bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterisation of strike-slip fault offsets using convolutional neural networks
Authors: Visage Sarah , Pousse Léa , Giffard-Roisin Sophie , Mouchené Margaux , Audin Laurence , Perrinel Sarah
Published: March 2024

The understanding of seismic recurrence relies on the chronology and magnitude of earthquake ruptures that have occurred in the past along a given fault. Knowledge of the rupture history of a fault provides valuable insights into its potential future behavior, aiding in the assessment of seismic hazard. Geomorphic evidence of faults is thus crucial for constraining models of seismic recurrence through surface rupture. The advent of remote sensing and other high-resolution datasets (such as Pleiades and SPOT satellite images) has improved tectono-geomorphological studies, promising to improve earthquake recurrence models. While manual or semi-automatic measurements of fault offsets using topographic markers like rivers have been conducted (Manighetti et al., 2015, 2020; Zielke et al., 2012), recent advances in artificial intelligence (AI) open new avenues for geoscientific applications (Ren et al., 2020) to handle the amount of high-resolution datasets.This study takes on the challenge of measuring slip offsets of faults using a Convolutional Neural Network (CNN) applied to synthetic Digital Elevation Models (DEM). The methodology involves generating realistic synthetic landscape models (DEM) using the Landlab software (Hobley et al., 2017), simulating slip faults based on the method of Reitman et al. (2019). The approach includes creating synthetic DEMs with Landlab, incorporating fault effects such as erosion, slip rates, and variable fault zone widths. Preliminary work in this study involves automating the creation of synthetic DEMs for a 2D prototype with a variable slip fault. A regression CNN model (with three convolutional layers followed by max-pooling layers and fully connected layers) is trained on these synthetic datasets, achieving slip offsets of ±3 meters on validation data. The model is then tested on real data labeled by experts, yielding satisfactory preliminary results.This study demonstrates the potential of CNNs for measuring slip offsets of faults using synthetic DEMs. The successful application of AI to geosciences paves the way for more efficient and automated analysis of fault activity in landscapes, thereby contributing to an enhanced assessment of seismic risks.
Deep-seated Gravitational Slope Deformations identification and trend analysis from ground deformation time series: A case study in the Italian Alps
Authors: Dong Yingbo , Floris Mario , Catani Filippo
Published: March 2024

In alpine regions, Deep-seated Gravitational Slope Deformations (DsGSDs) pose significant risks due to their continuous deformation rates, potentially leading to sudden and accelerated transformations that can cause unpredictable damage to local communities and infrastructure. Monitoring DsGSDs is crucial for effective risk assessment and land-use planning. Advances in remote sensing technologies, particularly InSAR (Interferometric Synthetic Aperture Radar), offer substantial advantages in monitoring and studying these widespread and slow processes. The European Ground Motion Service (EGMS), which provides Europe-wide ground motion data, emerges as a viable tool for detecting, monitoring, and characterizing DsGSDs. This study aimed to develop and evaluate an automated workflow for identifying and analyzing trends in DsGSDs in alpine areas using deformation time series datasets. The approach involves utilizing advanced statistical methods to characterize DsGSD phenomena in alpine regions. Focusing on the Carnic Alps area in the northern part of the Veneto Region and Friuli-Venezia Giulia Region (NE, Italy), our objective is to explore supervised machine learning (ML) and deep learning (DL) algorithms to automatically identify DsGSD areas and analyze the spatiotemporal behavior of long time series of ground deformations. The findings will be compared with data from the Italian Landslide Inventory (IFFI), serving to not only validate the newly extracted information but also assess the potential of integrating multi-source datasets. This work sets the foundation for further analyses on how transient climatic factors could influence DsGSDs regimes.
Application of WRF-Based Single-Point Data Artificial Intelligence Post-Processing Correction Method in Practical Short-Term Wind Speed and Power Forecasting
Authors: Xia Xin , Luo Yong
Published: March 2024

With the rapid development of wind energy, the imperative for precise wind power predictions has intensified, with the crux lying in forecasting wind speeds. The accurate short-term (1 to 3 days) forecast of wind speeds at the hub height in boundary layer poses a significant scientific challenge. Generating such forecasts for wind farms 1 to 3 days in lead time necessitates reliance on global weather forecast products and the WRF model. In pursuit of heightened accuracy, artificial intelligence (AI) algorithms are employed to refine WRF-predicted wind speeds based on observational data.This study draws upon observational data from five operational wind farms over three years, employing diverse deep time-series models, to examine the effectiveness and limitations of these models in post-processing corrections for WRF-predicted wind speeds. Based on our examination, we conclude that: 1) Transformer-based models have significant untapped potential, with the Pyraformer model emerging as a well-suited temporal model for post-processing corrections in wind speed and power predictions. 2) Traditional full-attention mechanisms are less effective, highlighting the importance of sparse attention as a vital approach for capturing temporal correlations in such problems. 3) The optimal model demonstrates a reduction of approximately 20% in RMSE for single-point post-processing corrections. In addition, wind speed prediction accuracy reaches around 86%, and power prediction accuracy is approximately 82%. 4) AI-based post-processing corrections may encounter challenges, including the underestimation for high-value and difficulties in reproducing forecasts below the average value.
Decomposing Realistic Oceanic Flow in Balanced and Unbalanced Parts Using a Novel Balancing Approach
Authors: Rosenau Silvano , Chouksey Manita , Eden Carsten
Published: March 2024

Decomposing oceanic flow fields into its slowly evolving geostrophic component and the fast wave mode is necessary to understand processes like mesoscale eddy dissipation and spontaneous wave emission. The application of existing decomposition methods, such as nonlinear normal mode decomposition or optimal balance is limited to idealized model settings that neither include topography nor a varying Coriolis parameter. To overcome these limitations, we propose a new approach that combines optimal balance with a time-averaging procedure. This approach eliminates the necessity for the Fourier transformation that is required in the original optimal balance method. We tested and compared the new  variation of optimal balance with the original method in a scaled rotating shallow water model in various dynamical regimes, with Rossby numbers ranging from 0.03 to 0.5. In all tested configurations, the imbalances obtained with the new method converges towards the imbalances obtained with the original method. We further show that the convergence rate can be improved by doing multiple short time averages instead of a single long one. The new method is applicable to realistic ocean scenarios that include topography and a varying Coriolis parameter and shows promising results in decomposing complex flow fields.
Better Climate Services: guidelines, standards and best practices for data processing
Authors: Pagé Christian , Muñoz Ángel G. ,   Climateurope2 WP2 Team
Published: March 2024

Timely delivery and effective use of climate information is fundamental for a green recovery and a resilient, climate neutral Europe, in response to climate change and variability. Climate services address this through the provision of climate information for use in decision-making to manage risks and create opportunities. In order to develop future equitable and quality-assured climate services to all sectors of society, it is important to work on developing standardisation procedures for climate services, as well as supporting an equitable European climate services community and also enhancing the uptake of quality-assured climate services to support adaptation and mitigation to climate change and variability.An important component of the climate service reliability and use depends on the data, specifically on the traceable quality of its input and output datasets. The output datasets need to be FAIR, also for machines, meaning the output datasets provide full provenance information about e.g. the input datasets, the processing software, the quality and accuracy, all supported by interoperable metadata, including information on uncertainty. To support those needs and objectives for climate services, we will present preliminary guidelines of good practices for vocabularies, formats, metadata and technical standards, including FAIR principles for data and software/processing. As well, preliminary best practices in provenance of processing methodologies to guarantee traceability and reproducibility of climate data and ways to communicate it in a user-friendly manner will also be shown along with climate uncertainty, risk assessment and communication. Eventually all guidelines and good practices will be shared via the Climateurope2 platform, set up under the project to support the climate services community.Everyone interested can also join our network to actively participate in developing best practices for climate services https://climateurope2.eu/This project (Climateurope2) has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement N°101056933.
Towards Digital Twin in Global Flood Forecasting - A Proof-of-Concept in Severn catchment and Alzette catchment
Authors: Nguyen Thanh Huy , Bhattacharya Sukriti , Wong Jefferson , Didry Yoanne , Matgen Patrick
Published: March 2024

Advancements in Earth Observation, coupled with the swift progress in big data analysis and access to distributed computing and storage, open up exciting possibilities for the development of Digital Twins of the Earth. These Digital Twins hold the potential to transform disaster preparedness, allowing us to foresee extreme events and assess the effectiveness of various policy measures. Within this framework, we propose here a specialized Digital Twin dedicated to flood disasters. Its primary goal is to enhance flood resilience by introducing an innovative inundation forecasting service that provides early warnings and enhances preparedness. To ensure the product aligns with user needs, a multi-tiered strategy for collecting user requirements was implemented. Key features identified by users include hourly flood depth predictions, updated daily, with a 72-hour lead time. The integration of local data and models for impact analysis at local scales was also recognized as crucial. The chosen pilot studies for this project focus on the winter 2020 storms in the Severn Catchment, UK and the summer 2021 storm in the Alzette Catchment, Luxembourg. Both events were observed by the Copernicus Sentinel-1 mission.To meet user requirements, the study aims to incorporate existing state-of-the-art global and regional near-real-time flood monitoring and forecasting products, namely GloFAS (Global Flood Awareness System) and GFM (Global Flood Monitor). The Digital Twin thus consists of four key elements:Numerical Weather Prediction (NWP) model, based on ECMWF or French/German weather service forecasts;
Land surface model and rainfall-runoff model, i.e. GloFAS HTESSEL or LARSIM;
Hydrodynamic model, with LISFLOOD-FP model for both catchments;
Flood impact assessment model, based on KONTUR population dataset and OpenStreetMap.
By integrating the GFM and GloFAS products through data assimilation, the Digital Twin is capable of short-term as well as medium-range daily inundation forecasting, reducing predictive uncertainties. The data assimilation strategy is flexible and accommodates various global- and local-scale models and resolutions. Its implementation involves particle filtering enabling weighted combinations of pre-computed flood depth maps based on LISFLOOD-FP, aligned with flood extent maps observed by GFM, providing a more accurate representation of the real world.Not only this strategy is spatiotemporally transferable but it is also adaptable to new test sites without extensive retraining or reconfiguration. The outcomes of this proof-of-concept study can lay the groundwork for future research in the field, contributing to closing the global flood protection gap.
Last Interglacial sea-level proxies along the Brazilian western Atlantic coasts
Authors: Cerrone Ciro , Lämmle Luca , Scicchitano Giovanni , Perez Filho Archimedes , Chauveau Denovan , Georgiou Nikos , Dean Silas , Rovere Alessio
Published: March 2024

Geological sea-level proxies, such as fossil intertidal or foreshore deposits, store fundamental information that allow reconstructing past changes in sea level, which may be used to evaluate the volume of ice sheets during past warm periods. Studies on Last Interglacial (LIG; Marine Isotope Stage 5e, ~ 125 ka) sea-level proxies are particularly important, as this highstand is a process analogue for the current interglacial, including warming caused by human greenhouse gas emissions. In fact, the LIG was characterized by slightly higher temperatures than the pre-industrial, that caused higher global sea level and, in turn, smaller ice-sheets.This work was done in the framework of the WARMCOAST Project funded by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovative Program (Grant Agreement No. 802414). This part of the project aims at surveying new geological sea-level proxies along the western Atlantic Brazilian coast, from Rio Grande do Sul to São Paulo and in southern Bahia State. Classical geological and geomorphological surveys were carried out in the field. We collected several samples for OSL dating and micropaleontological analysis. Samples consist mostly of shallow-water marine sands of supposed LIG age. The elevation of each proxy has been measured by a GNSS RTK station with centimetric precision and referred to a local geoid model (MAPGEO2015).In this work, we report the results of the field campaign along the Brazil coast and, the new data are interpreted in terms of Glacio-Isostatic Adjustment processes affecting the coasts since the Last Interglacial. 
A comparison of classification methods to perform a typology of precipitation events for soil erosion modelling
Authors: Özcelik Nur Banu , Laimighofer Johannes , Strohmeier Stefan , Vásquez Cristina , Klik Andreas , Strauss Peter , Pistotnik Georg , Yin Shuiqing , Dostal Tomas , Laaha Gregor
Published: March 2024

Soil erosion is a major threat to soil resources. Our ACRP-supported project EROS-A aims to improve erosion modelling by investigating the role of extreme precipitation and associated erosivity on soil erosion in the Main Agricultural Production Zones (MAPZ) of Austria. For this purpose, it is important to separate precipitation events into different process types (e.g. convective and stratiform events), as these are expected to follow different distributions and can be modelled more accurately using a mixture model approach.In this contribution, we assess the performance of different clustering methods to establish a process typology of precipitation events. The study uses high-resolution rainfall data with a time resolution of 5 minutes from 27 stations in the agricultural area of Austria. Hourly lightning data (ALDIS) is used as a conditional variable, as thunderstorms are a good indicator of convective events. In our approach, a precipitation event is defined as time spell when precipitation exceeds 0.1 mm per 5 minutes. Similar to a drought analysis, this can result in short, interdependent events. These are pooled using a minimum precipitation of 1.27 mm in 6 hours as an interevent time and volume criterium. The temporal characteristics of rainfall events are characterized by five indices: the amount (aggregated event precipitation), duration (the time between the start and end of the event), intensity (amount divided by duration), peak intensity (the maximum 5-min intensity), and the time-to-peak (relative to the duration of the event). These characteristics are typically dominated by small (positive) values and are thus assumed to follow a Gamma distribution. In addition, the binary lightning index was considered as this is expected to have discriminative power as well.Based on the rainfall events so obtained, cluster analysis is performed using partitioning around medoids (PAM) with Gower metric transformed lightning index. For comparison, model-based cluster analysis for mixtures of multivariate Gamma distributions is conducted. The results are compared using the discriminative power of principal component analysis (PCA) and measures of cluster homogeneity and discriminability.  In a final evaluation, the discriminative power of the event classification is assessed in terms of event type distributions. Initial results indicate that the event indices contain a wealth of information that can be profitably used to establish a typology of precipitation events. The results will feed into future studies to perform rainfall simulations that can serve as an input for erosion scenario modeling for agricultural decision support.
A meta-analysis of global soybean plant growth and yield improvement in response to phosphorus addition
Authors: Walling Hannah , Rufino Mariana , Rotundo Jose , Borras Lucas , Rothwell Shane , Quinton John , Haygarth Phil
Published: March 2024

Application of phosphorus (P) fertiliser to soybean accounts for a large proportion of the global consumption of P as an agricultural fertiliser. Despite this key a knowledge gap exists surrounding the mechanisms of P fertiliser uptake and how it interacts with nitrogen fixation processes and yield improvements.This paper aims to improve the understanding of P cycling in global cropping systems and will present a global meta-analysis of published data quantifying the effect of P fertiliser application on soybean above- and below-ground plant response variables. 790 paired observations (P fertiliser treatment and control treatment) were synthesised from 81 peer-reviewed articles that reported soybean response, including seed yield and nodulation, to P addition under a range of different environmental conditions.We tested the hypothesise that:soybean productivity will increase following P addition, with this response being driven by below-ground processes;
environmental conditions, particularly soil chemical properties would explain the variance in the observed response.
Analysis of these observations showed an overarching increase in soybean plant response following P addition. We found that several environmental and experimental conditions, particularly soil phosphorus status and phosphorus fertiliser rate influence the response of soybean to phosphorus addition, highlighting the complexities of sustaining P use across such a globally cultivated crop.We recommend further experimental work needs to be conducted, which controls for such factors and allows for the improved mechanistic understanding of below-ground processes, to inform better use of finite P resources.
Passive monitoring of a deep geothermal reservoir in the Strasbourg area by interferometric approaches using ambient seismic noise.
Authors: Mattern Flavien , Vergne Jérôme , Schmittbuhl Jean , Zigone Dimitri
Published: March 2024

We present preliminary results of ambient seismic noise monitoring near the deep geothermal reservoir at the Vendenheim site north of Strasbourg in France. From November 2019 to mid 2021, various operations led to an intense induced seismic swarm with several events of magnitudes above 3.0Mlv. This crisis is also characterized by the presence of an isolated swarm ~5km south of the geothermal site as well as the occurrence of the maximum magnitude event (3.9Mlv) 6 months after the cease of injection tests. Understanding these remote and delayed triggering mechanisms is essential for the successful development of future deep geothermal projects. We use ambient seismic noise correlations betweens pairs of sensors from a composite network of 137 permanent and temporary stations in the area. In particular, we intend to monitor the evolution of the upper crust around the reservoir by studying velocity variations and coda waveforms decorrelation in different frequency bands.At high frequencies (1-3Hz), velocity variations appear to be correlated with fluctuations of the water table elevation. Strong decorrelations in waveform coda are also observed during holidays, suggesting changes in anthropogenic noise sources illumination. At low frequencies (3-6s), apparent variations of velocity and decorrelation with mainly an annual periodicity are observed, but could be associated with seasonal variations in the position of the sources of the second microseismic peak. This study shows that in order to observe temporal variation in the properties of deep geothermal reservoirs with ambient noise coda wave interferometry, it is necessary to understand and model variations in the subsurface layers and in the sources of ambient seismic noise.  
Assessing extreme temperature volatilities across Germany between 1990 and 2022
Authors: Jordan Elisa , Shekhar Ankit , Gharun Mana
Published: March 2024

Climate change causes a global rise in mean air temperature and increased frequency of temperature extremes. Recent studies link sharp temperature changes between consecutive days to increased mortality, reduced economic growth, and negative effects on ecosystems. While climatological analyses predominantly focus on mean temperatures, extreme temperatures have higher impacts on human health. This study assesses the variability of the daily maximum air temperature between two consecutive days (i.e., volatility) across Germany from 1990 to 2022. We used observation-based raster data of the maximum daily temperature assessed volatility regarding: 1) magnitude, 2) seasonality, 3) the direction of temperature change, and 4) trends during the entire period. As changes of land use and land cover have a direct impact on local temperatures, we analysed the land cover changes during the same period and examine its correlation to extreme volatilities.The results showed a higher magnitude of rapid temperature decreases compared to temperature increases. Extreme volatilities increased with further distance to the coast from north of Germany to south. Overall, abrupt day-to-day temperature changes occurred mostly during the warming half-year (from March to August). During the study period, significant trends of 0.5 °C and 0.2 °C per decade showed a widening range of extreme volatility in spring and autumn. Compared to unchanged areas, changing land cover was predominantly liked to increasing volatilities of up to 0.5 °C. Understanding rapid temperature changes is crucial for climate change mitigation strategies and limiting impacts on human health and on the environment.
Machine learning in classifying morphological changes in the Brahmaputra River using multi-spectral Landsat images in the Google Earth Engine
Authors: Bhattacharya Biswa , Rahman Manzur , Alfonso Leonardo
Published: March 2024

Understanding morphological changes in river basins is important for efficient river basin management. Such studies on morphological changes can be efficiently carried out by processing remote sensing images. In this respect Google Earth Engine (GEE) provides an efficient platform for processing of such images. In this research an automatic identification of land and water from satellite imageries was carried out by using the water index based unsupervised classification approach. Multiple water indices were compared for the Brahmaputra River (Assam reach). Landsat images from 1990 to 2020 were used in the study. Various thresholding approaches available in the literature were applied to determine which particular index in combination with which thresholding approach provides the best classification. We found the Normalized Difference Water Index (NDWI) as the best index for unsupervised classification. Subsequently, a supervised classification approach was adopted to classify land and water from satellite images. In particular, three classification methods were used, namely: Classification and Regression Tree (CART), Random Forest (RF) and Support Vector Machine (SVM). The classifiers were trained with B2, B3, B5 and B6 (Blue, Green, NIR and SWIR1) bands as the input and the pre-classified pixel class as the output. The resulting classified images were compared with the Joint Research Centre (JRC) monthly water maps and a good accuracy was observed. Among the three methods RF gave the best results. For the Brahmaputra basin we noticed a lot of morphological changes during 1990 and 2020. This research showed that given good quality training data classifiers can be built, which can automatically extract water bodies from Landsat or similar images and can be used in morphological assessment of any river basin.Keywords: Surface water extraction, supervised classification, Brahmaputra, Google Earth Engine (GEE).
Long-term tropospheric ozone from SCIAMACHY+OMPS and effects of the upper limit definition of the column
Authors: Orfanoz-Cheuquelaf Andrea , Arosio Carlo , Rozanov Alexei , Weber Mark , Burrows John
Published: March 2024

About 10% of the total amount of ozone resides in the troposphere, which acts as a potent greenhouse gas. Anthropogenic emissions and biomass burning are the main sources of ozone in the troposphere, and overexposure to this pollutant causes health problems and damages vegetation.A combination of space-borne limb and nadir measurements in the UV-visible spectral range (so-called limb-nadir matching, LNM) provides valuable information on tropospheric ozone. This study uses data from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) (2002-2012) and Ozone Mapping and Profiler Suite on board of Suomi National Polar-Orbiting Partnership (OMPS/NPP, since 2012). Both instruments observe the atmosphere in both limb and nadir geometry. Tropospheric ozone columns are retrieved globally by subtracting the stratospheric ozone column calculated from limb observations from the total ozone column derived from the nadir measurements.Tropospheric ozone retrievals use different upper altitude limits to calculate the tropospheric ozone column. In the case of the LNM technique, the upper limit is defined by the thermal and/or dynamical tropopause. The Convective Clouds Differential technique (CCD) calculates the tropospheric ozone column up to 270 hPa. Phase II of the Tropospheric Ozone Assessment Report (TOAR-II) uses different pressure levels for different latitudes as an upper limit for the tropospheric column.After updating and improving the SCIAMACHY-LNM and the OMPS/NPP-LNM datasets, we obtained a long-term dataset of tropospheric ozone (2002-2023) by merging them. Here, we present this new long-term LNM tropospheric ozone column dataset, which has been converted to the different definitions of column heights as prescribed in TOAR II. The datasets are validated using ozonesondes, and the results for the different column definitions are evaluated and discussed.
Imaging of sediment-hosted Cu deposits using ambient noise tomography: a case study of the Kansanshi Cu-mine, Zambia.
Authors: Mackay-Champion Tobermory , Harmon Nicholas , Mutelekesha Sekelo , Chanda Mulenga , Hudson Thomas , Kendall John-Michael , Daly Michael C
Published: March 2024

Improved passive seismic imaging of sedimentary basins plays a crucial role in improving our understanding of basin inversion tectonics and sedimentary-hosted mineral systems. The Central African Copperbelt of Zambia and the Democratic Republic of Congo is hosted in the Neoproterozoic Katangan sedimentary basin and accounted for 8.8% of global copper production in 2021 (World Economic Forum, 2024). Despite this, the tectonic evolution of the basin in Northern Zambia is currently unclear, significantly hampering our understanding of the Cu, Co and Ni mineralisation in that area. To investigate the geodynamics that shaped this region, and to assess the suitability of MEMS-accelerometers for passive seismic imaging of sedimentary basins, an array of nodal accelerometers was deployed around the Kansanshi Mine (NW Zambia), previously Africa’s largest Cu mine. Surface wave phase velocities in the mine and surrounding area were analysed using ambient noise tomography, with average Rayleigh wave phase velocities ranging from 3.05 +/- 0.2 km/s at 3 s period to 3.5 +/- 0.15 at 6 s period. The S-wave velocity at points of particular interest was examined using iterative non-linear inversions of surface wave dispersion curves constructed from the tomography results. These S-wave profiles provide new insight into the structural configuration of the Kansanshi copper mine and show that the mine overlies a large thickness of sediments from which the copper could be scavenged. This study illustrates the efficacy of performing ambient noise tomography on MEMS-accelerometer data to investigate the structures controlling the inversion of sedimentary basins and the formation of sedimentary-hosted metal deposits at a local to regional scale.
Comparison of Kinetic Energies of Different Spraying Systems
Authors: Neumann Martin , Seitz Steffen , Krasa Josef , Falcao Raquel , Dostal Tomas
Published: March 2024

Rainfall simulators have been used for research of soil erosion by water for many years. Scientific teams around the world own a variety of different devices. In the case of comparing the results of several teams, the problem is the rainfall characteristics of different devices and therefore different input parameters. In this contribution, 3 devices were compared: a small rainfall simulator of the CTU, a small rainfall simulator of Tubingen University, and a laboratory rainfall simulator of the CTU. A laser diffractometer (Thies Clima Laser Precipitation Monitor 5.4110) was used to determine the kinetic energy (KE) and rainfall intensity and splash cups filled with sand (Tubingen Splash Cups, designed by Scholten et al., 2011) were used to compare the methods of the kinetic energy measurement. On each device, measurements were made on a plot with area 1 x 1 metre at nine positions with a rainfall intensity set at 60 mm h-1. Significant differences among the devices were observed using the laser disdrometer. Small rainfall simulator of Tubingen University achieving a KE of approximately 2.5 J m-2 mm-1, small simulator of the CTU a KE of approximately 5.5 J m-2 mm-1, and the laboratory simulator of the CTU a KE of approximately 8 J m-2 mm-1. The kinetic energies obtained by the splash cups did not reach the values produced by the laser diffractometer. During the experiments, local irregularities in rainfall were observed associated with different types of nozzles and different simulator constructions. The splash cups (46 mm in size) allowed one to measure exact locations proving that locally KE can reach much higher values.The experiments proved that the differences among different simulator constructions can greatly affect the results of the experiments performed, and the method of assessing the rainfall characteristics can help to understand the real functioning of each device.This research was supported by the research projects QK22010261, Mobility 8J23DE006, and by the Grant Agency of the CTU in Prague SGS23/155/OHK1/3T/11.
Reconstructing the Sea-Surface Temperature at the Equatorial Pacific using tree-ring proxies from the Peruvian central Andes. 
Authors: Rodriguez Morata Clara , Requena Rojas Edilson Jimmy , Ticse Otalora Ginette , Morales Mariano , Crispín DeLaCruz Doris , Andreu hayles Laia
Published: March 2024

Some El Niño events are characterized by very warm conditions in the far-eastern Equatorial Pacific (FEP), but cool conditions elsewhere in the central Equatorial Pacific (CEP). The impact of these so called Coastal El Niño (CEN) events is particularly strong, associated with extreme rainfall events over the coastal northern Peru, Ecuador and adjacent Andean slopes. Despite the fact CEN events represent a high cost for social and economic development of these countries, little is known in terms of frequency, mechanisms and predictability and only very recently science and society are paying attention to these episodes. Here we use the tree-ring width (TRW), as well as stable oxygen (δ18O) and carbon (δ13C) isotopes measured in tree rings to reconstruct Sea-Surface Temperature (SST) in the Equatorial Pacific Ocean described by the two first Empirical Orthogonal Function (EOF). While EOF1 corresponds to the CEP region, EOF2 represents the FEP region.The newly developed TRW and isotopic records span from 1890 to 2007 and were built from Polylepis rodolfovasquezii trees located at 4,360 m a.s.l in an Andean forest in Peru (11.72°S, 75.14°W). Our results show significant (-) correlation between tree-ring δ13C and temperature during the previous growing season peak, while non climatic signal was found in TRW and δ18O records. During the current growing season tree-ring δ18O is the proxy that exhibits the highest sensitivity to both, precipitation (-) and temperature (+) compared with the two other tree-ring parameters. In addition, the δ18O record displays more consistent correlation patterns with both EOFs, suggesting that δ18O may contain stronger climate signals than TRW and tree-ring δ13C. Lastly, the use of a sequential leave-20-out calibration-validation technique for reconstructing the variability of EOFs indicated that the δ18O record was effective to reconstruct EOF1. However, incorporating a multi-proxy strategy, which includes TRW, δ18O, and δ13C, enhanced the overall quality of the reconstruction. In contrast, the multi-proxy approach was not enough to reconstruct EOF2. We conclude that expanding the geographical distribution of proxy records into new in-land areas around the FEP, where SST variability has a local impact on hydroclimate, it is a priority in order to reconstruct CEN. Tree-ring stable isotopic records are valuable to complement existing TRW chronology to overcome the inherent difficulties on using tropical Andean species for paleoclimate research.
The origin of melilitites: preliminary results on melting of a carbonated wehrlite
Authors: Poli Stefano , Melluso Leone
Published: March 2024

Melilitites are ultramafic magmas characterized by normative Ca2SiO4, larnite, high FeO* and TiO2. Liquids compositionally close to melilitites were experimentally reproduced from carbonated lherzolites in alkali, Fe and Ti-free model systems at 3.2-3.3 GPa, approx.  1500 °C (Gudfinnsson & Presnall, 2005), at relatively high melt proportions. In complex compositions, MORB-eclogite derived, carbonated, partial melts reacted with a fertile peridotite were proposed at the origin of melilitites (Mallik & Dasgupta, 2013, 2014). The experimental reconstruction of phase relationships along a join olivine melilitite - carbonate revealed that at 3 GPa, clinopyroxene and olivine or garnet are stable on the liquidus (Brey & Ryabchikov, 1994), suggesting that carbonated wehrlites are potential sources for the genesis of melilitites.Here, we explore phase relationships on the high pressure melting of a model wehrlite, initially composed of a mechanical mixture of San Carlos olivine, diopside, aegirine, dolomite, rutile and kyanite. Starting materials were loaded in graphite capsules, inserted in sealed platinum capsules. Vitreous carbon spheres and synthetic diamond grains were adopted for liquid traps. Preliminary experimental results show that at 3 GPa the solidus is located at temperatures lower than 1200 °C. A thick, orthopyroxene-rich layer, with polygonal microstructure, forms at contact with aggregates resulting from quenched liquids, both at 1200 °C and 1400 °C. Estimates of liquid composition are melilititic, with TiO2 approx. 2.5 wt.% on a volatile free basis.Currently available experiments suggest that the solidus is controlled by the reaction dolomite + olivine + clinopyroxene = orthopyroxene + liquid, as suggested in Eggler (1976). This is feasible only if the liquid composition is located on the CaO-rich side of the plane diopside-forsterite-dolomite in the model system CaO-MgO-SiO2-CO2, i.e. on the normative larnite (akermanite) portion of the tetrahedron. Brey G.P. & Ryabchikov I.D. (1994). Carbon-dioxide in strongly silica undersaturated melts and origin of kimberlite magmas. Neues Jahrbuch Fur Mineralogie-Monatshefte, (10), 449-463.Eggler D.H. (1976). Does CO2 cause partial melting in the low-velocity layer of the mantle?. Geology, 4(2), 69-72Gudfinnsson G.H. & Presnall D.C. (2005). Continuous gradations among primary carbonatitic, kimberlitic, melilititic, basaltic, picritic, and komatiitic melts in equilibrium with garnet lherzolite at 3–8 GPa. Journal of Petrology, 46(8), 1645-1659.Mallik A. & Dasgupta R. (2013). Reactive infiltration of MORB-eclogite-derived carbonated silicate melt into fertile peridotite at 3 GPa and genesis of alkalic magmas. Journal of Petrology, 54(11), 2267-23
Terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X
Authors: Nelson Jacob A. , Walther Sophia , Kraft Basil , Gans Fabian , Duveiller Gregory , Weber Ulrich , Hamdi Zayd Mahmoud , Zhang Weijie , Jung Martin ,   FLUXCOM Contributors
Published: March 2024

Mapping in-situ eddy covariance measurements of terrestrial carbon and water fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented up-scaling framework, FLUXCOM-X. The X-BASE products comprise of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP) as well as evapotranspiration (ET) and, for the first time, a novel fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution for the period 2001-2020.One key improvement of the new products is the much more realistic estimates of global carbon uptake (NEE) at  -5.75 PgC yr-1, which is a marked improvement compared to previous FLUXCOM versions as well as reconciles the bottom-up global eddy-covariance-based NEE and estimates from top-down atmospheric inversions. The improvement of global NEE was likely only possible thanks to the international effort to improve the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site-years resulting in a wider coverage of bio-climatic conditions. However, X-BASE global net ecosystem exchange shows a very low inter-annual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge.With 125 PgC yr-1, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas and shows a good agreement with TROPOMI based SIF. X-BASE evapotranspiration amounts to 74.7x10³ km3 yr-1 globally, but exceeds precipitation in many dry areas likely indicating overestimation in these regions. On average 57% of evapotranspiration are estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models.Despite considerable improvements to the previous up-scaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy-covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. Here we will outline how the new FLUXCOM-X framework provides the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.   
Comparison and evaluation of neutron monitor based incoming corrections for Cosmic Ray Neutron Sensing
Authors: Hertle Lasse , Zacharias Steffen , Schrön Martin
Published: March 2024

Cosmic Ray Neutron Sensing (CRNS) is a technique to measure water content, for example soil moisture, on the hectare scale through the measurementof epithermal neutrons. The neutrons are results of particle showers in the earth’s atmosphere caused by cosmic rays impinging on it. The abundance andglobal distribution of neutrons is changed in time through different factors. On the largest scale, the heliosphere and therefore the solar cycle greatly affect the amount of galactic cosmic rays that are able to reach earth. Large solar events, such as Forbush decreases, also cause rapid changes in the cosmic ray flux. The aim of any correction method is ultimately to account for these heliospheric changes. The next smaller scale is the earth’s magnetic field. The biggest consequence here is an uneven distribution of neutrons across latitudes, as with increasing cut-off rigidity less cosmic rays are able to reach the atmosphere. This presents a challenge to correction methods based on neutron monitors, since any neutron measurement is always localised to specific geomagnetic and atmospheric conditions. Lastly, the abundance of neutrons at different energy bands is strongly tied to the local conditions. In particular hydrogen abundance is of vital importance. The CRNS technique is based upon the sensitivity of neutrons to hydrogen, which is dependent on the energy of any given neutron. As these neutrons are still dependent on heliospheric and geomagnetic conditions, their measurement needs to be corrected for the amount and variation in incoming radiation. Neutron monitor based correction methods are tackling two challenges at the same time. Firstly, a neutron signal, free of local interference, needs to be extracted from the neutron monitor data. This signal is representative of the heliospheric conditions localised through the geomagnetic conditions to the neutron monitor site. Secondly, the signal needs to be localised to the point of the CRNS measurement, which rarely coincides with the position of a neutron monitor. Multiple correction methods have been evaluated and compared, with consideration towards both challenges.
The Evolution of Climate Services: Shifting Paradigms from commercial exploitation to Societal Engagement
Authors: Petitta Marcello , Calmanti Sandro , De Felice Matteo
Published: March 2024

The landscape of climate services is undergoing a remarkable transformation with the definition of a new framework. We call this new framework: Societal Climate Services (SCS). This shift has been primarily driven by a growing trend among large corporations to decrease their reliance on external climate service consultancies in favor of developing dedicated in-house departments. Such a move signifies a transition towards self-reliance in climate-related decision-making and strategy formulation, marking a departure from the traditional reliance on external expertise prevalent in recent research projects.Traditionally, the development of climate services has relied on the co-creation, co-design and co-development (CO-CO-CO) approach, characterised by collaborative efforts among external experts, academics and researchers. However, the growing in-house expertise within these corporations indicates a significant shift towards more independent, customised climate solutions.There is the need to shift the current climate services from a purely business approach to a new framework where the society is central. Societal climate services complement this evolution by expanding the focus beyond the needs of businesses to broader societal concerns, particularly in vulnerable and underrepresented communities, especially in developing countries. SCS aims to democratise climate knowledge and make it accessible and usable not only for businesses, but for society as a whole. This approach promotes a people-centred model of engagement where community participation and local knowledge play a central role in shaping climate solutions.This summary outlines the principles of societal climate services and emphasises the importance of cross-sectoral cooperation for a comprehensive and integrated approach. It emphasises the role of SCS in building sustainable and resilient communities through long-term planning and investment in sustainable practises. It also emphasises the need for equity and justice in the provision of climate services to ensure that solutions do not exacerbate existing inequalities but contribute to their reduction.The emerging momentum of companies developing internal capacity for climate services alongside the emergence of SCS is a key development in this area. This combination promises a more holistic and effective framework for addressing the multi-faceted challenges of climate change, ensuring that both business interests and societal needs are aligned in the pursuit of global climate resilience. 
Advancing Development: The Impact of Geoscience Education in Nigeria’s Rural Coastal Areas of the Niger Delta Region
Authors: Chijioke Nwachukwu Martin , Omeje Ezekiel , Ojukwu Njideka-Nwawih , Ozobialu Benedicta C.
Published: March 2024

The Niger Delta region of Nigeria is a significant ecological and environmental zone that is classified as a rural coastal area. The development of this region is critical to Nigeria’s socio-economic growth. One of the key factors that have been identified to have a significant impact on the development of this region is geosciences education. Geoscience education helps to develop a better understanding of the natural environment, including the processes that have shaped it and the various resources available to it. This abstract presents an analysis of the impact of geoscience education in the rural coastal areas of the Niger Delta region of Nigeria. A review of existing literature on geosciences education and its impact on the development of rural coastal areas was conducted. The results show that geoscience education has significant potential in the development of the Niger Delta region of Nigeria. The research also indicates that geoscience education enhances awareness of the environmental challenges facing the region, engenders better adaptation to climate change, and underscores the importance of natural resources. Furthermore, geoscience education improves the competitiveness of the rural coastal area residents in the area of agriculture, fisheries, mining, and tourism. Therefore, it is recommended that geoscience education should be included in the curriculum of primary and secondary schools in the rural coastal areas of the Niger Delta region of Nigeria. As well as providing more opportunities for tertiary education and training in relevant geoscience subjects. Furthermore, the importance of these subjects should be widely publicized among community leaders, stakeholders, and residents to ensure they understand the positive impact on education and their development.