bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysing extreme sea levels on the Finnish coast using Block Maxima and Peak Over Threshold approaches
Authors: Leijala Ulpu , Johansson Milla , Pellikka Havu
Published: March 2024

Melting of the land-based ice and warming of the oceans around the world has resulted in acceleration of the pace of global mean sea level rise. Higher mean sea level causes more frequent extreme sea levels. This forces coastal cities urgently to do major preparedness and adaptation measures.In Finland, preparedness for coastal flooding hazards is relevant even though protection given by the post-glacial land uplift is helpful. This is especially true on the Finnish southern coast, where mean sea level rise is foreseen and increase of probability of high sea levels within the 21st century is expected (Pellikka et al., 2023, 2018). In the Finnish coastal area, the extreme sea level estimates are used e.g. to support infrastructure planning, flood maps and safe operation of nuclear power plants.On a short timescale, sea level variations are driven on the Finnish coast by storm surges, wind induced oscillations within the bays, and tides (playing a minor role). On the long-term side, global mean sea level rise, land uplift and the water inflow and outflow in the Danish straits (which change the total amount of Baltic Sea water) are the main factors controlling the sea level behaviour.In this presentation, a study aiming at improving extreme sea level estimates in Finland will be illustrated. Tentative results on how different sampling techniques and extrapolation approaches affect the probability estimates of coastal floods will be presented.Altogether 90 years of observations from the 13 Finnish tide gauges are analysed. We apply two different well-known sampling methods (Block Maxima and Peak Over Threshold) to the high tail of the sea level distribution and investigate which extrapolation function belonging to the family of Generalized Extreme Value (GEV) distribution matches best to the Finnish tide gauge observations. The results will be grouped into four coastal regions in Finland: the Gulf of Finland and Archipelago Sea in the south, and the Bothnian Sea and Bay of Bothnia in the west. Pellikka, H., Johansson, M. M., Nordman, M., and Ruosteenoja, K., 2023: Probabilistic projections and past trends of sea level rise in Finland, Nat. Hazards Earth Syst. Sci., 23, 1613–1630, https://doi.org/10.5194/nhess-23-1613-2023Pellikka, H., Leijala, U., Johansson, M. M., Leinonen, K., Kahma, K. K., 2018: Future probabilities of coastal floods in Finland, Continental Shelf Research, 157, 32-42, https://doi.org/10.1016/j.csr.2018.02.
UAV-based LiDAR and Multispectral images for forest trait retrieval
Authors: Vignali Luigi , Panigada Cinzia , Tagliabue Giulia , Savinelli Beatrice , Garzonio Roberto , Colombo Roberto , Cogliati Sergio , Gentili Rodolfo , Citterio Sandra , Rossini Micol
Published: March 2024

Woodlands cover 41% of the surface of the European Union and contribute to human well-being through the ecosystem services they provide. However, their extension and condition are under threat due to the impacts of climate change. Forest traits are commonly used in ecological and climate studies for the assessment of plants health status. In this contest, the use of unmanned aircraft vehicles (UAVs) is rapidly developing for forest monitoring and inventory. UAVs allow to acquire high spatial resolution data using different sensors, as LiDAR or optical sensor, with low operational costs. The main focus of this contribution is integrating LiDAR and multispectral data to detect and classify single trees and retrieve forest traits at tree scale employing machine learning approaches. The study area is a natural reserve located in the Ticino Valley Regional Park, in eastern Lombardy along the Po river (Italy). An intensive field campaign was conducted in the summer of 2022 to collect forest traits (leaf chlorophyll concentration - LCC and leaf area index - LAI) and UAV data. The UAV mounted a DJI L1 LiDAR sensor and a MAIA S2 multispectral camera. First, the individual trees were identified using the “lidR”, “rLidar” and “ForestTools” R packages. Each tree was then classified using a Random Forest classifier with an accuracy of 84% (Kappa coefficient =0.74). For the retrieval of the forest traits of interest, different machine learning regression algorithms (MLRAs) were tested. LAI was best estimated by the Gaussian Processes Regression (GPR), (R2=0.903, nRMSE=8.66%) and the Canopy Chlorophyll Content (CCC = LAI x LCC) by the Support Vector Regression (SVR) (R2=0.8327, nRMSE=9.1684%). MLR algorithms showed satisfactory performances in plant trait retrieval in forest ecosystem from UAV, opening interesting perspectives for forest monitoring, both at leaf and canopy level except for the LCC.
Regional mapping of soil organic matter and particle size in Northeast China using hyperspectral satellite images
Authors: Shang Kun , Xiao Chenchao , Tang Hongzhao
Published: March 2024

Soil organic matter (SOM) and particle size are key indicators for evaluating cultivated soil quality. Conventional soil quality surveys based on field sampling are resource-intensive and can only obtain the data at sampling points, making it difficult to meet the needs of plot-level cultivated land management. In recent years, a series of hyperspectral satellite sensors have provided an important data source for the estimation of cultivated soil parameters. In this study, we took all 1.26 million km2 of cultivated land (including paddy fields, dry land, and irrigated fields) in Northeast China as the study area. In April 2021, we conducted a synchronized sample collection experiment utilizing ZY1-02D satellite hyperspectral data, gathering a total of 171 soil samples. More than 1,400 hyperspectral images of satellites including GF5, ZY1-02D and ZY1-02E covering the entire study area were collected and preprocessed. Firstly, we developed a bare soil identification method by combining cultivated soil spectral library, spatial-spectral filtering, and spectral angle mapping. The average accuracy of bare soil identification results varies from 90% to 95%. Secondly, we analyzed the correlation between soil parameters and dual-band spectral indices using multi-platform observed data, as well as the radiation quality of massive satellite images. Combining the results of spectral band radiation quality analysis, the optimal spectral indices of SOM, sand, silt, and clay were constructed based on the collaborative observation of multi-source data. Then, we developed a soil parameter prediction model that combines topography and spectral information. In this research, a new feature selection technique called VIP-CARS-Frog based on multi-index evaluation, which combines three algorithms including variable importance plots, competitive self-organizing selection, and random frog, was proposed to select high-quality and stable features. These technologies have been successfully applied to hyperspectral satellite data such as GF5, ZY1-02D, and ZY1-02E to map the spatial distribution of SOM and particle size in cultivated land in Northeast China. The inversion results of SOM, sand, silt, and clay have R2 of 0.84, 0.9, 0.79 and 0.76, RMSE of 5.16g/kg, 7.16%, 7.25% and 4.7%, and RPD of 2.32, 2.87, 1.72, and 1.73, respectively. From the results, it can be seen that in Songnen Plain and Sanjiang Plain, where black soil and chernozem are concentrated, the SOM content is higher and the sand content is lower. On the contrary, in the southwestern region, the sand content is higher and the SOM content is lower. The results indicate that hyperspectral satellite images can be used to estimate SOM and particle size content at a regional scale, showing its great potential in cultivated land quality surveys and agricultural precision management.
Short-term water demand forecast considering SPEI and climate indices
Authors: Stelzl Anika , Fuchs-Hanusch Daniela
Published: March 2024

Water demand is influenced by a number of factors with temperature and precipitation being among the key elements. Especially during longer dry and heat periods, water demand changes due to changes in consumption patterns, filling of swimming pools and increased garden irrigation. Therefore, a reliable water demand forecast is very important for Austrian water utilities in order to be able to react to increasing water demand peaks. In a previous study (Stelzl A.; Fuchs-Hanusch D.), long-term forecasting models were developed using climate indices. The developed modeling approach achieved satisfactory results in terms of prediction accuracy. However, it was found that the effect of dry and hot periods could not yet be modeled with sufficient accuracy. For this reason, this study attempts to improve the modeling approach by adding the Standardised Precipitation Evapotranspiration Index (SPEI) as an additional parameter into the model. In addition, the new work targets short-term water demand forecasts to provide water utilities with a basis for taking timely action to cope with peak water demand or inform customers about necessary water saving measures. Current short-term forecasts of the meteorological situation (e.g. SPEI) are provided by Land Steiermark (Land Steiermark, 2024). The water demand forecasting model developed in this study can be applied to these short-term forecasts.In a first step, the relationship between SPEI, climate indices and water demand was determined. The SPEI and the climate indices are calculated from historical weather records for the selected study sites. During the model building process, a stepwise forward variable selection process is carried out to determine the significant parameters. The SPEI was found to be a significant parameter for water demand forecasting. The model building process and evaluation is still ongoing. It is expected that the use of the SPEI will improve the accuracy of peak water demand forecasting model. The final results will be available at the conference.References:Stelzl, A.; Fuchs-Hanusch, D. Forecasting Urban Peak Water Demand Based on Climate Indices and Demographic Trends. Water 2024, 16, 127. https://doi.org/10.3390/w16010127Land Steiermark, A 14 (2024) Dürreindex - Wasserversrogung. [online] https://www.wasserwirtschaft.steiermark.at/cms/beitrag/12903795/173854972. (Accessed:  10. January 2024) 
SAR and Optical Remote Sensing for Flood Mapping and Monitoring through GEE
Authors: Giannone Francesca , Guerrisi Erik , Scaglione Massimo , Di Francesco Silvia
Published: March 2024

The work explores the use of Synthetic Aperture Radar (SAR) and optical sensors on board the Sentinel-1 and Sentinel-2 satellites for mapping and monitoring the Earth's surface in response to flood events. The choice of SAR proves advantageous due to its ability to penetrate clouds, ensuring continuity in acquisitions even in adverse weather conditions.  The Google Earth Engine (GEE) platform, which provides the opportunity to customize algorithms and scripts, is used to perform the analysis. The goal is to develop an integrated methodology for early warning and impact mitigation. Two case studies are here presented: the flood that affected Ravenna in May 2023 and  the Apollo hurricane in Sicily in 2021. The results confirm the effectiveness of the proposed approach in monitoring and discriminating water-covered surfaces. Despite challenges in data processing and calibration, the approach proves to be a valuable monitoring tool. The integration of SAR and optical data provides a comprehensive view of the flood situation, confirmed by the convergence of information from both satellites and news services.
Morphological changes associated with the drier and windier LIA in the Danube delta
Authors: Preoteasa Luminita , Tsukamoto Sumiko , Timar-Gabor Alida , Zainescu Florin , Vespremeanu-Stroe Alfred
Published: March 2024

This study reports on the Letea dune field - the largest of this type in the Danube delta - and on the Sărăturile beach ridge plain, which both displayed the largest morphodynamics during the Little Ice Age (LIA: 1450 – 1850).
The reconstructed morphodynamics of the two deltaic units are based on GPR scanning of the marine and aeolian structures and OSL dating, which aimed to track the sea level curve, and the aeolian activity archived in these coastal barriers. The earliest aeolian features preserved in the modern Letea barrier landscape appeared ca. 2400 years ago as shore parallel foredunes and continued to form as such until ca. 770 years ago. Still, under the constant predominantly northern winds, they have been reworked into an extensive dunefield mostly between ca. 1500 and 1800 AD. The dunefield is composed of four large parabolic complexes containing parabolic dunes, precipitation ridges and remnant knobs as common morphotypes.
Intense dune activity during LIA was spurred by a significant river flooding during the 14th century AD, which caused the displacement of the Chilia distributary position and the subsequent beach ridge plain and dune truncation. High rates of dune mobility were maintained by the cumulative effect of the drier and windier climatic conditions, probably slightly lower sea level of the Black Sea during the Little Ice Age, and local deforestation during the Ottoman occupation of the Danube delta.
The most prominent ridge in the Sărăturile ridge plain developed 350-250 years ago, suggesting increased marine and aeolian energy, contributing to a larger sediment supply into the foredune.
Comparing mitigation, adaptation and residual damage costs under different socio-economic and climate scenarios
Authors: van der Wijst Kaj-Ivar , Hof Andries , de Bruin Kelly , van Vuuren Detlef
Published: March 2024

Future socio-economic development plays a crucial role in both climate policy and the impacts of climate change. In this study, we for the first time systematically compare the costs of mitigation, adaptation, and residual damage for different socio-economic and climate scenarios known as the Shared Socio-economic Pathways (SSPs). For this, we combine recent damage estimates with adaptation costs and introduce differences in the effectiveness of adaptation based on the SSP projection. The results can be presented in terms of SSP/RCP matrix, with optimal climate outcomes as a function of SSP. The results can also be used to identify critical factors determining the optimal temperature, including socio-economic development, technology development and limits to mitigation and adaptation. The socio-economic limits to adaptation lead to damage costs that are 15% to 60% higher than if optimal adaptation had been possible. Overall, this study demonstrates that the socio-economic developments assumed in the SSP, including inequality reduction and institutional strength, can be equally important for the optimal outcome as the factors typically studied such as discount rate.
Black Markina: an ornamental basque limestone (Spain)
Authors: Damas Mollá Laura , Aranburu Arantza , Bodego Arantxa , Yusta Iñaki , Ladron de Guevara Martin , Ilin Andrey , Antiguedad Iñaki , Uriarte Jesus Angel
Published: March 2024

Black Markina is a limestone that has been exploited for more than 100 years as an ornamental and construction stone in the Basque Country (Spain). This stone is of great international interest and is well known for the intense black colour it acquires when it is polished. Nevertheless, in natural outcrops and in construction elements with other finishes the colour that characterises it is more or less dark greyish. 
The Markina Limestone Formation is located in the Basque Arc, to the north of the Basque-Cantabrian Basin. It was formed on a shallow subtropical carbonate marine platform during the Aptian/Albian. The main facies are biomicrites with a dark micritic matrix containing abundant fossils that contrast with the white colour: tabular corals in life position, as well as branching and hemispherical corals and Chondrodonta sp. colonies, rudists and gastropods. These facies are well stratified and sometimes a certain degree of transport is observed. Among these facies, those with few carbonate bioclasts and abundant orbitolines (binders) stand out. These facies correspond to the most commercially valued stone variety due to its more homogeneous black tone. 

The origin of the intense black colour of this lithology has not been resolved: on the one hand, the existence of organic matter disseminated in the matrix (on a microscopic scale) and in the interior of the fossils in the form of masses of pseudovitreous appearance (opaque under the optical microscope) has been confirmed. This organic matter already gives the matrix a dark basic tone. On the other hand, the presence of certain minerals such as nanometric magnetite or cubic and framboidal pyrite disseminated in the matrix, smaller than a micron in size, could be what intensifies the black colour when polished. 

The variety of ornamental stone known as Black Markina florid corresponds to facies with diagenetic features, mainly white, contrasting with the intense black of the matrix. In this sense, a generalised recrystallisation/neomorphism of the fossil remains is recognised and different late fracture systems filled with white calcite crystals also stand out. 

Markina village is an example of the use of local stone as a distinctive feature that defines its landscape. Numerous palaces (Ansotegi, 16th century; Gaitan de Ayala or Patrokua, 17th and 20th centuries), religious buildings (Church of La Merced, 18th century) and other architectural elements such as the sculpture in homage to Juan Antonio Moguel (20th century) or the cobblestones of several streets in the municipality have been preserved. Black Markina can also be recognised in elements from other countries as emblematic as the hall of the Empire State Building or the lectern of the United Nations headquarters, both located in New York, or the Kaaba of Mecca (Saudi Arabia). 
FAIR Workflows and Methods for Scaling
Authors: Wilkinson Sean R.
Published: March 2024

The FAIR Principles, originally introduced as guiding principles for scientific data management and stewardship, also apply abstractly to other digital objects such as research software and scientific workflows. When introduced to the FAIR principles, most scientists can see that the concepts behind the FAIR principles — namely, to make digital objects Findable, Accessible, Interoperable, and Reusable — will improve the quality of research artifacts. It is less common, however, that scientists immediately recognize the ways in which incorporating FAIR methods into their research can enable them to tackle problems of greater size and complexity. In short, focusing on making artifacts that are reusable in the FAIR sense makes those artifacts reusable by humans as well as machines, thus enabling computational workflows that handle scaling issues automatically and someday even self-assemble. Here, we will discuss recent community developments in FAIR computational workflows and how they can impact the earth sciences now and in the future.
Rise and fall of lead (Pb) pollution in East Asia:  lessons learnt from a 60-yr long modern coral
Authors: Lin Ke , Chen Mengli , Chen Yue-Gau , Wang Xianfeng
Published: March 2024

Despite the global phase-out of leaded gasoline, lead (Pb) pollution remains a persistent and serious issue, particularly in developing nations. To portray the temporal dynamics of Pb emissions and their responses to evolving policy interventions in Asia, we reconstructed a 60-year record of Pb concentration (Pb/Ca) and isotopic composition (i.e., 206Pb/207Pb and 208Pb/206Pb) in a coral from Dongsha Atoll, the South China Sea. Our study reveals a fourfold increase in coral Pb/Ca levels from 1953 to mid-2000s, followed by a ~ 60% decline in the subsequent decade. In the early era from 1953 to 1960, Pb isotopic compositions in the Dongsha coral align closely with the values in natural marine sediments. When anthropogenic Pb sources became to prevail, we observe an increase in Pb/Ca values and altered isotopic compositions, attributable mostly to automotive Pb emissions but also with significant contribution from industrial Pb emissions especially after 1990s. With Pb isotopic analysis on the coral, we identify that, after 1990s, the Chinese Pb was the primary endmember that impacts the regional Pb. The influence of Chinese Pb is also registered in other East and Southeast Asian coral records, probably also in those from the Indian Ocean. The increasing trend of Pb in these records underscores the necessity to reduce Pb emissions in the post-leaded gasoline era, particularly in developing countries in the region. On the other hand, the decline in Pb/Ca in our record after the mid-2000s provides encouraging evidence of the positive impact of environmental policies in safeguarding the environment and public health.

 
Superresolution color images from the sparse data cubes of the Hyperscout-H hyperspectral imager aboard the Hera mission
Authors: Grieger Björn , de León Julia , Goldberg Hannah , Kohout Tomas , Kovács Gábor , Küppers Michael , Nagy Balázs Vince , Popescu Marcel
Published: March 2024

On 26 September 2022, NASA's Double Asteroid Redirection Test (DART) mission impacted Dimorphos, the moonlet of near-earth asteroid (65803) Didymos, performing the world's first planetary defence test. ESA's Hera mission will be launched in October 2024 and rendezvous with the Didymos system end of 2026 or beginning of 2027. It will closely investigate the system and in particular the consequences of the DART impact.  Hera carries the hyperspectral imager Hyperscout-H. Its sensor consists of 2048 x 1088 pixels which are arranged in macro pixel blocks of 5 x 5 pixels. The 25 pixels of each block are covered with filters in 25 different wavelengths where the center response ranges from 657 to 949 nm. Therefore, each of the 2048 x 1088 pixels provides only the brightness information for one wavelength and hence the theoretical 2048 x 1088 x 25 data cube is only sparsely populated. A simple straight forward approach to replenish the sparse data cube would be to move a 5 x 5 pixel window with one pixel steps horizotally and vertically over the whole frame and assign the obtained 25 wavelength spectrum to the center pixel of the window. Besides reducing the image resolution to the quite coarse macro pixels, the accuracy of this method is limited by pixel to pixel variations of the spectra and even more by varying albedo and shading effects caused by varying surface inclination. This makes the resultant spectra very noisy. In order to retrieve more accurate spectra with higher spatial resolution, we separate the spectrum at each micro pixel into a normalized spectrum and a brightness scaling factor. We assume the normalized spectra to be spatially smooth, but not necessarily the scaled spectra. Ratios of measured values are used to iteratively compute the normalized spectral value from adjacent pixels. After convergence, the spectra are brightness scaled to reproduce the measured values. This approach allows to replenish the complete data cube with full micro pixel resolution. The application to test images shows that spectra are recovered much more accurately than with the direct approach and that only very little spatial detail is lost. Having replenished the complete data cube allows us to construct color images at full micro pixel resolution. The three colors are sufficient to capture most of the spatial variation of the spectra of asteroid surfaces and hence the constructed color images provide a concise visualization of the respective full data cubes. 
Erosion rate of the north polar steep scarps on Mars
Authors: Su Shu , Fanara Lida , Xiao Haifeng , Hauber Ernst , Oberst Jürgen
Published: March 2024

Mass wasting activity, in the form of ice block falls, has been observed as the main erosion process at steep scarps of the North Polar Layered Deposits (NPLD) [1,2]. Our study focuses on leveraging a state-of-the-art deep learning technique to map the sources of such events throughout the entire NPLD region. By quantifying water ice loss, we derive the current erosion and retreat rate for each active NPLD scarp. We notice that these scarps have varying degrees of erosion, from less than 0.01 up to 0.88 m3 per Mars Year per meter along the scarp. The current most active scarp shows a retreat rate of ~6 mm per Mars Year. We want to compare our results to the detected ice block falls at the underlying Basal Unit (BU) region [3], to understand the difference between the two units’ geological processes, and help to constitute important constraints to the present-day mass flux of the north polar region. References[1] Herkenhof et al., 2007. Science, 317(5845), pp.1711-1715.[2] Dundas et al., 2021. J. Geophys. Res. Planets, 126(8), p.e2021JE006876.[3] Martynchuk, et al., 2023. AGU23, 11-15 Dec.
Inorganic biogenic carbon redistribution and transport in marine sediments
Authors: Hewage Prabodha Lakrani , Mejía Luz María , Haghipour Negar , Saavedra-Pellitero Mariem , Trundley Ben , Eglinton Timothy , Hodell David , Ausín Blanca
Published: March 2024

Coccolithophores are calcifying marine phytoplankton whose blooms can be seen from space and play an important, yet complex, role in the global carbon cycle. On one hand, coccolithophores sequester atmospheric CO2 to the deep ocean via photosynthesis contributing to the biological pump. On the other hand, coccolithophores increase aqueous CO2 via precipitation of tiny calcite scales named coccoliths (i.e., carbonate counter pump), which are a major component of marine sediments. Coccoliths are generally in the 2-20 µm size range, and thus they can be winnowed by strong currents and transported to distal locations. Here, we show the first coccoliths radiocarbon (14C) ages and explore the influence of size-dependent coccolith sorting and transport, redistribution, and fate in marine sediments. Because the coccolith depends on the species, we have separated and 14C dated four coccolith size fractions: 8-11 µm, 5-8 µm, 3-5 µm, and 2-3 µm, in  five depth intervals on a sediment core recovered from SHAK06-5K site, off the Iberian Margin. Coccolith separation was achieved by a combination of dry sieving, microfiltration, centrifugation, and settling experiments. Energy Dispersive Spectroscopy (EDS) images of selected size fractions were used to estimate the relative contribution of coccolith and non-coccolith carbonate. A relationship between coccolith 14C age and grain size is apparent in all samples, with the smallest size class recording the youngest ages and the largest coccoliths being the oldest. The latter suggests that hydrodynamic sorting largely influences coccolith redistribution in marine sediments, where larger coccoliths result in increased mobility, as they are prone to resuspension than coccoliths in 2-3 µm size fraction that tend to show cohesive behaviour. The 14C ages of coccoliths are older than those of co-deposited planktic foraminifera, bulk organic carbon (OC), long-chain fatty acids (LCFA), and alkenones. Coccoliths within the 2-3 µm size class show 14C ages comparable to those of OC in all samples. Such a pattern indicates similar transport mechanisms for both the smallest coccoliths and OC, and that the majority of carbonate in the 2-3 µm size fraction, including the non-coccolith particles, is predominantly derived from marine primary production and thus, of biogenic origin. Our study has implications for palaeoceanographic studies using coccoliths as paleo-productivity and geochemical proxies.
Structural elements from gravity and magnetic data in the Phlegrean Fields
Authors: Florio Giovanni , Fedi Maurizio , Di Vito Mauro , Cella Federico , Paoletti Valeria
Published: March 2024

A comprehensive analysis of the gravity and magnetic fields of the Phlegrean Fields volcanic area reveals a complex structural setting. High resolution techniques, including multiscale boundary analysis and field transformations, highlight the position of density and magnetization boundaries of the Phlegrean Fields. The structural elements of the two datasets appear in a general agreement, but at the same time present differences, so yielding a complex and rich picture of the collapsed Phlegrean caldera and of the surrounding areas. Inside the caldera, a good consistence among some structural elements identified from our analysis and the seismicity can be established. Some hypotheses about the geological significance of the gravity and magnetic anomalies in the frame of the Phlegrean volcanological context are finally set up.
Progress in the Global Sea Level Fingerprints since the 20th century
Authors: Liu Yuxin , Deng Shanshan , Zhang Wenxi , Hu Ange
Published: March 2024

Ocean mass change is the primary driver of sea level rise. Understanding the mechanisms of mass sea level change can help coastal areas scientifically respond to climate change. Under combined the self-attraction and loading effect and the Earth's rotational feedback, land-source freshwater input leads to global spatiotemporal heterogeneity of mass sea level, known as Sea Level Fingerprints. In this study, Sea Level Fingerprints were simulated under three different scenarios, covering periods from January 1901 to July 2019, January 1981 to June 2020, and July 1979 to June 2020. These scenarios encompassed: (1) consideration of climate variability alone; (2) consideration of both climate variability and actual glacial mass balance; and (3) alignment with recent climate change trends. The study aimed to analyze the contribution of Sea Level Fingerprints to satellite-derived mass sea level across these three scenarios. Results showed that in all three scenarios, the significant seasonal amplitude regions include the South China Sea and the Bay of Bengal, with peak values ranging from 42.60 to 45.20 mm. Changes in mass sea level are primarily caused by climate variability. Sea Level Fingerprints, which considered only precipitation and temperature as key indicators of climate variability, best reproduced the variation signal of the GRACE-derived data and the Altimetry-derived mass component. The spatial similarity coefficient derived between their global change range distributions were 0.67 and 0.87, respectively. Sea Level Fingerprints, which additionally considered glacial mass balance, provided a more accurate depiction of the spatial distribution and long-term trend of mass sea level derived from Altimetry satellites and Argo systems. This was demonstrated by the similarity between the sea-level fingerprints and altimetry-derived mass components across global long-term trend distribution patterns, with a spatial similarity coefficient of 0.75. The main contributing regions to these patterns include the Greenland Ice Sheet, Alaska, the Southern Andes, the Caucasus, the Middle East, and West Antarctica.
Paleoenvironmental variations in the coal-bearing deposits of the Lower Gosau Subgroup (Turonian to Campanian) in the Northern Calcareous Alps, Austria.
Authors: Xiang Xinxuan , Lee Eun Young , Wagreich Michael
Published: March 2024

The Gosau Group is a terrestrial to deep-water succession formed on the northern margin of the Austroalpine microplate during the early stages of Alpine orogenesis. The sedimentary characteristics of the Gosau Group reflect the paleoenvironment of the Northern Calcareous Alps from the Late Cretaceous to the Eocene. It has been divided into the Upper Gosau Subgroup and the Lower Gosau Subgroup based on the sedimentary facies. The Lower Gosau Subgroup indicates a transitional environment from terrestrial to shallow water. It has been subdivided into the Lower Gosau Subgroup, composed of fluvial, lacustrine to shallow marine sediments during the Turonian to Santonian-Campanian, and the Upper Gosau Subgroup, characterized by deep-water succession up to Eocene in age. The shallow to deep environmental transition was derived from the subsidence of the continental margin, associated with the subduction of the South Penninic Ocean. However, details of the Late Cretaceous environmental variations have not been understood enough for reconstructing the formation of the Gosau Group. This study investigates environmental signals by analyzing coal-bearing deposits in the Lower Gosau Subgroup. We selected seven outcrop sites including coal seams ranging from the Turonian to Campanian in Austria, which showed fluvial and/or lacustrine depositional settings, and collected fourteen coal samples. Based on the industrial analysis and vitrinite reflectance, the samples were evaluated as low to medium ranks. Our results indicate a wide range of variations in silicon oxides, organic matters, and clay contents that are related to changes in depositional environment and water energy. These correspond to occasional occurrences of pyrite and carbonates, which could have been caused by interaction with seawater. Changes in the marcel contents also could be influenced by varying water level. Our study suggests that the coal-bearing sediments of the Lower Gosau Subgroup in Austria were deposited in unsteady environments and occasionally affected by seawater, which might correspond to the short-term sea-level fluctuations.
Investigating the Impact of Aerosols on Liquid-Origin Cirrus from Global Observations and Reanalysis Data
Authors: Sourdeval Odran , Saiprakash Athulya , Coopman Quentin , Bucci Silvia , Müürsepp Tuule
Published: March 2024

Complementarily to their formation mechanism, the origin of cirrus (liquid or in-situ) can substantially affect their microphysical and radiative properties. Liquid-origin cirrus, which stem from the freezing of water droplets at cirrus temperatures, are typically characterised by high ice crystal concentrations and associated with strong cooling effect. However, the global occurence and distribution of this cirrus type as well as the environmental conditions in which they originate. The role of aerosols on liquid-origin cirrus, through their influence on liquid clouds, is also not well understood but can be critical for understanding radiative forcings associated with aerosol-cloud interactions and in implications of potential geo-engineering strategies.This study investigates cirrus by coupling satellite and reanalysis dataset. Observations from lidar-radar satellite instruments (DARDAR-Nice) provide detailed retrievals of cirrus microphysical properties, such as ice water content and crystal number concentration. To trace the origins of cirrus clouds, we employ Lagrangian air mass trajectories based on ERA5 reanalyses, using FLEXPART. The presence and role of aerosols during the formation phase of these clouds, either in mixed-phase or warm regions, are assessed by integrating these trajectories with aerosol reanalysis products, specifically from CAMS. This joint cloud-aerosol dataset from satellite and reanalysis tools is created for one year of satellite observations. The global occurence of liquid-origin cirrus is analysed. The role of aerosols on the formation of liquid-origin clouds is finally investigated, in particular to understand the relevance of low-level aerosols on cirrus properties. Associated radiative effects will also be explored.
Scaling of Precipitation in the Alps: Insights from a Convection Permitting Regional Climate Model Ensemble
Authors: Lehmann Luna Santina , Velasquez Patricio , Ossó Albert , Schär Christoph
Published: March 2024

Previous studies predict an intensification of heavy precipitation events with climate change. These events are widely known to cause natural disasters with great property damage and loss of life, like flash floods or landslides. Knowledge about the scaling of precipitation, referring to the changes of precipitation intensity to warmer temperatures, is important for effective mitigation measures. Previous studies have investigated this scaling with regards to the Clausius Clapeyron relation, over various regions worldwide, using observational as well as model data. In this study we analyze the precipitation scaling over an orographically complex region as the Alps, as well as compare different methods to obtain the scaling rate.To this end, we employ a 10-year multi-model ensemble of kilometer-scale convection-permitting climate model (CPM) simulations over the Greater Alpine Region from the CORDEX-FPS, with a spatial resolution ranging from 2.2 to 4 km. These simulations were obtained by downscaling global climate model (GCM) projections to intermediate regional climate models (RCMs), which were in turn further downscaled to kilometer scale by convection permitting climate models (CPMs). Previous work has shown the added value of these CPMs compared to lower resolution RCMs especially for extreme precipitation. We analyze these simulations over four alpine subdomains, which are characterized by different climatological characteristics.In the calculation of precipitation scaling rates, we use two different precipitation indices, wet-hour percentiles and all-hour percentiles. These indices differ in that the latter encompasses all events, wet and dry, whereas the wet-hour percentile only includes events that go over a certain threshold. We compare the scaling calculated using these precipitation indices on an annual and seasonal basis, to show insights into the mechanisms that may cause scaling rates to exceed expectations given from the Clausius Clapeyron relation. Our results show that future precipitation intensity may be inferred from present-day scaling. The seasonal analysis shows scaling exceeding the Clausius Clapeyron scaling in the summer and autumn seasons for the wet-hour analysis, but not for the all-hour analysis.
Exploring the influence of land-atmosphere interactions on humid heat extremes in a convection permitting model simulation
Authors: Chagnaud Guillaume , Taylor Chris , Birch Cathryn , Jackson Lawrence , Marsham John , Klein Cornelia
Published: March 2024

Ambient humidity reduces the ability of the body to cool down through sweating, adding to the heat stress caused by elevated air temperature alone. Indeed, humid heat waves (HHWs) are already a threatfor humans, livestock and wildlife, and their impacts are projected to increase with global warming.HHWs result from the combination of thermodynamic and dynamic processes interacting on a range of time and space scales and whose relative importance may vary according to location and time of year.Africa is one continent where HHWs, defined here as extremes of wet-bulb temperature (Twb), are expected to become more important under global warming. Local-scale humid heat extremes may occur within more moderate larger-scale events across much of the continent. Yet, climatological characteristics of these smaller-scale events such as location and timing (in year and day) are poorly documented in the current climate, due to a lack of high-resolution data and research focus. Moreover, a comprehensive understanding of their meso- to synoptic-scale drivers is still lacking. Here, we explore these two issues using a 10-year pan-African convection-permitting model simulation that explicitly resolves land-atmosphere interactions, and particularly those involving moist processes that are instrumental to HHWs.We find humid heat extremes in semi-arid regions occurring in the core of the rainy season, on length scales down to a few tens of kilometers. During HHWs, Twb peaks several hours later than the climatological peak in the late morning. This diurnal cycle shift is likely due to HHWs typically developing in the aftermath of a rainfall event: the resulting positive anomaly in soil moisture induces increased latent heat fluxes, low level divergence, and a reduced PBL height, all ingredientsdisplaying sharp spatial gradients conducive to locally high Twb values. These results have implications for the improvement of localized HHW predictability based on local soil moisture conditions, a key step towards climate change adaptation through e.g., early-warning systems.
The course of microplastics before and after UK WWTPs and their release into the environment.
Authors: Grassineau Nathalie , Eldridge Louise , Rossouw Simone
Published: March 2024

Plastic has become an invasive material in modern human lifestyle and is heavily relied upon as an essential resource. It is identified as one of the chief environmental problems. Although identified primarily into marine environments, the main source of the plastics is from land and is discharged into our shores via rivers. To be able to lessen their impacts into the ocean, it is important to understand how to reduce their production upstream. This research is focussing on the fate of the secondary microplastics (MP) from when they leave the household with the greywaters to when they are released via the WWTP (wastewater treatment plant) discharges into our urban rivers.The household laundry of synthetic textiles has been recognised as one of the largest sources of MP production. This counts for most of the MPs leaving our home via greywaters to reach urban WWTPs. Consequently, the study has focussed on MPs released from 24 washing machine loads, consisting of well-catalogued and weighed various combinations of synthetic garments, under “normal wash conditions”. It was determined that an average load can produce up to 93,000 MP fibres per kg, but it was found that heavier loads released fewer MP fibres. Using a full washing load can reduce the number of fibres produced by up to 70%.To estimate the release of MPs into freshwater rivers from WWTPs, six discharges from urban plants from middle size towns around Greater London have been sampled and analysed. It was found that although MP quantities are very high the numbers vary greatly due to the age and the size of those sites, but also the technique that is used. It results in a range between 0.5 and 18 million MP per hour being released. This highlights that WWTPs are not advanced enough to remove MP pollution, making these discharges the main source into the freshwater environment.Furthermore, the MP release from plant discharges into rivers is not the main secondary source as up to 98% of the MPs passing through WWTPs might end up as sludge that can later be applied to improve agricultural land for higher crop yields. This creates a major source of MP fibres into our rural rivers upstream of the urban hubs. Not only does this introduce microplastics to terrestrial habitats but it also creates a direct secondary pathway for microplastics to enter surface waters. This study highlights the urgency to update wastewater treatment and disposal practices to tackle the various issues of fibres getting into surface and groundwaters.
Active faulting and seismogenic potential in low-strain rate southern Tuscany (Italy)
Authors: Burrato Pierfrancesco , Brogi Andrea , Vannoli Paola , Zucchi Martina , Fracassi Umberto , Valensise Gianluca , Hu Hsun-Ming , Shen Chuan-Chou
Published: March 2024

We explored the behaviour and earthquake potential of an active fault system in the slowly deforming part of southern Tuscany. This region corresponds to the eastern margin of the Siena Basin, a Neogene structural depression that developed during the extensional tectonics that affected the inner northern Apennines. Here, N-, NE- and WNW-trending faults were active during the Zanclean-Latest Quaternary. Clear evidence of the activity of these faults, particularly the most recent WNW-striking ones, is represented by faulted Late Pleistocene-Holocene travertine deposits that preserve also evidence of active seismogenic faulting. Indeed, this area in recent times was mostly interested by low-magnitude seismic sequences that occurred in the uppermost 10 km of the crust, mainly characterized by transcurrent and transtensive faulting mechanisms. However, the historical record includes also damaging earthquakes in the 5.0-6.0 Mw range, such as the 7 August 1414, Mw 5.7, Colline Metallifere, 13 April 1558, Mw 6.0, Valdarno Superiore, and 25 August 1909, Mw 5.3, Crete Senesi events, but, to date, very little is known about the geometry, maximum earthquake potential and slip rate of their causative faults.In this study, we characterize an active, capable, and seismogenic fault system identified in the saw-cut walls of an active travertine quarry near Serre di Rapolano, a few kilometres south-east of the city of Siena. To document the geometric and kinematic features of the active faults, we carried out a detailed geological and structural field survey of the quarry outcrop, collected samples for U-Th dating and constructed a virtual outcrop model. We found compelling evidence for nearly SW-NE surface-breaking faulting, perpendicular to the main structural fabric of the central and northern Apennines, whose activity extends at least into the Upper Pleistocene. The peculiar geology of the area also suggests that these faults have generated earthquakes associated with surface faulting, namely the occurrence of clastic dykes injected within the fault zones during earthquake-induced liquefaction.Our results may help to address the current lack of understanding concerning earthquake activity in the slowly deforming region, and improve the current knowledge of the seismotectonic setting of the Siena Basin and the corresponding part of the inner northern Apennines. Our findings hint to a still unexplored tectonic mechanism, which suggests that the earthquakes affecting this part of southern Tuscany may be caused by segments of rather elusive, very long, SW-NE and WNW-ESE lineaments crossing the entire Apennine stack.
Decoding Ocean Depths: Machine Learning Insights into Tidal Dynamics with UPFLOW’s OBS Data
Authors: Corela Carlos , Saoulis Alex , Tsekhmistrenko Maria , Loureiro Afonso , Miranda Miguel , Ferreira Ana
Published: March 2024

The iReverb project explores technical methodologies employed in the UPFLOW project, which addresses the challenges associated with tidal-induced noise on Ocean Bottom Seismometers (OBS) deployed in the North Atlantic Ocean. OBS sensors, unlike those on land stations, are exposed to oceanic currents, whose coupling with the instruments induces reverberations in the recordings. This project showcases a method for exploration of reverberations of tidally-modulated current-induced noise across different OBS types around the Azores, Madeira and Canaries region. The overarching objective is to present a comprehensive technical framework to enhance our understanding of Ocean Bottom Circulation (OBC), providing insights for calibrating current models. A central aspect of this project is the proposed utilisation of machine learning (ML) algorithms for automating the mapping of resonances and obtaining a proxy for OBC.Here, we present the iReverb methodology, involving manual curation of a pixel-level annotated spectrogram dataset, after this, a ML classifier is trained to identify features in each spectrogram (known as supervised semantic segmentation). To begin with, 15-minute spectrograms between 1-20 Hz are manually annotated using an open-source labelling tool. A deep Convolutional Neural Network (CNN), consisting of a ResNet Encoder, a UNet decoder, and a pixel-wise classification head, is then trained to classify features in each spectrogram using supervised learning. We explore the various factors, such as architecture changes to the CNN, that contribute to improving the model performance for annotating key features. We also discuss insights into attempted alternatives to standard supervised learning (semi-supervised and synthetic labels).Finally, we discuss the results and evaluate the effectiveness of the ML/DL approach in mapping resonances, demonstrating its potential in utilising resonances as signals for tracking ocean currents (and whales). This project was funded by the UPFLOW project (ERC grant 101001601). This work was partially funded by FCT I.P./MCTES through PIDDAC (UIDB/50019/2020, UIDP/50019/2020 and LA/P/0068/2020).