bluuebunny/crossref_metadata_2025 huggingface dataset:
Shear weakening with increasing temperature: effect of clay fraction in low plasticity soils from the Melamchi catchment in Nepal
Authors: Dhakal Om Prasad , Loche Marco , Scaringi Gianvito
Published: March 2024

The shear strength is a fundamental mechanical parameter that controls the occurrence and propagation of landslides. In pure clays, this parameter is temperature-dependent according to the clay’s mineral composition and hydro-mechanical boundary conditions. Landslide soils are typically heterogeneous mixtures with a variable content of clay minerals. Particularly for low-plasticity soils, the impact of changes in temperature on the mechanical response remains to be determined, and little can be said about possible macroscopic alterations of slope stability or landslide dynamics.In this study, we conducted ring-shear tests using natural soils from the Melamchi catchment in central Nepal, which suffered widespread instabilities and rainfall-induced debris flows. We performed experiments under typical landslide stress levels (50-150 kPa) in water-saturated conditions and under a constant rate of shearing (0.1 mm/min). We controlled the temperature during testing and performed a heating-cooling cycle (20-50-20 °C) only after attaining the residual shear condition. We prepared multiple samples from the same soil by retaining its finest portion under different cutoff grain sizes (0.125-0.020 mm) to evaluate the fine fraction's role in the thermo-shear response.As expected, we observed a decrease in shear strength with the clay fraction increasing. Samples with a coarser cutoff (and hence a lower clay fraction) did not exhibit any change in shear strength during the heating-cooling cycle. However, as the clay fraction increased, a heating-induced weakening emerged, corresponding to up to a 1° difference in friction angle in the samples with a 0.020 mm cutoff. In the specific case study, this weakening may be minor and will not affect evaluations of slope stability in simple limit equilibrium analyses, especially in the absence of explicitly accounting for spatial heterogeneities in soil properties and boundary conditions. Nevertheless, incorporating this effect into physically-based models, either entailing advanced soil constitutive models or equations for surface flows (both of which can include additional temperature-dependent parameters), may provide useful insights into the complexity of thermo-hydro-mechanical responses and their effects on landslides at the local and regional scales.
Fluid-induced failure and sliding of a gouge-filled fault zone: Hysteresis, creep, delay and shear-strengthening.
Authors: Aharonov Einat , Sarma Pritom , Toussaint Renaud , Parez Stanislav
Published: March 2024

Many previous studies have explored the role of granular media in controlling friction of faults. A gap exists though in understanding the failure process and sliding of a fluid-saturated fault gouge. Here we use a coupled 2D DEM-fluid code to simulate fault-gouge as a layer of grains, sheared by a constant stress boundary. We explore and compare two scenarios: 1) a dry granular layer, in which shear stress on the top wall is incrementally increased, or 2) a fluid-saturated granular layer, into which fluid is injected, so that fluid pressure is incrementally increased. Once the applied stress/pressure is high enough, the layer fails and starts accelerating, until it reaches a steady-state sliding rate (determined by the layers’ velocity-strengthening friction). We next incrementally step-down the shear stress or fluid pressure. Consequently, the slip-rate is observed to slow down linearly with decreasing stress/pore-pressure, until the layer finally stops, at a stress/pressure lower than that required to initiate the failure. Both the dry and fluid-saturated granular systems exhibit two main behaviors: 1) velocity-strengthening friction, following the mu(I) rheology, 2) a hysteresis effect between friction and velocity, porosity and grain coordination numbers. The hysteresis and strain-rate dependence agree with previous experimental, numerical and theoretical results in dry granular media, yet our work suggests these behaviors extend to fluid-filled granular media. We theoretically predict the transient and steady-state observations for dry and fluid-saturated layers, using the mu(I) friction rheology with an added component of hysteresis. Importantly, we show that fluid-filled faults exhibit a process which is absent in dry systems: fluid-injected layers may exhibit failure delay, with some time passing between pressure rise and failure. We link this delay to pre-failure creeping dilative strain, interspersed by small dilative slip events. Our numerical and analytical results may explain: (i) field measurements of fault creep triggered by fluid pressure rise (e.g. via injection), (ii) fault motion which is triggered by fluid-injection but continues even after fluid pressure returns to its pre-injection level. (iii) observed delay prior to failure in fluid-injection experiments.
Can energy and environmental taxation be progressive in the EU?
Authors: García-Muros Xaquín , Alonso-Epelde Eva , González-Eguino Mikel , Rodríguez-Zúñiga Alejandro
Published: March 2024

The success of the targets established in the European Green Deal depends on the correct design of ambitious policies that utilize all available instruments, including energy and environmental taxation. In the “Fit for 55” package, the EC proposed a deep reform of the Energy Taxation Directive (New ETD) to update the current taxation and align it with current environmental goals. However, due to the war in Ukraine, the energy crisis, and the risk of regressive effects the current proposal of the EC is stalled. Therefore, this analysis seeks to provide new evidence from a microsimulation model developed to assess the direct, overnight distributional impacts of the proposed new ETD reform on households. Our aim is to explore whether the proposed EU-level polluter pays instruments can be designed to achieve progressive distributional impacts, to identify policy options that ensure they strengthen social justice without undermining it, and thereby remove social barriers. Moreover, we explore a dimension often underrepresented in distributional analyses, namely gender. Our results indicate that, with the correct design from the outset, environmental tax reforms can be progressive and not increase current inequalities between and within Member States of the EU, including those related to gender.
Improved Mapping of Perennial Crop Types Based on Patterns of Intra-Annual Variation in Land Surface Components
Authors: Gao Xiang , Hu Qiyuan , Lun Fei , Sun Danfeng
Published: March 2024

Perennial crops hold significant importance in global agricultural markets, local agricultural economies, poverty reduction, and biodiversity conservation. Accurate spatial distribution data of different perennial crops are crucial for local agricultural management, crop yield prediction, and sustainable agricultural development. However, precisely obtaining the spatial distribution of different perennial crops using remote sensing data, especially in regions with complex cropping patterns, remains a challenge. This study, focusing on Yantai City, China, and three counties in California, USA, aims to develop a method suitable for both smallholder and intensive production systems. On the Google Earth Engine (GEE) platform, we applied linear spectral mixture analysis (LSMA) to transform Sentinel-2 time-series data (2020-2022) from the original spectral space into a unified endmember space, including photosynthetic vegetation, non-photosynthetic vegetation, soil, and shadow, thereby characterizing the time-series land surface component information. Subsequently, based on the time-series endmembers data, we quantified seven sets of harmonic features and five phenological features. Relative phases were employed as phase indicators for the harmonic features. These seven harmonic features represent the intra-annual patterns of land surface component changes and inter-component interactions, while the phenological features quantify the timing of phenological events. Our findings reveal significant variations in the intra-annual patterns of land surface component changes among different perennial crops, attributable to differences in phenology and phenology-associated human management. Building on this, the study achieved precise mapping of different perennial crops, even in areas with complex cropping patterns. The overall classification accuracy for perennial crops in Yantai City and the three counties in California was 90.3% and 94.8%, respectively, with Kappa coefficients of 89.2% and 93.9%. Utilizing intra-annual time-series land surface component information for extracting the spatial distribution of perennial crops demonstrated advantages over traditional optical indices. This work provides a method that is applicable to both smallholder and intensive production systems, enabling precise mapping of perennial crop types. It represents an important step towards achieving large-scale mapping of perennial crop types.
Linking satellite-derived greening trends and field observations in the high-alpine
Authors: Rutzinger Martin , Waymel Mathilde , Kollert Andreas , Mayr Andreas , Hülber Karl , Pauli Harald , Dullinger Stefan
Published: March 2024

An increase in vegetation productivity has been attributed to accelerated warming in different mountain ranges over the last decades by analysis of satellite imagery. Here, we quantify such a greening trend on 767 sampling plots with a high topographic variety in elevation, slope, and aspect in the sub-alpine to nival vegetation belt of Mt. Schrankogel (Tyrol, Austria) over the past four decades by analysing Landsat satellite image time series. We found (i) a good agreement of NDVI with in-situ vegetation cover estimates in a reference year and (ii) a widespread greening trend. Our set of plots has experienced a median greening trend of 0.018 NDVI units per decade, with 98% of the plots showing a positive NDVI trend. These results need to be considered with caution as the detailed analysis of the NDVI time series together with knowledge of the local conditions at the plots reveals potential pitfalls for interpretation. These are related to geomorphological disturbance of soil and vegetation, legacy effects of 20th century glacier retreat, or data scarcity (due to snow and clouds). Nevertheless, our study generally supports the notion that the productivity of cold-limited vegetation has increased which is even detectable from space.
Situation and stresses: a spatial analysis of near-surface drinking water resources in Germany 
Authors: Szillat Kathrin , Stahl Kerstin , Hellwig Jost , Schmit Max
Published: March 2024

Decreasing groundwater recharge and competing water uses challenge drinking water supplies worldwide and noticeably in Germany as well. Groundwater is a significant source of drinking water, making it essential to maintain its quality and quantity. In Germany, about 74% of drinking water originates from groundwater. However, various stress factors significantly affect the quality and quantity of the groundwater resource. The combined effects of climate change and diverse physical and social factors pose a central challenge for current and future drinking water supply. To address this challenge, a good understanding of the varieties of situations needs to support tools and decision-making frameworks to manage groundwater sustainably and ensure resilient drinking water. This study conducts a nationwide spatial analysis of various influencing factors. It focuses primarily on drinking water protection areas used for agriculture, examining their natural and hydro-climatic characteristics and changes, and the nitrate pollution they experience due to agricultural activities. Currently, Germany has around 11270 designated drinking water protection areas, of which 84 % are used for agriculture. We create a unique dataset for them. This spatial dataset quantifies numerous potential characteristics and stress factors for each of the (n) drinking water protection areas. These factors include groundwater recharge rates, drought response times, agricultural usage, nitrate pollution, aquifer type, and more. Applying clustering methods to the n x m matrix data helps to identify typical situations for drinking water supply. By considering three dimensions—drinking water extraction/hydrogeology, nitrate pollution, and drought vulnerability we aim to characterize and depict diverse situations across Germany while determining broader trends. Achieving sustainable drinking water management requires a systematic analysis of the heterogeneous natural, political-regulatory, and agro-economic conditions to identify transferable success factors. Building on this study with model developments in the "LURCH-StressRes" project, we later aim to develop transferable stress tests for the identified typical situations across Germany to inform adaptation and best practices for achieving sustainable nationwide drinking water management.
Metamorphic evolution of eclogite of Kem-Ludy Islands, Early Precambrian Belomorian eclogite province
Authors: Grigorieva Varvara , Perchuk Alexei , Kozlovsky Vasiliy , Sandalov Fedor
Published: March 2024

The Belomorian eclogite province (BEP) of the eastern Fennoscandian Shield (Russia) is one of the oldest eclogite metamorphic complexes on Earth, providing an opportunity to study the most ancient subduction processes. The BEP gained prominence due to the numerous publications on petrology and geochemistry of Archean-Paleoproterozoic HP metamorphic rocks from Gridino, Salma, and Kuru-Vaara areas. Here, we present results from a detailed petrological study of a representative retrograde eclogite sample from a new HP locality in the Kem-Ludy Islands, where eclogites form lenticular bodies and have conformable contacts with country gneisses.The studied retrograde eclogite sample has a massive structure with a fine- to medium-grained granoblastic texture. At least three metamorphic stages were identified in the rock based on the mineral assemblages. The pre-eclogite stage is indicated by epidote inclusions in the cores of garnet porphyroblasts. Garnet, matrix omphacite, and quartz represent peak metamorphism stage. Plagioclase-clinopyroxene symplectites after the omphacite and amphibole-plagioclase kelyphytes around the garnet were formed at the retrograde stage, while peak metamorphism minerals were then replaced to different extents by secondary amphibole during fluid-rock interaction.The application of garnet-clinopyroxene geothermometer and clinopyroxene-plagioclase-quartz geobarometer assessed peak metamorphic temperature of 625-670°C and minimum pressure of 1.2-1.3 GPa, respectively. The retrograde stage corresponds to conditions of 600-725°C and 0.6-0.7 GPa as determined by garnet-amphibole, amphibole-clinopyroxene, amphibole-plagioclase geothermometers, and clinopyroxene-plagioclase-quartz and amphibole-plagioclase geobarometers.The established P-T metamorphic evolution of the retrograde eclogite from Kem-Ludy area differs from most of the eclogites of Gridino and Salma areas by lower pressure at the peak of metamorphism and a lack of decompressional heating up to the UHT granulite facies conditions. Therefore, Kem-Ludy area likely pertains to another tectonic slice than Gridino and Salma areas, where the Neoarchean and Paleoproterozoic ages of HP metamorphism are under debate. Further investigation is needed to clarify the tectonic position of Kem-Ludy area.Financial support of Russian Science Foundation project 23-77-00066.
Incoherent scatter radar measurements of ion-to-neutral collision frequencies and neutral temperatures in the D-region ionosphere
Authors: Thomas Neethal , Kero Antti , Virtanen Ilkka , Nozawa Satonori
Published: March 2024

We have analyzed all the existing European incoherent scatter (EISCAT) radar VHF measurements carried out together with the neutral temperature measurements from LIDAR collocated at Tromsø, Norway. Incoherent scatter radar (ISR) spectral parameters are estimated from the backscattered signal autocorrelation function by fitting the D-region lag profiles (pulse-to-pulse fitting). This study focuses on the ISR spectral width which is a function of the ion-to-neutral collision frequency, neutral temperature, and ion mass. Using the neutral temperatures obtained from LIDAR, we have measured for the first time the ion-to-neutral collision frequency in the mesosphere lower thermosphere (MLT) altitude range (80-100 km) by fitting the ISR spectral width. The model ion-to-neutral collision frequencies estimated using MSIS neutral densities are found to be underestimated on average by 1.5 in comparison to the measurements. Also, the ISR collision frequencies showed large temporal variations caused by neutral density fluctuations, which are absent in the model values. These large-scale neutral density fluctuations which are thought to be caused by atmospheric waves are found to have amplitudes as large as 50% of the background density. This indicates that the ISR spectral width is largely influenced by the neutral density fluctuations. In light of these observations, the inherent limitations of inferring the neutral temperatures from ISR spectral width are studied. This study showcases the challenges of estimating neutral temperatures from ISR spectral width in the MLT altitudes, which is significant in the context of the upcoming EISCAT_3D.
Fusion of geostatistics and machine learning under a stochastic approach for the spatial analysis of groundwater level variations 
Authors: Varouchakis Emmanouil
Published: March 2024

Successful modelling of the groundwater level variations in hydrogeological systems of complex formations considerably depends on spatial and temporal data availability and knowledge of the boundary conditions. Geostatistics plays an important role in model-related data analysis and preparation but has specific limitations when the aquifer system is inhomogeneous. In this research work, we show how the fusion of geostatistics with machine learning can solve some of these problems in complex aquifer systems, mainly when the available dataset is large and randomly distributed in the different aquifer types of the hydrogeological system. Self-Organizing Maps can be applied to identify locally similar input data, to substitute the usually uncertain correlation length of the variogram model that estimates the correlated neighborhood, and then by means of Transgaussian Kriging to estimate the bias-corrected spatial distribution of groundwater level. The proposed methodology was tested on a large dataset of groundwater level data in a complex hydrogeological district, and the results were significantly improved if compared to classical geostatistical approaches.The research project is implemented in the framework of H.F.R.I call “Basic research Financing (Horizontal support of all Sciences)” under the National Recovery and Resilience Plan “Greece 2.0” funded by the European Union – NextGenerationEU (H.F.R.I. Project Number: 16537).
Indigenous Wisdom and Geological Understanding: Exploring Andean Indigenous Perspectives on Geology Through Myths and Legends in Ecuadorian Geoparks. 
Authors: Ona Lisbeth , Rengel Patricia
Published: March 2024

In Ecuador, several tools have been extensively utilized to disseminate the principles of geoheritage and geoconservation, effectively integrating geological aspects with tourism and local development initiatives. Ecuadorian Geoparks such as Imbabura and aspiring ones like Napo Sumaco and Tungurahua Volcano encompass geological sciences and intricately intertwine with cultural essence. Tales and legends from indigenous communities inhabiting these landscapes greatly enhance this integration. These geoparks serve as unique reflections of indigenous perspectives on the formation of the Earth. We aim to explore how geosciences and ethnohistory within these geoparks have established intergenerational connections and facilitated geologic communication with the public.
The indigenous people of the Ecuadorian Andes maintain a profound spiritual connection with nature, deeply rooted in their language, Runa Shimi, which surpasses mere communication. This Andean indigenous worldview recognizes the interconnectedness between God (Wiraqucha), nature (Pachamama), and humans (Runas), emphasizing mutual respect. Their belief system acknowledges elements like rivers, mountains, and stars as lifeless entities and manifestations of Pachamama's essence. This worldview advocates maintaining harmony between humans and nature, rooted in their culture, social order, and values, evident in ceremonies, music, and rituals. It illustrates the Runas' commitment to upholding solidarity and respect as part of their cultural identity while living with volcanoes.
Embracing the essence of Runa Shimi, myths, and legends play a fundamental role in understanding the intricate ties between humans and nature. Narratives such as the legend of Mama Cotacachi recount the Earth's transformations through thunder and lightning, symbolizing geological events. While these stories may not entirely align with scientific explanations, they offer insights into natural phenomena. Current scientific knowledge allows for geological interpretations, explaining landscapes shaped by seismic activity, winds, and tectonic forces mentioned in the legends.
This interdisciplinary approach emphasizes the potential for collaboration between geosciences and humanities. It showcases harmony between indigenous beliefs and geological knowledge, demonstrating that both disciplines share more interfaces than boundaries. In addition, it encourages dialogue between seemingly distinct disciplines, promoting openness to new perspectives and facilitating a more holistic understanding of the relationship between humans and their natural environment within the context of Ecuadorian geoparks.
Sub-field detection of cereal yield losses and its causes using Sentinel-2 time series and weather data
Authors: Duan Keke , Vrieling Anton , Schlund Michael , Nidumolu Uday Bhaskar , Ratcliff Christina , Collings Simon , Nelson Andrew
Published: March 2024

Weather extremes severely affect agricultural production and threaten food security worldwide. Throughout the growing season, crops can experience various degrees of weather stress whereby multiple stressors could occur simultaneously or intermittently. For large spatial extents, it is difficult to estimate actual crop damage merely through field experiments or crop models. Remote sensing can help to detect crop damage and estimate lost yield due to weather extremes over large spatial extents, but current RS-based studies usually focus on a single stress or event. We propose a novel scalable method to predict in-season yield losses at the sub-field level and attribute these losses to different weather extremes. To assess our method’s potential, we conducted a proof-of-concept case study on winter cereal paddocks in South Australia using data from 2017 to 2022. To detect crop growth anomalies throughout the growing season, we aligned a two-band Enhanced Vegetation Index (EVI2) time series from Sentinel-2 with thermal time derived from gridded meteorological data. The deviation between the expected and observed EVI2 time series was defined as the Crop Damage Index (CDI). We assessed the performance of the CDI within specific phenological windows to predict yield loss. Finally, by comparing instances of substantial increase in CDI with different extreme weather indicators, we explored which (combinations of) extreme weather events were likely responsible for the experienced yield reduction. We found that the use of thermal time diminished the temporal deviation of EVI2 time series between years, resulting in the effective construction of typical stress-free crop growth curves. Thermal-time-based EVI2 time series resulted in better prediction of yield reduction than those based on calendar dates. Yield reduction could be predicted before grain-filling (approximately two months before harvest) with an R2 of 0.83 for wheat and 0.91 for barley. The combined analysis of CDI curves and extreme weather indices allowed for timely detection of weather-related causes of crop damage, which also captured the spatial variations of crop damage attribution at sub-field level. Our approach can help to improve early assessment of crop damage and understand weather causes of such damage, thus informing strategies for crop protection.
Faraday cup instrument for the solar wind monitoring at 0.9 AU — HENON mission
Authors: Přech Lubomír , Šafránková Jana , Němeček Zdeněk , Čermák Ivo , Ďurovcová Tereza , Marcucci Maria Federica , Laurenza Monica , Calgano Davide
Published: March 2024

The HEliospheric pioNeer for sOlar and interplanetary threats defeNce (HENON) mission funded by the Italian Space Agency has recently advanced to implementation (Phase C). The HENON 12U cubesat is expected to reach a Distant Retrograde Orbit (DRO) of the Sun–Earth system before the end of this decade. For several months it will stay about ≈ 0.1 AU in front of the Earth, providing thus a unique vantage point for the in-situ solar wind monitoring and allowing to send space weather alerts several hours before the related causal geoeffective structures can reach the Earth. The payload of the mission consists of the high-resolution radiation monitor (REPE), magnetometer (MAGIC), and the Faraday cup based solar wind monitor (FCA), provided by the Italian, Finnish, UK, and Czech consortium members.In this contribution we focus to the description of latter sensor — the Faraday Cup Analyzer (FCA), developed at Charles University as a simple and robust sensor for long-term monitoring of the basic solar wind parameters — density, velocity and temperature. We describe the overall instrument design, discuss many important technical aspects of the development including a computer modeling of the most important parts — Faraday cups (FC). We report on results of testing of an FCA development model with newly designed FC sensors, the instrument operation modes and future telemetry data products. As the HENON mission is greatly constrained with limited spacecraft telemetry, we also discuss the data strategy and on-board data processing allowing maximum scientific income and satisfying the mission requirements.
Estimation of time-varying tidal amplitudes using a state space model
Authors: Haakman Koen , Slobbe Cornelis , Verlaan Martin
Published: March 2024

Recently, global trends in tidal amplitudes have been estimated from satellite radar altimetry data by including several constituents with linearly changing amplitudes into the harmonic analysis least squares problem. However, changes in tidal amplitudes do not have to be linear. The assumption of linearity can potentially obscure the true time-varying evolution of tidal amplitudes. Revealing deviations from linearity could be useful for attribution of physical mechanisms responsible for changes in tidal amplitudes and may have implications for future projections.To address this limitation, an algorithm that estimates time-varying amplitudes without making any assumptions about the temporal shape is desired. To that end, we propose to use a state space time series model, for which time-varying parameters are estimated using a Kalman filter. Unlike the conventional least squares problem, the state space approach allows the value of a parameter to vary at each time step, providing a more flexible representation of the dynamic nature of tidal amplitude changes.We apply the model to global TOPEX/Poseidon and Jason altimetry data from 1993-2023 at satellite crossover locations, aiming to identify if and where tidal amplitude changes are deviating from linearity. Provisional results show that, in many locations, the M2 amplitude trend is close to linear during the considered timescale. Nevertheless, there are some regions where the estimated M2 amplitude trends are clearly deviating from linearity. However, these results should be interpreted with caution since the 95% confidence intervals around the estimated amplitudes are often of similar magnitude as the temporal variability of the amplitude. One potential strategy to mitigate this issue involves increasing the number of samples per time series by binning altimetry observations, as opposed to restricting the analysis solely to crossover locations. To fully understand whether the generated time-varying amplitudes are reliable, the state space model will be thoroughly tested with synthetic data.
Investigating the 3D distribution of GEM (Gaseous Elemental Mercury) in the lower atmosphere via a UAV (Unmanned Aerial Vehicle) - Lumex® assemblage
Authors: Cabassi Jacopo , Lazzaroni Marta , Giannini Luciano , Mariottini David , Nisi Barbara , Meloni Federica , Rappuoli Daniele , Vaselli Orlando
Published: March 2024

The occurrence of gaseous mercury pollution has to be identified and monitored through innovative methods and techniques, which would serve as a step toward strengthening the knowledge of the mechanisms of mercury dispersion in the atmosphere, in accordance with the provisions of the Minamata Convention on Mercury. Consequently, the aim of this work is to present the very first data obtained by directly and continuously measuring GEM (Mercury Elemental Gas) in the lower atmosphere through an original assembly of a UAV (Unmanned Aerial Vehicle, a heavy-lift octocopter) and a Lumex® RA-915M (a portable spectrometer for gaseous mercury). A few sites pertaining to both the mining facilities of the former Hg-mining area of Abbadia San Salvatore (Mt. Amiata, Italy) and the surrounding urban zones were selected to test the performance and effectiveness of the UAV-Lumex® combination at different heights. The octocopter agility and directional versatility, able to stop at selected altitudes, and the Lumex® great sensitivity made it possible to shed light on the variability of GEM concentrations and to represent its distribution via dot-map graphical visualization, providing a tridimensional picture of GEM profiling during the flights. This approach allows checking in near real-time whether the guideline concentrations are eventually exceeded. More specifically, the acquisition system was optimized through: i) the use of a stand-alone GPS as a synchronization tool for Lumex® and UAV GPS data; ii) the connection of a vertical sampling tube to the Lumex® inlet to overcome the strong airflows of the UAV rotors; iii) the use of batteries for power supply to avoid the release of exhaust gases. Moreover, all flights were standardized based on previously acquired data thanks to the method accuracy and the UAV pilot experience, allowing reprogramming and repeating the routes in different times. The results showed significant concentration variations between the urban and the most contaminated mining area, and highlighted the differences when the flight was repeated at a later date.
Evaluation of Mesoscale Eddy-Ice Interaction in the Southern Ocean using High-Resolution Models
Authors: Libera Stephy , Goosse Hugues , Putrasahan Dian
Published: March 2024

Antarctic sea ice plays an important role in the global climate through its influence on local and global oceanic and atmospheric circulations, planetary radiative balance, and the crucial support it provides for Southern Ocean ecosystem. Understanding the physical processes influencing Antarctic sea ice, and the drivers of its change are therefore of broad interest. The sea ice–covered the Southern Ocean, has relatively weak stratification in the upper ocean, where a relatively thin halocline separates the cold winter mixed layer from significantly warmer ocean interior. When warmer waters from the ocean interior enter the mixed layer, it can melt sea ice at its base. Features in the upper ocean, like mesoscale eddies can impact the thermohaline structure and stratification in this region and can impact the heat delivered to the surface. However, the mesoscale dynamics in the polar regions, especially under sea ice cover, is little known due to the limited observations and the inability of many numerical models to resolve mesoscale processes in the high latitudes.   This study aims to understand better the interaction between ocean mesoscale eddies and sea ice using high-resolution European Eddy RIch Earth System Models (EERIE) models. We investigate the effect of mesoscale eddies locally, and the integrated effect of eddy-sea ice interaction in the circumpolar Southern Ocean. Previous studies have identified eddy ice interactions to vary within regions of varying sea ice concentrations, such as in the high concentration pack ice and low-concentration marginal ice zones. The variations in the eddy-sea ice interaction in the Southern Ocean, within the open ocean, pack ice, and marginal ice zones are further investigated in this study.  
Reacting to climate change and temperature extremes: A case study on the tiger mosquito in Italy­
Authors: Garrido Zornoza Miguel , Caminade Cyril , Tompkins Adrian
Published: March 2024

Native to tropical and subtropical regions of Southeast Asia, Aedes albopictus, commonly known as the tiger mosquito, has been spreading worldwide with the aid of human activity. The geographical distribution and temporal dynamics of this mosquito are of special interest, given its role as a vector for arboviruses such as dengue (DENV) and chikungunya (CHIKV). Climate change, and its consequent increase in ­­both mean surface temperatures and the frequency and intensity of heat waves, has the potential to affect the behavior and seasonal activity of this mosquito, thereby posing a significant risk to human health. Understanding the impact of mean temperature changes and extremes on potential vector-borne disease risk is paramount to forecasting future trends as well as developing meaningful intervention strategies. In this work, we study the dynamics of Ae. albopictus over three decades, spanning 1990-2019, with a particular emphasis on the Italian Peninsula, which has remained a significant hotspot in Europe, since its introduction in the 1990s. We employed and adapted VECTRI, a climate-sensitive dynamical model that was originally designed for malaria. The model has been modified to parameterize Ae. albopictus and successfully calibrated to reproduce the seasonality of the vector using ovitrap data from various locations in Italy. Driving the model using high resolution EOBS gridded observation data, we perform various experiments to isolate the impact of temperature trends and late-spring to summer temperature extremes. Our results show a temperature-driven linear increase in the length of the mosquito season, with larger increases over the southern regions. Overall, temperature extremes tend to increase the bulk egg population across the country, although different spatial trends are highlighted: warm events tend to reduce vector populations in the Po valley and southern regions of Italy,already subject to the highest temperatures, while they tend to increase vector abundance over fringe highland areas. Our results indicate that 10-day temperature forecasts could be utilized to predict mosquito activity and consequently guide vector control intervention strategies such as insecticide spraying in the higher altitude regions identified in this study.
Graph Neural Networks for Atmospheric Transport Modeling of CO2 
Authors: Benson Vitus , Bastos Ana , Reimers Christian , Winkler Alexander J. , Yang Fanny , Reichstein Markus
Published: March 2024

Large deep neural network emulators are poised to revolutionize numerical weather prediction (NWP). Recent models like GraphCast or NeuralGCM can now compete and sometimes outperform traditional NWP systems, all at much lower computational cost. Yet to be explored is the applicability of large deep neural network emulators to other dense prediction tasks such as the modeling of 3D atmospheric composition. For instance the inverse modeling of carbon fluxes essential for estimating carbon budgets relies on fast CO2 transport models.Here, we present a novel approach to atmospheric transport modeling of CO2 and other inert trace gases. Existing Eulerian transport modeling approaches rely on numerical solvers applied to the continuity equation, which are expensive: short time steps are required for numerical stability at the poles, and the loading of driving meteorological fields is IO-intensive. We learn high-fidelity transport in latent space by training graph neural networks, analogous to approaches used in weather forecasting, including an approach that conserves the CO2 mass. For this, we prepare the CarbonBench dataset, a deep learning ready dataset based on Jena Carboscope CO2 inversion data and NCEP NCAR meteorological reanalysis data together with ObsPack station observations for model evaluation.Qualitative and quantitative experiments demonstrate the superior performance of our approach over a baseline U-Net for short-term (4x) of our model, thereby speeding up forward runs. This is especially useful when applied multiple times with the same driving wind fields, e.g. in an inverse modeling framework. Thus, we pave the way towards integrating not only atmospheric observations (as is done in current CO2 inversions), but also ecosystem surface fluxes (not yet done) into carbon cycle inversions. The latter requires backpropagating through a transport operator to optimize a flux model with many more parameters (e.g. a deep neural network) than those currently used in CO2 inversions – which becomes feasible if the transport operator is fast enough. To the best of our knowledge, this work presents the first emulator of global Eulerian atmospheric transport, thereby providing an initial step towards next-gen inverse modeling of the carbon cycle with deep learning. 
SWOT lake processing and products
Authors: Pottier Claire , Cazals Cécile , Battude Marjorie , Delhoume Manon , Crétaux Jean-François , Fjørtoft Roger
Published: March 2024

The Surface Water and Ocean Topography (SWOT) satellite, launched on December 16th 2022, is a CNES and NASA joint project, in collaboration with the Canadian Space Agency (CSA) and the United Kingdom Space Agency (UKSA). SWOT represents a major breakthrough in space altimetry by using a new technical concept based on interferometric synthetic aperture radar (InSAR): in comparison with conventional altimetry, which provides point data along profiles at resolutions of tens or hundreds of kilometres, wide-swath altimetry provides a two-dimensional image with a horizontal resolution of the order of tens or hundreds of meters. Therefore, this mission will significantly improve both offshore and coastal ocean observation, while enabling global measurement also of the water levels (and their variations over time and space) of rivers, lakes and flood zones, with a repeat period of 21 days.Over land, SWOT is planned to survey lakes with a surface area larger than 250 m by 250 m (objective: 100 m by 100 m). To do so, three main products are available to the user community. The pixel cloud (L2_HR_PIXC) product provides longitude, latitude, height, corrections and uncertainties for pixels classified as water and pixels in a buffer zone around these water bodies, as well as in systematically included areas (defined by an a priori water occurrence mask). The product specific to lakes (L2_HR_LakeSP) is computed from the pixel cloud for each water feature observed by SWOT and not assigned to a regular river. It consists of polygon shapefiles, delineating the lake boundary and providing the area and average height of each observed lake. A Prior Lake Database (PLD) allows to link the SWOT observations to known lakes and help monitoring them over time. The L2_HR_LakeAvg product aggregates L2_HR_LakeSP data over a 21-day cycle.The validation of L2_HR_LakeSP water surface elevations is mainly based on existing gauge networks. It is a challenge to obtain reference height data that have an absolute accuracy well below what is required for the SWOT lake products we are validating (10 cm 1-sigma at the lake level). The validation of water surface areas relies on reference water masks obtained mainly from (Very-) High-Resolution optical or radar satellite images (Pléiades, Sentinel-2, Sentinel-1, RCM…), pre-processed so that comparisons can be made at the lake scale.This presentation will first outline the lake processing and the Prior Lake Database. Then examples of products, preliminary accuracy assessments and associated Cal/Val activities will be presented.
Quantifying the Hydraulic Health of Fennoscandian Boreal Forests in a Changing Climate
Authors: O'Sullivan Hannah , Junttila Samuli
Published: March 2024

Drought-induced tree mortality in the Anthropocene has increased at an unprecedented rate and is expected to increase even more sharply in the next few decades due to anthropogenic climate change. Fennoscandian boreal forests are particularly at risk of drought-related mortality because they are less adapted to drought conditions compared with lower latitude forests. Currently, tree mortality research is inhibited by a lack of data on tree deaths, but we can still anticipate mortality events by monitoring forest health. In this study we determine indicators of forest ‘hydraulic health’ which we define as the ability of a forest to withstand and recover from drought events. Ultimately, this may help to predict and prevent drought-induced tree deaths under future climatic shifts.   To describe the hydraulic health of Fennoscandian forests we examine vegetation water content at both short (sub-daily) and intermediate (weekly) timescales using remotely sensed vegetation optical depth (VOD) measurements. Whilst short-timescale VOD is more tightly linked to water stress, intermediate-timescale VOD can demonstrate forest resilience and recovery to drought events. Here, we use a multivariate time series model to integrate VOD measurements at different timescales, presenting a novel opportunity to disentangle the drivers and responses of forests to drought.  The method introduced here is a first step towards quantifying abiotic hazards for forests. By focusing on smaller time steps of VOD data we can minimise the noise attributed to biomass changes over time and can better detect changes in vegetation water content. We hope that by quantifying hydraulic health indicators, they can serve as an early warning system for drought-induced mortality or help in predicting other hazards such as wildfire. Although we focus on Fennoscandian forests, in principle, these methods could be applied to other biomes.  
Ice-ocean coupled modelling for Nioghalvfjerdsbræ (79NG), Greenland
Authors: Zanker Joanna , De Rydt Jan
Published: March 2024

The Northeast Greenland Ice Stream (NEGIS) drains approximately 12 % of the Greenland Ice Sheet’s surface area, containing an ice volume of 1.1 m sea-level equivalent. Nioghalvfjerdsbræ (79NG) is one of two main outlet glaciers of NEGIS, extending into a large floating ice tongue, one of few remaining in Greenland. It is currently not well understood how 79NG will respond to the changing atmosphere and warming oceans, with possible implications for the catchment’s surface mass balance (SMB) and ocean-induced ablation. This research aims to assess the importance of feedbacks between ice-sheet geometry, SMB and ocean-driven melt by having a mutually evolving dynamical ice sheet with evolving SMB parameterization and a 3D ocean circulation model utilising the ice-ocean coupled model Úa-MITgcm. The potential feedbacks between changes in ice-sheet surface geometry, ice-tongue cavity geometry and the atmosphere/ocean mass balance are as-of-yet poorly understood, especially in the context of Greenland. Of particular interest for NEGIS is the potential for geometry induced changes in melting of the ice tongue, as found for some Antarctic ice shelves. Development of the Úa ice-flow model will begin with a Greenland-wide setup and experiments based on the ISMIP6 protocol, before focussing on a regional setup of the NEGIS catchment and coupling to a regional configuration of the MITgcm ocean model of the adjacent fjord and continental shelf. The coupled approach of this project aims to improve the representation of the feedbacks between different climate components at a regional scale and draw conclusions about the fidelity of projections of ice sheet-wide mass loss and sea-level rise from ISMIP. 
Using crystal-lattice distortion data for geological investigations: the weighted Burgers vector method 
Authors: Wheeler John , Sandra Piazolo , Prior David , Trimby Patrick , Tielke Jacob
Published: March 2024

Janos Urai made major contributions to our understanding of rock deformation and the microstructural fingerprints that can be used to investigate it.One such fingerprint is intracrystalline distortion. Crystals can be distorted due to deformation or growth but the distortion gives insights into processes in either case. Distortion is generally due to the presence of dislocations which give information on slip systems, stress levels, growth mechanisms etc. Electron backscatter diffraction (EBSD) allows detailed quantification of distorted crystals, and we summarise here a method for extracting information on dislocations from such data. The weighted Burgers vector (WBV) method calculates a vector at each point on an EBSD map, or an average over a region. The vector is a weighted average of the Burgers vectors of dislocation lines intersecting the map surface. It is weighted towards dislocation lines at a high angle to the map but that can be accounted for in interpretation. The method is fast and does not involve specific assumptions about dislocation types; it assumes only that elastic strains have little effect on the calculation. It can be used, with care, to analyse subgrain walls (sharp orientation changes) as well as gradational orientation changes within individual grains. It can complement established methods for subgrain wall analysis and frees us from some assumptions made in other methods.We give examples of its use applied to olivine and plagioclase. The magnitude of the vector relates to dislocation density but, as a vector, we find its directional information particularly informative. Code to implement this approach is available from the first author (“Crystalscape”), from Oxford Instruments (a commercial version) and aspects are implemented in MTEX.Urai, J. L., Means, W. D. & Lister, G. S. 1986. Dynamic recrystallisation of minerals. In: Mineral and Rock Deformation: Laboratory Studies (edited by Hobbs, B. E. & Heard, H. C.). Geophysical Monograph 36. AGU, Washington, D.C., 161-199.Urai, J. L. & Spiers, C. J. 2007. The effect of grain boundary water on deformation mechanisms and rheology of rocksalt during long-term deformation. In: 6th Conference on the Mechanical Behavior of Salt. Proceedings and Monographs in Engineering Water and Earth Sciences, Fed Inst Geosci & Nat Resources, Hannover, 149-+.Wheeler, J., Piazolo, S., Prior, D. J., Trimby, P. W. & Tielke, J. A. 2024. Using crystal lattice distortion data for geological investigations: the Weighted Burgers Vector method. Journal of Structural Geology 179, 105040.