bluuebunny/crossref_metadata_2025 huggingface dataset:
Conservation paleobiology of the Montalbano Jonico succession (southern Italy): A Standard Auxiliary Boundary Stratotype (SABS) for the Middle Pleistocene of the Quaternary System
Authors: Scarponi Daniele , Cervellieri Matilde , Crippa Gaia , La Perna Rafael , Girone Angela , Maiorano Patrizia , Marino Maria
Published: March 2024

Conservation paleobiology (CP) is a relatively new, synthetic field of research that combines paleontology theories and analytical methods to address current issues related to conserving and managing biodiversity and understanding long-term present-day ecosystem dynamics.  This research focuses on the latter aspect of CP and investigates how macrobenthic communities have responded to climate change in the past in the Pleistocene marine setting of Montalbano Jonico (Bradanic Trough, southern Italy). Specifically, being a SABS, the Montalbano Jonico Ideale Section presented a significant opportunity to explore past macrobenthic environmental dynamics of shelf marine environments in a data-rich and well-known environmental and stratigraphic framework.We quantified responses of shelf macrobenthic assemblages to long-term climate changes using 29 samples (∼ 3,975 fossil remains) retrieved along the SABS, deposited between MIS 20 and MIS 18. Previously established paleo-bathymetric reconstructions indicate shelf environments during cold periods (glacials and stadials), which alternated with deeper settings (outer shelf/slope) during warmer phases (interstadials), reflecting the orbitally-driven climate shifts registered by stable oxygen isotopes.Shelf macrobenthic assemblages naturally alternated between two states over observed long-term climate oscillations. Cold climate faunas were characterized by lower species richness and negligible abundance of species exclusive to the Mediterranean-to-Lusitanian regions compared to warm interstadial assemblages. The high similarity between cold climate assemblages and the distinct composition and abundances of interstadial faunas suggests that, over millennial timescales, shelf benthic assemblages have been primarily structured by environmental forcing, proving either remarkable resilience or persistence in the face of significant environmental and climatic perturbations.In addition, being the interglacial MIS 19 a climate analog for future climate change, paleobiologic features (e.g., standardized richness or amount of most abundant taxa) might serve as an ecological baseline for the near future.While biomonitoring, ecological data, and strategies are the main avenues for conservation and ecosystem management, conservation paleobiological approaches can provide unique insights from the recent past into biodiversity dynamics and ecosystem structure of present-day ecosystems that would have otherwise gone unnoticed.
Application Research of Multi-source New Detection Data in Snow Depth Prediction for Beijing Winter Olympics
Authors: Du Jia , Yu Bo , Dai Yi , Li Sang , Xu Luyang , Fu Jiaolan , Li Lin , Jing Hao
Published: March 2024

According to the demand of the Winter Olympic Organizing Committee for snow depth prediction, the application of multi-source new data in snow depth was studied based on densely artificial snow-depth measurement, microscopic snowflake shape observation and PARSIVEL data. The specific conclusions are as follows: (1) Most of the Snow-Liquid-Ratio(SLR) in Beijing competition zone was between 0.69 and 1.43 (unit: cm/mm, the same below), while that in Yanqing zone was between 0.53 and 1.17. But 7.5% of the SLRs in Yanqing zone exceeded 3.5, which all occurred in the same period of the key service time of 2022 Beijing Winter Olympics, making it more difficult to predict new snow depth. (2) The higher the SLR, the lower the daily minimum surface temperature and lowest air temperature.  Plate or column ice crystals, rimed snowflakes, and dendritic snowflakes were observed, whose corresponding SLRs increased. The average falling speed of particles falling below 2m/s can be used as an indicator of phase transfer. (3) The vertical distributions of temperature and humidity with SLR 2 were summarized. It was found that when the cloud area coincided with the dendritic growth zone with height close to Yanqing zone, the SLR would be more than 2, higher than that of Beijing zone. (4) A weather concept model generating large SLR was extracted. Snow in Beijing is often accompanied by easterly winds in boundary layer, which is easy to form a wet and ascending layer in the lower troposphere due to the blocking of western mountain. In the late winter season, helped by the temperature’s profile, it tends to produce unrimed dendritic snowflakes, leading to a great SLR.
Massive Micron Meteoroids in the near-Sun Space as Observed by Parker Solar Probe
Authors: Chen Tianhang , He Jiansen , Wu Ziqi , Zhuo Rui
Published: March 2024

The interplanetary dust, together with solar wind plasma, forms the space environment of the inner heliosphere. There are two main particle populations of dust, α-meteoroids in bound orbits with micron size and β-meteoroids in hyperbolic orbits with sub-micron and nano size. Collisions between dust particles and dynamical evolution of their orbits greatly shape the grain size and heliocentric distance distributions of dust cloud, yet the specific mechanism still remains unknown. After Parker Solar Probe (PSP) successfully performed more than 10 encounter missions, plenty of dust impact events have been recognized, providing a glimpse of the complex. In this work, we analyze the geometry feature of streaks captured by the Wide-field Imager for Parker Solar Probe (WISPR) and try to locate the impact origins. In addition, we translate the results of streak storms in WISPR images to dust impact rates so as to compare with those recorded by the PSP FIELDS Experiment (FIELDS). We find there is evidence for the α-meteoroids impact. The debris products are directly observed by WISPR. We also find that the dust impact rates determined by the two methods are in good agreement. A pure α-meteoroid model is used to fit the observed impact rates within about 0.3 AU (~67 solar radii) and the fit is pretty well, especially for the rates near perihelion of PSP. Based on these results, we suggest that α-meteoroids can take a significant proportion of zodiacal dust near the Sun and this may lead to a different size distribution of dust cloud and a different mechanism of meteoritic evolution from what they are observed as at 1 AU.
Carbon sequestration uncertainties: bridging the model-data gap for enhanced weathering
Authors: Calabrese Salvatore , Bertagni Matteo , Cipolla Giuseppe , Noto Leonardo V. , Porporato Amilcare
Published: March 2024

Enhanced weathering (EW) is a promising strategy for sequestering CO2 by amending cropland and forest soils with crushed silicate materials. However, current model-based estimates suffer from numerous uncertainties resulting from the incomplete representation of the weathering process in soils and a lack of model-data comparisons. Here, we address this gap by improving and validating an ecohydrological and biogeochemical soil model that captures the EW dynamics in the upper soil layers. We present a systematic model-experiment comparison leveraging four experiments with different degrees of complexity, ranging from simple closed incubation systems to fully open mesocosm experiments. The comparison reveals an encouraging observation-model agreement for the primary variables of interest, such as rock alkalinity release and CO2 sequestration. The comparison also demonstrates that the weathering rates consistently fall below those of flask dissolution experiments, underlining the need to update mineral weathering rate formulations in soils. As measurements from field trials become available, further model-data comparisons will help refine the model in support of large-scale EW deployments.
The potential of the electromagnetic induction method to monitor temperature changes in the near-surface
Authors: Carrizo Maria , Werthmüller Dieter , Slob Evert
Published: March 2024

Geothermal heat production might pose the risk of degrading groundwater quality due to temperature changes, which may lead to ecological and economic impacts. Monitoring and quantifying spatial and temporal changes in the groundwater temperature are challenging but necessary for reliable environmental evaluations. Electromagnetic Induction (EMI) measurements have been extensively used in environmental monitoring, since Electrical Conductivity (EC) is very sensitive to changes in the groundwater properties, such as the presence of contaminants or changes in fluid temperature. Subsurface EC estimates can be obtained through the inversion of EMI measurements in a non-invasive and cost-effective way. However, these estimates are inherently ambiguous because of the ill-posed nature of the inverse problem.In this project, we investigate how to provide an accurate EC estimation of the subsurface using EMI measurements, with the aim of understanding the near-surface groundwater temperature evolution. We test two different inversion methodologies to estimate horizontally layered EC models. The first, using a search in a pre-computed and stored database containing a discrete version of the full solution space finds the model that fits the data best in the least squares sense. The second, using a gradient descent optimization. We tested the method using different numerical scenarios. We show that for a horizontally 3-layered model using a gradient descent optimization might be insufficient to obtain an accurate estimate. Moreover, we demonstrate that the in-phase part of the measurement contains information about the electrical conductivity that might be useful to include in the estimation. Finally, our results give insight into the challenges and limitations of the estimation of EC horizontally layered models using frequency domain EMI data in the context of geothermal operations in the Netherlands.
Slab tear of subducted Indian lithosphere beneath the Eastern Himalayan Syntaxis region
Authors: Zhang Bo , Li Ziqing , Zhang Jinjiang
Published: March 2024

In the southeastern Tibetan Plateau, a series of region-scale dextral strike-slip shear zones play important roles in accommodating the continental collision and continental subduction during India-Asia convergence. This study provides structural, kinematic and geochronological data along the Dulongjiang shear zone, a newly recognized region-scale dextral strike-slip zone around the Eastern Himalayan Syntaxis (EHS) region. The structures and kinematic indicators record dextral lateral shearing within the zone in the Dulongjiang and Nabang regons of western Yunnan, China. The temperature range for dextral ductile shearing is estimated to be between 550 and 450 ℃, based on ductile feldspar deformation and CPO patterns of quartz in the granitic mylonites. Zircon U-Pb dating of syn-shearing leucogranites indicateds a period of dextral strike-slip movement between 30 and 18 Ma. The 40Ar/39Ar dating results from the mica fragments in mylonitic granites suggest rapid cooling since approximately 17-14 Ma. Combining these findings with previously published data on other dextral strike-slip faults/shear zones around the EHS and southeastern Asia, it is concluded that the Dulongjiang shear zone is connected with the Parlung shear zone in Tibet, the Nabang shear zone in western Yunnan and Sagaing Fault in the southeastern Asia. The Parlung-Dulongjiang-Nabang shear zone, along with other dextral strike-slip zones, forms a regional-scale Cenozoic dextral shear system around the EHS, extending into southeastern Asia. In addition, our study, in conjuncation with high wavespeed tomographic anomalies beneath the India-Asia collision zone, emphasizes the distinct evolution at lithospheric scales in  the southeastern and eastern parts of the collision zone. The intracontinental continuous strike-slip shearing indicates a tectonic transformation from extension in Tibet to block rotation around the EHS. From 30 to 18 Ma, the slab tear is associated, spatially and temporally, with a clockwise rotation and dextral strike-slip shearing around the EHS. These characteristics suggest a warmer geodynamic setting during the rotation and the influence of  a hot mantle flow associated with the tear in ongoing India lithosphere subduction. The Oligocene-Miocene dextral strike-slip shearing around the EHS and their linkage southwards with the dextral Sagaing Fault may correspond to the rotation required for the slab to bend, stretch and eventually tear beneath the EHS region.
Spatial variability in global atmospheric CO during Covid-19 lockdown: Implication of air quality policies
Authors: Pathak Mansi , Patel Vikas Kumar , Kuttippurath Jayanarayanan
Published: March 2024

The COVID-19 lockdown (LD) presented a unique opportunity for examining shifts in regional and global air quality. The alterations in atmospheric carbon monoxide (CO) during LD necessitate thorough analysis, given that CO is a significant air pollutant impacting human health, ecosystems, and climate. Our examination reveals a 5-10% decrease in the CO column during LD (April-May 2020) compared to the pre-lockdown (PreLD, March 2020) periods in regions with elevated anthropogenic activity, such as East China (EC), Indo-Gangetic Plain (IGP), North America, parts of Europe, and Russia. However, this reduction was absent in regions prone to frequent and intense wildfires and agricultural waste burning (AWB). There is substantial heterogeneity in CO column distributions, ranging from regional to city scales, during the LD period. To identify the sources of CO emissions during LD, we analyzed the ratios of nitrogen dioxide (NO2), sulfur dioxide (SO2) to CO for major cities worldwide. This analysis facilitated the identification of contributions from various sources, including vehicles, industries, and biomass burning during LD. Comparisons between CO levels during LD and PreLD periods indicate a significant reduction in global tropospheric CO but no noteworthy change in the stratosphere. Notably, CO emissions decreased during LD in hotspot regions but rebounded after the lifting of LD restrictions. This study underscores the importance of policy decisions and their implementation on both global and regional scales to enhance air quality, safeguarding public health and the environment.
Linking phosphorus research to impact: advances and challenges in mapping soil phosphorus pools
Authors: Helfenstein Julian , Ringeval Bruno , Tamburini Federica , Goll Daniel S. , He Xianjin , Mulder Vera , Wang Yingping , Alblas Edwin , Frossard Emmanuel
Published: March 2024

Improved management of phosphorus (P) is essential for achieving a range of Sustainable Development Goals (SDGs), including maintaining food security, preserving water quality, and mitigating climate change. This requires an integration of comprehensive mechanistic understanding with accurate spatial data. In this interdisciplinary review, we combine insights from empirical P research, digital soil mapping, biogeochemical modeling, and environmental law to critically examine the current state, pinpoint challenges and propose novel pathways for desperately needed P maps. We first elucidate the relevance of spatial data on P for different SDGs. Subsequently, we summarize the current efforts in mapping P pools at regional to global scales, and discuss the challenges of mapping “available P” due to substantial local scale variability and poor correlation with predictors relative to other soil properties. The practical applicability of these recently published maps is tested by evaluating them with independent measurement data. Finally, we outline ways forward to enhance the accuracy and reliability of P maps, as a basis for science-informed management of P resources.
Modelling the intermittence of watercourses in the small French Mediterranean catchments of the Maures massif (Réal Collobrier ) with the SMASH platform (Spatially distributed Modelling and ASsimilation for Hydrology) 
Authors: Folton Nathalie , De Fournas Thomas , Colléoni François , Tolsa Mathieu
Published: March 2024

Intermittent rivers and ephemeral streams represent half of the global river network and span all climates. The intermittent rivers and ephemeral streams is a short-hand term for all flowing water that ceases to flow or that dries up completely at some point in time and/or space They are more frequent in arid and semi-arid areas but are also present in temperate, tropical humid, boreal, and alpine areas, where they are mainly located in headwaters. Their abundance is increasing due to climate change and water withdrawals for human activities.The objective of this study is to represent the spatio-temporal dynamics of flow intermittence at the reach level in river of the seven sub-catchments of the Maures massif (between 1.5 km² and 70 km²).First, two hydrological continuous models of varying complexities are performed: GR6J (lumped and conceptual), and SMASH (spatially distributed and conceptual) in terms of temporal calibration/validation, by dissociating dry and wet years, to asses the models’ability to simulate observed drying event over time. The metrics are based on daily flow records observed in the 7 catchments since 1968 to 2023.In the second part, a regionalization method is tested on the spatially distributed model (SMASH). The HDA-PR approach (Hybrid Data Assimilation and Parameter Regionalization) incorporating learnable regionalization mappings, based on multivariate regressions is used. This approach consist to search for a transfer function that quantitatively relates physical descriptors to conceptual model parameters from multi-gauge discharge in order to produce a regional model.Flow condition observed from multiple data sources (daily flow time series from gauging stations, phototrap installed along the river network taking daily pictures from 2021-04-01 to 2023-31-12, daily conductivity measurements series from 2021-01-01) are used to validate the ability of the regional model to simulate flow intermittence (prediction of dry events) at river section level.The distributed modelling approach, with a high-resolution conceptual hydrological modeling at 0.250 km² and coupled with Hybrid Data Assimilation and Parameter Regionalization descriptors shows results highlight the effectiveness of HDA-PR surpassing the performance of a uniform regionalization method with lumped model parameters. However, the results on smallest catchments area are lowest.The study shows the interest of using daily photos which are a good indication of the hydrogical state of the streams to obtain intermittence data and increasing the spatial coverage of observations in order to validate regional model.
A Novel Operational Risk and Resilience Management Process for Emergency Planning and Civil Contingency
Authors: Meslem Abdelghani , Huang Chen
Published: March 2024

Intensive and extensive risks are growing at an unprecedented rate as reported by the Global Assessment Report on Disaster Risk Reduction. While disasters are claiming fewer lives annually, they are also costing more and increasing poverty and economic losses. Understanding and managing risk and resilience helps governments, institutions, businesses, and communities make better decisions in a world of uncertainty. Building on the existing risk and resilience management processes (e.g., national risk assessments, international risk management standards, literature on risk and resilience assessment), this study proposes a novel operational risk and resilience management process for emergency planning and civil contingency. The proposed framework is an iterative process consisting of interrelated phases:Scope, context and criteria
Risk and Resilience Identification, analysis and evaluation
Risk mitigation and resilience strengthening
Monitoring and review
Communication and consultation
Recording and reporting
Initial and detailed assessment
The proposed operational framework will provide guidance for disaster management authorities to better understand and manage complex impact and systemic risk from a multi-hazard and disaster risk perspective.
Hybrid statistical-dynamical seasonal prediction of summer extreme temperatures over Europe
Authors: Famooss Paolini Luca , Ruggieri Paolo , Pascale Salvatore , Brattich Erika , Di Sabatino Silvana
Published: March 2024

Several studies show that the occurrence of summer extreme temperatures over Europe is increased since the middle of the twentieth century and is expected to further increase in the future due to global warming (Seneviratne et al., 2021). Thus, predicting heat extremes several months ahead is crucial given their impacts on socio-economic and environmental systems.In this context, state-of-the-art dynamical seasonal prediction systems (SPSs) show low skills in predicting European heat extremes on seasonal timescale, especially in central and northern Europe (Prodhomme et al., 2022). However, recent studies have shown that our skills in predicting extratropical climate can be largely improved by subsampling the dynamical SPS ensemble with statistical post-processing techniques (Dobrynin et al., 2022).This study assesses if the seasonal prediction skill of summer extreme temperatures in Europe in the state-of-the-art dynamical SPSs can be improved through subsampling. Specifically, we use a multi-model ensemble (MME) of SPSs contributing to the Copernicus Climate Change Service (C3S), analysing di hindcast period 1993—2016. The MME is subsampled by retaining a subset of members that predict the phase of the North Atlantic Oscillation (NAO) and the Eastern Atlantic (EA), typically linked to summer extreme temperatures in Europe. The subsampling relies on spring predictors of the weather regimes and thus allows us to retain only those ensemble members with a reasonable representation of summer heat extreme teleconnections.Results show that by retaining only those ensemble members that accurately represent the NAO phase, it not only enhances the seasonal prediction skills for the summer European climate but also leads to improved predictions of summer extreme temperatures, especially in central and northern Europe. Differently, selecting only those ensemble members that accurately represent the EA phase does not improve either the predictions of summer European climate or the predictions of summer extreme temperatures. This can be explained by the fact that the C3S SPSs exhibits deficiencies in accurately representing the summer low-frequency atmospheric variability.BibliographyDobrynin, M., and Coauthors, 2018: Improved Teleconnection-Based Dynamical Seasonal Predictions of Boreal Winter. Geophysical Research Letters, 45 (8), 3605—3614, https://doi.org/10.1002/2018GL07720Prodhomme, C., S. Materia, C. Ardilouze, R. H. White, L. Batté, V. Guemas, G. Fragkoulidis, and J. Garcìa-Serrano, 2022: Seasonal prediction of European summer heatwaves. Climate Dynamics, 58 (7), 2149—2166, https://doi.org/10.1007/s00382-021-05828-3Seneviratne, S., and Coauthors, 2021: Weather and Climate Extreme Events in a Changing Climate, chap. 11, 1513—1766. Cambridge University Press, https://doi.org/10.1017/9781009157896.013
36Cl/10Be as a dating tool for old ice
Authors: Kappelt Niklas , Wolff Eric , Christl Marcus , Vockenhuber Christof , Muscheler Raimund
Published: March 2024

The 36Cl/10Be ratio has the potential to be a dating tool for old ice, as it decays with a combined half-life of  years and is thought to be independent of production changes, which affect the individual radionuclide concentrations in ice cores. However, when EDC samples with various ages between the Holocene and 887 kyr BP were analysed, the 36Cl/10Be ratio was found to vary significantly between samples instead of decaying smoothly over time. Due to the different physical and chemical properties of 36Cl and 10Be, different sensitivities to changes in climatic parameters, such as tropopause pressure and precipitation, are potentially the cause of the observed variability. Additionally, chlorine can be lost at low accumulation sites, such as EDC, as it can turn into hydrogen chloride and gas out from the firn. We present new measurements of the 36Cl/10Be ratio from the Skytrain ice core, which should be unaffected by chlorine loss, due to the higher accumulation rate at its drilling site. The measurement series extends below the dated sections of the ice core to test the decay dating and help extend the Skytrain age scale. To analyse differences in transport and deposition between radionuclides, the 36Cl/10Be ratio will also be determined with annual resolution in samples from 1982 – 2013 and compared to several climate parameters of the NOAA/CIRES/DOE 20th century reanalysis (V3) dataset. However, the data of this project are not yet available.
Terrestrial Water Storage Reconstruction: A Causal Inference Approach
Authors: Yadav Vivek Kumar , Vishwakarma Bramha Dutt
Published: March 2024

The water availability in a region is driven by the water cycle, which is changing quickly in response to climate change and direct human interventions. The water cycle is defined and controlled by the variation in water fluxes such as Precipitation (P), Evapotranspiration (Et), Runoff (R), and Storage change (ΔS). Out of these water fluxes, ΔS is a key variable for ecosystem habitability and surviving droughts. It is an important parameter in drafting water management policy, but due to lack of long and reliable data the impact of climate change on ΔS is yet to be understood. The only Global observations of Terrestrial water storage (TWS) are available from GRACE satellite mission since 2002 at monthly scale.Although GRACE data has transformed hydrological science significantly, its short time series limits usage of GRACE for climate change analysis of hydrological fluxes (closing the multidecadal water budget and sea level budget, understanding the spatiotemporal evolution of water availability, and so on). To tackle this, several studies have attempted reconstructing ΔS prior to GRACE period. These studies employ either hydrological modelling of ΔS, statistical regression,  or machine learning techniques. While machine learning methods have been assessed superior, they suffer from issues such as a lack of explainability, failure to identify causal drivers of TWS change, and use of short time series for feature extraction and training leading to poor or no representation of decadal natural variability.Furthermore, in all the studies till now, representation of local human activities, such as ground water extraction or reservoir operation,  was either absent or assumed to be a linear trend. Here we revisit a reconstruction method by Humphrey et al., 2017 and show that these approximations have a considerable impact on the quality of reconstruction. Then we propose a multivariate regression model that relates selected hydrometeorological variables with TWS. These variables are identified from causal analysis of JULES model outputs. We show that temperature has a very weak relation with TWS compared to precipitation. The causal inference based model is able to capture realistic variability in reconstructed TWS. Our TWS reconstruction for the Ganges basin outperforms the contemporary attempts and is able to identify the drivers for interannual changes in TWS . The results bring historical perspective to the current state of water resources in the basin and provide context for design of future water resources policy.
Modeling of spectral induced-polarization measurements on cm-sized metallic spheres in sand-water-mixtures
Authors: Kreith Dennis , Breede Katrin , Zhang Zeyu , Weller Andreas , Bücker Matthias
Published: March 2024

The detection of metallic particles in the subsurface has been an important field in applied geophysics for several decades, e.g. in the exploration of ore deposits or in monitoring measurements at bioremediation sites. Due to the comparably high conductivity and high polarizability of metallic particles, geophysical methods using the electrical conductivity and especially induced polarization are highly suitable methods for applications of this kind.To correctly interpret data measured in the field, a deep understanding of the underlying conduction and polarization mechanisms is necessary. Both, laboratory measurements with controlled experimental conditions and theoretical models describing the basic physical processes can help to achieve this kind of understanding. However, theoretical models usually are not suitable to be directly compared to laboratory measurements, because they usually consider idealized situations and exhibit a large number of free parameters that can not be controlled in measurements.To overcome this gap, we compare experimental data of a cm-sized metallic sphere embedded in water-saturated sand with a corresponding theoretical model. To explain the remaining differences between measured and modeled data, we discuss how different processes, e.g. the geometry of the measurement setup or dissolved metal ions in the fluid, might affect the measurement and adapt our model accordingly. By doing so, we are able to reproduce the experimental results with the predictions by our theoretical model.
The role of tree species and microbes for the development of net greenhouse gas fluxes from soils after afforestation of agricultural lands
Authors: Rheault Karelle , Riis Christiansen Jesper , Steenberg Larsen Klaus
Published: March 2024

Greenhouse gas (GHG) emissions, in the form of CO2, CH4 and N2O, from land use change and agriculture are responsible for up to 20% of anthropogenic emissions, mainly due to deforestation, livestock production and crop fertilization. Afforestation is proposed as an effective means to sequester atmospheric carbon in biomass and soils. However, there is a lack of knowledge about the resultant soil GHG fluxes from temperate afforested ecosystems, how they develop in the field and over many years. Furthermore, tree species choice (deciduous/conifers) may impact the soil biogeochemistry differently through the soil physicochemical properties and the soil microbiome with a currently uncertain outcome in relation to GHG fluxes and the climate mitigation potential.In this study, we investigate the development of soil GHG fluxes, soil physicochemistry, and the soil microbiome on arable land using a well-established forest chronosequence (Vestskoven, Denmark), which is a former cropland area afforested over the last 50 years with Norway spruce (Picea abies), oak (Quercus robur) and beech (Fagus sylvatica). The total of 19 selected sites in Vestskoven includes 6 to 7 stand ages per tree species. We measured CH4 and CO2 fluxes in situ, and sampled soil for physicochemical and microbial analyses.We present data on how net soil CH4 uptake and soil CO2 efflux develop with time since planting and how the net soil CH4 uptake correlates with the relative abundance of methanotrophic and methanogenic soil communities. We expect these relationships to be dependent of tree species due to differences in how soil physicochemical properties impact the microbial communities responsible for soil CH4 cycling.Preliminary results show that afforestation increases net soil CH4 uptake, since all tree species had higher net soil CH4 uptake rates compared to cropland, but the effect of plantation age was only visible in oak stands after 50 years. This indicates tree species-specific regulation of the net CH4 flux and its development over time. There was no clear trend for a development of the soil CO2 efflux after planting for either tree species. We will further present analyses of structural equation modelling elucidating the interactions between gas fluxes, soil physicochemical environment and microbial communities. 
Soil Organic Carbon Retrieval from DESIS Images by CNN
Authors: Zhao Xiangyu , Heiden Uta , Karlshöfer Paul , Xiong Zhitong , Zhu Xiao Xiang
Published: March 2024

Imaging spectroscopy is commonly used for many applications like soil, water, and vegetation. Digital soil mapping, especially by space-borne sensors, has become advantageous and promising due to its high efficiency. By using multispectral or hyperspectral images, topsoil properties could be estimated efficiently and accurately on a large area scale. Moreover, deep learning has been explored in the remote sensing community and achieved excellent performances in many remote sensing tasks. In this work, we explore deep learning methods to retrieve Soil Organic Carbon (SOC) value from DESIS hyperspectral images for the whole Bavaria state in Germany. For the hyperspectral data, we use all available DESIS images in Bavaria, which is 560 in total. Regarding the soil data, we combine SOC data from LFU (Bavarian State Environment Agency) and LUCAS 2018 (Land Use and Coverage Area frame Survey). Following a rigorous data selection process, we opted to include 1200 soil samples in our experiments. Starting from the raw hyperspectral images, we conduct a few preprocessing steps such as land cover masking, filtering by NDVI, building temporal composite, and then extracting patches surrounding each soil sample. These preprocessed patches are fed into deep learning models such as 1D CNN and 2D CNN, which are trained to predict the SOC value. To better interpret the model's performance, we also compute the SHAP(Shapley Additive Explanations) value for both frameworks. Specifically, we explore the SHAP value in spectral dimension for 1D CNN and analyze digital elevation features with 2D CNN in spatial dimension. During experiments, we split the whole dataset into train, validation, and test. To evaluate the performance, RMSE, R2, and RPID are computed. For the specific structure of the models, many different parameters are investigated in parameter tuning. For each trial, 5 cross-validation is applied. In the end, we visualize the prediction results by a soil map.  From the results, the best-performed model could get RMSE 0.62 and R2 0.40 on the test set. Moreover, we find that the first-order derivative of the spectrum is the most important feature for predicting SOC, while 1D CNN is capable of extracting useful information from it and achieving excellent regression results with RMSE 0.66 and R2 0.32. Additionally, spectrums between 530 nm - 570 nm and 730 nm - 780 nm are the most informative according to SHAP analysis.
Representing explicit microbial processes enhances methane modeling under oxygen fluctuation
Authors: Wang Gangsheng , Zhou Shuhao
Published: March 2024

The dynamics of soil carbon (C) emissions along with their biogeochemical and environmental control have garnered increasing attention. However, the role of methane (CH4) in soil organic carbon (SOC) modelling has been relatively underexplored compared to carbon dioxide (CO2), and the omission of microbial processes may prevent us from accurately modelling CH4 dynamics under environmental changes. Here, we incorporated an explicit microbial CH4 module into the Microbial-ENzyme Decomposition (MEND) model and evaluated it against a sub-version with the first-order kinetics (First-order) and the previous MEND (MEND_old) model. We conducted a rigorous calibration and validation of MEND with high-resolution CO2 and CH4 efflux observations across two soil types and five different oxygen (O2) fluctuation conditions. Beyond precisely capturing soil CO2 and CH4 effluxes, the model could also effectively simulate the relative contents of microbial biomass and enzymes. The multi-model comparison further revealed that the inclusion of new processes did not necessarily enhance model performance if microbes were not perceived as explicit state variables. Our results demonstrated that adopting microbial functional groups as drivers of soil CH4 cycle could provide a basis for testing hypotheses on microbially mediated CH4 processes and their responses to environmental changes. With the availability of diverse data and the development of genetic technologies, our modelling framework present here will empower ecologists and governments to perceive and intervene in global warming from underlying biogeochemical mechanisms rather than predictions.
A comparison of bivalve, gastropod and fish otolith stable isotope profiles from the Aalter Sands, early Eocene southern North Sea Basin
Authors: Vellekoop Johan , Vanhove Daan , Jelu Inge , Claeys Philippe , Ivany Linda C. , de Winter Niels J. , Speijer Robert P. , Steurbaut Etienne
Published: March 2024

Stable isotope sclerochemistry of mollusks and otoliths is key in reconstructing temperature and seasonality in past greenhouse climates. It is therefore crucial to understand the paleoecology and –environment of these organisms, and how these factors influence intra-and inter-taxon isotope variability and variation. To gain more insights in these factors, we measured seasonal changes in δ18O and δ13C compositions in multiple specimens of two carditid bivalve species, a turritelline gastropod species, and two species of otoliths from demersal fish, from two successive early Eocene (latest Ypresian, 49.2 Ma) coquinas in the inner neritic Aalter Sand Formation, located in the Belgian part of the southern North Sea Basin (paleolatitude ~41°N). Results demonstrate variability among taxa in average, amplitude and shape of intra-annual δ18O and δ13C values. This intertaxon variability is at least partly caused by growth cessation during winters in turritellines and otoliths, leading to an incomplete representation of the seasonal cycle in their growth increments, compared to carditid bivalves. Other contributing factors to isotopic variability include sedimentary transport, mobility, and the lifespan of the specimens. Specifically, ophidiid fish otolith isotope records appear to reflect environmental conditions over a wider range of habitats and environments, due to sedimentary transport and postmortem transport by free-swimming predatory fish. Our study therefore highlights the variability between different taxa and environments in the shallow marine realm, which has implications for seasonality reconstructions. Studying multiple taxa and specimens in a death assemblage provides a more complete spectrum of isotope variation and variability.
Spatial downscaling of CAMS surface pollutants using Machine Learning
Authors: Tsikerdekis Athanasios , Tsikerdekis Michail , Eskes Henk
Published: March 2024

In order to monitor regional pollution over Europe, the Copernicus Atmosphere Monitoring Service (CAMS) coordinated by the European Centre for Medium-Range Weather Forecasts (ECMWF) implemented an operational multi-model air quality forecast system over Europe. CAMS regional products provide a 5-day forecast of several chemical species (e.g. NO2, CO, PM2.5, PM10) from the surface up to 5 km with a spatial resolution of 10 km. In addition, CAMS global services provide similar products globally in a coarser resolution of 0.4° (40 km approximately).Motivated by the fact that air pollution is a global problem and responsible for millions of premature deaths each year, combined with the lack of a 10 km global air quality forecast system, we train a convolutional neural network (CNN) in order to downscale the spatial resolution of CAMS surface NO2 from 40 km to 10 km. Since most pollutants are affected by meteorological conditions and topographic characteristics, we use as input several meteorological variables (e.g. wind, temperature, humidity, boundary layer height) from ECWMF high-resolution forecasts (HRES) as well as surface elevation and emission information of several pollutants. All inputs are available at 10 km resolution globally.In order to validate if there is an added value in our downscaled results, we evaluate against observations collected by a network of surface stations. Our downscaling efforts in this study focus over the European domain, where the reference of a high-resolution chemistry is available from the CAMS regional services, but we aim to train a model that will be general enough for global application.
Creating an Inventory of Seismic Signals at Vulcano Island, Italy, using Unsupervised Learning Techniques
Authors: Langer Horst , Falsaperla Susanna , Ferrari Ferruccio , Spampinato Salvatore
Published: March 2024

The island of Vulcano gives its name to the so-called “Vulcanian eruptions”, an eruptive style with strong explosive characteristics and observed there for the first time. The last eruptive activity occurred between 1888 and 1890. Starting from mid-September 2021, an unrest, marked by relevant variations in geochemical and geophysical parameters, affected the island. Here, we analyze the seismic signals recorded from the onset of the unrest until December 2022. An increasing number of Very Long Period events was detected from September 2021 onwards, enhancing concerns linked to other measured anomalies, such as increasing CO2 emissions and fumarole temperatures. Numerous types of signals were generally recorded on the island, partly caused by various man-made sources, such as the close-by passage of ships, dropping anchors, etc. The large variety of the seismic signals made standard amplitude-based monitoring techniques, such as RSAM, questionable. We therefore focused on creating an inventory of the recorded signals exploiting unsupervised machine learning techniques, namely Self-Organizing Maps and Cluster Analysis. We were able to identify various classes of seismic events related to volcanic dynamics and to distinguish exogenous signals, such as anthropic noise. This allowed us to visualize the development of signal characteristics efficiently. This classification can help build an effective alert tool to automatically identify different types of seismic signals, useful for surveillance purposes. Furthermore, it is a preparative step for other studies, such as event location and source process modeling.
Geochemistry and molybdenum isotopes of the Lower Cambrian Yuertusi Formation in Tarim Basin（China）: Implications for ocean-redox conditions
Authors: Liu Pengwei , Wang Qi , Tian Jinqiang
Published: March 2024

During the Early Cambrian epoch, a sequence of global marine transgressions culminated in the extensive deposition of organic-rich shales across the planet. This phenomenon was especially pronounced over the Tarim Block, where these organic-rich sediments accumulated significantly during this period. However, the paleomarine environment of it is still poorly constrained due to deep burial and the rare samples. We conducted an integrated study of iron speciation, redox-sensitive trace elements(RSTE), and Molybdenum(Mo) isotopes for samples from the Luntan 1 borehole, located in the Lunnan depression. Yuertusi Formation mainly includes mudstone in the lower member (LM) and limestone in the upper member (UM). Iron speciation data (FeHR/FeT, Fepy/FeT) suggest euxinic in the LM and Anoxic-ferruginous conditions in the UM. Whereas the trace-element and Mo isotopic data show more pronounced variation in redox conditions. The LM shows higher trace element concentrations and lower and more variable Mo isotopic composition relative to the UM. Ratios of redox-sensitive trace element(RSTE) concentrations to total organic carbon(TOC) are significantly more variable and higher on average in the LM relative to the UM. The stable and high Mo isotopic composition (about 1.7‰) in the UM may exist Fe-Mn shuttle, varial and lower Mo isotopic composition (about 0.9‰) in the LM reflect to [H2S]aqueous fluctuate with H2S
The Impact of Tropical Atlantic SST Variability on the Tropical Atmosphere duringBoreal Summer
Authors: Ren Hongchang
Published: March 2024

The interannual variability of boreal summer sea surface temperature (SST) in the tropical Atlantic displays two dominant modes, the Atlantic zonal mode highlighting SST variations in the equatorial–southern tropical Atlantic (ESTA) region and the northern tropical Atlantic (NTA) mode focusing on SST ﬂuctuations in the NTA region except in the Gulf of Guinea. Observational evidence indicates that both the boreal summer ESTA and NTA warming are accompanied by a pair of anomalous low-level anticyclones over the western tropical Paciﬁc, and the NTA-related anticyclone is more obvious than the ESTA-related one. Both atmosphere-only and partially coupled experiments conducted with the Community Earth System Model version 1.2 support the observed NTA–Paciﬁc teleconnection. In contrast, the ESTA-induced atmospheric circulation response is negligible over the tropical Paciﬁc in the atmosphere-only experiments, and although the response becomes stronger in the partially coupled experiments, obvious differences still exist between the simulations and observation. The ESTA-induced atmospheric circulation response features an anomalous low-level cyclone over the western tropical Paciﬁc in the partially coupled experiments, opposite to its observed counterpart. It is found that the ESTA warming coincides with signiﬁcantly La Ni ñ a–like SST anomalies in the central–eastern equatorial Paciﬁc,the inﬂuence of which on the tropical atmospheric circulation is opposite to that of the ESTA warming, and therefore contributes to difference between the ESTA-related simulations and observation. Moreover, the cold climatological mean SST in the ESTA region is unfavorable to enhancing the ESTA–Paciﬁc teleconnection during boreal summer
Optimizing NetCDF performance for cloud computing : exploring a new chunking strategy
Authors: Gouillon Flavien , Pénard Cédric , Delaunay Xavier , Wery Florian
Published: March 2024

Owing to the increasing number of satellites and advancements in sensor resolutions, the volume of scientific data is experiencing rapid growth. NetCDF (Network Common Data Form) stands as the community standard for storing such data, necessitating the development of efficient solutions for file storage and manipulation in this format.Object storage, emerging with cloud infrastructures, offers potential solutions for data storage and parallel access challenges. However, NetCDF may not fully harness this technology without appropriate adjustments and fine-tuning. To optimize computing and storage resource utilization, evaluating NetCDF performance on cloud infrastructures is essential. Additionally, exploring how cloud-developed software solutions contribute to enhanced overall performance for scientific data is crucial.Offering multiple file versions with data split into chunks tailored for each use case incurs significant storage costs. Thus, we investigate methods to read portions of compressed chunks, creating virtual sub-chunks that can be read independently. A novel approach involves indexing data within NetCDF chunks compressed with deflate, enabling extraction of smaller data portions without reading the entire chunk.This feature is very valuable in use cases such as pixel drilling or extracting small amounts of data from large files with sizable chunks. It also saves reading time, particularly in scenarios of poor network connection, such as those encountered onboard research vessels.We conduct performance assessments of various libraries in various use cases to provide recommendations for the most suitable and efficient library for reading NetCDF data in different situations.Our tests involved accessing remote NetCDF datasets (two files from the SWOT mission) available on the network via a lighttpd server and an s3 server. Additionally, simulations of degraded Internet connections, featuring high latency, packet loss, and limited bandwidth, are also performed.We evaluate the performance of four Python libraries (netcdf4 lib, Xarray, h5py, and our chunk indexing library) for reading dataset portions through fsspec or fs_s3. A comparison of reading performance using netCDF, zarr, and nczarr data formats is also conducted on an s3 server.Preliminary findings indicate that the h5py library is the most efficient, while Xarray exhibits poor performance in reading NetCDF files. Furthermore, the NetCDF format demonstrates reasonably good performance on an s3 server, albeit lower than zarr or nczarr formats. However, the considerable efforts required to convert petabytes of archived NetCDF files and adapt numerous software libraries for a performance improvement within the same order of magnitude can raise questions about the practicality of such endeavors and benefits is thus extremely related to the use cases.