bluuebunny/crossref_metadata_2025 huggingface dataset:
Computing precipitations with a 1D vertical (radiative-convective) model using zero parameterizations.
Authors: Pikeroen Quentin , Paillard Didier
Published: March 2024

The main philosophy in building a climate model is to represent the most possible number of phenomena, with the purpose of answering the most possible number of questions, with one unique perfect model. For this purpose, climate models have historically evolved from energy balance models, to radiative-convective models, to general circulation models, to the earth system model, with growing complexity. While this approach is relevant in some domains (e.g. climate services), more simple models could answer simple questions (e.g. calculate the mean temperature or precipitations for paleoclimates). Moreover, all climate models use parameterizations to represent the processes with unknown or not numerically solvable physical laws. Moreover, to make them accurate, all climate models tune their parameters. For example, in the atmosphere in the vertical direction, the energy flux often obeys a Fourier-like law with a "conductivity" coefficient tuned to fit observations. The approach we use is entirely different, and because of that, we need to rebuild everything from scratch. We want to construct a simple atmospheric model with no parameterizations (the ultimate goal could be to couple it to a vegetation or an ice model and run long simulations).We use the MEP hypothesis (maximum entropy production) to do so. This hypothesis has been used in realistic cases with parameterizations, or without parameterizations in more theoretical cases (like 2-box models). However, we aim to construct a full climate model with the MEP hypothesis. First, we restrict ourselves to a vertical tropical atmosphere: a radiative-convective model. Only stationary states are considered. Also, the relative humidity is fixed at 100%. A realistic radiative code is used, and convection is computed with the MEP hypothesis. The computed temperatures fit well with the observations. Also, precipitations can be computed and are coherent with observations. This means that almost only the knowledge of radiative transfer is needed to obtain a good order of magnitude of precipitations. In recent developments, the model has allowed deep convection, leading to slightly different precipitations. When relative humidity is allowed to vary; in the simple convection case, the MEP solution gives a 100% relative humidity almost everywhere; and the deep convection case gives a non-trivial relative humidity profile.Because MEP is only a hypothesis, we still need to find out if the MEP solution is the exact solution. However, it must represent some upper bound in the system because it corresponds to a maximum. It is already interesting to explore what this upper bound is.
Evaluating a state of the art, internationally coordinated pan-Arctic regional climate model ensemble
Authors: Mooney Priscilla , Samantaray Alok , De Falco Chiara , Mottram Ruth ,   PolarRES regional climate modellers
Published: March 2024

Within the Horizon 2020 project PolarRES, a new ensemble of regional climate simulations has been developed using the latest generation of regional climate models (RCMs) for the Arctic. These state-of-the-art RCMs downscale the ERA5 reanalysis over the period 2001-2020, covering the entire Arctic region at a grid spacings of approximately 12km. Furthermore, all simulations follow the Polar CORDEX protocol for the next generation of regional climate projections of the polar regions. This new ensemble of high-resolution climate simulations offers considerable opportunities to advance our understanding of the present-day climate of the Arctic. However, a first step to realising this potential is to evaluate the performance of the regional climate models, highlighting their strengths and limitations. This is also necessary for understanding and interpreting the future projections that will be generated by these RCMs using a novel storylines approach to downscale CMIP6 models. The work presented here will focus on the simulations of the present-day climate driven by the ERA5 reanalysis. As part of the evaluation process, a clustering technique is applied to reanalysis data to identify regions with similar annual and seasonal characteristics of surface temperature and precipitation. This approach allows for a better understanding of the regional climates of the Arctic, provides a more physically consistent basis for model evaluation, and eases the investigation of model deficiencies in simulating regional scale forcings. This work will focus on the regionalisation of the Arctic for model evaluation and present preliminary results of the application of this regionalisation to the aforementioned Arctic climate simulations.
Unveiling the Geodetic Distribution of Temporal Characteristics in Rainstorm Events across Republic of Korea
Authors: Cha Hoyoung , Baik Jongjin , Kim Hyeon-Joon , Lee Jinwook , Byun Jongyun , Jun Changhyun
Published: March 2024

AbstractThis study analyzed geodetic distribution about temporal characteristics in rainstorm (> 1 hour) observed at approximately 600 rainfall stations across Republic of Korea. Utilizing minute-scale precipitation data observed by rainfall stations from 2000 to 2022, independent rainstorm events separated from rainfall data per unit time (i.e., 10, 20, 30, and 60 minutes) and Inter-Event Time Definition (IETD) (i.e., 2, 3, 4, and 6 hours). The significant variations in rainfall characteristics are defined as the number of independent rainstorm events, rainfall duration (hour), amount (mm), and intensity (mm/hour) for quantifying the temporal characteristics across rainfall stations. We quantified temporal characteristics among rainfall characteristics observed by rainfall stations based on latitude and longitude. The number of independent rainstorm events varies significantly depending on unit time and IETD, and the occurrence of events was frequently observed in areas characterized by island features. The rainfall amount for independent rainstorm events obscured significant characteristics, excluding Halla Mountain on Jeju Island. The geodetic distribution for the duration and intensity per rainstorm event varied depending on the characteristics of the region (i.e., island, mountain, etc.). Based on these results, it was confirmed that certain temporal characteristics vary according to regional features. In future research, we intend to utilize this information to cluster rainfall stations based on temporal characteristics.Keywords: Independent Rainstorm Events, Temporal Characteristics, Geodetic Distribution, Regional Features, Republic of KoreaAcknowledgmentThis research was supported by Korea Environment Industry & Technology Institute (KEITI) funded by Korea Ministry of Environment (RS-2022-KE002032 and 2022003640001) and was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1A4A3032838 and No. RS-2023-00250239).
A holistic examination of Disaster Risk Management in the context of volcanic risk in the Canary Islands
Authors: García-Vaquero María , García-González Sara , Padrón-Fumero Noemi , Crummy Julia , Febles-Arévalo Tamara , Díaz_Pacheco Jaime
Published: March 2024

Understanding the complexity of past chain events in depth and learning from them to improvedecision-making in a dynamic context can be challenging. Although efforts have been made toaddress these challenges, further research is needed. Storylines have proven to be a valuablequalitative tool not only for describing multi-hazard scenarios, understanding the system andthe interrelationships between different elements, but also for improving resilience by takinginto account lessons learned throughout the process.The 2021 La Palma volcanic eruption, with its enduring aftermath characterised by atmosphericgas emissions in one of the island's prime tourist locales, exemplifies the intricate challenges indecision-making for planning, procedural execution, and organisational management. Thisevent highlights the extensive and profound impacts of such dynamic risks, underscoring theneed for adaptable and robust strategies in risk management and response. Our study aims toprovide a comprehensive understanding of the whole volcanic disaster in detail by integratingthe different dimensions (multi-hazard, multi-risk and systemic impacts) into the disaster riskreduction cycle (prevention and preparedness, response and recovery). This approach providesa holistic and proactive approach and allows for an assessment of the impact andconsequences of the decision making process in the Canary Islands at each stage over time. Forthis purpose, a 20-year timeline will be used, starting in 2004 when the first seismic swarmindicated a possible volcanic eruption in the island of Tenerife.This research uncovers a significant shortfall in risk planning across all stages of the disasterreduction cycle on the islands, noting a disproportionate emphasis on administrativecoordination during emergencies. The absence of preemptive measures in land-use planning,especially in areas highly vulnerable to exposure, exacerbates the complexity of post-eruptionrecovery. By thoroughly examining the decision-making processes, planning strategies, andorganisational procedures, this study aims to distil key lessons from recent experiences. Suchan endeavour enhances our comprehension of the complex interplay between decisions andrisks, providing critical insights for bolstering resilience against volcanic disasters.
Innovative irrigation strategies for rice in the Mediterranean areas
Authors: Gharsallah Olfa , Facchi Arianna , Arbat Gerard , Cufí Sílvia , Ramírez de Cartagena Francisco , Romani Marco , Rienzner Michele , Tkachenko Darya , Mira Concepcion , de Lima Isabel Pedrosa , Gonçalves José Manuel , Aboukheira Abdrabbo Shehata , Shebl Saad , Enginsu Melih
Published: March 2024

Rice is the world's most important food crop, as it is a staple food for more than half of the world's population, and the global demand for rice is expected to increase. More than 1,000,000 hectares in the Mediterranean basin are devoted to rice cultivation. The most important producing countries are Italy (IT) and Spain (SP) in Europe (over 310,000 ha), and Egypt (EG) and Turkey (TR) among non-EU countries (over 600,000 ha). In the Mediterranean region, rice production is of great socio-economic and environmental importance, as rice is often a crucial product for internal consumption and export, especially in Egypt, where it is considered strategic for food security. Despite of this, the peculiar flooding conditions in which rice is traditionally grown lead to the use of huge water volumes, as well as to the potential release of greenhouse gases and pesticides into the environment. For this reason, the introduction of water-saving irrigation strategies could reduce water consumption and decrease the harmful environmental impacts associated with rice flooding, while maintaining yield and rice grain quality.In the context of the MEDWATERICE project (https://www.medwaterice.org/; PRIMA-2018), alternative irrigation methods to WFL were tested in case studies implemented in five Mediterranean countries (Italy, Spain, Portugal, Turkey, Egypt). Irrigation strategies for each CS were selected with the support of local Stake-Holder groups and applied in experimental fields measuring/estimating all the water balance terms on a daily basis. Wet seeding and alternate wetting and drying (AWD), dry seeding and delayed flooding (DFL), reduction of inlet/outlet discharges (WIR), a better control of ponding water level through automated gates (DFL-aut), hybrid irrigation (HYBRID), sprinkler irrigation (SPRINKLER), surface drip (DRIP) and subsurface drip irrigation (SDI) were implemented for at least two years in the period 2019-2021 alongside the traditional WFL, to investigate their environmental and economic sustainability and social acceptability.
High-resolution modelling of methane plumes: validation and sensitivity experiments to explore UAV and satellite observations
Authors: Yuvaraj Rakesh , Lauvaux Thomas , Ciais Philippe , Bonne Jean-Louis , Joly Lilian , Groshenry Alexis , Ba Antoine
Published: March 2024

With the rapid expansion of high-resolution satellite imagers collecting methane plume images across the globe, emissions assessment has been performed using Gaussian plume approaches, mass-balance estimations, or flux divergence methods. But many plumes of methane sampled by space borne imagers present complex features due to topography, to the presence of infrastructures, or to discontinuous turbulent structures inherent to the near-surface atmospheric dynamics. We present here the results from a Computational Fluid Dynamics (CFD) model to study and to analyse methane emissions from point sources using the Fire Dynamics Simulation (FDS) model. High-resolution models like FDS allow to include the terrain characteristics, buildings, canopy cover, and use the real-time weather (re-analyses or field measurements of 3-D wind conditions) to simulate the observed plumes. In addition, FDS enables the study of the non-linear relationship between emissions and the height of the methane release, the temperature of the decompressed gas, and its mass flow rate.
Controlled released experiments of methane measured by drone are used as a starting point to evaluate our FDS simulations and to perform various sensitivity experiments applied to real-cases (with terrain information from SRTM30, temperature and wind from meteorological ERA-5 re-analyses). We defined the optimal model physics configuration and domain characteristics based on two UAV campaigns (TADI campaigns in 2019 and 2021). The second part of our work is based on controlled releases measured by the high-resolution PRISMA satellite, covering a wide range of methane concentrations under various atmospheric conditions to evaluate the performances of FDS when simulating pressure-weighted columns.
We conclude here that high-resolution atmospheric simulations outperform current approaches when analysing irregular plumes due to uneven terrains, buildings, and canopy. This method helps to improve the quantification of even small methane leaks from different point sources such as oil and gas storage facilities.
On the detection and tracking of mesoscale ocean eddies: Parameter sensitivity
Authors: Bērziņa Stella , Gruber Nicolas , Münnich Matthias
Published: March 2024

The characteristics of coherent mesoscale eddies are an important point of evaluation for high-resolution ocean and coupled climate models. Mesoscale eddies are rotating features in the ocean on horizontal scales from 10 to 100 km that transport physical, chemical and biological properties of the ocean water. There are many possible ways to identify and track eddies (sea surface height anomalies, sea surface temperature anomalies, vorticity, etc.) and even within one method parameters can be adjusted to lead to different eddy identification results, for example, the allowed shape error of eddies.  Here we explore systematically the sensitivity of the identification and tracking results to choices made with regard to data, allowed eddy size and shape error and the use of different high-pass filters. Additionally, eddy identification and tracking are done on a regular latitude-longitude grid rather than the native model grid, therefore, the impact of the chosen grid size is assessed.To this end, we use “py-eddy-tracker” (Mason et al. 2014) a commonly used open-source geometry-based approach. The algorithm uses sea level anomaly data and several adjustable parameters to identify eddies. It then joins the identified eddies to form tracks by using the ellipsoid method described in Chelton et al. 2011, where the two closest lying eddies in subsequent time steps are connected if they occur within a restricted search region.We apply this identification and tracking algorithm to high frequency output from different high-resolution coupled climate models run as part of the EERIE project and compare the results of eddy characteristics to observations. This study will help to make more informed and study-specific choices when setting threshold values in eddy identification algorithms for model assessment or creating eddy observational data set from satellite altimetry data.
Integration of NDT data for monitoring road pavement distresses in hydrogeologically complex areas
Authors: Bianchini Ciampoli Luca , Di Benedetto Alessandro , Fiani Margherita , Benedetto Andrea
Published: March 2024

Achieving a comprehensive understanding of the health condition of the pavement asset is a crucial step for road network managers to establish an efficient maintenance and rehabilitation program. This is particularly true when the managed infrastructure traverses hydrogeologically complex areas that are reported to be highly vulnerable to both surface and deep hydraulic phenomena. Often, these areas are simultaneously affected by geotechnical events such as landslides and settlements. Monitoring the evolution of the effects related to these occurrences is indeed crucial to understand the actual risks to traffic, predict the remaining service life, and assess the overall resilience of the transport network to major natural events.The integration of non-destructive testing (NDT) data, typically collected through high-productivity surveys, is now widely recognized as a method for gaining a deep understanding of pavement decay phenomena, with significant implications for the reliability of their evolution predictions.This study presents the results of the integration of ground-penetrating radar (GPR) and mobile laser scanner (MLS) developed within the context of monitoring the A3 motorway, near the city of Salerno, Southern Italy. In particular, the focus is on a specific road stretch enclosed between two viaducts and affected by a remarkably complex hydrogeological scenario.The integrated analysis revealed the possibility of identifying severe distress occurring at the subgrade level, successfully linked to underground water movements induced by the relationship between slope morphography and road embankment.AcknowledgementsThis research is supported by the Italian Ministry of Education, University and Research under the National Project “EXTRA TN”, PRIN2017, Prot. 20179BP4SM. In addition, this study was funded by Regione Lazio through the Project “PIASTRE” (PR FESR Lazio 2021-2027). We would like to thank C.U.G.RI. (Inter-University Research Center for the Prediction and Prevention of Major Hazards), Leica Geosystems for the collaboration in field survey operations and the Consorzio Stabile SIS S.c.p.a. for the logistical support and assistance.
Effects of initialization of sea ice properties on medium-range forecasts in the Korean Integrated Model
Authors: Choi Hyun-Joo , Kim Seok Hwan , Kim Baek-Min , Koo Myung-Seo , Cho Eek-Hyun , Kwon Young Cheol
Published: March 2024

The Korean Integrated Model (KIM) has been in operation at Korea Meteorological Administration (KMA) since April 2020 and its forecasting performance has been improved by updating model physical processes and data assimilation system. The model performance is comparable to that of the Unified Model run in parallel with the KIM at KMA during Boreal summer, but is relatively poor during the winter. One of the major biases in 5-day temperature forecasts for Norther Hemisphere winter is the low atmospheric cold bias over the Arctic region, and thus this study modifies the initialization of sea ice properties (sea ice thickness and temperature) to reduce the bias. First, the initial sea ice thickness data prescribed by climatology data produced using reanalysis data from the past 10 years (2000~2009) is replaced using the latest (2019~2021) reanalysis data. Second, the initial temperatures of the 1st and 2nd sea ice layers are set to the sea water freezing temperature instead of the currently applied first guess (background) sea ice temperatures. The effects of initialization modification on the medium-range forecasts of KIM are analyzed by performing two sets of experiments: cold start and warm cycle experiments without and with a data assimilation system in January 2022. The latest sea ice thickness initial data shows that sea ice thickness has decreased by about a factor of two. And its adoption by KIM increases surface and lower atmospheric temperatures in the Arctic sea ice region, alleviating cold biases in the region for both analysis and forecasts. In addition to sea ice thickness, sea ice temperature initialization modifications enhance Arctic warming and lead to greater improvement of cold bias. The warming effect in the lower Arctic is consistent in both cold start and warm cycle experiments. However, secondary effects induced by the Arctic warming occur significantly only in the warm cycle experiment and significantly affect forecasts fields not only in the polar region but also in the Southern Hemisphere and mid-latitude regions. Skill scores for medium-range forecasts in January 2022 are mostly improved (degraded) for the 12 UTC (00 UTC) initial conditions in the warm cycle experiment.
From the river to the sea: Microplastics in water and sediments of the Elbe and Thames rivers and the North Sea
Authors: Stock Friederike , Pabortsava Katsia , Lampitt Richard , Pedrotti Maria Luiza , Rodriguez Rocio , Beck Aaron , Achterberg Eric , Voges Kathrin , Feltham Christopher , Scheidemann Lindsay , Engel Anja , Golde Sandra , Horton Alice
Published: March 2024

Microplastics have been investigated for over 45 years especially in the marine environment, but only in the past years research has started to focus on freshwater environments. In the frame of the H2020 LABPLAS project, different compartments in the Elbe and Thames river basins and the North Sea were studied in order to better understand the sources, transport, distribution and impacts of plastic pollution and to detect the amount of plastics transport via the rivers into the sea.In the frame of the project, a winter and a summer campaign were conducted 2022 and samples taken from 6 sites within each river basin and from 4 sites from the North Sea between the Elbe and Thames estuaries. Samples collected were floating macroplastics, surface microlayer samples (Garrett screen), water samples (10-1000 µm with a pump and stainless-steel filters; >335 µm using a manta net) and sediments (with a Van-Veen-grabber). Density separation and organic digestion took place and analysis was done with a hyperspectral camera, FTIR and LDIR.The preliminary show that microplastics are present in all samples. The number of particles varies significantly between the compartments, sampling sites and the seasons showing the complexity of plastic sampling and analysis. In the sediments (>10 µm), considerably more microplastics were counted than in the water. Higher values were observed close to cities and the Elbe estuary, in the North Sea close to the Thames estuary. In general, more microplastics are present in manta nets (>335 µm) of the tidal part of the rivers than in the freshwater part. The contrary occurs for small microplastics (10-1000 µm). Only few macroplastics were found. Most common polymers were PP, Acrylates/PU/Varnish, PS and PE as well as PTFE and rubber.
Climate signal in Pericopsis elata tree rings d18O series and potential for precipitation reconstructions in the eastern Congo Basin
Authors: De Mil Tom , Colombaroli Daniele , Luambua Nestor , Kafuti Chadrack , Cherubini Paolo , Saurer Matthias , Hubau Wannes , Beeckman Hans
Published: March 2024

it is unclear whether pronounced droughts reaching the most remote regions of the Congo Basin are within a historical norm or have occurred only in the last decades. There is a growing evidence that a number of species with anatomically distinct rings can be used for dendroclimatological studies in the Congo Basin, such as Afrormosia (Pericopsis elata) (PEEL). Annual growth increments, i.e. Tree-Ring Width (TRW), are often co-determined by many environmental factors and yield low potential for reconstructions. Earlier work has shown that δ18O measured in PEEL tree rings holds a precipitation amount effect. Here we focus on new P. elata isotope series to estimate the isotope-precipitation relationship at the annual-scale and discuss its potential for reconstructing precipitation variability back to 1850 AD. δ18O values yielded better sensitivity as well as coherence between trees compared to TRW. Lower δ18O values (28-29‰) after 1960 reflect the anomalously wetter conditions between 1950 and 1970 recorded in the Congo Basin and neighbouring areas. Higher δ18O values after 1970 are in agreement with the reduction in precipitation reflected in gauges and satellite data. Further comparisons with instrumental data and other proxies can refine a precipitation reconstruction currently extending to 1850 AD.
So, will you live an unprecedented life?
Authors: Thiery Wim
Published: March 2024

Under a continued increase in global warming, extreme events such as heatwaves will further rise in frequency, intensity, and duration over the next decades. Climate change impact studies routinely assess hazard and exposure change across discrete time windows, but thereby ignore how vulnerability and climate risk evolve across a person’s lifetime. Conversely, demographic research has a long tradition of assessing population processes and vulnerability from a cohort perspective, but generally neglects climate impacts. In the soon-to-start ERC CoG project LACRIMA (LAgrangian Climate Risk and Impact Attribution), we will develop novel concepts and methodologies to express climate change impacts and risk from a cohort perspective. More specifically, the project pursues to (i) to reconstruct two iconic climate change impacts on people around the world using machine learning (heat-related mortality and burned area), (ii) to uncover age-specific vulnerability to climate extremes including heatwaves, wildfires, river floods, droughts, tropical cyclones, and crop failures, (iii) to detect and attribute changes in lifetime extreme event exposure and climate impacts on mortality across generations and regions, (iv) to quantify how these attributable cohort impacts change country-level life expectancy around the world under a range of warming scenarios, and finally (v) to project how lifetime exposure to extreme events including compound events may trigger irreversible impacts under scenarios of temporary overshooting of long-term warming targets.By bridging physical climate science, demography, and planetary health, LACRIMA will comprehensively identify whether and where people will live an unprecedented life in terms of climate impacts, and how mitigation choices can alter the climate change burden on current young generations around the world
Seismological investigation on the recent unrest of Tenerife (Canary Islands)
Authors: García Hernández Rubén , Fan Kevin , Morales Fernández Claudia , Ní Nualláin Kendra , Barrancos José , Padilla Germán D. , Martínez Van Dorth David , Ortega Ramos Víctor , D'Auria Luca , Pérez Nemesio M.
Published: March 2024

Tenerife is an active volcanic island belonging to the Canary Islands Archipelago. After its last eruption in 1909, the only visible volcanic manifestations consisted of weak fumaroles from the summit crater of Teide volcano, the most prominent geographic feature of the island. Tenerife has been monitored since 2016 by a seismic network consisting currently of 21 broadband stations.Since October 2016, the seismic activity has shown an increase, corresponding to a relevant growth of the diffuse degassing from the summit of Teide. This has been interpreted as the effect of pressurization of the hydrothermal system triggered by repeated injections of fluids of magmatic origin.Here, we present different analyses realized on the seismic catalogue of the island. First, we show the spatio-temporal variation in the hypocenter distribution, highlighting the temporal evolution of seismicity clusters. Then, we discuss the spatial and temporal variations of the Gutenberg-Richter b-value, which shows a remarkable increase and, in general, higher values around the central part of the island. We also highlight the presence of a significant long-period seismic activity, consisting of both isolated events and dense swarms.Finally, we discuss the relationship between the seismicity and the internal structure of the island, inferred by recent seismic tomography studies, as well as the temporal correlation with other geophysical and geochemical parameters measured on the island.
Extreme sea ice motion -- analysis of ice drifter buoy data in the Gulf of Bothnia 
Authors: Vuollekoski Henri , Lensu Mikko , Haapala Jari
Published: March 2024

Sea ice and particularly its motion are problematic for vessels and structures in water areas that experience sea ice. For example, several offshore wind farms are planned to be installed in the Gulf of Bothnia, but uncertainty related to extreme sea ice motion is likely to worry potential investors. Winter navigation, particularly in the coastal boundary zone, can be difficult. While climate change is likely to decrease the average ice concentration, extrema may become more severe. 

The motion of sea ice is affected by wind, currents and internal dynamics of the ice field, which are highly complex and inadequately understood. In this study we analyze time-series of data from ice drifter buoys deployed in the Gulf of Bothnia, Baltic Sea, during 2012 - 2023. The combination of data from multiple buoys, ice charts as well as other observations and model forecasts on the atmosphere-sea-ice interaction allows for estimating various parameters for the respective ice fields, such as shear, divergence and deformation, as well as temporal and spatial variability.
The microstructure of naturally deformed gneissic Zechstein 2 rock salt (Kristallbrockensalz) from the northern Netherlands – a review
Authors: Barabasch Jessica , Schmatz Joyce , Klaver Jop , Schwedt Alexander , Urai Janos L.
Published: March 2024

Janos Urai's contributions have significantly enhanced our understanding of salt deformation, particularly in predicting the long-term evolution of solution-mined caverns and radioactive-waste repositories in salt formations. His work delved into phenomena such as the weakening of rock salt by water during long-term creep at low differential stresses. Unlike most laboratory measurements, which are at higher differential stress, Urai's research considers dislocation creep and pressure solution (dissolution-precipitation creep), processes not commonly included in current engineering predictions.Microstructural observations on Zechstein 2 (Z2) rock salt cores in the northern Netherlands reveal substantial grain-size-dependent differences in rock salt rheology. The study compares undeformed salt layers with strongly deformed diapiric ones, showcasing variations in megacrystals and fine-grained halite microstructures that point to different microphysical processes. The microstructural analysis, including optical microscopy of gamma-irradiated thin sections, recrystallized grain-size measurements, electron microscopy, and subgrain-size piezometry, indicates differential stresses between 0.5 and 2 MPa during deformation.The findings highlight the importance of pressure solution creep at low differential stresses, demonstrating its significant impact on strain rate in rock salt. Integrating these results into constitutive flow laws reveals a four-order-of-magnitude difference in strain rates between halite types, emphasizing the role of different dominant deformation mechanisms. The study suggests that incorporating pressure solution creep and microstructural analysis can substantially enhance engineering and tectonic models of rock salt deformation in low-stress conditions.
Techno-Economic Optimization of a CO2-based Advanced Geothermal System (AGS)
Authors: Pokras Daniel , Hefny Mahmoud , Huang Po-wei , Saar Martin O.
Published: March 2024

Advanced Geothermal Systems (AGS) are power systems that harness energy by circulating a working fluid through a closed-loop circuit, extracting thermal energy from deep geologic reservoirs via conductive heat transfer across an impermeable wellbore wall. AGS benefit from using carbon dioxide (CO2) as the working fluid within the wellbores, at least for electricity generation and possibly also for direct heat usage. Here, we investigate a range of configurations for combined electricity and heat production. These designs aim to enhance flexibility and efficiency in AGS while reducing system costs. Central to this research is formulating an optimal AGS pilot plant design, complemented by a comprehensive techno-economic feasibility study. Compared to the design benchmarks of previous work on AGS for electricity generation only, this optimization yields an improvement in the Specific Capital Cost (SpCC) by approximately 215%. Furthermore, by incorporating heat co-generation with electricity, the SpCC is considerably further reduced. 
Delineating Standing Deadwood in High-Resolution RGB Drone Imagery
Authors: Möhring Jakobus ,   co-authors
Published: March 2024

We have observed tree die-offs in a variety of regions in the world. Understanding the diverse causes of tree mortality requires exact information about which trees are dying and where. With the increased user-friendliness of drones and the availability of airborne imagery, high-resolution imagery of forests is becoming widely available. Delineating standing deadwood in such aerial imagery has become a classic segmentation task and several models with varying accuracy have been developed. However, these machine-learning based models are not generic and limited to specific image resolutions, sensor characteristics, geographic regions, and forest ecosystems. The reason for this lack of generality is that previous models have been trained using only datasets representative of specific regions and obtained from a single source. In this study, we obtain a diverse dataset spanning more than a dozen countries across continents and implement a single convolutional neural network (CNN) model that is able to cope with most forest ecosystems, varying image quality, and spatial resolutions. 
Statistical analyzes of the shapes of marine sand dunes off the Opal Coast (Eastern English Channel)
Authors: Gaullier Virginie , Schmitt François , Laurencin Muriel
Published: March 2024

Numerous very high-resolution seismic lines (Sparker/single-channel seismic reflection) were acquired in the Eastern Channel, along the the Opal Coast, between the Bay of Somme and Cape Gris-Nez, during the oceanographic missions GEOBAS (2016-2020), TREMOR 1 (2014), TREMOR 2 (2017) and MARCOPALE (2023). In this sector, numerous sandy banks are observed, especially the Bassure of Baas. These geophysical data were analyzed as part of the TURBODUNES project, by comparing two reflectors, respectively the sea floor and the base of the dunes (corresponding to the top of the deformed Cretaceous and Eocene bedrocks). The difference between the two signals makes it possible to identify areas with dunes and areas where dunes are absent. Assuming a constant boat speed, the extraction of signals provides spatial information on the height of the dunes. We carry out analyzes of these signals using different methods, including Fourier spectral analysis, empirical mode decomposition and structure functions. Empirical mode decomposition is a method which allows a one-dimensional series to be decomposed into a sum of several series, called “modes”, each having a characteristic wavelength. This makes it possible to quantitatively characterize the shape of the dunes via different modes, each having a wavelength ranging between 25 and 400 m. The lines for which dunes are absent nevertheless have profiles with strong multi-scale variability, with scale-invariant Fourier spectra with a slope of -2, for scales between 2.5 m and approximately 1 km.
uniWeather™: Advancing real-time outreach in urban environmental sciences through app and platform
Authors: Feigel Gregor , Zeeman Matthias , Plein Marvin , Schindler Dirk , Matzarakis Andreas , Christen Andreas , Metzger Swen
Published: March 2024

Research concerning the general public and influencing decision-making necessitates timely dissemination of easily accessible results and data, with a focus on directly verifiable hands-on exploration rather than authoritative assessments in order to raise awareness and engage the public. This applies, for instance, to the high spatial and temporal resolution street-level weather and thermal comfort monitoring network operated in the City of Freiburg. Germany, by the University of Freiburg, to raise awareness for the significant spatial and temporal differences in, e.g., outdoor heat stress patterns in urban areas, which are crucial for informed urban planning and climate resilience. Addressing this gap, the uniWeather™ app and platform were developed to provide end-users, stakeholder and the general public with free, easily accessible near-real-time data and interpretation. With regard to the FAIR principles, the platform is being developed to support data form other research organisations such as universities, government agencies or companies that operate environmental sensor networks to be provided free of charge. uniWeather™ aims to encourage the sharing and access to data in near real-time by providing an easy-to-integrate service for tailored visualisation and interpretation.In June 2023, the uniWeather™ app and monitoring network were announced in a press release from the University of Freiburg and in a newspaper article providing access to maps and real-time data from 42 street-level weather stations in the Freiburg region within 60 seconds of measurement. The app was readily welcomed by the public, researchers and the city of Freiburg. The project was also well received at public outreach events such as the Eucor-MobiLab Roadshow 2023 in Freiburg (26-30 June 2023) and the exhibition DATEN:RAUM:FREIBURG (4-31 August 2023) of the city of Freiburg. With more than 1.5k users in the first few weeks and continued interest in further functionalities, the platform will be continued and further developed to address the needs of the general public and different scientific communities.
Agricultural Drought Case Study in South Korea: Selection of Rural Specialization Districts based on Principal Component Analysis
Authors: Kim Hyochan , Cha Hoyoung , Baik Jongjin , Park Kihong , Jun Changhyun
Published: March 2024

Recently, the frequency and severity of droughts have gradually increased due to extreme weather events and global warming. As the demand for drought management increases, field surveys and water supply are actively conducted in many countries. Given that such drought assessment and support require the consumption of labor and financial resources, the prioritization of essential agricultural areas has become a major topic for efficient decision-making in drought relief. In this study, we proposed a Principal Component Analysis (PCA) for selecting rural specialization districts across the 162 administrative regions of South Korea. Additionally, we aimed to investigate real cases of agricultural drought occurred in these regions by utilizing the survey of water supply measures derived from Ministry of Agriculture, Food and Rural Affairs. The research data comprised seven agricultural specialization factors, exemplified by agricultural workforce and infrastructure. First, we implemented singular decomposition method included in PCA process to represent the comprehensive trends of the agricultural specialization factors with maximum reflection. High value of principal component scores (PCS) estimated from PCA was interpreted as regions with high agricultural relevance. Lastly, the PCS were classified into different levels, defining top-ranking regions as rural specialization districts. Based on agricultural drought case studies from 2018 to 2021, it is expected that finding relative damage-prone areas and establishing appropriate drought responses will be feasible.
Keywords: Principal Component Analysis, Rural Specialization Districts, Agricultural Specialization Factors, Principal Components Score
Acknowledgement
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00250239) and this research was supported by Korea Environment Industry & Technology Institute (KEITI) through Water Management Innovation Program for Drought (RS-2022-KE002032) funded by Korea Ministry of Environment.
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No.NRF-2022R1A4A3032838).
Role of size and height of ice sheet on millennial-scale climate variability
Authors: Kuniyoshi Yuta , Abe-Ouchi Ayako , Sherriff-Tadano Sam , Chan Wing-Le
Published: March 2024

Unlike the interglacial stable climate, glacial climate was dominated by millennial-scale variability, which is strongly associated with changes in the Atlantic meridional overturning circulation (AMOC). The development of the North American ice sheet has been shown to have a significant impact on the strength of the AMOC through surface cooling and enhanced surface winds. However, the impact of mid-glacial ice sheet involved in millennial-scale variability of the AMOC are still elusive. Here, using a coupled atmosphere-ocean model MIROC4m, we perform several climate simulations under mid-glacial ice sheet configurations. We use Marine Isotope Stage (MIS)-5a and MIS-3 ice sheet configurations as boundary conditions, which are derived from the simulation of an ice sheet model, IcIES-MIROC. These volumes are the 40 m sea level equivalent for MIS5a (approximately 33% of the LGM) and the 96 m sea level equivalent for MIS3 (approximately 80% of the LGM). To account for uncertainty in the altitude of the ice sheet, we also conduct experiments under topographic conditions in which only the altitude was changed, but not the extent, for each ice sheet configuration. As a result, self-sustained oscillations of millennial-scale periodicity in the climate and AMOC are simulated for both ice sheet cases. The result suggests that the millennial-scale climate variability could occur as long as the North American ice sheet exists, even if the ice sheet is small. The expansion of the North American ice sheet from MIS5a to MIS3 have an influence of shortening the weak AMOC period (stadial) and lengthening of the strong AMOC period (interstadial), because the stronger surface winds over North Atlantic enhance retreat of sea-ice during the stadial and increase salt transport via wind-driven ocean circulation during the interstadial. Meanwhile, one of the other simulations under the ice sheet condition with MIS3-equivalent extent but altitudes as low as 50% results in a persistent stadial state, which is due to the large cooling effect. Our results show that the relative strength of surface wind and surface cooling effects depends on the ice sheet configuration, which could modify the length of stadial and interstadial.
Insights from steep-bedrock, high-altitude mountain permafrost laboratory at the Matterhorn
Authors: Beutel Jan , Cicoira Alessandro , Morra di Cella Umberto , Pogliotti Paolo , Weber Samuel
Published: March 2024

High-altitude mountain areas are very susceptible to the climate evolution at all scales. However little is known about this extreme end member characterized by steep topographies and remoteness. Therefore in-situ observations are scarce and often limited in their temporal and spatial coverage as well as their fidelity. Over the past two decades teams from Italy as well as Switzerland have concentrated multiple interdisciplinary research efforts at and on the slopes of the Matterhorn. This cross-border laboratory today covers a full altitude transect from the valley floor to the summit at 4478 m asl as well as from south to north with a dense network of permanent in-situ observation locations. In addition, several research campaigns have been historically undertaken and add to this unique footprint of observation data as well as insight. Primary data observed are ground-surface temperature as well as permafrost active layer depth, meteorological parameters, surface kinematics using crackmeters as well as GNSS, resistivity, optical imaging, seismic signals as well as personal observations through a regional observer network. In this presentation, we will summarize the activities over the past two decades and discuss insights, key findings as well as data availability.
Potential of Employing a Machine Learning Model for Glacier Motion Monitoring
Authors: Łucka Magdalena , Hejmanowski Ryszard , Witkowski Wojciech
Published: March 2024

Monitoring marine-terminating glaciers and their dynamics in the light of advancing climate change is a critical concern for many scientists. Observing marine-terminating glaciers in Greenland is especially significant because glacier calving and melting influence sea level. One component of glacier monitoring is velocity estimation, which can also be used as an indicator of climatic change and may reveal the existence of other underlying processes that cause speed changes on the surface. Using SAR images, this type of monitoring can be done permanently and at a minimal cost. However, present approaches that focus on offset-tracking algorithms have some disadvantages. Despite the rapid development of artificial intelligence, there is still some immense potential in the synergy of SAR datasets and machine learning models to determine rapid displacement, such as in the case of glaciers. This study demonstrates the feasibility of determining glacier displacement using Sentinel-1 satellite SAR information and convolutional neural networks (CNN).The method proposed in this study uses pairs of SAR data to find the matching patterns on both images. The CNN with the AlexNET architecture is utilized to discover the corresponding areas, and data augmentation techniques such as rotation, filtering, or resizing of the SAR image are employed to extend the training dataset. Finding the appropriate areas on both images allows for the calculation of the displacement in radar coordinates, as well as the mean velocity and direction of the movements over the investigated period. This study examines the proposed method's results for two Greenland glaciers with varying speeds: Jakobshavn and Petterman. Furthermore, two different input datasets are evaluated and compared. The first strategy simply employs the amplitude obtained in HH polarization, while the second uses amplitude information from HH and HV polarizations, as well as the backscatter coefficient. Displacement values obtained for both glaciers and using various input datasets are compared to the velocities collected using the offset-tracking approach, which is extensively used for glacier monitoring.The potential of using machine learning models to determine glacier displacement values utilizing SAR datasets is presented in this study. The results' reliability is further validated by comparison with well-known processing procedures. In addition, different input datasets are examined for two glaciers with different dynamics to determine the utility of the proposed approach for monitoring glacier motion. The proposed method's adoption could benefit glaciological society by providing an alternate method for detecting ice motion.