bluuebunny/crossref_metadata_2025 huggingface dataset:
Introducing CAMELS-SE: Connecting 60 Years of Hydroclimatic Observations with Catchment Attributes for 50 Sites in Sweden
Authors: Teutschbein Claudia
Published: March 2024

The field of hydroclimatology is witnessing a transformative era with the convergence of various technologies and methodologies aimed at enhancing research reproducibility and collaboration. Within this context, hydroclimatic datasets have emerged as fundamental tools for unraveling the interplay between climate and hydrology, resonating across geographical boundaries. Particularly, the exploration of large-scale datasets can shed light on hydrological differences and similarities across diverse catchments, serving both scientific and educational purposes. Efforts to enhance the availability of such datasets are ongoing globally, with the introduction of initiatives like CAMELS (catchment attributes and meteorology for large-sample studies). Despite this collective global effort to unravel hydroclimatic complexities, and the abundance of online hydrologic databases, valuable information remains fragmented and scattered across different platforms. Much local data is still presented and documented in languages other than English, impeding the transfer of knowledge between local and international communities. For example, a considerable portion of open hydrologic data provided by Swedish governmental authorities is solely accessible in Swedish, hindering its integration into pan-European or global research.Therefore, we here introduce the community-accessible CAMELS-SE dataset, which covers 50 catchments in Sweden spanning a wide range of hydroclimatic, topographic and environmental catchment properties. The dataset includes daily hydroclimatic variables (precipitation, temperature, and streamflow) over a 60-year period (1961-2020), and information on geographical location, landcover, soil classes, hydrologic signatures, and regulation for each catchment. Data was collected from various sources, such as the Swedish Meteorological and Hydrological Institute (SMHI), the Swedish Geological Survey (SGU) and several Copernicus products provided by the European Environment Agency (EEA). The compiled, spatially-matched, and processed data is publicly available online through the Swedish National Data Service (https://snd.gu.se/en). CAMELS-SE adds a new region to the list of existing CAMELS datasets, offering a valuable resource for studying hydrological processes, climate dynamics, environmental impacts and sustainable water management strategies in Nordic regions.
Modelling multi-phase flows in magmatic systems
Authors: Keller Tobias
Published: March 2024

Magmatic systems in the Earth's mantle and crust range from melt-poor partially molten rock, to mush bodies at intermediate melt fractions, and lenses of melt-rich, eruptible magma suspensions. Previous process-based models, however, have represented magmatic systems as either porous flows at low melt fractions (60%). A lack of theoretical basis to represent mush flows at intermediate phase fractions has thus far hindered investigations into the dynamics of crustal mush bodies. Previous theories were formulated specifically for two-phase flows of melt-solid mixtures, hence not allowing for the inclusion of a third, volatile or other fluid phase. My contribution addresses this gap by presenting a comprehensive theoretical model [1] of magmatic multi-phase flows across all phase fractions at the system scale, rooted in mixture theory. I substantiate its applicability with a numerical implementation utilising a finite-difference staggered-grid approach [2].  Numerical experiments replicate expected behaviours for two-phase flows including rank-ordered porosity wave trains in 1D, and porosity wave breakup in 2D in the porous flow regime, as well as particle concentration waves in 1D, and mixture convection in 2D in the suspension flow regime. In the mush regime, numerical experiments show strong melt localisation into lenses and stress-aligned melt-shear bands. A further application to a three-phase flow problem of immiscible melt segregation from a crystallising magma body demonstrates the versatility of the theoretical model and its numerical implementation. The model code is available open source at github.com/kellertobs/pantarhei. References[1] Keller & Suckale, GJI, 2019. https://doi.org/10.1093/gji/ggz287.[2] Wong & Keller, GJI, 2022. https://doi.org/10.1093/gji/ggac481.
Extreme climatic events and public health in the UK
Authors: Sanderson Michael , Eastaugh Kimberley , Barciela Rosa , Bernie Dan
Published: March 2024

Extreme events such as storms, heatwaves and flooding are increasing in severity worldwide owing to climate change. This study evaluates impacts of future projected climate events that could pose a threat to public health in the UK. An aging population means more people will be susceptible to trips and falls during and following extreme climatic events, such as being blown over during high winds. Data from the UK Climate Projections 2018 (UKCP18) were used to analyse daily extreme events for the current climate and assess projected changes in these events during the remainder of the 21st century. The hazards studied are heat and cold waves, heat stress related events, extreme precipitation and extreme wind speeds and gusts. The use of the latest convection-permitting climate model simulations (2.2 km resolution) from UKCP18 allows better simulation of localised events which could lead to differing levels of impact on public health across the UK. Under a high emission scenario (RCP8.5), extreme heat and precipitation events are projected to increase in frequency (and in some cases duration) throughout the 21st century. Alternately, extreme cold and cold wave events could reduce in frequency, although extreme cold events could still occur and thus monitoring annually would be advised. Little change is projected in extreme wind speeds and gusts. Many of the existing hazards that the UK is already vulnerable to are therefore likely to increase in severity in most cases, which therefore escalates the threat to public health. Although this study focuses on public health in the UK, a similar approach could be used for hazards in other countries.
Simulating Flow Dynamics in Debris Flows: Transition from Rigid to Erodible Beds in Granular Dam Break Experiments
Authors: Hung Chi-Yao , Tsai I-Ling
Published: March 2024

Debris flow, a prevalent natural hazard in mountainous terrains, exhibits distinct flow dynamics depending on its occurrence over a bedrock (rigid bed) or atop a substantial deposition (erodible bed). The investigation of this flow transition is imperative for the comprehension and mitigation of debris flow dangers. This study introduces a unsteady, and non-uniform model, conceptualized to simulate the transition between rigid and erodible beds in debris flows. The model's foundation lies in the principles of mass, momentum, and kinetic energy conservation. It integrates a linearized mu(I) rheology to articulate granular flow deformation, thereby capturing the intricate interplay among particles during flow. Additionally, the model considers the impact of Coulomb friction along the sidewalls. To derive numerical solutions, the governing equations undergo depth integration, employing the HLL scheme (Harten, Lax, and Van Leer) in synergy with a finite volume numerical method. Furthermore, to corroborate the model's predictions, a novel granular dam break experiment was conducted. These experiments utilized a narrow glass channel (3.5 meters in length and 0.04 meters in width), with variations in the initial deposit depth downstream to establish diverse basal boundary conditions. High-speed camera footage facilitated the application of the Particle Tracking Velocimetry (PTV) method for capturing granular motion and generating a velocity field. A thorough analysis of the measured velocity field enabled the validation of the model's predictions, affirming its efficacy in accurately simulating the flow transition between rigid and erodible beds in debris flows.
Legacy effects of post-storm silvicultural treatments on plot-scale soil erosion in a subalpine headwater catchment of the Italian Alps
Authors: Koyanagi Kenta , Nordio Giovanna , Andreoli Andrea , Tomelleri Enrico , Pöppl Ronald , Comiti Francesco
Published: March 2024

Wind-disturbed mountain forests are often subject to artificial deadwood extraction and tree planting to accelerate the recovery of timber resources. However, little is known about to what degree and extent those post-storm silvicultural treatments modify the surface processes of wind-affected hillslopes. This study aims to understand how post-storm silvicultural treatments affect soil erosion from wind-disturbed mountain forests by coupling monitoring and modeling approaches. We continuously collected and measured soil losses from four 4.5-m-wide and 6.0-m-long bounded field plots located on wind-disturbed hillslopes with a slope angle of 45 % in a subalpine headwater of the Italian Alps during the vegetation periods from 2021 to 2023. The dominant ground cover of four plots resulting from altered post-storm interventions is characterized by residual deadwood, native herbs, 20-year-old plantation, and 5-year-old plantation, respectively. During 75 analyzed storm events, average soil loss from the native herbs-covered plot (2.4 t ha-1; SD: ±3.5 t ha-1) was the smallest, followed by plots covered with residual deadwood (mean±SD: 3.1±2.9 t ha-1), 20-year-old plantation (mean±SD: 3.5±5.2 t ha-1), and the 5-year-old plantation (mean±SD: 4.5±4.2 t ha-1). Moreover, linear regression models (p-value < 0.001) indicated that two plantation plots potentially yield 2-fold sediment of naturally regenerating deadwood and herbs-covered plots as storm rainfall depth increases. Our three-year field observations highlight the persistent impact of post-storm forest management activities in accelerating soil erosion potentially even 20 years after their implementation. In the next step, the Water Erosion Prediction Project (WEPP) model will be used to further investigate the effect of human treatments on hydrology and sediment transport in storm-affected mountain areas.
Repeating events detection in northeastern Taiwan using a broadband seismometer array
Authors: Ku Chin-Shang , Huang Bor-Shouh , Lin Cheng-Horng
Published: March 2024

In this study, we document unusual and recurring events that transpired within one hour on November 17, 2021. These incidents were identified through a seismometer array deployed in the Yilan area and Turtle Island, northeastern Taiwan. Preceding this series of events, a shallow submarine volcano near Turtle Island emitted sulfur smoke from October 28, 2021, lasting until November 22, 2021. This eruption was marked by a significant release of white sulfur smoke from the sea near Turtle Island. It reached a height exceeding 3 meters and extended over 100 meters into the air, making it the most substantial eruption of the year. At first, we proposed that the giant bubble could be generated during the submarine eruption and expanded through the water and into the atmosphere; the collapse of this bubble was considered a potential source of the recurring events. However, a grid-search method utilizing the arrival times of seismic stations indicates that the source location is close to the seacoast of Yilan, still dozens of kilometers away from Turtle Island. Upon further analysis of the seismic waveforms, it was observed that the propagation velocity is close to the speed of sound and only detected by surface stations, not by shallow-hole stations. This suggests that the source likely produced signals that couple well with the atmosphere rather than the solid Earth. The waveforms exhibit high consistency between different events at the same station, indicating that the sources occurred at the exact location several times within one hour. The possibility of an aircraft-induced shock wave was considered but needs more investigation. Trustworthy sources and their mechanisms remain to be clarified, and additional data, such as infrasound and pressure data, will be essential for a more comprehensive understanding shortly.
Anatomy of a subglacial “deforming bed” beneath a Late Palaeozoic glacier in Namibia
Authors: Le Heron Daniel , Wohlschlägl Ricarda , Mejías-Osorio Paulina , Kettler Christoph , Nduutepo Andreas
Published: March 2024

Namibia is remarkable in terms of its network of 300-million-year-old fjords, cut by Gondwanan glaciers at high palaeolatitudes during the Late Palaeozoic Ice Age. A classic suite of structures is preserved on Proterozoic bedrock, including striations, roches moutonnées and other subglacial features within many of these palaeovalleys. Some palaeovalleys are plastered with comparatively thin diamictites (a few metres) of presumed subglacial origin, in turn capped by paraglacial to postglacial delta successions (tens of metres). Close examination of deposits in the Otjihaa valley reveals an architecture that shows departure from this trend. There, boulder-bearing diamictites pass laterally into highly contorted heterolithic successions comprising folded and faulted sandstones, siltstones and shales. Aerial imagery from UAVs in tandem with traditional field observations permits mapping of (i) highly asymmetric fold structures (tens of metre-scale), (ii) ball and pillow structures, (iii) the orientation of the long-axis of boulders together with (iv) striation orientations, (v) pervasive lineations and (vi) shear bands in sandstone. Collectively, this assemblage of structures points towards subglacial deformation, and hence an origin as a “deforming bed” beneath a glacier. In this paper, we present a synoptic profile along the palaeo-fjord axis charting the architecture of these deposits. The lateral and vertical distribution of different deformation products, together with their orientations, is argued to allow subglacial stresses to be reconstructed, and hence ice flow dynamics to be better understood. In studies of deep time glaciations, the discovery of a significant “deforming bed” cradled within a bedrock palaeovalley is a new development, interrupting the classic deglaciation-transgression sequence established by previous work. 
Sensitivity study of WRF and RegCM models to different physics schemes during two extreme weather events over Europe 
Authors: Verma Shruti , Villalba-Pradas Anahí , Halenka Tomáš , Machado Crespo Natália , Karlický Jan , Huszár Peter
Published: March 2024

Urban environments not only affect the warming rate over cities but also induce changes in other relevant meteorological variables. One of the main goals of the FPS URB-RCC Project and the Horizont research project Impetus4Change (I4C) is to improve our understanding of the impact of urban areas on the regional climate and vice versa, as well as to identify how urban parameterizations impact the regional-to-local scale processes, and, in general to improve the quality, accessibility and usability of near-term climate information. To evaluate these impacts in the long term, first we need to find the “best” configuration possible for our models and then validate them against high-quality observations.  

 

In this study, we present preliminary results from a series of sensitivity tests focusing on two extreme events occurred in 2020 over Paris, with the aim of finding the “best” model configuration. Simulations were performed using two models (WRF and RegCM5) with a double-nested domain at 12 and 3 km resolution, respectively, centered over Paris. Urban schemes of different complexity are used in WRF (in particular, we use the bulk, SLUCM and BEP+BEM urban schemes) as well as different physics options in both models. In the case of the RegCM5 model, different cores were tested too. The results show that relevant meteorological variables, such as temperature and precipitation, depend on the urban canopy scheme used as well as on the microphysics and planetary boundary layer schemes. Moreover, the effects of dynamical core in RegCM5 are more prominent than explicit moisture schemes for simulation of heat wave events. 
Simulating air quality management policies in Europe with the SHERPA-Cloud model
Authors: Pisoni Enrico , De Marchi Davide , Di Taranto Alberto , Bessagnet Bertrand , Zauli Sajani Stefano , De Meij Alexander , Monforti-Ferrario Fabio
Published: March 2024

This presentation deals with the SHERPA-Cloud online simplified air quality model. Based on a previous version of the offline SHERPA model, this new online model can be used a) to simulate the impact of emission reduction scenarios on air quality, and b) to understand the main (sectoral and geographical) sources impacting air pollution for a given EU region or city.From a methodological point of view, the model implements a set of SRR - source-receptor relationships (meta-model of the EMEP Chemistry Transport Model) and it is able to simulate the impact of an air policy in few seconds, with a good level of accuracy.From the IT infrastructure and technologies points of view, the SHERPA-Cloud is based on an on-premise cloud system called BDAP (Big Data Analytics Platform) which provides a JupyterLab service and the tools to create dashboards from Jupyter notebooks using the Voilà plugin.Thanks to its simple and easy-to-use interface, SHERPA-Cloud allows for various types of users, policy makers, citizens, NGOs and industries, to quickly test how air quality can changes when implementing new emission reduction strategies, and to focus efforts to the most efficient actions to improve air quality, in terms of geographical and sectoral policies. SHERPA-Cloud can also be used to support cities when dealing with the ‘Covenant of Mayor’ or the ‘Climate Neutral Cities’ initiatives, to evaluate the side-effects on air quality of climate mitigation measures.The SHERPA-Cloud web application is available at this link: https://jeodpp.jrc.ec.europa.eu/eu/dashboard/voila/render/SHERPA/Sherpa.ipynb. The access to the application requires first a EUlogin account, the European Commission’s user authentication service.
New Open-Loop Tracking Command (OLTC) platform : AltiGIS
Authors: Wery Florian , Boy François , Le Gac Sophie , Homerin Alexandre , Boussaroque Malik , Aublanc Jeremie
Published: March 2024

Over the last decade, there has been a burgeoning interest in altimetry measurements for inland waters, with a focus on comprehensive studies of water levels in lakes, reservoirs, and rivers on a global scale. This research is crucial for the hydrology community to accurately assess the Earth's freshwater resources. Significant advancements have been achieved in enhancing altimeters' capacity to obtain high-quality measurements over inland waters.The Open-Loop Tracking Command (OLTC) stands out as a noteworthy development in altimeter on-board tracking modes. Its effectiveness has been proven through successful implementation in previous missions and is now designated as the operational mode for current missions, including Sentinel-3, Sentinel-6, and SWOT nadir.Over the past decade, OLTC data, crucial in tracking inland water bodies from radar altimetry satellites, has undergone substantial refinement. Originally developed for Jason-2, new missions as Jason-3, Sentinel-3A&B, Sentinel-3B, Sentinel-6, SWOT nadir have been incorporated. Algorithms and procedures to compute location and elevation of inland waters targets (rivers, lakes, reservoirs) have also been largely improved. The number of hydrological targets has increased fivefold with an acquisition success rate which is now close to 90%. Presently, each mission tracks between 30,000 to 70,000 hydrological targets.Despite modifications to a software developed 15 years ago, ongoing advancements and the necessity for covering  land ice surfaces in preparation of upcoming S3C&D missionshave prompted the development of a new software. In addition, the availability of new input data provided by the SWOT mission (water mask and elevation) required also to revise the current software to make their usage efficient. Work is currently underway to establish a new OLTC platform, named AltiGIS. The platform is designed with three primary objectives: facilitate collaboration, enhance data generation validity, and broaden dissemination through the use of DevOps practices. The presentation aims at harvesting new user needs but will also cover both the undergoing software development and roadmap.
Modelled ice sheet sensitivity to basal friction parameterizations is controlled by the amount of buttressing
Authors: van den Akker Tim , Lipscomb William H. , Leguy Gunter R. , van de Berg Willem Jan , van de Wal Roderik S.W.
Published: March 2024

The basal friction parameterization is often mentioned as key source of uncertainty when using ice sheet models to project future evolution of the ice sheet. Previous work suggests that parameterizations with an exponential relationship between friction and basal velocity (power laws) predict lower sea level rise than ‘Coulomb-style’ friction laws. For Coulomb laws, the basal friction asymptotes for high velocities and is effectively independent of velocity for fast-flowing ice. We use the Community Ice Sheet Model (CISM) for two kinds of simulations: one with present-day climate forcing, including sub-shelf ocean temperatures kept constant and one with 1-degree ocean warming in the Ross Sea, both matching the current rate of ice thickness changes. In the constant scenario, Thwaites Glacier and Pine Island Glacier collapse, creating a huge, laterally bounded ice shelf. In the scenario with Ross Sea warming, a large part of the Ross Ice Shelf disappears, allowing Siple Coast glaciers to flow freely into the ocean. For Thwaites and Pine Island Glaciers, there are competing processes causing increases or decreases in ice flux across the grounding line, ice shelf thickness, buttressing, and ice velocities, once the glaciers are collapsing. These processes work in the opposite direction of the differences caused by choosing different basal friction parameterizations. Therefore, in our model runs, the choice of basal friction parameterization has little effect on the collapse of Thwaites and Pine Island glacier. In the unbuttressed Siple Coast case, we confirm earlier results: Coulomb friction leads to more ice mass loss and sea level rise. We conclude that unbuttressed glaciers are more sensitive to the choice of basal friction parameterizations than are heavily buttressed glaciers, and that the presence of a large buttressing ice shelf decreases the sensitivity of glacier dynamics to different basal friction parameterizations. 
Self-supervised learning for the exploration of continuous seismic records at the Fani Maoré submarine volcano (Mayotte)
Authors: Hibert Clément , Rimpot Joachim , Retailleau Lise , Saurel Jean-Marie , Malet Jean-Philippe , Forestier Germain , Weber Jonathan , Stangeland Tord S. , Turquet Antoine , Pelleau Pascal
Published: March 2024

Continuous seismological observations provide valuable information to deepen our understanding of processes occurring in both aerial and submarine volcanoes. However, the wealth of the seismicity recorded near volcanoes makes exhaustive exploration of these seismological chronicles very complex and time-consuming. In this study, we present a systematic analysis of two months of seismological records using a self-supervised learning (SSL) approach for the unsupervised clustering of continuous seismic data acquired by ocean bottom seismometers deployed in the vicinity of the Fani Maoré volcano (Mayotte). The proposed clustering process allows the identification of individual seismic events, seismic crisis and tremors that would be challenging to observe using conventional approaches. We show that our approach detects and classifies both known and new events, including two eruptive sequences previously unknown. We also demonstrate the potential of self-supervised methods for the analysis of seismological records, providing a synoptic view and facilitating the discovery of insightful yet rare events. This approach has numerous applications in exploring various seismological datasets, simplifying analysis while making it more comprehensive.
HydroSOS: Knitting local and global hydrological status and outlooks systems together for seamless water resources assessment 
Authors: Facer-Childs Katie , Barker Lucy , Dixon Harry , Jenkins Alan , Mishra Sulagna , Silva Vara Luis Roberto , Berod Dominique , Kim Hwirin , Nelson Jim , Hales Riley , Huber Rachel , Gutierrez Angelica
Published: March 2024

Many hydroclimate services exist across the world at different scales. However, these services all use different categorisation schemes, different presentation styles, and are hosted across countless different websites. The Hydrological Status and Outlook System (HydroSOS) is a World Meteorological Organization initiative uniting, or “knitting”, hydrological status and sub-seasonal to seasonal outlooks products across scales in a consistent framework, weaving seamless services for water resources assessment.HydroSOS extends beyond uniting existing services, also building capacity where services do not currently exist. It provides essential guidance and frameworks enabling the assessment of hydrological status for different variables. Additionally, HydroSOS is reviewing methods of producing useful hydrological forecasts in data sparse regions using statistical methods, or hydrological models, with and without real-time meteorological forecast inputs. Working in collaboration with the GEOGloWS initiative, global scale services are being improved with bias correction using machine learning and local scale data.This fiber-art poster presents the HydroSOS initiative, its progress, and calls for ideas and collaborations on how we can knit hydroclimate services together to make the best fabric for water resources management.
Distributed Acoustic Sensing automated classifiers design via transfer learning for seismology
Authors: Donnadille Mathieu , Turquet Antoine , Hibert Clément , Richard Cédric
Published: March 2024

For a decade, Distributed Acoustic Sensing (DAS) has become an exciting new tool for research in geophysics. However, the vast amount of data produced by hundreds of virtual sensors presents a challenge, and the lack of labeled data hampers the training of new automated classifiers based on machine learning methods from scratch. Automatic classifiers are essential tools for labeling observations across large, complex, and continuous datasets. They are commonly used in seismology to classify all the geophysical events recorded by seismic stations with a high degree of accuracy. Transfer learning is a machine learning technique where a model trained on one task is repurposed on a second related task. This method is particularly beneficial as it allows for the reuse of pre-existing, labeled datasets, significantly reducing the need for new data collection and annotation. This approach is a promising way to create efficient DAS classifiers without requiring a lot of resources. We built three different classifiers: the first classifies events based on their location, distinguishing local earthquakes from distant events; the second differentiates anthropogenic events from natural ones, specifically quarry blasts from earthquakes; and the third is capable of identifying all three types of events - local earthquakes, distant events, and anthropogenic quarry blasts - simultaneously. We used random forest models to train our classifiers using a labeled dataset of 14345 seismometer signals from the NOA network made for seismological research and nuclear monitoring. We studied the transferability of those classifiers to DAS data from a new NORSAR facility called NORFOX. This infrastructure consists of 8 km of cables located in Norway with a sampling frequency of 100Hz. Its multidirectional cable configuration makes it ideal for seismological surveys. We built a small test dataset of 543 signals using 20 channels equally distributed along the array. Our approach succeeded in reaching F1 score thresholds above 76%. We also showed, by fine-tuning feature selection according to their correlations between the seismic and DAS domains, that these results can be improved. In this way, we were able to increase the scores of our models from 5.89% to 11.36%. Several transfer learning approaches were also explored and discussed. Those encouraging results highlight the potential of a transfer learning approach to build new DAS classifiers. By leveraging historical seismometer catalogs, this approach facilitates the creation of DAS classifiers, thereby saving substantial time and avoiding the need for creating specialized datasets exclusively for DAS. Several strategies for improving score thresholds for future classifiers based on these transfer learning methods can be derived.
Generalising Tree–Level Sap Flow Across the European Continent using LSTMs
Authors: Loritz Ralf , Wu Chen Huan , Klotz Daniel , Gauch Martin , Kratzert Frederik , Bassiouni Maoya
Published: March 2024

In this presentation, we explore the application of Long Short-Term Memory networks (LSTMs) to predict hourly tree-level sap flow across Europe, utilizing the comprehensive SAPFLUXNET database. This study emphasizes the potential of deep learning in estimating transpiration and understanding forest water use dynamics and plant-climate interactions. By developing LSTM models with varied training sets, we assess their capability to perform in previously unencountered conditions. Our research reveals that these models achieve an average Kling-Gupta Efficiency of 0.77 when trained on 50% of the time series across all forest stands, and 0.52 for models trained on 50% of the forest stands without prior gauging. These continental-scale models not only meet but often exceed the performance of specialized and baseline models across all tree genera and forest types. In this submission, we will discuss the methodologies employed, the challenges faced, and the insights gained from this research. The presentation will also highlight the broader implications of this study for ecohydrological investigations, particularly the enhanced capacity of deep learning models to generalize sap flow data, thereby improving our understanding of ecohydrology from individual trees to a continental scale.
A 10-Year climatology of hail in France: towards an estimate of the hail hazard
Authors: Trevisani Maxime
Published: March 2024

According to France Assureur (French insurance unions), 2022 hail damage in France is estimated at more than €6.5 billion, i.e. more than half of all climate-related damage in 2022, or 60% of all hail damage accumulated between 2013 and 2021. This record-breaking year is in line with the growing concern about hail in France among public and private stakeholders. Despite its increasing impact on society the hail hazard in France remains largely unknown or under investigated at the national level, with a single 20x20 km hail risk map produced up in 1998 by F. Vinet using economic data (insurance) and measurements (hailpad). Hail hazard is poorly studied in France due to the great difficulty of observing or modelling hailfall, which are highly localised in time and space. The emergence of social networks since the late 2000s has led to a proliferation of potential hail observers across France. These new data, combined with insurance data, make it possible to study hail at a level of resolution never seen before in France.The main objectives of our study are therefore to update the geographical assessment of the hail hazard in France, while improving the granularity of the existing geographical hail assessment. To this end we studied the hail hazard in terms of frequency and maximum diameter at the municipal level (average 16 km²), using hail reports (Keraunos, European Sever Weather Database) and insurance data (Generali France, around 5% market share) over the period 2013-2022.Our study thus provides a resolution 25 times finer than that of Vinet and reveals a southwest - northeast axis dividing France into two parts: the southern part is heavily affected by hail while the northern part is less affected. It also highlights 3 main geographical areas with the highest hail hazard. The Massif Central stands out as the main hail-prone area in France, with a notable maximum in its northern part. The Bordeaux-Paris axis comes second, with a local maximum in the southwest Atlantic coast. In third place comes the Provence-Alpes-Côte d'Azur region, particularly in the Pre-Alps and Pre-Atlantic massifs. There also seems to be a correlation between orography and areas of high hail hazard, particularly noticeable in the Massif Central and Pre-Alps regions, but this assumption needs to be further investigated.
Unravelling the impact of subpolar gyre variability on climate extremes and variability:  Insights from an ensemble atmospheric model study
Authors: Karami Mehdi Pasha , Koenigk Torben , Schenk Frederik
Published: March 2024

The North Atlantic Subpolar Gyre (SPG) plays an important role in climate predictability and influences climate variability due to its complex coupling with the atmospheric circulation in the North Atlantic and the Atlantic Meridional Overturning Circulation (AMOC). In this study, we investigate the impact of sea surface temperature (SST) variability in the SPG on atmospheric circulation patterns and climate extremes. We use the EC-Earth3 model (T255~80 km) and perform four sets of AMIP-type ensemble experiments with four different prescribed SST anomalies, each with 10 members and spanning 35 years from 1980 to 2014. The experimental design allows the climatic impact of SPG SST variability to be isolated from other global SST modes. Our results show that SPG SST anomalies directly influence atmospheric circulation between 30-75°N, causing zonally oriented wave-like anomalies. Notably, a warm SST anomaly in the subpolar gyre causes strong low-pressure anomalies over the North Atlantic and North Pacific, leading to warming of regions mainly between 45-60°N and cooling of regions mainly between 60-75°N. We find that the anomalous temperatures are particularly pronounced over the North American continent. We also investigate the indirect effects of SPG variability through its synergy with the North Atlantic and North Pacific SSTs, as well as the atmospheric teleconnections and extreme events associated with SPG variability. The results underline the importance of the SPG for the atmospheric circulation, the teleconnections, the regional climate and the extreme events.
Towards a better understanding of ENSO diversity: a paleoclimate perspective
Authors: Abdelkader Di Carlo Isma , Braconnot Pascale , Carré Matthieu , Elliot Mary , Marti Olivier
Published: March 2024

El Niño-Southern Oscillation (ENSO) events are hard to put in one category because they differ in intensity, spatial pattern, and temporal evolution. Studies have characterized events into two main categories: central Pacific (CP) and eastern Pacific (EP) events. The indicators used to compute EP and CP events are varied, from area-averaged regions to Empirical Orthogonal Function (EOF) analysis. In the recent climatic period, they all show similar results. However, future projections show differing results when using two different methods of computing EP and CP events. Since the observational period is too short, we use paleoclimate reconstructions, which provide unique and quantitative measures of past climate changes over long time scales. We will first synthesize previous studies and discuss how they have used paleoclimate modeling and/or data to provide clues into how ENSO diversity may have been shaped in past climates. Our results indicate that many apparent inconsistencies in future projection studies are due to misleading use of ENSO diversity indicators and that investigating ENSO diversity with a climate change perspective requires assessing both changes in the climate mean state (annual mean and seasonality) and changes in variability. 
Historic changes and future projections of surface water temperature in Lake Titicaca
Authors: Dinh Dieu Anh , Woolway R. Iestyn , Jennings Eleanor , McCarthy Valerie
Published: March 2024

Lake Surface Water Temperature (LSWT) plays a crucial role in aquatic ecosystems, influencing lake physical and biogeochemical processes. LSWT serves as a critical measure of the effects of climate change on lakes. Therefore, analysing LSWT variability is vital for understanding lake response to a warming climate. Lake Titicaca, the largest lake in South America and one of the highest lakes in the world, served as an important water resource in Peru-Bolivia. However, Lake Titicaca is also affected by climate change and anthropogenic activities. In this study, we investigate the historical and future change in LSWT of Lake Titicaca at different timescales (diel, seasonal, and annual). This research used the Global LAke Surface water Temperature (GLAST) dataset for the historical period of 1981-2020 and the future projected period of 2021-2099 for SWT of Lake Titicaca. Model projections were validated with LSWT from the ESA CCI Lakes dataset (2000-2020). The results showed that (1) LSWT has an increasing trend of  +0.16 K decade-1 annually and of +0.01 K decade-1 in diel range from 1981 to 2020, (2) LSWT is expected to warm at a rate of 1-4 K under future climate change scenarios. This finding gives an insight into LSWT and diel temperature range in Lake Titicaca, and LSWT changes in historical and future under climate change. This study could be beneficial for water resource managers and decision-makers to adapt and mitigate the climate change impacts.
Multidisciplinary geophysical approach to investigate the deeper portion of the Central Apennines (Italy)
Authors: Tiberti Mara Monica , Maesano Francesco Emanuele , Buttinelli Mauro , De Gori Pasquale , Ferri Fernando , Minelli Liliana , Di Nezza Maria , D'Ambrogi Chiara
Published: March 2024

In the Central Apennines (Italy), the project RETRACE-3D provided a reliable 3D model of the crust in the area affected by the 2016-17 Amatrice-Visso-Norcia seismic sequence, highlighting that the coseismic rupture at the surface can involve old inherited normal faults while the seismogenic sources lay at depth, possibly reactivating and inverting previous thrust faults, as in the case of the Mw 6.5 Norcia earthquake (30 october 2016). Here we present a 2D gravity model across the Central Apennines, spanning from the Tyrrhenian coast to the Adriatic Sea, aimed at completing and verifying the crustal geometries resulting from the 3D model itself. The cross-section was built integrating different types of data, such as surface geology, hydrocarbon wells, seismic lines, and results from receiver function analysis. It was then checked against gravity anomalies and the velocity distribution from Local Earthquake Tomography (LET), adding further details, and, finally, against seismicity recorded during the 2016-2017 sequence. The results substantiate the reliability of the geometries proposed in the RETRACE 3D model, as they fit well, except for some local misfits, with the other independent data, such as the Bouguer anomalies and the velocity distribution from LET. Furthermore, the integration of different types of data allowed us to describe in detail the structural setting of the Apennine chain also in the surroundings of the RETRACE study area, where the cross-section length exceeds the 3D model, and to add some new elements at seismogenic depths, that exceed those typical of hydrocarbon exploration. In particular, we were able to investigate the nature of the basement top and its relationship with seismotectonics.
Numerical modelling of flood hazard mitigation strategies: the case of the Baganza River after the 2014 inundation of the city of Parma
Authors: Ferrari Alessia , Vacondio Renato , Mignosa Paolo
Published: March 2024

Urban flood risk mitigation is a paramount priority given the increasing frequency of flood events, which have become predominant natural disasters in recent decades. Over half of the global populace now resides in urbanized areas, amplifying the vulnerability to such events that is further accentuated by climatic shifts and rapid urban sprawl. In addressing these challenges, sophisticated flood risk management strategies often integrate advanced numerical models for precise hydrological assessments. These models can support e.g. urban planning, emergency response preparedness and the design of structural measures. In the present work, the Baganza River in the city of Parma (Northern Italy) is investigated with particular emphasis on recent modifications that have been designed with outcomes deriving from a computationally efficient parallel 2D numerical model solving the Shallow Water Equations (SWEs).On October 2014, a severe flood event occurring on the Baganza River caused the inundation of the southwestern part of the city of Parma. Since the urban river reach showed limitations in the propagation of the flood wave, a comprehensive re-evaluation of the river's hydraulic conveyance capacities was required. Thus, in 2015, hydraulic authorities started designing and realizing several modifications along this river reach, including levee modification and removal, in order to increase its conveyance. With the aim of assessing the effectiveness of these strategies, the PARFLOOD numerical model, which solves the 2D-SWEs on a finite volume scheme and ensures high computational efficiency due to its parallel implementation on GPU, was adopted. The model was initially calibrated and adopted to simulate the 2014 flood event. Thereafter, leveraging a refined spatial resolution and incorporating detailed urban topographies, the model delineated residual flood hazard maps, facilitating evidence-based mitigation strategy refinements.Once the most promising strategies were outlined and implemented over these last ten years, a new high-resolution Digital Terrain Model (DTM) deriving from a LiDAR survey was provided in 2023. By simulating the same synthetic discharge hydrograph, e.g. with a return period of 100 and 200 years, using both the 2014 DTM and the 2023 one, it clearly emerged that the current asset strongly reduces the residual flood hazard in these districts of the city of Parma, both in terms of flood extent and magnitude.
Renewable Electric Energy Storage Systems by Storage Spheres on the Seabed of Deep Lakes or Oceans
Authors: Schmidt-Boecking Horst , Luther Gerhard , Düren Michael
Published: March 2024

A new underwater pumped storage hydropower concept (U.PSH) is described that can store electric energy by using the high water pressure on the seabed or in deep lakes to accomplish the energy transition from fossil to renewable sources. Conventional PSH basically consists of two storage reservoirs (upper and lower lake) at different topographical heights. It needs special topographic conditions, which are only limitedly available in mountain regions. Furthermore, due to the lack of acceptance and the environmental impact, new conventional PSH projects are very unlikely to be built in larger numbers in Europe in the near future. The presented solution solves these issues by placing the storage system on the seabed, thus having other geographical requirements. It operates as follows: in contrast to well-known conventional PSH plants, which use two separated water reservoirs of different heights, the U.PSH concept uses the static pressure of the water column in deep waters by installing a hollow concrete sphere in deep water. Storage of electricity is achieved by using a reversible pump in the hollow sphere. Upon opening a valve, water flows into the sphere, driving a turbine/generator, thereby discharging the storage device. In order to re-charge, the water is pumped out of the sphere against the pressure of the surrounding water. The power and energy, respectively, are proportional to the surrounding water pressure at the seabed. The amount of energy stored depends on the water depth and the volume of the spheres. The spheres need a cable connection to the shore or to a close-by floating transformer station (e.g., an offshore wind plant). No other connections such as pipes are needed. The functional principle of this energy storage technology, its state of the art, its storage capacity and the shape and size of the required spheres are discussed in this paper. 
Investigating typical patterns for co-occurring heatwaves
Authors: Galfi Vera Melinda
Published: March 2024

The typicality of extreme weather and climate events denotes their property to exhibit similarities in spatial patterns, temporal evolution, and underlying physical processes, with this resemblance intensifying as events become more extreme. Recent findings highlight that highly intense heatwaves, defined as prolonged local temperature anomalies, are consistently associated with specific large-scale circulation patterns. This suggests that there is a typical way to realise very extreme local temperature anomalies. Here, I will explore typical ways for the emergence of extremely intense hemispheric anomalies, characterized by notably large zonal variations in air temperature or geopotential height. This investigation aims to shed light on preferred atmospheric configurations leading to the simultaneous occurrence of heatwaves on a hemispheric scale.
 A Fundamental Climate Data Record Derived fromAMSR-E, MWRI, and AMSR2 
Authors: Wu Banghai , Wang Yu
Published: March 2024

Fundamental climate data records (FCDRs) play a vital role in monitoring climate change. In this article, we develop a spaceborne passive microwave-based FCDR byrecalibrating the Advanced Microwave Scanning Radiometerfor Earth Observing System (AMSR-E) on the Aqua satellite,the microwave radiometer imager (MWRI) onboard the FengYun-3B (FY3B) satellite, and the Advanced Microwave ScanningRadiometer-2 (AMSR2) onboard the JAXA’s Global ChangeObservation Mission first-Water (GCOM-W1) satellite. Beforerecalibration, it is found that AMSR-E and AMSR2 observations are stable over time, but MWRI drifted colder beforeMay 2015 and had nonnegligible errors in geolocation formost channels. In addition, intersensor differences of brightnesstemperatures (TBs) are as large as 5–10 K. To improve dataconsistency and continuity, several intersensor calibration methods are applied by using AMSR2 as a reference while usingMWRI to bridge the data gap between AMSR2 and AMSRE. The double difference method is used to provide intersensordifference time series for correcting calibration biases, such asscene temperature-dependent bias, solar-heating-induced bias,and systematic constant bias. Hardware differences betweensensors are corrected using principal component analysis. Afterrecalibration, the mean biases of both MWRI and AMSR-Eare less than 0.3 K compared to the AMSR2 reference andtheir standard deviations are less than 1 K for all channels.Under oceanic rain-free conditions, the TB biases are less than0.2 K for all channels and no significant relative bias driftswere found between sensors for overlapping observations. Thesestatistics suggest that the consistency between these instrumentswas significantly improved and the derived FCDR could be usefulto obtain long-term water cycle-related variables for climateresearch. 
 The eight-year solar cycle during the Maunder minimum 
Authors: Yan Limei , He Fei , Yue Xinan , Wei Yong , Wang Yuqi , Chen Si , Fan Kai , Tian Hui , He Jiansen , Zong Qiugang , Xia Lidong
Published: March 2024

The Maunder minimum (1645–1715 AD) is a representative grand solar minimum with highly depressed sunspot activity and coincident with the “Little Ice Age” on the Earth. Owing to the limited data quality of the currently used solar activity proxies, the cyclic solar activity variations during the Maunder minimum still need to be explored. By analyzing the red equatorial aurorae recorded in Korean historical books in the vicinity of a low-intensity paleo-West Pacific geomagnetic anomaly, we find clear evidence of an eight-year solar cycle during the Maunder minimum. This result provides a new data source on solar activity and a key constraint to theoretical solar dynamo models. It helps understand the generation mechanism of grand solar minima and the solar-terrestrial relations during the Maunder minimum.