bluuebunny/crossref_metadata_2025 huggingface dataset:
JAXA Level-2 Algorithms, Validations and Applications Preparation for the EarthCARE
Authors: Kubota Takuji , Okamoto Hajime
Published: March 2024

Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission (Illingworth et al. 2015) is designed to produce the maximum synergetic collaboration of European and Japanese science teams (Wehr et al. 2023, Eisinger et al. 2024). The EarthCARE products will be developed and distributed from both JAXA and ESA. Continuous exchanges of information have been conducted between Japan and Europe through the Joint Algorithm Development Endeavor (JADE). CPR, ATLID and MSI Level-2 provide cloud mask, cloud phase and cloud microphysics (such as cloud effective radius, liquid water content, optical depth, etc) for the respective sensor products, together with the synergy products by using the combination of the sensors. Further, the CPR provides the Doppler velocity measurement (which gives the vertical information of the in-cloud velocity), and precipitation products. ATLID Level-2 includes aerosol flagging, aerosol component type (such as dust, black carbon, sea salt and water soluble), as well as the aerosol optical properties including aerosol extinction. The cloud and aerosol products will be used to derive the radiative flux at shortwave and longwave, whose consistency with the BBR will be checked to produce the final radiation product by 4-sensors.EarthCARE synthetic data using a global storm-resolving (NICAM) and Joint-Simulator (Joint Simulator for Satellite Sensors) have been developed in Japan and used in the JAXA L2 algorithm developments (Roh et al. 2023).Validation activities are necessary to distribute the scientific products whose quality and reliability are assured. The JAXA is planning the validation activities by utilization of the existing observation network, campaign observation, and cross comparison with other satellite data.Furthermore, a wide range of application research activities will be planned to achieve the mission objectives. EarthCARE observation data will contribute to understanding cloud, aerosol, and radiation processes, evaluations and improvements of climate models and numerical weather prediction (NWP) models, and atmospheric quality monitoring. JAXA is conducting joint-works with universities and research institutes. The Intergovernmental Panel on Climate Change (IPCC) report published in August 2021, “Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the IPCC”, summarizes that the cloud feedback remains the largest contribution to overall uncertainty, and contributions to mitigate the uncertainty can be expected by new insights by the EarthCARE observations.This presentation will introduce JAXA Level 2, Validation and Applications Preparation for the EarthCARE mission.
Africa's Lithospheric Architecture with Multi-mode Body Wave Imaging
Authors: Legre Jean-Joel , Olugboji Tolulope
Published: March 2024

Africa’s lithosphere hosts the longest-lived cratons on our planet and records a rich and diverse tectonic history: plate subduction to the North, a long rift system in the East, the super swell in the South, and a record of continental breakup to the West. However, gaps remain in our current efforts to study its lithospheric layering due to sparse coverage and noisy short-term seismic deployments. Here, we present a body-wave dataset and model assessment products for investigating Africa’s lithosphere (ADAMA). We address the challenge of lithospheric imaging on the continent using sparse and noisy teleseismic body wavefields, i.e., receiver functions and SS precursors. The latter extends lithospheric illumination in regions without station coverage. In both cases, we explore novel denoising approaches: (1) CRISP-RF (Clean Receiver Function Imaging with Sparse Radon Filters), which uses sparse Radon transforms to interpolate the sparse receiver function data and eliminate incoherent noise, and (2) FADER (Fast Automated Detection and Elimination of Echoes and Reverberations), which deconvolves thin-layer reflections buried in long-period SS precursors. We improve constraints on bulk crustal structure and lithospheric layering, e.g., from H-k stacking, following CRISP-RF denoising. We extend spatial sampling and detections of lithospheric layering by jointly interpreting receiver functions and SS precursors following cepstral deconvolution of long-period SS precursor waveforms. Our final model, ACE-ADAMA-BW (Africa’s Continental Layering Evaluated with ADAMA’s Body Waves), will improve 3-D resolution of lithospheric layering spanning the cratons (West Africa, Tanzania, Congo, Kaapvaal, Zimbabwe), rifts (Gourma, East African Rift System) and basins (Taoudeni, Goo, Congo) of Africa.
Hydrology in differently drained agricultural peatlands in Norway 
Authors: Gunathilake Miyuru , Takiriti Mounir , Marttilla Hannu , Rivedal Synnøve , Kløve Bjørn
Published: March 2024

High water content and poor trafficability are typical challenges of cultivation on peatlands. Draining of peatlands is necessary for cultivation which results in peat degradation and emission of Green House Gases (GHGs). The primary aim of this ongoing study is to understand the hydrology of “peat inversion” used as an alternative to other drainage systems in Norway. In the peat inversion method, the mineral soil layer underlying the peat soil is excavated and placed on top of the peat to provide a cover layer to limit further decomposition of peat and GHG emissions. To better understand drainage effects on hydrology, Carbon balances and GHG emissions in agricultural peatlands in Norway, we study different drainage systems located in different climatic settings. Water table behavior and the relationship with precipitation is investigated at four cultivated peatland sites: Farstad (Western Norway, wet, mild climates), Våler (Southeast Norway, dry, cold winter dominated), Sortland (Northwest Norway, mild climate), Pasvik (Northern Norway, dry, cold winter dominated). Different drainage settings including pipe drainage, surface grading and peat inversion exist in these fields.
Analysis of the Signatures Related to the Upper Charge Regions in an Isolated Thunderstorm Observed by Dual-Polarized Phased Array Weather Radar
Authors: Wang Shuo
Published: March 2024

The evolution of charge structure plays a crucial role in thunderstorm electrification. In this paper, the signatures related to the upper charge regions consisting of charged ice crystals are analyzed in an isolated thunderstorm, observed by an X-band dual-polarized phased array weather radar (DP-PAWR), which operates in its normal operational mode which performs a volume scan with 110 elevations at a temporal resolution of 30 seconds. The radar data quality control is applied to polarized parameters of DP-PAWR, including the horizontal reflectivity ZH, differential propagation phase shift, and specific differential phase. The lightning data was obtained by a lightning detection system called LIDEN (LIghtning DEtection Network system) operated by the JMA. A flash group algorithm is employed to group lightning discharges into flash branches according to a spatial range, azimuth interval, and time criterion. To explore the mean structure of upper charge regions in the convective part of the thunderstorms, an expanded quasi-vertical profile method is applied to examine the temporal evolution of microphysical processes of upper charge regions. The convective part in the isolated thunderstorm is defined as one separated from nearby storms by an area of composite ZH larger than 40 dBZ at and above -10℃ layer, and a criterion of correlation coefficient ρHV greater than 0.8 is used to remove poor quality radar data. Meanwhile, only the lightning flashes within the given volume are used to calculate the IC lighting flash rate and explore the signatures with the upper charge regions. The results indicate that during the different stages from the early developing stage of isolated thunderstorms to the end of the mature stage, the upper charge regions above the -10 ℃ layer experienced an evolution process from initiation to development accompanied by the rise of the charge region in the updraft and the enhancement of charge concentration. In the mature stage of thunderstorm, the upper charge regions extended from the -30℃ layer to the cloud top, followed by a decay process in the upper charge region at the end of the mature stage, in which the IC lightning flash rate is larger than 60 flashes/min. At the same time, the mean structure evolution of the upper charge regions exhibited a good relationship with the in-cloud lightning flash rate.
Hazard forecasting: is it a matter of time?
Authors: Selva Jacopo
Published: March 2024

Hazard models aim at making explicit our forecasting capability about future potentially adverse natural events. Hazard events are typically rare and not deterministically predictable, forcing hazard models to speak the language of certainty and uncertainty, that is, of probability. This is valid for any forecasting time window, from years to days/hours in the future (long- to short-term hazard), to the evaluation of the potential impact of an ongoing event in the next seconds/minutes/hours (warning/now-casting to urgent computing). Even though the definition of the target time window is driven by the users of the forecast (e.g. civil protections) and is not a scientific matter, the quantification of existing uncertainty given the time frame is certainly a scientific matter. Probabilistic hazard is commonly discussed mainly for long-term hazards, where large uncertainty dominates. In shorter-term forecasts, uncertainty may deacrease and practitioners are often tempted by simplified approaches that neglect uncertainty, like for eruption forecasting during volcanic crises, or for tsunami warning models after seismic or volcanic events. Nevertheless, uncertainty may still exist, and a rational scientific approach should let the results to speak about existing uncertainty, rather than to neglect it by definition. Is it possible to define a unified approach to probabilistic hazard entailing all time scales? The long-term integral hazard integrating all potential sources and generation/propagation conditions can be adapted to the different forecasting time windows, generating a unified framework in which the different time scales may feed to each other, producing homogeneous and easy-to-interpret results. This unified vision of hazard models, embracing long- to short-term hazard as well as warning and urgent computing models, is here discussed based on the recent advancements in models for volcanic, seismic and tsunami hazard and warning.
Geochemical characteristics of Neogene mudstone in Guanzhong Basin,recovery of provenance and paleo-sedimentary environment
Authors: Lan Huaping
Published: March 2024

At present, the geothermal resources developed and utilized in the Guanzhong Basin are mainly Cenozoic sandstone and glutenite pore -fissure geothermal resources, and the development and utilization horizons are mainly Neogene thermal reservoirs. The occurrence characteristics of geothermal resources, the amount of geothermal resources, and the distribution of favorable areas for geothermal resources development are closely related to the provenance and paleo-sedimentary environment. Identifying the characteristics of Neogene mudstone provenance and paleo-sedimentary environment is helpful to indicate the characteristics of sandstone provenance and paleo-sedimentary environment in the same sedimentary period, which is of great influence for the investigation and development and utilization of geothermal resources in the Guanzhong Basin. The geochemical characteristics of elements in sedimentary rocks record important information of provenance and sedimentary environment. Based on the characteristics of major elements, trace elements and rare earth elements of Neogene mudstone core samples in Guanzhong Basin, the provenance and sedimentary environment were comprehensively studied. The results show that the tectonic setting of the source area of the Neogene mudstone in the Guanzhong Basin is mainly the active continental margin, and the source rocks are mainly the Taibai syenogranite and the Huashan biotite monzonitic granite in the northern of the basin, which contain some intermediate-basic igneous rocks. The chemical alteration index (CIA) is between 61.34 and 76.78, with an average of 70.78, reflecting that Neogene mudstone has undergone moderate weathering, indicating that the climate of Gaoling Group and Lantian-Bahe Formation is in a warm and humid climate environment during the sedimentary period, and the climate of Zhangjiapo Formation sedimentary period is transformed from warm and humid climate to cold and dry climate. Geochemical indicators comprehensively reflect that the Neogene mudstone deposition period is mainly in the reducing environment, and the paleosalinity of the water body is generally in a freshwater and brackish water environment. Finding out the provenance and paleo-sedimentary environment features has practical guiding significance for the calculation of resource quantity, the division of geothermal resources sweet spot area and the determination of key strata for development and utilization in Guanzhong Basin.
The Association Between Nitrous Oxide (NO2) Levels and Seasonal Variations of Weather Conditions Using Artificial Intelligence 
Authors: Tawabini Bassam
Published: March 2024

It is well known that degraded air quality affects human health and the surrounding environment. Air quality is related to emissions from various sources, meteorological (weather) conditions, topography, and vegetation. Weather conditions such as temperature, humidity, dew point, wind speed and precipitation vary significantly over the year and have the potential to affect the formation, transport, and dispersion of air pollutants. Therefore, it is important to understand the correlation between the seasonal variations of weather conditions on the air quality and be able to forecast it with reasonable accuracy. The aim of this study is to apply Artificial intelligence (AI) technique to investigate such correlation. For this purpose, four (4) AI algorithms namely: neural networks (NN), Decision tree (DT), Random forest (RF) and Gradient boosting (GB) have been applied to assess the correlation between Nitrous Oxide (NO2) and seasonal variations of weather conditions (i.e. temperature, humidity, wind speed, wind direction, and pressure). NO2 was selected as a target air pollutant which considered a serious air quality parameter and one of the greenhouse gases. The effect of seasonal variations of weather conditions on the air quality parameters was presented by the date of measurement as a parameter or feature. Air quality data were collected for the period between 2017 and 2021 from a local air monitoring station, while weather conditions were obtained from the weather station at the airport located the Eastern region of Saudi Arabia. The accuracy of the correlation between was tested using mean square error (MSE), mean root square error (MRSE), mean absolute error (MAE) and correlation coefficient (R2). Results of the study revealed a strong association between NO2 levels and seasonal variations of weather conditions. The MEA ranges between 1.765 to 1.439 using NN, DT, RF and GB respectively.  The correlation coefficient (R2) ranges between 0.564 to 0.826 using NN, DT, RF and GB respectively. The results showed that GB algorithm generated better correlation for NO2 compared to other algorithms. The study results can be used for better predicting air quality for NO2 that can be used for the assessment of potential global warming and climate change phenomena
Exploring Machine Learning Models to Detect Outliers in HydroMet Sensors
Authors: Parvez Iram
Published: March 2024

Iram Parvez1, Massimiliano Cannata2, Giorgio Boni1, Rossella Bovolenta1 ,Eva Riccomagno3 , Bianca Federici11 Department of Civil, Chemical and Environmental Engineering (DICCA), Università degli Studi di Genova, Via Montallegro 1, 16145 Genoa, Italy (iram.parvez@edu.unige.it,bianca.federici@unige.it, giorgio.boni@unige.it, rossella.bovolenta@unige.it).2 Institute of Earth Sciences (IST), Department for Environment Constructions and Design (DACD), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), CH-6952 Canobbio, Switzerland(massimiliano.cannata@supsi.ch).3 Department of Mathematics, Università degli Studi di Genova, Via Dodecaneso 35, 16146 Genova, Italy(riccomag@dima.unige.it).The deployment of hydrometeorological sensors significantly contributes to generating real-time big data. The quality and reliability of large datasets pose considerable challenges, as flawed analyses and decision-making processes can result. This research aims to address the issue of anomaly detection in real-time data by exploring machine learning models. Time-series data is collected from IstSOS - Sensor Observation Service, an open-source software that stores, collects and disseminates sensor data. The methodology consists of Gated Recurrent Units based on recurrent neural networks, along with corresponding prediction intervals, applied both to individual sensors and collectively across all temperature sensors within the Ticino region of Switzerland. Additionally, non-parametric methods like Bootstrap and Mean absolute deviation are employed instead of standard prediction intervals to tackle the non-normality of the data. The results indicate that Gated Recurrent Units based on recurrent neural networks, coupled with non-parametric forecast intervals, perform well in identifying erroneous data points. The application of the model on multivariate time series-sensor data establishes a pattern or baseline of normal behavior for the area (Ticino). When a new sensor is installed in the same region, the recognized pattern is used as a reference to identify outliers in the data gathered from the new sensor.
Atmospheric correction method and application of satellite hyperspectral data: A case study in mineral resource monitoring
Authors: Jiang Qianqian , He Tao , Li Wenchang
Published: March 2024

Hyperspectral sensors have become indispensable tools in remote sensing applications, playing a pivotal role in precision agriculture, mineral alteration mapping, land cover classification, and autonomous satellite wildfire detection. Their high spectral resolution and comprehensive spectral information about ground objects underscore their significance. However, despite the wealth of hyperspectral data sources, challenges in data processing have impeded their quantitative application on the Earth's surface. Atmospheric correction, a critical procedure for deriving surface reflectance that accurately captures surface properties, is essential to overcoming these challenges.In this context, we present an adaptive and automated atmospheric correction scheme specifically designed for hyperspectral data. This approach involves the inversion of atmospheric parameters, including aerosol optical depth (AOD) and precipitable water vapor content (PWV), utilizing the inherent hyperspectral information in the image. Importantly, the atmospheric correction is performed without the need for simultaneous atmospheric and surface observations. AOD retrievals exhibit excellent consistency with ground measurements (RMSE < 0.05, R2 > 0.78), and PWV retrievals are also accurate, with an RMSE less than 0.17 g/cm2 and an R2 greater than 0.94. The acquired surface reflectance demonstrates a remarkable resemblance in terms of shape (spectral angle < 2.2°) and magnitude (RMSE < 0.02) compared to in-situ measurements.The ZY-1 02D Satellite (ZY02D), led by the Ministry of Natural Resources of China, is purposefully designed for monitoring natural resources. The Advanced HyperSpectral Imager (AHSI) aboard ZY02D covers a wide area of 60 km * 60 km with a medium-to-high resolution of 30 m and a spectral range spanning from 400 to 2500 nm, featuring 166 channels. To monitor mineral resources in Guangdong Province, China, ZY02D AHSI images are acquired. After atmospheric correction using our method, the resulting surface reflectance spectral curve is utilized to identify mineral areas. The similarity between satellite-based and in-situ measured surface reflectance is assessed by spectral angle and Euclidean distance to identify potential mineral areas. The absorption characteristics of minerals are extracted from the satellite-based surface reflectance to enhance the results. Through comparison with mining rights maps, more than 80% of mining area maps are successfully identified. Moreover, it facilitates the monitoring of unauthorized mining activities, thereby improving the enforcement efficiency of government agencies.
Modelling of urban lake breeze circulation: the implications on urban heat island mitigation
Authors: Zhong Qilong , Song Jiyun , Wang Xiaoxue , Li Yuguo
Published: March 2024

Recent years have seen more intense and frequent heatwaves across the globe. Urban overheating phenomenon induced by global warming and urban heat island (UHI) effect has adverse impact on human health. In particular, compact high-rise cities witnessed worsened wind environment, exacerbating the UHI phenomenon. Blue space such as urban lakes may help mitigate the UHI effect and improve citizens’ living environment. Under weak synoptic wind conditions, the temperature difference between built-up areas and lakes can induce wind circulation, known as lake-breeze circulation (LBC). The LBC system can transport cool and fresh air from lake surfaces into built-up areas, reducing urban air temperature and improving urban wind environment, while increasing urban air humidity. In this study, we developed a multi-scale water-energy coupled CFD model to simulate the transport processes of heat and moisture between lake surfaces and built-up areas within the urban boundary layer. The model adopted a porous turbulence model to simulate the entire urban canopy layer, a lake evaporation model and a species transport model to simulate lake dynamics, and a coordinate transformation method to simulate the effect of the background atmosphere. The model features the capability of resolving dynamics of atmospheric temperature, humidity, and wind at both street canyon scale (1 m) and city scale (50 km) with relatively low computational costs. Based on this model, we conducted sensitivity analysis to investigate the impact of urban parameters (e.g., city scale, building height and density, anthropogenic activities) and lake parameters (e.g., lake scale and lake surface temperature) on the spatial variation of temperature, humidity, wind, and thermal comfort index. Our results can provide significant references for urban planning and city design for sake of UHI mitigation.
 Remote sensing monitoring and trend analysis of Chl-a changes in cultured fish ponds in the Greater Bay Area from 2013 to 2022
Authors: Li zikang
Published: March 2024

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most economically developed and active regions in China. Fish pond farming is the most important aquaculture model in the GBA. In recent years, climate change and the continuous interference of human activities have led to Chl-a content There are significant differences in time and space, and timely monitoring is crucial to protecting the ecosystems of inland water bodies and adjacent sea areas. Most previous studies have focused on inland lakes or adjacent sea areas, and there have been few studies on fish ponds in the GBA. Based on the BST model, this study selected Landsat image data from 2013 to 2022 to invert the Chl-a concentration of cultured fish ponds in the GBA, and analyzed the temporal and spatial differences in Chl-a contained in cultured fish ponds in the GBA. The results show that: (1) The BST model performs well in retrieving Chl-a concentration in cultured fish ponds in the GBA.(2) In the past ten years, Chl-a has declined year by year from 2013 to 2018, fluctuated slightly from 2018 to 2020, and continued to rise from 2020 to 2022. (3) Aquaculture fish ponds are mainly distributed in the central and southern areas of the GBA. Aquaculture fish ponds near the Pearl River Basin are denser and have higher concentrations. (4) Chl-a has shown an overall upward trend in the past ten years. Among them, the aquaculture fish ponds in Dongguan and Zhongshan have the largest upward trend. Dongguan has the highest increase rate and Guangzhou has the lowest increase rate. (5) Chl-a in cultured fish ponds in the GBA has obvious seasonal variation characteristics, with the highest value in summer and the lowest value in winter. Chl-a concentration in the four seasons is highly correlated with water temperature. Changes in water temperature may be the main factor causing this phenomenon. (6) The concentration of Chl-a in the water bodies of fish farming ponds in the GBA is significantly higher than that of the Pearl River water body and sea water, and the Pearl River water body near the shore is higher than that in the center of the river. This may be due to human overuse of feed and disinfectants Caused. Increasing human activities have caused a significant increase in the degree of eutrophication of water bodies in farmed fish ponds. Control of nutrients such as N and P produced by human activities should be strengthened. The results of this study are important references for water body protection in the GBA and the sustainable development of the aquaculture industry value.
Predictability of Magnetopause Location
Authors: Nemecek Zdenek , Safrankova Jana
Published: March 2024

Understanding the dynamics and predictability of magnetopause location is crucial for space weather forecasting and the safeguarding of critical technological infrastructure. The first part of the talk surveys previous effort in development of magnetopause models that gradually involve more and more driving parameters, starting from solar wind dynamic pressure, interplanetary magnetic field (IMF) magnitude and orientation, tilt angle of the Earth dipole and/or IMF cone angle. We show that, in spite of different forms of the magnetopause surface and different functions used for quantification of effects of driving parameters, their ability of prediction of magnetopause location is nearly identical in a statistical sense. Following this survey, we discuss main contributors to the uncertainty of this prediction like variations of upstream parameters or effects of other parameters not included in the present models and suggest a possible way for development of a new, more precise, model. The last part of the talk discusses effects of foreshock and magnetosheath transients that are unpredictable but that can result in extreme magnetopause displacements.
Multi-scale Investigation of a Triassic Sherwood Sandstone Aquifer and Its Impact on Aquifer Thermal Energy Storage
Authors: Gong Shuangyi , Taylor Kevin , Ma Lin
Published: March 2024

The transition of energy supply from mainly fossil sources to low-carbon energy sources is essential for future environmental sustainability. The current worldwide energy demand for heating and cooling in buildings accounts for 40% of the primary energy consumption. The use of aquifer thermal energy storage (ATES) is predicted to play an increasing role as a regenerative energy source. The Triassic Sherwood Sandstone aquifer is the second most important aquifer in England and Wales, providing about 25% of groundwater resources. Hence, understanding its aquifer characteristics is important for assessing the suitability of its use for ATES.This study utilizes samples of the Permo-Triassic Sherwood Sandstone from the Abbey Arms Wood borehole in Delamere, Cheshire, UK. This borehole was drilled to approximately 150m and penetrates the Helsby and Wilmslow Formation. The samples are selected from 5 major facies (coarse- and fine-grained fluvial channel fill sandstones, sandy sabkha, sand sheet and dune aeolian sandstones, and massive sandstone facies). XRD data show that samples are mainly composed of quartz, feldspar, and muscovite, with minor calcite and hematite, with some accessory phases. Quartz contents are between 58.4%- 88.6%, with an average of 76.9%. Feldspar contents are between 6.0%-23.9%, 16.0% in average. Muscovite contents are in the range of 3.3%-12.5%, the mean value is 5.6%. Thin section observation shows that selected Sherwood sandstone samples are characterized by high quartz and feldspar content with few lithic fragments, and hematite coatings are well-developed around mineral grains. The dominant sandstone types are arkose (37.5%) and lithic arkose (18.8%).The porosity of the samples is between 19.2%-26.2%, with the majority being more than 20%. The permeability is between 3.6*10-14m and 1.2*10-11m, mean value is 2.2*10-12m. At room temperature, the testing of 14 samples of the Sherwood sandstone group found that the average intrinsic thermal conductivity is 1.4 w/mK, thermal diffusivity is 1.2 mm2/s and heat capacity is 0.7 J/gK. The physical properties of each lithofacies show subtle systematic differences, with the fluvial sandstone facies and massive sandstone facies having a relatively higher permeability and thermal conductivity. However, significant heterogeneity is not present, suggesting that this aquifer is a good target for ATES.
Driving forces for the ongoing India-Asia convergence: insight from global high-resolution numerical modeling of mantle convection
Authors: Zheng Qunfan , Hu Jiashun
Published: March 2024

The India-Asia convergence has persisted since the onset of collision at ~55 Ma, indicating the driving forces of Indian indentation do not disappear on continental collision in the convergence process. What drives ongoing India-Asia convergence? This puzzle cannot be well resolved by the traditional theory of plate tectonics and the concept of Wilson Cycle. Consequently, questions concerning the primary driving force of the ongoing India-Asia convergence and the magnitude of this force still await an answer. Previous works have proposed multiple candidates for the primary driver of India-Asia convergence, including the continental subduction of the Indian lithosphere under Tibet, oceanic subduction at the Sumatra-Java trench, as well as the basal drag exerted by the mantle flow on the base of Indo-Australia plate. Here we present global geodynamic models to investigate the driving forces behind the India-Asia convergence, which produce good fits to the observed motions, stresses and strains within the Indo-Australia plate. On this basis, we quantitatively calculate the magnitude of effective forces of boundary forces (slab pull and ridge push) and basal drag. We conclude that the Sumatra-Java subduction is the primary driver of the ongoing India-Asia convergence. Indo-Australia plate motion is driven at the Sumatra-Java trench, impeded along the Himalaya, which could increase the shear stress within the plate. Different from the recent emphasis on the basal drag as a dominant driving force for the India-Asia convergence, this study shows that basal drag acts as the resisting force for the northeastward motion of the giant Indo-Australia plate, though it serves as a driver in some local regions. 
Exploring Magnetospheric Substorm Avalanche Dynamics: on Crackling Noise Nature 
Authors: Consolini Giuseppe , De Michelis Paola
Published: March 2024

The dynamics of the Earth's magnetosphere/ionosphere system is remarkably complex, particularly in response to changes of the solar wind and interplanetary conditions. This interplay between the Earth's magnetic field and the solar wind generates a highly complex dynamics. The interaction between the interplanetary medium and the Earth's magnetosphere triggers significant changes within the magnetosphere/ionosphere system. These alterations can lead to various phenomena, including magnetospheric substorms, which exhibit an avalanche dynamics and scale-free energy dissipation. This complex behavior resembles crackling noise phenomena observed in certain physical systems. By examining the scaling properties of auroral electrojet AL-index bursts during these substorms, we have identified similarities with crackling noise in front propagation models. Furthermore, our investigation has unveiled a scaling function describing the avalanche profile of the AL-index, shedding light on the underlying mechanisms governing these bursty dynamics. These findings significantly contribute to our understanding of magnetospheric plasma sheet dynamics and the mechanisms behind the magnetospheric substorms. By linking the scale-free characteristics of these bursts to crackling noise behavior, we gain valuable insights into the underlying physics governing these complex phenomena within Earth's magnetosphere/ionosphere system.
Plant-mycorrhizal associations vary with climate and soil in tropical mountainscapes influenced by landslides: Implications for ecosystem development and soil formation
Authors: Restrepo Carla , Ortiz Yakshi
Published: March 2024

Landsliding creates new substrates upon which ecosystems develop. From a recovery perspective, these substrates may limit plant growth due their harsh conditions. Yet, from a soil formation perspective, these substrates may enhance weathering rates due to a combination of abiotic and biotic factors. Central to both is the role that mycorrhiza may play in ecosystem development, including biogeochemical cycles. Given that at mountainscape scales landslide populations are diverse due to variation in underlying climatic and edaphic conditions, we hypothesize that plant-mycorrhizal associations and their functions will mirror this diversity. To test this hypothesis, we focus on the Sierra de Las Minas in Guatemala (SLM), a mountain range that offers contrasting climatic characteristics associated with aspect (south aspect is dry to mesic and north aspect wet) and steep elevation gradients (400 – 2600 m a.s.l.). Leveraging plant and soil inventories conducted in forest and landslide habitats in the SLM we ask 1) How do plant-mycorrhizal associations vary with aspect, elevation, and habitat? 2) What is the contribution of soil chemistry to the observed variation in plant-mycorrhizal associations? And 3) How do plant-mycorrhizal associations and environmental conditions explain variation in weathering rates? To answer these questions, we integrated our plant inventories with a global database on plant-mycorrhizal associations. The former contains species composition and soil elemental analyses that we used to estimate a variety of weathering indices. The latter was used to assign plants from our field inventories to one or more mycorrhizal type.Plant-mycorrhizal associations were diverse and greatly contributed to the separation of plant communities in multivariate space. Aspect followed by habitat explained a large fraction of the observed variability. Subsets of soil variables correlated with different dimensions derived from principal component analyses suggesting that plant-mycorrhizal associations contribute diverse functions. In general, weathering indexes differed with aspect and habitat. For example, Vogt Residual Index and Chemical Index of Alteration, were higher in landslide than forest and this difference was more pronounced in the wet than dry to mesic aspects. Further analyses will allow us to examine the contribution of plant-mycorrhizal associations to ecosystem development and soil formation in tropical mountainscapes influenced by landslide activity.
Comparison between Developing and Nondeveloping Disturbances for Tropical Cyclogenesis in Different Large-Scale Flow Patterns over the Western North Pacific
Authors: Wang Ziqing , Chen Guanghua
Published: March 2024

This study classifies 407 developing disturbances (DEV) and 2309 nondeveloping disturbances (NONDEV) over the western North Pacific into five large-scale circulation patterns, namely the pre-existing cyclone (PC), easterly wave (EW), zonal wind convergence (CON), zonal wind shear line (SL), and mixed zonal wind convergence and shear line (CON-SL) patterns. The SL pattern has the highest TC yield percentage, followed by the CON-SL, while the EW is the least favorable pattern. The composite analysis shows that upper-level divergence, midlevel relative humidity, and surface heat flux (SHF) growth are crucial to the disturbance development in all the five patterns. Besides, large lower-level barotropic kinetic energy conversion and a well-developed primary circulation are good indicators for disturbance development in the PC, EW, and CON rather than in the SL and CON-SL patterns. Furthermore, for the PC, EW and CON patterns, the DEV features strong and rapidly growing SHF and mesoscale convective systems (MCS) closer to the disturbance center, which allows deep-layer warming and moistening, and drives a deep secondary circulation. Interestingly, due to an environment with high lower-level vorticity, the SL and CON-SL patterns typically foster a relatively mature primary circulation with strong SHF and MCS concentrated close to the center, especially for the NONDEV at the pre-genesis stage. However, a drier mid-to-upper-level environment for the NONDEV inhibits deep convection and causes insufficient upper-level suction, which may explain its shallow secondary circulation and therefore poor potential to develop further.
Towards learning human influences in a highly regulated basin using a hybrid DL-process based framework
Authors: Deng Liangkun , Zhang Xiang , Slater Louise
Published: March 2024

Hybrid models have shown impressive performance for streamflow simulation, offering better accuracy than process-based hydrological models (PBMs) and superior interpretability than deep learning models (DLMs). A recent paradigm for streamflow modeling, integrating DLMs and PBMs within a differentiable framework, presents considerable potential to match the performance of DLMs while simultaneously generating untrained variables that describe the entire water cycle. However, the potential of this framework has mostly been verified in small and unregulated headwater basins and has not been explored in large and highly regulated basins. Human activities, such as reservoir operations and water transfer projects, have greatly changed natural hydrological regimes. Given the limited access to operational water management records, PBMs generally fail to achieve satisfactory performance and DLMs are challenging to train directly. This study proposes a coupled hybrid framework to address these problems. This framework is based on a distributed PBM, the Xin'anjiang (XAJ) model, and adopts embedded deep learning neural networks to learn the physical parameters and replace the modules of the XAJ model reflecting human influences through a differentiable structure. Streamflow observations alone are used as training targets, eliminating the need for operational records to supervise the training process. The Hanjiang River basin (HRB), one of the largest subbasins of the Yangtze River basin, disturbed by large reservoirs and national water transfer projects, is selected to test the effectiveness of the framework. The results show that the hybrid framework can learn the best parameter sets of the XAJ model depicting natural and human influences to improve streamflow simulation. It performs better than a standalone XAJ model and achieves similar performance to a standalone LSTM model. This framework sheds new light on assimilating human influences to improve simulation performance in disturbed river basins with limited operational records.
Impact of terrestrial reference frame on the SLR validation results of GNSS and LEO orbits
Authors: Strugarek Dariusz , Zajdel Radosław
Published: March 2024

The Satellite Laser Ranging (SLR) technique is used to independently validate the microwave-based satellite orbit products. In the so-called SLR validation, the orbit quality is assessed based on the analysis of the SLR residuals, which are the discrepancies between the direct SLR range measurements and the station-satellite vector calculated based on the SLR station positions and the evaluated orbits in Earth-fixed reference frame. Therefore the results of SLR validation are strongly related to the SLR station coordinates. In 2022, the new realization of the International Terrestrial Reference Frame – ITRF2020 – has been released, which considers a few innovations, mainly, an extended model of post-seismic deformations, and the seasonal station coordinate variations in form of annual and semi-annual terms.  In this study, we investigate the impact of recent advancements in ITRF into the SLR-based orbit validation of LEO and GNSS satellites.      We perform the SLR validation of LEO orbit (Swarm-ABC, Sentinel-3A/B, Jason-3) products provided by European Space Agency (ESA) Copernicus Service and Technical University of Graz for one year. Also, we validate Galileo and BeiDou-3 orbit products delivered by ESA and Center for Orbit Determination in Europe in 2023. We incorporate the latest ITRF2020 realization into the SLR validation processing, contrasting the outcomes with solutions that involve the previous ITRF2014 release to illustrate the impact of TRF aging on validation results. Additionally, we examine the influence of including seasonal station motions on SLR validation outcomes. Furthermore, a comparison is made between SLR validation results when utilizing the most recent alternative TRF realizations, namely DTRF2020 and JTRF2020. We discuss the dependency of residuals on different measurement conditions, such as elevation angle and azimuth angle, and their time variability.
Earth's evolution over time revealed by the Nb/U, Ce/Pb and Nb/Th ratios in the sources of mantle plumes.
Authors: Sobolev Alexander , Vezinet Adrien , Chugunov Aleksandr , Esteban Mateo , Batanova Valentina , Arndt Nicholas , Jain Charitra , Sobolev Stephan , Asafov Evgeny , Valley John
Published: March 2024

Magmas from mantle plumes are potentially the best monitors of Earth's compositional and thermal evolution over time. However, their erupted products are commonly modified by syn- and post-magmatic processes and thus do not fully retain original information about their mantle sources. Such data can be recovered from melt inclusions in olivine phenocrysts in the most primitive magmas from mantle plumes. Such inclusions, shielded by host olivine, retain original isotopic and critical trace element signatures of deep mantle sources even for Archean and Hadean Eons.We will present the results of a study of chemical and Rb-Sr isotope composition (EPMA, LA-ICP-MS and RAMAN) of melt inclusions and chemical (EPMA, LA-ICP-MS) compositions of host olivines for komatiites and plume-related picrites with eruption age from 3.3 Ga to 1 Ka.Recent advances in in-situ split stream LA-ICP-MS measurements of 87Sr/86Sr ratios and trace element contents of olivine-hosted melt inclusions revealed significant mantle source heterogeneities of magmas from individual plumes. The results are confirmed by geodynamic modelling (Jain et al., this meeting).We show that the melt inclusions of most studied mantle plumes display heterogeneous populations in age-corrected 87Sr/86Sr ratios and include groups with model ages more than 1 Ga older than the emplacement age. The oldest inclusion groups found in Archean komatiites correspond to Hadean (4.3±0.2Ga, Vezinet et al., in review) and Eo-Paleoarchean (3.6±0.2 Ga) model ages. These and most inclusions from studied komatiites and picrites display Nb/U, Nb/Th and Ce/Pb significantly higher than in BSE.Evolution over time of canonical proxies of continental crust generation (Nb/U, Th/U and Ce/Pb, Hofmann et al., 1986) in mantle plumes, combined with geodynamic modelling, suggests:Most of the continental crust was generated in several Hadean and Archean pulses by plume-induced subduction and melting of the hydrated mafic/ultramafic crust or mantle. Hadean continental crust was subducted or/and reworked.
Restites left after extraction of continental crust were continuously subducted to the core-mantle boundary from the mid-Hadean and later recycled in Archean mantle plumes.
Active formation of both continental and oceanic crust in Hadean was governed by plume-induced subduction, which ceased after cold subducted material hindered the propagation of large plumes at the core-mantle boundary. After heating the recycled lithosphere at the core-mantle boundary, the process repeats, producing oscillating subduction and crustal formation in Hadean-Archean.
Study on energy and displacement evolution of rock slope during the development of landslide by multi-scale modeling
Authors: Wu Yu Chen , Lo Chia ming
Published: March 2024

Slope monitoring is a commonly way to mitigate the hazard of landslide. The displacement is one of the main parameters being used in slope monitoring, however it is not significant until landslide occurs. According to the literature, energy will accumulate, transfer and dissipate during the development of landslide. So, it is possible to take energy as one of parameters used in slope monitoring if it’s property was understood sufficiently. This study is aimed to find the relationship between energy evolution, displacement of sliding mass and mechanical behavior of rock materials during the development of landslide. In addition, the energy data and displacement data were compared to find the difference between them. Science the mechanical properties of rock mass is affected by scale, four kind of numerical models were created using different scales. Then the energy data and displacement data of specific particles inside each models were recorded during the simulation. The small-scale models include direct shear test model and uniaxial compression test model. The large-scale models include simplified toppling failure model and full-scale landslide model. The results show that in the large-scale models, the variation of energy data is more significant than displacement data. However, in the small-scale models, the variation of displacement data is more significant.
Black Crusts as Geochemical Archives: Preliminary Results from Antwerp, Belgium
Authors: Deboli Sofia , Visschers Silke , Astray Uceda Blanca , Šípková Adela , Wilhelm Katrin , De Kock Tim
Published: March 2024

Interaction between the historical built environment and environmental pollution can result in the accumulation of weathering crust on building material surfaces. A subgroup of weathering crusts are black crusts, which consist of gypsum layers formed by sulfation on calcium-rich substrates. These crusts occur more often and are more pronounced in polluted environments such as urban settings. As a result, they can incorporate particulate matter, polyaromatic hydrocarbons, and heavy metals. Black crusts can act as non-selective passive samplers, accumulating distinct layers of air contaminants depending on historical pollution levels.Existing studies provide only coarse-resolution reconstruction of pollution, differentiating solely between inner and outer crust layers. Just a few explore the correlation between different periods of exposure to pollution and the variation of the composition of these crusts. This study focuses on the stratigraphic analysis of black crusts to assess their potential as a reliable geochemical archive for the reconstruction of past anthropogenic pollution within urban settings.Following technological developments in transportation and combustion, the composition of pollutants in the atmosphere has evolved over the centuries, likely reflected within weathering crusts where pollutants accumulate. For the identification of past air pollution signatures, lead can serve as a useful tracer due to its isotopes, their presence is the result of different historical pollution sources. Variations in the ratios of lead isotopes provide a means to attribute and differentiate among these pollution sources. For lead isotope analysis, high-resolution laser ablation mass spectrometry will be used to distinguish between 206Pb, 207Pb, and 208Pb.This study deepens the understanding of localized pollution levels in urban settings, allowing the implementation of conservation interventions including cleaning and consolidation, strategies to mitigate the impact on human health, local ecosystems, and biodiversity, and to support urban planning.