSOMA enables study into the formation and fate of particles in the mixed layer, producing particle size distributions of the flux exported. Through sensitivity tests on the drivers of fragmentation rates, fed by Underwater Vision Profiler (UVP) and Biogeochemical-Argo floats observations, we can determine what drives particle size distribution and ultimately carbon export. We apply a DVM component to SISSOMA, driven by ecological observations of migrating zooplankton (e.g. EcoTaxa) to investigate the extent to which this process contributes to export flux and its particle size composition. We implore future modelling and observationally-based studies related to constraining the biological pump to consider these processes when designing their research.
Predicting global soil organic carbon dynamics in tidal marshes
Authors: Maxwell Tania L. , Spalding Mark , Worthington Thomas A. ,   global marsh soil C team
Published: March 2024

Tidal marshes are known for their capacity to store large amounts of carbon in their water-logged soils; however, this coastal ecosystem is threatened by land conversion, climate change, and habitat degradation. Therefore to support conservation efforts, it is important to accurately quantify and map the benefits of this ecosystem such as their current soil organic carbon (SOC) stocks. Based on the newly developed tidal marsh extent map by Worthington et al. (2023), we produced the first global spatially-explicit map of SOC storage in tidal marshes at 30 m resolution, as well as presenting the uncertainty and limitations around the predictions  To produce our predictions, we used training data from the recently published global tidal marsh soil organic carbon (MarSOC) dataset, supplemented by data from the Coastal Carbon Research Coordination Network database. We modelled SOC in relation to potential landscape-level environmental drivers, including vegetation indices, elevation, tidal amplitude, and climatic variables. Finally, we trained a random forest model using the dataset and the environmental covariates, taking into account the spatial nature of the data in the cross validation. We applied a new area of applicability method from Meyer & Pebesma (2021) to avoid predicting SOC values into unknown space, and estimated pixel-level uncertainty using the predicted model error. Globally the model predicts on average 83.09 Mg SOC ha-1 (average predicted error 44.77 Mg ha-1) is held in the 0-30 cm layer and 185.27 Mg ha-1 (average predicted error 105.71 Mg ha-1) in the 30-100 cm layer. However due to the current sparsity of data in places, the area of applicability of the model for the 0-30 cm layer represents 58.0% of mapped marshes and this drops to 46.2% for the 30-100 cm layer. Considering the total tidal marsh extent, we estimate tidal marshes to hold 1.44 Petagrams of SOC to 1 m globally. Regionally, higher predicted stocks per unit area are found in the Arctic; however, this is confounded by high uncertainty. The Temperate Northern Atlantic is estimated to hold the highest amount of carbon due to the large tidal marsh extent in this region. Due to the lack of training soil carbon data we were unable to provide accurate predictions in several areas, therefore our approach also highlights the need for further sampling efforts in specific geographies. It also highlights the needs for the development of additional global covariate layers, to improve our estimates on SOC stocks in tidal marshes. Notwithstanding, our model and map will be valuable to support conservation efforts, aiding the implementation of blue carbon actions in Nationally Determined Contributions.
Effects of Anthropogenic Emissions on Secondary Organic Aerosol Formation from Biogenic Volatile Organic Compound
Authors: Xie Guangzhao , Voliotis Aristeidis , Bannan Thomas , Coe Hugh , McFiggans Gordon
Published: March 2024

Atmospheric secondary organic aerosols (SOA) can significantly affect air quality, climate, and human health. The formation of SOA is attributable to the vapour phase oxidation of biogenic or anthropogenic organic compounds and subsequent partitioning to the particulate phase. The oxidation of biogenic volatile organic compounds (bVOCs), such as monoterpenes, has received extensive attention owing to their larger global emissions compared with anthropogenic volatile organic compounds (aVOCs). α-Pinene, constituting nearly 50% of the global monoterpene emissions and with a high SOA forming efficiency is thereby considered one of the most important SOA precursors in the atmosphere.The essential characteristics of α-pinene SOA, such as the oxidation pathways, molecular constitutions, volatility, and yields, have been widely studied in chamber experiments. However, most of them focused on single precursor systems. In the real atmosphere, SOA formation is influenced by the interactions of other molecules. Human emissions, such as the aVOCs, NOx, and CO, are likely to affect α-pinene SOA formation processes. Thus, the chamber investigation on SOA formation should be considered more realistically. Establishing a framework to understand the interactions of mixed SOA precursors in the presence of NOx and CO is needed.Diesel vehicular emission is an important anthropogenic source for SOA precursors in urban areas. n-Dodecane (C12H26) represents a reasonable proxy for intermediate volatility organic compounds (IVOC) in diesel exhaust. In this study, we plan to investigate the SOA formation from (i) α-pinene and n-dodecane system and (ii) α-pinene and diesel exhaust system, under controlled NOx and CO conditions.The experiments are conducted at the Manchester Aerosol Chamber (MAC) facility, which is an 18 m3 fluorinated ethylene propylene bag. A combination of gas-phase and particle-phase analytical instruments are employed for the experiments: High-Resolution Time-of-Flight Chemical Ionization Mass Spectrometer with a Filter Inlet for Gases and Aerosols (FIGAERO-CIMS) equipped with iodide reagent, Proton-transfer-reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS), Differential Mobility Particle Sizer (DMPS), Compact Time-of-Flight Aerosol Mass Spectrometer (C-ToF-AMS), and Gas Analysers.This work reports the changes in SOA compositions, SOA particle volatility, and yields in the mixtures of α-pinene and n-dodecane/diesel exhaust under controlled NOx and CO conditions. The results provide new insights into SOA formation in mixtures.
Precipitation fuels dissolved greenhouse gas (CO2, CH4, N2O) dynamics in a peatland-dominated headwater stream: results from a continuous monitoring setup
Authors: Piatka David , Nánási Raphaela , Mwanake Ricky , Engelsberger Florian , Willibald Georg , Neidl Frank , Kiese Ralf
Published: March 2024

Stream ecosystems are actively involved in the biogeochemical cycling of carbon (C) and nitrogen (N) from terrestrial and aquatic sources. Streams hydrologically connected to peatland soils are suggested to receive significant quantities of particulate, dissolved, and gaseous C and N species, which directly enhance losses of greenhouse gases (GHGs), i.e., carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and fuel in-stream GHG production. However, riverine GHG concentrations and emissions are highly dynamic due to temporally and spatially variable hydrological, meteorological, and biogeochemical conditions. In this study, we present a complete GHG monitoring system in a peatland stream, which can continuously measure dissolved GHG concentrations and allows to infer gaseous fluxes between the stream and the atmosphere and discuss the results from March 31 to August 25 at variable hydrological conditions during a cool spring and warm summer period. Stream water was continuously pumped into a water-air equilibration chamber, with the equilibrated and actively dried gas phase being measured with two GHG analyzers for CO2 and N2O and CH4 based on Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) and Non-Dispersive Infra-Red (NDIR) spectroscopy, respectively. GHG measurements were performed continuously with only shorter measurement interruptions, mostly following a regular maintenance program. The results showed strong dynamics of GHGs with hourly mean concentrations up to 9959.1, 1478.6, and 9.9 parts per million (ppm) and emissions up to 313.89, 1.17, and 0.40 mg C or N m−2h−1 for CO2, CH4, and N2O, respectively. Significantly higher GHG concentrations and emissions were observed shortly after intense precipitation events at increasing stream water levels, contributing 59% to the total GHG budget of 762.2 g m−2 CO2-equivalents (CO2-eq). The GHG data indicated a constantly strong terrestrial signal from peatland pore waters, with high concentrations of dissolved GHGs being flushed into the stream water after precipitation. During drier periods, CO2 and CH4 dynamics were strongly influenced by in-stream metabolism. Continuous and high-frequency GHG data are needed to assess short- and long-term dynamics in stream ecosystems and for improved source partitioning between in-situ and ex-situ production.Piatka DR, Nánási RL, Mwanake RM, Engelsberger F, Willibald G, Neidl F and Kiese R (2024) Precipitation fuels dissolved greenhouse gas (CO2, CH4, N2O) dynamics in a peatland-dominated headwater stream: results from a continuous monitoring setup. Front. Water 5:1321137. doi: 10.3389/frwa.2023.1321137
Freddy: breaking record for Tropical Cyclone precipitation?
Authors: Scoccimarro Enrico , Lanteri Paolo , Cavicchia Leone
Published: March 2024

Depending on the location on the Earth planet, the amount of precipitation associated with Tropical Cyclones (TCs) can reach 20% of the total yearly precipitation over land and up to 40% over some ocean regions. TC induced freshwater flooding has been suggested as the largest threat to human lives due to TCs. Therefore, a reliable quantification of the precipitation amount associated with each past TC is important for a better definition of the TC fingerprint on the climate. The temporal and horizontal resolution of state-of-the-art observational datasets and atmospheric reanalysis give the possibility to quantify the TC-associated precipitation over the Earth planet following the observed TC tracks. In this work we compare results from different observational and reanalysis datasets in terms of TC-associated precipitation, to verify the consistency between them. A particular focus is given to the record-breaking TC Freddy (Southern Indian Ocean, 2023).  Here we show that the time-varying bias in TC associated precipitation, due to the positive trend in assimilated observations, makes it difficult to assess long-term trend investigation based on reanalysis: to this aim we need to build on state-of-the-art General Circulation Models, free to evolve under historical radiative forcing. This work is part of CLINT EU project activity (grant agreement ID: 101003876; DOI: 10.3030/101003876).
Quantifying daily volcanic SO2 emissions on a global scale
Authors: Esse Ben , Burton Mike , Hayer Catherine , Queißer Manuel
Published: March 2024

The expression of volcanic activity at the Earth’s surface is accompanied by the emission of a cocktail of different gases, including water, carbon dioxide, sulphur species, halogens and metals. The composition and magnitude of these emissions reflects the state of magmatic systems, providing insights into volcanic processes and key hazard monitoring information. Many of these products also have serious health implications for local communities and are important species for the global climate. The primary target species for quantification of volcanic emissions is SO2, due to its high prevalence in volcanic emissions, its low typical atmospheric concentration and the ability to detect it remotely using UV and IR spectroscopy from both ground and space.Satellite instruments provide a global view of volcanic activity through a combination of geostationary and polar orbiting platforms. This is particularly useful for remote or difficult to reach volcanoes, as well as for identifying eruptions from those which have not been historically active. Most previous satellite work has focused on explosive eruptions due to the decreased sensitivity of satellites to SO2 lower in the atmosphere, however recent advances in instrumentation and processing algorithms have opened the possibility of detecting and quantifying passive emissions in the troposphere.In this work we combine daily SO2 imagery from the TROPOMI satellite instrument with the PlumeTraj back-trajectory analysis toolkit to detect and quantify daily eruptive and non-eruptive SO2 emissions as a function of time and altitude from volcanoes globally throughout the year 2020. We consistently detect more than 20 degassing volcanoes per day, dominated by non-eruptive emissions. We also investigate the emissions with respect to latitude, tectonic setting and volcano type.These results demonstrate the ability of TROPOMI and PlumeTraj to provide daily automatic SO2 emissions for volcanoes globally. In the future, this analysis will be extended to the full TROPOMI dataset (from 2018 to present) as well as to the development of a near real-time processing workflow. This will generate an invaluable dataset of volcanic degassing for investigating volcanic processes and characterising SO2 emissions as a function of latitude and altitude, an important input for global climate modelling. Finally, the near real-time analysis will provide a key monitoring tool for volcano observatories worldwide.
Global Modeling of Organic-related New Particle Formation and its Contribution to Global Aerosol Number Concentrations using CAM6-Chem
Authors: Shao Xinyue , Wang Minghuai , Carslaw Ken , Dong Xinyi , Liu Yaman
Published: March 2024

New particle formation involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Here a global chemistry-climate model has been developed to include explicit chemical reactions of highly oxygenated molecules (HOMs) and accretion products based on monoterpene-derived peroxy radical (RO2) unimolecular autoxidation and self- and cross-reactions with other RO2 species. The improved model incorporates a comprehensive biogenic organic nucleation scheme including heteromolecular nucleation of sulfuric acid and organics, neutral pure organic nucleation, and ion-induced pure organic nucleation. These organic-related mechanisms are combined with an inorganic nucleation scheme derived from published chamber experimental data from the CLOUD project. Additionally, the organic condensational growth rate for newly formed particles (sub-20nm) is taken into account. The updated model captures the occurrence frequency of new particle formation events (normalized mean bias, NMB changes from -96% to -15%) and shows reasonable agreement with measured rates of nucleation (NMB changes from -97% to -64%) and growth (NMB changes from -54% to 39%) globally except in China (NMB of nucleation rate > -100%). The model successfully reproduces surface-level aerosol number concentrations over oceans and vertical profiles over the Amazon Basin. Globally, we find that organics contribute to 45% of the annual average vertically integrated nucleation rate and 25% of the vertical mean growth rate. The inclusion of organic-related processes leads to a 39% increase in the global annual mean aerosol concentration and a 33% increase in cloud condensation nuclei at 0.5% supersaturation compared to a simulation with only inorganic nucleation. Our work also indicates that organic initial growth is more important for particle number than organic nucleation on global average.
The 3D anatomy of magma transport in fast-spreading oceanic crust of the Oman ophiolite
Authors: Morris Antony , Parsons Andrew , Harris Michelle , MacLeod Chris , Ildefonse Benoit , Atton Charlotte , Allerton Simon , Gürer Derya
Published: March 2024

At fast-spreading oceanic ridges such as the East Pacific Rise, divergence between tectonic plates is accommodated almost exclusively by magmatic accretion. A robust understanding of magmatic accretion during seafloor spreading is therefore necessary to model the structure and composition of oceanic lithosphere and exchanges in heat and mass at a global scale over geological time. Whereas most models consider magmatic accretion in 2D, variations in ridge axial morphology and magmatic compositions highlight the occurrence of ridge-parallel variations in magmatic processes along fast-spreading systems. This suggests that magmatic accretion may be a 3D process involving significant ridge-parallel magma transport.To constrain the process of magmatic accretion at fast-spreading ridges, we present our on-going investigation of magma transport in the Oman ophiolite. The first order structure and composition of the ophiolite, defined by a sheeted dyke complex with an underlying axial melt lens of variable thickness on top of foliated gabbro, is analogous to the East Pacific Rise. This provides a unique opportunity to investigate magmatic accretion processes above and below an axial melt lens system in three dimensions at ridge segment- to grain-scales for the first time.We present new data constrains the directions of magma transport in the crust of the Oman ophiolite. This includes analyses of foliated gabbros and sheeted dyke complexes from the Fizh, Salahi, and Sarami blocks, which define a complete ridge segment. Using anisotropy of magnetic susceptibility (AMS), we report the orientations of magnetic fabrics that serve as proxies for magmatic flow directions. Combining AMS data with paleomagnetic analyses of magnetic remanence directions allows us to restore magmatic flow directions to their paleo-ridge orientation, prior to obduction. Our results indicate that magmatic flow directions vary along the length of the ridge segment and cannot be explained by simple 2D models. Our data show that ridge-parallel lateral flow is a common phenomenon in both the sheeted dykes and foliated gabbros over the length of a ridge segment. Our results also have important implications for competing models of crustal accretion.
Analyzing the fixed or variable effect of considering hydrological loss functions on the runoff coefficient in continuous modeling
Authors: Eslami Zahra , Abdollahi Khodayar , Kirchner James
Published: March 2024

Hydrological losses play a significant role in determining the runoff coefficient, influencing the amount of precipitation that ultimately contributes to surface runoff. These losses are influenced by various characteristics, including rainfall, the physical and geographical attributes of the watershed (such as slope and land use), and the soil moisture content within the watershed.Here, we evaluate the effect of the variability of the loss function on the amount of simulated runoff and the runoff coefficient in specific watersheds in Iran. The investigation entails the assessment of two distinct conditions. First, the runoff coefficient is calculated under the assumption of a constant loss, utilizing the φ index. Second, a variable loss function, derived from a soil moisture algorithm, is employed to determine the runoff coefficient.Our analysis shows that the assumption of a variable loss function yields more realistic results. When the variable losses are considered, the simulated runoff coefficient is closer to the observed values and determines the runoff coefficient for all months, including those characterized by low rainfall. The constant loss φ index exhibits two significant practical limitations: the overestimation of runoff coefficient values, and an inability to estimate runoff coefficient during months with low rainfall. The study emphasizes the need for a variable loss function to provide more realistic results. Our findings suggest that utilizing the variable loss function within the soil moisture algorithm produces more accurate results. Thus, the application for improved forecasting of rainfall and runoff processes is recommended. 
A portable luminescence dating instrument: a new insight for in-situ Earth applications
Authors: Di Iorio Alessio , Pascucci Vincenzo , Filippone Roberto , Di Iorio Giulia , Sechi Daniele , Andreucci Stefano , Di Pietro Ilaria
Published: March 2024

The age determination is crucial to unravel the evolution and to provide a framework of the geological, paleo-anthropological, and cultural conditions of a specific region of interest. The lack of chronological information makes difficult to correlate the site of interest with other temporal attributes provided by stratigraphy and paleoclimatology. Luminescence is a well-established dating technique for determining the absolute age of formation (or most recent reworking event) of geological deposits/sediments and archaeological finds on Earth, with a time range that spans from the last few decades up to one million years. The most common geological targets are dust, silt, sand, cobbles, and rock outcrops originating from different environments: aeolian, fluvial, alluvial, lacustrine, marine, glaciogenic, slope deposits, karstic, soils, tectonic activity. In the archaeological field, this technique is applied not only to the geological sediments in excavation sites but also directly to artifacts of interest, especially when they are made of pottery or stone.A miniaturized luminescence dating prototype for in-situ examination has been designed by Alma Sistemi S.r.l., Guidonia, Italy, and validated by University of Sassari, Sassari, Italy, under European Union H2020-MSCA-RISE-2018 research programme (G.A. n.823934). The instrument is equipped with an infrared and blue optical stimulation subsystem to perform both optically and infrared-stimulated luminescence (OSL, IRSL) and is able to measure both paleo-dose and dose rate. An X-ray generator (XRG) irradiates the sample, while the response luminescence signal is obtained through a photon counting photomultiplier tube (PMT). A thermal subsystem consisting of a heater and air-cooling pumps allows the instrument to heat during SAR (single-aliquot regenerative-dose) procedure and to perform thermally stimulated luminescence. Remote control for data analysis application and a battery power supply are implemented on the instrument for usage on the field.The development of this portable instrument is of great relevance since it finds practical use in geological and archaeological Earth's field applications. In fact, compared to current luminescence dating technologies and considering its reduced dimensions (11x11x18 cm excluding electronic box and cover) and weight (currently
Enhancing Water Quality Monitoring: An Integrated Machine Learning Framework with Physical Constraints for Imputation and Time Series Downscaling
Authors: Li Leifang , Yang Dawen
Published: March 2024

Extreme climate change can lead to a drastic deterioration in water quality. However, researchers often struggle to find long-term water quality monitoring data, especially at a daily scale, which hinders the understanding of the response relationship between extreme climate, hydrology, and water quality. This study proposes an integrated machine learning framework with physical constraints from various environmental domains such as meteorology and water quantity that can effectively impute a high percentage of missing data and downscale time series data of water quality, producing satisfactory results. Over 78% of the physical water quality variables exhibit NSE (Nash-Sutcliffe efficiency coefficient) values greater than 0.45, and more than 66% of the chemical water quality variables achieve NSE values greater than 0.35. The results of this work demonstrate the effectiveness of the proposed framework as a data augmentation and temporal interpolation tool to enhance the adequacy of water quality monitoring and explore the mechanisms underlying the impact of extreme climate on water quality.
Towards a better understanding of pyroconvective clouds using Meso-NH/ForeFire coupled model
Authors: Couto Flavio T. , Campos Cátia , Filippi Jean-Baptiste , Baggio Roberta , Purificação Carolina , Santos Filippe L. M. , Salgado Rui
Published: March 2024

In 2017, Portugal was affected by several mega-fire episodes, which led the convective clouds formation, i.e., pyroCumulus (pyroCu) or pyroCumulonimbus (pyroCb). The pyroCb plays a crucial role in the fire front evolution through feedback processes between the atmosphere and the fire, including increased burn and spread rates by surface wind speed and direction variations. In order to investigate the pyro-convective activity during mega-fire events, numerical simulations were performed with the Meso-NH atmospheric model coupled to the ForeFire fire propagation model. The present study considers the mega-fires occurred in Pedrógão Grande and Góis on June 17, 2017, and in Quiaios on October 15, 2017. The experiments were configured into three nested domains with horizontal resolution of 2000 m (600 km × 600 km), 400 m (120 km × 120 km) and 80 m (24 km × 24 km) for the innermost model. The vertical resolution is the same for all the nested domains, with 50 levels and a first level above the ground at 30 m height. Initial and lateral boundary conditions for the outer domain were provided by ECMWF analysis, with updates every 6 h. Heat and water vapour were emitted into the atmosphere using the ForeFire model. In this case, the fire front evolution is directly imposed from a pre-defined time of arrival map (one-way coupling) and obtained from official reports. The results from the simulation of 80 m horizontal resolution showed that in the Pedrógão Grande mega-fire, the violent fire-driven convection manifested as a pyroCb cloud. The convective column penetrated the upper troposphere, and an intense outflow originated from the pyroCb cloud. In Quiaios mega-fire, the simulation also well represented the pyro-convection phenomenon, characterised by a northward-oriented smoke plume and the development of a pyroCu cloud. This study has provided important insights into the numerical modelling of pyroconvective clouds using Meso-NH/ForeFire simulations. This study was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Ref. PCIF/MPG/0175/2019).
Influence of Titan's Variable Electromagnetic Environment on the Global Distribution of Energetic Neutral Atoms
Authors: Simon Sven , Tippens Tyler , Liuzzo Lucas
Published: March 2024

We combine the electromagnetic fields from a hybrid plasma model with a particle tracing tool to study the spatial distribution of energetic neutral atoms (ENAs) emitted from Titan's atmosphere when the moon is exposed to different magnetospheric upstream regimes. These ENAs are generated when energetic magnetospheric ions undergo charge exchange within Titan's atmosphere. The spatial distribution of the emitted ENA flux is largely determined by the parent ions' trajectories through the draped fields in Titan's interaction region. Since images from the ENA detector aboard Cassini captured only a fraction of the ENA population, we provide context for such observations by calculating maps of the ENA flux through a spherical detector concentric with Titan. We determine the global distribution of ENA emissions and constrain deviations between the locations of ENA production and detection. We find that the ENA flux is highest in a band that encircles Titan perpendicular to the ambient magnetospheric field, which was strictly perpendicular to the moon's orbital plane during only one Cassini flyby. The field line draping strongly attenuates the emitted ENA flux, but does not alter the overall morphology of the detectable flux pattern. The majority of detectable ENAs leave Titan's atmosphere far from where they are produced, that is, even a spacecraft located directly above the moon's atmosphere would detect ENAs generated beyond its immediate environment. Some energetic parent ions produce ENAs only after they are mirrored by the field perturbations in Titan's wake and return to the moon, demonstrating the complex histories of detectable ENAs.
Investigation of VLF/LF electric field variations related to magnitude Mw≥5.5 earthquakes in the Mediterranean region for the year 2023
Authors: Eichelberger Hans , Boudjada Mohammed Y. , Schwingenschuh Konrad , Besser Bruno P. , Wolbang Daniel , Solovieva Maria , Biagi Pier F. , Galopeau Patrick H. M. , Jaffer Ghulam , Schirninger Christoph , Nina Aleksandra , Jovanovic Gordana , Nico Giovanni , Stachel Manfred , Aydogar Özer , Muck Cosima , Wilfinger Josef , Jernej Irmgard , Magnes Werner
Published: March 2024

Strong natural hazards together with their societal impact are usually accompanied by multiple physical phenomena which can be an important information source about the underlying processes.  In this study we statistically analyze the lithosphere–atmosphere–ionosphere couplings of magnitude Mw5.5+ earthquakes (EQs) in the year 2023 with the aid of sub-ionospheric VLF/LF radio links. The electric field amplitude and phase measurements with a temporal resolution of one second are from the seismo-electromagnetic receiver facility in Graz (GRZ), Austria (Galopeau et al., 2023), which is part of the INFREP network. The spatial extend of the study area has the range [-10°E ≤ longitude ≤ 40°E] and [20°N ≤ latitude ≤ 50°N], in total are 17 EQs according to the United States Geological Survey (USGS) data base, among them the Turkey–Syria EQs (main shocks Mw7.8 and Mw7.5) and the Morocco Mw6.8 EQ. We apply the night-time amplitude method (Hayakawa et al., 2010) for all available paths, of particular importance are the transmitter links TBB (26.70 kHz, Bafa, Turkey), ITS (45.90 kHz, Niscemi, Sicily, Italy), and ICV (20.27 kHz, Tavolara, Italy). Relevant crossings are determined by the size of the Dobrovolsky-Bowman relationship (Dobrovolsky et al., 1979; Bowman et al., 1998).A major finding is the statistically significant electric field variation of the TBB-GRZ link related to the Turkey–Syria EQ sequence. A physical interpretation is based on atmospheric gravity waves (AGWs) which could alter the E-layer in the lower ionosphere during nighttime and modulate the height of the waveguide cavity.References:Galopeau et al., A VLF/LF facility network for preseismic electromagnetic investigations, Geosci. Instrum. Method. Data Syst., 12, 231–237, 2023, https://doi.org/10.5194/gi-12-231-2023Dobrovolsky et al., Estimation of the size of earthquake preparation zones, PAGEOPH 117, 1025–1044, 1979, https://doi.org/10.1007/BF00876083Bowman et al., An observational test of the critical earthquake concept, JGR Solid Earth, 103, B10, 24359-24372, 1998, https://doi.org/10.1029/98JB00792Hayakawa et al., A statistical study on the correlation between lower ionospheric perturbations as seen by subionospheric VLF/LF propagation and earthquakes, JGR Space Physics, 115(A9), 09305, 2010, https://doi.org/10.1029/2009JA015143
Role of degree and depth extent of slab-mantle hydration in controlling the intraslab fluid flow upon dehydration
Authors: Cerpa Nestor , Wada Ikuko
Published: March 2024

Fluid release from dehydration reactions and subsequent fluid migration in the subducting slab control the distribution of fluids in subduction zones, impacting many subduction processes, such as intraslab earthquakes, megathrust earthquakes, episodic slip and tremor, mantle wedge metasomatism, and arc-magma genesis.  Previous numerical models of two-phase flow indicate that compaction-pressure gradients induced by the dehydration reactions could drive updip intraslab fluid flow near the slab surface (Wilson et al., 2014). However, how the initial hydration in the incoming oceanic mantle prior to subduction impacts the updip fluid flow has not been investigated. Here, we use a 2-D two-phase flow model to investigate this effect under various initial slab-mantle hydration states and slab thermal conditions, the latter of which impact the depth extent of the stability of hydrous minerals. We especially focus on quantifying the lateral shift between the site of dehydration reactions and the location at which the fluids reach the slab surface due to their updip migration within the slab. The modeling results show that the most favourable path for updip flow is the antigorite dehydration front, the spatial extent of which depends on the slab-temperature and the thickness of the hydrated slab mantle. Our models predict that slab-derived fluids can travel over tens of km updip within the slab before reaching the slab surface. Such updip migration is more likely in warm(ish)-slabs, in which the formation of the antigorite dehydration front in the slab mantle does not require deep hydration of the incoming oceanic mantle prior to subduction.
Analysis of drought characteristics and causes in Yunnan Province in the last 60 years (1961-2020)
Authors: Lan Tianqing , Yan Xiaodong
Published: March 2024

Droughts are becoming more frequent and severe in Southwest China, with Yunnan being the most affected region. Most of the current studies on droughts in Yunnan are limited to individual cases and lack a common determination of the causes of historical drought events. In this study, we analyzed drought characteristics and causes over the last 60 years (1961-2020) in Yunnan Province in two seasons: dry and rainy. There was a clear trend of aridity in Yunnan Province in terms of both temporal and spatial changes, and there was a long-term drought period in approximately 2010; in particular, the frequency of drought in the dry season significantly increased. Due to its unique geographical location, precipitation in Yunnan Province is influenced by various factors, and the main influencing factors differed in different periods. SST variation is the most important factor affecting Yunnan drought, precipitation in Yunnan Province is affected by the warm pool of the Indian Ocean throughout the year, and thermal anomalies in different locations of the Pacific Ocean have different effects on Yunnan Province and often overlap with the effects of SST anomalies in the Indian Ocean.
Breathing cities: improving water quality in urban channels by controlling tidal flows, an idea for Ho Chi Minh City
Authors: Toffolon Marco , Casadio Francesco , Chau Nguyen Xuan Quang , Ngo Ngoc Hoang Giang , Aimini Matteo
Published: March 2024

Coastal cities are constantly facing new challenges in their relationship with the accelerated sea level rise associated with global warming, and with the quality of the water that flows in their urban canals. Indeed, some of the largest conurbations are innervated by a network of channels, which serve many purposes and provide preferential pathways for water exchange, but also make them prone to flooding. Flows periodically change their direction due to the tidal cycle, letting the fluxes of water, heat, and contaminants, enter and leave the city, like the breath of a living body. However, the presence of these channels is also a major threat of flood risk propagation, and in some cases motivated the construction of tidal gates to protect the city from high water levels. Ho Chi Minh City (HCMC) is an example where this strategy is progressively being applied.In this work, we discuss how the existence of tidal gates for flood protection may be exploited to control the tidal flows in the urban canals with the aim of improving water quality. Interestingly, the channel network in HCMC is characterized by several closed loops, where the periodic “breathing” is not efficient to renew the water in the central branches of the network because the water tends to enter and leave the system synchronously at the two ends of the loop, dictated by the water levels at the two connecting sections in the estuary, where tide propagation is typically fast so that the levels are similar. Therefore, we propose to exploit the gates not only to protect the city from high tides, but also to induce a prevalent unidirectional flow in the closed loops by alternately opening and closing the gates according to the difference in water levels between the channels and the estuary. Careful management can promote the removal of pollutants with beneficial effects on water quality, and potentially contribute to the transport of sediments, thus reducing the need for dredging. We demonstrate how the system can work by means of hydrodynamic modelling, first considering an idealized closed loop and then extending the simulation to a realistic model of the HCMC channel network.