bluuebunny/crossref_metadata_2025 huggingface dataset:
Global Streamflow Seasonal Forecasts: Impact of soil moisture initialization in a novel two-way AOGCM-River Routing coupling approach
Authors: Narváez Gabriel , Ardilouze Constantin
Published: March 2024

Accurate seasonal streamflow forecasts (SSF) are crucial for disaster prevention, water management, agriculture, and hydropower generation. A global approach becomes imperative in regions lacking forecast systems. The Météo-France seasonal prediction system (MF System 8 - SYS8), contributing to Copernicus Climate Change Services (C3S), employs a fully coupled Atmosphere-Ocean General Circulation Model (AOGCM) with an advanced river routing component (CTRIP) interacting with the ISBA land-surface scheme. This study evaluates the skill of the SYS8 global SSF through hindcast river discharges. This work is part of the European project CERISE, which aims to enhance the C3S seasonal forecast portfolio by improving land initialisation methodologies.SYS8 derives land initial conditions from a historical initialisation run where land (such as soil moisture and river discharges) is weakly constrained, contrasting with the atmosphere and ocean counterparts, which are nudged to the ERA5 and GLORYS re-analysis. This study improves the initialisation run by relaxing soil moisture to fields reconstructed from an offline land simulation.  Daily streamflow ensemble hindcasts of 25 members are generated in a  0.5° grid, with a lead time of up to 4 months initialised on the first day of May and August between 1993-2017. May and August initialisations allow forecasting of summer (JJA) and fall (SON) seasons. Actual forecast skill is assessed against streamflow observations in 1608 monitored basins worldwide (with areas > 3000 km2) using deterministic and probabilistic metrics. The classical Ensemble Streamflow Prediction approach (ESP) serves as a benchmark to evaluate the control SYS8 SSF skill and the additional skill of soil moisture nudging.Globally, hindcast skill improves with enhanced land-surface initial conditions, especially during summer. Lower latitudes (
Modeling the Antarctic Surface Mass Balance with a coarse temporal resolution
Authors: Maiero Enrico , Colleoni Florence , Agosta Cécile , Barbante Carlo , Stenni Barbara
Published: March 2024

Sublimation is the most important ablation term in the Antarctic Surface Mass Balance (SMB) (Agosta et al., 2019), while it is currently negligible for both Greenland and mountain glaciers (prevailing surface melt). Since simple parameterized SMB models are usually developed for Greenland and Alpine glaciers, they mostly misrepresent sublimation. To face this problem, we developed EBAL, a new parameterized Energy SMB model for Antarctica based on SEMIC (Krapp et al., 2017), which is an Energy SMB model developed for Greenland whose main innovations are a sinusoidal parameterization for the diurnal cycle to assess melt and refreezing and an albedo dependence on snow depth. EBAL was calibrated with both MAR (Kittel et al., 2022) and RACMO (Wessem et al., 2018) outputs for the period 1979-2000 and for the period 2075-2099 under the SSP5-8.5. EBAL can reproduce the statistical properties of MAR and RACMO sublimation time series and spatial distribution even if it uses a coarse time step (1 day). However, our final aim is to use EBAL for paleoclimate simulations, for which the temporal resolution of the inputs is even coarser, as often only monthly data is available. Thus, we have tested the idea of superimposing the present day-to-day variability on the MAR monthly atmospheric forcing of SSP5-8.5. Simulated SMB with EBAL forced with MAR original daily SSP5-8.5 inputs leads to a 210 Gt/yr sublimation, and to a 1425 Gt/yr melt. When forcing EBAL with monthly means only (linearly interpolated), we obtain a 113 Gt/yr sublimation and a 620 Gt/yr melt. When adding present-day variability to linearly interpolated monthly inputs, EBAL computes a 175 Gt/yr sublimation and a 1386 Gt/yr melt. Those latter numbers are very similar to those obtained when forcing with daily inputs. We propose to use this method to test EBAL for paleoclimate applications.ReferencesAgosta, C. et al., (2019). “Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes”. The Cryosphere. 13,  pp. 281-296. 10.5194/tc-13-281-2019. 
Kittel, C. et al., (2022). “Clouds drive differences in future surface melt over the Antarctic ice shelves”. The Cryosphere. 16, pp. 2655-2669. 10.5194/tc-16-2655-2022.
Krapp, M et al., (July 2017). “SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet”. The Cryosphere 11.4, pp. 1519–1535. 10.5194/tc-11-1519-2017
Wessem, J. M. et al., (Apr. 2018). “Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016)”. The Cryosphere 12, pp. 1479–1498. 10.5194/tc-12-1479-2018
Designing an Early-Warning System to Forecast Extreme Climate Conditions Using Data-Driven Approaches with Machine-Learning and Deep-Learning Methods
Authors: Shafei Afshin , Cioffi Francesco
Published: March 2024

This study introduces a methodology for enhancing early-warning systems (EWS) for climate variables such as temperature, humidity, and precipitation. These systems are crucial for predicting hydrological extremes, including heat waves and floods. Traditional forecasting methods face challenges due to the complex nature of climate systems, limitations of global circulation models, and computational demands, often resulting in predictions with coarse spatial and temporal resolutions.Our approach integrates advanced Machine Learning (ML) models with comprehensive data collection for global climate forecasting and regional downscaling. The methodology centers on the use of the ERA5 reanalysis dataset from the European Center for Medium-Range Weather Forecasts (ECMWF) and the CMCC dataset, which provides high-resolution climate data.The core of our global forecasting relies on FourCastNet, a cutting-edge deep learning model developed by NVIDIA. Utilizing Fourier Neural Networks, FourCastNet excels in generating high-resolution global climate forecasts quickly and accurately. It offers a lead time of up to 96 hours for various atmospheric variables, with a specific focus on precipitation forecasts up to 36 hours ahead. This model’s ability to handle complex climate patterns makes it ideal for initial global forecasting.For regional downscaling, we employ Stacked Super-Resolution Convolutional Neural Network (SRCNN) and Super-Resolution Generative Adversarial Network (SRGAN) models, which are trained on the CMCC dataset. This dataset contains dynamically downscaled ERA5 reanalysis and has a 2.2 km spatial resolution and a 6-hourly temporal resolution, matching the temporal resolution of FourCastNet outputs. This compatibility enables seamless linking of global and regional forecasts. The downscaling aims to increase spatial resolution by eight times, providing detailed local climatic insights.All computational models and simulations are conducted on the Google Cloud platform. This platform provides the necessary computational resources, including GPUs, to handle the large-scale processing of climate datasets and the execution of complex ML models efficiently.In summary, this methodology combines advanced ML models and detailed data collection from both ERA5 and CMCC datasets for both global forecasting and regional downscaling. This integrated approach aims to deliver accurate, high-resolution predictions of climate variables, significantly enhancing the capabilities of early-warning systems. The selection of suitable high-resolution datasets for training downscaling models is a key step, ensuring the generation of detailed regional forecasts.
Estimation of aeolian sediment volume in the middle reaches of the Yarlung Zangbo River based on GPR and LiDAR
Authors: Ling Jianyu , Qian Rongyi , Liu Xu , Huang Zhibo , Wang Ding , Hu Ketong , Zhang Jinhang
Published: March 2024

Sand control is one of the most important components of environmental protection. In the middle reaches of the Yarlung Zangbo River, the phenomenon of desertification is becoming serious, which has a great impact on the local ecological environment protection and economic development. The accurate estimation of the volume of aeolian sediment is of great significance to the formulation of the treatment plan. However, most of the existing studies are based on remote sensing interpretation to estimate the area of aeolian sediment, and the research on the volume of aeolian sediment is relatively weak. To make up for this research gap and provide reliable basic information for sand control in the middle reaches of the Yarlung Zangbo River, we carried out research on estimation of aeolian sediment volume based on GPR and LiDAR. The experimental area of this study is located in Zhanang County in the middle reaches of the Yarlung Zangbo River, with an area of approximately 1.8 km2. We set up six GPR survey lines in the experimental area and obtained the bottom interface and corresponding average elevation of aeolian sediment. Subsequently, high-precision surface elevation of the study area was obtained by LiDAR, and the average surface elevation was calculated. Then we obtained the average thickness of the aeolian sediment is 3.25 m by subtraction of the average surface elevation and the elevation of the aeolian sediment bottom interface. Finally, we determined that the volume of aeolian sediment in the experimental area was about 5,850,000 m3. Our study has realized the volume estimation of typical aeolian sediment area in the middle reaches of Yarlung Zangbo River, which has important guiding significance for sand control.
Machine learning-based discrete post-processing of visibility ensemble forecasts
Authors: Nagy-Lakatos Maria , Baran Sandor
Published: March 2024

In aviation meteorology, as well as in water and road transportation, the accurate andreliable prediction of visibility is of utmost importance. Despite various meteorologicalservices offering ensemble forecasts for visibility, the predictive accuracy and reliability forthis parameter are notably lower compared to variables like temperature or wind speed.Therefore, it is strongly recommended to implement some form of calibration, typicallyinvolving the estimation of the predictive distribution through parametric or non-parametricmethods, including machine learning techniques. The World Meteorological Organizationsuggests that visibility observations should be reported in discrete values, turning thepredictive distribution into a discrete probability law. Consequently, the calibration processcan be simplified to a classification problem. This study investigates the predictiveperformance of locally, semi-locally, and regionally trained proportional odds logisticregression (POLR) and multilayer perceptron (MLP) neural network classifiers usingvisibility ensemble forecasts from the European Centre for medium-range weatherforecasts. The findings reveal that while climatological forecasts surpass the rawensemble, post-processing leads to a substantial improvement in forecast skill. Overall,POLR models exhibit superiority over their MLP counterparts.ReferenceBaran, S., Lakatos, M., Statistical post-processing of visibility ensemble forecasts.Meteorol. Appl. 30 (2023), paper e2157, doi:10.1002/met.2157.*Research is supported by the ÚNKP-23-3 New National Excellence Program of theHungarian Ministry for Culture and Innovation from the source of the National Research,Development and Innovation Fund and the Hungarian National Research, Developmentand Innovation Office under Grant No. K142849.
Relation between water-use efficiency and nutrient availability in European semi-natural ecosystems 
Authors: Šigut Ladislav , Oulehle Filip ,   ICOS ecosystem site PIs
Published: March 2024

The CO2 and H2O exchange between plant ecosystem and the atmosphere is commonly interpreted in the terms of plant performance in response to micrometeorological conditions. Though changing light and weather conditions play a primary role in determining yearly ecosystem CO2 uptake and water loss, CO2 and H2O budgets are further modulated by nutrient availability (NA) and air deposition (AD). The influence of changes in NA and AD is observable only over longer time periods, thus when evaluating the time series of eddy covariance fluxes it is more practical to compare across different sites with contrasting levels of NA and AD. Water-use efficiency (WUE) proved to be a useful indicator of ecosystem performance and fitness and allows to evaluate changes in ecosystem functioning since it reflects the degree of stomatal regulation of carbon assimilation and water loss.In this contribution we will focus on the evaluation of NA of nitrogen, phosphorus, and calcium ions on WUE. For this purpose, we take advantage of the existing NA survey performed yearly within ecosystem stations belonging to the Integrated Carbon Observation System (ICOS) network. Nutrient concentrations are obtained from the leaf samples cut from sun-exposed part of the vegetation canopy. Though nutrient content in the soil is not available, leaf samples are expected to be a better measure as they should reflect both soil NA and nutrient accessibility to the plant. The wide selection of semi-natural ecosystems across Europe will allow to evaluate the capability of ICOS network to capture the impact of NA on WUE. Furthermore, we will evaluate how leaf NA relates with AD, especially in the case of nitrogen depositions. For this purpose, EMEP MSC-W modelled air deposition results will be used.
Impact of dam construction on suspended sediment load alteration
Authors: Karimidastenaei Zahra , Darabi Hamid , Torabi Haghighi Ali
Published: March 2024

Impact of dam construction on suspended sediment load alterationZahra Karimidastenaei a*, Hamid Darabi b, Ali Torabi Haghighi a a Water, Energy and Environmental Engineering Research Unit, University of Oulu, P.O. Box 4300, FIN-90014 Oulu, Finland.bDepartment of Geosciences and Geography, University of Helsinki, Helsinki, Finland*Corresponding author: Email: zahra.karimidastenaei@gmail.com AbstractClimate change and human activities have always impacted the fluvial processes, encompassing floods, soil erosion, sedimentation, and sediment transport in rivers, resulting in huge environmental concerns. Dynamics analysis of suspended sediment concentration (SSC) is a determining factor in the sediment budgets, and it has an important role in water resources management. In the current research, the relationship of the suspended sediment (SS) with precipitation (R) and flow discharge (Q) has been analyzed to assess the impact of Saveh Dam on the SSC during 1971-1982 and 1983-1994 as pre and 1995-2006 and 2007-2018 as post-impact periods in the Ghareh-chay basin, Iran. To quantify the spatio-temporal variation of SSC (due to climate change and anthropogenic activities such as dam construction and land use changes), a new measure Δα-based approach was introduced. The newly developed approach, referred to as the Δα-based method, was formulated by calculating the angle between (or the change in the slope of) the optimal Precipitation-Sediment (P-S) and Flow-Sediment (F-S) fit lines. This calculation is conducted spatially, encompassing both upstream and downstream locations, and temporally, by comparing data from different periods. The findings showed that Δα for the Precipitation-Sediment (P-S) relationship between upstream and downstream increased significantly after the Saveh dam commissioning. Initially, Δα was measured at 2.69 degrees and 1.35 degrees for the two pre-impact periods upstream and downstream, respectively. However, these values rose to 5.65 degrees and 9.39 degrees in the corresponding post-impact periods. Based on these results, it is evident that the notable changes in Δα for the Precipitation-Sediment relationship between upstream and downstream indicate the dam's impact on the Suspended Sediment Concentration (SSC) patterns in the Ghareh-chay river. The relatively short distance between the upstream and downstream gauge stations further supports the conclusion that these observed changes in Δα are directly attributable to the dam's influence, significantly altering sediment dynamics in the river system.Keywords: Saveh dam; dynamics analysis; pre- and post-impacted; quantitative approach, sediment rating curve Fig. 1. Location of the study area
Forensic insights into Gloria's storm multi-hazard damages in Catalonia
Authors: Pantaleoni Reluy Nuria , Hürlimann Marcel , Lantada Zarzosa Nieves
Published: March 2024

Conducting a forensic analysis of catastrophic multi-hazard episodes is a challenging yet essential undertaking to enhance our understanding and preparedness for future events. In this study, the multiple direct damage costs for repairing and replacing the effects of the Gloria storm, which struck Catalonia from January 20 to 23, 2020, are thoroughly examined. The storm, characterized by persistent and intense rainfall coupled with strong winds, resulted in a significant sea-level rise heightened by large waves, numerous slope failures and widespread pluvial and fluvial floods, leading to substantial direct economic losses. While databases of damage and losses provide valuable insights into documenting disaster effects, we propose an integrative approach that combines post-event data compilation with forensic analysis to understand the hazard conditions. The resulting database in our study includes parameters such as geographical location, triggering hazard, exposed element at risk, and cost, providing a comprehensive understanding of the Gloria storm's impact. By interpreting the collected data, we derive with key insights of the economic impacts and severity of the hazards caused by the storm in Catalonia. The compilation of data from 14 different sources revealed extensive repair and replacement costs of approximately 390 million Euros for the damages caused by the Gloria storm. Fluvial and coastal processes were the primary contributors to direct economic losses in Catalonia, with fluvial hazards accounting for 44% and coastal processes for 41%. Slope failures and meteorological hazards accounted for 9% and 5%, respectively, in the overall damages. By complementing this with forensic analysis, the integrated approach allows us to discern how and why these events occurred, whether they were amplified or diminished by management strategies, and what strategies could be applied. Additionally, the study incorporates the development of an impact chain, illustrating potential sequences of events and relationships based on the Gloria Storm case. This analytical diagram serves to better comprehend the interrelationships and cascading effects of different hazards, as well as the environmental and socio-economic factors contributing to the damages. The integrated approach contributes to more effective risk management strategies and enhances the broader field of disaster analysis.
Sequential calibration and data assimilation for predicting atmospheric variability
Authors: Forootan Ehsan , Farzaneh Saeed , Dehvari Masoud , Retegui-Schiettekatte Leire , Schumacher Maike
Published: March 2024

Estimating global and multi-level variations of the atmospheric variables and being able to predict them are very important for studying coupling processes within the atmosphere, and for various geodetic and space weather applications. These variables include the thermosphere neutral density, the ionospheric electron density, and the tropospheric water vapour, which are relevant to applications such as orbit determination, satellite navigation, and weather/climate monitoring. Available models have difficulties in realistic prediction of these variables due to the simplicity of their structure or sampling limitations. In this study, we present an ensemble-based simultaneous Calibration and Data Assimilation (C/DA) algorithm to integrate freely available satellite geodetic data (e.g., CHAMP, GRACE(-FO), Swarm, and GNSS) into empirical models with the focus on improving the predictability of atmospheric variables. The improved model, called `C/DA-model' will be assessed in relevant geodetic and space weather applications. For demonstration, the CDA-NRLMSISE-00 is examined during seven periods with relatively high geomagnetic activity and CDA-IRI-ZWD during extensive rainy events.
Experimental imaging of pore scale stretching and coalescence as drivers for solute mixing in porous media
Authors: Pierce Kevin , Le Borgne Tanguy , Linga Gaute
Published: March 2024

The combined action of stretching and diffusion within solute plumes controls mixing in flows through soils and fractured rocks, ultimately affecting the rates of subsurface reactions. Stretching enhances mixing by increasing the area available for diffusion to act and steepening concentration gradients. Ultimately, the resulting solute filaments coalesce which drives the transition of concentration profiles toward uniformity. While the role of stretching is well described by current models, the effect of coalescence on mixing has been more challenging to understand, partly because the spatial extent and distribution of coalesced regions depends on the geometric structure of the medium. Here we present a new set of experiments designed to isolate the role of coalescence on mixing in porous media. Using stereolithography 3D printing, we have fabricated transparent porous models with different geometric structures. By imaging pulses of fluorescent dye as they mix in flows through these models, we have resolved the dependence of mixing rates on both Peclet number and the medium geometry. We observe that converging streamlines downstream of stagnation points establish local zones in the flow where coalescence is enhanced. From these observations, we describe the statistics of coalescence and its impact on mixing and reaction rates. These findings support the ongoing effort to improve our predictions of mixing and reactive transport in the subsurface.
Estimating bed material transport in Himalayan streams using the virtual velocity approach
Authors: Yadav Anshul , Sen Sumit , Mao Luca , A. Hassan Marwan
Published: March 2024

This study investigates sediment mobility and transport dynamics in two Himalayan rivers, the Aglar and Paligad Rivers, during both monsoon and non-monsoon flows. Employing the virtual velocity approach, key parameters such as bed proportional mobility (Y), active layer depth (ds), and displacement length were measured to estimate the virtual velocity of mobilized grains. Local parameters (0.5 m sub-sections) and wetted cross-sectional averages were utilized. Using local parameters, the total annual bed material transport was determined as 67,100 t (±20,400 t) and 18,400 t (±6,000 t) for the Aglar and Paligad Rivers, respectively, with nearly 60% occurring during the monsoon. The significant contribution of non-monsoonal flows (~ 40 %) could be ascertained to higher enough flows in specific sub-sections inducing partial or full mobility. Still, the contribution of partial transport (PT) remained lower (< 6%). In contrast, based on cross-section average parameters, total transport was estimated at 42,300 t (±15,800 t) and 12,200 t (±4,700 t) for the Aglar and Paligad Rivers, respectively, with approximately 79% and 68% occurring during the monsoon. The contribution of PT increased to nearly 18% and 29% for the Aglar and Paligad Rivers, respectively, attributed to the averaging effects of shallower sections. Furthermore, the interdependence of partial transport on Y and full transport on ds leads to discontinuities in transport curves, prompting the proposal of a unified function to represent transport extent for both partial and full transport conditions. The unified function ensured the generation of continuous transport curves, yielding similar transport patterns concerning the contribution of PT, FT, monsoonal, and non-monsoonal flows. The findings are particularly relevant for efficient river management as the region houses several hydropower plants and is highly susceptible to climate change.Keywords:Painted tracers, partial transport, full transport, active layer, monsoonal flows
Temporal and spatial changes in DOM revealed by FT-ICR MS
Authors: Moody Catherine , Bell Nicholle , Mackay Logan , Kitson Ezra
Published: March 2024

DOM from peatlands is a collection of complex molecules, but also a significant source of carbon to aquatic pathways. It has a wide impact on aquatic ecosystems, providing an energy source for microbes and buffering capacity for water chemistry changes. The composition of DOM in drinking water reservoirs also impacts on chemical and energy demands of treatment processes, and is an area of growing concern for UK drinking water providers.DOM was extracted from water collected from peatland headwater streams and reservoirs in the UK. The DOM was analysed with elemental analysis and FT-ICR MS to determine how the composition changes as water moves through the catchment. A combination of spatial and temporal sampling strategies allowed seasonal and catchment characteristics to be investigated (from 2018-2021, and 53-61°N).There were significant trends in DOM composition metrics across a north/south gradient, with higher lipid content, and lower carbohydrate and peptide content in northern sites than southern sites. Samples collected in 2021 had several significant composition differences to other years. Monthly sampling showed the largest changes in DOM composition coincided with the end of the growing season (September in the UK).These results show variable DOM in headwaters can be, and how reservoirs act to buffer the most extreme changes, resulting in more stable DOM compositions in reservoirs. Understanding how DOM composition is impacted by season, climate and catchment characteristics will have important ramifications for drinking water providers, and will help catchment managers plan land use changes and timing of water draw-off from peatland reservoirs.
Triassic Stratigraphy of the North Sea: A New Cross-border Chronostratigraphic Framework using Age Equivalent Units from the Tampen Spur Area, Norwegian North Sea
Authors: Saltapidas Spyridon , Hartley Adrian , Howell John , Schofield Nicholas , Brackenridge Rachel , Watson Douglas
Published: March 2024

The Triassic interval of the northern North Sea contains important hydrocarbon reservoirs and potential targets for CO2 sequestration. However, understanding of the age and distribution of sedimentary facies within the Triassic succession is hampered by the absence of a robust chronostratigraphic framework. Although recent studies for the UK Central North Sea (UK CNS) have defined a robust Triassic chronostratigraphic framework, significant stratigraphic nomenclature differences coupled with lack of dateable palynomorphs within the Triassic continental Hegre Group of the Norwegian Northern North Sea have led to non-biostratigraphic cross-border correlations.Preliminary results from palynology and heavy mineral studies from the Norwegian Northern North Sea within a newly refined tectonostratigraphic framework have prompted a re-examination of the chronostratigraphic correlations between the Central and Northern North Sea. In the greater Tampen Spur area, a lack of active fault movement during sedimentation suggests that deposition of up to 2 km of Triassic Hegre Group sediments is largely climatically controlled and potentially regionally correlatable. Herein we aim to extend the well-established Triassic chronostratigraphic framework of the UK CNS to the Norwegian Northern North Sea area using distinct and age-equivalent Triassic mudstone units.Well data from the Tampen Spur area reveal a regionally correlatable Norian mudstone which represents the Alke formation of the Hegre Group and an additional unassigned Ladinian mudstone package. These mudstone units were deposited on the distal fringes of a major distributive fluvial system sourced from the Norwegian margin. The Alke Formation seals the progradational motif of the Norian Lunde Formation and the Ladinian mudstone seals the Norian-Ladinian sandstone of the Lomvi Formation. The sandstones record the progradation and mudstones the retrogradation of the distributive fluvial system.Given the age and similar petrophysical properties, we propose that the Alke Formation is equivalent to the Jonathan Mudstone Member and the Ladinian Mudstone is equivalent to the Julius Mudstone Member of the Skagerrak Formation in the UK CNS. Thus, the Lunde formation is Josephine equivalent and the Lomvi formation represents the Joanne Member. This layer-cake reservoir configuration is completed with a sandier and locally truncated Raude Formation which is equivalent to the Rhaetian Joshua Mudstone Member of the UK CNS.This preliminary cross-border chronostratigraphic framework unifies the Triassic stratigraphy of the North Sea within a newly refined tectonostratigraphic framework. Regional chronostratigraphic correlations allow a comprehensive paleogeographic reconstruction between the Central and Northern North Sea enlightening all major climatic alternations from Olenekian to Rhaetian.
Better integration of nutritional quality of plants in ecological research
Authors: Berzaghi Fabio , Makowski David
Published: March 2024

Plant nutritional traits (or nutritional values) are a fundamental property of the food web and also important for human beings' health. Much research on nutritional values has focused on a small selected group of plants and primarily crops, but their broader importance for wild animals has been neglected. In particular, the effect of climate change on the nutritional quality of plants is poorly understood even though it may have major implications for the food web and ecosystems. Here we use a dataset covering > 1450 plant species to identify the factors driving plants nutritional properties and develop global projections. We reveal that plant type, CO2, and solar radiation are major drivers controlling nutritional properties. Projections for 2050 show a decline in nutritional quality (-8%, on average at the global scale), measured as the protein to fiber ratio, a strong decrease in minerals (-18%), and a small decrease in digestibility (-3%). Plants in arid and tropical areas will experience the largest decline in quality, which will decline minimally in temperate areas and improve in cold, and polar regions. Quality trends will be opposite in grasses. These results have important implications for human's health, livestock management, and wildlife conservation.
Spatial analysis of the annual and seasonal aridity trends in the Main Olive-Growing Areas of Extremadura (southwestern Spain)
Authors: Moral García Francisco Jesús , Rebollo Castillo Francisco javier , Aguirado Montero Cristina , Rebollo Moyano Lourdes , García Martín Abelardo , Paniagua Simón Luis Lorenzo , Honorio Guisado Fulgencio
Published: March 2024

Understanding drought, or wetness, conditions is essential not only for the rational use of water resources but also for explaining landscape and ecological characteristics. Climate change is expected to lead to an increase in aridity in many parts of the world. In semi-arid regions with warm climates, aridity poses a significant hazard, leading to the potential for desertification due to increased precipitation variability and prolonged droughts. Aridity indices can be employed to identify areas susceptible to desertification. In order to analyse the distribution of aridity in Extremadura, particularly in the areas covered by the olive oil denominations of origin in this region (the cultivation of olive trees is of great economic and social importance in Extremadura), the De Martonne aridity index (IDM) has been used. Temperatura and precipitation data from 81 weather stations located throughout Extremadura, within the 1951–2010 period, were utilised to calculate IDM at every station. Later, the IDM was mapped using an integrated Geographic Information System (GIS) and a multivariate geostatistical approach (regression-kriging) that incorporated comprehensive secondary information on elevation. Annual an seasonal IDM-kriged maps were generated. Finally, temporal trends were analysed using the Mann-Kendall test, and the Sen’s estimator was utilised to estimate the magnitude of trends. An increase in aridity, as the IDM decreased, was apparent during the study period, mainly in the more humid locations of the north. An increase of the seasonal IDM was also found, but it was only statistically significant in some locations in spring and summer, with the highest decreasing rate in the north of Extremadura. Although the denominations of origin in the north of the region have higher decreasing rates, leading to a drier climate, the areas in the centre and south of the region and, in consequence, the denominations of origins within these areas, with more arid climates, can be more seriously affected by the increasing aridity.Keywords: Aridity; Climate Change; De Martonne aridity index; Extremadura; Olive tree.
New data for a model update of the Waiwera geothermal reservoir in New Zealand
Authors: Kühn Michael , Viskovic Paul , Kempka Thomas
Published: March 2024

Waiwera is a small coastal village located on New Zealand's North Island. The geothermal reservoir below the town consists of compacted and cemented sandstones and siltstones of the Waitemata Group [1]. These are some 400-m thick and have been folded, faulted and fractured by tectonic processes throughout the entire depth. The source of the hot water is not well understood because the deeper structure of the field has mainly been inferred from the spatial distribution of thermal water from producing bores. An inferred fault zone at the base of the reservoir is thought to be the source of the upwelling thermal water.The most recent model of Waiwera integrates the depositional environment, mineralogical composition and geological structures [2]. Numerical simulations indicated that further model revisions are required with support by additional field campaigns to increase the knowledge of the complex reservoir geology [3].In this study, gravity data from 77 new stations were acquired around the greater Waiwera area, modelled and interpreted. Two 2.5D gravity models show a 180-m high, NNW-trending step that may represent either steep topography or a fault downthrow to the east in the basement. The position and size of this step are well constrained, but the feature is too deep to confidently predict the dip, and hence is modelled as being almost vertical. This feature may provide a focus for hot water to rise upwards into the Waiwera geothermal system [4].Further, radiocarbon analysis of three groundwater samples show that age of the geothermal water at Waiwera is >20,000 years with
Increased climate change mitigation and adaptation intentions through learning about an event attribution result for the 2021 European floods
Authors: Undorf Sabine , Undorf Monika
Published: March 2024

Event attribution science quantifies the influence of anthropogenic climate change on the occurrence of extreme weather events. One incentive for such research is an assumed motivational effect on people’s climate change mitigation and adaptation efforts, but little empirical evidence exists regarding this. While subjective attribution has been shown to matter, the few studies concerned with scientific attribution were gathered in societies polarised above average. Moreover, scientists and stakeholders have suggested that intellectual and communicative obstacles hinder motivational effects. They also questioned any effect on adaptation (rather than mitigation) intentions.Here, we present results using the high-impact flood in July 2021 in Germany to empirically test the motivational effect of scientific attribution on mitigation and adaptation intentions. Data from a nationally representative sample and oversamples from the two flood-affected federal states in a control (n=663) and an attribution (n=611) group were collected in March 2022. Both groups learned about the consequences and immediate causes of the flood. The attribution group additionally learned about the World Weather Attribution's result that climate change to date had made the associated heavy rainfall more likely and more intense and that this influence would increase further in future. Groups did not differ in socioeconomic factors; mediation analyses and ordinary least squares linear regressions were applied.Results showed that learning about event attribution results increased people’s subjective attribution of the event to climate change and their mitigation and adaptation intentions. It also increased their belief that the climate is changing and that this is due to human activities. Subjective attribution, but not personal flooding experience, mediated these effects. The effect on adaptation but not mitigation intentions was positively related to low education and to far-right political orientation. We set the results in the context of related evidence, highlight methodological caveats, and discuss implications for climate/impact attribution science.
Abrupt onset and termination of the Holocene Humid Period across Asia
Authors: Goldsmith Yonaton , Xu Hai , Ts Narantsetseg , Torfstein1 Adi , Stein Mordechai , Enzel Yehouda
Published: March 2024

The termination of the Holocene Humid Period between 6-5 kyrs ago is relatively well-documented in Africa. By contrast, outside of Africa the spatial extent of this termination, the rate of change (gradual vs. abrupt) and the timing of this termination remain obscure. To assess whether such a termination occurred in Asia and to characterize the spatial and temporal evolution of this termination, we constructed lake-level histories of five closed-basin lakes, four of which are located along a north-south transect in East Asia (Lakes Khukh, Dali, Daihai and Chenghai from 50ᵒN to 25ᵒN) and the fifth is the Dead Sea in western Asia (33ᵒN). A closed-basin lake has no outlet, and therefore its size varies as a function of precipitation and evaporation. Distinct shoreline deposits form at the lake’s margin and are physical relict imprints of past lake-levels. These lake-level histories provide a powerful, first order, quantitative record of past water availability. For each lake, we developed a detailed lake-area history based on numerous radiocarbon, Optical Stimulated Luminescence and U/Th disequilibrium ages.All five lakes show that substantial changes in lake-level (up to 60 m) and surface area (of up to six times that of modern area) occurred throughout the Holocene. The results indicate that in East Asia wet conditions were initiated during the Bølling-Allerød and weakened and dried during the Younger-Dryas. The onset of the Holocene Humid Period, at 11.5 kyrs, was rapid, with the lakes rising to their high-stands within a half millennium. In western Asia, the lake-level rise most likely occurred later, at ~10 kyrs. During the Holocene Humid Period the lakes were significantly larger than the modern lakes. The wet conditions in northeast Asia and western Asia prevailed until 6 kyrs, when the lakes dried out abruptly, within a few decades, and have not been restored to their pre-6 kyrs sizes since. In South China, the rapid drying occurred earlier, at ca. 8 kyrs. All five lakes show a substantial dry period between 6 – 4 kyrs. In northeast Asia the dry conditions prevail until today. However, in both South China and western Asia the lakes rose at 3 kyrs and remained mostly high until recently.Our findings from the five Asian closed-basin lakes show that during the early Holocene, Asia was scattered with lakes that were much larger than today and that an abrupt onset and abrupt termination of the Holocene humid period occurred across Asia. We use the lake-level histories to quantify regional water availability, to discuss the migration of rain-belts in Asia, speleothem oxygen isotopes and pollen records, and the ability of transient climate models to capture the magnitude, extent and rapidness of these wet conditions and hydroclimatic transitions.
Preconditioned biosphere flux extremes in terrestrial carbon cycle models and reanalyses in the recent past, present, and future
Authors: Riebandt Björn , Adam Moritz , Ziegler Elisa , Rehfeld Kira
Published: March 2024

The increasing frequency and severity of climate extremes pose a multifaceted threat to health, economic stability, and both natural and human-made environments. Potential overlap and accumulation of extremes as compound extremes poses further challenges. Ongoing climate change intensifies these challenges, underscoring the importance of a better understanding of the causes and drivers for compound events. Earth system model projections suggest that more frequent climatic compound extremes affect terrestrial biosphere fluxes, potentially reducing the land’s CO2 storage potential. However, whether models are able to represent such interactions like the priming of the biosphere towards extremes accurately remains to be shown.Here, we focus on the role of concurrent precipitation and temperature as drivers of biosphere flux extremes and investigate their change in frequency and intensity based on their occurrence in historical simulations, reanalyses, and future projections. We use thresholds to define concurrent extremes and Monte Carlo randomization to constrain uncertainties. Further, we examine the association of climatic compound events with anomalies in biosphere carbon fluxes to ascertain their mutual relation, aiming to establish how these climatic compound events contribute to preconditioning extremes in the biosphere. Given this assessment of the occurrence change of climatic compound events and their connection to extremes in biosphere carbon fluxes, we infer how climatic compound events may precondition the biosphere for extremes. Lagged overlaps show significant seasonality and spatial heterogeneity in preconditioning. Comparing reanalyses and historical simulations in a model of the terrestrial carbon cycle and a comprehensive Earth System Model, we examine how well primed biosphere extremes agree in different data sources. Leveraging these findings, we evaluate if model projections show signs of stronger climatic priming of the biosphere in the next century.
The TRIQUETRA Knowledge Base Platform
Authors: Kontopoulos Christos , Anastasiou Anastasia , Magkoufis Efthymios , Sarris Apostolos , Klinkenberg Victor , Polidorou Miltiadis , Verykokou Styliani , Charalampopoulou Vasiliki
Published: March 2024

The TRIQUETRA project seeks to establish an evidence-based assessment platform for precise risk assessment. Functioning as a Decision Support Tool, this platform aims to enhance efficiency in risk mitigation and site remediation. The TRIQUETRA project's overall approach is structured around three key elements: (i) Risk Identification, (ii) Risk Quantification, and (iii) Risk Mitigation.Within this framework, a novel Knowledge Base Platform (KBP) has been created, serving as an electronic repository equipped with advanced search tools and capabilities. It encompasses information on Climate Change (CC), geological, historical, and site-specific data, along with risks and mitigation measures for Cultural Heritage (CH) sites based on the verified data, geographical identification and results obtained from the outputs of the project.The primary goal of the KBP is to comprehensively integrate and visualize all shared project data, utilizing both a searchable literature database and a sophisticated WebGIS platform that adheres to the standards set by the Open Geospatial Consortium (OGC) and INSPIRE. It also incorporates various features for the deployment, cataloguing and categorisation of the data produced and shared within the project, to enhance the discoverability of the data. The KBP is structured based on two distinct key components, namely the Bibliography inventory and the WebGIS. These distinct sections of the platform gather all the data and information related to the pilot CH sites of the project. The combination of available datasets for each pilot site leads to the creation of a data cube - a multidimensional structure facilitating the efficient representation and analysis of data across various dimensions, including time and location.It is imperative to point out that the platform will keep evolving throughout the course of the project in order to align with upcoming project outputs, enabling the fusion of different data types and efficient research on each pilot CH site. This, in turn, contributes to advancing knowledge in CH monitoring and facilitating optimal preservation and risk mitigation actions.
Investigating the relationship between the presence of active seismicity and the displacement of the eastern flank of Piton de la Fournaise, La Réunion. 
Authors: Lengliné Olivier , Firode Lise , Duputel Zacharie , Ferrazzini Valérie
Published: March 2024

Geodetic observations indicate a seaward displacement of the eastern flank of Piton de la Fournaise volcano on La Réunion Island. Previous studies have suggested that the this displacement could be the result of a sheared sill. However, the location of the sill inferred from InSAR data is currently inconsistent with the distribution of earthquakes observed at greater depth. However, other results have attributed the current distribution of seismic activity beneath the eastern flank to the combined effect of overpressure in the magma chamber and loading of the volcanic edifice. The aim of the our study is to investigate the relationship between these two phenomena: the presence of active seismicity and the displacement of the eastern flank of Piton de la Fournaise. With this purpose, we enhance the characterization of seismic activity using template matching, double-difference relocation and focal mechanisms determination. We then explore the link between the spatio-temporal evolution of the seismicity and the displacement of the eastern flank. Additionally, we evaluate the impact of the velocity model to determine if we can reconcile hypocenter locations with the destabilization structure inferred from InSAR.
Forecast Salinity Changes in Coastal Wetland Using Deep Learning-based LSTM Model
Authors: Afsar Mohammad , Jin Yan
Published: March 2024

Understanding and predicting salinity dynamics in marshlands is crucial for effective management and biodiversity conservation. Those ecosystems are facing increasing threats due to climate change and anthropogenic activities as they are located at the interface of terrestrial and aquatic environments. Here we present a cutting-edge study on the forecasting of salinity changes in St. Jones Reserve (39.10 ◦N, 75.44 ◦W) in Dover, DE utilizing a recurrent neural network-based Long Short-Term Memory (LSTM) model. Our overall objectives are to enhance the accuracy and robustness of salinity forecasts and facilitate informed decision-making for marshland conservation and sustainable land use. Model input features include measured groundwater and salinity levels as measured by Solinst 3001 Levelogger LTC 5 and 3001 Barologger 5 sensors at four sites along the transects. All the sensors collected data at a 15-minute interval from March 2022. The key contribution of this research includes the development of a novel LSTM architecture optimized marshland environments, as well as the integration of advanced feature engineering techniques to enhance model performance. The methodology is validated through extensive experimentation, utilizing historical salinity data from diverse marshland locations worldwide. Results demonstrate the model’s ability to outperform existing forecasting methods, providing timely and accurate predictions of salinity changes. Furthermore, the research explores the potential for real-time monitoring applications, aiding land managers and policymakers in implementing strategies to mitigate the impact of salinity fluctuations on marshland ecosystems.