bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating probabilities of earthquake fault jumps from 2D numerical simulation of seismic cycles
Authors: Michel Sylvain , Scotti Oona , Hok Sebastien , Bhat Harsha , khairdast Navid , Almakari Michelle , Cheng Jinhui
Published: March 2024

The efficiency of an earthquake to cross a barrier can be evaluated based on geometric and frictional properties of faults, and specific seismic parameters such as the stress drop during an earthquake. Numerical modelling of seismic cycles allows to generate thousands of seismic events and to explore the effect of the physical properties with respect to a barrier effectiveness criteria. The probability of an event passing a barrier can thus be evaluated on the basis of this barrier effectiveness criteria. Such approach has been used for frictional barriers and fault bends. In this study we focuses on earthquake fault jumps which has been observed on multiple occasions such as the latest 2024 M7.5 earthquake in Japan. We use the quasi-dynamic algorithm VEGA, which numerically simulates seismic cycles of 2D fault networks and is based on rate and state friction. The problem is simplified to two planar faults separated by a gap. Among other parameters, we explore the effect of the overlap, distance and angle between the two faults. The loading of a fault network can be done in multiple ways. We thus explore the impact on the dynamics of sequences of earthquakes either from a far-field stress loading or from imposing a back slip rate loading on each fault. We also look at the effect of adding creeping - velocity strengthening - sections at the borders of the faults. We finally compare our results with the statistics of jump probabilities from published observed seismic events. Our study allows for a rapid assessment of thousands of earthquake scenarios and is a promising approach to facilitate the integration of earthquake physics into seismic hazard.
Revisiting the Pulse-Width Method to Estimate the Source and Attenuation Parameters from Local Earthquake Seismic Records
Authors: Russo Guido , Petito Penna Rodolfo , Nazeri Sahar , Zollo Aldo
Published: March 2024

The quality factor Q is the medium properties quantifying seismic waves attenuation due to anelastic rock behavior. It can be measured from earthquake seismic signals both in frequency and time domain and separately for P and S waves.
Assuming  that Q is frequency-independent over the seismic frequency band, Kjartansson (1979) developed a model suggesting that, if the seismic source generates a symmetric pulse, the pulse width at any station is proportional to t* via a coefficient, named C. Here t* represents the travel time divided by Q. It is noteworthy that C may depend on Q and remains relatively constant for Q>20.
To test the validity of the model under more general source and propagation conditions, we applied it to a set of simulated seismograms generated by different earthquake sources and recorded at seismic stations located at the surface of a homogeneous half-space. The source model is a circular rupture propagating at uniform rupture speed, under the action of a constant stress-drop and for different seismic moments (magnitudes). The far-field source radiated pulses for both direct P and S waves are generally represented by a non-symmetric triangles that are convolved with the Kjartansson’s attenuation function to simulate the propagation to the station. We developed an automatic technique to measure both pulse width and half-width on synthetic attenuated signals and validated it against the known theoretical values.  In our simulations we explored a wide range of values for magnitude, stress drop, rupture velocity and Q. Since these parameters affect the shape of the triangular pulse, we investigate their possible influence on C of the Kjartansson’ equation. Preliminary results show that C depends on Q (even for Q>20) and magnitude. Here we present the complete analysis of the results with the aim to obtain the explicit dependence of C on the most waveform-sensitive source and attenuation parameters in terms of a polynomial expansion.
 
References

Kjartansson. Constant Q–Wave propagation and attenuation. J. Geophys. Res., 84, 4737-4748, 1979. Doi 10.1029/JB084iB09p04737
Exploring the application of deep learning techniques to facilitate the management of invasive species 
Authors: Flexa de Castro Arianne , Lehmann Jan Rudolf Karl , Buttschardt Tillmann , Gastauer Markus
Published: March 2024

Biological invasion threatens biodiversity protection and ecosystem services and is considered one of the major threats to the long-term success of mineland restoration projects. Especially due to the unrestrained growth and significant dispersal capacity of invasive species that jeopardize not only the recovery areas but also pose risks to neighboring environments. Despite the urgency, combating invasive species is still conducted in a manner incompatible with the need for effective large-scale monitoring. A significant challenge has been developing methods capable of detecting these species during the early stages of invasion and monitoring the population on a large scale.The utilization of refined data, particularly those collected with multi and hyperspectral sensors, has been a focal point for species detection in ecological research, particularly in environments with higher diversity. However, the adoption of such approaches is not yet widespread among environmental monitoring companies, primarily due to challenges associated with costs and the complexities of data collection. Using deep-learning algorithms can than facilitate species detection with simple RGB images providing more possibilities to ecological studies in this field, while improves application as simplifier the process of data acquisition to ecosystems managers. For this purpose, this work used a deep-learning model using RGB images to detect two invasive species Melinis minutiflora Beauv. (Poaceae) and Muntingia calabura L. (Muntingiaceae) in mining restoration sites in the eastern Amazon. Unoccupied aerial systems image data of a waste pile was collected with a total size of approximately 108 ha.The applied methodology was able to differ invasive species in our study site and the spatial distribution map generated revealed hotspots of M. minutiflora and M. calabura in the restoration area. The detection of these species using RGB images underscores the potential of deep learning to map invasive species and provides a more accessible way for monitoring on a larger scale. In conclusion, our results contribute to improve efficiency of large-scale monitoring of invasive species in restoration projects. By facilitating data collection and highlighting the potential for economically viable management, our findings provide a valuable perspective for stakeholders engaged in enhancing invasive species management practices.
Quantifying the contribution of oceanic evaporation to tropical cyclone development with WRF-age 
Authors: Wei Jianhui , Olschewski Patrick , Sun Qi , Li Yu , Laux Patrick , Kunstmann Harald
Published: March 2024

Global warming is accelerating the global water cycle. On a short temporal scale, such acceleration may modify weather regimes and, thus, potentially increase the number of compound weather and climate events. Among them, tropical cyclones can bring destructive high winds, torrential rain, storm surges and occasionally tornadoes in association with a variety of hazards, especially in coastal urban regions. In this study, we apply a newly developed WRF-age model, i.e., the Weather Research and Forecasting model enhanced with an age-weighted water tracking approach, to a coastal urban region in Southeast China. The source and transport of atmospheric water vapor in one Northwest Pacific Ocean cyclone, here, Hato in August 2017, are exemplarily examined by means of tracking oceanic evaporation. Two indices, i.e., the contribution ratio and the atmospheric water residence time, are used to better understand how much and how fast the oceanic evaporation contributes to the development of tropical cyclone Hato. Our simulation results show that, within 24 hours, the contribution ratio of the tagged oceanic evaporation to the total water vapor researches up to around 25%. In addition, the spatial pattern of the atmospheric water residence time shows that the oceanic evaporation below the rainbands of Hato (around 9 hours) fuels faster in its development than the oceanic evaporation from the surrounding region (15 hours). These findings emphasize the important role of oceanic evaporation to tropical cyclone development. Our study demonstrates that the WRF-age model can be applied to quantify the acceleration of tropical cyclone development under global warming.
Toward Determining the Controls on Subduction Zone Seismic Behaviour with Machine Learning
Authors: Locher Valerie , Bell Rebecca , John Cedric , Salah Parastoo
Published: March 2024

Variations in earthquake frequency and magnitude across global subduction zones are thought to be influenced by a combination of geological and geophysical factors, such as the age and dip angle of the subducting plate. Despite numerous previous qualitative studies on the correlation between seismic behaviour and subduction zone characteristics, the parameters and mechanisms governing seismicity at subduction zones remain elusive. Our limited historical record of earthquakes further complicates this understanding. Finding underlying general correlations and mechanisms that are valid across different subduction trenches is critical for assessing seismic behaviour and earthquake hazards along subduction plate boundaries which are poorly monitored or have been seismically quiet during the short instrumental record. This study aims to bridge the knowledge gaps highlighted above by applying specific unsupervised machine learning techniques to publicly available data on subduction zone parameters and earthquake catalogues. This approach is particularly adept at uncovering hidden correlations in complex, high-dimensional datasets, which might not be discernible through traditional analysis methods. We suggest that seismic behaviour may be describable as a non-linear combination of subduction margin parameters and present a quantitative tool for comparing seismic behaviours across different margins. This may help assess seismic hazards in regions with scant seismic records or that have been historically quiescent. By doing so, we hope to contribute significantly to the predictive modelling of earthquake occurrences and their potential impacts globally.  
Interconnections and decadal predictability of global hot, dry and compound hot-dry events
Authors: Aranyossy Alvise , Donat Markus , Deluca Paolo , Delgado-Torres Carlos , Solaraju-Murali Balakrishnan
Published: March 2024

We investigate the representation of compound hot-dry events in decadal predictions and their relationship with their univariate hot and dry components. We use a CMIP6 multi-model ensemble (MME) of 125 members from the Decadal Climate Prediction Project (DCPP) hindcast simulations and compare it with different observational references. Our analysis focuses on the first five lead years of the simulations, with the different ensemble members initialised every year from 1960 to 2014. We analyse the skill of predicting hot, dry and hot-dry events in the multi-model ensemble. Specifically, we select the days above the 90th percentile of the daily maximum temperature for hot events. For dry events, we use two indicators, the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI), with accumulation periods of 3, 6 and 12 months, and we consider a dry event a month that shows an SPI or an SPEI value ≤1. Finally, we identify days that present both hot and dry conditions according to these criteria as compound hot-dry days.Preliminary results for the observations show a strong correlation between precipitation and the occurrence of compound events, especially for long accumulation periods, suggesting the importance of dryness as a driver for compound hot-dry events. In the DCPP hindcasts, the hot events show some robust predictive skill, mainly as a consequence of the increasing trend in temperature. On the other hand, dry events show sparse skill, concentrated in dry areas of the world and especially for extended accumulation periods. Further analysis of the skill of compound events and their relationship to their univariate counterparts in DCPP hindcasts will shed light on the representation of such events in decadal forecasts. However, these initial results underline the importance of precipitation in both the occurrence of present hot-dry compound events and the prediction of such events in the future.
Ocean liming in the oligotrophic Eastern Mediterranean: impact on the planktonic microbial food web
Authors: Pitta Paraskevi , Magiopoulos Iordanis , Romano Filomena , Tsiola Anastasia , Chantzaras Christos , Gonzalez Jose , Serret Pablo , Valsecchi Silvia , Varliero Selene , Basso Daniela , Azzellino Arianna , Barbaccia Eleonora , Traboni Claudia , Nocera Ariadna C. , Courboules Justine , Tsapakis Manolis
Published: March 2024

Ocean Alkalinity Enhancement (OAE) allows for active removal of atmospheric CO2, therefore is considered as one of the most promising Carbon Dioxide Removal (CDR) technologies. OAE could be obtained by discharging alkaline material in the wake of ships, however very little is known on potential negative effects on marine communities. We report here the first study focusing on the response of the entire pelagic microbial food web to the addition of calcium hydroxide in real oligotrophic conditions. In a mesocosm experiment performed at the CretaCosmos facility in Crete, Greece, in May-June 2023, we tested the response of the eastern Mediterranean oligotrophic waters to two different treatments of calcium hydroxide slurry addition (SL; High and Low concentrations, three replicate mesocosms each), while three more mesocosms served as Controls (no addition). Mesocosms, filled with natural coastal seawater, were treated with slurry on days 1, 3, 5, 7, 9, 11 to simulate the chronic disturbance, expected from repeated discharge of SL from ships; while the possible precipitation of carbonate crystals was assessed by putting a sediment trap at the bottom of each mesocosm. The carbonate-equilibrium and dissolution-kinetics were monitored by measuring temperature, solution-conductivity, and changes in pH. Photosynthetically-Active-Radiation and visible light were monitored by sensors in each mesocosm. Plankton productions (bacterial, viral, secondary) as well as community composition of all plankton groups from viruses to copepods were assessed by optical microscopy, flow cytometry and metagenomics; chlorophyll was also measured. Although an important alteration of pH was observed in the High lime addition, only heterotrophic bacteria production was found to be negatively affected and only in the second half of the experiment. The rest of the plankton groups presented different patterns and not a clear response to the lime addition. This first attempt to study the effect of lime addition on the complex pelagic food web will serve as a first step to an extensive testing needed before any application of ocean liming at a large scale.
Understanding recent trends in lower stratospheric ozone: an update with CCMI-2022 models
Authors: Benito-Barca Samuel , Abalos Marta , Calvo Natalia , Garny Hella , Birner Thomas
Published: March 2024

Lower stratospheric ozone between 60S and 60N has continued to decline since 1998, despite the reduction of ozone-depleting substances as a consequence of the Montreal Protocol. Previous studies have shown that Chemistry Climate Models are not able to reproduce these negative trends in mid-latitudes, although the reason for this discrepancy between models and observations remains unknown.In this study, we re-examine recent trends in lower stratospheric ozone using the new simulations from the Chemistry Climate Model Initiative 2022 (CCMI-2022). Historical simulations with observed sea surface temperatures (SSTs) and nudged QBO (ref-D1), and fully-coupled atmosphere-ocean simulations (ref-D2) are available covering the period up to 2018, which allows a better analysis of the role of natural variability in recent ozone trends compared to previous studies.CCMI-2022 models show a slight improvement in the representation of lower stratospheric ozone trends in mid-latitudes compared to previous studies that used CCMI-1 and CCMVal models. The observational trend now lies inside the 90% confidence interval of the models’ trend distribution. However, the majority of the models are still not able to reproduce the pattern of negative trends in the tropics extending into mid-latitudes. Intermodel differences dominate the spread in the trends, while natural variability from SSTs and QBO are not decisive in explaining the negative mid-latitude trends.  The role of the different ozone transport representations in models, in particular the mixing between the tropics and mid-latitudes, is also explored.
Can 3-D X-Ray tomography imaging improve the estimation of saturated hydraulic conductivity of soils?
Authors: Låker Einar Emil , Nemes Attila , Hirmas Daniel
Published: March 2024

Saturated hydraulic conductivity (Ksat) is one of the most fundamental parameters in soil hydrology. It governs the rate of saturated flow through porous media and functions as a scaling factor for unsaturated flow. Knowledge of Ksat is key to understanding the movement of water in soils, transport and recharge of groundwater, suspended and dissolved transport in soils, and soil-air water exchange. In hydrology and climate modeling Ksat is often estimated through pedotransfer functions. A large effort has been committed to the development of these models, using an array of differing algorithms and methods. However, estimating Ksat has been somewhat troublesome, since the commonly measured soil properties, such as soil texture, bulk density and organic matter content, used as predictor variables in PTFs do not explain Ksat variation well. Instead, Ksat is largely controlled by pore-network characteristics especially in highly-structured soils. Using an extended, methodologically homogeneous dataset of commonly measured soil physical properties, 3-D X-ray computed tomography imaged pore-network parameters, and quasi-continuous particle-size measurements using the Integral Suspension Pressure method, we assess the benefits of using combined soil textural and structural information on the estimation of Ksat. Using this dataset, we have built models that estimate Ksat using a boosted random forest algorithm (XGboost) and used explanatory model analysis to tune and evaluate the models. Three input data scenarios included (i) basic soil inputs only (ii) imaged pore metrics only, and (iii) their combination. Using or adding imaged pore metrics as inputs greatly improved the Ksat estimations that were reflected, for example, by the respective coefficients of determination, evaluated using a cross-validation scheme (R2 = -0.05/0.60/0.58 for the three input scenarios respectively). 3-D imaging of soil and the subsequent characterization of its pore-space may serve multiple research purposes, but such data are still not routinely collected due to cost of measurement and general lack of access to equipment. Our study confirms, however, that when collecting such metrics will become economically feasible through e.g. better automation of image processing using tools like SoilJ, having those metrics will show great potential towards improving the estimation of the soil’s water transport properties. 
Supervised segmentation algorithm for coastal dunes delimitation and classification
Authors: Lopez-Nieta Diego , Guisado-Pintado Emilia , Canero Francisco M , Rodriguez-Galiano Víctor F
Published: March 2024

Coastal dunes systems play an important role as a defensive barrier against erosive and flood processes caused by storms and sea level rise. Delimiting coastal dunes is important for management and analysing local dynamics. Although, it is a complex task due to their inherent variability. This process can be optimized using remote sensing methods, showing to be essential, especially when dealing with extensive and complex systems or when analysing spatio-temporal changes.This contribution shows a preliminary approach to the automatic segmentation of coastal dunes using the Multiresolution Segmentation (MRS) algorithm. The case of study is located in the Trafalgar Cape (Cádiz), in the southwest of the Iberian Peninsula. This area, that is part of the La Breña and Marismas de Barbate Natural Park, is composed of a combination of cliffs, beaches, dunes, and marshes, creating a diverse ecosystem. Dune vegetation, dominated by species such as stone pine, mastic, coastal juniper, and palmetto, is adapted to the climatic conditions, playing an important role in stabilizing the dunes and soils.MRS was applied to different data sets i) RGB and NIR reflectances from Sentinel-2 L2 2017 composites at 10 m spatial resolution, ii) NDVI for the same year, and iii) a Digital Terrain Model (MDT). Different combinations of the algorithm hyper-parameters: “image layer weights”, “Scale Parameter”, shape/colour (0-0.9), and compactness/smoothness (0-0.9) were evaluated using the algorithm ESP2.The proportion of different land cover categories in this area (built-up, cropland, barren/sparse vegetation, trees, grassland, open water, herbaceous wetland and shrubland), was compute for every segment, considering the ESA WorldCover map at 10 m spatial resolution. The segments with the highest dune cover were compared to those obtained from a manual interpretation of very high resolution digital orthoimage.
Tourism water demand modelling in Mediterranean cities under current and future climate
Authors: Toth Elena , Neri Mattia
Published: March 2024

Even if tourism represents only a fraction of water consumption at the global scale, in some regions such demand may represent a critical share. The Mediterranean coast is an emblematic case, since it receives many millions of visitors in summer, when rainfall is scarce and there is competition with water demand for irrigation. Many important tourism locations face permanent limitations or temporary restrictions on urban demand due the occurrence of drought events, including the last one in 2022. As the climate changes, water scarcity events have become more frequent and the need for addressing tourism water demand, starting from its understanding, has become a priority.The study presents analyses carried out in two important beach tourism cities (Rimini, in Italy, and Benidorm, in Spain), where water demand models were developed and validated over historical data and then applied for future climate scenarios.Two modelling experiments were carried out:- Modelling of monthly water demand at municipal scale, through implementation of non-linear (stepwise linear regression) and non-linear (based on parsimonious architectures of artificial neural networks) models for the Rimini urban area;- Modelling of hotels water demand: the monthly consumption series of the hotels in Benidorm were averaged to obtain the time series of a "typical hotel”, modelling was carried out and its performance assessed also in relation to the anomalous pandemic years 2020 and 2021.In both types of model implementation (municipal and hotel scale), the input variables included climatic factors (monthly precipitation, number of rainy days, maximum and minimum temperatures) and socio-economic factors (in particular indicators on tourist attendance, resident population and tariff, where available).Finally, a set of 10 EC-JRC raw and bias-corrected Euro Cordex climate simulations were processed and validated against local ground observations on the control period; the corresponding rainfall and temperature series simulated for the future decades (up to 2100) under the RCP8.5 scenario were then used in input to the water demand models in order to analyse the impact of expected climate change on the water demand.
Impact of shrubby willows on seepage lines of flood protection dykes
Authors: Mueller Helene , Ferchl Elias , Sokopp Manuel , Rauch Hans Peter
Published: March 2024

Vegetation on flood protection dykes (FPD) is an ambivalent topic. It can provide multiple ecosystem services (e.g. erosion stability). Mostly herbaceous vegetation is used. Many rules, standards and technical codes ban woody vegetation from FPDs. While herbaceous vegetation leads to higher efforts regarding continuous maintenance work, it could be assumed that woody vegetation can provide additional benefits.  The spectrum reaches from less maintenance, impacts on biodiversity, shadowing effects that might counteract the drought stress of herbaceous vegetation under climate change aspects etc.. Nether the less effects of woody vegetation on FPDs reach from positive to negative influence, covering the spectrum of soil stabilization to tilling of the dyke matrix. Failure mechanisms of dyke stability with positive or negative influence of woody vegetation are surface erosion, subsurface erosion leading to ground failure, slope failure with deep sliding horizon and slope failure with shallow sliding horizon. A first step towards consideration of woody vegetation on FPDs is the prove of stability of dykes covered by woody vegetation. Up to now these issues were faced with individual expert opinions conducted for unique dyke situations and single tree individuals.Focusing on the mechanism of ground failure, which is depending on the course of the seepage line through the dyke. The influence of the vegetation type covering the dyke surface on the seepage line has been analyzed over 15 years at an experimental dyke in Austria. Typical dyke related herbaceous vegetation communities were compared to woody vegetation implemented via soil bio-engineering techniques. Flooding experiments were carried out and the height of the seepage line in the dyke was measured cross-sectional at two to four points. The results represent newly built dykes considering the current state-of-the-art. The tested woody vegetation covers shrubby willows, implemented via cuttings and brush mattresses.  Seven flooding experiments were conducted, covering durations from 5 to 49 days. Comparing the seepage lines of day 7 no clear patterns could be detected. For 42 % of measuring points the seepage line in the area of herbaceous vegetation is higher than in related areas with woody vegetation. For 37 % of measuring points the seepage line in the section covered by willows exceeds the height values related to herbaceous vegetation. 21 % of measuring points show almost the same heights for both vegetation types. Based on the conducted measurements no seepage section on the dyke surface could be assumed, dam stability appears not to be threatened by ground failure in both vegetation scenarios.As first results it can be stated that continuously growing shrubby willows shows no negative effects on the seepage line of FPDs compared to herbaceous vegetation cover. Tough, this study shows some limitations: The results are only valid for dykes constructed under state-of-the-art standards and for shrubby species.
Stability of magnesite (MgCO3) in the presence of a hydrous fluid in the upper mantle
Authors: Sieber Melanie J. , Reichmann Hans Josef , Farla Robert , Koch-Müller Monika
Published: March 2024

Understanding the stability of carbonates under high pressure and temperature is essential for modelling the carbon balance and cycle in the deep Earth. In the presence of an H2O-containing fluid, the melting curve of carbonates can be strongly reduced to a lower temperature. Since magnesite is an important carbonate host in the Earth's mantle, the melting curve of magnesite in the presence of an H2O-containing fluid is of particular interest.Here we report results from in situ synchrotron energy dispersive X-ray diffraction experiments and use texture observations from ex situ falling sphere experiments in the brucite-magnesite system between 1 and 12 GPa. We define the dehydration and melting curve of brucite and elucidate the stability of magnesite in the presence of a liquid and periclase.The observed liquidus provides information on the fate of magnesite-bearing rocks in subduction zones. Our results show that magnesite remains stable under typical subduction zone gradients even when infiltrated by hydrous fluids released by dehydration reactions during subduction. We conclude that magnesite can be subducted to depths below the arc and beyond. Our results therefore have important implications for the carbon budget of the Earth's mantle and its role in the regulation of the carbon cycle.
A novel proxy approach to constraining atmospheric modes in central and southwestern Iran during Marine Isotope Stage 3
Authors: Soleimani Mojgan , Baker Jonathan , Nadimi Alireza , Dublyansky Yuri , Koltai Gabriella , Spötl Christoph
Published: March 2024

Terrestrial paleoclimate records from arid southwestern Asia are relatively sparse. Therefore, the regional impact of abrupt glacial climate variability remains poorly constrained for much of the Western Asia, particularly winter (wet season) dynamics during Marine Isotope Stage 3. Here, we present the first paleoclimate reconstructions of Southwestern and Central Iran, which span the interval ~50-30 ka, based on speleothem δ18O and δ13C. Stable-isotope signals in the two stalagmites are generally uncorrelated and do not exhibit a consistent response to Greenland stadials or interstadials; however, both show a positive δ18O excursion that coincides with Heinrich event 4. This behavior contrasts with that observed in northern Iran, Anatolia, and Levant for the last glacial period. We explore the potential mechanisms for intermittent coupling of speleothem δ18O across Iran through isotope-enabled atmospheric modelling outputs, from which we utilize the spatial δ18O gradient as a proxy for wintertime westerly vs. southerly jet strength. Our results suggest that during Heinrich event 4 and several Greenland stadials, stronger westerly winds enhanced Mediterranean moisture contributions to both sites and reduced aridity in southern Iran. We emphasize the importance of analyzing spatial trends in speleothem δ18O to interpret atmospheric dynamics, rather than relying on time series from single sites.
Simulation of scale-resolved mixing of passive scalars in waves and turbulence
Authors: Loft Malte , Ellingsen Simen Å. , Hearst R. Jason , Rømcke Olav , Gautam Priyanka , Rung Thomas
Published: March 2024

The accuracy of global circulation models partly relies on understanding the dynamics at the coupled atmosphere-ocean interface. Related current research efforts focus on a range of aspects, including the quantification of energy budgets, an understanding of wave growth mechanisms as well as other processes relating to the interaction between waves and ambient turbulence of the upper ocean. The latter is particularly important for the understanding of gas transports close to the surface in the presence of old and long waves (swell). Reported efforts are based on a previously introduced hybrid scale-resolving, numerical method that fully resolves both the air and water phase at realistic Reynolds numbers [Phys. of Fluids, Vol. 35 (7): 072108]. In this context, we enhanced the model by a passive scalar transport procedure to observe the transport of an arbitrary number of passive scalars close to the surface within the upper ocean layer. The presentation will address the treatment of numerical issues, primarily related unintended numerical diffusion through the interface, and explain the layout of a method to obtain accurate results for different wave-turbulence scenarios. Data processing follows experimental approaches [Journal of Fluid Mechanics, Vol. 962: R1], thereby supporting future joint numerical/experimental studies. Results display wave effects on both the turbulence and the scalar transport close to the surface. In particular, enstrophy and turbulent kinetic energy (TKE) are affected in the vicinity of surface waves. The developed two-phase flow model proves to be a promising approach for future collaborative experimental/numerical studies of transport processes in this highly dynamic domain.
Atmospheric circulation changes and turbulence modifications over Europe: implications for commercial flight operations in a changing climate
Authors: Alberti Tommaso
Published: March 2024

The unprecedented changes in Earth's climate are reshaping atmospheric dynamics on a global scale, with profound implications for various sectors, including aviation. One of the critical facets of this transformation lies in the alterations to atmospheric circulation patterns and the concurrent modifications in turbulence characteristics.We investigate the intricate interplay between climate change, atmospheric circulation patterns, and turbulence modifications over Europe, with a specific focus on their implications for commercial flight operations. Drawing upon ERA5 reanalysis data at 200 hPa pressure level we explore the evolving climatic conditions shaping the European airspace. By jointly looking at the cube-rooted eddy dissipation rate, vorticity, and horizontal divergence we evidence increasing trends of anomalously turbulent conditions over UK and Northern Europe. Otherwise, decreasingly frequency anomalies are associated with light-turbulent conditions over Central and Mediterranean Europe. Overall, increasing trends also correspond to increased severity in terms of turbulence strength levels, with a clear increase in moderate-to-severe turbulence episodes, mainly associated with both converging and diverging atmospheric ridges.The study highlights the region's vulnerability to significant changes in atmospheric pattern dynamics, emphasizing the potential increase in turbulence-related episodes and severity, impacting aviation safety, fuel efficiency, and passenger comfort. Our analysis aims to provide valuable insights for aviation stakeholders, policymakers, and researchers, contributing to the development of adaptive strategies and operational guidelines.
From paper reports to 3D models for all – Irish geodata in urban settings
Authors: O'Connor Sophie , Mozo Lopez Beatriz
Published: March 2024

Communicating the subsurface is a challenge. Geoscientists are trained to visualise what is underneath them and to see the subsurface in 3D, whereas planners, policy makers and the people impacted by both (i.e., the public) are not.Over many years, Geological Survey Ireland has developed several services in different formats to help pull together information about the subsurface, to present it in an organised manner and to portray it in three dimensions. Underpinned by the organisation’s commitment to open data and re-use of public sector information, these services are:National Geotechnical Borehole Database
Geotechnical Viewer
3D models and model viewer
Assembled over several decades, the National Geotechnical Borehole Database has expanded with the submission of ground investigations that have been carried out ahead of development projects by the private and public sectors. It acts as a secure, national repository and is a valuable resource for:planning and optimising future ground investigations;
understanding the subsurface and urban geology;
for helping construct 2D and 3D models.
For ease of access, data and reports from the National Geotechnical Borehole Database are published on the Geotechnical Viewer, freely available to all.  The online Geotechnical Viewer displays ground investigations as digitised, georeferenced polygons, with an associated downloadable report in .pdf format. Several thousands of ground investigations projects are presented.With time and technical and software advances, Geological Survey Ireland has produced urban 3D geological models using the National Geotechnical Borehole Database. A primary function of these models is visual communication of the subsurface to geoscientists, professionals from other disciplines, researchers, students and members of the public.Our urban 3D models can assist with:Resource (water and geothermal) mapping;
Understanding and characterising urban geology, with potential relevance for basement impact assessment, Sustainable Drainage Systems (SuDS), flooding and, subsurface management;
Optimising geotechnical investigation, design and construction;
De-risking human activities from impact of our subsurface environment;
Investigating impact of human activities on environment around and beneath us, e.g., dewatering;
and informing policy, planning, protective and climate adaptation measures.
3D geological models allow everyone to visualise the subsurface and can be used to communicate the geoscience behind policy, thereby making defensible decisions visible. To ensure the 3D models are easily accessible by all, Geological Survey Ireland have a 3D model viewer where no software or zip file downloads are needed. The 3D model viewer has Interactive and Augmented Reality functionality.Recognising the importance of freely available, accessible data for non-geoscientists, Geological Survey Ireland has created and smoothed pathways for stakeholders to access and visualise geological data in urban settings.
Regional scale landslide susceptibility maps: strengths and weaknesses
Authors: Molin Paola , Sembroni Andrea , Vetere Gioia
Published: March 2024

Landslides are among the most dangerous natural hazards impacting on human life claiming lives and affecting economy and society. For this reason, the cost of the repeated occurrence of landslides could become unsustainable for a country. In this respect, the assessment of the susceptibility to landslide of a region becomes crucial to mitigate the economic and societal implications and to save lives. A typical approach starts from the inventory of landslides by field survey coupled with database consulting. This activity could assess the discriminating and predisposing factors, defining the weight of each of them on the slope stability. Overlaying resulting maps in GIS environment, a susceptibility map of each type of landslide could be produced. At local scale, the field survey allows to identify properly the past events and the factors that contributed to the instability. Unfortunately, sometimes managers and policy makers ask for landslide prediction regarding areas that are too large for a detailed field survey. As a consequence it is necessary to work out methods that start from available database. The main problem is to check the quality of the data and to eliminate possible errors. Starting from a classical susceptibility analysis based on landslide inventory derived from filed survey, we propose a modified method applicable to database on regional scale area. In detail, we check the quality of the database with respect to landslide locations eliminating unproper sites according to hillslope interval or rock-type, i.e. the two main discriminating factors. Our results show how this kind of approach allows to produce maps that are useful for general landscape management indicating the areas susceptible to each type of landslide. These preliminary maps are the basis for identifying the areas where more detailed studies are needed.
Forecasting Permafrost Carbon Dynamics in Alaska with GeoCryoAI
Authors: Gay Bradley , Pastick Neal , Watts Jennifer , Armstrong Amanda , Miner Kimberley , Miller Charles
Published: March 2024

Complex non-linear relationships exist between the permafrost thermal state, active layer thickness, and terrestrial carbon cycle dynamics In Arctic and boreal Alaska. The rate, magnitude, and extent of permafrost degradation remain uncertain, with an increasing recognition of the importance of abrupt thaw mechanisms. Similarly, large uncertainties in the rate, magnitude, timing, location, and composition of the permafrost carbon feedback complicate this issue. The challenge of monitoring sub-surface phenomena, such as the soil temperature and soil moisture profiles, with remote sensing technology further complicates the situation. There is an urgent need to understand how and to what extent permafrost degradation is destabilizing the Alaskan carbon balance and to characterize the feedbacks involved. We employ our artificial intelligence (AI)-driven model GeoCryoAI to quantify permafrost thaw dynamics and greenhouse gas emissions in Alaska. GeoCryoAI uses a hybridized multimodal deep learning architecture of stacked convolutionally layered memory-encoded bidirectional recurrent neural networks and 12.4 million parameters to simultaneously ingest and analyze 13.1 million in situ measurements (i.e., CALM, GTNP, ABoVE ReSALT, FLUXNET, NEON), 8.06 billion remote sensing airborne observations (i.e., UAVSAR, AVIRIS-NG), and 7.48 billion process-based modeling outputs (i.e., SIBBORK-TTE, TCFM-Arctic) with disparate spatiotemporal sampling and data densities. This framework introduces ecological memory components and effectively learns subtle spatiotemporal covariate complexities in high-latitude ecosystems by emulating permafrost degradation and carbon flux dynamics across Alaska with high precision and minimal loss (RMSE: 1.007cm, 0.694nmolCH4m-2s-1, 0.213µmolCO2m-2s-1). GeoCryoAI captures abrupt and persistent changes while providing a novel methodology for assimilating contemporaneous information on scales from individual sites to the pan-Arctic. Our approach overcomes traditional model inefficiencies and seamlessly resolves spatiotemporal disparities.
Copula-based statistical post-processing for multi-site temperature forecasts
Authors: Perrone Elisa , Flos Maurits , Schicker Irene
Published: March 2024

Modern weather forecasts are typically in the form of an ensemble of forecasts obtained from multiple runs of numerical weather prediction models. Ensemble forecasts are usually biased and affected by dispersion errors, and they should be statistically corrected to gain accuracy. This is often done following a two-step approach: first, we correct the univariate forecasts, and then, we reconstruct the dependence structure non-parametrically via empirical copulas. The parametric correction of the dependence structure is limited to Gaussian copula-based methods. In this work, we propose a novel approach based on a more general parametric class of copulas called Archimedean copulas. We test the new method in both a simulated scenario and a case-study setting for multi-site temperature forecasts from the ALADIN-LAEF ensemble system in Austria. Our findings show that the state-of-the-art non-parametric techniques perform well in the simulation study. However, Archimedean copulas outperform the existing techniques, especially Gaussian copula approaches, and output well-calibrated forecasts in the real-case study. Our analysis demonstrates the usefulness of including advanced parametric copula methods in the post-processing context and the need of a more realistic simulated framework to test new methodology.
Comparison of Historical and Speleothem (Paleo)climate Records from Northwest Yucatán (Mexico)
Authors: Intveld Aviva , Breitenbach Sebastian F.M. , Carolin Stacy A. , James Daniel H. , Kwiecien Ola , Brenner Mark , Peraza Lope Carlos , Hodell David A.
Published: March 2024

Paleoclimate studies on the Yucatán Peninsula, Mexico, are important for understanding relationships between past climate change and ancient Maya cultural evolution. The Postclassic Maya capital of Mayapán is a site of interest for such studies,  given that evidence of repeated drought conditions corresponded to times of violent conflict, from ~1400 to 1450 CE (Kennett et al., 2022), just before site abandonment in ~1450 and prior to the protracted Spanish conquest of the Yucatán region from 1527 to 1697 CE. As part of further efforts to identify past droughts in northwest Yucatán, we studied a new stalagmite from Cenote Ch’en Mul, located directly beneath the archaeological site of Mayapán. The upper 120 mm section of stalagmite MAYA-22-7 is chronologically constrained by five uranium-series dates between 1618 ± 23 (2σ) and 2001 ± 11, and grew at a near-constant rate of 0.3 mm/yr. Stable isotopes (ẟ18O and ẟ13C) of calcite were measured every 0.1 mm along the upper section growth axis and compared with Colonial-period records of known droughts, famines, and population declines (Hoggarth et al., 2017). The ẟ18O and ẟ13C records capture abrupt increases (1-2 ‰ above baseline), coincident (±5 years) with some of the historical records of extreme drought. One notable example includes ẟ18O values 1.0 ‰ above baseline from 1767 to 1770 CE, indicative of an extended dry period contemporaneous with the “Great Famine” of 1765 to 1773. That dry interval is described in historic records as having been characterized by drought, locusts, famine, widespread epidemics, and mortality, which caused a 39 % population reduction (Hoggarth et al., 2017). Evidence for severe drought is replicated for the interval 1765-1768 in a nearby speleothem record from Belize (Kennett et al., 2012). Furthermore, ẟ13C values demonstrate distinct 2 ‰ shifts, from -10 to -8 ‰, and frequent (3-5 year) repeated oscillations, indicating a strong, rapid response of the overlying ecosystem’s carbon budget to climate variability, perhaps related to the El Niño/Southern Oscillation (ENSO). Ultimately, in combination with other local and regional paleoclimate records, study of MAYA-22-7 will help assess the reliability of stalagmite records to capture historic droughts with high temporal accuracy, document patterns of climate variability (e.g., ENSO-related changes), and track land-use change across cultural transitions, while contributing to our understanding of human-climate-environment interactions in the Maya Lowlands.
A modeller’s compass: how modellers navigate dozens of decisions
Authors: Remmers Janneke , Teuling Ryan , Melsen Lieke
Published: March 2024

The usage of hydrological models is diverse and omnipresent. For practical purposes, these models are applied to, for example, flood forecasting, water allocation, and climate change impacts. Numerous methods exist to execute any modelling study. Choosing a method creates a narrative behind each model result, which implies that models are not neutral. So, how do modellers make these decisions? What motivates them to choose a certain method? We conducted fourteen semi-structured interviews between September and December 2021 with nine modellers from six different water authorities and five modellers from four different consultancy companies in the Netherlands. The interviewees are hydrodynamic modellers executing decision-support modelling. The interviews were all recorded and transcribed. We executed an inductive content analysis on the transcriptions. We will discuss how the interviewees motivate the decisions they have made in the modelling process, exploring the non-neutrality of the modelling process. With these insights, we aim to contribute to a discussion on how models, despite their unavoidable non-neutrality, can be robust and dependable to support decision making. Understanding the social aspects behind the modelling process is necessary to create a more complete picture of all the uncertainties involved in modelling, which should include sharing and reflecting on the narrative behind the modelling results.