bluuebunny/crossref_metadata_2025 huggingface dataset:
Microbialite development in the Ediacaran Qigebrak Formation of the Tarim Basin, Northwest China: An examination of characteristics, distribution, and paleoceanographic reconstruction
Authors: Chen Xudong , Xu Qilu
Published: March 2024

Microbialite development in the Ediacaran Qigebrak Formation of the Tarim Basin, Northwest China: An examination of characteristics, distribution, and paleoceanographic reconstructionXudong Chen1,2, Qilu Xu1,2National Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China;
School of Geosciences, China University of Petroleum (East China), Qingdao, 266580, China
 The Upper Ediacaran Qigebrak Formation in the Tarim Basin of NW China preserves abundant and well-preserved microbialites with primary textures. These provide valuable insights into Precambrian sedimentology and paleoceanography. Our study focuses on elucidating the relationship between paleoceanic conditions and the development of these microbialites to understand their Precambrian origin.A comprehensive analysis of Ediacaran outcrops in the northwestern Tarim Basin identified 12 distinct microbialite types, ranging from mafic (F1) to flat-laminated stromatolite (F12). These comprise F2 (micrite dolomite), F3 (granular dolomite), F4 (bonded sand debris dolomite), and spongiomicrobialite variants (F5-F7). Additionally, we observed F8 (fenestral tectonic thrombolites), F9 (micrite thrombolites), and diverse stromatolite dolomites (F10-F12). Their occurrence is spatially distributed: F1 and F2 in the nearshore supratidal low-energy zone; F3, F4, and F7 in granular beach and microbial mound zones; F5 and F8 in the environmental transition zone; F6 and F11 in the lower intertidal high-energy zone; F10 predominantly in the upper subtidal high-energy zone; and F9 and F12 in both upper intertidal and lower subtidal low-energy zones.The shale-normalized REE patterns of these microbialites exhibit weak negative Ce anomalies, weak positive Eu anomalies, and positive La anomalies, suggestive of suboxic seawater deposition. Their chemical signatures, characterized by low V, Ni, and Co concentrations, high Sr content, and Sr/Cu ratios exceeding 50, collectively indicate warm and arid paleoclimatic conditions. Compared to F9, F6, F10, and F11 show lower V/(V+Ni) values, higher Mg/Ca ratios, and stronger LREE and MREE deficits, suggesting formation in shallower, more dynamic, saline, and oxygenated waters.Our findings offer fresh perspectives on the formation mechanisms of Precambrian microbial rocks and paleo-oceanic reconstruction.
Unraveling biogeochemical transformation of organic carbon and nitrogen compounds in groundwater along a hill slope transect
Authors: Duong Thanh Quynh , Hildebrandt Anke , Thullner Martin
Published: March 2024

The origin and the fate of organic carbon and nitrogen compounds in groundwater play an important role in the global biogeochemical cycling of carbon and nutrients and have implications for drinking water production. While the input of these compounds into the subsurface is strongly driven by land use, their fate in subsurface environments such as fractured aquifers is controlled by a complex interplay between hydrological and biogeochemical processes at different temporal and spatial scales and is poorly understood yet. Determining the fate of these organic compounds in fractured aquifers is additionally challenging due to spatial heterogeneities at various scales down to centimeter scales, leading to a multitude of flow paths of different lengths and residence times.  This causes an overlap of solute residence times for compounds moving from the surface through the subsurface to surface waters or groundwater observation wells, stretching from days to many years, thus affecting the dynamics of the biogeochemical processes and the quantitative assessment of compound fluxes. To address this issue, a travel time-based modeling approach is employed to simulate the fate of carbon and nitrogen compounds in groundwater along a hill slope transect of the Hainich Critical Zone Exploratory (CZE), located northwest of Thuringia (central Germany). This transect is set up under the Collaborative Research Center AQUADIVA. It is subject to an intensive surface and subsurface monitoring program providing groundwater quality and quantity data. Travel time distributions obtained from a numerical groundwater flow model of the transect and its vicinity are combined with a set of numerical 1D simulations describing the biogeochemical transformations of carbon and nitrogen. The simulated complex reaction network describes the transformation of carbon and nitrogen along individual groundwater flow paths, which considers varying microbial functional groups such as aerobes and anaerobes, as well as key microbial life processes under different redox conditions, including aerobic, nitrate-reducing, ammonia-oxidizing, and sulfate-reducing conditions.  The model-predicted concentrations of reactive species at various observation wells are compared to measured concentrations to validate the approach. The results show that processes on the surface strongly shape the dynamics of resulting recharge zones represented by different land use areas, which have an impact on observed concentrations at wells. Travel time distributions combined with simulations of the biogeochemical transformation along a flow path can provide a model-based interpretation of measured observations and the factors controlling them. This allows predicting fluxes of chemical species through the entire sub-catchment and their dependency on the dynamics of surface conditions.
Incorporating roots into Plant-FATE, a dynamic eco-evolution trait-based vegetation model
Authors: Maxwell Tania L. , Stefaniak Elisa , Hofhansl Florian , Joshi Jaideep
Published: March 2024

To predict the response of forest ecosystems and how projected climate change will shift plant species composition, we need models that can account for adaptations encompassing multiple temporal and organizational scales. Recently, eco-evolutionary optimality-based models have emerged, which need fewer parameters than their empirical counterparts, i.e. standard dynamic global vegetation models. The new Plant-FATE (Plant Functional Acclimation and Trait Evolution) model embodies functional diversity through the representation of species across trait space. It integrates ecosystem adaptations across three distinct levels: firstly, it captures the acclimation of plastic traits in individual plants by harnessing the principles of eco-evolutionary optimality. Secondly, to simulate shifts in species composition through demographic changes and species immigration, a trait-size-structured demographic vegetation model is implemented. Lastly, the model addresses the long-term genetic evolution of species by incorporating novel evolutionary theory tailored for trait-size-structured communities. Currently, Plant-FATE implements fine roots by scaling these to total leaf area, and coarse roots as a fraction of stem mass. Thus, rooting structures, plant root traits, and belowground trade-offs are not represented.

To expand the modelling framework, we are implementing fine roots in a similar way as the crown, as a function of the root length profile and the root projection area. We are maintaining the current model structure so that total fine root mass is related to total leaf mass, which reduces the additional parameters needed to model. Instead, we are incorporating one additional trait, specific root length (SRL), which will determine the rooting profile, and which can evolve by natural selection in response to environmental changes. This allows for a depth distribution of fine roots, and for the plant water uptake to be dependent on both soil water potential and root distribution. At a community level, this implementation now means that changes in soil water content, e.g., during drought, can influence belowground competition and trade-offs between above- and below-ground biomass for different species. By modelling rooting strategies of deep-rooted vs shallow-rooted species, or evergreen vs deciduous species, the new root implementation in Plant-FATE will enable correct prediction of differential drought and climate response of coexisting plant species in line with the observed trade-offs in relative investment in above- and belowground tissues in association with their life-history strategy. It will thus allow to create a continuum of plants and their eco-evolutionary niches, which will allow us to predict plant functional diversity in response to environmental cues. Ultimately, incorporating roots in Plant-FATE will better represent ecosystem adaptation and community shifts in response to a changing climate.
Enhancing Hydrological Simulation Efficiency by Improving Initial Soil Moisture Conditions through Reanalysis Data
Authors: Zhou Li , Liu Lingxue
Published: March 2024

In the domain of hydrological modeling, accurately determining initial conditions such as soil moisture content is crucial for enhancing simulation efficiency and applying these models effectively in water resource management, flood prediction, and drought forecasting. Traditional methods often rely on a data-intensive warm-up phase to establish these conditions, which diverts valuable data from calibration and validation. Addressing this challenge, our study introduces an innovative methodology that utilizes an alternative global soil moisture dataset to optimize these initial conditions without the conventional warm-up phase, thereby aiming to improve both the accuracy and efficiency of hydrological simulations. We focused on the Block-wise use of the TOPMODEL (BTOP) and ERA5-Land reanalysis data, specifically analyzing three soil moisture variables within the Fuji and Shinano River Basin, Japan. Through a comprehensive correlation analysis, we examined the dynamics between these variables and employed a range of curve-fitting functions alongside advanced techniques, particularly Long Short-Term Memory (LSTM) networks, to establish a robust relationship between BTOP and ERA5-Land soil moisture variables. The LSTM, known for their effectiveness in handling complex time series data, were instrumental in capturing the intricate spatial and temporal correlations between the variables. To validate the efficacy of our proposed methodology, we conducted four hydrological simulation scenarios, meticulously designed to assess the benefits of incorporating ERA5-Land soil moisture data into the model's initial conditions. The results were compelling: simulations using the enhanced initial conditions significantly outperformed those without the warm-up phase and closely approximated the 'optimal' scenario typically reliant on extensive warm-up data. This study not only underscores the potential of using reanalysis soil moisture data to refine initial conditions, thereby revolutionizing water resource management and forecasting practices, but also presents a scalable solution that can be adapted to various hydrological models and scenarios. Consequently, our research contributes significantly to the ongoing discourse on improving environmental modeling and management practices, advocating for more precise, resource-efficient, and adaptable methodologies in hydrological modeling.
Airvolution: Translating Emerging Techniques in Air Quality Monitoring to Philippine Society
Authors: Manapat Jill , Hizon John Richard
Published: March 2024

Air quality monitoring (AQM) research is still in its nascent stages in the Philippines. One of the few academic research programs in the country focusing on the development of AQM technologies is the Center for Air Research in Urban Environments (CARE). Based at the University of the Philippines Diliman, CARE is an interdisciplinary group funded by the Department of Science and Technology (DOST) that aims to expand the current coverage of AQM stations by complementing a network of affordable AQM nodes. Its technologies include a multi-stakeholder IoT Platform with data processing and modeling capabilities, stationary indoor and outdoor (I/O) sensor nodes that detect a wide array of I/O particulates and gases, an AI-powered eTraffic system, locally designed equivalent black carbon (eBC) and volatile organic compound (VOC) sensors, and mobile and wearable sensors, among others. However, CARE acknowledges the gap between developing AQM technologies in the lab and actual adoption and utilization by its target users. Research and innovation can only achieve its intended impact if they are successfully transferred to society.This study will explore various translational methodologies implemented by CARE to increase the chances of AQM technology adoption beyond its three-year DOST grant. Strategies in multi-stakeholder engagement (both local and global), participatory design and co-creation, capacity-building, community-building, and other relevant approaches will be examined through case studies and success stories. Lessons learned and implications for future innovations will also be discussed to provide insights for other research groups that are also working towards effective and efficient AQM technology transfer.
Deep Structure of the Western Alps Derived from New Data — P and S wave velocity images from Finite Frequency Tomography
Authors: Mao Yuantong , Xu Xiaobing , Tang Xiaotian , Zhao Liang , Yang Lei , Solarino Stefano , Paul Anne , Pondrelli Silvia , Aubert Coralie , Salimbeni Simone , Eva Elena , Guillot Stephane
Published: March 2024

The Western Alps are a crucial region for studying subduction-collision processes. The deep structure beneath the orogenic belts has been a topic of ongoing debate and has undergone continuous refined investigations. In this study, we utilized the most extensive dataset available, covering the period from 2012 to 2020, with 1093 stations. This dataset comprises 659 permanent stations, 110 CIFALPS and CIFALPS-2 temporary stations, along with 324 AlpArray temporary stations.We employed the finite-frequency method to conduct inversion of the regional deep velocity structure. Meticulous waveform analyses were performed across various frequency bands for both P and S waves (P: 0.1-0.5Hz, 0.5-2Hz; S: 0.05-0.1Hz, 0.1-0.5Hz). Additionally, for regions with insufficient ray coverage, we utilized the LSBP_Alpscrust1.0 model [Lu et al., 2020], derived from ambient noise tomography, to correct crustal velocities.We have presented for the first time the deep velocity results of S-waves, demonstrating a good consistency with the P-wave velocity structure. Additionally, we re-selected the dataset pairs for the inversion of Vp/Vs images. Our findings provide further insight into the underground structure beneath the Western Alps, uncovering the presence of a continuous subducted slab. Furthermore, in the southern part of the Western Alps, there is a potential indication of high Vp/Vs ratios within the depth range of 100-150 km.
Exploring Remote Sensing Methodologies for River Bed Grain Size: Insights from a Mountainous Watershed Study in Val Camonica, Italy
Authors: Benetti Matteo , Heidarian Payam , Bonomelli Riccardo , Pilotti Marco
Published: March 2024

The measurement of river bed grain size has become an integral aspect of fieldwork in river geomorphology and regional ecology. Over the past years, various authors have proposed remote sensing methodologies to assess grain size based on ground and aerial images. With the burgeoning applications of small unmanned aerial systems (SUAS) in geomorphology, there is a burgeoning interest in leveraging these remote sensing granulometry methods for SUAS imagery. However, a dearth of studies exists that systematically investigate spatially consecutive images yielding grading curves or specifications over extensive areas within mountainous watersheds.This study focuses on the granulometry of the mountainous watershed in Val Camonica, located in northern Italy, employing a drone for initial photographic documentation. The study incorporates the BaseGrain software for importing drone spatially consecutive images and extracting granulation curves from the photographed areas. Additionally, the study encompasses the utilization of Structure-from-Motion (SfM) photogrammetry within a Ground Control Points (GCP) workflow to scale the drone-acquired photos. The precision of this scaling is systematically validated by comparing photos with scaling images including meter using BaseGrain software. The precision of AGISOFT software, employed in the SfM-photogrammetry process, is also critically evaluated by itself with different numbers of benchmarks.Results indicate that, despite the non-professional nature of the instrumentation, the acquisition of high-resolution images is feasible. These images enable the generation of Digital Elevation Models (DEMs) with accuracies ranging between 2 and 3 cm, contingent upon the number of ground control points. The granulation curve, extracted through BaseGrain, exhibits acceptable accuracy within meter-scale resolution. This research contributes valuable insights into the potential of SUAS-based remote sensing granulometry for mountainous watersheds and underscores the importance of methodological precision for reliable results in river geomorphology studies.
Deep Learning-Based Analyses of Feedback Mechanisms in the Land-Atmosphere Interactions during Droughts over the Vietnamese Mekong Delta
Authors: Zhou Keke , Shi Xiaogang , Renaud Fabrice
Published: March 2024

The Vietnamese Mekong Delta (VMD) is the most productive region in Vietnam in terms of agriculture and aquaculture. Unsurprisingly, droughts have emerged as a persistent concern for stakeholders throughout the VMD in recent decades. In the evolution and intensification of droughts, local feedbacks in the Land-Atmosphere (LA) interactions were considered to play a crucial role. Previous studies mainly focused on the water cycle feedback loop (e.g., soil moisture-evaporation-precipitation) in the LA interactions. However, there is a noticeable gap in the feedback loop of coupled water and energy balances (e.g., soil moisture-sensible heat-precipitation) associated with the anomalies in sensible heat and precipitation. Therefore, deep understanding of the roles of key variables and their inter-relationships in the LA interactions is of great significance for local communities and authorities. In this study, a deep learning model, named Long- and Short-term Time-series Network (LSTNet), was applied to simulate the LA interactions over the VMD. With the ERA5 data as modelling inputs, the role of each key variable (e.g., soil moisture, sensible and latent heat) in the LA interactions over the past decade (2011-2020) was investigated, and the variations of these variables and their inter-relationships in the future period (2015-2099) were also analyzed based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) data. The LSTNet model has demonstrated that the deep learning algorithm can effectively capture the relative importance of key variables in the LA interactions. We found it is crucial to evaluate the effect of coupled temperature and sensible heat on the LA interactions, particularly for the regions that are susceptible to concurrent droughts and heatwaves, as the co-occurrence of dry and hot weather conditions would inhibit the formation of precipitation and intensify the drought severity. Moreover, the decline in soil moisture and the rise in sensible heat under a changing climate are anticipated to further diminish precipitation in the future. This study would not only enhance our knowledge of the feedback mechanisms in the LA interactions during the drought evolution and intensification, but also provide valuable insights for further development and advancement of hydrologic models for drought monitoring and forecasting.
Validation of regional climate model ALADIN-CLIM-CZ
Authors: Rulfova Zuzana , Beranova Romana
Published: March 2024

Regional climate model ALADIN-CLIM-CZ operated by Czech Hydrometeorological Institute has been upgraded to the convection permitting resolution of 2.3 km together with the implementation of the non-hydrostatic, fully elastic dynamical core. This study deals with the validation of the reanalysis using the ALADIN-CLIM-CZ model in the area of Europe with a focus on the area of Central Europe. The main motivation for this validation is to evaluate the quality of the model in connection with its planned use for forecasting the future climate in Central Europe and especially in the territory of the Czech Republic.Due to the goal of validation, the study presents standard climate statistics for months and quarters such as long-term means and mean annual cycles and compares them with measurements at selected stations. We validated the following predicted quantities: precipitation amount and number of wet days, mean, minimum and maximum temperature at 2 m above surface, relative humidity at 2 m above surface, wind speed at 10 m above surface and global radiation at the surface.
Understanding the uncertainty in the climate and water resource availability interplay: a distributed analysis of the Italian territory
Authors: Amaranto Alessandro , Mancusi Leonardo , Braca Giovanni
Published: March 2024

As the tangible impacts of climate change continue to unfold, the imperative to assess and prepare for its repercussions on water resources becomes increasingly evident. This study addresses the urgent necessity to foresee future scenarios of surface water availability in Italy, recognizing the crucial role of water in sustaining ecosystems, agriculture, and human life. To unravel the intricate interplay between climate change and water availability, our methodology integrates the three representative concentration pathways (RCPs) from the Intergovernmental Panel on Climate Change with six regional circulation models. This combination projects future trajectories of temperature and precipitation. Utilizing the time-varying quantile mapping downscaling technique, we refine these trajectories for enhanced spatial and temporal resolution (1 km). These downscaled data feed into the water balance model BIGBANG, developed by the Italian Institute for Environmental Protection and Research (ISPRA), facilitating the generation of the spatiotemporal distributions of surface water availability across Italy. A probabilistic analysis offers a nuanced understanding of potential future water scenarios. Our findings highlight the profound influence of emission scenarios on water availability's future trajectory. Under maximum adaptation conditions (RCP 2.6), a relatively stable water availability pattern is projected through the century. Conversely, the business-as-usual scenario predicts a significant decrease of up to 50% in surface water availability, particularly in historically drought-prone southern regions of the country. These results underscore the critical importance of proactive adaptation measures to mitigate the potential impacts of climate change on Italy's water resources.
The impact of convection-permitting simulation on the mesoscale structures of two severe synoptic-scale cyclones on the south-southeast coast of Brazil in 2023 austral winter
Authors: Reboita Michelle , da Rocha Rosmeri , da Silva Leidinice , Coppola Erika , Raffaele Francesca
Published: March 2024

Synoptic-scale cyclones in the southwestern South Atlantic Ocean often result in heavy rainfall, strong winds, sudden temperature drops, and other abrupt changes that affect important metropolitan areas along the south-southeastern coast of Brazil. Despite notable advancements in understanding these systems, numerical simulations continue to face difficulties in accurately reproducing cyclone-induced rainfall and intense winds. Therefore, the aim of this study is to assess the ability of convection-permitting scale simulations (CP) with a spatial resolution of 3 km, to reproduce the mesoscale structures associated with two extratropical cyclones that caused multiple fatalities in the southern Brazil in June and July of 2023. Regional Climate Model (RegCM) version 5 is configured in CP mode and runned continuously from May to July 2023 in a large domain (lon: -81.12 to -33.09; lat: -48.45 to -10.47). The first month is considered a spin-up period. Precipitation simulated in CP mode is compared with locally observed data and with satellite estimates. The comparison with observations indicates that the resolution refinement and the use of cloud microphysics in CP simulation develop many of the cyclone mesoscale structures generating intense precipitation events. The authors thank CNPq, FAPESP and FAPEMIG for their financial support.
Investigation of low wind events over Germany from high resolution regional climate models
Authors: Isik Cetin Irem , Frisius Thomas , Keup-Thiel Elke , Rechid Diana
Published: March 2024

Wind energy has become one of the most important mitigation options for climate change over the last decades. However, variability and availability of wind are also expected to be changed due to climate change. For this purpose, the KliWiSt project has been initiated to determine the influence of climate change on wind energy site assessments in Germany. Within the scope of the project, many aspects of climate change impacts on wind energy have been studied to determine uncertainties about the topic and to develop recommendations for actions. Although there are many studies in literature which evaluate the effects of climate change on wind in the upcoming decades, low wind events are scarcely investigated so far. However, low wind events pose a risk for achieving long term renewable energy targets and ensuring stability of the electricity grids. Wind drought is increasingly becoming a significant phenomenon which determines low wind energy production due to extreme low wind resources.In this study, we have investigated the frequency of low wind events in Germany due to climate change until the end of the 21st century by using an ensemble of high-resolution regional climate model simulations available from the EURO-CORDEX initiative. We also evaluated the performance of the regional climate models with data from different observation stations and with re-analysis data sets. For our investigation we used thresholds of 2 m/s and 3 m/s for wind speed at 10 m and 100 m – respectively for – calculating “calm wind” climate indices. The threshold is determined as 3 m/s (at 100 m height) for low wind events since most of the wind turbines starts wind energy production at this value (“cut in” wind speed). We used two different benchmark data sets (ERA5 and CERRA) to determine historical variation of “calm days” over Germany and to evaluate the performance of the high-resolution regional climate models. Moreover, seasonal, annual, and spatial distributions of low wind events are investigated for Germany where the country has already a high installed wind energy capacity and ambitious renewable energy targets. The study aims to determine trend and frequency of low wind events in the past and future at different terrain conditions at different time scales from different regional climate models. The anticipated results of the study and the project are expected to give insight for policy makers and stakeholders from the renewable energy sector.* *This study is part of the project "The influence of climate change on wind energy site assessments (KliWiSt)" which is funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK).
Response of Late-Eocene warmth to incipient glaciation on Antarctica
Authors: Vermeulen Dennis , Baatsen Michiel , von der Heydt Anna
Published: March 2024

The Eocene-Oligocene Transition is marked by a sudden δ18O excursion occurring in two distinct phases: a precursor event at 34.15±0.04 Ma and the Earliest Oligocene oxygen Isotope Step at 33.65±0.04 Ma. These events signal a shift from the warm Late-Eocene greenhouse climate to cooler conditions, with temperature decreases of 3-5 °C, and the emergence of the first continent-wide Antarctic Ice Sheet (AIS). Despite clear evidence from proxy data, general circulation models (GCMs) struggle to replicate this Antarctic transition accurately, failing to capture the shift from warm, ice-free to cold, glaciated conditions. Even with unrealistically low pCO2 levels, Late-Eocene Antarctic summers in GCMs remain too warm and moist for snow or ice to survive. This study evaluates CESM1.0.5 simulations conducted by Baatsen et al. (2020), using a 38 Ma geo- and topographical reconstruction, considering different radiative (4 pre-industrial carbon levels (PIC) and 2 PIC) and orbital (present-day insolation and low Antarctic summer insolation) forcings. The climate is found to be highly seasonal, characterised by hot and wet summers and cold and dry winters. While reduced radiative and summer insolation forcing weaken this seasonality, the persistent atmospheric circulation still impedes ice sheet growth by limiting summer snow survival. For that reason, a new simulation is conducted with regional, moderately-sized ice sheets imposed on the continent, in order to investigate their stability and their influence on the atmospheric circulation. These ice sheets demonstrate self-sustaining and even expansion potential under 2 PIC and low summer insolation conditions. However, correlating resulting temperature and precipitation patterns with proxy data proves challenging, given the absence of terrestrial proxies. Extended simulations with coupled GCM-ISM models are therefore recommended, allowing for more dynamic atmosphere-ice-ocean-vegetation feedback mechanisms and dynamic radiative and orbital forcing.
The characteristics of eastward-moving regional rainfall events originating in the northeastern of Tibetan plateau
Authors: Chen Haoming , He Mu
Published: March 2024

Using the FengYun (FY) satellite products and hourly rain gauge data, the east-moveing regional rainfall events (RREs) with long duration and large areas originated in the northeastern Tibetan Plateau (TP) were identified. Our findings reveal that 70% of heavy and long-duration(≥6h) RREs originating in the northeastern TP have the potential to move a thousand kilometers eastward during the warm-season. We noted distinct differences in the speed and spatial location of rainfall for the two types of eastward-moving RREs under investigation.. For the long-distance eastward-moving RREs, three local enhancements of precipitation centers, corresponding to the center moving out of 105°E, 110°E and 115°E are evident. In contrast, for the short-distance eastward-moving RREs, the precipitation centers mainly reach the second topographical terrace without further eastward moving. The evolution of mid-level trough and upper troposphere warm anomalies are closely related to the eastward-moving RREs. With the eastward movements of middle troposphere trough, coupled with the synergistic effects of the convergence and a change in wind orientation at the lower level, and the divergence at the upper-level, collectively contribute to the long-distance eastward moving RREs. The short-distance eastward moving RREs, influenced by the ridge of western Pacific subtropical high over North China and the low-level anomalous anticyclone, remains west of 110°E. This study offers an in-depth understanding of how upstream precipitation events influences the downstream rainfall.
Synergistic relationships between the age of soil organic matter, Fe speciation, and aggregate stability
Authors: Siebers Nina , Voggenreiter Eva , Joshi Prachi , Rethemeyer Janet , Wang Liming
Published: March 2024

Understanding the formation and stability of soil aggregates is crucial for sustaining soil functions. This study investigates the impact of organic matter (OM), pedogenic Fe (oxyhydr)oxides, and aggregate size on aggregate stability in an arable soil. Samples were collected from the Ap and Bt horizons of a Luvisol after 14 years of bare fallow, and results were compared with a control field under permanent cropping. In the Ap horizon, bare fallow led to a 26% reduction in the median diameter of the 53-250 µm size fraction, indicating decreased stability of larger microaggregates. Simultaneously, the mass of the 20-53 µm size fraction increased by 65%, suggesting reduced stability, particularly of larger soil microaggregates, due to the absence of fresh OM input. The 14carbon (14C) fraction of modern C (F14C) under bare fallow ranged from 0.50 to 0.90, lower than the cropped site (F14C between 0.75 and 1.01). This difference was most pronounced in the smallest size fraction, indicating the presence of older C. Higher stability and reduced C turnover in
Assessing NOX emission reduction of Shanghai during city-wide lockdown from TROPOMI high spatial resolution observations
Authors: Xue Ruibin , Wang Shanshan , Zhou Bin
Published: March 2024

In this study, TROPOspheric Monitoring Instrument (TROPOMI) observations were resampled to obtain 0.01° × 0.01° NO2 VCD (vertical column density) of Yangtze River Delta (YRD), China. The adjusted Exponentially-Modified Gaussian (EMG) model was improved to estimate the quantified nitrogen oxides (NOX) emission. The estimation in typical cities under regionally polluted YRD area has a good correlation with Multi-resolution Emission Inventory for China (MEIC) emission with R more than 0.9 but lower results mainly due to the underestimation of NO2 VCD by TROPOMI in polluted areas. On this basis, using the adjusted EMG method, this study quantified NOX emission in Shanghai during 2022 lockdown period as 32.60 mol/s with a decrease of 50–80%, which was mainly contributed by the transportation and industrial sectors. The significant reduction of NOX emission in Shanghai is much higher than that of volatile organic compounds (VOCs), which led to dramatic changes in formaldehyde-to-nitrogen dioxide ratio (HCHO/NO2, FNR). Thus, when enforcing regulation on NOX emission control in the future, coordinately reducing VOCs emission should be implemented to mitigate urban O3 pollution.This work was supported by Sino-German Mobility Program (M-0509) and National Natural Science Foundation of China (grant number 42075097, 22176037, 42375089, 22376030).
Salt marsh organic matter quality and decomposition under sea-level rise scenarios: from leaves to fine absorptive roots 
Authors: Arnaud Marie , Bakhos Melissa , Rumpel Cornelia , Dignac Marie-France , Norby Richard J. , Bottinelli Nicolas , Deborde Jonathan , Geairon Philippe , Kostyrka Pierre , Gernigon Julien , Lemesle Jean-Christophe , Polsenaere Pierre
Published: March 2024

Salt marshes are among the most efficient blue carbon (C) sinks in the world, partly due to the slow decomposition of their plant-derived organic matter (OM) in the soil. The fate of this C sink under sea-level rise is still uncertain due to limited knowledge about the processes controlling OM decomposition under different inundation levels. In an in-situ manipulative experiment, we compared salt marsh OM decomposition and quality across simulated sea-level scenarios and litter types (absorptive root, fine transportive root, leave, and rhizome of the shrubby C3 halophyte Halimione Portulacoide) for 170 days. The OM decomposition rate varied only between the longest and shortest inundation treatments, that was lower than the mean inundation of our site. The OM decomposition and C loss rates varied strongly across litter types. Fine absorptive was the slowest to decay, releasing up to 40% less C than the other litter types. Changes in lignin composition varied across litter types, but were unaffected by sea-level rise scenarios. Our study suggests that 1) the assessment of soil C dynamics in salt marshes based on aboveground litter or bulk belowground litter patterns is inadequate because of a marked difference in OM decomposition across litter types; 2) belowground litter lignin quality could be a good proxy for OM decomposition in salt marshes; and 3) sea-level rise is unlikely to decrease OM decomposition under current sea-level rise projections.
Pathways for avoiding ocean biogeochemical damage: Mitigation targets, mitigation options, and projections
Authors: Bourgeois Timothée , Torres Olivier , Fröb Friederike , Jeltsch-Thömmes Aurich , Tran Giang T. , Schwinger Jörg , Frölicher Thomas L. , Joos Fortunat , Keller David , Oschlies Andreas , Bopp Laurent
Published: March 2024

Tipping points are thresholds beyond which large, abrupt and possibly irreversible changes in the climate system or in large scale ecosystems would occur. The crossing of such tipping points under anthropogenic forcing poses a threat to biodiversity, food security, and human societies. However, due to the complexity of the processes involved, it remains notoriously difficult to determine exact thresholds that need to be avoided to stay within a “safe operating space” for humanity. Here, we map, for a variety of mitigation metrics, the crossing of thresholds, which we define to represent a wide range of deviations from the unperturbed state. We assess the crossing of these thresholds in a wide range of plausible future emission pathways: two climate mitigation scenarios (one with a strong overshoot) and one no-mitigation high-emissions scenario. These scenarios are simulated by the latest generation of Earth system models and by two Earth system models of intermediate complexity, for which we created large perturbed-parameter ensembles. Using this comprehensive model database we provide estimates of when and at which warming level 4 mitigation targets (thresholds) for 14 different impact metrics are exceeded along with an assessment of uncertainties. We find that under the high-emissions scenario, even the highest thresholds for many of the impact metrics are exceeded with high confidence, such as the expansion of ocean areas that are undersaturated with respect to aragonite, decreases in plankton biomass, Arctic summer sea ice extent, strength of the Atlantic meridional overturning circulation (AMOC), and subsurface oxygen concentration. The risk of exceeding a given mitigation target decreases under low-emissions and overshoot scenarios. Yet, exceedance of ambitious targets for aragonite undersaturation, Arctic summer sea ice extent, and steric sea level rise (SSLR) are projected to be difficult to avoid (high confidence) even under the low-emissions scenario. The overshoot scenario reduces the risk of exceeding mitigation targets related to Arctic summer sea ice extent, SSLR, AMOC and plankton biomass compared to the high-emissions scenario, particularly in the long-term. Uncertainties in Earth system model projections of net primary production prevent us from concluding on the risk of mitigation target exceedance for this impact metric.
Validation of SWOT data using airborne LiDAR off the coasts of Normandy during the fast sampling orbit phase
Authors: Froideval Laurent , Kersimon Hugo , Conessa Christophe , Benoit Laurent , Salameh Edward , Bonnefond Pascal , Picot Nicolas , Turki Imen , Benoit Laignel
Published: March 2024

The Surface Water and Ocean Topography (SWOT) altimeter will perform a continuous global water survey with unprecedented resolution and accuracy across its 3-year mission. After being launched on December 16th 2022 with a SpaceX Falcon 9 rocket from Vandenberg in California, it was successfully commissioned followed by a Calibration and Validation (Cal/Val) phase that lasted approximately between April and July 2023. During this period, numerous in-situ measurements were performed across the globe to assess the altimeter’s performance. Airborne Light Detection And Ranging (LiDAR) campaigns were conducted off the coasts of Normandy, France as part of other measurements in this region. We carried out 4 different missions, 2 in May and 2 in June, using a Leica ALS 60 airborne sensor aboard 2 different planes, a Piper Navajo and a Swearingen Fairchild Merlin. The flight plans were designed below the SWOT Ka-band Radar Interferometer (KaRIn) along and across the 1-day fast sampling ground track. Ground Control Points (GCP) were acquired under the LiDAR coverage, close to the city of Cherbourg. The plane’s trajectory was processed using CNES GINS software, using the integer Precise Point Positioning (iPPP) mode, resulting in centimetric antenna phase positioning. LiDAR data were calibrated using the GCPs with a millimetric average accuracy. First results between SWOT data and airborne LiDAR indicate very good consistency. Indeed, the differences between the SWOT LR 2 km pre-cal product and LiDAR data, averaged over a similar 2 km grid, gives centimetric standard deviation.
Deep Learning for Detecting Thrust Faults in Subduction Zones
Authors: Zheng Wenhao , Bell Rebecca , John Cédric M. , Guasch Lluis
Published: March 2024

Subduction plate boundary faults and splay faults in accretionary wedges are capable of generating some of the largest earthquakes and tsunamis on Earth. Owing to the complexity of geological structures and the inherent ambiguity in geophysical data, comprehensively characterizing potential thrust fault systems presents a considerable challenge. Current automated fault detection methods, primarily targeting normal faults, show limited efficacy in complex fault systems of subduction zones. Treating the task of fault detection as a binary image segmentation issue, we propose a supervised end-to-end fully convolutional neural network (U-Net) to automatically and accurately delineate thrust faults from seismic data. To circumvent the labour-intensive and potentially subjective manual labelling process required for model training, we have designed a workflow to efficiently auto-generate more than 10000 training pairs comprising both 2D synthetic seismic images and their corresponding labelled images of the thrust faults simulated in the seismic images. Each synthetic seismic image includes randomly undulating stratigraphic strata and faults with dip angles between 5 and 40 degrees, aiming to simulate realistic and varied geological structures and thrust fault features in subduction zone, which equipped the U-Net model to achieve a 91% accuracy rate in fault detection within the test dataset. The example from the Hikurangi subduction zone, New Zealand demonstrates that the U-Net trained by only synthetic data is superior to conventional automatic methods, such as unsupervised methods or supervised methods trained by normal faults, in delineating more than 70% thrust faults from seismic images. To enhance the U-Net model's adaptation to specific regional fault characteristics and reduce the interference from noise, we incorporated a select set of real 2D seismic images and manually interpreted fault labels into the transfer learning process, which significantly improved its prediction accuracy and make the results clearer. From the comprehensive 2D characterizations based on the U-Net model, we can further extract 3D thrust fault systems and quantitatively measure their geometric parameters.
Deep learning techniques applied to 3-D probabilistic inversion of controlled-source electromagnetic data in a marine environment
Authors: Elias Matias , Rosas-Carbajal Marina , Zyserman Fabio I.
Published: March 2024

We designed an computer efficient, probabilistis 3-D inversion algorithm for CSEM data. It is commonly known that multiple physical descriptions of the subsurface fit the geophysical data equally well, due to incomplete measurement coverage, incomplete physical description of the problem, and model overparameterization. A probabilistic inversion approach allows us to explicitly account for data and model uncertainty. Probabilistic inversion is a demanding process in terms of the number of forward model computations required to sample the posterior probability density function of model parameters. Therefore, we use an efficient sampling algorithm (DREAM(ZS)) combined with strategies to optimize the forward model by approximations and error estimation with deep learning techniques. Regarding the latter, we propose an alternative (approximate) approach to our forward model for simulating the electromagnetic (EM) response which reduces the computing time, and we quantify the modeling error committed directly in the inversion process. Thus, we create a statistical error-model related to the approximate EM response by training a Spatial Generative Adversarial Network (SGAN). In contrast to other neural networks, the SGAN training process has the particularity of being a competition between a Generator, which creates fake samples of the training set, and a Critic, which scores the quality of both true or fakesamples. After training the Generator results in a parametric model of the probability density function of the training set (modeling errors). This parametric error-model is incorporated into the inversion process as a complement to correct and quantify the error in our approximate forward model. To test our methodology we first proposed a synthetic experiment of a marine exploration environment. The implementation and subsequent training of the network allowed us to show that SGAN is useful to generate a statistical error-model. The comparison between a set of samples created with the Generator and the training set shows similarities in the statistical properties of both. Thus, we obtain a parameter-reduced error-model capable of representing the different components of the EM response at a considerable number of receivers and frequencies. In addition, the inversion process is significantly accelerated by introducing the forward model approximations, and the incorporation of the statistical error-model improved the determination of the true parameters in our synthetic test case. We then applied our methodology to the inversion of CSEM data acquired in a marine environment.
Extending back in time the Kp-like, open-ended, high-cadence geomagnetic Hp60 and Hp30 indices to cover the period starting from 1985
Authors: Kervalishvili Guram , Matzka Jürgen , Yamazaki Yosuke , Rauberg Jan , da Silva Marcos Vinicius
Published: March 2024

Geomagnetic indices are commonly used for various purposes, including the characterization of geomagnetic disturbance levels, parametrization of physical and empirical models of the near-Earth space environment, and data (re)analysis. The Kp (and ap) index, which is derived and disseminated by the GFZ German Research Centre for Geosciences, is one of the most extensively used such indices. The Kp index has been available since 1932 and therefore is particularly useful for studying long-term space climate trends. However, the Kp temporal resolution is limited to a three-hourly interval, which means that it cannot correctly capture rapid changes in geomagnetic activity that occur on shorter timescales. Secondly, the Kp index has an upper limit of 9, which means that all events of extremely disturbed conditions are described with one single number, which makes it difficult to differentiate between different levels of extreme geomagnetic activity.We developed a new family of geomagnetic indices, called Hpo (“H” stands for half-hourly or hourly, “p” for planetary, and “o” for open-ended). This open-ended, high-cadence index family is similar to the Kp index in its representation of planetary geomagnetic activity, but with higher time resolution and without an upper limit. The Hpo index family consists of the half-hourly Hp30 and the hourly Hp60 indices, as well as their linear versions, the ap30 and ap60 indices. The Hpo index family is based on the same 13 geomagnetic observatory data as the Kp index. Previously, the Hpo index values were only available back to 1995. However, we have recently derived Hpo indices for the period from 1985 to 1994. This period includes several strong geomagnetic storms in 1989-1992 that have been analysed using the newly derived Hpo indices. The Hpo index family provides a more comprehensive view of the geomagnetic activity, allowing for better analysis and understanding of space weather.