bluuebunny/crossref_metadata_2025 huggingface dataset:
Seismic hazard related to deep geothermal operations (Part I): identification of key criteria for hazard assessment 
Authors: De Santis Francesca , Maury Julie , Klein Emmanuelle , Peter-Borie Mariane , Contrucci Isabelle , Dominique Pascal
Published: March 2024

Deep geothermal projects can trigger seismic events depending on geological context and operations. This seismicity is generally of low magnitude but, in some cases, larger events may occur, which could lead to geothermal project abandonment and could present risk to neighboring populations. Thus, development of deep geothermal projects requires the management of induced seismicity to control it and to avoid any surface disturbance. It is from this perspective that, in 2023, Ineris and BRGM published a guide of good practices and recommendations for operators and French administration involved in deep geothermal energy.The guide provides recommendations for assessing geothermal-induced seismic hazard, depending on the type of geothermal system and its intrinsic and operational characteristics, at each key step of a project (i.e. from the exploration phase until the end of the project). A worldwide review of deep geothermal projects, carried out with the aim of identifying key factors triggering induced seismicity, has enabled the definition of the most relevant criteria to take into account in the hazard assessment. In this review, geothermal projects were chosen to be representative of different types of geothermal systems (e.g. deep sedimentary aquifers, volcanic and plutonic regions, deep dry crystalline basements, etc.) and operating conditions (e.g. well configuration, type of operation, etc.). Moreover, the review includes projects associated with several episodes of induced seismicity, ranging in magnitude from microseismicity (M < 2) to large seismic events (M > 5), as well as projects marked by the absence of induced seismic activity.From the 53 projects and 77 seismic episodes analyzed in this review, we can state that not all geothermal projects are equally prone to seismic events. The occurrence and the intensity of induced seismicity are the results of interactions between several natural (intrinsic) and anthropogenic (operational) factors, often concomitant and dependent on each other. Seismic response of analyzed projects appears to be largely different depending on the type of geothermal system. Indeed, the type of geothermal system characterizes reservoir porosity, as well as heat transfer and fluid circulation modes in the reservoir. Other key factors include the presence of faults that can be critically loaded and/or connected with the basement, the use of EGS technologies, and situations where injected and produced volumes are highly unbalanced. These results allowed defining key criteria for seismic hazard assessment methodology proposed within the good practice guide.
Construction and Calibration of Dripping Rainfall Simulator with a Single Dripper for Soil Research
Authors: Rončević Vukašin , Živanović Nikola , H. van Boxel John , Iserloh Thomas , Antić Nevena , Ferreira Carla , Spasić Marko
Published: March 2024

Dripping rainfall simulators for soil research generate water drops with different types of drippers, such as plastic and glass tubes, drippers in a form of holes, irrigation drippers and hanging yarn, among which metal tubes are the most commonly used. Metal tubes appear in the form of capillaries with a flat tip or in the form of hypodermic needles. Hypodermic needles are suitable for this purpose because their diameter size is standardized with relatively small deviations from the standardized dimensions, they are available on the market, relatively cheap, made of stainless material and have a threaded connector (Luer taper). However, very often the descriptions of the rainfall simulators were not complete, nor was the calibration of the needles. In order to conduct calibration and define water drops diameter for different hypodermic needles size and dripping speed, it was constructed rainfall simulator with one dripper in a form of hypodermic needle. Simulator was designed in accordance to research of Rončević et al., (2022), needle calibration research and future soil research requirements. Simulator was intended primarily for laboratory use. It consists of structural support, water tank, water pump, mechanism of water flow regulation and simulator operation, water tank with dripper and dripper. Calibration was conducted for 11 different needles, ranging in size from 16 G to 32 G (G – gauge number), at different dripping speed, using drop counting sensor. Water drops are measured using weight measuring method. Obtained water drops size ranging from 3.70 to 1.48 mm. Based on research data, two nomograms were made for determination of interconnected parameters of potentially simulated rainfall: water drops size under different dripping speed, drippers discharge, number of drippers, and kinetic energy of water drops for the given falling height. The results of research provide the data necessary for the design of future dripping rainfall simulators for soil research and use of hypodermic needles as drippers.
Green Remediation: Canna Indica for Sustainable Detoxification of Metals and Excess Nutrients
Authors: Bodana Dikshant , N Srivastava Abhishek , Vinnarasi Rajendran , K Jain Sharad
Published: March 2024

Rivers are susceptible to metal pollution arising from anthropogenic activities such as mining, industrial processes, and urban runoff. Metals from both natural and man-made sources enter the river system and either settle in the riverbed sediments or are distributed in the aqueous, floating matter. Under some environmental conditions, the accumulation of metals in river systems disrupts biological processes. Apart from metal pollution, the escalating concentrations of nutrients, specifically nitrogen and phosphorus into aquatic ecosystems are of growing concern. The excess concentartions of metals and nutrients pose severe environmental challenges such as lake eutrophication and groundwater pollution. Therefore, the sustainable solution to mitigate their adverse environmental effects is need of the hour.Phytoremediation is a green remediation technology that employs plants to remove, detoxify, or immobilize toxins from soil, water, or air. The plants and their related microbial populations improve water quality by absorbing, adsorbing, and transforming contaminants like metals, nutrients, etc. In this research, a pot study was performed to investigate the efficacy of phytoremediation. In the controlled environment, small-scale tests were undertaken to examine the growth, pollutant removal capabilities, and effectiveness of using specific plants for larger-scale applications. The target pollutants were heavy metals (As, Al, Ca, Cd, Co, Cu, Fe, Pb, Mg, Hg, and Ni), macro-nutrients (Na, K, and Ca), and micro-nutrients (nitrates, ammonia nitrogen, and phosphates). Experimental setup included polyvinyl chloride containers (5 L capacity) as the vessel (pot) for growing Canna Indica plants. Water sample from Ratanpuri in Hindon river, one of the highly polluted rivers in north India, was used for the treatment. Initially, the containers were ﬁlled with 2.5 L of growing medium (soil, sand and gravels), arranged in a block design, and the experiment was performed for ten days (two runs), depending upon their treatment efficiency. Initial and final characterizations of water samples were performed as per standard methods.The phytoremediation efficiency of all considered metal parameters through Canna Indica was observed in the range of 52-60 % which prospectively got absorbed via phytoextraction. Moreover, the efficacy of nutrient removal, was also obtained satisfactorily ranging from 60-78%. Considering removal efficiencies, phytoremediation using Canna Indica could be economically and environmentally sustainable for countering nutrient and metal pollution at field scale, provided its controlled monitoring is performed effectively. Pot-scale study results could be baseline that support usage of Canna Indica at field scale in wetland systems for detoxifying ecosystems and assuring soil and water quality restoration in the face of increasing anthropogenic demands.
How will interplanetary magnetic field topology modify solar wind kinetics?
Authors: Lin Rong , Lapenta Giovanni , He Jiansen
Published: March 2024

Recent observations of the interplanetary magnetic field have enlarged the magnetic field topology family in the inner heliosphere, and raises interest in the relationship between those topologies and the evolution of solar wind. For example, switchbacks that are kinks of magnetic field lines accompanied by velocity spikes and enhancement of the proton parallel temperature, have free energy both of the field and of the particles, and thus have potential for a series of plasma instabilities. It is favorable to extract elementary topologies from complicated structures like switchbacks before we look further in. Based on Particle-in-Cell simulations, we discuss from elementary topologies on the effect they have on kinetic processes of the solar wind plasma.
Exploring Biases and Long-term Trends in Tropospheric OH: A Synergistic Approach with Model Simulations, Interpretable Machine Learning, and Satellite Observations
Authors: Duncan Bryan , Souri Amir , Strode Sarah , Anderson Daniel , Manyin Michael , Liu Junhua , Oman Luke , Weir Brad
Published: March 2024

The accurate representation of tropospheric hydroxyl radical (TOH) is crucial for reasonably modeling methane concentrations — a potent greenhouse gas. We use an improved parameterization of TOH using an interpretable and agile machine learning module named ECCOH (pronounced "echo") in NASA's GEOS global model to unravel the intricacies of TOH to its key inputs. However, the accuracy of this model is hampered by the accurate representation of its critical inputs. Fortunately, retrieving trace gases like nitrogen dioxide (NO2) and formaldehyde (HCHO) from space-borne sensors, like the Aura Ozone Monitoring Instrument (OMI), has seen remarkable progress. Consequently, we leverage these observations to assess how they can effectively alleviate some biases in TOH and can help better reproduce its long-term trends. In contrast to the earlier investigations, the refined representation of TOH archives a finer spatial resolution (1x1 degrees), and it is more up to date (2005-2019), allowing for elucidating the impact of recent emission regulations, such as those imposed in China, on TOH. OMI NO2 yields valuable insights over biomass-burning areas in Eastern Europe and central Africa, where our prior emission estimates possess significant biases, mitigating regional TOH biases up to 20%. Oceanic HCHO concentrations, serving as a proxy for TOH due to the predominant chemical pathway of VOC oxidation through OH, are only moderately altered by OMI HCHO, attributed to low signal-to-noise ratios and satisfactory representation of HCHO in the a priori simulations. Ultimately, we disentangle the convoluted map of TOH linear trends by isolating five pivotal inputs to the TOH parameterization, including stratospheric ozone, tropospheric ozone, water vapor, HCHO, and NO2. Our results demonstrate that these five parameters can collectively explain 65% of the variability in TOH trends alone. With the deployment of new satellites with enhanced sensor configurations and better temporal resolutions, our mission at NASA is to exploit those observations to improve the representation of many variables highly linked to TOH.
Surface roughness: capturing rough-bed river diversity
Authors: Houseago Robert , Hodge Rebecca , Ferguson Rob , Hardy Rich , Hackney Chris , Rice Steve , Johnson Joel , Yager Elowyn , Hoey Trevor , Yamasaki Taís
Published: March 2024

Channel geometry and bed surface roughness modulate the flow resistance of river channels, which is fundamental to the conveyance of water and sediment. In rough-bed rivers, where the flow is shallow relative to roughness height, there is notable uncertainty in flow resistance calculations based on sediment percentiles (D50 or D84) or the standard deviation of bed elevations. A new approach based on alternative surface roughness metrics is required to encompass the diversity of rough-bed rivers and to identify alternative metrics capable of characterising their complex topography and elements including boulders and bedrock.Here, geostatistical analysis is conducted for 20 rough-bed river reaches with varying channel characteristics (channel geometry, bedrock exposure, sediment grainsize, boulder density, and lithology). Multi-scale elevation- and gradient-based surface roughness metrics are extracted from high-resolution digital elevation modes and analysed to determine the most applicable metrics to fully define rough-bed rivers. Statistical analysis includes application of correlation analysis, Principal Component Analysis (PCA), and Hierarchical clustering. The results reveal that a complete description of the topographic properties of rough-bed rivers requires the use of multiple roughness metrics. Research outside Geomorphology has found that elevation skewness and frontal solidity are two metrics that can comprehensively define surface roughness. We find these metrics are capable of distinguishing between channels with differing characteristics, including bedrock or boulders, across multiple scales. The results provide a framework to support further research on the topographic controls on flow resistance and offer insights that advance topographic analysis across geomorphology.
Areas available for potential carbon sequestration in European agricultural soils
Authors: Schneider Florian , Seitz Daria , Seidel Felix , Don Axel
Published: March 2024

In order to estimate a feasible carbon (C) sequestration potential in European agricultural soils, we need to know the area where additional measures that increase soil organic carbon (SOC) can be implemented and the corresponding SOC accrual rates. In this study, we focus on the former and identify areas where promising SOC increasing practices can be implemented on European agricultural soils.The practices considered include a higher share of agroforestry, cover crops replacing bare winter fallows, reduced tillage instead of ploughing and the integration of perennial legumes and leys into crop rotations. Open-access data of European Farm Structure Surveys as provided by EUROSTAT at NUTS2 level serve as a reference for the intensities at which the measures are already implemented in Europe. It was assumed that only the further spread of these measures could potentially sequester additional C in soils.We argue that the adoption of reduced tillage is the practice that covers by far the largest area relevant for potential C sequestration in soils under current food, feed, and fibre demands. The replacement of bare winter fallow with cover crops is restricted to regions with sufficient growing degree days to allow a second crop after harvest. The introduction of more woody features like hedgerows and alley cropping to agro-ecosystems, as well as the integration of more perennial legumes or leys in present crop rotations creates the need for land reallocation and likely compromises agricultural productivity.Overall, we conclude that reduced tillage may emerge as the most promising practice for atmospheric C sequestration in European agriculture despite its reported relatively low SOC accrual rate per hectare. Trade-offs between C sequestration in soils, agricultural production and agricultural demand warrant further inter-disciplinary attention.
Seagrass meadows provide essential coastal protection against future marine storms
Authors: Jaca Estepa Julia , Jordà Sánchez Gabriel
Published: March 2024

Climate change is already modifying the marine environment, and these alterations will presumably increase in the coming decades. Some of the most significant changes expected during this period include ocean warming, rise of sea level, and modifications to circulation and wind wave patterns. For instance, in the Mediterranean, ocean surface temperatures are projected to increase by 1-4 ºC by the end of the century, triggering a chain of impacts on marine ecosystems, such as species migration, significant mortality in some species, and an increase in harmful algal blooms.Furthermore, sea levels are expected to rise, reaching values ranging from 30 cm to over 1 m by the end of the century. The consequences include the increased permanent flooding of low-lying areas, the salinization of coastal water reservoirs, and damage caused by marine storms.In this context, despite ongoing efforts to reduce greenhouse gas emissions, it is crucial to develop realistic and effective plans for adapting to climate change. Nature-based solutions (NBS) present a particularly interesting approach to addressing climate change impacts. One NBS option suitable for reducing the impacts of climate change in coastal areas is to increase seagrass meadows through restoration interventions. The interaction of seagrasses with water flow leads to a reduction in flow energy, thereby limiting the impact of waves reaching the coast.However, ocean warming poses a threat to seagrass meadows, as some species are particularly vulnerable to marine heatwaves. Therefore, the primary goal of the SEAFRONT project is to quantify the potential benefits of seagrass meadows in protecting the coast from future marine storms under different scenarios of global warming and seagrass evolution. SEAFRONT focuses on Spanish coastal areas, which exhibit a variety of hydrodynamical situations and seagrass coverages.Specifically, SEAFRONT aims to 1) assess the impacts of marine storms over the last decades, evaluating the role of seagrasses; and 2) generate future scenarios of physical and economic impacts.In this presentation, we share the results of numerical simulations focused on measuring the total water level at the shore under various scenarios. These simulations account for sea level changes, wave patterns, coastal shapes, and seagrass coverage. Additionally, we discuss the economic impacts of marine storms based on information from insurance companies.Our initial analyses suggest that restoring seagrass meadows is a highly effective way to adapt to marine storms, countering the effects of rising sea levels. However, in areas where seagrasses already exist, losing them could lead to severe consequences, increasing the impact of marine storms.
Interannual variation of stomatal traits in tree crops and its impact on environmental resilience
Authors: Zuffa Francesca , Jung Michaela , Yates Steven , Quesada-Traver Carles , Patocchi Andrea , Studer Bruno , Dow Graham
Published: March 2024

Climate change is driving an increased demand for freshwater in agriculture and this highlights an important need to enhance crop water-use efficiency. Making these improvements in perennial crops, such as fruit trees, can be particularly challenging because of long generation cycles and difficulties in genetic transformation. Nonetheless, tree crops play critical roles in global food security and strategies for climate adaptation are strongly needed. Stomata are fundamental gatekeepers of plant-water relations and represent promising targets for crop improvement. Here, we investigated stomatal density (SD) and function in four consecutive years from 2019 to 2022 in a genetically diverse population of 269 apple accessions from across the globe (Malus × domestica Borkh.). Apples are the third most valuable fruit crop worldwide and physiologically representative of many temperate tree crops. SD exhibited a normal distribution within the population, showing significant differences among accessions that remained consistent across 2019, 2020, and 2021. From this population, we identified two subsets of 20 accessions with contrasting SD: the highest stomatal density (HSD) ranging from 370 mm-2 to 500 mm-2, and the lowest stomatal density (LSD) ranging from 192 mm-2 to 316 mm-2. These SD groups were used to compare stomatal function, leaf physiology, and crop productivity across two seasons in 2021 and 2022. While SD defined consistent differences in stomatal conductance (gs) and instantaneous water-use efficiency (iWUE) between groups, seasonal conditions defined the operational values. LSD had lower gs and greater iWUE in both years. However, in 2022, characterized by hotter conditions and a nearly double VPD compared to the previous year, LSD reduced gs to rates that constrained photosynthesis and ultimately reduced fruit yield compared with 2021. HSD experienced an equivalent gs decline in 2022, but photosynthesis and fruit yield were unaffected compared with 2021. Our results demonstrate a clear trade-off between water savings (LSD) and tree productivity (HSD) as driven by stomatal traits. Moreover, the consistency of SD across years makes it a reliable functional trait for predicting plant performance amidst environmental responses. Finally, in contrast to the prevailing literature that suggests LSD would be the preferred ideotype for climate adaptation in crops, HSD plants may actually provide greater resilience to climate variability in managed orchards and other agricultural systems.
Recent advances from the ESA CCI+Sea Surface Salinity project
Authors: Boutin Jacqueline , Thouvenin-Masson Cloivs ,   CCI+SSS consortium
Published: March 2024

Sea Surface Salinity (SSS) is an increasingly-used Essential Ocean and Climate Variable. The SMOS, Aquarius, and SMAP satellite missions all provide SSS measurements, with very different instrumental features leading to specific measurement characteristics. The Climate Change Initiative Salinity project (CCI+SSS) aims to produce a SSS Climate Data Record (CDR) that addresses well-established user needs based on those satellite measurements. To generate a homogeneous CDR, instrumental differences are carefully adjusted based on in-depth analysis of the measurements themselves, together with some limited use of independent reference data [Boutin et al., 2021]. An optimal interpolation in the time domain without temporal relaxation to reference data or spatial smoothing is applied. This allows preserving the original datasets variability. SSS CCI fields are well-suited for monitoring weekly to interannual signals, at spatial scales ranging from 50 km to the basin scale.
In this poster, we review recent advances of the CCI+SSS phase 2 project and the performances of the last (version 4) CCI+SSS product which covers the 2010-2022 period.
With respect to global CCI+SSS v3 dataset, CCI+SSS v4 dataset includes the following updates. According to several users recommendations, global fields are now on a rectangular 0.25°grid, and polar fields on EASE polar grid are also delivered. The ice filtering has been refined (it was too strong in CCI v3). A correction for contamination by radio frequency interferences has been developed and applied around Samoa island, Barbados island and in the Gulf of Guinea. Latitudinal-seasonal corrections have been applied on SMOS, Aquarius and SMAP SSS. SSS changes related to SMOS direct models updates (wind, dielectric constant, rain) have also been taken into account. This leads to significant improvements at high latitudes, allowing to monitor the interannual SSS variability in the Barents Sea, or the spatio-temporal evolution of a fresh event west of Greenland in Fall 2021. In the tropics, we show that the RFI contamination correction allows to restore the interannual SSS variability related to ENSO which was completely masked by RFI contamination around the island of Samoa. We also illustrate how the CCI+SSS fields have been used to assess model results, at global scale with or without data assimilation (GLORYS model), and in the Amazone plume (NEMO-PISCES biogeochemical model).
References
Boutin, J., et al. (2021), Satellite-Based Sea Surface Salinity Designed for Ocean and Climate Studies, Journal of Geophysical Research: Oceans, 126(11), e2021JC017676, doi:https://doi.org/10.1029/2021JC017676.
Gévaudan et al. (2022). Influence of the Amazon-Orinoco discharge interannual variability on the western tropical Atlantic salinity and temperature. Journal of Geophysical Research: Oceans, 127, e2022JC018495. https://doi.org/10.1029/2022JC018495
A new inventory of High Mountain Asia surging glaciers derived from multiple elevation datasets since the 1970s
Authors: Guo Lei , Li Jia , Dehecq Amaury , Li Zhiwei , Li Xin , Zhu Jianjun
Published: March 2024

Glacier surging is an unusual instability of ice flow, and inventories of surging glaciers are important for regional glacier mass balance studies and glacier dynamic studies. Glacier surges in High Mountain Asia (HMA) have been widely reported. However, the completeness of available inventories of HMA surging glaciers is hampered by the insufficient spatial and temporal coverage of glacier change observations or by the limitations of the identification methods. In this project, we established a new inventory of HMA surging glaciers based on glacier surface elevation changes and morphological changes over four decades. Three elevation change observations based on four elevation sources (the KH-9 DEM, NASA DEM, COP30 DEM, and HMA DEM), three publicly released datasets, and long-term Landsat satellite image series were utilized to assess the presence of typical surging features over two time periods (1970s–2000 and 2000–2020). Through a multi-criteria and cross-validation workflow, all surging glaciers within HMA were identified and indicated with different possibility of surging. Particular efforts were taken to exclude advancing glaciers and separate surging tributaries from glacier complexes. In total, 890 surging and 336 probably or possibly surging glaciers were identified in HMA. Compared to the most recent inventory of surging glaciers in HMA, our inventory incorporated 253 previously unidentified surging glaciers, and most of them are quite small glaciers due to the more complete coverage. The number and area of surging glaciers accounted for ∼ 2.49 % (excluding glaciers smaller than 0.4 km2) and ∼ 16.59 % of the total glacier number and glacier area in HMA, respectively. Glacier surges were found in 21 of the 22 subregions of HMA (except for the Dzhungarsky Alatau); however, the density of surging glaciers is highly uneven. Glacier surges occur frequently in the northwestern subregions (e.g., Pamir and Karakoram) but less often in the peripheral subregions. The inventory further shows that surge activity is more likely to occur for glaciers with a larger area, longer length, and wider elevation range. Among glaciers with similar areas, the surging ones usually have steeper slopes than non-surging ones. Finally, we leverage 50 years of multi-temporal glacier mass balance observations to investigate the relationship between glacier surges and mass balance.
Climate-Informed-Seasonal Mixing Approach to Estimate Flood Quantiles
Authors: Ganapathy Abinesh , Merz Bruno , Vorogushyn Sergiy , Agarwal Ankit
Published: March 2024

Traditional flood frequency analysis assumes that the probability distribution is stationary over time. However, this assumption has been challenged, given widespread changes in catchments and climate. One of the inherent handicaps of the stationarity assumption is its non-inclusion of changes in extremes associated with future climatic conditions. To overcome this handicap, climate covariates can be incorporated into the estimation of flood probability through the non-stationary Climate-Informed Flood Frequency Analysis (CIFFA). The CIFFA methodology comprises 1) selection of predictands (usually seasonal maxima), 2) identification of suitable predictors (large-scale climate indices), and 3) derivation of a statistical link between predictands and predictors. Since CIFFA typically considers the flood peaks in the dominant season, its applicability to gauges, where flood extremes occur in several seasons, is limited. Here, we develop and test a novel non-stationary Climate-Informed-Seasonal-Mixing approach across various European basins. In the proposed Climate-Informed-Seasonal-Mixing approach, we fit the seasonal peak distribution (boreal seasons) with the location parameter conditioned on the selected covariate using the Bayesian Inference. The best climate covariates for each season among a set of predictors are identified based on widely applicable information criterion (WAIC), which computes log posterior predictive density and adjusts the overfitting using the effective number of parameters. Even the traditional stationary model could be a preferred model for any season if it has a minimum WAIC value. Following the estimation of seasonal distribution parameters, the annual flood quantiles are derived by multiplicatively mixing all the seasonal distributions. In order to demonstrate the performance of the proposed approach, we split the entire period into calibration and validation sets, fitting the model based only on calibration samples. The projected quantiles during the validation period are then compared with a benchmark model (traditional model fitted solely with validation samples). Our results suggest that for many gauges, the flood quantiles estimated by the proposed Climate-Informed-Seasonal-Mixing approach align with the baseline estimates where the traditional approaches fall short.
Intercomparison of Different Automatic Threshold Selection Methods in Modelling Precipitation Extremes via Peak Over Threshold Model
Authors: Ganapathiraju Sree Anusha , Rathinasamy Maheswaran
Published: March 2024

The peak-over-threshold (POT) model is the most extensively used for regional precipitation frequency analysis (RPFA) for estimating extreme precipitation events (EPEs). Yet, choosing proper threshold values is critical and challenging while estimating rainfall quantiles for the Indian subcontinent due to the diverse climatic conditions and physical barriers. This study investigates and compares various threshold methodologies, including graphical, analytical, and multiple threshold methods (MTM) for identifying EPEs. These extracted extreme events with high thresholds followed the Generalized Pareto distribution (GPD), whose shape and scale parameters remain constant and increase linearly with increased threshold values. Therefore, the POT-GPD model was employed in the current work, and the parameters were estimated using L-moments to explore and quantify the heavy tail behavior. In addition, the uncertainty associated with the quantiles was also evaluated using nonparametric bootstrapping techniques and later understanding the spatial variability of the GPD parameters from various methods. The effectiveness of the models is assessed on daily gridded precipitation datasets for the Indian region and validated using synthetic datasets generated through Monte Carlo simulations. Results reveal the importance of combining the MTM and analytical threshold methods for identifying a range of critical thresholds to overcome the subjectivity of graphical methods and quantify the uncertainty. These findings contribute to developing region-specific thresholds, highlighting the importance of modifying thresholds to the regional characteristics rather than relying on a fixed percentile for characterizing the EPEs. The proposed approach is essential for assessing the increasing intensity and frequency of precipitation extremes associated with climate change while allowing for more focused mitigation actions and disaster risk reduction.
A study about the initial stages of wind-wave growth in the presence of mixed sea state conditions
Authors: Mora Escalante Rodney Eduardo , Osuna Pedro José , Ocampo-Torres Francisco Javier , Villareal-Olavarrieta Carlos Eduardo
Published: March 2024

It is well known that the swell modifies the wind stress or wind wave properties, but it is not considered in studies of wind-generated wave growth. In most of the world's oceans, swell is present. During the early stages of wave development, swell plays an essential role in modulating the transfer of heat, momentum, and gases. During a measurement campaign in the Gulf of Mexico (GoM), continuous, high temporal resolution measurements of the directional spectrum of wave and turbulent Reynolds stresses were recorded with a platform moving with the free surface. Events were selected under cold front or northerly conditions. These events are nearly ideal for studying wave growth because the wind is nearly homogeneous and stationary with a predominant direction. Using Hanson and Phillips (2001) method, the swell is separated from the wave's directional spectrum to analyze the wind-sea's evolution in mixed conditions. The wind wave conditions are defined based on two swell criteria: the swell index (R = Eswell / Etot) and the swell slope. The observations show that the swell dampens the energy of the young wind-sea. In the equilibrium region, the wind-sea energy is lower in the presence of the swell than in the absence. The physical process that explains this is that the swell reduces the surface roughness, i.e., the short waves have less slope, and therefore, their ability to extract momentum from the atmosphere is reduced. The swell modifies the Toba constant to a sub-saturated energy level. The spectral shape of the wind wave in the equilibrium region tends to have a more considerable spectral dip with a background swell. The transition frequency is shifted toward n times the spectral peak. There is no evidence of swell influence in the saturation spectral region of the wind-sea. It is concluded that the effect of the swell on the wind wave is a function of the direction of the swell, the ratio of the swell energy present in the spectrum, the slope of the swell, and the height of the swell. This research emphasizes the importance of swell inclusion in the analysis to better understand the physical processes of numerical wave models, the information processed by remote sensors, the modulation of swell on flow transfer, and the complexity of the wave field in hurricanes.
Quantitative Insights on Impurities in Ice Cores at the Grain Scale
Authors: Bohleber Pascal , Larkman Piers , Stoll Nicolas , Clases David , Gonzalez de Vega Raquel , Šala Martin , Roman Marco , Barbante Carlo
Published: March 2024

Understanding the spatial variability of impurities in glacier ice on a quantitative level has importance for assessing the preservation of paleoclimatic signals and for the study of macroscopic deformational as well as dielectric ice properties. Two-dimensional imaging via laser ablation - inductively coupled plasma - mass spectrometry (LA-ICP-MS) can provide key insight into the localization of impurities in the ice matrix: Employing the relatively recent advances in LA-ICP-MS featuring fast wash-out devices and single laser shot resolution, state-of-the-art LA-ICP-MS imaging has revealed snapshots showing a close association between grain boundaries and some impurities as well as dispersed clusters in dust-rich ice. So far, these findings are mostly qualitative and gaining quantitative insights remains challenging. Accurate calibrations rely on matrix-matched standards which ideally show the same ablation behavior as the sample. Previous studies successfully prepared ice blocks on glass slides as calibration standards at a resolution of a few hundred microns. State-of-the-art LA-ICP-MS imaging fully reveals the imprint of the ice matrix on the impurity distribution at the grain scale, which also introduces the need for new adequate quantification strategies and consequently, the design of new calibration standards. Here, we present different quantification methods, which provide a high level of homogeneity at the scale of a few microns and, which are dedicated to imaging applications of ice core samples. For this purpose, we use small µL volumes and fast freezing techniques. One of the proposed methods has a second application, offering laboratory experiments to investigate the displacement of impurities by grain growth, with important future potential to study ice-impurity interactions. Standards were analyzed to enable an absolute quantification of impurities in selected ice core samples. Calibrated LA-ICP-MS maps indicate similar distributions of impurities in all samples, while impurity levels vary distinctly: Higher concentrations were calibrated in glacial periods and Greenland, and lower levels in interglacial periods and samples from central Antarctica. These results are consistent with known ranges from bulk meltwater analysis. Further comparison with bulk meltwater analysis calls for a more sophisticated representation of the ice chemistry across spatial scales, for which the calibrated LA-ICP-MS maps now also introduce the quantitative domain.
Coastal vulnerability assessment in the central Mediterranean area: A case study of the Maltese coast
Authors: Sarkar Nabanita , Rizzo Angela , Vandelli Vittoria , Soldati Mauro
Published: March 2024

Coastal areas are primarily exposed to a range of coastal hazards, including both climate- and marine-related processes, due to their close proximity to the sea. In this context, the Maltese Islands, located in the centre of the Mediterranean Sea, are prone to be affected by various coastal risks in the form of erosion, flooding, landslides, storm surges and, on a longer-term, permanent inundation as a consequence of the ongoing sea level rise. These Islands have evolved over time from a complex interplay of marine, morphodynamic and tectonic processes resulting in highly diversified coastal landforms and scenic landscapes.Considering primary and secondary data sources, this study investigates the coastal vulnerability of the north-west coast Malta with respect to a series of hazardous processes by applying an index-based approach supported by extensive field surveys. This stretch of coastal area attracts a large number of visitors each year, raising serious concerns about coastal vulnerability, thus, challenging sustainable management of coastal touristic assets.  In the first phase of this research, a set of indicators pertaining to the local land use, anthropogenic, and natural assets were used in order to estimate the level of coastal exposure. The following phase entailed the zonation of the areas exposed to rock falls, and storm surges, erosion and sea level rise, which enabled us to estimate the overall coastal vulnerability. The results show that the bay areas of the north-west coast of Malta dominated by tourist activities can be considered as the most vulnerable zones and targets of different climate- and marine-related impacts. These are the areas where it would be challenging to prevent future impacts if no adaptation and sustainable management strategies are taken into account.
Exploring Sentinel-1 for Coastal subsidence monitoring along India’s Gujarat shore using MT-InSAR Technique
Authors: Sharma Sona , Ojha Chandrakanta
Published: March 2024

India’s long 7500 km coastline covers vast habitats of rich biodiversity and occupants of about 26% of the country’s population in the coastal zone. By 2060, about 60 million of India’s coastal population will be exposed to a low-elevation coastal zone (LECZ) due to global mean sea level rise (GMSL) and its associated hazards (Neumann et al., 2015). However, the low-lying coastal zones are vulnerable to increasing sea levels and coastal subsidence, which threaten the region's socio-economic development (Shirzaei et al., 2021). The erosion assessment report depicts that 60% of the Gujarat shore covering 1600 km of extensive coastline in western India is undergoing erosion. This study investigates and analyzes the combined influence of coastal subsidence and SLR along the south of Gujarat shoreline. In that context, we explored the descending track (path 34) of C-band Sentinel-1 satellite data (92 SAR imageries) in interferometric wide swath mode (IW2 and IW3) of the European Space Agency (ESA) covering the study area from March 2020 to June 2023. The data sets were processed in an open-source GMTSAR software following an advanced Small BAseline Subset (SBAS) based Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique (Berardino et al., 2002). The results exhibit a deformation rate of  >5 mm/year in various parts of Gujarat's Surat, Bhavnagar, and Bharuch districts. Kododara region in Surat district shows a maximum deformation of >15 mm/year, Navamadhiya in Bhavnagar district is showing subsidence of >20 mm/year, and Chanchvel village in Bharuch is also showing subsidence of >15 mm/year. However, the precipitation data shows a total deviation of -3 % and -5 % in the monthly average compared to normal rainfall observed in Bharuch and Surat districts, respectively, from January 2000 to November 2023 (WRIS, India). Rapid urbanization, dependency on groundwater for basic needs and industrialization, and the impact of increasing sea levels could influence the coastal deformation and inundation hazard risk over the long shorelines and those coastal cities, which needs to be investigated in detail.ReferencesBerardino, P., G. Fornaro, R. Lanari, and E. Sansosti. 2002. "A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms." IEEE Transactions on Geoscience and Remote Sensing 40 (11): 2375–83. https://doi.org/10.1109/TGRS.2002.803792.
Neumann, B., et al. (2015). "Future coastal population growth and exposure to sea-level rise and coastal flooding-a global assessment." PloS one 10(3): e0118571.
Shirzaei, M., et al. (2021). "Measuring, modelling and projecting coastal land subsidence." Nature Reviews Earth, Environment 2(1): 40-58.
Stable isotope composition and airborne concentration of CO2 in Rome capital city (Italy)
Authors: Carapezza Maria Luisa , Di Martino Roberto , Capasso Giorgio , Di Gangi Fabio , Ranaldi Massimo , Tarchini Luca
Published: March 2024

Airborne CO2 has played a pivotal role in maintaining the Earth's atmospheric temperature at reasonable levels throughout its history. Since the onset of the industrial revolution, the level of airborne CO2 has surged due to the combustion of hydrocarbons, leading to global warming. Hydrocarbon consumption is predominantly concentrated in metropolitan areas, driven by various human activities. Estimations of CO2 emissions into the atmosphere rely on the growth of electrical power generation through hydrocarbon combustion. This study presents the outcomes of direct measurements of stable isotope concentrations in airborne CO2 in the urban area of Rome, Italy. We focused on Rome capital city, because i) it is the most populous municipality in Italy (2.8 millions inhabitants), ii) it is the European municipality with the largest surface of green areas and iii) in its south-east sector it borders the Colli Albani quiescent volcano. The dataset encompasses stable isotope compositions and airborne CO2 concentrations gathered to investigate variations in CO2 emissions across space and time. The spatial survey conducted throughout Rome's urbanized area, on a 250 km long path, aims to pinpoint the relevant sources of CO2 based on the stable isotope signature. Results reveal that the combustion of fossil fuels, stemming from urban mobility and household heating, constitutes the predominant source for the excess of airborne CO2 across a wide area of Rome centre. On the contrary, within the Rome south-east sector, including Colli Albani periphery, the carbon isotopic signature of airborne CO2 discloses the endogenous origin of the gas emissions. Continuous monitoring was carried out by the installation of an isotope analyser in three specific points of interest throughout Rome: the busiest area of the city centre, the woodland urban park of Villa Ada and the endogenous gas emission of Cava dei Selci. Findings unveil cyclic variations in human-related CO2 emissions in the city centre. The highest concentrations of airborne CO2 coincide with rush hours during morning and evening. The urban park is not affected by anthropic CO2 and its trend displays the typical day-night cycle. At Cava dei Selci we found high CO2 concentrations by a volcanic source and variations in the urban area correlate with changes in environmental conditions, such as wind speed and direction.
Impact analysis of Relative Sea Level Rise in the entire Kerala Coast of India using MT-InSAR Technique
Authors: Raman Aparna , Ojha Chandrakanta
Published: March 2024

Coastal Subsidence is a complex phenomenon with large spatiotemporal variability to natural processes and anthropogenic activities, leading to the potential inundation risk of major coastal cities worldwide with the increase in relative sea level rise and shoreline sinking (Shirzaei et al., 2021). India’s coastal metro-politician cities are vulnerable to future inundation risk due to the rising sea level. Kerala, a southern state in India with about 590 km of coastline covering vast habitats of rich biodiversity and occupants, has faced the impacts of coastal subsidence for the past few decades. There is a wide scope of detail investigating Kerala’s coastal land subsidence and its impact due to the rise in sea level using geodetic techniques. In this context, we explored the data from Sentinel-1 of ESA acquired along the descending track (Path 63 and 165) with a VV polarization for monitoring subsidence. The Vertical Land Motion (VLM) is analyzed using the Small BAseline Subset (SBAS) based MT-InSAR technique along the entire coastline of Kerala which is spread across 590 km (Berardino et al., 2002). A total of 1443 interferograms were generated by co-registering 326 single-look complex images and applying a spatial baseline threshold of 85 m and a temporal baseline threshold of 65 days. The result shows that most regions in Kerala are subsiding at a rate of > 5mm/year, with the Kuttanad region of Alappuzha showing a maximum subsidence of > 20mm/year. The tide gauge station of Kochi Willingdon Island shows a relative sea level trend of 1.97±mm/year. NASA’s Intergovernmental Panel on Climate Change (IPCC) AR6 report has projected a future sea level change of 0.71 meters by 2100, considering the socioeconomic scenario SSP3-7.0. The InSAR-derived VLM, projection data of sea level from the IPCC-AR6 report, and the high spatial resolution of the Digital Elevation Model (DEM) have been incorporated to map the low-lying fast subsiding zones that are prone to future flood inundation due to relative sea level rise for all the 14 districts of Kerala. We further aim to incorporate a U-net-based deep learning model to efficiently handle these terabytes of data and develop more accurate inundation maps. This study will be helpful for policymakers to take precautionary measures to prevent future inundation hazards over the shoreline.  ReferencesShirzaei, M., et al. (2021). "Measuring, modelling and projecting coastal land subsidence." Nature Reviews Earth, Environment 2(1): 40-58. Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti, (2002). "A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms." IEEE Transactions on Geoscience and Remote Sensing 40 (11): 2375–83. https://doi.org/10.1109/TGRS.2002.803792. 