bluuebunny/crossref_metadata_2025 huggingface dataset:
Nd-Hf isotopic mapping based on a large archive of age data reveals voluminous continental growth of the Altaids and its control on metallogeny
Authors: Wang Tao , Huang He , Zhang Jianjun , Wang Chaoyang , Cao Guangyue , Xiao Wenjiao , Yuan Lingling , Tong Ying , Guo Lei
Published: February 2023

The Altaids, or the Central Asian Orogenic Belts, is generally considered to be the largest Phanerozoic accretionary orogen on Earth, but it is unclear if it was associated with extensive continental crustal growth and whether there is a link between the crustal growth and ore mineralization. This study, based on 5507 whole-rock Nd and 39514 (2443 samples) zircon Hf isotope data of felsic-intermediate-mafic igneous rocks as well as associated 1830 ore deposit data for the Altaids, presents Nd + Hf isotopic contour maps for this region. The maps highlight the three-dimensional (3D) lithospheric compositional architecture of the Altaids and make it possible to quantitatively evaluate the crustal growth and its relationship to ore deposits. The Altaids hosts ~4,107,350 km2 and ~184,830,750 km3 (assuming a crustal thickness of 40-50 km) juvenile crust (εNd(t) > 0), accounting for 58% by isotope-mapped area (~7,010,375 km2) of almost all outcrops of the Altaids (~8,745,000 km2) and formed during 1000–150 Ma (mainly 600–150 Ma). Therefore, the Altaids can be viewed as the largest storage area and most typical "fossils" of the juvenile crust in orogens worldwide. Our results are applicable to other types of orogens, particularly to the final continental collision and its control on mineralization. The juvenile crustal, slightly juvenile-reworked crustal, and slightly reworked crustal provinces controlled the Cu-Au, the Pb-Zn-Ag, and the Li-Be, Nb-Ta, and W-Sn ore deposits. According to the crustal architecture and background of deep compositions, we propose that the ore deposits can be grouped into three types: juvenile crust-related, mixed source (or slightly juvenile crust)-related, and reworked crust-related. This highlights the close relationship between accretion, continental growth, and mineralization and will facilitate exploration for specific ore deposit types in the Altaids.
Studying flood risk and social resilience at city level by socio-hydrological approach in Can Tho City of Vietnam
Authors: Nguyen Thanh Binh , Tien Le Van Thuy
Published: February 2023

Socio-hydrological approach is a new science that is aimed at understanding the dynamics and co-evolution of coupled human-water systems. We use this concept to analyze how flood risk related to social resilience in Can Tho city, one of the biggest urban area located in the Vietnamese Mekong delta. The study employed both secondary and primary data collected in two inner districts of Ninh Kieu and Cai Rang. Key informant interview with related stakeholders and focus group discussion with local community were conducted in the reserach sites. The results showed that urban flood tends to rise up year by year because of various drivers such as increase of rainfall in a short time combined with the blockage of sewers due to garbage or/and lack of green areas. In term of hydrological aspect, rainfall, river water level and discharge are key factors. In addition, the social drivers like ineffective urban planning and inappropriate human behaviour also play an important role causing serious inundation. We also found that flood risk contributes to reduce social resilience by different ways including infrastructure damages, transportation disruption, livelihood decline, social network discontinuance, landscape degradation, environmental poluttion, human health and fatality. Therefore, it is necessary to take into account both social and hydrological drivers to mitigate the flood risk on one hand and enhance social resilience on the other. Green urban development which has the greatest potential for improving the quality of ecosystem services and providing opportunities for urban dwellers to reconnect with nature should be a good strategy for disaster risk reduction in this situation.
A dataset of Earth Observation Data for Lithological Mapping using Machine Learning
Authors: Vernikos Ioannis , Giannopoulos Georgios , Christopoulou Aikaterini , Begaj Anxhelo , Stefouli Marianthi , Bratsolis Emmanuel , Charou Eleni
Published: February 2023

Machine Learning (ML) algorithms had successfully contributed in the creation of automated methods of recognizing patterns in high-dimensional data. Remote sensing data  covers  wide  geographical areas and could be used to solve the problem of the demand of various  in-situ data.  Lithologicall mapping using remotely sensed data  is one of the most challenging  applications of ML algorithms. In the framework of the “AI for Geoapplications” project , ML and especially Deep Learning (DL) methodologies are investigated  for  the identification and characterization of the lithology based on remote sensing data in various  pilot areas  in Greece.  In order to train and test the various ML algorithms, a dataset consisting of  30 ROIs selected  mainly  from low -vegetated areas,  that cover 2% of the total  area of Greece was created . For each  ROI 

the corresponding shape file  with the lithological units
the corresponding  Sentinel2 (10 bands)  and/or Aster (14 bands) images

are provided
The dataset is  being publicly  available in the cloud along with the necessary code for visualization and processing.
System Dynamic model of Mangrove Restoration Projectin Klawalu Mangrove Park of Sorong West Papua
Authors: Bless Aplena Elen , Raharjo Syafrudin , Pattiasina Thomas , Tjolli Ihwan , Lekito Krisma , Sagrim Meky
Published: February 2023

Mangrove forest ecosystem, has a distinctive characteristics and important ecological functions in coastal areas. This paper describes the system dynamic model of mangrove restoration program at Klawalu Mangrove Park (TWMK) in Sorong Municipality Papua Barat Daya Province. Mangrove vegetation at TWMK is spread and cover two small rivers. TWMK area and its surrounding are about 144.66 ha, which 47.71% from the total area had a very dense vegetation, 24.17% were dense, 16.75% rather dense and about 2.42% had rarely vegetation. Ten primary mangroves are found at TWMK, which Rhizophora apiculate is the dominant species. The mangrove distribution in TWMK is still dense, yet there is still treat of mangrove longing for support economical activities for local people. Thus the system dynamic model will show the extent of mangrove restoration project on carbon stock in TWMK.Key Words : Mangrove, Carbon stock, System Dynamic Dynamic Model, TWMK Sorong
Idealised studies of aerosol effects on precipitation – from aqua-planets to global km-scale models
Authors: Stier Philip , Williams Andrew , Herbert Ross , Weiss Philipp , Dagan Guy , Watson-Parris Duncan
Published: February 2023

Aerosol effects on precipitation can be broadly categorized into radiatively and microphysically mediated effects – all of which remain highly uncertain. Their assessment in atmospheric models generally relies on the simulation of a complex chain of microphysical process growing aerosols into radiatively active size ranges and into size ranges suitable to act as cloud condensation nuclei, subsequently perturbing radiative fluxes, diabatic heating, cloud microphysical processes and ultimately precipitation formation.  The associated uncertainties along each step in these complex process chains remain significant and make it difficult to disentangle uncertainties in aerosol and cloud processes. Here we present results from a hierarchy of highly idealised model simulations in which aerosols are prescribed as fixed plumes of radiative properties, with an optional associated semi-empirical scaling of droplet number perturbations. These idealised simulations provide fascinating insights into the physical processes underlying aerosol effects on precipitation and into the interaction of local perturbations with the larger scale dynamics. Idealised aqua-planet general circulation model simulations reveal that the response of regional precipitation to idealised and realistic aerosol radiative perturbations can be well explained in an energetic framework (because associated changes in the net diabatic heating needs to be balanced by latent heat release, surface or top-of-atmosphere fluxes or compensated for by energy divergence/convergence). Extending this framework by adding land and realistic sea surface temperatures in an AMIP setup, we probe the regional sensitivity of precipitation changes to absorbing aerosol perturbations across the globe. Our results confirm the findings from the aqua-planet studies that that the local precipitation response to aerosol absorption is opposite in sign between the tropics and the extratropics and we show that this contrasting response can be understood in terms of different mechanisms by which the large-scale circulation responds to heating in the extratropics and in the tropics. Finally, we apply our framework in cloud resolving km-scale model simulations regionally and globally, which highlights the importance of radiative perturbations as well as a complex interplay of aerosol effects with the diurnal cycle of precipitation. 
Detection of land cover changes based on the Sentinel-2 multitemporal data on the GEE platform
Authors: Rynkiewicz Alicja , Hoscilo Agata , Chmielewska Milena , Lewandowska Aneta , Aune-Lundberg Linda , Nilsen Anne
Published: February 2023

The world around us is constantly changing, and humans contribute to many of these changes. Land cover and land use (LCLU) changes over time have a significant impact on the functioning of the Earth, particularly climate change and global warming. Spatial data of LCLU changes find important applications in land management, monitoring the sustainable development of agriculture, forestry, rural areas, assessing the state of biodiversity and urban planning.In the frame of the InCoNaDa project "Enhancing the user uptake of Land Cover / Land Use information derived from the integration of Copernicus services and national databases”, the maps of land cover (LC) changes were developed for two study areas - the Łódź Voivodeship in Poland and the Viken County in Norway. The detection of LC changes was performed on the annual bases for the period 2018-2021 based on the analysis of multitemporal optical data from the Sentinel-2 mission. The Google Earth Engine (GEE) platform was used, which allows to analyze satellite data and to perform spatial analyses anywhere in the World while providing computing power. The LC change detection method was divided into two phases. The first phase is based on the analysis of spectral signatures, and the second phase applies the machine learning Random Forest algorithm. The classification was performed separately for each time interval: 2018-2019, 2019-2020, 2020-2021. In this way, three independent classification models were developed for each study area. The following three LC change classes were distinguished:  a) no-change, b) forest loss, and c) construction sites and newly built-up areas. The minimum mapping unit (MMU) was 0.2 ha. The LC change detection models reached high accuracy - in both study areas for all time intervals, the overall accuracy was equal to or greater than 0.97 and the Kappa coefficient than 0.95. The independent verification carried out based on the aerial orthophotos proved that the overall accuracy of the LC changes is pretty good for both study areas (around 0.9). The changes occurring in the construction sites and newly built-up area class reached slightly lower accuracy and has the lowest precision. The presented method showed its universality and adaptability, giving the possibility for further development. We will present the method, algorithm, results and their verification for Poland and Norway.
Crustal rhyolite melts at mantle depths
Authors: Dallai Luigi , Bianchini Gianluca , Avanzinelli Riccardo , Gaeta Mario , Deloule Etienne , Natali Claudio , Cavallo Andrea , Conticelli Sandro
Published: February 2023

Melts with rhyolite compositions originate from partial melting of crustal rocks or extensive differentiation of basaltic melts, at temperatures in the range of 800 °C. Accordingly, they are confined to the shallow continental crust. Nevertheless, experimental studies have demonstrated that dacite-rhyolite melts can be generated at higher temperature (> 1000°c) and pressure (>2 GPa), by partial melting of continental crustal lithotypes, but direct evidence for their occurrence has never been found. This implies that rhyolite melts may be produced at mantle conditions either by subduction of sedimentary material or exhumation of subducted continental crust.Ephemeral rhyolite melt inclusions were found preserved in peridotite xenoliths from Tallante (Betic Cordillera, southern Spain) that are remnants of a supra-subduction mantle wedge. Here, the interaction of silica-rich melts with peridotite generated hybrid mantle domains, characterized by the occurrence of millimetre-sizes felsic veins with crust-like Sr-Nd-Pb-O- isotope compositions. The “Tallante” composite xenoliths were found among a wide population of peridotitic xenoliths, and display extreme compositional and isotopic heterogeneities both within the ambient peridotite and within the felsic veins. The latter consist of orthopyroxene, plagioclase, and quartz, and they are separated from the surrounding peridotite by an orthopyroxene-rich reaction zone. In their mineral phases, rhyolite glass inclusions and interstitial films associated to quartz crystals were observed. Petrological evidence and thermodynamic modelling indicate that rhyolite melts were originated by partial melting of near an-hydrous garnet-bearing metapelites at temperatures above 1000 °C. Partial melting was likely triggered by near-isothermal decompression during rapid exhumation of previously subducted crustal slivers. The melts reacted with the ambient lithospheric mantle at lower temperature (900 °C) and produced orthopyroxene, followed by plagioclase, quartz, and phlogopite. On the basis of chemical characteristics, it is hypothesized that potassic (HK-calc-alkalic to shoshonitic) and  ultrapotassic magmas may originate from metasomatic mantle sources generated from the interaction of crustal rhyolitic melts with mantle peridotite.
NASA’s Geospace Dynamics Constellation (GDC) mission: a multi-spacecraft mission to explore the ionosphere-thermosphere
Authors: Rowland Douglas , Garcia-Sage Katherine , Kepko Larry , Bell Jared , Andersson Laila , Andersson Phillip , Moldwin Mark , Gershman Daniel , Benna Mehdi
Published: February 2023

The Geospace Dynamics Constellation (GDC) is NASA's next strategic Living With a Star mission. GDC's goals are: 1) Understand how the high-latitude ionosphere-thermosphere system responds to variable solar wind/magnetosphere forcing; and 2) Understand how internal processes in the global ionosphere-thermosphere system redistribute mass, momentum, and energy.Planned for launch by the end of the decade, GDC will use six identical observatories, each identically instrumented to fully characterize the magnetospheric drivers of the I-T system as well as the global response of the ionized and neutral gases. GDC will do this with a series of orbital conegurations that will enable it to study the widest range of spatial and temporal scales to date, ranging from hundreds of kilometers and several seconds to tens of minutes, and extending through the regional to the global scale.This poster presents GDC's current status, measurement capabilities, sampling scheme, and model development efforts and show how GDC will et into the larger Heliophysics ecosystem, by 1) obtaining critically needed scientiec observations; 2) providing a source for real-time space weather and situational awareness, as well as retrospective studies to further the science of space weather; 3) serving as a "strategic hub" for other space-based and ground- based efforts that want to leverage GDC to perform complementary science.
Naturally Occurring Asbestos (NOA) in sedimentary rocks: state of the art and perspectives
Authors: Barale Luca , d'Atri Anna , Petriglieri Jasmine , Piana Fabrizio , Turci Francesco
Published: February 2023

Studies on naturally occurring asbestos (NOA) and on the relevant geo-environmental problems have been traditionally focused on metamorphic rocks (and, more recently, on magmatic rocks). Besides these 'primary' occurrences (i.e., those related to the in situ growth of NOA minerals), 'secondary', detrital NOA may occur in sediments, sedimentary rocks and soils derived from the erosion of 'primary' NOA bearing rocks.The occurrence of detrital NOA in sediments and soils is increasingly recognized worldwide. However, a few studies exist that investigate the 'sedimentology of NOA', i.e., the mechanisms underlying the genesis, transport, deposition and post-depositional modifications of detrital NOA particles in the different sedimentary environments. A better understanding of these mechanisms would give us the tools to predict the presence and possible concentration of detrital NOA in sediments and sedimentary rocks.The occurrence and distribution of detrital NOA within the Oligocene-Miocene succession of the southern Tertiary Piemonte Basin (NW Italy), will be investigated as a scientific development in the frame of the CARG project (Geological Mapping at 1:50,000 scale - sheet 195 Novi Ligure). This succession consists of stratigraphic units rich in ophiolite clasts and deposited in a variety of sedimentary environments, from continental to deep marine, thus representing an ideal study case.
Evidence of Early Supershear Transition in the Mw 7.8 Kahramanmaraş Earthquake From Near-Field Records
Authors: Elbanna Ahmed , Abdelmeguid Mohamed , Rosakis Ares
Published: February 2023

The Mw7.8 Kahramanmaraş Earthquake was larger and more destructive than what had been expected for the tectonic setting in Southeastern Turkey. By using near-field records we provide evidence for early supershear transition on the splay fault that hosted the nucleation and early propagation of the first rupture that eventually transitioned into the East Anatolian fault. The two stations located furthest from the epicenter show a larger fault parallel particle velocity component relative to the fault normal particle velocity component; a unique signature of supershear ruptures that has been identified in theoretical and experimental models of intersonic rupture growth. The third station located closest to the epicenter, while mostly preserving the classical sub-Rayleigh characteristics, it also features a small supershear pulse clearly propagating ahead of the original sub-Rayleigh rupture. This record provides, for the first time ever, field observational evidence for the mechanism of intersonic transition. By using the two furthest stations we estimate the instantaneous supershear rupture propagation speed to be ~1.55 Cs and the sub-Rayleigh to supershear transition length to be around 19.45 km, very close to the location of the station nearest to the epicenter. This early supershear transition might have facilitated the continued propagation and triggering of slip on the nearby East Anatolian Fault leading to amplification of the hazard. The complex dynamics of the Kahramanmaraş earthquake warrants further studies.
Geodetically and seismically informed rapid 3D dynamic rupture modeling of the Mw7.8 Kahramanmaraş earthquake
Authors: Gabriel Alice-Agnes , Ulrich Thomas , Marchandon Mathilde , Biemiller James
Published: February 2023

The destruction unfolding after the February 6, 2023 Turkey-Syria Earthquake sequence is devastating. First observations reveal complex earthquake dynamics challenging data-driven efforts. We present rapid, data-informed and physics-based 3D dynamic rupture simulations of the puzzling Mw7.8 Kahramanmaras earthquake providing a first-order mechanical explanation of this earthquake’s complexity and its implications for the Mw7.5 doublet event.By incorporating detailed fault geometries constrained by satellite geodetic observations into 3D dynamic rupture simulations, we show how dynamic interactions between fault geometric complexity and the heterogeneous regional stress field generated the unique and unexpected rupture behaviors observed, including localized supershear, backwards rupture branching, and locally strong shaking.Our supercomputing empowered simulations that tightly link earthquake physics with interdisciplinary observations can provide a direct understanding of the fault system mechanics, reconcile competing interpretations and serve as a constraint to understand the short- and long-term Eastern Anatolian Fault system interaction.
Surface Displacement and Source Parameters of the Mw 7.7 and Mw 7.6 Kahramanmaraş Earthquakes
Authors: Özener Haluk , Zoroğlu Çağkan Serhun , Vardar Egehan , Havazlı Emre , Kaya Eken Tülay , Shafapour Tehrany Mahyat
Published: February 2023

On February 6th, 2023, a devastating earthquake with a magnitude of Mw7.7 occurred in the Kahramanmaras region of Türkiye. The earthquake is caused by the rupture of a NE-SW oriented left lateral strike-slip Pazarcık fault segment located between the East Anatolian Fault (EAF) and Dead Sea Fault (DSF) fault systems. The aftershock sequence of the earthquake indicated that post-seismic deformation continued along the EAF and DSF toward the NE and SW. Just 9 hours later, another earthquake with a magnitude of Mw7.6 occurred along the EW-oriented left lateral Sürgü Fault, located approximately 100 km north of the first event. These two earthquakes released a significant amount of energy and affected ten provinces in southeastern Türkiye. The earthquake region is characterized by a complex tectonic structure actively deforming through a network of strike-slip, thrust, and normal faults formed by the convergence of the Arabian Plate to the Eurasian Plate and the westward movement of the Anatolian Plate. It is of utmost importance to understand the co-seismic and post-seismic surface deformation behavior to make reliable seismic hazard assessments.To better understand the deformation patterns during and after the Kahramanmaraş earthquakes, we processed Interferometric Synthetic Aperture Radar (InSAR) data sets obtained before and after the earthquakes. We used both ascending and descending track SAR images of the ESA Sentinel-1 to detect the surface displacement. Then, we incorporated the post-seismic deformation patterns from the relocated aftershock events to the InSAR derived deformation field to gain insight into the source properties of the events. Our preliminary results revealed several meters of displacement across the faults.
Application of Decision-Making Techniques for Prioritizing Water Treatment Technology in Flood Events: A Preventive Crisis Management in the Czech Republic
Authors: Akrami Mehran , Behzadian Kourosh , Gheibi Mohammad , Khaleghiabbasabadi Masoud , Wacławek Stanisław
Published: February 2023

Flood is one of the phenomena that threaten people's life and property, which occurs every year in developed and developing countries [1]. Meanwhile, rapid response to water quality problems during this natural disaster is one of the most critical factors of an Early-Warning System (EWS). Due to the change in the river network and the washing of urban and rural environments, the quality of water in flood is significantly reduced, and the residents face the problem of water supply during this period [2]. This paper presents a fast response framework for selecting the best water treatment techniques in unusual pollution loads of urban floods based on water qualitative analysis and methods of Game Theory (GT) as decision-making techniques. The main goal of this study is to provide a framework for improving drinking water supply services during flood risk management in the Czech Republic. To achieve the fast water treatment technologies, Ordered Weighted Averaging (OWA), mulTi-noRmalization mUlti-distance aSsessmenT (TRUST) and VIekriterijumsko KOmpromisno Rangiranje (VIKOR) computations as Multi Criteria Decision Making (MCDM) were applied. In fact, based on this structure, an operational model for the Czech Republic as per the Preventive Crisis Management (PCM) approach has been expressed as the primary outcome of this investigation. The results demonstrated that mobile membrane technologies could have higher efficiency than other methods. However, from the economic aspect, many options can be utilized in different scenarios according to the managerial opinions.Keywords: Early-Warning System; Flood; Water Quality; Preventive Crisis Management; Czech RepublicReference[1] Zabihi, O., Siamaki, M., Gheibi, M., Akrami, M. and Hajiaghaei-Keshteli, M., 2023. A smart sustainable system for flood damage management with the application of artificial intelligence and multi-criteria decision-making computations. International Journal of Disaster Risk Reduction, 84, p.103470.[2] Akbarian, H., Gheibi, M., Hajiaghaei-Keshteli, M. and Rahmani, M., 2022. A hybrid novel framework for flood disaster risk control in developing countries based on smart prediction systems and prioritized scenarios. Journal of environmental management, 312, p.114939.
Tracing Extended Internal Stratigraphy in Ice Sheets using Computer Vision Approaches
Authors: Moqadam Hameed , Steinhage Daniel , Eisen Olaf , Wilhelm Adalbert
Published: February 2023

Polar ice sheets Greenland and Antarctica are integral parts of the climate system. Understanding their history, dynamics and past accumulation rates determines projections of sea level change. Ice englacial stratigraphy is used to assign ages, taken from ice cores, to radar reflections and subsequently connect these known layers over large areas. One of the main methods to investigate these characteristics is radar reflections. Ground-penetrating radar (GPR) has been used as the primary technique to detect internal ice architecture.Mapping the internal reflection horizons in order to study and investigate the features, accumulation rates, and ice streams is an important step, which is conventionally done through a semi-automatic process. Such methods are prone to shortcomings in terms of continuity and layer geometry. Moreover, it is highly time-consuming to map an entire profile, the abundance of unmapped radar profiles especially from antarctic ice sheet is an evidence for this. Thus, there is the need for more comprehensive and efficient methods.The use of machine learning to perform this task automatically will make a significant difference for internal layer detection in terms of efficiency and accuracy. Such machine and deep learning methods would be a suitable fit for radar surveys with different properties, such as center frequencies, making them appropriate for both ice, firn and snow data. In this project, apart from classical computer vision methods and image processing, deep learning methods are used to map the internal reflection horizons (IRH). Convolutional Neural Networks (CNN) are a powerful tool to learn features and track the IRHs continuously.In this talk, the implemented classical computer vision methods are enumerated, and the machine learning methods that have been used (the specific pre-processing methods unique to this project, labeling method, architecture and hyperparameters) are explained. The results from some more promising architectures such as U-net are presented and compared to the results from image processing methods. The main challenges in this project are lack of complete training data, unknown number of IRHs in a profile, and abundance of features in a single radargram. These challenges are shown and possible solutions are presented.
Linking the Filomena snowstorm event in Spain to global warming
Authors: Insua-Costa Damián , Lemus-Cánovas Marc , Senande-Rivera Martín , Llasat María del Carmen , González-Alemán Juan J. , Miguez-Macho Gonzalo
Published: February 2023

In early January 2021, an exceptional snowstorm hit Spain, causing widespread damage and chaos across the country. The extreme event was driven by the extratropical cyclone Filomena and left a snow cover of up to 50 cm in the capital, Madrid. In the days following the event, many media outlets hypothesized a link between the episode and climate change. Here we explore this link using a pseudo-global warming attribution approach. Specifically, we reproduce the event using the WRF regional atmospheric model forced with ERA5 reanalysis data. The thermodynamic fields, including temperature and humidity throughout the atmospheric column, skin temperature, and sea surface temperature, are perturbed using five different CMIP6 climate models in order to simulate the event in both a pre-industrial and a future (SSP5-8.5) scenario. In addition, the greenhouse gas concentrations are adjusted to their respective pre-industrial and future values, and the dynamic conditions (i.e., the atmospheric pattern) are fixed using a spectral nudging technique. We found that global warming affects snowfall amounts very unevenly across the country. At higher elevations and especially in northern areas, where the temperature increase is insufficient to convert snow to rain, the amount of snowfall increases due to a general increase in atmospheric water vapor available for precipitation. However, in lower elevations and especially in the south of the country, anthropogenic forcing results in a generalized reduction in snowfall amounts. Under an extreme future warming scenario, increases in snow water equivalent are found to be above +30% in many areas in the north, while in large parts of the south, snow is converted entirely to rain (-100%). Our results demonstrate that the effect of climate change on these cold and wet compound events is highly location-dependent, meaning that in one place the amount of snow recorded during one of these extreme events may increase due to warming, while in another place a few kilometres away the snow may disappear completely.
The Global Environmental Measurement and Monitoring Initiative – An International Network for Local Impact
Authors: Klingenberg Daniel , Bailey D. Michelle , Lang David , Shimamoto Mark
Published: February 2023

The Global Environmental Measurement and Monitoring (GEMM) Initiative is an international project of Optica and the American Geophysical Union seeking to provide precise and usable environmental data for local impact. The Initiative brings together science, technology, and policy stakeholders to address critical environmental challenges and provide solutions to inform policy decisions on greenhouse gases (GHGs) and air and water quality. GEMM Centers are currently established in Scotland, Canada, New Zealand, and the United States. These Centers represent partnerships with leading institutions that are actively working toward developing or deploying new measurement technology and improved climate models. Additional Centers are under development in India and Australia with plans to expand to Asia and Africa.In addition to establishing monitoring centers worldwide, GEMM actively engages with other sectors (including industry, standards organizations, and regional or national governments) to support the incorporation or adoption of these evidence-based approaches into decision making processes. For example, Glasgow, Scotland is piloting the GEMM Urban Air Project, deploying a low-cost, real-time, ground-based network of devices that continuously monitors GHGs and air pollutants at a neighborhood scale. The sensor network in Glasgow is increasing the precision of local models that can provide the city with information to assess current policies and support future action. Here we will share the progress and outputs of the GEMM Initiative to date and highlight paths forward to grow the network.
Functional regression for space-time prediction of precipitation-induced shallow landslides in South Tyrol, Italy
Authors: Moreno Mateo , Steger Stefan , Lombardo Luigi , Opitz Thomas , Crespi Alice , Marra Francesco , de Vugt Lotte , Zieher Thomas , Rutzinger Martin , Mair Volkmar , Pittore Massimiliano , van Westen Cees
Published: February 2023

Shallow landslides are frequently occurring hazards in mountainous landscapes all over the world. These processes are caused by a combination of static (i.e., predisposing factors: topography, material properties) and dynamic controls (i.e., preparatory and triggering factors: heavy rainfall, snow-melt). Data-driven methods have been used to model shallow landslides at regional scales, in which efforts have been taken to separately investigate the spatial component (i.e., landslide susceptibility) and temporally-varying conditions (e.g., rainfall thresholds). However, the joint assessment of shallow landslides in space and time using data-driven methods remains challenging.In the present work, we aim to predict the occurrence of precipitation-induced shallow landslides in space and time (i.e., the where and the when) within the Italian province of South Tyrol (7,400 km²). In this context, we test the added value of describing the precipitation leading to landslide occurrence as a functional predictor, in contrast to traditional approaches where precipitation is taken as a scalar predictor. We built upon hourly precipitation data from the Integrated Nowcasting through Comprehensive Analysis system (INCA, provided by Geosphere Austria) and past landslide occurrences from 2000 to 2021, which systematically relate to damage-causing landslide events. The methodical framework comprised filtering the landslide inventory, sampling landslide absences in space and time (i.e., balanced across years and months), extracting static and dynamic environmental factors (e.g., topography, lithology, land cover, and hourly precipitation), and removing trivial areas and time periods. We implemented a Functional Generalized Additive Model (FGAM) to derive statistical relationships between the different static factors as scalar predictors, the hourly precipitation preceding a potential landslide event as a functional predictor, and the occurrence in space and time of shallow landslides. The resulting predictions were assessed using cross-validation and transferred into space for different precipitation measures in order to hindcast landslide events.The results from this novel approach are expected to integrate landslide predictions in space and time for large areas by accounting for static and dynamic (i.e., hourly precipitation grids) landslide controls, seasonal effects, and the underlying data limitations (e.g., inventory incompleteness). The findings associated with this research are framed within the PROSLIDE project, which has received funding from the research program Research Südtirol/Alto Adige 2019 of the Autonomous Province of Bozen/Bolzano – Südtirol/Alto Adige.
Defining areas to assess ecosystem services provided by geodiversity: methodological analyses on the coast of São Paulo, Brazil
Authors: Queiroz Debora , Motta Garcia Maria da Glória , Pereira Paulo
Published: February 2023

Ecosystem services are essential for life. Nature's biotic and abiotic elements provide goods and services, though this topic has traditionally been the focus of biodiversity research. In the last decade, some studies on geodiversity ecosystem services have been published, dealing with concepts and proposing some identification and quantification methodological procedures. However, one of the main problems in the assessment of geodiversity ecosystem services is related to the delimitation and zoning of the areas to be assessed. Furthermore, the services to be identified and assessed rely on the available data regarding the geodiversity elements in a region. Criteria for selecting potential areas to identify and assess geodiversity ecosystem services are presented, with the study case developed in Baixada Santista, central coast of São Paulo, Brazil. The criteria are organized in (i) characterization of the physical environment and (ii) description of the land use planning. In the first step, geology, landforms, soils and mineral resources maps were used to prepare the index map of geodiversity and to overlay it with the watersheds map. In the second step, land use, ecological economic zoning and protected areas maps were considered to identify potential services provided by geodiversity. Combining these two levels of information, a watershed (Aguapéu River) was selected, presenting a wide range of geodiversity indices and highdiversity of land uses. With this procedure, it was possible to select and discriminate areas considering territorial variations of geodiversity and its use, evidencing a higher diversity of ecosystem services. In addition, the watershed is a management unit already used by decision-makers and eases communication between geoscientists and managers.
HYPE model workflow – a “bottom-up” approach to community large-domain hydrological modelling
Authors: Wijayarathne Dayal , Keshavarz Kasra , Stadnyk Tricia , Pietroniro Alain , Clark Martyn , Knoben Wouter
Published: February 2023

Large-domain hydrological modelling is vital to understand and predict water resources under a changing climate. Here we summarize our efforts to develop a model configuration workflow for the Hydrological Predictions for the Environment (HYPE) model as a proof-of-concept of a “bottom-up” approach to community large-scale hydrological modelling. The initiative of Community Workflows to Advance Reproducibility in Hydrologic Modeling (CWARHM, Knoben et al. 2022) provides a blueprint of a hydrological modelling workflow, separating the model-agnostic and model-specific pre-processing tasks. We extend the CWARHM blueprint to establish an open-source and automated HYPE workflow by adding processing codes to generate geospatial fabric, climate forcing, and parametrization.Our primary contribution is to generalize and automate the HYPE workflow to improve the reproducibility of hydrologic experiments. In this research, numerous global geographic, physiographic, and climatic datasets, covering various spatiotemporal scales are used to develop a geospatial fabric and climate forcing for the HYPE model, using the Bow River watershed in Alberta, Canada as a test case. The geographic and physiographic data are obtained through the “gistool” (https://github.com/kasra-keshavarz/gistool), while climate forcing is obtained using the “datatool” (https://github.com/kasra-keshavarz/datatool). Independent of the data source, these tools provide physiographic attributes and meteorological time series as catchment averaged quantities, enabling semi-distributed hydrological modelling with HYPE. The preliminary analysis shows that the HYPE workflow has successfully separated the model-agnostic and model-specific parts of the model workflow. It substantially reduces manual work in preparing model geospatial fabric and input datasets, saving more time for hydrological analysis. This workflow will support developing probabilistic streamflow using different input datasets and will be upgraded to create a HYPE model instantiation for the entire North American domain.Reference: Knoben, W. J. M., Clark, M. P., Bales, J., Bennett, A., Gharari, S., Marsh, C. B., et al. (2022). Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating model-agnostic and model-specific configuration steps in applications of large-domain hydrologic models. Water Resources Research, 58, e2021WR031753. https://doi. org/10.1029/2021WR031753
WRF Dynamical Downscaling of CCSM over the Arabian Peninsula
Authors: Alsarraf Hussain , Kokkalis Panos
Published: February 2023

This study proposes dynamical downscaling simulations-high resolution of 12 km- by Weather Research and Forecasting (WRF) model, over the Arabian Peninsula. The downscaling of the Community Climate System Model (CCSM), to simulate (2000–2010), and future (2050–2060) time periods. The Arabian Peninsula is experiencing extreme weather events characterized by large precipitation and above average summer maximum temperatures, which are strong indicators of the climate change impact in the region.  The CCSM-WRF model values were evaluated against values obtained by the Center for Climate Integrity (CCI) on a monthly basis, and during extreme weather events 10 years’ period (2000-2010). The CCSM-WRF results at 12 km are comparable with published outcomes of high-resolution regional climate models, and shows better performance especially during the extreme events over the region (flash floods and heat waves). The future projection of the model shows that the maximum summer average values of temperature, soil temperature, and soil moisture, will increase in the next 30 to 40 years. 
Methane Alert and response system (MARS): IMEO’s satellite-based system for detection and attribution of methane point sources around the world
Authors: Guanter Luis , Irakulis-Loitxate Itziar , Maasakkers Joannes D , Aben Ilse , Lelong Christian , Randles Cynthia A , Zavala-Araiza Daniel , Hamburg Steven P , Caltagirone Manfredi
Published: February 2023

The reduction of anthropogenic methane emissions, and especially those from the fossil fuel industry, is one of the most effective ways to slow down global warming in the next decade. Methane emissions from fossil fuel activities often happen as plumes emanating from strong point sources, such as flares, compressor stations, storage tanks, and mine vents.The Sentinel-5P TROPOMI mission can detect the largest plumes from these sources daily and at a global scale thanks to its continuous spatial coverage and daily temporal resolution. Complementary to TROPOMI, several high spatial resolution satellite missions with sensitivity to methane are now being used to attribute plumes to point sources. These missions, so-called point-source imagers in the methane mapping context, sample the methane absorption features in the shortwave infrared with a spatial resolution of 20-60 m, enabling the detection and attribution of plumes from point sources >200-1000 kg/h. Point-source imagers can be hyperspectral (also known as imaging spectrometers), including the GHGSat, PRISMA, EnMAP, and EMIT missions, and multispectral instruments, such as Sentinel-2, Landsat, and WorldView-3. The observations by these point-source imagers often follow a previous identification of large methane hotspot areas by TROPOMI.In connection with this increasing landscape of methane-observing satellites, the United Nations Environment Programme (UNEP) is implementing a Methane Alert and Response system (MARS) as part of its International Methane Emissions Observatory (IMEO). MARS was recently launched at COP27 in direct support to the Global Methane Pledge. It relies on the combined use of multiple methane-observing satellites for the systematic detection, attribution and monitoring of methane sources. In its initial phase, the focus is on point sources associated to the energy sector.  In this contribution, we will describe the satellite component of MARS and will provide examples of how satellites are being used to detect and mitigate active methane point sources from the energy sector around the world. 
Point cloud analysis and segmentation procedures in the PZero software
Authors: Benedetti Gabriele , Casiraghi Stefano , Bistacchi Andrea , Arienti Gloria , Bertolo Davide
Published: February 2023

With the rapid increase in computing power, 3D modelling and efficient visualization of complex geological features has become more common and accessible. We propose a new point cloud visualization and data analysis module for the open source 3D geomodelling software PZero (https://github.com/andrea-bistacchi/PZero) with the goal to carry out geological, and in particular structural, analysis on Digital Outcrop Models (DOMs). A solid codebase was implemented in PZero to import and analyse DOM data enabling the users to:
Import and visualize dense point cloud data sets

Calculate normals data if missing

Pick plane orientation

Segment the point cloud both manually and semi-automatically

The possibility to study and extrapolate properties from dense point clouds directly in a geomodelling software is a big advantage. Bistacchi et al. (2015) demonstrated that carrying out DOM analysis within a geomodelling package improves both the precision and the accuracy of the resulting 3D model, while Martinelli et al. (2020) demonstrated that reservoir-scale characterization could be carried out starting from the analysis of km-scale DOMs.The open nature of PZero and the readability of its Python code, offers a clear advantage over other closed alternatives in terms of ease of editing and writing new functions. Moreover PZero is robust and efficient in visualizing dense datasets, allowing to easily render on a laptop point clouds reaching hundreds of millions of points. As a result large high-resolution DOMs can be exploited to map complex structures or to carry out dense statistical analysis at the reservoir scale. By including the DOM workflow in a geomodelling package, geologists can approach the modelling problem with new valid tools and techniques and seamlessly include in the final model quantitative and statistically robust properties.
Evaluating trends and risks of aquatic pesticide pollution in the Western Cape, South Africa
Authors: Chow Reynold , Davies Emma , Fuhrimann Samuel , Stamm Christian
Published: February 2023

South Africa is the leading user of pesticides in Sub-Saharan Africa. Consequently, there is an urgent need to improve our understanding of which pesticides persist in the environment and how they are being transported to non-target environments. The presence of pesticides in non-target environments, such as surface water or groundwater, could be detrimental to aquatic ecosystems and human health.Our research focuses on monitoring for pesticides in the rivers of three agricultural catchments (Grabouw, Hex River Valley, and Piketberg) within the Western Cape, South Africa. Passive samplers are being deployed from March 2022 to March 2023, adding to a pre-existing dataset of analytical and pesticide application data from 2017 to 2019. Laboratory methods are being developed and validated at Stellenbosch University (SU) to analyze for pesticides using Liquid Chromatography-Mass Spectrometry. Duplicate samples were analyzed at the Swiss Federal Institute of Aquatic Research (Eawag), as a quality control step. Limits of Quantification were lower at Eawag and measured concentrations were typically higher compared to SU. These differences are likely due to variations in the instrument used and sample extraction procedure. Results from 2017-2019 indicate that 83% of samples contained five or more pesticides. In every year of sampling, total pesticide concentrations were typically attributable to a single/few compounds per catchment. Six pesticides exceeded Environmental Quality Standard (EQS) values in at least one of the sampling periods. Imidacloprid was highlighted as a pesticide of concern since it consistently exceeded EQS values over all sampling periods. Detection/exceedances of pesticides generally coincided with their application and rainfall events, except for imidacloprid and terbuthylazine. This suggests that alternate transport pathways, such as storage and input from groundwater, may be relevant. Recent results from 2022 sampling indicate that the concentrations of imidacloprid are decreasing; however, they are still exceeding EQS values. Lastly, expansion of the analytes in 2022 led to the detection of two new pesticides, dimethomorph and diphenylamine.Our results suggest that establishing a long-term data set regarding aquatic pesticide pollution in the Western Cape will lead to a better understanding of the trends and risks of pesticide use. This improved knowledge will lead to the development of targeted mitigation measures for more sustainable agricultural practices in South Africa and beyond.