bluuebunny/crossref_metadata_2025 huggingface dataset:
Can Blended Model Improve Streamflow Simulation In Diverse Catchments ?
Authors: Sourya Daneti Arun , Rathinasamy Maheswaran
Published: March 2024

Streamflow simulation or rainfall-runoff modelling has been a topic of research for the past few decades which has resulted in a plethora of modelling approaches ranging from physics models to empirical or data driven approaches. There are many physics-based (PB) models available to estimate streamflow, but still there exists uncertainty in model outputs due to incomplete representations of physical processes. Further, with advancements in machine learning (ML) concepts, there have been several attempts but with no/little physical consistency. As a result, models based on ML algorithms may be unreliable if applied to provide future hydroclimate projections where climates and land use patterns are outside the range of training data. Here we test blended models built by combining PB model state variables (specifically soil moisture) with ML algorithms on their ability to simulate streamflow in 671 catchments representing diverse conditions across the conterminous United States.For this purpose, we develop a suite of blended hydrological models by pairing different PB models (Catchment Wetness Index, Catchment Moisture Deficit, GR4J, Australian Water Balance, Single-bucket Soil Moisture Accounting, and Sacramento Soil Moisture Accounting models) with different ML methods such as Long Short Term Memory network (LSTM), eXtreme Gradient Boosting (XGB).The results indicate that the blended models provide significant improvement in catchments where PB models are underperforming. Furthermore, the accuracy of streamflow estimation is improved in catchments where the ML models failed to estimate streamflow accurately.
Dynamics of the Karnali River Bifurcation in Nepal 
Authors: Gautam Kshitiz , Wolf Marijn , Ahmad Rahil , Bogaard Thom , Blom Astrid
Published: March 2024

The Karnali River in Nepal bifurcates into two major branches (i.e., the eastern Geruwa branch and the western Kauriala branch), as it flows out from the Himalayan foothills onto a low relief area in southern Nepal, where it has created an alluvial fan of order 1000 km2. Its dynamics are governed by the natural geomorphological processes of an alluvial fan. The eastern Geruwa branch, which until 2009 used to be the dominant branch regarding its share of the upstream water discharge, now receives a minor share of the water discharge. The reducing discharge in the Geruwa branch has decreased heterogeneity and suitability of wildlife habitat in its floodplains, which constitutes a significant area of Bardiya National Park. The dynamic river branches exhibit a high level of braiding, switching of the dominant channel, and an uneven discharge partitioning between the bifurcates. Our objective is to provide insight on how the system is affected by and will respond to anthropogenic interventions, especially the discharge distribution between the Geruwa and Kauriala branches. The switch in the flow partitioning since 2009 seems to be associated with an intense monsoon season. Besides this, embankments along the Kauriala branch, discharge intakes for irrigation, and unmanaged sediment mining may have affected the partitioning of flow and sediment flux over the Karnali River bifurcates. Furthermore, plans to develop multiple hydropower projects upstream will likely affect the system in the future. We study the impact of these factors on the discharge partitioning between the Geruwa and Kauriala branches, and in particular the flow rate in the eastern Geruwa branch, as the latter is the lifeline for wildlife in the Bardiya National Park, using field surveying/monitoring and numerical models. For this purpose, we have performed an intensive field campaign for data collection and have set up numerical models of various levels of complexity. We have measured cross-sectional profiles and spatial variation of the bed surface grain size distribution. Our observations reveal that bed level in the upstream Geruwa branch is higher than that of the upstream Kauriala branch. Furthermore, we observe river bend sorting in the bifurcation region, which results in a larger bed surface grain size in the upstream Geruwa branch. We have set up a one-dimensional hydrodynamic model to simulate the effects of interventions on the flow partitioning at the Karnali River bifurcation, as well as a two-dimensional hydro-morphodynamic model to study the impact of bend sorting and other two-dimensional aspects on the flow partitioning, as well as sediment deposition in and possible closure of the Geruwa branch.
Reflecting on the use of Generative AI in Higher Education Teaching & Learning
Authors: Petrie Elizabeth , Mutz Sebastian
Published: March 2024

Generative AI tools such as Chat GPT or Google Bard provide new capabilities that can potentially be used by both students and those teaching them. However, as with most new tools, they also come with pitfalls. As those capabilities are likely to also be increasingly integrated into the world of work, we need to look to inform students about sensible use and avoiding problems. We also need to think about how assessment interacts with learning and potentially redesign assessment. This work will reflect on issues and experiences with generative AI in a HE context focusing around an interdiscliplinary course in climate and sustainability..
Predictability of midlatitude Rossby wave packets 
Authors: Riemer Michael , Prestel-Kupferer Isabelle , Schmidt Sören , Teubler Franziska
Published: March 2024

Rossby Wave Packets (RWPs) are linked to extreme weather events and exert a strong influence on the predictability of weather systems in the midlatitudes. Considering the whole wave packet, in the sense of the packet envelope, RWPs can be viewed as entities that describe variability of the atmosphere beyond the synoptic scale. We here examine the predictability of RWPs as such entities. As a verification metric we used the so-called Displacement and Amplitude Score (DAS) applied to the envelope field of the midlatitude flow. The DAS is based on a field deforming method and, as one of its major advantages, avoids the “double-penalty” verification problem without the need to identify single RWP objects. We assess RWP predictability using a 19-year period of NOAA GEFSV12 ensemble reforecasts for RWPs that have been previously tracked in reanalysis data.Forecast errors defined by this metric asymptote towards saturation but do not completely reach saturation within the 10 days lead time available to this study. Corresponding error growth rates maximize during the medium range, in contrast to common error-growth models, in which growth rates are a maximum initially and monotonically decrease with lead time. We hypothesize that this difference relates to the lead-time dependence of error-growth mechanism. Variations in RWP predictability are dominated by the stage of the RWP life cycle, with higher predictability found for the propagation stage than the onset and decay stages. In addition, RWP predictability exhibits a seasonal cycle, with higher predictability in winter than in summer. Controlling for seasonality and the stage of the life cycle, we find i) that high-amplitude RWPs exhibit higher predictability than low-amplitude RWPs for medium-range forecasts and ii) that there is a general pattern of higher predictability over Eurasia than over the ocean basins, with some more detailed variations according to different lead times and life- cycle stages. Finally, predictability of the propagating stage is higher if forecasts are initialized after RWP onset than if initialized before onset. RWP onset thus acts as a partial predictability barrier to the subsequent propagation stage.
First results of an inventory of mountain snow information at global scale
Authors: Schöner Wolfgang , Matiu Michael , Wydra Carlos
Published: March 2024

Snow information from mountain regions worldwide is of high relevance but its spatial and temporal distribution inhomogeneous. The currently running IACS Joint Body on the Status of Mountain Snow Cover, a joint initiative of IACS together with MRI and WMO GCW aims at improving the snow information, data availability and the access to the data for mountain regions worldwide. As part of the initiative, an inventory was initiated which should provide a first and overall picture on the spatial and temporal availability of snow information in the various mountain regions of the world. As there is no strict delineation of mountain from non-mountain regions, it has been up to the contributing experts to decide on what is part/not part of a mountain region. For larger mountain regions with rather different snow climates, the spatial resolution of the inventory was split into several parts. The inventory was launched in May 2023 and was implemented as on online tool.The paper presents initial analyses of the inventory, looking at the spatial and temporal patterns of snow information at a global scale. The picture derived from the feedback of the inventory shows fairly clear global differences, with regions where individual researchers (e.g. Central Asia) are driving access to snow information, while other regions have well established access routines/portals provided by the institutions operating the snow networks (e.g. the US). A preliminary analysis based on metadata from the inventory, a digital elevation model and the GMBA mountain delineation identifies the distribution of in-situ station and their snow information worldwide and how this varies by region and elevation. Information on already estimated spatial and temporal trends of key snow cover variables from mountain regions, such as for snow depth HS and depth of snowfall HN (from unpublished and published papers), are compiled together, although the different trend periods do not make comparison easy. Overall, a rather inhomogeneous picture emerges with regions such as the Alps or the Scandinavian mountains on the one hand, in which the snow information is spatially and temporally dense (with many published studies), and on the other hand regions (such as Greenland or Patagonia) in which the snow information from observations is extremely sparse.
The regularity of climate-related extreme events under global warming
Authors: Zantout Karim , Frieler Katja , Schewe Jacob ,   ISIMIP team
Published: March 2024

Climate variability gives rise to many different kinds of extreme impact events, including heat waves, crop failures, or wildfires. The frequency and magnitude of such events are changing under global warming. However, it is less known to what extent such events occur with some regularity, and whether this regularity is also changing as a result of climate change. Here, we present a novel method to systematically study the time-autocorrelation of these extreme impact events, that is, whether they occur with a certain regularity. In studies of climate change impacts, different types of events are often studied in isolation, but in reality they interact. We use ensembles of global biophysical impact simulations from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) driven with climate models to assess current conditions and projections. The time series analysis is based on a discrete Fourier transformation that accounts for the stochastic fluctuations from the climate model. Our results show that some climate impacts, such as crop failure, indeed exhibit a dominant frequency of recurrence; and also, that these regularity patterns change over time due to anthropogenic climate forcing.
Comparison of predicted soil physical property maps based on (i) LUCAS topsoil database and (ii) Hungarian Soil Information and Monitoring System
Authors: Benő András , Szatmári Gábor , Laborczi Annamária , Kocsis Mihály , Bakacsi Zsófia , Pásztor László
Published: March 2024

The adaption of our land use and agricultural practices requires more detailed and more reliable spatial soil physical data. The LUCAS topsoil database is an up to date collection of soil physical data, however it is spatially scarce. The soil physical data of the Hungarian Soil Information and Monitoring System (SIMS) is spatially denser and has data from multiple layers from 1992. Harmonizing and combining the two datasets can lead to the creation of better resolution and more accurate maps. Before combining the databases, we must make sure, that the sample points represent the area in the same way. The comparison of the data began with the cleansing of the datasets, followed by the conversion of the many sampling depths of the SIMS data to 0-20 cm using mass preserving splines and the conversion of the particle size limit from FAO/WRB to USDA standard. To make sure, that the sum of the sand, silt and clay fractions was 100% additive log ratio (ALR) transformation was applied on both LUCAS and SIMS. Mapping was carried out using random forest kriging with 10-fold cross-validation on a 100 m * 100 m grid using 28 environmental covariates. The ALR maps were converted back, resulting in the sand, silt and clay maps. Using the three maps, soil texture classes were calculated for both datasets using the USDA soil texture triangle. The soil texture classes were compared to each other pixel-by-pixel using the taxonomical distances of the texture classes. The particle fraction maps were compared to each other also pixel-by-pixel using linear regression. The results let us conclude that the LUCAS and SIMS databases produce very similar maps of both sand, silt a clay. The soil texture class comparison also resulted in a very close match with the majority of the country producing very close or perfect matches.  The two soil monitoring systems produce very similar results when mapping sand, silt, clay and soil texture for the whole country and can safely be combined together for future use and mapping.
Investigation of sedimentary structures associated with the Deep Western Boundary Current in French Guiana (Demerara Plateau)
Authors: Blin Paul , Loncke Lies , Durrieu de Madron Xavier , Dupont Pauline , Pairaud Ivane , Zaragosi Sébastien , Fauquembergue Kelly , Basile Christophe , Diadem Scientific team
Published: March 2024

The Demerara Plateau in the Equatorial Atlantic is a transform marginal plateau (TMP) where the Deep Western Boundary Current (DWBC) transports North Atlantic Deep Water (NADW) to the South Atlantic. This current, circulating in the depth between 1300 and 3500 m, represents the deep part of the thermohaline circulation. It also forms hundreds of sedimentary structures along its path, looking like giant flute-casts and called 'comets’. Those comets can reach 3 km in length and theses field of 'comets' more than ten kilometers large. Nautile dives, AUV acquisitions (equipped with Multibeam Sounder SMF, Doppler current meter ADCP, Sediment Sounder) and a mooring, implemented during the DIADEM campaign (N/O Pourquoi Pas?, January-February 2023, DOI : 10.17600/18000672), first allow to document the dynamics of the current DWBC in this equatorial domain, its spatial and temporal variability. Furthermore, investigated the numerous associated sedimentary systems associated with this current, as the "comets" forming giant erosion structures. Two AUV bathymetric surveys and four Nautile dives have helped to better understand the location of these hydrodynamic structures. They are located along outcrops of intensely tilted and fractured carbonated rock, probably associated with an ancient sliding mass. Nautile data coupled with photogrammetry are also used to reconstruct the outcrops of these carbonate blocks and to characterize their deformation. AUV ADCP data (hydrodynamics) acquired in parallel highlight the difference in current intensity between the comet head, where the current has a much greater magnitude than in the comet tail, which appears more sedimented. Measurements of currents and turbidity recorded at the mooring deployed upstream of the comet over 17 days of recordings clearly demonstrate the effect of the semidiurnal tide in the high-frequency variability of currents and sediment resuspension. Taken together, these geomorphological, oceanographic and sedimentary parameters provide a clearer picture of those complex seafloor sedimentary structures that seem to result from the interaction of the DWBC with remobilized carbonated outcrops. Our observations also suggest that those comets initially formed under higher hydrodynamic conditions than those recorded today.
A Machine Learning Algorithm for Cloud Detection Based on the CO2M Multi-Angular Polarimetric Satellite Measurements
Authors: Jahani Babak , Yuan Zihao , van Diedenhoven Bastiaan , Hasekamp Otto , Fu Guangliang , Lu Sha
Published: March 2024

The Earth’s atmosphere contains suspended particles and molecules with a wide range of characteristics. Their interaction with radiation (in both solar and thermal spectral regions) affects the transfer of energy as well as its spatial distribution in the atmosphere, affecting the weather at any moment and climate in the long term. Multi-Angular Polarimetric (MAP) observations have a great potential for quantifying the properties (e.g., size, concentration, etc.) of aerosol particles at a high accuracy. For this reason, a MAP is included on the Copernicus Carbon Dioxide Monitoring satellite mission (CO2M; intended launch date: 2026) to provide a correction of the light path to meet the mission’s stringent requirements for CO2 column retrievals. However, for both trace gas and aerosol retrievals it is also essential to filter out any cloud-contaminated measurements, because clouds strongly interact with radiation and cover between 60-70% of the Earth’s surface at any given time. This study presents an algorithm designed for detecting clouds based on the MAP instrument on CO2M. The algorithm is an adaptation of an approach that was newly developed at SRON Netherlands Institute for Space Research for the MAP instrument onboard the Polarisation and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) platform (i.e., POLarization and Directionality of Earth Reflectances; POLDER) and we are working towards making it applicable to other MAP instruments. This algorithm consists of an Artificial Neural Network model that is trained based on synthetic measurements with realistic geometry, aerosol, and cloud inputs. The synthetic measurements correspond to a wide range of atmospheric conditions and were produced for using the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) forward radiative transfer model developed at SRON Netherlands Institute for Space Research. This algorithm is designed to predict the cloud fraction based on the observed multi-angular polarization and radiance data, plus the instrument specifications and the corresponding viewing- and solar- geometry parameters. Here we focus on the efficacy of the approach for the CO2M mission. Furthermore, the sensitivity of the algorithm’s performance as a function of instrument characteristics (e.g, viewing angles, wavelengths, accuracy) will be discussed.
A geodynamic perspective on the formation of intraplate volcanism in Central East Asia
Authors: Rutson Alexander , Barry Tiffany , Fishwick Stewart , Lane Victoria
Published: March 2024

Central East Asia has experienced intraplate volcanism over the past ~110 Myrs. The mechanism for this volcanism is enigmatic, with several potential causes put forward for the origin, including a mantle plume, edge convection, and lithospheric delamination. One of the big questions for the region is the role played by the long-term subducting systems of the Pacific/Izanagi and the Tethys Ocean(s). And secondarily, how much the volcanism is influenced by the lithospheric conditions and its changing thicknesses across the region.  To recreate the conditions of mantle circulation and flow beneath Central East Asia, a mantle circulation model has been created using the fluid dynamics code ASPECT; the mantle circulation model is coupled with the plate reconstruction of Muller et al. (2019) for the surface conditions of the past 200 Myrs. To better understand the patterns of mantle flow, particles are emplaced into the model to track flow beneath the region, particularly around the subducted slabs. The mantle flow is compared to localities of intraplate volcanism across Central East Asia to assess whether any upwelling regions correlate with the spatial and temporal origins of the volcanism. Initial results show colder downwelling mantle from the surface boundary beneath Central East Asia at ~120-110 Ma, with warmer mantle upwelling into the region to replace it. The timing of this upwelling mantle coincides with the initiation of intraplate volcanism in the region; however, whether this results in the onset of intraplate volcanism in the region and the following 110 Myrs of intraplate volcanism is still being investigated. The mantle flow from the global models will then be used to inform the boundary conditions of a localised box model for Central East Asia. This model will be used to examine any potential effect of delamination beneath Central East Asia, and whether this model can explain any of the timings of intraplate volcanism formation. 
Future Projections and Complementarity Assessment of Solar and Wind Power in China Using CMIP6 Models
Authors: Liao Zhouyi , Xia Xin , Luo Yong
Published: March 2024

As China strides towards its carbon neutrality target by 2060, the strategic planning of renewable energy distribution and power plant installations becomes imperative to fulfill the renewable energy penetration goals. This study presents a comprehensive assessment of the future projections of solar and wind power resources in China, utilizing the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models. We examine various CMIP6 scenarios to project the geographical and temporal variations of solar and wind energy potential up to 2100. A verification assessment was carried out using terrestrial solar radiation and wind speed data sourced from 17 stations operated by the China Meteorological Administration (CMA). This evaluation revealed that the Meteorological Research Institute Earth System Model version 2-0 (MRI-ESM2-0) demonstrated overall superior performance in terms of correlation coefficients (R) and Root Mean Square Error (RMSE). Then MRI-ESM2-0 was selected to examine the spatial and temporal shifts in solar and wind potential in China. Notably, in the SSP585 scenario, a marked decrease in both PV power potential and wind power potential was observed. Additionally, the future spatial complementarity between solar and wind power in China was evaluated using the Pearson correlation coefficient and Kendall rank correlation coefficient and this was juxtaposed with the present complementarity. These maps provide a crucial reference for guiding the planning and management of renewable energy resources in China.
Risk Tipping Points in an Interconnected World
Authors: Eberle Caitlyn , O'Connor Jack , Narvaez Liliana , Mena-Benavides Melisa , Sebesvari Zita
Published: March 2024

The convergence of multiple societal and ecological challenges threatens to push us into an uncertain, risky future. Our critical life-supporting systems, such as the human climate niche, hydrological cycles, natural ecosystems, food production, knowledge systems, and risk management tools, are all fundamentally challenged. While these systems have been continually reshaped throughout human history, the speed of change and the simultaneous changes occurring today are unprecedented. Our research shows how we are teetering on the precipice of multiple tipping points that can trigger abrupt and often irreversible changes to the systems we rely upon.Our research provides a conceptual definition of risk tipping points as a new way to think about the risks we face and illustrates examples of how the concept can be applied. While climate tipping points refer to tipping elements of Earth systems, such as hydrological cycles or climate patterns, risk tipping points concern the socioecological systems dependent on them and when they stop being able to buffer risk and provide their expected functions. We discuss six prominent examples of risks facing these socioecological systems, such as groundwater depletion and space debris, and identify conceptual tipping points for each of them.Furthermore, our research discusses each of these risk tipping points within a context of interconnectivity. We analyze how similar human behaviors and values are at the root of multiple risk tipping points, putting pressure on multiple systems simultaneously. Since none of these systems are isolated from each other, when one system passes a risk tipping point, it increases the overall risk across systems and may actually accelerate tipping in another system. Feedback loops between systems can amplify the impacts of risks and can create self-reinforcing dynamics that increase the speed of change. The effects of these manifesting risks may accumulate over time, causing multiple risk tipping points to overlap and increase risk even further.Finally, our research demonstrates that any attempt to reduce risk in these systems must acknowledge and understand these underlying pressures and their interconnectivity. Actions that affect one system will likely have consequences on another, so integrated and informed solutions are necessary to avoid negative consequences. This also means that interconnectivity can be used as an advantage through solutions that provide co-benefits to address risk tipping points in multiple systems at once. Interconnected risks require interconnected solutions to ensure a safe and sustainable future for all.
On the fidelity of numerical weather prediction model forecasts to identify ice supersaturated regions for aircraft contrail management
Authors: Durant Adam , Thompson Greg , Sholzen Chloé , O’Donoghue Scott , Haughton Max , Jones Rod , Farrington Conor
Published: March 2024

The potential atmospheric warming and impact on climate by aircraft contrails may be similar in magnitude to the direct effect from carbon dioxide emissions across all aviation.  Contrail management via optimized flight planning considering aircraft performance and CO2 emissions, and the presence of ice supersaturated regions (ISSR), could mitigate any potential climate impacts.  The success of aircraft deviations depends on accurate predictions of the water vapor in the upper troposphere and lower stratosphere (UTLS). To evaluate the performance of two global numerical weather prediction (NWP) models (the US Global Forecast System, GFS; and the European Integrated Forecast System, IFS), one reanalysis model (the European fifth generation ECMWF atmospheric reanalysis, ERA5), and one research-grade mesoscale model to predict UTLS moisture and ISSR, we compared humidity forecasts to observations from 383 aircraft flights and radiosondes from 168 launch times over Europe and the Middle East for 10 months in 2022.The research model mirrored observed distributions of relative humidity with respect to ice (RHice)  at all locations above 25,000 ft AMSL, while GFS and IFS forecasts poorly reproduced the observed distribution, and ERA 5 reanalysis only slightly improved on the skill of the IFS. Furthermore, ISSR validation was performed using near equal-area neighbourhoods to compute the Matthew Correlation Coefficient and F1-score and demonstrated a higher model score (F1=0.66) than IFS (F1=0.62), while the GFS score is close to zero (F1≈0) due to an absence of predictions of RHice greater than 100% in stark contrast to observations.  Importantly, the research model also correctly predicts RHice
A robust, user-friendly tool for accurate fluvial grain-size/substrate class estimation
Authors: Soto Parra Tulio , Farò David , Zolezzi Guido
Published: March 2024

Accurate estimation of sediment size and substrate classes in fluvial remote sensing is pivotal for habitat modeling and hydrodynamic applications. While recent advancements have adopted computer vision based approaches (i.e. deep learning), the complexity of setting up these algorithms, along with the requirement of dedicated hardware, and the lack of readily available tools, hinder their wider adoption. This study presents a novel, user-friendly two-step tool tailored for precise substrate class estimation in clear-water river environments from ultra high-resolution orthoimagery, typically coming from UAVs. Leveraging image texture properties (evaluated with the co-occurrence matrix), image color channels (typically Red, Blue, and Green bands) and machine learning classificators (i.e. Random Forest, Support Vector Machine), the proposed methodology is able to accurately identify substrate classes ranging from fine sediments (e.g. sand and lime), various size gravel and cobbles, and boulders, both submerged (wet) and above water. It is a 2-step methodology that involves (a) manual labeling of homogeneous substrate class patches within any Geographic Information System (GIS) platform, followed by (b) streamlined data input. Validation across three reaches of gravel-bed rivers —Aurino, Piave, and Brenta rivers in NE Italy— with differing sizes and morphologies, and substrate ranging from fine sediments to boulders, yielded F1 scores of 0.86, 0.97, and 0.938, respectively. Some challenges still arise when classifying substrate in areas where visibility and light conditions are significantly altered, such as in very deep water, within tree canopy shadows, or due to strong sun reflections. Finally, this tool enables easy and accurate substrate class estimations in riverine environments, offering a significant contribution to fluvial studies and applications.
MODEL OF THE FORMATION OF THE SEDIMENTATION SYSTEM OF THE EURASIAN BASIN OF THE ARCTIC OCEAN AS A BASIS FOR RECONSTRUCTING Its TECTONIC HISTORY
Authors: Neevin Igor , Rekant Pavel , Budanov Leonid
Published: March 2024

The presentation is based on the results of the research work of the Arktic-2011, Arktic-2014 and Arktic-2022 expeditions and contains the results of analysis of the structure of the sedimentary cover of the Eurasian basin of the Arctic Ocean. For the first time, the entire array of seismic data, including Russian and foreign seismic profiles, was used for tectonic constructions. The results obtained make it possible to reconstruct extensive areas of continental lithosphere development in the Eurasian basin. Based on the analysis of the structure of the sedimentary cover of the Amundsen Basin, four stages of the geological history of the formation of the sedimentary system of the Eurasian basin of the Arctic Ocean are substantiated. During the first (Cretaceous-Paleocene) stage, extensive axis-symmetric epicontinental paleo-basins of the Amundsen and Nansen Basins were formed on the shoulders of the continental rift, which were subsequently separated by seafloor spreading. Evidence of similar riftogenic settings in the second half of the Cretaceous is recorded along the entire periphery of the Arctic basin from Greenland to the Chukchi Rise. The second (Eocene)-spreading stage was characterised by stage accretion of the oceanic crust in the Gakkel Ridge and was accompanied by a gradual expansion of the sedimentary basin up to the present-day boundaries of the Eurasian basin. The third stage (Oligocene-Miocene) of sedimentary flexure corresponded to the accumulation of a thick undisturbed sedimentary cover over the entire Eurasian basin, indicating the temporary cessation of spreading in the Gakkel Ridge and the establishment of a tectonic quiescence regime. Similar conditions at this stage are recorded throughout the periphery of the Arctic basin. The resumption of spreading processes occurred at the fourth (Pliocene-Quaternary) neotectonic stage. As the result of the intensification of spreading processes in the Norwegian-Greenland Basin, tectonic stresses penetrated intothe Eurasian Basin along the axis of the Gakkel Ridge. The distinct morphological division of the Gakkel Ridge into Siberian-Marine and Atlantic segments is explained by the jump-like transmission of tectonic stresses of the North Atlantic, which is also confirmed by the anomalously high tectonic, volcanic and hydrothermal activity of the Gakkel Ridge.
Data access for km-scale resolution models
Authors: Ziemen Florian , Kölling Tobias , Kluft Lukas
Published: March 2024

With the transition to global, km-scale simulations, model outputs have grown in size, and efficient ways of accessing data have become more important than ever. This implies that the data storage has to be optimized for efficient read access to small sub-sets of the data, and multiple resolutions of the same data need to be provided for efficient analysis on coarse as well as fine-grained scales.In this high-level overview presentation, we present an approach based on datasets. Each dataset represents a coherent subset of a model output (e.g. all model variables stored at daily resolution). Aiming for a minimum number of datasets makes us enforce consistency in the model output and thus eases analysis. Each dataset is served to the user as one zarr store, independent of the actual file layout on disks or other storage media. Multiple datasets are grouped in catalogs for findability.By serving the data via https, we can implement a middle layer between the user and the storage systems, allowing to combine different storage backends behind a unifying frontend. At the same time, this approach allows us to largely build the system on existing technologies such as web servers and caches, and efficiently serve data to users outside the compute center where the data is stored.The approach we present is currently under development in the BMBF project WarmWorld with contributions by the H2020 project nextGEMS, and we expect it to be useful for many other projects as well.
GeoGPT, the large earth science language model system
Authors: Wang Jian
Published: March 2024

GeoGPT, a large earth science language model system for geoscientists, was designed and developed in response to the Deep-time Digital Earth (DDE) International Science Initiative, which was officially launched at DDE Open Science Forum co-organized by UNESCO in 2021.Starting with leading open-source large language models, GeoGPT has built fundamental capabilities, including extraction of key information from geoscience documents, question-and-answer interaction, logical reasoning, automatic code generation, and numerical computation analysis. Smart incremental training strategy based on open-source large-scale models rapidly enhances the adaptability and performance of GeoGPT in the field of Earth sciences. GeoGPT is architected to be flexible in adapting to different foundation models in the future.To ensure accuracy and professionalism in the field of earth science, GeoGPT has specifically constructed a large high-quality geoscience corpus covering 8 secondary disciplines of earth science and innovatively developed a software system designed for annotating geoscience data more efficiently. Hundreds of Earth scientists have collaborated to complete the annotation of nearly one hundred thousand highly specialized question-and-answer pairs, which greatly enriched the training data resources for this geoscience model.GeoGPT is a global effort of open science practice across research institutes, universities, industry, and other organizations. GeoGPT model is open to the global research community today. It is also being planned to provide open access to large-scale datasets used in GeoGPT and GeoGPT API to Earth science community. GeoGPT is helping to transform the research paradigm of earth science through its potential capabilities of generating scientific hypotheses, constructing theoretical models, and doing research plans.
Root hairs prevent excessive losses in leaf water potential of field grown maize at high atmospheric vapor pressure deficits even in wet soils
Authors: Stoll Florian , Mustafa Osman , Akale Asegidew , Carminati Andrea , Vanderborght Jan , Javaux Matthieu , Ahmed Mutez
Published: March 2024

High atmospheric vapor pressure deficits lead to high transpiration demands which can induce plant water stress because of large dissipation of water potential within plant tissues, but also because the transpiration demand exceeds the possible root water uptake rate from the soil. The latter point might be particularly critical in coarse textured soils which display poor soil-root contact and an unsaturated hydraulic conductivity curve steeply decreasing with matric potential. Root hairs can increase the possible root water uptake rate by increasing the root-soil contact and the effective root radius. Thus, we hypothesize that plants with functional root hairs display (1) less negative leaf water potentials at midday at high transpiration rates in comparison to plants without root hairs; and (2) that this effect is more pronounced in coarse textured soils at low soil matric potentials.To test these hypotheses, we grew two maize (Zea mays) genotypes (wildtype and its root hairless mutant) in two contrasting soil textures (Sand vs Loam). We measured leaf water potential (leaf Psychrometer), transpiration rate (sap flow), atmospheric vapor pressure deficit, soil water potential and soil water content every ten minutes for 30 consecutive days in summer of 2023.The root hair bearing wildtype consistently maintained a higher transpiration rate at relatively less negative leaf water potentials when the atmospheric vapor pressure deficit was high. This effect was more pronounced in coarse textured soil (sand) even in relatively wet soils (soil matric potentials > -100 kPa).We concluded that root hairs enabled plants, in relatively wet soils to maintain high transpiration rates without excessive leaf dehydration. This suggests that at high atmospheric vapor pressure deficit, losses in the hydraulic conductivity of the rhizosphere can already limit transpiration even when the soil would be typically considered wet. Our findings highlight the importance of rhizosphere processes and their relevance for plant water use at the field scale.
Agricultural management determines the size of the terrestrial carbon sink
Authors: Heinke Jens , Müller Christoph
Published: March 2024

Agricultural management can significantly impact biogeochemical cycles. In this study, we estimate the effect of various agricultural management practices such as grazing management, manure application, residue management, tillage, and cover crops on land use change emissions using the LPJmL dynamic vegetation model. We follow the TRENDY protocol to perform model simulations and estimate land use change emissions. Our results show that these practices mitigate a large proportion of emissions from land conversion (such as deforestation) and thus substantially determine the size of the current terrestrial carbon sink. We argue that there is substantial potential to further enhance carbon sequestration by optimizing agricultural management practices. We demonstrate that changes in agricultural management practices typically have smaller effects on albedo, surface roughness, and evapotranspiration compared to dedicated CO2 removal techniques that entail land cover changes (such as afforestation). However, due to limited global data on agricultural management practices, the actual contribution of these practices to emissions and their potential to reduce emissions remain highly uncertain. Our study highlights the need for more research in this area and the importance of considering agricultural management practices in dynamic vegetation models to estimate land use change emissions accurately.
Disko Bay ocean and sea ice forecast
Authors: Rasmussen Till , Hvid Ribergaard Mads , Sievers Imke
Published: March 2024

The maritime industry continues to expand in the waters around Greenland. Apart from fisheries, which by far is the most important income for Greenland, another important element is transportation of goods and tourist, which in many locations are dependent on the conditions at sea. During the last two winters (2022 and 2023) severe sea ice conditions have been seen in Disko Bay. Especially in 2022, there were discussions on whether or not to fly in supplies instead of using the usual transportation on the ocean. A trustworthy high-resolution forecast of ocean and sea ice conditions could have remedied this decision.Currently automated retrievals of observations from remote sensing and forecast model are doing a reasonable job when describing the current conditions and forecasting the short-term offshore conditions, however users are often interested in near shore coastal areas, where resolution matters. The near coastal environment is often not well resolved in Arctic/global models forecast models.This study aim at developing a high-resolution (sub kilometer scale) operational coastal marine forecasting system built on the shoulders of already existing Copernicus services for the area of Disko Bay on the west coast of Greenland. In combination with already, existing products such as automated and manual ice charts it will improve the warning system for the area. A side effect is that the ice service will produce more frequent ice charts for Disko Bay, which will benefit the existing Copernicus Marine Service.The seamless physical downscaling from the Copernicus Marine Services system to the near coastal area in Disko Bay will utilize boundary conditions from the Arctic Marine forecasting system. The system will be forced by a high-resolution none hydrostatic atmospheric forecast from the Danish Meteorological Institute at 2½km resolution. The study is funded by the Copernicus user demonstration program named “COP-INNO-USER”.This presentation will focus on the developments within the service, benefits and challenges. It will also discuss how to integrate the results into operations at the Danish Meteorological Institute. 
Investigating the role of air mass history of Arctic black carbon in GCMs
Authors: Cremer Roxana S. , Kim Paul , Blichner Sara M. , Tovazzi Emanuele , Johnson Ben , Kipling Zak , Kühn Thomas , Watson-Parris Duncan , Neubauer David , Stier Phillip , Sellar Alistair , Holopainen Eemeli , Riipinen Ilona , Partridge Daniel G.
Published: March 2024

Black Carbon (BC) aerosols are known to be important for the Earth’s climate, yet their exact role to the changing of the Earth’s climate and Arctic amplification remains unclear. An accurate description of the BC life cycle in general circulation models (GCMs) can help reduce the uncertainties due to BC aerosols and specify BC's role in the Arctic.In this study, several GCMs (ECHAM6.3-HAM2.3, ECHAM6.3-HAM2.3-P3, ECHAM6.3-HAM2.3-SALSA2 and UKESM1.0) are compared in terms of their representation of BC mass in the Arctic within the AeroCom project GCM Trajectory. A novel Lagrangian framework is employed to examine the history of air masses reaching the observational station Zeppelin, Svalbard. Therfore the removal processes were analysed along the trajectory and the GCMs compared with each other. The analysis emphasises the impact of remote emissions on local BC concentrations in the Arctic, indicating a longer BC lifetime compared to the global average. This underlines the importance of dry and wet scavenging parametrisations in the GCMs.   
South Atlantic Anomaly as marker of geomagnetic jerks during satellite era
Authors: Campuzano Saioa A. , De Santis Angelo , Pavón-Carrasco F. Javier , Qamili Enkelejda
Published: March 2024

The South Atlantic Anomaly (SAA) is an area with values of the geomagnetic field intensity lower than expected ones. The SAA represents one of the most important features of the present geomagnetic field and it is related to the presence of reversed flux patches at the Core-Mantle Boundary. In the satellite era, it has been observed that the SAA areal extent has been continuously growing, with periods alternating positive and negative accelerations. Periods with minima in the acceleration of the SAA areal extent seem to be related to the occurrences of geomagnetic jerks for the last 2 decades. This finding was published in 2021 using the CHAOS-7.2 model. Here, we use the new updated CHAOS-7.16 release to confirm these results, especially relevant in very recent times when edge effects could have affected previous calculations. This new analysis reinforces the proposed link and weaken the idea of a connection by chance. We have also analyzed the acceleration of the areal extent of South American and African reversed flux patches at the Core-Mantle Boundary related to the presence of the SAA at surface and have registered minima in the same periods when they are observed in the SAA at surface. As geomagnetic jerks are sudden changes in the geomagnetic field secular variation related to changes in outer core flow patterns, this result could reinforce the hypothesis that the core dynamics involved in the origin of jerks is related to the physical processes that produce the reversed flux patches, and in turn the SAA evolution.
Sensitivity Analysis of Image Augmentation Methods to Improve Flooded Area Detection Performance
Authors: Kim Seon Woo , Kwon Soon Ho , Jun Sanghoon , Jung Donghwi
Published: March 2024

Recently, detecting flooded areas in CCTV images was performed based on semantic segmentation models (e.g., U-Net, FCN, etc.). However, these flooded area detection techniques are based on large-scale manually annotated images, which consume manpower and time. Image augmentation is one of the ways to overcome the limitations mentioned above. Some previous studies have used image augmentation to improve the performance of flooded area detection by combining two or more methods. However, there has been no study quantifying which augmentation methods are reasonable. This study aims to verify which image augmentation method is reasonable to improve the performance of urban flooded area detection techniques. First, this study develops a flood area detection technology corresponding to training images augmented with five different methods (Brightness, Blur, Contrast, Rotation, Crop). Subsequently, the performance changes for each technique were quantified, and characteristics related to the performance variations of each method were examined.
Lava tubes formation and extensive flow field development during the 1858 eruption of Mount Vesuvius. 
Authors: Lemaire Thomas , Morgavi Daniele , Petrosino Paola , Calvari Sonia , Repola Leopoldo , Esposito Lorenzo , Di Martire Diego , Morra Vincenzo
Published: March 2024

Lava tubes are an important transport mechanism in active lava flows. Their presence in a lava flow can influence its distance of emplacement due to the insulation of the hot molten lava by a cooled overlying crust. Understanding mechanisms of formation and development of lava tubes is fundamental to comprehend lava flow propagation and improve knowledge to better manage the hazard during a volcanic crisis. Vesuvius is known for its major explosive eruptions; however, in its history it underwent extensive periods of open conduit, with prolonged explosive activity and lava flows. After the 1631 eruption, Vesuvius entered an effusive period that ended with the 1944 eruption. During these 313 years, over one hundred lava flows emplaced on Vesuvius flanks, particularly the 1858 eruption which produced a compound pahoehoe lava flow that emplaced on the western flank of Vesuvius. In this study, we conducted: (1) a temporal and spatial reconstruction of the 1858 lava flow using historical documents (geological maps, paintings, descriptions of eruptions), (2) a morphological and surficial analysis of the 1858 lava flow as well as the definition of new contours based on geological maps and digital elevation models and (3) a complete morphological analysis of the lava tube using high-end technologies (time-of-flight terrestrial laser scanner, Lidar equipped drone and optical cameras).  On the 1858 lava flow field surface we found numerous tumuli and ephemeral vents. We discovered a small lava tube present in a flat area of the lava flow field (