bluuebunny/crossref_metadata_2025 huggingface dataset:
Variable-resolution global atmospheric models are sensitive to driving SST in ENSO/IOD-Australian rainfall teleconnections
Authors: Liu Ying Lung , Alexander Lisa , Evans Jason , Thatcher Marcus
Published: March 2024

We have investigated the sensitivity of a global climate model to driving sea surface temperatures (SST) in simulating Australian rainfall characteristics, including the El Niño-Southern Oscillation (ENSO)- and Indian Ocean Dipole (IOD)-related rainfall variability. We employed the Conformal Cubic Atmospheric Model (CCAM), a global atmospheric model characterized by variable resolution, CCAM was forced by two SST datasets with different spatiotemporal resolutions: the 0.25° daily Optimum Interpolation Sea Surface Temperature (CCAM_OISST) version 2.1 and the 2° monthly Extended Reconstruction SSTs Version 5 (CCAM_ERSST5). A benchmarking framework was employed to appraise model performance, revealing strong agreement between the simulations and the Australian Gridded Climate Data (AGCD) in climatological rainfall spatial patterns, seasonality, and annual trends. It is noted that both simulations tend to overestimate rainfall amount, with CCAM_OISST exhibiting a larger bias.Moreover, CCAM's performance in capturing ENSO and IOD correlations with rainfall was assessed during Austral spring (SON) using a novel hit rate metric. The findings underscore that only CCAM_OISST effectively reproduces observed SON ENSO- and IOD-rainfall correlations, achieving hit rates of 86.6% and 87.5%, respectively, in contrast to 52.7% and 41.8% for CCAM_ERSST5. Noteworthy disparities in sea surface temperatures were observed along the Australian coastline between OISST and ERSST5 (the so-called “Coastal Effect”). These disparities may be attributed to spatial interpolation errors arising from the differences in resolution between the model and driving SST. An additional experiment within CCAM, masking OISST with ERSST within a 5° proximity to the Australian continent, underscores the pronounced impact of the “Coastal Effect” on IOD-Australian rainfall simulations. Conversely, its influence on ENSO-Australian rainfall was constrained. Therefore, realistic local SSTs are important if model simulations are to reproduce realistic IOD-rainfall responses over Australia. Additionally, even though an SST product with a longer time span is preferred in simulating IOD-related variability, circumspection is warranted in the analysis of the impact of IOD on Australian rainfall when utilizing climate model output with a substantial discrepancy in spatial resolutions between the model and the driving SST. After showing CCAM’s ability to simulate ENSO- and IOD-rainfall, our future research will involve pacemaker experiments to isolate remaining climate modes and investigate their independent impact on Australian rainfall.
Progress in forecasting carbon, water and energy fluxes in improved and degraded pastures: data-model comparison near Sydney Australia 
Authors: Pendall Elise , Knauer Juergen , Wright-Osment Nick , Macdonald Catriona , Barton Craig , Chandregowda Manju , Power Sally , Medlyn Belinda
Published: March 2024

Livestock grazing contributes to greenhouse gas (GHG) emissions, soil degradation and erosion, and loss of biodiversity. Regenerative pasture management includes improvements such as sowing high-diversity seed mixtures with legumes and other deep-rooted forbs in addition to C3 and C4 grasses, alternating intensive grazing with rest periods, bio-based fertilizers, etc. These improvements may alleviate degradation and restore multiple ecosystem services, including soil carbon sequestration and heat wave mitigation. Predictive understanding of management impacts requires process-based models that accurately simulate herbaceous growth and allocation in response to grazing and irrigation events. Moreover, accurate and timely model forecasts depend on well-validated data collected at appropriate temporal and spatial scales, delivered with low latency.We used four years of eddy covariance data in combination with vegetation indices and a process-based model to improve estimates of Net Ecosystem Production (NEP) and energy balance in response to livestock and wildlife grazing in an area with fluctuating soil moisture availability. The enhanced vegetation index (EVI) for the degraded pasture, grazed mainly by native wildlife (kangaroos), demonstrated wide seasonal variations of 0.2 to 0.6, whereas EVI was maintained more consistently close to 0.5 for an improved pasture, grazed intermittently by cattle or sheep. Across three wet years, NEP for the improved pasture averaged 12% higher compared to the degraded one (153 vs. 137 g C m-2 y-1), associated with average 20% greater gross primary production (GPP; 1822 vs. 1521 g C m-2 y-1). However, NEP on the improved pasture was lower than on the degraded pasture in two of those three years, possibly due to grazing-related differences in biomass removal. Sensible heat fluxes were higher from the degraded pasture, especially during hot/dry periods. Ongoing analyses are evaluating soil C storage for benchmarking flux data. Model predictions are also being improved by validating representation of productivity by C3 and C4 species and carbon allocation to roots and crowns. This work contributes to enhancing environmental sustainability in managed grasslands with near-real-time forecasting ability for grazing and irrigation management.
Advancing in the estimation of effective recharge and its propagation in karst aquifers by combining soil moisture observations and the natural responses of springs. An example from Southern Spain.
Authors: Carrasco Martín Alejandro , Mudarra Martínez Matías , De la Torre Martínez Beatriz , Hartmann Andreas , Andreo Navarro Bartolomé
Published: March 2024

Improving our comprehension of infiltration processes in karst systems is crucial for a better adaptation to the global change regarding water resources availability and management. In this work, the effective recharge under different meteorological conditions and its transfer along the vertically distributed compartments of a geologically complex karst aquifer in southern Spain have been evaluated. Continuous records of soil moisture and temperature values (at 5 and 10 cm depth and the soil-rock transition -average depth of 28 cm-) have been combined with hourly hydrodynamic and hydrothermal responses recorded at two springs with a marked influence of the unsaturated zone (UZ) and the saturated zone (SZ), respectively.Most rainfalls generate soil moisture signal in the shallowest probes. However, a mean increase of soil water content of 10.5% in summer (from background values of 2.5%) and 6.1% in autumn-winter (from 9.6%) at the soil-rock interface were needed to produce hydrodynamic responses in the system: first in the spring related to the UZ, with a time delay of 4-9 hours after moisture peaks, and then (14-18 hours) in the spring draining the SZ, but only during autumn-winter recharge events. In addition, recharge caused decreases (up to 0.9°C) in the temperature of the water drained by the first spring, while lagged rises (up to 0.6°C) occurred in the second outlet.Transmission of the input signal would be favoured by stronger karstification, but the presence of inter-bedded detrital formations in the lithological sequence of the aquifer (partially confined in the SE border) filter and buffer groundwater flows before being drained by the spring related to the SZ. These findings will help to assess thresholds for effective infiltration and to predict groundwater recharge in karst aquifers under different climate change scenarios.
How to tackle climate-related restoration in the forest-based sector? A focus on policy trade-offs 
Authors: Ludvig Alice
Published: March 2024

When the EU Commission launched the plan of planting additional “three billion trees” within the Green Deals` strategy, it did not foresee the outcry amongst environmentalist groups and forestry sector groups alike. For both types of stakeholders, the measure is not effective, albeit for opposite reasons: Whilst environmentalists criticise that it halters the increase of biodiversity, the forestry sector interest groups denote the strategy as not understanding the practices of tree planting in forest management. Indeed, the policy so far is reported as one of European failure, at least according to the forest reporting and monitoring systems (Forest Information System for Europe, 2022). The paper sets out to investigate the current policy responses which mirror the manyfold demands around forests for both climate mitigation and adaptation measures (Ludvig et al. 2021). Forests are often depicted as best solutions to carbon storage and the building of carbon stocks (Law et al. 2011). However, foresight studies on grounds of forest inventories have shown that forests cannot respond to many of these demands (Ledermann et al 2022)By way of policy document analysis and expert interviews with different decision takers and interest groups at EU level (forestry, environment and climate), my research firstly asks “How is restoration for reaching climate goals perceived?” and secondly “how do the current policies relate climate-goals with restoration in the forest and land use sector?”.The paper will contribute to disentangle the principal debates about principal trade-offs and accompanying policy mixes in the field of contested natural resources and eco-system services. Across the different documents, the understanding of “restoration” differs; likewise so along the range of stakeholder opinions. Not surprisingly, all interviewed stakeholders see the tackling of climate change as a priority. But the grounds of (scientific) understanding and argumentation are diverse. The paper disentangles those differences with outlining a classification of the principal grounds of understanding/perceptions in order to conclude with a proposal for synergetic effects of the key policy strategies involved.
NITRINET: A nitrification predictive model for reclaimed water distribution networks
Authors: Gómez Lucena Ignacio , Camacho Poyato Emilio , Rodríguez Díaz Juan Antonio
Published: March 2024

The present work consists of the development of a model (NITRINET) to simulate nitrification processes in reclaimed water distribution networks for agricultural irrigation. Due to water scarcity and climate change scenarios, irrigation with reclaimed water has gained interest worlwide, especially in arid and semi-arid regions, like the Mediterranean Basin. The Tintín Irrigation District distribution network (Montilla, southern Spain) was selected as case study. The importance of this model relies on the fact that the chemical composition of reclaimed water varies spatially along the distribution network. It has been observed that nitrate concentrations increase along the irrigation network in contrast to the reduction observed in the ammoniacal forms. It confirms that nitrification processes are occurring inside the pipes. To carry out precision fertigation strategies (fertilization and irrigation simultaneously) and optimize the amount of fertilizer applied it is necessary to determine the concentration of nutrients present in the water arriving at each farm. The nutrients that reclaimed water already carries must be considered when planning fertilization. This allows for a significant reduction in the amount of fertilizer applied to the soil, which has a positive impact both on the environment and on the farmer’s economy. Simulations performed with NITRINET have shown promising results, predicting water pH and the concentration of ammoniacal nitrogen (NH4+-N) and nitric nitrogen (NO3--N) in irrigation water arriving at farms with a mean absolute error of 0.34, 1.46 mg·L-1 and 1.23 mg·L-1, respectively. The main purpose of NITRINET is that it can be used as a Decision Support System when planning fertilization at irrigation district level. The findings of this work suggest that spatio-temporal variability of water quality must be considered when reclaimed water is used for irrigation, especially in big irrigation districts with long pipe distances. 
Improving fertigation scheduling by combining continuous monitoring and numerical modeling of the root zone
Authors: Lazarovitch Naftali , Simunek Jiri
Published: March 2024

In recent years, tremendous progress has been made in making the information gathered by sensors located on agricultural fields available almost immediately. Transferring the data directly to the cloud and rapidly presenting it to researchers, decision-makers, and farmers assist in optimally determining the timing, amount, and composition of fertigation. There have been ongoing efforts to reduce the technological and economic barriers to the efficient and reliable use of sensors that continuously monitor the root system’s heterogeneous and dynamic nature. Despite this, there are still many open questions related to determining the structure and installation locations of the sensors, the optimal algorithm with which the scheduling is determined, and how different sensing methods are combined to make optimal decisions.Sensor development is usually done using in situ experiments. These complex and expensive experiments ultimately result in a long development time. Using numerical models may accelerate the development of sensing methods and the selection of the optimal algorithm for fertigation. Numerical models are used as a research tool for understanding, quantifying, and predicting phenomena and processes in the soil-plant-atmosphere system and for planning and managing water resources and their quality, including irrigation and drainage. Despite their complexity, numerical models are increasingly used thanks to a better understanding of water flow and solute transport processes, the development and improvement of mathematical methods for solving governing equations, and the accelerated development of computers capable of calculating different processes simultaneously in small intervals of time and space.The presentation will review three sensing methods and present a combination of models that solve the water status and the fertilizer concentration in the root zone. The methods that will be reviewed are a) a tensiometer for measuring soil pressure heads, b) a suction cup for inferring soil solution concentrations, and c) a minirhizotron for evaluating the root system structure.Determining optimal fertigation undoubtedly requires a multidisciplinary approach that considers the root zone’s physical, chemical, and biological characteristics. The combination of continuous measurements and numerical models may improve decision-making regarding resource application, thus optimizing the use of water and fertilizers while increasing economic profit and reducing environmental impacts.
Understanding the tropical high-cloud feedback through the ice-water-path lens
Authors: Deutloff Jakob , Naumann Ann Kristin , Brath Manfred , Buehler Stefan
Published: March 2024

The response of tropical high clouds to global warming has the potential to produce an important climate feedback but remains poorly constrained. To improve our understanding of the tropical high-cloud feedback, we develop a conceptual model of the high-cloud radiative effect as a function of the ice water path (IWP) and surface temperature. This model provides a framework for analysing how changes in IWP distribution and cloud top height with surface warming can generate a tropical high-cloud feedback. By including the entire IWP range, it improves on previous conceptual models that rely on cloud fractions. To parameterize our conceptual model, we use atmospheric profiles from global simulations with the ICOsahedral Nonhydrostatic weather and climate model (ICON) with 5 km horizontal resolution, which are used to calculate the radiative fluxes offline with the line-by-line Atmospheric Radiative Transfer Simulator (ARTS). This setup allows us to “switch off” the high clouds in the radiative transfer calculations to better study the radiative effect of high clouds over low clouds. Our conceptual model represents the main physical processes underlying the high-cloud radiative effect and is able to reproduce the results from the ARTS simulations. It therefore provides a valuable framework for analysing the tropical high-cloud feedback produced by climate models and helps to understand the origin of the associated uncertainties.
The Influence of Freshwater Input on the Evolution of the 1995 Benguela Niño
Authors: Costa Aroucha Leo , Lübbecke Joke , Körner Mareike , Imbol Koungue Rodrigue Anicet , Awo Founi Mesmin
Published: March 2024

Benguela Niño events are characterized by strong warm sea surface temperature (SST) anomalies off the Angolan and Namibian coasts. In 1995, the strongest event in the satellite era took place, impacting fish availability in both Angolan and Namibian waters. In this study, we use direct observations, satellite data, and reanalysis products to investigate the impact that the up-until-now unnoticed mechanism of freshwater input from Congo River discharge (CRD) and precipitation had on the evolution of the 1995 Benguela Niño. Before the onset phase of the event, anomalous rainfall in November/December 1994 at around 6ºS, combined with a high CRD, generated a low salinity plume. The plume was advected into the Angola-Namibia region in the following February/March 1995 by an anomalously strong poleward surface current generated by the relaxation of the southerly winds and shifts in the coastal wind stress curl. The presence of this low surface salinity anomaly of about -2 psu increased ocean stability by generating barrier layers, thereby reducing the turbulent heat loss, since turbulent mixing acted on a weak vertical temperature gradient. A mixed layer heat budget analysis demonstrates that southward advection of Angolan waters drove the warming at the onset of the event, while reduced mixing played the main role at the event’s peak. We conclude that a freshwater input contributed to the SST increase in this exceptionally strong event and suggest that this input can influence the SST variability in Angola-Namibia waters through a combination of high CRD, precipitation, and the presence of a strong poleward surface current.
Deep learning-based super resolution generative adversarial network for gridded precipitation downscaling across India
Authors: Kumar Pankaj , Murukesh Midhun
Published: March 2024

Precipitation downscaling is recognized as a challenging problem due to its stochasticity and highly skewed distribution. The downscaling of coarse resolution global climate data is most important in the context of regional-scale climate change impact research and assessments. Image super-resolution is a well-established domain in deep learning, which is also analogous to gridded data downscaling. In this study, the performance of a Super-Resolution Generative Adversarial Network (SRGAN), a cutting-edge deep learning-based image super-resolution technique, is assessed in downscaling and reconstructing high-resolution rainfall data over India from the low-resolution input. The main component of SRGAN is a generator network that takes abstract information from low-resolution (10x10) rainfall data to infer a potential high-resolution (0.250x0.250) counterpart. A super-resolution residual neural network is used as the generator network, which is trained via a supervised learning strategy and adversarial learning strategy. The long-term record of gridded rainfall provided by the India Meteorological Department for the period 1901-2021 is leveraged in this study. A statistical downscaling method called bias correction and spatial disaggregation (BCSD) is also deployed under the same constraints of the train-test split to benchmark deep learning-based downscaling methods. The novel methods are comprehensively assessed for their ability to reconstruct distribution, mean, and extreme rainfall during the test period. Our results show that the deep learning-based methods have an upper hand over the BCSD method for gridded rainfall downscaling over the highly complex terrain of the Indian subcontinent.
 
Keywords: Downscaling, Climate data, Gridded rainfall, Deep learning, SRGAN, Image super-resolution
The exploitation of resources created by human beings, an additional alternative for reducing emissions
Authors: Gil García Isabel C. , Fernández Guillamón Ana , Ramos Escudero Adela , Molina García Ángel
Published: March 2024

The urgency of mitigating emissions on our planet drives the exploration of various sources of clean energy. Natural resources, such as solar radiation, wind and water, provide the opportunity to transform them into forms of sustainable energy. In recent decades, the advancement of wind technologies has led the sector to reach full maturity, encompassing both large-scale wind energy generation in marine and terrestrial environments and the implementation of mini-wind solutions. However, we often underestimate the human activities, production processes or technological innovations that generate clean resources, without fully taking advantage of their potential. In this context, the central purpose of this work is to take advantage of wind gusts caused unnaturally and, through small wind power, convert them into clean energy. The proposal is organized in three phases: in the first, a data analysis is carried out that involves taking in situ samples of wind speed and an evaluation of wind potential; In the second stage, the energy conversion is carried out, selecting the mini-wind technology through multi-criteria evaluation methods and determining the amount of electrical energy to be generated; Finally, in the third phase, an analysis of results is carried out that covers different scenarios evaluated according to indicators such as the electricity consumption to be replaced, the quantification of avoided emissions and an economic analysis.
Acknowledgements: Project PID2021-126082OB-C22 funded by MICIU/AEI/10.13039/501100011033 and FEDER, EU
Integrated Approach to Mekong River Flow Modeling: Data Gaps and Climate Trends
Authors: Morovati Khosro , Zhang Keer , Tian Fuqiang
Published: March 2024

The transboundary Mekong River, spanning approximately 4800 km with numerous tributaries and floodplains, serves as a vital resource for power generation, fisheries, and agriculture. Despite its significance, the river's productivity faces disruption due to inadequate cooperation among riparian countries regarding data sharing, the uneven distribution of gauging stations, and data gaps for many parts of the river length. This disparity poses challenges in accurately modeling the river's natural runoff, flow characteristics, and the flooded area, navigating through mountainous and relatively flat terrains.To address this, we have developed an integrated modeling framework comprising a physically-based hydrological model and a hydrodynamic model. For 2500 km of the Mekong River’s mainstream, a highly accurate hydrodynamic model was developed. The produced velocity, water level, and discharge data were compared with gauging stations with continuous data records, showing high accuracy with NSE exceeding 0.93. Additionally, a point-by-point comparison of the yielded water level and discharge data by the hydrodynamic model was conducted with the low-resolution recorded data for stations lacking continuous time series data. Results indicated a high accuracy with an average NSE greater than 0.91, demonstrating the model's precision in capturing the dynamic behavior of the Mekong River.The hydrodynamic model's results were then used to fill data gaps in stations with significant data deficiencies, allowing the production of reliable data and sufficient gauging network distribution for the entire basin. These datasets, combined with recorded gauging data, served as the calibration stations for the developed physically-based hydrological model. This calibration aimed to assess the impacts of climate change on natural runoff, encompassing not only the mainstream but also tributaries and lake floodplains of the Mekong River. Findings revealed a discernible declining trend in natural runoff within the Mekong River over the specified four-decade period.This enhanced modeling capability is particularly crucial for accurately simulating dynamic river flows with insufficient continuous data. Our comprehensive approach contributes to a more precise understanding of the Mekong River's complex hydrological dynamics, supporting informed decision-making for sustainable resource management.
Equality of opportunities in EGU recognitions: The EGU Awards Committee experience
Authors: Blunier Thomas
Published: March 2024

The European Geosciences Union (EGU) is the leading organisation supporting Earth, planetary and space science research in Europe, upholding and promoting the highest standards of scientific integrity, open science and open access research. EGU’s vision is to realise a sustainable and just future for humanity and the planet through advances in Earth, planetary and space sciences.The EGU awards and medals programme acknowledges distinguished scientists every year for their exceptional research contribution to the Earth, planetary and space sciences. Furthermore, it recognises the awardees as role models for the following generation of early-career scientists, encouraging geoscience research. Except for EGU council and award committee members everyone (including non-EGU members) is eligible for receiving an EGU award. Nominations need to be submitted by EGU members online by 15 June every year. Each EGU medal or award is selected through a rigorous assessment of the candidates and their merits through the respective committee. The procedures for nomination, selection of candidates and the time schedule are described in detail on the EGU website. EGU is committed to recognizing scientific excellence providing equal opportunities. The processes and procedures that lead to the recognition of excellence must be transparent and free of biases. However, establishment of clear and transparent evaluation criteria and performance metrics to provide equal opportunities to researchers across gender, continents and ethnic groups can be challenging since the definition of scientific excellence is often elusive. The purpose of this presentation is to share the experiences and efforts of the European Geosciences Union to ensure equal opportunities. The presentation will showcase data and statistics to provide constructive directions towards the objective of offering equal opportunities to researchers from diverse demographic backgrounds.
A remote sensing detection method of the earth's surface anomalies based on multi-dimensional feature space
Authors: Wei Haishuo , Jia Kun , Wang Qiao
Published: March 2024

On-orbit processing is an important way in the real-time remote sensing detection of earth's surface anomalies (ESSA). However, the existing methods cannot comprehensively utilize multidimensional remote sensing characteristics to detect multi-type ESSA in a unified manner. Meanwhile, it is also difficult to realize the comprehensive utilization of multidimensional remote sensing characteristics under the condition of limited storage and computing resources on satellites. Therefore, this study proposed a remote sensing method for detecting multi-type ESSA on orbit based on multidimensional feature space. The proposed method first selected the remote sensing characteristics reflecting the basic earth's surface elements to construct a multidimensional feature space and generated two comprehensive remote sensing characteristics. Then, the optimized storage content of the two comprehensive remote sensing characteristics were used to build a prior knowledge base reflecting the normal conditions of the earth's surfaces. Finally, through comparing the prior knowledge base and the real-time acquired data, this study completed the ESSA detection. The validation results indicated that the proposed method can effectively detect multi-type ESSA with a accuracy of over 85%. Meanwhile, the proposed method simplified the large and complex ESSA remote sensing characteristic system, which would be conducive to greatly reducing the complexity of ESSA detection methods and increasing the possibility of on-orbit processing.
Assessing drought induced subsidence risk in France under current and future climate
Authors: Joffrain Mathis , Bruneau Nicolas
Published: March 2024

Subsidence risk induced by drought produced widespread damages to low- rise buildings in France in 2022, and has become of increasing concern for insurers. Companies expect greater average annual costs in the near future, and modeling solutions are scare to model the impacts by extreme events. In this poster, we present a stochastic model designed to calculate the full distribution of annual losses over an home insurance portfolio. It generates a stochastic set of SSWI footprints based on ERA Land data and at each location, evaluates both the claim propensity and the insured damage. Results will show (i) how damage rates for drought induced subsidence risk compare to other perils in France and (ii) how the risk changes between current and future climate.
What is more important for model calibration: information on the discharge dynamics or information on the discharge volume?
Authors: Clerc-Schwarzenbach Franziska , van Meerveld Ilja , Vis Marc , Seibert Jan
Published: March 2024

Previous studies have shown that information on the discharge dynamics (e.g., variation in the water level) is valuable to constrain the parameters of a lumped hydrological model for some catchments, and that information on the discharge volume further improves model performance for most catchments. It has been suggested that for some catchments an estimate of the mean discharge already leads to a good model fit but so far, there have not been any systematic studies to test this. Therefore, it remains unclear for which catchments (i.e., for which regions or for catchments with specific characteristics) information on the discharge dynamics are most valuable for model calibration, for which catchments an estimate of the mean annual discharge is already sufficient, and for which catchments both data sources are needed for model calibration. Therefore, we used a subset of the Caravan large-sample dataset and assessed the value of water level measurements, estimates of the mean discharge, and both data sources together for the calibration of a simple bucket-type hydrological model. Preliminary results suggest that mainly climatic characteristics determine the relative value of the different data types for hydrological model calibration. This type of assessment of the value of data for a wide range of catchments allows for more optimal allocation of resources when it comes to obtaining limited data for the calibration of hydrological models for ungauged catchments.
Study on the influence of scour around tripod foundation for offshore wind turbine using Discrete Element Method
Authors: Yang Yu-wen , Lo Chia-Ming , Lai Yu-Sen
Published: March 2024

The seabed depth on the western coast of Taiwan is approximately between 20 to 50 meters, making it suitable for the installation of offshore wind turbines with a tripod foundation. Under the influence of water flow, the surrounding sand of the foundation can be eroded, forming scour holes and subsequently reducing the foundation's bearing capacity. The scour holes, influenced by the inherent angle of repose of the sand, undergo continuous erosion and collapse due to water flow, eventually reaching dynamic equilibrium. This study employs the Discrete Element Method (DEM) to conduct numerical simulations of scouring around the tripod foundation of offshore wind turbines. Different diameter particles are used to construct models of the offshore wind turbine tripod foundation and the sand. The dimensions of the seabed sand are 150 cm * 100 cm * 30 cm, with a particle diameter of 20 mm. This study observes the scouring of sand particles under different normal and shear stiffness conditions, resulting in various forms of scouring. The variations in scouring depth, length, and width under different normal and shear stiffness conditions will be discussed.
Elucidating the Impacts of Various Atmospheric Ventilation Conditions on Local and Transboundary Ozone Pollution Patterns: A Case Study of Beijing, China
Authors: Yang Yuanjian
Published: March 2024

The ventilation condition in the atmospheric boundary layer, which varies with the synoptic pattern, is a crucial factor affecting the transport and dispersion of air pollutants. In this study, taking Beijing as an example, local ozone (O3) accumulation and the transboundary O3 pollution (TOP) patterns during the warm season were explored under different boundary layer ventilation conditions by using integrated objective weather classification, non-negative matrix factorization, and backward trajectory model. Results show that local sources are a major contributor to O3 pollution in the whole of Beijing, accounting for ~73.36% of the O3 concentration on average. The local accumulation is mainly facilitated by poor ventilation conditions with weak wind speeds (
Agricultural Drought in Sweden: Assessment of Hazard and Impacts
Authors: Canedo Rosso Claudia , Nyberg Lars , Pechlivanidis Ilias
Published: March 2024

Sweden is known for its abundance of water resources, while future climatic projections indicate a rise in precipitation and temperature rates. However, droughts had severe effects on the environment, society, and agriculture in 2016, 2017 and 2018, highlighting the need for improved drought monitoring and management. The agricultural sector, in particular, suffered significantly during the 2018, 2021, and 2023 droughts, inquiring the need for enhancements in climate adaptation and preparedness. This study aims to assess the agricultural drought in Sweden with a focus on hazard assessment and its associated impacts. Firstly, we unfold the lessons learnt from continental observatories and national services by evaluating the reliability of the derived information and identifying the added value for local decision making. For this, we compare the simulated soil moisture derived from the LISFLOOD and S-HYPE hydrological models, and we evaluate the modelled simulations against earth observation-based soil moisture from the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). Based on the LISFLOOD model, we used anomalies of the soil moisture index and the combined drought index at a 10-day average and at a 5 km spatial resolution. Daily runoff and soil moisture data were also used from the S-HYPE model at about 13 km2 spatial resolution. Secondly, the spatiotemporal drought hazard is assessed using drought indicators to identify drought frequency and intensity. Here, drought indicators such as Standardized Precipitation Index (SPI), Soil Moisture Anomaly (SMA), and Combined Drought Index (CDI) are computed using S-HYPE model outputs. Finally, we evaluate the utility of integrating data from drought indices (SPI-1, SPI-3, SMA and CDI) and crop yield of wheat and potato to improve the understanding of the links between impacts and statistical indices. The relationships between drought onset and yield response are evaluated for different aggregation of time periods and lags (i.e., monthly). The study outputs are used to assess alternative ways to improve decision-making regarding adaptation strategies to reduce agricultural vulnerability and the capability of addressing the challenges posed by a changing climate.
Assessing the distribution and characteristics of supraglacial channels in an Alpine setting
Authors: Wytiahlowsky Holly , Stokes Chris , Hodge Rebecca , Clason Caroline , Jamieson Stewart
Published: March 2024

Supraglacial channels are an increasingly common glaciological feature due to intensifying surface melt and form a key component of glacier hydrology and mass balance, transporting meltwater to englacial, subglacial, and peripheral positions. Whilst their occurrence is becoming increasingly well-documented on ice sheets, little is known about the distribution of channels on mountain glaciers, which often fall below the resolution of commercial satellites. Using high-resolution orthophoto imagery (~10 cm) and digital elevation models (~0.5 m), we provide the first inventory of supraglacial channels in an alpine environment, focusing on Valais Canton, Switzerland. We manually delineated 1890 channel segments on 85 glaciers, recording glacier characteristics across all 207 snow-free glaciers >0.1 km2 in Valais Canton, encompassing glaciers of differing debris-cover, altitude, and slope. We find that channel segments have a mean length of 212 m and a slope of 8°, with most channels exhibiting low sinuosity (mean: 1.1) and those with higher sinuosity (max: 3.8) only existing on very low surface slopes (
Emission Inventory and Critical Assimilative Carrying Capacity of Petroleum Refinery in India
Authors: Gupta Udita , Jayaraj Sruthi , Nagendra S. M. Shiva
Published: March 2024

Petroleum refineries generate hydrocarbons, SO2, SO3, VOCs, NOx, CO, and PM10/2.5 as air pollutants through fuel combustion for operating process units/stacks, evaporation from tank farms, fugitive emissions, etc., which have been found to be responsible for causing episodic health effects in the population residing nearby the refinery. The stack emissions are one of the lesser studied and a major contributor to air pollution from a petroleum refinery. This paper calculates its emission inventory using the USEPA Methodology based on fuel consumption and simulates ground-level concentration using the dispersion model. Further, the study calculates critical assimilative carrying capacity (ACC) and remaining carrying capacity (RCC) by conducting iterative simulations on CALPUFF View, a Lagrangian approach based Gaussian Puff Dispersion Model. The total emissions of SO2, NO2, PM10, and CO are found to be 2331.57, 1665.34, 213.565, and 800.841 tons/year respectively, the majority of which are contributed by primary and captive process units. The 24-hour average maximum predicted concentration values for SO2 and NO2 are 26.8 μg/m3 and 27.9 μg/m3 respectively which occurred in the winter season. The lower ground levelconcentrations are attributed to the use of fuel oil with sulphur content (0.75% by mass), Sulphur Recovery Unit (SRU) which recovers sulphur element from acid gases and low NOx burners. By iterative simulations, it is found that for SO2 and NO2, 65% of the carrying capacity remains at current emissions and the current RCC of NO2 and SO2 stands at 4327.6 tons/year and 3091.06 tons/year respectively. The minimum RCC is observed for winters, corresponding to the minimum ventilation coefficient of 1517.15 m2/s, and similarly, the maximum RCC is observed for the summer season at maximum ventilation coefficient of 3413.49 m2/s. The peak values of ACC and RCC can be used for planning possible expansion of the refinery and seasonal variation of the ACC and RCC can be used to bring down the plant capacity in winter and post-monsoon seasons.
Structural softening in poro-elasto-plastic media
Authors: Alkhimenkov Yury , Juanes Ruben
Published: March 2024

Structural softening is a well-known phenomenon in single-phase materials. If we consider a single-phase material, assume an elastoplastic rheology, and perform a strain-driven loading under pure shear boundary conditions, the evolution of the integrated stress will exhibit a softening beyond its peak. This is true for non-associated flow rules considering an ideal plasticity model with, for example, Mohr-Coulomb or Drucker-Prager yield criteria. The post-peak softening is usually associated with the development of the localized shear zones. However, this phenomenon hasn’t been properly analyzed for the case of porous rocks modeled with the quasi-static Biot’s poroelastic equations.In this contribution, we present numerical results considering the poro-elasto-plastic rheology with a focus on structural softening. We show that the post-peak structural softening might be significant and exhibit large stress drops. The most important outcome is that even a little fluid overpressure leads to much larger stress drops compared to scenarios without any kind of fluid overpressure. This result may shed some light on the phenomenon of large earthquakes associated with small injection rates in geothermal or CO2 sequestration fields. References:Vermeer, P. A. (1990). The orientation of shear bands in biaxial tests. Géotechnique, 40(2), 223-236.
Optimisation of Regional Weather Forecasts for Northern Algeria Using a Convolutional Neural Network and AROME Model Analysis.
Authors: Bousri Islam
Published: March 2024

This study introduces an innovative approach aimed at enhancing the accuracy of regional weather forecasts from the AROME model, covering northern Algeria. By leveraging AROME analysis, a refined representation based on real observations and widely used for monitoring and validating our model, our primary objective was to precisely correct surface parameters, including temperature at 2 meters, humidity, wind force, and sea-level atmospheric pressure (MSLP). This correction was performed based on their forecast ensemble, all while preserving spatial resolution.This methodology has yielded promising results, demonstrating a significant improvement in the accuracy of regional weather forecasts. The presentation will delve into the detailed integration process of the Convolutional Neural Network (CNN) and AROME analysis, highlighting the successes achieved in correcting essential surface parameters. These advancements strengthen the reliability of regional meteorological models, with positive implications for resource planning and management in the northern region of Algeria.
Internal wave topography interactions in the presence of a steady surface current
Authors: Gururaj Saranraj , Guha Anirban
Published: March 2024

Wave--topography interaction is one of the primary mechanisms through which internal wave energy cascades to small length scales in the oceans. At small length scales, internal waves become unstable and break down, leading to turbulent diffusion and mixing. Precise diffusivity parametrisations are crucial for modeling ocean flows accurately. We study the interactions of a mode-1 internal wave with an isolated topography in the presence of a steady, stable surface current. For various amplitudes of the surface current, we investigate scattering caused by Gaussian shaped topographies by independently varying height and slope. In the presence of a surface current, a mode-1 wave that propagates in the direction of the current (denoted by M1W) has different properties compared to a mode-1 wave that propagates against the current (denoted by M1C), and we focus on both M1W and M1C. For all the heights considered, for both M1W and M1C, the current does not have a singular effect: it can reduce or increase scattering depending on the slope of the topography. Scattering due to large amplitude topographies (even with a small slope) can be quite different in the presence of a surface current. However, scattering caused by small amplitude topographies does not change significantly even in the presence of strong surface currents. Topographies with very high slopes (commonly known as supercritical topographies) scatter M1C more compared to M1W. Finally, we provide a brief analysis of the generation of superharmonic waves due to wave--topography interactions that occur in the presence of a surface current.
Using FracpaQ and seismic attributes to assess seismic scale fractures in carbonate reservoirs
Authors: Elattar Hager , Collier Richard , Glover Paul W.J.
Published: March 2024

Abstract: Fractured carbonate reservoirs are of great importance in the oil industry due to their significant role in global oil reserves and complex nature, where the majority of these reservoirs are naturally fractured, making them complex and challenging for oil recovery. The detection and characterization of fractures are essential for understanding the reservoir's petrophysical properties and hydrocarbon recovery potential as they play a critical role in reservoir performance. In this paper we have used 3D seismic from the Razzak field in the Western Desert, Egypt, with a specific focus on the Alamein dolomite reservoir. The reservoir holds significance due to its prolific oil-bearing nature, and featuring widespread lateral distribution in the northern Western Desert. Additionally, its contribution to an active Mesozoic petroleum system emphasizes its importance. Using Petrel software, the Alamein top and visible faults were identified, leading to the creation of a structural map illustrating the WSW-ENE axes of the Alamein's structural culminations in the southern part of the horst block. Owing to an extensional force during the Jurassic period with a NE-SW orientation, resulting from rifting, was evident, marked by the formation of normal faults associated with the opening of the Neotethys in the NE-SW direction. In the interpretation of 3D seismic data for Alamein dolomite reservoir, only one major listric normal fault was identified. However, the presence of minor faults or fractures, not easily discernible with conventional seismic techniques, is plausible. To address this, volume attributes were applied to detect subtle changes in seismic properties: (i) the curvature operation calculated the dip and azimuth angles, aiding in identifying structural complexities like faults and fractures, (ii) the maximum curvature value highlighted areas of steeply dipping or folded structures, (iii) Edge detection emphasized sharp boundaries, yet no hidden fractures or minor faults were revealed. The variance attribute yielded limited information, but Ant tracking on the variance cube effectively identified hidden minor faults and fractures. Incorporating the Ant track attribute into FRACPAQ software provided an objective methodology for quantifying fracture patterns, revealing NW-SE-oriented fracture segments in contrast to the WSW-ENE orientation of the major fault. Consequently, seismic attributes will unveil concealed fractures, and the application of FRACPAQ will prove effective in furnishing data on fracture orientation and length statistics.Key words: FracpaQ; seismic attributes; fractured carbonate; Razzak fieldHow to cite: Elattar, H.A., Collier, R., and Glover, P. W. J.: Using FracPaQ and seismic attributes to assess seismic scale fractures in carbonate reservoirs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1674, https://doi.org/10.5194/egusphere-egu24-1674, 2024.
The influence of rainfall patterns on shallow landslides in New Zealand
Authors: Smith Hugh , Neverman Andrew , Betts Harley , Spiekermann Raphael
Published: March 2024

Understanding how rainfall events influence the pattern and magnitude of landslide response is an important research focus from geomorphological and hazard planning perspectives. Few studies quantitatively relate spatial patterns in rainfall and landslides, largely due to difficulties in acquiring landslide inventories and data on rainfall patterns for individual storm events. Here, we aim to a) identify which factors most influence susceptibility to rapid shallow landslides at the event scale and b) assess how the spatial density of landslides varies in relation to rainfall. While we do not know precisely when individual landslides were triggered during an event, we can examine how the overall pattern of landslides varies spatially in relation to rainfall and geo-environmental factors.
Rapid landslides triggered by intense rainfall occur extensively in New Zealand’s hill country (land