bluuebunny/crossref_metadata_2025 huggingface dataset:
How do interest rates affect decarbonisation pathways? A stakeholder-driven multi-model analysis.
Authors: Frilingou Natasha , van de Ven Dirk-Jan , Mittal Shivika , Anastasios Karamaneas , Nikolakakis Thomas , Gardumi Francesco , Koasidis Konstantinos , Nikas Alexandros
Published: March 2024

Decarbonisation of the energy sector is a critical task in the efforts to mitigate climate change. As sectoral emissions cuts in modelled pathways aligned with the Paris Agreement are projected to come from at-scale diffusion of emerging or new technologies as well as further development of existing solutions, energy-sector decarbonisation entails major investments in low-carbon technologies. At the same time, a significant chunk of these investments must be made in emerging and developing economies, which currently receive just one-fifth of global energy investments. This underinvestment is, at least partly, due to the large disparities in financing conditions and higher-risk profiles in said countries. Models used to assess decarbonisation pathways typically assume a uniform cost of capital; such assumption, however, does not do justice to real-world conditions and may therefore lead to inaccurate policy recommendations. Moreover, there is considerable uncertainty over how these costs may evolve in the future. In this study, we apply an empirical dataset of estimated cost of capital differentiated by technology and country and explore stakeholder-driven pathways of (de-)risking investments in clean energy vs. fossil-fuel technologies, using an ensemble of two global integrated assessment models and one electricity-system model. Furthermore, we attempt to incorporate a corrective justice dimension in our narratives by assessing the impacts of risk underwriting for low-carbon investments through taxing corporate windfall profits for 2022 and distributing the revenue as subsidies towards high-risk regions.
Unraveling the link between precipitation and land use changes to water quality in Lake Victoria using remote sensing
Authors: Nakkazi Maria Theresa , Nkwasa Albert , Martinez Analy Baltodano , Griensven Ann van
Published: March 2024

Due to the continued increase in land use changes and changing climatic patterns in the Lake Victoria basin, understanding the impacts of these changes on the water quality of Lake Victoria is imperative for safeguarding the integrity of the freshwater ecosystem. Thus, we analyzed spatial and temporal patterns of land cover, precipitation, and water quality changes in the Lake Victoria basin from 2000 to 2022 using processed remote sensing (RS) data. Focusing on chlorophyll-a (Chl-a) and turbidity (TUR) in Lake Victoria, we used statistical metrics (correlation coefficient, trend analysis, change budget, and intensity analysis) to understand the relationship between land use and precipitation changes in the basin with changes in Chl-a and TUR at two major pollution hotspots on the lake i.e. Winam Gulf and Inner Murchison Bay (IMB).Results show that the Chl-a and TUR concentrations in the Winam gulf increase with increases in precipitation. Through increases in precipitation, the erosion risks are increased and transport of nutrients from land to the lake system, promoting algal growth and turbidity. In the IMB, Chl-a and TUR concentrations decrease with increase in precipitation, possibly due to dilution, but peak during moderate rainfall. Interestingly, LULC changes showed no substantial correlation with water quality changes at selected hotspot areas even though LULC change analysis showed a notable 300% increase in built-up areas across the Lake Victoria basin. These findings underscore the dominant influence of precipitation changes over LULC changes on the water quality of Lake Victoria for the selected hotspot areas.
Adaptive Data Reduction Techniques for Extreme-Scale Atmospheric Models
Authors: Böing Niklas , Holke Johannes , Hergl Chiara , Basermann Achim , Gassner Gregor
Published: March 2024

Large-scale earth system simulations produce huge amounts of data. Due to limited I/O bandwidth and available storage space this data often needs to be reduced before writing to disk or storing permanently. Error-bounded lossy compression is an effective approach to tackle the trade-off between accuracy and storage space.We are exploring and discussing error-bounded lossy compression based on tree-based adaptive mesh refinement (AMR) techniques. According to flexible error-criteria the simulation data is coarsened until a given error bound is reached. This reduces the number of mesh elements and data points significantly.The error criterion may for example be an absolute or relative point-wise error. Since the compression method is closely linked to the mesh we can additionally incorporate geometry information - for example varying the error by geospatial region.We implement these techniques as the open source tool cmc, which is based on the parallel AMR library t8code. The compression tool can be linked to and used by arbitrary simulation applications or executed as a post-processing step. As a first example, we couple our compressor with the MESSy and MPTRAC libraries.We show different results including the compression of ERA5 data. The compressed sample datasets show better results in terms of file size than conventional compressors such as SZ and ZFP. In addition, our method allows for a more fine-grained error control.
Early warning Demonstration of pan-European rainfall-induced impact forecasts – the EDERA project
Authors: Berenguer Marc , Park Shinju , Baugh Calum , O'Regan Karen , Prudhomme Christel , Pulkkinen Seppo , Myllykoski Heikki , Santiago Antonio , Durán Ana M. , Torres Rosa M. , Vara María , Gomes Abel , Pereira Colonese Juan , Tasev Dimitar
Published: March 2024

Heavy rain and convective storms trigger a number of hazards (floods, landslides, debris flows…) that have impacts on people’s life and goods. In these situations, Civil Protection Agencies (CPAs) face multiple challenges in their decision-making processes such as the absence of multi-hazard forecasts or difficulty in translating hazards forecasts in impact-based decisions, or the coordination between CPAs during extreme and/or large-scale events affecting multiple regions and neighbouring countries.The EDERA project, funded by the EU Civil Protection Mechanism, focuses on the integration of real-time pan-European forecasts of storm and heavy rainfall impacts in the Early Warning Systems of CPAs. The main objective of the project is assessing the added value of these products during an 18-months demonstration in collaboration with end users.The study focuses on the evaluation of the quality of the hazard and impact forecasts during recent events at two different scales: (i) at the European scale (analysing the skill of the products to identify/anticipate the occurrence of the most significant events), and (ii) in two pilot sites (one focused in Finland and the other one covering Spain and Portugal), analysing their usefulness to support emergency management with the participation of relevant authorities.
Evaluation of EnMAP imagery for predictive modelling of soil salinity in highly saline soils
Authors: Canero Francisco M. , Lopez-Nieta Diego , Rodriguez-Galiano Victor
Published: March 2024

Soil salinization is a paramount issue affecting crop yields and soil productivity, specially threatening the soil in arid and semi-arid regions. In Bajo Guadalquivir (southern Spain), one of the main rice production areas of Spain, soil salinity has been reported by local stakeholders as the main ecological stressor affecting rice crops. EnMAP hyperspectral mission might rise promising opportunities to improve the monitoring of soil salinity and other environmental stressors. This mission provides continuous vis-NIR spectral data with a moderate temporal resolution. The aim of this study is to evaluate EnMAP imagery in two different predictive modelling workflows based on Random Forest and Support Vector Machines.100 samples of electrical conductivity (EC) measures were collected in May-June 2023 in the study area. A EnMAP image was acquired over the study area on 22 March 2023. Vegetated and water surfaces were masked out, resulting in 80 samples of bare soils for the date of Enmap acquisition. Raw bands and soil salinity indices (SSI) were used as predictive features. SSI were based on an iterative procedure calculating normalized indices between all pair of bands, selecting the 1% of indices with higher correlation with EC. Two ML algorithms, Random Forest and Support Vector machine, were used together with a Sequential Feature Selection method built with each modelling algorithm.The sampling results showed high soil salinity contents, with a median value of 10.96 dSm-1. EnMAP image reached the higher accuracy using RF with R2 = 0.14, RMSE = 3.14, RPIQ = 1.53. SVR performed worse, with a model achieving R2 of -0.37, RMSE of 3.38 and RPIQ = 1.42. Both models selected the same two features, two SSI built with the 756/871 nm and the 972/1234 nm pairs. Given that the features were similar, differences might be derived from modelling algorithms. The results suggested that hyperspectral images are promising data sources, but their processing to get meaningful features is perhaps the most important task to obtain accurate soil salinity products. 
Bayesian Joint Inversion of Bouguer Gravity and Surface Wave data: application to the Western Alps
Authors: Scarponi Matteo , Bodin Thomas
Published: March 2024

The Western Alps constitute a complex and heterogeneous orogenic system, generated by the continental collision between the European and Adriatic tectonic plates. Three main tectonic domains can be identified across local to regional scales, based on geophysical and geological observations: the European and Adriatic domains, and the high-density, high-velocity anomaly known as Ivrea geophysical body (IGB). Despite being one of the best-studied collisional systems in the world, the 3D Western Alpine lithosphere and its along-arc compositional and structural variations are still subjects of investigations. In this framework, we exploit the inherently-3D information provided by gravity data. In particular, we set up a 3D Bayesian joint inversion of Bouguer gravity anomaly and surface wave dispersion data, to obtain a new 3D ρ-vS model of the Western Alpine lithosphere. We benefit from the Bouguer anomaly map by Zahorec et al. (2021), obtained by homogeneous processing of gravity data across the Alpine domain, and from seismic data recorded by permanent and temporary seismic networks: e.g. IvreaArray, AlpArray (Hetényi et al. 2017, 2018), CIFALPS I and II (e.g. Paul et al. 2022). We perform 3D forward gravity modeling by discretizing the study area in unitary volumes of constant density (voxels), accounting for spherical Earth structure and surface topography. The gravity effect of each voxel is pre-computed, and then only needs to be scaled with density during the inversion. This significantly decreases the computational cost of the forward model, and thus allows us to explore the parameter space with Monte Carlo sampling. We use a Bayesian framework and implement a Markov chain Monte Carlo (McMC) algorithm. We test different types of  parameterizations to reduce the non-uniqueness of gravity inversion. We plan to jointly invert gravity with surface wave dispersion data, providing complementary information on vS. Finally, existing receiver function studies (e.g. Monna et al. 2022, Paul et al. 2022, Michailos et al. 2023) provide prior information on crustal and lithospheric geometry.We expect to obtain a new 3D ρ-vS model for the Western Alpine crust and lithosphere. This will provide new information on the European-Adriatic collision boundary, together with the IGB structure, and their three-dimensional variation along the orogen. The new model will be also useful to constrain rock composition, upon comparison with the geological observations at the surface.
Electron heat flux instability in the near-Sun solar wind
Authors: Zhao Jinsong
Published: March 2024

How the solar wind heat flux is constrained and how strahl electrons are scattered are two fundamental problems in the study of the electron dynamics in the solar wind. Recently, much attention has been paid to the role of the electron heat flux instability on these two problems. We have performed the instability analyses for the electron heat flux instability in the near-Sun solar wind where the plasma beta is much lower than one. We found that lower-hybrid waves and oblique Alfvén waves can be primarily triggered by the electron heat flux in the low-beta plasma environment, and we also explored the wave-particle interactions in each type instability through the energy transfer rate method. Moreover, using PSP observations, we will show the possible observation signature for the lower-hybrid waves in the near-Sun solar wind.
Assessment of the Accuracy of Numerical Morphological Models based on Reduced Saint-Venant Equations
Authors: Barneveld Hermjan , Mosselman Erik , Chavarrias Victor , Hoitink Ton
Published: March 2024

Sustainable river management often requires long-term morphological simulations. As the future is unknown, uncertainty needs to be accounted for, which may require probabilistic simulations covering a large parameter domain. Even for one-dimensional models, simulation times can be long. One of the acceleration strategies is simplification of models by neglecting terms in the governing hydrodynamic equations. Examples are the quasi-steady model and the diffusive wave model, both widely used by scientists and practitioners. We established under which conditions these simplified models are accurate.Based on results of linear stability analyses of the St. Venant-Exner equations, we assessed migration celerities and damping of infinitesimal, but long riverbed perturbations. We did this for the full dynamic model, i.e. no terms neglected, as well as for the simplified models. The accuracy of the simplified models was obtained from comparison between the characteristics of the riverbed perturbations for simplified models and the full dynamic model.We executed a spatial-mode and a temporal-mode linear analysis and compared the results with numerical modelling results for the full dynamic and simplified models, for very small and large bed waves. The numerical results match best with the temporal-mode linear analysis. We show that the quasi-steady model is highly accurate for Froude numbers up to 0.7, probably even for long river reaches with large flood wave damping. Although the diffusive wave model accurately predicts flood wave migration and damping, key morphological metrics deviate more than 5% (10%) from the full dynamic model when Froude numbers exceed 0.2 (0.3).
Comparing PV and Wind Models to Analyse Dunkelflaute Events in Ireland
Authors: Morin Boris , Flynn Damian , Sweeney Conor , Maimo Far Aina
Published: March 2024

The 2024 Government of Ireland Climate Action Plan aims to increase the share of renewable energy sources (RES) from 38% to 80% by 2030. In 2022, the installed capacity of wind power will surpass 4.5 GW, and the goal is to reach the same level as solar power by 2025. As the proportion of energy generated from these weather-dependent sources increases, there is a need to more accurately quantify periods when the energy generated from such sources is low for an extended period, in order to plan for appropriate reserve capacity.
The terms "Dunkelflaute" and “Renewable Drought” have been used to refer to extended periods of time when the capacity factor of both wind and solar power falls below a given threshold for a set period of time. In this study, we define a Dunkelflaute event as occurring when the combined capacity factor for wind and solar falls below a fixed threshold for at least 24 hours. The effect of choosing different values for this fixed threshold is also investigated in our study.
This study aims to investigate how the expected frequency and duration of Dunkelflaute events identified in different RES datasets may change depending on the assumptions made by the underlying RES datasets.
The first RES dataset investigated is an hourly estimate of electricity generation based on ERA5 climate variables, made by C3S Energy, which was produced using statistical and physical models. The C3S Energy dataset provides a time series of electricity supply from wind and solar photovoltaic and is trained using European Network of Transmission System Operators for Electricity (ENTSO-E) data.
This dataset has certain limitations. First, it assumes a homogeneous spatial distribution of the installed capacity of wind and solar energy production, to maintain a methodological coherence between the two RES sources. Second, the energy conversion models applied, contain simplifying approximations, such as using a single wind turbine model with a fixed hub height for all locations.
The second RES dataset has been created by the authors, which uses more detailed information about the location of the wind and PV farms. Relevant atmospheric variables are interpolated from ERA5 data to the location of each RES farm. In addition, the characteristics of the wind and PV panels at each farm are taken into account.
Both datasets are compared against the actual wind and PV capacity factor data supplied by the national grid operator of Ireland, EirGrid, for the year 2023, to indicate the performance of each model. The two datasets are then analysed across the full range of the time series, from 1979 to 2023, to determine the frequency and duration of all Dunkelflaute events during this period.
Differences in the identified Dunkelflaute events highlight the importance of considering results in the context of the driving data, which would be important for future policy decisions such as planning reserve capacity requirements, or locating future RES farms.
Measuring the Transport of Floating Plastic Debris Using Vessel-Based Optical Data and Artificial Intelligence
Authors: Romero Mattia , Pham Yannick , Gómez Navarro Laura , de Vries Robin , Sainte-Rose Bruno
Published: March 2024

The North Pacific Garbage Patch (NPGP) is known for accumulating floating plastic debris, but little is known on the dominating mechanisms that form its spatial heterogeneity in concentration. Submesoscale processes are likely to be the main drivers of such heterogeneity, especially if their effect on transport is object-specific. Dynamics at these spatial scales remain largely unresolved to date in ocean circulation models, therefore, current studies have to rely on in-situ measurements. The authors present a new method that measures floating plastic debris’ horizontal transport over small scales along vessels’ trajectories. The method applies particle tracking velocimetry on objects detected by an optical artificial intelligence algorithm during The Ocean Cleanup’s campaigns. Given the method’s sensitivity to the vessel’s movement, a Monte Carlo simulation is conducted to estimate object position errors with and without the presence of waves. The same method is applied to overlapping samples of drone-based optical data and the results are compared across measuring devices. Measurement accuracy depends on factors such as sea state, object distance from the vessel, and tracking duration. A first application on a subset of manually classified objects is presented. The ability to estimate floating plastic debris’ transport from in-situ measurements, combined with the collection of meteorological and oceanographic data, will likely gather insightful information on object-specific small scale dynamics in the region of interest. This is not only valuable for research purposes, but essential to assess and improve clean-up efforts.
From Glaciers to Courtrooms: Translating Natural Science Concepts into Legal Frameworks for Climate Litigation
Authors: Muñoz Randy , Huggel Christian , Haeberli Wilfried , Mergili Martin , Emmer Adam , Arenson Lukas , Sturzenegger Matthieu
Published: March 2024

The integration of natural science concepts into climate change litigation, particularly in cases related to glacier lake outburst floods (GLOFs) in mountainous regions like the Andes, faces significant challenges due to the differing nature of scientific and legal frameworks.Scientific understanding of climate change impacts on phenomena such as GLOFs relies heavily on scenarios, modeling, and projections that evolve over time with advancements in technology and knowledge. These models need to be comprehensive, and consider an array of factors including glacier retreat, temperature changes and various risk factors. However, legal standards often require definitive proof of causation. There may arise a discrepancy creating  a gap in case of prevailing uncertainties inherent to high-mountain processes which may not always meet the exacting evidentiary requirements of litigation.An illustrative example of this challenge is the case of a citizen in Huaraz, in the Andes of Peru, using a major German energy producer over the risks of a catastrophic flood from a GLOF at Lake Palcacocha. The German court’s decision to admit this case is groundbreaking in climate litigation. It implies a recognition of legal responsibilities of large emitters for potential losses and damages caused by anthropogenic climate change globally, provided a causal relation between emissions and risk can be established. This case exemplifies the challenge in linking complex scientific causation with legal accountability.In the Palcacocha case, the German court defined to distinguish between i) the hazard and risk posed to the plaintiff in Huaraz, and ii) the attribution to anthropogenic climate change and the emissions produced by the defendant. Here we report on the geoscientific studies undertaken to analyze the hazard situation posed by potential rock and ice avalanches, impacting the glacial lake and producing potentially devastating floods in the city of Huaraz. Critical among other are concepts and methods to quantify probability of occurrence of an event, and the effect of cascading slope and mass flow processes.In conclusion, the challenges in adapting natural science concepts for climate change litigation, particularly regarding GLOFs, stem from different concepts, standards of proof, and conceptual understandings in science and law. Bridging this gap is essential for effective climate litigation and requires innovative interdisciplinary approaches that facilitate the translation of scientific findings into legally cogent arguments. The framework, methods and standards we applied in the case of Palcacocha could serve for other litigation cases in similar environments, highly impacted and vulnerable to anthropogenic climate change. 
Impact of urease inhibitor and biofertilizer application on N2O emissions derived from fertilizer using 15N-labelled urea
Authors: Heiling Maria , Mirkhani Rayehe , Resch Christian , Hood-Nowotny Rebecca , Gerd Dercon Gerd
Published: March 2024

The introduction of nitrogen (N) fertilizers into agricultural soils represents the predominant anthropogenic contributor to the emission of the greenhouse gas N2O. The impact of N management choices on nitrous oxide (N2O) fluxes is contingent upon interactions with both soil biotic and abiotic factors. This study, conducted by the Joint FAO/IAEA Centre in the spring of 2022 at the experimental station of the University of Natural Resources and Life Sciences (BOKU) near Vienna, Austria, aims to explore the influence of a urease inhibitor (UI) and biofertilizer (BI) on N2O emissions arising from fertilizer use in wheat cropping systems. Employing a randomized complete block design with five treatments and four replicates, including a control treatment (T1), urea-only application (T2), urea with UI (T3), urea with BI (T4), and urea with both UI and BI (T5). For this study, the application rate was 50 kg N ha-1 at the tillering stage (GS 31), except for T1. N-(n-butyl) thiophosphoric triamide (nBTPT) was used as the UI, and Azotobacter chroococcum as the BI. N2O gas fluxes were measured using the static chamber method eight times between 3 to 84 days post-fertilizer application, and gas samples were analysed via off-axis integrated cavity output spectroscopy (ICOS, Los Gatos). The highest cumulative N2O and 15N2O emissions occurred in the T3 treatment, where urea was combined with UI. The emission factors for N2O in T2, T3, T4, and T5 were 0.63%, 0.85%, 0.52%, and 0.68%, respectively. Results from 15N2O emissions and the fraction of N2O from 15N-urea confirmed that UI increased N2O release from the added fertilizer source. The fraction of N2O from 15N-urea reached 26% in the Urea+UI (T3) treatment, decreasing to 12% in the Urea+BI (T4) treatment.  
Estimation of local biogeophysical effects of the continuous logging using a dynamic vegetation model forced by C-based wood harvest
Authors: Shu Shijie , Holm Jennifer , Di Vittorio Alan , Koven Charles , Knox Ryan , Lemieux Gregory
Published: March 2024

Global continual logging activities have modified the regional landscape and disrupted the energy balance through changing the surface albedo, evapotranspiration and roughness length in both current location (local) and nearby areas through feedback to the atmospheric circulation (non-local). Compared to land use change, less attention has been given to understanding the local biogeophysical effect of the different land use management practices, e.g., wood harvest (logging). Uncertainties from the reconstructed global wood harvest rate forcing data, simplified land heterogeneity and processes representation in the classic big-leaf models largely changed the outcomes. We apply a next generation dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator, FATES), coupled with the land component (ELM) of DOE’s earth system model E3SM to study the local biogeophysical effect and the redistribution of energy after accounting the continuous logging activity on a global scale. In order to account for the uncertainties from forcing data and modeling approaches, we designed 9 parallel experiments with 4 different sets of global wood harvest rates derived from LUH2 reconstructed historical harvest rates combined with 2 different wood harvest methods: area-based harvest and carbon-based harvest. The results highlighted a divergent pattern of the local biogeophysical impact from logging under two dominant stages: regrowth dominant and logging dominant. We found the continuous logging causing up to 5% of the reduction of global canopy coverage and 2% of the increase of albedo. The study also highlighted the uncertainty from the forcing of data sources and modeling approach can lead to a several times difference in the magnitude of local biogeophysical effect.  
Modelled Multidecadal Trends in (Very) Large Hail in Europe, the United States and Globally
Authors: Battaglioli Francesco , Groenemeijer Pieter , Taszarek Mateusz , Pucik Tomas , Rädler Anja
Published: March 2024

Large hail events worldwide result in extensive damage, with individual events occasionally exceeding USD 1 billion in losses. Addressing the lack of comprehensive global observational networks, we developed Additive Logistic Regression Models for mapping the frequency of large and very large hail. These models were trained with data from lightning observations, hail reports, and convective parameters from the ERA5 reanalysis. Applying these models to ERA5 data spanning from 1950 to 2021, we reconstructed the probability of large and very large hail events across Europe and the United States. In the United States, hail trends during this period were generally weak and statistically non-significant. In Europe, trends were predominantly positive and significant with northern Italy standing out as a hotspot. Here, the convective activity has seen an abrupt increase with very large hail being 3 times more likely in recent years (2012-2021) than it was in the 1950s. This trend was corroborated by recent observations in the region, including the establishment of a new European hail record with hailstones measuring 19 cm in north-eastern Italy in July 2023. To create a globally applicable hail model, we used a training dataset of hail reports from Europe, the United States, and Australia combined. This effort resulted in the development of a comprehensive global climatology for very large hail. Additionally, we compared the modelled changes in hail frequency to observed changes in insured losses to better understand the complex relationship between hail frequency and hail risk across different regions worldwide.
Advancing Solar Energetic Particle Event Forecasting: Integrating Remote Sensing Techniques into the Relativistic Electron Alert System for Exploration
Authors: Martens Janna , Dröge Henrik , Heber Bernd , Klein Karl-Ludwig , Berdermann Jens , Banys Daniela , Wissing Jan Maik , Wilken Volker , Höfig Lukas
Published: March 2024

The Relativistic Electron Alert System for Exploration (REleASE) forecasting metric, developed by Posner (2007), utilizes electron data collected by the Electron Proton Helium Instrument (EPHIN) aboard the SOHO spacecraft. Our project aims to enhance the probability of detection, decrease the false alarm rate and extend the warning time by implementing various remote sensing techniques. These include automatic flare detection and localization, as well as automatic radio burst detection using the ROBUST algorithm developed at the University of Graz. Historically, a range of diagnostics for Solar Energetic Particle (SEP) events based on radio observations from Earth has been developed since the 1960s, which are to some extent utilized in contemporary prediction models. These diagnostics span from the occurrence of long-lasting broadband radio emissions (cm-m waves) to the spectra of microwave bursts (mm-cm waves). The presence of radio emission at meter wavelengths (e.g., type III bursts) is crucial, since it indicates particle injection into the high corona, but is absent in confined flares, where no particles escape from the active region and no CME is available to accelerate particles higher up.Moreover, our project explores the extent to which diagnostics across diverse frequency ranges can enhance the REleASE system. Initial results of this integration and its impact on the accuracy of SEP event forecasting will be presented.
The effect of forest cover changes on the regional climate conditions in Europe during the period 1986-2015
Authors: Breil Marcus , Schneider Vanessa , Pinto Joaquim
Published: March 2024

Afforestation affects the earth’s climate system by changing the biogeochemical and biogeophysical characteristics of the land surface. While the regional effects of afforestation are well understood in the tropics and the high-latitudes, its climate impact on the mid-latitudes is still subject of scientific discussions. The general impact of afforestation on the regional climate conditions in Europe during the last decades is investigated in this study. For this purpose, regional climate simulations are performed with different forest cover fractions over Europe. In a first simulation, afforestation in Europe is considered, while this is not the case for a second simulation.  We focus on the years 1986-2015, a period in which the forest cover in Europe increased comparatively strong, accompanied by a strong general warming over the continent.Results show that afforestation has both local and non-local effects on the regional climate system in Europe. Due to an increased transport of turbulent heat (latent + sensible) into the atmosphere, afforestation leads to a significant reduction of the mean local surface temperatures in summer. In northern Europe, mean local surface temperatures were reduced about -0.3 K with afforestation, in central Europe about -0.5 K and in southern Europe about -0.8 K. During heat periods, this local cooling effect can reach to -1.9 K. In winter, afforestation results in a slight local warming both in northern and southern Europe, because of the albedo effect of forests. However, this effect is rather small and the mean temperature changes are not significant. In downwind direction, locally increased evapotranspiration rates with afforestation increase the general cloud cover, which results in a slight non-local warming in winter in several regions of Europe, particularly during cold spells. Thus, afforestation had a discernible impact on the climate change signal in Europe during the period 1986-2015, which may have mitigated the general warming trend in Europe, especially on the local scale in summer.
Detecting methane from thawing yedoma: an OSSE evaluating tall towers, TROPOMI, and MERLIN’s capabilities.  
Authors: Pallandt Martijn , Chatterjee Abhishek , Ott Lesley , Marshall julia , Göckede Mathias
Published: March 2024

Climate change is exerting severe impacts on the Northern high latitudes. Large quantities of carbon stored in Yedoma, a carbon and ice-rich permafrost soil, become catalysts for rapid degradation and subsequent carbon release as temperatures rise. The resulting radiative forcing, expected to be 40 to 70 percent in the form of CH4, necessitates accurate detection and quantification to properly account for these fluxes into the global carbon budget. Greenhouse gas observation systems monitor GHG concentrations to infer surface-atmosphere exchange processes. In this study The pan-Arctic tall tower network, passive TROPOMI, and active MERLIN satellites are considered as monitoring platforms. We employ an observing system simulation experiment (OSSE). Utilising a 4D atmospheric transport model, synthetic observations are generated through the Goddard Earth Observing System model (GEOS). To which established errors and biases are added. We simulate a disturbance scenario of enhanced methane release from anticipated Yedoma thaw. A nature run with 'natural' emissions serves as the basis when compared to an enhanced CH4 release run from Yedoma soils. The strength of the enhancement is scaled to establish lower detection limits Satellite systems demonstrate lowest detection limits when aggregating data over a 112-day period, requiring a 1.9 to 2.8 times increase in fluxes compared to current conditions for reliable change detection, which is increased by a factor 1.2 when considering transport modelling uncertainties. Tall tower networks exhibit varied detection limits, emphasising the influence of tower placement and transport errors.
This research not only informs the development of a comprehensive methane observing system but also sheds light on the challenges and strengths of in situ and satellite-based monitoring in high latitude environments. 
DRYTIP – understanding drought-induced changes in ecosystem functioning across Europe
Authors: Abel Christin , Cheng Yan , Schurgers Guy , Horion Stephanie
Published: March 2024

Terrestrial ecosystems are increasingly confronted with environmental changes such as climate change, natural disasters, or anthropogenic disturbances. Prolonged droughts, heat waves and increasing aridity are generally considered major consequences of ongoing global climate change and are expected to produce widespread changes in key ecosystem attributes, functions, and dynamics. Europe has been heavily affected by consecutive and increasingly severe droughts in the past decades, leading to large-scale vegetation die-offs and land degradation. This enhanced frequency in the past, combined with potential impacts of future climate change, makes it important to understand how these droughts affect ecosystem stability functioning and induce changes in ecosystem functioning, which is the aim of the DRYTIP project.  As carbon gain in terrestrial ecosystems is a compromise between photosynthesis and transpiration, a ratio that is also known as water-use-efficiency (WUE), assessing changes in WUE plays a key role in assessing changes in terrestrial ecosystem functioning. We used a remote sensing-based approach to describe changes in ecosystem functioning (similar to the approach suggested in Horion et al. (2019)) across Europe between 2000 and 2023.  We investigate how the severity and duration of droughts relates to the intensity of the change in ecosystem functioning, as well as what are the characteristics of ecosystems where abrupt changes in WUE were observed as a result of drought. We expect to find regional differences in the WUE response scenarios to drought and we will explore the underlying ecosystem conditions in exemplary cases. We finally hypothesise that these differences in ecosystem response to drought can be linked to ecosystem resilience.  We are looking forward to presenting and discussing preliminary results at the General Assembly.  
Groundwater Level Assessment using Data logger and Manual monitoring in developing Country, southwestern Ethiopia
Authors: Kebede Adisu Befekadu , Feyessa Fekadu Fufa , Hermans Thomas , Walraevens Kristine
Published: March 2024

Groundwater monitoring is fundamental, especially for areas where there is a high dependency on groundwater use. Groundwater level (GWL) monitoring is poorly known in Ethiopia. The study focused on evaluating groundwater levels and their relation to precipitation in Ethiopia's Gilgel Gibe and Dhidhessa catchment areas. Groundwater levels (GWL), spring discharges, and rainfall data were collected from various points over the 2022/2023 hydrological year.  Rainfall varied across the region, increasing from April to September and decreasing from plateaus to lowlands with a value between 1539 mm to 1973mm annually. Groundwater levels showed significant spatial and temporal variation, influenced by precipitation and local topography.  Maximum water level varies between 17.6 and 5.75 m in the northwest, 11.6 and 6.2 m in the central part, 11.5 and 3.2 m in the east, 13.1and 4.2 m in the south. Minimum water level varies between 13.2 and 3.8 m in the northwest, 5.8 and 2.7 m in the central, 3.5 and 1.1 m in the east and 7 and 3. 6 m in the south of the study area. Groundwater level fluctuation in the automatically monitored well was 1.55m in the deep well and 3.99m in the shallow well. The spatial drop of the water table in the northwest and south is due to a hydraulic gradient to lowlands and depressions, and evapotranspiration from dense forest coverage. In the central and eastern study area, GWL is shallow and intermediate based on the positions of monitoring wells. Some wells are fully saturated during the rainy season between August and September. Shallow wells reacted swiftly to rainfall, but their levels declined in the dry season. Some wells in high elevation areas experienced minimal fluctuations due to their perched aquifer positions. Groundwater drawdown from usage in dug wells quickly recovered, suggesting potential for small-scale agricultural use. Long-term monitoring and increased data logging are recommended for future studies.
Challenging the complexity: assessing the performances of the convection-permitting configuration of the Regional Earth System Model RegCM-ES over northern Italy
Authors: Reale Marco , Giuliani Graziano , Pichelli Emanuela , Garcia-Valdecasas Ojeda Matilde , Giordano Fabio , Coppola Erika , Querin Stefano , Salon Stefano
Published: March 2024

Northern Italy is an area located in the northern part of the Mediterranean region where several factors make the modeling of its climate dynamics particularly challenging. The area is characterized by significant environmental gradients due to the complexity and high orography of  the Alpine arc surrounding the relatively flat area of the Po Valley, while strong air-sea interactions and deep water formation processes in the northern Adriatic Sea are associated with Bora wind episodes flowing over the basin. Moreover, the peculiar West-East oriented topography of the region drives the formation of a complex river network including the Po river, which is one of the major freshwater sources of the Mediterranean Sea. Here we assess the performances of a state-of-the-art convection-permitting configuration of the Regional Earth System Model RegCM-ES specifically developed for the northern Italy region. The modeling tool components are : (i) RegCM5  with an horizontal resolution of 3 km and 50 vertical levels for the atmosphere, (ii) MITgcm  with an horizontal resolution of approximately 700 m and 59 vertical levels (non hydrostatic) for the ocean and (iii) CHyM with an horizontal resolution of approximately 1 km for the rivers.Model performances have been evaluated against observations and reanalysis datasets (available for the region) in a numerical experiment driven at the boundaries by ERA5 for the atmosphere and by the Copernicus Marine Service (CMS) reanalysis for the ocean. The model well captures  the spatial gradients and mean values of land and seawater temperature, precipitation and sea surface salinity. Still some deficiencies are observed such as a warm bias in summer over the western part of the Po Valley and an overestimation of precipitation over the Alps, although the latter is likely linked to the poor coverage of high altitude measurement stations in the area. This configuration will be adopted in the future to produce high resolution climate projections for the region.
Fire regime alteration and regeneration dynamics in Pinus ponderosa stands of the Southwestern United States
Authors: Mantero Giulia , Mouallem Nadav , Yocom Larissa , Garbarino Matteo , Marzano Raffaella
Published: March 2024

The wildfire regime of dry conifer forests dominated or co-dominated by ponderosa pine (Pinus ponderosa Douglas ex C. Lawson) in the Southwestern United States has been increasingly altered in the last decades. These changes, caused by the ongoing climate change and by the fuel build-up due to several decades of fire exclusion, resulting in a denser and more homogeneous forest structure, are leading to uncharacteristically large and severe wildfires, uncommon for these stands, adapted to fire regimes characterized by frequent low-severity surface fires. Large openings resulting from high-severity fires, together with post-fire drought and competition from herbaceous and shrubby vegetation, may hinder ponderosa pine regeneration, leading to shifts in forest composition or transition towards shrubland or grassland. The lack of pine regeneration caused by the higher severity of a first fire event can be reinforced by subsequent reburning, whose frequency is also increasing in the area. This study investigates how an altered fire regime can interrupt successional pathways in ponderosa pine stands in the Southwestern United States, focusing on the ecological and management implications associated with repeated fire occurrences after an initial high-severity wildfire. We analyzed the spatial and temporal patterns of post-fire regeneration after reburns through a combination of field surveys, remote sensing, and historical fire records, considering fire severity, topography, distance to seed trees, and time between the reburn events. The study aims to enhance our understanding of post-fire regeneration dynamics in the context of an altered fire regime and the ecological consequences and management strategies associated with this phenomenon.
Anthropogenic and natural tritium radioisotope in terrestrial water cycle of Fukushima, Japan
Authors: Gusyev Maksym , Cauquoin Alexandre , Igarashi Yasunori , Takata Hyoe , Hirao Shigekazu , Akata Naofumi
Published: March 2024

Environmental tritium (3H) radioisotope with a half-life of 12.32 years is naturally generated in the upper atmosphere by cosmic rays and enters the water cycle in the troposphere as the water molecule (HTO) to become a useful tracer in Japan and other countries. In 2011, anthropogenic 3H entered the terrestrial water cycle due to the Fukushima Daiichi Nuclear Power Plant (FDNPP) atmospheric release and discharged in Advanced Liquid Processing System (ALPS) treated water from the FDNPP site to the Pacific Ocean in 2023 raising concerns internationally. In Japan, 3H measurements in monthly precipitation have been conducted by the Government and Universities while many surface water sites were sampled twice per year across Fukushima Prefecture accumulating a decade-long record of 3H measurements. However, there are no 3H measurements in precipitation during the FDNPP accident requiring atmospheric numerical modeling to quantify anthropogenic 3H in Fukushima. To utilize 3H as a tracer in Fukushima, we combine simulated anthropogenic 3H released by the FDNPP in 2011 with the long-term time-series of 3H in precipitation from 1950 to present in the Tokyo area, which was scaled to Fukushima area. Using annual 3H in precipitation is 2.86 TU-3.70 TU with an average of 3.37 TU from 2016 to 2021 lead to the scaling factor from Tokyo area to Fukushima city between 1.30 and 1.61. For Fukushima surface water sites, measured 3H concentrations are at low levels of natural 3H concentrations and lead to insignificant doses due to drinking water exposure. In addition, we sampled several headwater catchments near Fukushima city in October 2023 for measuring 3H and estimated tritium-tracer mean transit time and subsurface water storage volume after the ALPS-treated water discharge. As a result, we demonstrate that environmental 3H radioisotope is a useful tracer with developed 3H time-series in precipitation and surface water measurements to evaluate terrestrial water cycle in Fukushima. 
Climate Adaptation Digital Twin transforming climate data to actionable information
Authors: Kontkanen Jenni , Manninen Pekka , Acosta Mario , Bretonnière Pierre-Antoine , Castrillo Miguel , Davini Paolo , Doblas-Reyes Francisco , Früh Barbara , von Hardenberg Jost , Jung Thomas , Järvinen Heikki , Klocke Daniel , Naraynappa Devaraju , Niemelä Sami , Sievi-Korte Outi , Thober Stephan
Published: March 2024

Destination Earth (DestinE) program develops high-precision digital twins (DTs) of the Earth to support decision making in Europe and thus enable more sustainable development and increased resilience against environmental changes. Climate Change Adaptation Digital Twin (Climate DT in brief) is one of the first priority DTs developed within DestinE. It will provide capabilities supporting climate change adaptation at regional and national levels at multi-decadal time scales. We introduce here the first prototype of Climate DT developed during Phase 1 of DestinE.The Climate DT system is built around three one-kilometer-scale Earth-system models (ESMs); ICON, IFS-NEMO and IFS-FESOM. The ESMs have been adapted to run on the fastest supercomputer in Europe, EuroHPC LUMI that is in operation in Kajaani, Finland. The Climate DT system will also harness another state-of-the-art EuroHPC system, MareNostrum 5 that will become operational during 2024 in Barcelona, Spain. The extreme computing capacities provided by these systems enable Climate DT to perform global climate simulations at an unprecedented scale: multi-decadal simulation on 5 km global meshes. This enables providing globally consistent climate information at local levels.  Climate DT introduces a novel approach where ESMs and impact-sector applications operate as part of the same workflow and the output of the ESMs is streamed to applications on real-time in a standardized form called generic state vector (GSV). This approach enables users to access the full model state as soon as it has been produced by the ESMs. It also makes the system scalable across an unlimited number of applications and solves a technical challenge of handling huge amounts of data. Most importantly, this new climate information system enables transforming climate data to actionable information. During Phase 1 of DestinE, this approach is demonstrated through five impact-sector applications that provide information on (1) wind energy supply and demand, (2) wildfire risk and emissions (3) river flows and fresh water availability, (4) hydrometeorological extreme events, and (5) heat stress in urban environments.  In this presentation, we will present the overview of the first prototype of Climate DT, including technical design of the system, performed simulations and implications for the users. We will also discuss the plans for the future development of the system.