bluuebunny/crossref_metadata_2025 huggingface dataset:
NSSDC's Practices toward FAIR Data and AI for Space Science
Authors: Hu Xiaoyan , Zou Ziming , Tong Jizhou , Xu Qi
Published: March 2024

The age of big science is leading to the fact that many of today's important scientific problems and grand human challenges call for major breakthroughs through interdisciplinary joint research. Space science research and innovative applications are facing such a situation. Open science and artificial intelligence enable a new era in the space science research and application, offering new opportunities as well as challenges, such as the absence of data governance theories and standards, data quality and interoperability to be improved, and insufficient supply of data & intelligence-driven analysis models and tools.To make good use of large-scale space science research data and effectively support across-domain joint research, the Chinese National Space Science Data Center (NSSDC), in conjunction with several universities and research institutions, has carried out a series of practices on FAIR data implementation and AI for space science, contributing to the development of a new generation of open research infrastructure.On data governance and stewardship side, NSSDC actively promotes the FAIR principles in China's space science satellite missions and large-scale ground-based observation network projects, develops a theoretical model of scientific data governance and a set of data standards. For intelligent data application, NSSDC is exploring the development of AI-ready space science big data along with the development of intelligent analysis tools and models for automatic target identification, feature extraction, correlation and causal analysis, and event evolution prediction. In this process, we found that many of these AI-ready demands coincide with FAIR principles. How to achieve AI-ready and FAIRness are two closely related goals. In fact, both need to deal with the scale disaster and dimensional disaster of domain data, to enhance the openness of scientific resources including data, models, software and scientific workflows, to adapt to the tendency of significantly increasing machine participation in the scientific research process, and to address the complexity puzzle of frontier scientific problems. Through the fusion, integration and efficient interconnection of these scientific resources, an open scientific infrastructure that supports cross-domain and cross-platform data discovery, access, analysis and mining has been established, effectively supporting joint innovation for major scientific issues. Currently, NSSDC is also exploring connections and interactions with scientific infrastructures in other related disciplines, such as astronomy, high-energy physics and Earth system science.
Development of a land model for the next generation MIROC climate model and evaluation of its simulated land-atmosphere coupling
Authors: Nitta Tomoko , Arakawa Takashi , Takeshima Akira , Yamazaki Dai , Yoshimura Kei
Published: March 2024

We have been developing Integrated Land Simulator as a land model for the next generation of the MIROC climate model. Using a general-purpose coupler, ILS couples various land component models with minimum modifications and makes a land model independent from the atmospheric model. The major changes from the previous version of the land model in MIROC6 are the method of coupling land and atmosphere, the independent grid system and spatial resolution for the land model, and the river model. In MIROC6, the land model was part of the physical process of the atmospheric model and was run sequentially, but in the new model (MIROC-ILS), the land and atmospheric models are run in parallel. We have confirmed the MIROC-ILS meets the requirements such as water balance closure and computation time. In the presentation, we will show how the changes of land-atmosphere coupling method and coupling frequency affects the simulated atmosphere field.
Characterization of the Groundwater Induced Land Subsidence and Aquifer Parameters Using InSAR Measurements in the Xingtai, North China Plain
Authors: Song Sha , Bai Lin
Published: March 2024

Long-term overexploitation of groundwater has led to significant land subsidence and ground fissures in the Xingtai plain. It is extremely important to investigate the coupling relationship between land deformation and hydraulic head change for controlling land subsidence and mitigating ground fissures. In this study, we obtained the spatial and temporal evolution of land deformation in the Xingtai plain by using Envisat/ASAR data during 2009~2010 and Sentinel-1A data during 2015~2021. We investigated the response of land deformation to head change and estimate the aquifer parameters, combining InSAR results, head observations and geological data, . First, joint analysis of displacement time series and head changes infers that land subsidence was mainly caused by the inelastic compaction in aquitards. Compared with the subsidence patterns during 2009~2010, both the rate and spatial extent of land subsidence increased obviously during 2015~2021. Second, seasonal fluctuations in hydraulic head resulted in significant seasonal deformation with an amplitude of 10~30 mm and peak time of January~March, of which the spatial–temporal distribution was consistent with that of the rapid subsidence. Third, obvious differences in the deformation rate and seasonal amplitude were observed across the Longyao ground fissures and other three potential fissures during 2015~2021, suggesting that the activity of ground fissures increased compared with that during 2009~2010. Finally, using InSAR results and head observations, we estimated the elastic and inelastic skeletal storativity, with values ranging from 0.9 × 10−3 to 12.4 × 10−3 and 6.2 × 10−3 to 88.0 × 10−3, respectively. The comparison between elastic and inelastic skeletal storativity suggests that ~84.5% of total subsidence was irreversible and permanent.
Exploring the biogeophysical and biogeochemical impacts of an Arctic poleward expansion of the boreal forest
Authors: Zaini Adele , Blichner Sara M. , Tang Jing , Fisher Rosie A. , Lund Marianne T. , Berntsen Terje K.
Published: March 2024

A poleward migration of vegetation is expected in response to rising surface temperatures in the boreal zone and the Arctic regions. This land cover change is proposed to have important impacts on the climate through biogeophysical and biogeochemical feedback mechanisms (Brovkin, 2002; Bonan, 2015; Spracklen et al., 2008). While the benefits of CO2 uptake from forest expansion are better known, further exploration is needed to disentangle the full spectrum of consequences that such a significant land cover change can lead to, including changes in surface albedo, Biogenic Volatile Organic Compounds (BVOC) emissions, evapotranspiration, and turbulent fluxes. These might have an even larger quantitative impact on the climate than carbon sequestration itself at these latitudes (Bonan, 2015).In this work, we use the Norwegian Earth System Model (NorESM2) to simulate the climatic impacts of both idealized and more realistic (forecast using a Dynamic Global Vegetation Model) patterns of high-latitude vegetation expansion with a specific focus on quantifying the radiative forcing of the albedo and BVOC emissions-related changes affecting aerosols and clouds.The results show that the expected vegetation migration in the northern latitudes can have a substantial impact on a global scale. In total, the surface albedo changes dominate at these high latitudes (+0.48 W/m2, as average value over 50°N) over the effects from changes in aerosols and clouds related to changes in BVOC emissions, resulting in a total of +0.43 W/m2. Surprising results are found regarding the BVOC emission-related impacts. We expected that the indirect impact on cloud radiative effect from increasing BVOC emissions and subsequent aerosol formation, would lead to a cooling effect. However, the BVOC-related contribution to the total radiative forcing is +0.01 W/m2, and to the forcing related to changes in cloud properties is +0.05 W/m2. This signal is small but positive. This is consistent with the observed decrease in aerosol and cloud droplet number concentrations (respectively -0.18% and -1.00%), which affect the cloud albedo by lowering it. The processes that take place from the increase in BVOC emissions to its impact on the radiative forcing revealed complexity that needs to be further disentangled. A deeper understanding of atmospheric chemistry, aerosol and cloud formation, dynamics, and interactions at these latitudes is necessary to fully understand the role of large-scale ecosystem shifts in the coupled climate system. 
Applying the DestinE Extremes digital twin to air quality forecasts and emission scenario simulations
Authors: Lange Anne Caroline , Schröder Sabine , Franke Philipp , Langguth Michael , Friese Elmar , Schultz Martin G.
Published: March 2024

Events of extreme air pollution pose threats to humans and the environment. To investigate air quality under extreme atmospheric situations, the DestinE air quality use case developed a comprehensive user interface that enables high-resolution air quality forecasts with diverse analysis options. The user interface encapsulates the two state-of-the-art approaches that are physics-based numerical simulations with the chemistry transport model EURAD-IM (European Air pollution Dispersion – Inverse Model) and data-driven machine learning forecasts with MLAir (Machine Learning on Air data). The EURAD-IM simulations are coupled to the meteorological output of the DestinE digital twin for weather extremes, which provides high-resolution information (~4.4 km). An additionally implemented machine learning based postprocessing even allows for the downscaling of the EURAD-IM forecast output to a resolution of 1 km. MLAir produces 4-day point forecasts at station sites using data from the Tropospheric Ozone Assessment Report (TOAR) data base. The developed system is complemented by an efficient module that enables emission scenario simulations to investigate and develop air pollution mitigation strategies for future extreme events under realistic conditions.The established user interface is demonstrated by two selected air quality extreme events in early 2017 and summer 2018. It aims to provide a new quality of air pollution information that supports the core users, i.e., environment agencies, in decision making. For the near future, it is planned to fully embed the system to the Destination Earth Service Platform (DESP) such that it will be available to a wider community. Besides assisting policy making, the air quality products help to answer scientific questions on air quality and atmospheric chemical processes under extreme weather conditions that are expected to increase in future. 
Understanding the effects of heterogeneity, salinity and background flow on convective dynamics of CO2-brine mixture in fully saturated porous media at geologic carbon storage conditions
Authors: Sen Sayan , Hansen Scott K.
Published: March 2024

Capturing large quantities of CO2 from the atmosphere and sequestering voluminous amounts into deep saline aquifers form one of the key aspects of modern-day climate change mitigation strategies. However, the technical challenge lies in understanding the non-linear dynamics which govern the flow and transport of CO2 in the subsurface. Diffusion of CO2 into brine causes the development and growth of a diffusive layer having a density greater than the ambient brine. This layer yields to small scale perturbations in the flow field thereby producing fingers which propagate with time, facilitating dissolution and trapping. In natural systems, the solubility of CO2 and the mixing behavior is influenced largely by the simultaneous impact of ambient pressure, temperature, brine salinity, heterogeneity and background flow. Although, previous studies have mainly investigated fingering dynamics for homogeneous and heterogeneous cases, employing little or no background flow, a full-scale study collectively considering the different parameters remains to be done.  For our research we developed a 2D particle tracking reservoir simulator to model the transport dynamics of single-phase CO2-brine mixture for a system with spatially varying density, viscosity and local diffusion coefficient, governed primarily by variations in salinity and mixture concentration. Using this simulator, we perform a large-scale Monte Carlo parametric study to establish a thorough understanding regarding the influence of heterogeneous permeability-porosity fields, variable background flow, multicomponent electrolyte brine systems and dispersion anisotropy on the fingering dynamics and transport behavior of CO2-brine mixtures in the subsurface. We will demonstrate how salinity gradients in typical aquifers influence the viscosity and density variations of the mixture at wide ranges of reservoir heterogeneities and investigate its effect on the convective mechanism and mixing behavior. Additionally, in this regard, we will also examine how transverse shearing disrupts fingering thereby influencing the dissolution rate of CO2 into the aquifer. We will also present results highlighting fingering dynamics in preferential permeability pathways of aquifers having very high heterogeneities at different salinities and background flow. Finally, we will investigate how the interplay of these above physical parameters at different degrees affect the standard transition regime stages that are developed previously for homogeneous and heterogeneous cases. The novelty of study lies in considering a much wider range of attributes deemed important to influence large scale fingering dynamics and mixing behavior, where currently to our knowledge, no studies have been performed.
Evaluating the national CO2 budgets of East Asian countries (2015-2022) using the top-down approach
Authors: Bae Yeon , Jeong Sujong , Yun Jeongmin
Published: March 2024

he precise estimation and verification of country-specific net carbon exchange are growing in importance for meeting greenhouse gas reduction targets outlined in the Paris Agreement. In the East Asian region, carbon dioxide emissions account for more than one-third of global emissions; however, the values remain highly uncertain. This study aims to calculate the country-specific Net Carbon Exchange (NCE) for the years 2015–2022 in three East Asian countries—Korea, Japan, and China—using a top-down assessment approach. We utilize the atmospheric inversion system developed based on Geos-Chem adjoint v35j to assimilate OCO-2 XCO2 retrievals, generating net carbon flux. These values compare with national emission inventory data reported to the IPCC and forest growing stock form the National Forest Inventory. We evaluate the national CO2 budgets for the three East Asian countries and analyze the spatial and temporal variations in carbon fluxes.
Lianas buffer tropical forest understories
Authors: Coppieters Kasper , Verbeeck Hans , Visser Marco , Schnitzer Stefan , Meunier Félicien
Published: March 2024

Lianas are an iconic and important feature of tropical forests. On average, they represent about 24 percent of the woody stems and they contributie significantly to the total leaf area. Their abundance increases with increasing seasonality, and they are able to keep their leaves for a longer period in the dry season. Their abundance in the neotropics has been increasing in the last decades. Lianas have a negative impact on the carbon storage of forests by reducing individual tree growth and increasing tree mortality and turnover. However, their impact on the energy balance of the forest, and the forest understory microclimate in particular, is poorly understood. To fill this gap, we installed two experimental setups in a 12-year, ongoing liana removal experiment on Gigante, Panamá. We installed 180 TOMST TMS-4 microclimate sensors in 8 removal and 8 control plots to monitor the microclimate temperature and soil moisture. Next to that, we installed  ~24 pyranometers and photosynthetic actieve radiation (PAR) sensors in a subset of two removal and two control plots, both horizontally, at 1 meter above the soil, and vertically in the canopy. Our findings revealed that lianas buffer the forest microclimate more than trees, leading to an average midday temperature reduction of 0.2°C at the soil surface (measured 15 cm above the soil). The effect increased at higher temperatures during the dry season (temperature reduction up to 0.35°C on the maximum temperature in the forest). For half of the plots, we were able to account for the impact of forest density and structure on the microclimate using simultaneously collected TLS (terrestrial laser scanning) and ALS (aerial laser scanning) data. Lianas likely reduce soil understory temperatures by reducing the amount of solar radiation that penetrates the forest canopy or by reflecting more light back into the atmosphere.
A rapid approach for integrating high-resolution remote sensing and eddy flux observations
Authors: Prikaziuk Egor , Van der Tol Christiaan , Tomelleri Enrico
Published: March 2024

The Eddy Covariance (EC) method is a state-of-the-art ecosystem flux measurement technique. EC data is used to calibrate and validate biogeochemical models for downstream Earth Observation (EO) products. Despite being a point measurement, the EC method samples an area around the measurement tower, called a flux footprint (FFP). The extent and direction of an FFP depend on the wind speed and direction and the state of the atmosphere, thus it changes continuously. Although most of the EC towers are placed in homogeneous areas, where the footprint direction should not play a role, at the modern 10-m spatial resolution of EO satellites such as Sentinel-2, the area under FFP may be seen as heterogeneous because of phenological differences or temporal changes in vegetation cover. The land cover heterogeneity under the FFP may cause challenges in interpreting the EC data and discrepancies in the calibration and validation of EO downstream products.In this study, we investigated the FFP heterogeneity of 72 European EC sites from the ICOS Warm Winter 2020 dataset (https://doi.org/10.18160/2G60-ZHAK). Firstly, the footprint size was statistically estimated according to the dominant plant functional type. Secondly, the heterogeneity was assessed for a circular buffer and twelve sub-sectors of the buffer on Sentinel-2-derived normalised difference vegetation index (NDVI) with several statistical criteria (e.g. Tukey’s test, Z-score). This approach was demonstrated to be an alternative to precise FFP models, as the latter might require parameters not available to the end users, such as standard deviation of the v-wind component or atmospheric boundary layer height. The tool was developed as a stand-alone application and can be used for spatial heterogeneity assessment beyond the tested EC footprints. 
Early humans migration and adaptation in the Palaeolithic Tibetan Plateau
Authors: Chen Fahu , Li Hao , Zhang Dongju , Xia Huan , Jia Zhenxiu
Published: March 2024

 Due to the unique environmental conditions of the Tibetan Plateau, understanding when and how the Palaeolithic ancestors migrated and adapted in the region is a key issue in the course of human evolution. In recent years, along with the increased findings of archaeological evidence and a series of high-level studies, our knowledge regarding the prehistorical human activities on the plateau has been dramatically changed. Evidence from the Baishiya Cave in northeastern plateau have shown that Denisovans occupied the cave since at least 200 ka years ago and stayed in the cave for a relatively longer time. The site of Piluo which is located in southeastern side of the plateau indicates that humans possessing handaxe technology dispersed to the plateau at a time older than 130 ka year ago. In addition, a new lithic technological type called Quina technology has also been identified in the southern part of the Hengduanshan Mountains in Yunnan Province, which is probably related to the emergence of a new human group. Altogether, these findings indicate that different types of archaic humans have ever lived on the plateau. The earliest evidence for the arrival of modern humans is from the Nwya Devu site (~4600 m), given the diagnostic blade products excavated from the site. The site has been dated to ca. 40 ka years ago. Based on current evidence, we propose some possible routes for the migration of humans into the plateau. Denisovans may disperse to the plateau from the northeast direction, handaxe population and Quina population may disperse from the southeastern side, while early modern humans may come from the western side, with two possible sources of Central Asia and Southwest Asia. Overall, it is clear that the Palaeolithic Tibetan Plateau consists of an important region for the exchanges of early humans in different areas.Keywords: Tibetan Plateau, Palaeolithic, Denisovans, Early modern human, Human migration and adaptation
The Horizon Europe AGEMERA Project: Innovative Non-Invasive Geophysical Methodologies for Mineral Exploration
Authors: Joutsenvaara Jari , Holma Marko , Kuusiniemi Pasi , Pirttijärvi Markku , Stimac Tumara Barbara , Schimmel Martin , Martin David
Published: March 2024

The AGEMERA project [1], which is an acronym for Agile Exploration and Geo-Modelling for European Critical Raw Materials, employs three non-invasive survey methods for mineral exploration: a passive seismic method to assess bedrock hardness and rock type boundaries; an integrated, multi-sensing fixed-wing drone system for measuring conductivity, magnetism, and radioactivity; and a multidetector system based on muon detection for detailed 2D, 3D, and 4D density profiles of large-volume rock bodies (with the 4th dimension being time). The technologies are designed to map geological structures in scenarios where traditional methods are either environmentally unsound or socially challenging. By the project's conclusion, these methods are anticipated to achieve a Technological Readiness Level (TRL) of 5 within a three-year timeline.The technologies vary in their operational capacities, including acquisition time, depth penetration, area coverage, and volume assessment. The multi-sensing drone effectively probes to 300-500 meter depth and can survey vast areas, up to hundreds of square kilometres, in a single campaign. Muography, on the other hand, can reach depths of up to 1000 metres and cover large volumes, up to a cubic kilometre. Passive seismic analysis, meanwhile, can survey any area and depth while a larger depth usually implies a lower resolution. While these techniques, especially when combined with deep 3D muography, may require extended periods for data collection, the valuable insights they offer make them a worthwhile investment.After conducting these innovative, non-invasive geophysical surveys, the findings will be consolidated in a web-based data repository. This repository will be accessible for in-depth analysis to enhance our understanding of critical raw material distribution.The project receives funding from the Horizon Europe program (Grant agreement ID: 101058178). [1] AGEMERA project homepage, www.agemera.eu (accessed 9.1.2024)
Monitoring wildfires from satellite, integration in Copernicus services and characterizing atmospheric impacts from the regional to the global scales
Authors: Leskow-Czyżewska Dominika , Bojinski Stephan , Chimot Julien , Meraner Andrea , Parrington Mark , Fierli Federico
Published: March 2024

Satellite-borne observations offer the possibility to monitor wildfires and their impact worldwide. In addition, satellite products are increasingly used in early warning and forecasting systems for fire management. Europe is implementing a long-term and reliable observational programme and, within this frame, EUMETSAT, the European meteorological satellite operator, provides numerous observational products ranging from near-real-time wildfire identification (e.g. fire radiative power) to atmospheric impacts (e.g. major pollutants and smoke). 

Our presentation will focus on the satellite data value chain, e.g. the integration in the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS). To do that, we will firstly present datasets addressing wildfires (e.g. Fire Radiative Power, atmospheric composition, and smoke) currently generated at EUMETSAT and its Satellite Applications Facility (SAF). We will also introduce upcoming (based on the Flexible Combined Imager on-board the Meteosat Third Generation) and future products (Sentinel-4 and 5), with an example of potential joint use for a past intense fire case in the Mediterranean (Greece, August 2023).  

We will then show the entire value chain, including how the data is used in the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS), with an example on the recent intense and anomalous fire season in Canada (spring to summer 2023). This will show how distinct phases of wildfires management – from early warnings up to the impacts on yearly emissions – can be monitored with the synergy of satellite data and Copernicus forecast and analysis. Finally, we will touch also on the user support activities within EUMETSAT in this area. 
Is impact ripple flattening caused by aeolian shear melting of the granular bed?
Authors: Rein Constantin , Saban Lior , Yizhaq Hezi , Kroy Klaus , Katra Itzhak , Tholen Katharina
Published: March 2024

Ripples are common aeolian sand waves that can broadly be classified into megaripples, impact ripples and a newly proposed aerodynamic ripple type [1]. Grain scale numerical simulations and conventional theories associate impact ripple formation with a characteristic hop length for the grain trajectories over a quasi-static bed [2-5]. Based on original and literature data we show that impact ripple patterns vanish structurally with increasing shear stress not far from the transport threshold. We correlate the experiments with recent observations of the mass-flux scaling as a function of the shear stress and accompanying grain-scale transport models [6,7]. The comparison suggests that impact ripple vanishing may be associated with a crossover between two fundamentally different transport modes. Only at low wind speeds, near the transport threshold, a description in terms of grain hopping on a quasi-static dilatant sand bed applies, consistent with impact ripple formation. Under stronger winds, the bed-air interface becomes increasingly blurred, due to the formation of a collision-dominated fluidized transport layer that fails to support quasi-static short-wavelength ripples but remains susceptible to longer-wavelength hydrodynamic instabilities. Our observations and tentative physical explanations may contribute to a better understanding of impact ripple formation and provide a new criterion to discriminate between impact ripples and other, more stable ripple types.[1] Yizhaq, H., Tholen, K., Saban, L. et al. Coevolving aerodynamic and impact ripples on Earth. Nat. Geosci. (2024).[2] Bagnold, R. A. The Physics of Blown Sand and Desert Dunes (Methuen, 1941).[3] Sharp, R. P. Wind ripples. J. Geol. 71, 617–636 (1963).[4] Anderson, R. S. A theoretical model for aeolian impact ripples. Sedimentology 34, 943–956 (1987).[5] Durán, O., Claudin, P. & Andreotti, B. Direct numerical simulations of aeolian sand ripples. Proc. Natl Acad. Sci. USA 111, 15665–15668 (2014).[6] Pähtz, T. & Durán, O. Scaling laws for planetary sediment transport from dem-rans numerical simulations. J. Fluid Mech. 963, A20 (2023).[7] Tholen, K., Pähtz, T., Kamath, S., Parteli, E. J. R. & Kroy, K. Anomalous scaling of aeolian sand transport reveals coupling to bed rheology. Phys. Rev. Lett. 130, 058204 (2023).
The realization of a high-temperature ATES in Berlin: from explorational drilling to implementation in Berlin-Adlershof
Authors: Norden Ben , Kranz Stefan , Blöcher Guido , Regenspurg Simona , Virchow Lioba , Saadat Ali
Published: March 2024

Concepts for achieving sustainable energy provision in urban areas require also an appropriate exploration concept for a succesful planning of a possible site-development. Geophysical exploration data and deep reaching boreholes are commonly rare in such areas. In Berlin, Germany, the German Research Centre for Geosciences drilled a research borehole to investigate the usability of Mesozoic aquifers as underground thermal storage reservoirs, the Gt BtrKoe 1/2021 borehole in Berlin-Adlershof. The information gained from this borehole provides new structural data and encounters several Mesozoic potentially ATES aquifers. The general depth of those aquifers are largely determined by the ascent and location of the underlying Permian salt structure. The research well was completely cored from a depth of 210 m (close to the top of pre-Tertiary) to the final depth of the well at 456 m. Based on an in-depth characterization of the cores that included also geophysical measurements on cores (like gamma-ray, bulk density, thermal properties, and p-XRF) and a detailed geological description, the porosity, permeability, and lithological heterogeneity of the drilled succession was evaluated and integrated in a 3D geological model. In the cored borehole section, several promising sandy reservoir sections were drilled, with a main storage reservoir in the Lower Jurassic Hettangian at a depth of 360–400 m. The sandstone is very fine grained and only weakly consolidated, showing porosities of 25–30% and permeabilities of more than 1 Darcy (> 10-12 m²). A first simulation allows for a successful integration of an ATES using this horizon at this site. The simulation is based on the seasonal provision of 35 GWh of storeable heat provided from a wood-fired combined heat and power plant  for a time period of 4 months with a temperature of 90°C, which is stored in the 24°C warm sandstone reservoir. The simulation shows that it will take about two years of operation to reach the full storage potential of the reservoir. Based on the findings, a real ATES will be established at the site, allowing to study in detail possible rock-fluid interactions and the overall performance of the system. The site activities are funded by the BMWK (FKZ 03EE4007 and FKZ 03EWR022C) and the EU project PUSH-IT (https://www.push-it-thermalstorage.eu/).
Themachinethatgoesping: Pythonic(++) processing of MBES and SBES data
Authors: Urban Peter , Praet Nore , Vandorpe Thomas , Hermans Thomas
Published: March 2024

A few powerful tools already exist for processing and investigating multibeam echosounder (MBES) data. They fulfill many industrial and scientific needs regarding quick visualization and bathymetric processing. However, none of these tools sufficiently target scientists that need to- develop new or custom MBES processing methods.Projects focusing on investigating objects in the water column (e.g. gas bubble streams, suspended particulate matter, fish, …) formed the base for a new MEBS processing tool that is currently being developed within the framework of the TURBEAMS project. The aim is a tool that possesses the flexibility to execute custom processing routines, the transparency to understand the specific equations applied to the acoustic raw data, and the power to efficiently apply these customized routines to large amounts of MBES data gathered during scientific surveys.The result of these specifications evolved into themachinethatgoesping (short: Ping), a new open-source python library (implemented in c++) for processing multi- and singlebeam echosounder data. Ping aims at simplifying the development and application of novel processing methods by providing a performant, pythonic interface to the acoustic raw data, together with commonly needed processing routines. A few examples:Extract configuration and navigation data.
Extract quantitative meaningful backscatter data.
Implement and test water column calibration routines.
Create time series echograms or render water column images.
Filter, georeference and grid acoustic samples in 2D and 3D space.
These functions – and the large amount of python data science libraries – form the base to implementing processing methods (or tools) that are shareable as comprehensive python scripts. Ping is still incomplete and e.g. currently limited to processing Kongsberg .all and Simrad EK80 .raw data files. But you can test it and follow the active development here: https://github.com/themachinethatgoesping
Detection and classification of volcanic ash based on satellite UV/VIS measurements 
Authors: Azoulay Alon , Hedlt Pascal , Efremenko Dmitry
Published: March 2024

Volcanic eruptions impact human populations and the environment, with volcanic ash contributing to these effects through its influence on air quality, agriculture, and air transportation. Traditional satellite observation methods for monitoring volcanic ash encounter several challenges, including distinguishing ash from other aerosols, coverage area limitations, frequency of observations, and the impact of adverse weather and atmospheric conditions. These issues highlight the need for supplementary satellite-based approaches to improve volcanic ash monitoring. This project introduces a new method that utilizes machine learning techniques to analyze UV and visible satellite data for detecting and classifying volcanic ash. The research focuses on exploring how satellite UV and visible light observations can be used to identify volcanic ash in the atmosphere. A classifier was developed using simulations from a radiative transfer model, which represents various atmospheric scenarios. This classifier is then applied to analyze spectral measurements obtained by the TROPOspheric Monitoring Instrument (TROPOMI) on the ESA Sentinel-5p satellite. The complexity of detecting and classifying volcanic ash arises not only from the presence of other aerosols in the atmosphere but also from the changing characteristics of the ash, influenced by the type of magma and ongoing alterations as the ash remains airborne. This research presents progress in tackling these challenges and in developing a complex algorithm that incorporates a wide range of parameters. The application of this method to the Raikoke eruption case study enables the identification of some volcanic ash, illustrating the potential of this approach. However, this case study also reveals the presence of misclassifications, highlighting the need for continuous improvement in the classifier. This research offers valuable insights into the detection and classification of volcanic ash, contributing to the enhancement of monitoring strategies for hazard mitigation.
Dynamics of Intraseasonal Compound Whiplash Event: A Retrospective Analysis in India
Authors: Kumar Aman , Arya Dhyan Singh
Published: March 2024

Hydroclimatic Whiplash events refer to the extreme variability characterising the rapid transitions from one hydroclimatic extreme to another, occurring in consecutive periods. Rapid transition from one extreme to the other. The compound consecutive extremes impact often exceeds the magnitude of individual events given their occurrence at distinct times. This study introduces a comprehensive investigation into Intraseasonal compound whiplash occurrences in India, focusing on the rapid shifts between drought/heat and pluvial conditions. The data used in the study is taken from IMD precipitation of 0.25˚ x 0.25˚ and temperature at 1˚x 1˚ for the time span 1901 to 2022. This study involves distinct thresholds for duration and intensity to identify the heat dry and wet events. Dry events are characterised by prolonged low rainfall and sustained minimum temperatures throughout the dry period. Conversely, wet events exhibit high intensity within relatively shorter durations. Emphasising the 70th percentile for temperature thresholds acknowledges that extreme conditions in each component aren't mandatory for a compound event's occurrence. Our study delves into the frequency of individual extremes and compound whiplash occurrences, calculating swing severity using mean temperature quantiles for warm/dry spells alongside precipitation anomalies. The Mann-Kendall test and Sen’s slope is used for the check frequency and severity evolution at the grid level. Results highlight diverse regions witnessing increasing trends in wet and dry events, signifying a notable surge in compound whiplash incidents. This is especially worrying in areas that have typically been dry because the increase in rain can disrupt the usual climate there. This concerning trend raises alarms for local ecosystems, water resources, and socio-economic activities. Recognising these evolving patterns is critical for making strategies and long-term planning in the recent climate variability.
Impacts of forest cover and disturbance on Holocene forest biodiversity
Authors: Schild Laura , Herzschuh Ulrike
Published: March 2024

Forests play a critical role in carbon storage and actively mitigate climate change. By fostering biodiversity they offer further intrinsic and economic value through ecosystem functions and services. However, logging and the increasing frequency and intensity of wildfires and pest outbreaks pose significant disturbances to forests. Understanding the interactions between forest cover, biodiversity, and disturbance is essential for determining effective strategies for forest management and conservation. To investigate past dynamics in diversity and forest cover, we utilized pollen-based vegetation reconstructions for the Northern Hemisphere over the past 10 000 years. We derived richness and forest cover and computed metrics for forest cover trends, centennial forest cover variability, and disturbance frequency and intensity. We analyzed the relationship of these potential drivers and forest cover and richness using loess models and explored spatio-temporal patterns.Our findings reveal a negative relationship of richness with forest cover, with maximum richness observed at low to intermediate forest cover values.This indicates a potential tradeoff between high forest cover for optimal carbon storage and high biodiversity. Richness also demonstrates a normal response to centennial forest cover variability, supporting the intermediate disturbance hypothesis. Interestingly, we also find that increasing the cumulative disturbance intensity increases richness. This indicates a positive effect on forest richness from both many small and few large disturbances. This highlights the potential of disturbances to increase and maintain biodiversity in temperate and boreal forest.These findings could help with designing forest management and conservation measures that align with carbon storage and biodiversity goals.
Risk of falling stone material on the Ramps of Piazzale Michelangelo in Florence
Authors: Palamidessi Anna , Intrieri Emanuele , Salvatici Teresa , Centauro Irene , Garzonio Carlo Alberto
Published: March 2024

The Ramps of Piazzale Michelangelo (Michelangelo Square) in Florence are a pedestrian connection between the Arno riverside and the higher Piazzale Michelangelo, leaning against the side of the hill called "Monte alle Croci," a hill delimiting Florence to the south. Over the years, this area has experienced a long series of instabilities that have affected some of the most significant testimonies of the city's architecture. The Ramps of Piazzale Michelangelo are popular both with tourists visiting the city and with the residents of Florence, who use them as a picturesque place to stroll.The Ramps and contiguous Viale dei Colli (Hills Avenue) are one of the most interesting projects of the architect Giuseppe Poggi during the period when Florence was the capital of Italy (1865-1871). The staircases of the Ramps feature stone balustrades, topped with Pietraforte sandstone caps. Geologically, Pietraforte is a turbiditic sandstone characterized by numerous sedimentary layers typical of the Bouma sequence and by the presence of secondary calcite veins. These features are the main weak points where detachment phenomena can occur.The action of rainwater leads to the dissolution of calcium carbonate, present both in the calcite veins and in the carbonatic cement within the rock. In the first case, this mechanism can result in the decohesion of the rock with the complete opening of veins and possible detachment and fall of blocks (even blocks with volume up to about 50 dm3). In the second case, detachments occur as a superficial exfoliation rather than detachments of entire portions of material.Recent restoration works, completed in May 2019, focused on the conservation and recovery of architectural elements. However, in July 2020, a wedge collapsed, hitting a vehicle below. Subsequently, as a temporary countermeasure, the parapets were covered with nets to prevent new possible accidents.For a long-term countermeasure, this architectural problem has been investigated assimilating it to a rockfall scenario. First of all it was necessary to manually detect and evaluate every block's discontinuity to assess susceptibility. An equation for calculating the risk of each identified block was then implemented. Differentiated interventions were proposed for each block based on its possible kinematics.Using an approach based on statistical analysis of the rockfall’s susceptibility, this study aims to: 1) Quantify the spatial distribution of rockfalls; 2) Build an equation to identify the more dangerous blocks; 3) Propose safety interventions with minimal impact, diversifying them based on the kinematics of each individual block. Keywords: Cultural Heritage, Stone element risk, rockfall, road safety, susceptibility.
Eyes on the Water: Leveraging Citizen Photos and AI for River Health Assessment and Management
Authors: Hung Ho Tin , Pearce Daniel , Wang Li-Pen , Ochoa-Rodriguez Susana , Jones Amy
Published: March 2024

River pollution is a global challenge recognized as unacceptable by citizens. Despite increasing awareness and investment in river water quality monitoring worldwide, current monitoring strategies fail to well characterise river health. In particular, the spatial and temporal resolution at which river health is currently monitored is insufficient and falls short to identify e.g., pollution spikes and point pollution sources. At the same time, the rise in citizen engagement in river monitoring, driven by increased awareness and widespread availability of smart phones and other monitoring technologies, has generated opportunities to overcome current monitoring barriers.  In this paper, we share our experience collaborating with the community group Friends of Bradford’s Becks (FoBB, UK) to use citizen-collected photos for AI-based detection of health indicators, leading to enhanced river health management. More specifically, FoBB has collected around 100,000 photos of the streams that flow through and under Bradford. These images offer insights into the health of the becks, including specific pollution issues such as discharging overflows, sewage litter, discolouration, amongst other things, as well as how pollution has changed in time and space. The number of photos makes analysis challenging. In this project, we used AI models for automatic image labelling and prototyped several landing solutions for embedding the labelling model into a tool usable by citizens. The project was initially set up in a Hackathon, funded by Natural England, and aimed to develop solutions using AI models. The landing solutions employed classification and object detection deep learning models to assist citizens by offering automatic detection of river health indicators. This not only reduces the cost of reporting but also improves the quality of reporting with comprehensive labels. Through community engagement, high spatio-temporal resolution data can be collected from citizens to fill the data gaps, including pollution levels, natural habitat conditions, and biodiversity. Additionally, while collecting the data, the deep learning models can be further fine-tuned to better assist citizens and managers in river health assessment and management. In summary, the project presents a holistic approach to river health management, combining the strengths of AI with the insights and engagement of local communities. The success of this approach in Bradford offers a template for similar initiatives globally, marking a step towards more informed and responsive river health management strategies.
Unmixing halophytes in coastal wetlands using a multi-sensor approach at two spatial scales
Authors: Silvestri Sonia , Yang Zhicheng , Blount Tegan , D'Alpaos Andrea , Murray A. Brad , Marani Marco
Published: March 2024

Coastal wetlands are geomorphic systems highly sensitive to shifts in environmental forcings such as variations in fluvial sediment transport rates, sea level rise, subsidence rates, nutrient concentrations, temperature, and atmospheric CO2 levels. Despite these influences, the presence of vegetation growing on salt marshes significantly enhances their resilience. It mitigates surface and lateral erosion while fostering the accumulation of organic matter, which contributes to marsh soil accretion and the sequestration of organic carbon. Therefore, the characterization of vegetation properties, canopy biomass and species distribution, is crucial to provide a quantitative basis for bio-geomorphic modeling in coastal wetlands.This study aims to spatially characterize key parameters—such as vegetation species distribution and biomass production—through repeated observations utilizing drone, airborne, and satellite multispectral (MS) imaging. The chosen site for this investigation is North Inlet in South Carolina (USA), renowned for its extensive tidal marshes supporting diverse vegetation species. MS and field data acquisitions were conducted in summer (August 2022 and August 2023), coinciding with the period of maximum biomass, and in winter (February 2023), corresponding to the phase of lowest biomass.The application of a random forest (RF) approach proved highly effective in the unmixing process of halophytic vegetation species, enabling the retrieval of the percentage cover for each species. To train the algorithm, field observations were employed to classify drone-captured images within a limited section of the marshland. The random forest classification (RFC) algorithm achieves high accuracies in the classification of vegetation species based on the drone image, with a spatial resolution of about 0.02m and the overall accuracy of about 0.99. Based on this classification result, we applied the random forest regression (RFR) algorithm to unmix vegetation species using coarser-resolution WorldView2 data (pansharpened data with pixel of 0.5 × 0.5 m). Our results suggest that RFR achieves high accuracy in the unmixing process (0.80