bluuebunny/crossref_metadata_2025 huggingface dataset:
Upper tropospheric humidity and ISSRs: near real-time flight data delivery, statistics, and application for contrail forecast model assessment
Authors: Li Yun , Rohs Susanne , Blomel Torben , Bundke Ulrich , Petzold Andreas
Published: March 2024

The so-called ice-supersaturated regions with air parcels in the status of ice supersaturation (ISSRs) are potential formation regions of cirrus, making them of particular interest to contrails and aviation-induced cirrus. Contrail persistence requires slight ice subsaturation to ice supersaturation (Lee et al., 2021; Li et al., 2023); otherwise, ice crystals would sublimate quickly. Contrails and contrail cirrus in regions with high relative humidity with respect to ice (RHice) have been derived to cause a net warming impact in earlier studies (Sausen et al., 2005; Stuber and Forster, 2007; Lee et al., 2021)Seasonal and regional variabilities and long-term trends of upper tropospheric RHice and ISSRs have been studied using IAGOS routine measurements from passenger aircraft (Petzold et al., 2020; Rohs et al., 2023, see also https://www.iagos.org/). With increasing awareness of the strong climate impact of contrails and contrail cirrus among other aviation emissions, re-routing aircraft to avoid contrail formation becomes an important mitigation target for the aviation industry. However, the correct representation of ISSRs in forecast models is an essential prerequisite to plan robustly more climate-friendly flight trajectories.In this work, we will show the status of weather forecast models in representing real upper tropospheric ice supersaturation. The near real-time RHice dataset from IAGOS observations, provided post-flight to Copernicus Atmosphere Monitoring Service (CAMS), are used to study the occurrence patterns and favourable spatial and temporal conditions of ISSRs in dense air traffic regions, e.g., the North Atlantic flight corridor. Cases demonstrating the assessment of ISSRs and contrail forecast models at cruise levels with in-situ aircraft observations will be showcased.[Note: This work is conducted within the framework of the Horizon 2020 project ACACIA with Grant Agreement No. 875036 and the SESAR 3 JU project CICONIA with Grant Agreement No. 101114613.]
Analysis and modelling of compound hazards to the desalination plants on Gotland: The Hans Storm 2023 event
Authors: Koszalka Inga Monika , Masini Matteo , Antivachis Dimitrios , Döös Kristofer , Karlsson Agnes , Karlsson Bengt , Axell Lars , Arneborg Lars
Published: March 2024

The island of Gotland located in the middle of the Baltic Sea is Sweden's largest island, and also a county and municipality with the population of about 60,000, employed mainly in agriculture and tourist sectors. Gotland is a very popular domestic tourist destination for mainland Swedes, reaching nearly 2 million ferry and plane passengers per year. Gotland experiences limited capacity in groundwater reservoirs combined with increased demand during the warm season when tourists visits peak leading to recurring water stress. Desalination of drinking water from the Baltic Sea is a promising alternative to complement municipal water supply. The operation of the two major desalination treatment plants becomes however disturbed by compound hazards due to extreme sea weather events (marine heatwaves, strong upwelling events) and related hydro-sedimentary and biological processes (macro- and microalgae blooms) that are predicted to intensify under the climate change. Developing an apt forecasting system for this "multi-hazard" to inform sustainable management of Gotland's water resources becomes thus a priority and is of broader relevance to other regions in Sweden.The ALGOTL project, funded by the Swedish research council for sustainable development (FORMAS), is a collaboration between Stockholm University, the Swedish Meteorological and Hydrological Institute (SMHI) and Region Gotland to develop a novel forecast framework for natural hazard impacts on management of water resources, both short term (early warning) and long term (climate scenarios). The project aims at development of Lagrangian- and risk modelling tools based on the operational ocean state forecast at SMHI. Our stakeholders on Gotland will provide input on adverse impacts, information required for management, and feedback on the forecast framework during the project.This contribution will summarize results from observational and modelling analysis of the oceanographic, hydrological and biological conditions due to the Hans storm event in August 2023 that led to the disturbance in operation of the desalination plants on Gotland, located at the Herrvik (eastern side) and Kvarnåkershamn (western side of the island). The storm triggered an upwelling event leading to sea temperature changes of 10 K (prompting the change from summer to winter operational mode) and high vertical and horizontal velocities and associated excessive transport of sediment and biological (algae) material disrupting the filtering process. We will also show results from Lagrangian backtracking of the source waters reaching the desalination plants and present prospects for developing of a forecast system for related events in the future.More information about the ALGOTL project: https://www.su.se/english/research/research-projects/algotl-forecast-framework-for-algae-blooms-to-secure-water-supply-on-gotland
DInSAR analysis to detect local and regional coseismic ground deformation: insights from the 2016 central Italy earthquake
Authors: Porreca Massimiliano , Carboni Filippo , Manzo Mariarosaria , Valerio Emanuela , De Luca Claudio , Occhipinti Martina , Ercoli Maurizio
Published: March 2024

Over the past three decades, remote sensing techniques, particularly Differential Synthetic Aperture Radar Interferometry (DInSAR), have been used to investigate ground deformation phenomena accurately. The DInSAR method is extensively adopted for reconstructing the deformation pattern induced by earthquakes and for discerning the seismogenic fault, particularly in cases where field evidence are not comprehensive.This study focuses on the application of DInSAR method to the 2016 Mw 6.5 mainshock occurred in the Apennines, central Italy. The earthquake produced a complex surface rupture distribution in a wide area which was meticulously examined by field geologists for a long time after the seismic sequence.Here, we present detailed maps of the surface deformation pattern produced by the M. Vettore Fault System (VFS) during the October 2016 earthquakes, derived from ALOS-2 SAR data via DInSAR technique. On these maps, we trace a set of cross-sections to analyse the coseismic vertical displacement, essential to identify both surface fault ruptures and off-fault deformations. At a local scale, several coseismic ruptures are identified in agreement with previous field observations. On a larger scale, the VFS hanging-wall displays a long-wavelength upward-convex curvature, less evident toward the south and interrupted by the presence of an antithetic NE-dipping fault. The quantitative comparison between DInSAR- and field-derived vertical displacement highlights the reliability of the approach for constraining ruptures with vertical displacement up to 50-60 cm. The rapid detection of deformation patterns using DInSAR provides crucial information on activated fault segments, their distribution, and interaction shortly after seismic events. The proposed workflow, applicable globally with satellite SAR data, can support geological field surveys during seismic crises and offer rapid insights into surface ruptures essential for emergency management in not easily accessible areas.
Palaeobathymetry of the Mid-Norwegian volcanic margin during continental breakup and paleoclimate implications
Authors: Tugend Julie , Mohn Geoffroy , Kusznir Nick , Planke Sverre , Berndt Christian , Manton Ben , Zastrozhnov Dmitrii , Millet John, M.
Published: March 2024

The Mid-Norwegian volcanic rifted margin and its NE-Greenland conjugate formed in relation to continental breakup in the latest Palaeocene to earliest Eocene during the emplacement of the North Atlantic Igneous Province (NAIP). The development of the NAIP and opening of the North Atlantic occurred contemporaneous to the Paleocene Eocene Thermal Maximum (PETM) which corresponded to a rapid 5-6 °C global warming episode.The cause of this rapid global warming, explored as part of IODP Expedition 396, is thought to relate to the thermogenic gases released to the atmosphere via thousands of hydrothermal vents. The thermogenic gases were produced by contact metamorphism of carbon-rich sediments during widespread sill emplacement from the NAIP. The potential of hydrothermally-released greenhouse gases to influence climate depends strongly on the water depth at which they get released. Unless it is released in a shallow marine environment most methane will be oxidized before it reaches the atmosphere.Early results from IODP Expedition 396 have documented that at least one of the Mid-Norwegian hydrothermal vents was emplaced in shallow marine to potentially sub-aerial conditions. The aim of this contribution is to constrain further the paleo-water depth at which hydrothermal vents formed along the other parts of the mid-Norwegian volcanic rifted margin. This study focuses on an integrated workflow of quantitative geophysical and geodynamic analyses calibrated by new IODP drilling results and structural and stratigraphic observations. We use a 3D flexural-backstripping, decompaction and reverse thermal subsidence modelling to predict the palaeobathymetry and palaeostructure at keys stages of the syn- to post-breakup evolution that can be compared with palaeo-water depths estimated from biostratigraphic data. Results provide new constraints on the paleobathymetry of hydrothermal vent complexes required to confirm whether the global warming recorded by the PETM was triggered by the magma-rich continental breakup leading to the opening of the northeast Atlantic Ocean. 
DL-Driven Precipitation Correction for Enhanced Hydrological Simulations over Central Europe
Authors: Patakchi Yousefi Kaveh , Belleflamme Alexandre , Goergen Klaus , Kollet Stefan
Published: March 2024

Integrated hydrologic models are useful for assessing the impact of climate change on water resources and associated risks. The performance of these models strongly depends on the quality of precipitation forcing data, where errors can significantly affect the simulation accuracy. Therefore, methods such as data assimilation (DA) bias adjustments, and data-driven (e.g., deep learning, DL) methods are in use to improve precipitation simulation data. However, given the high spatiotemporal variability of hourly precipitation, challenges such as availability of “ground truth” measurements, data imbalance, and evaluation of the methods affect the applicability and assessment of these methods. In this study, we correct precipitation data for the first 24h obtained from the  ECMWF HRES 10-day deterministic forecast using EUMETSAT H-SAF h61 satellite observations, by learning the errors using a U-Net convolutional neural network (CNN) as a DL technique. Our findings show good agreement between the corrected precipitation data (HRES-C) and the reference data (H-SAF) with roughly about 49%, 33%, and 12% improvement in mean error, root mean square error, and Pearson correlation, respectively. Additionally, we investigate the impact of original HRES, H-SAF, and HRES-C corrected products used as forcing data in high-resolution (~0.6km) integrated hydrologic simulations using ParFlow/CLM over central Europe in daily and monthly scales from April 2020 to December 2022. We choose soil moisture (SM) as a diagnostic variable for our evaluation. SM simulations produced with uncorrected HRES 24h show a better agreement with ESA CCI SM satellite data compared to SM produced with HRES-C. Further comparison of the three products with in-situ rain gauge measurements over the same period shows superiority of HRES 24h in representing the “ground truth” precipitation.  Our study highlights the need for better precipitation reference data, challenging reliance only on satellite observations (H-SAF) for DL-based correction of precipitation forcing data in hydrological simulations.
Enhanced exhumation in the East Karakoram during themid-Pleistocene climate transition: A detrital provenance assessment
Authors: Mark Chris , Clift Peter , Paolucci Célia , Alizai Anwar , Garzanti Eduardo
Published: March 2024

Around the Nanga Parbat-Haramosh massif in the west and the Namche Barwa massif in the east, the Himalayan orogen exhibits an abrupt strike change from roughly E-W to N-S, forming two structural syntaxes. Each syntaxis is drained by a major trans-orogenic river system: the Indus and Ganges-Brahmaputra, respectively. The syntaxial massifs record rapid exhumation rates (up to c. 10 mm/a), together with Plio-Pleistocene mineral (re)crystallisation and cooling ages (Bracciali et al, 2016; Crowley et al., 2009; Zeitler et al., 1993). The Namche Barwa massif supplies c. 65-74% of Brahmaputra bedload (Enkelman et al., 2011; Dong et al., 2023). In contrast, the Nanga Parbat massif supplies c. 10% of modern Indus bedload, which instead is dominantly sourced from the East Karakoram (Clift et al, 2022).We present detrital rutile and zircon U-Pb data from the Indus fan, sampled by IODP expedition 355 and ODP leg 117. These data record abrupt increases in the proportion of sediment sourced from the Nanga Parbat massif between c. 8-6 Ma and again at c. 2 Ma, coherent with bedrock studies (Crowley et al., 2009; Zeitler et al., 1993). The Nanga Parbat massif then dominates sediment supply until c. 1.5-0.6 Ma, followed by an abrupt switch to East Karakoram sourcing.The East Karakoram includes some of Earth’s highest peaks, and largest extra-polar glaciers. Therefore, a provocative possibility is that the jump in erosion focus was driven by the switch from c. 41 ka, obliquity-dominated, to 100 kyr, eccentricity-dominated orbital forcing (the Mid-Pleistocene Transition). This transition occurred at c. 1 Ma (Clark et al., 2006), and could have driven enhanced glacially-mediated erosion in the east Karakoram, outpacing Nanga Parbat exhumation. Approximately synchronous increases in exhumation rate are also documented at Nanga Parbat-Haramosh massif, and the Namche Barwa massif (Guevara et al., 2022; Govin et al., 2020; King et al., 2016;).   Bracciali, L., et al., 2016, Earth-Sci. Rev., 160, 350-358, doi: 10.1016/j.earscirev.2016.07.010; Clark, P., et al., 2006, Quat. Sci. Rev., 25, 3150-3184, 10.1016/j.quascirev.2006.07.008;; Clift, P., et al., 2022, Earth Plan. Sci. Lett., 600, 117873, 10.1016/j.epsl.2022.117873; Crowley, J., et al., 2009, Earth Plan. Sci. Lett., 288, 408-420, doi: 10.1016/j.epsl.2009.09.044; Dong, X., et al., 2023, Basin Res., 35, 2193–2216, doi: 10.1111/bre.12795; Enkelman, E., et al., 2011, Earth Plan. Sci. Lett., 307, 323-333, 10.1016/j.epsl.2011.05.004; Govin, G., et al., 2020, Geology, 48, 1139-1143, doi: 10.1130/G47720.1; Guevara, V., et al., 2022, Science Advances, 8, eabm2689, 10.1126/sciadv.abm2689;King, G., et al., 2016, Science, 353, 800-804, doi: 10.1126/science.aaf2637; Zeitler, P., et al., 1993, Geology, 21, 347-350, doi: 10.1130/0091-7613(1993)0212.3.CO;2
Frictional strength, healing behaviour and deformation mechanism of low-grade serpentinites at hydrothermal conditions
Authors: Salvadori Leonardo , Tesei Telemaco , Di Toro Giulio
Published: March 2024

Serpentinites are “weak” rocks that play a critical role in the nucleation and propagation of slow slip events, tremors and earthquakes due to their unique rheological properties that promote strain localization and are common in a variety of tectonic settings, from mid-ocean ridges, to transform faults and subduction zones. In this study we analyze the microstructures of natural and experimental faults made by low-grade serpentinites (chrysotile and lizardite ± magnetite) to infer the possible deformation mechanisms operating in nature at hydrothermal conditions.The natural serpentinites pertain to the exhumed Monte Fico shear zone (Elba Island, Italy) that reached greenschist facies conditions during subduction related to the Apennine orogeny. The shear zone is made of dm-m scale lenses of massive and less deformed serpentines surrounded by foliated serpentinites and cut by brittle faults. Bulk deformation in the natural shear zones was accommodated by anastomosing and pervasive S/C foliation structures. Fault surfaces are covered with slickenfibers mostly composed of chrysotile and polygonal serpentine. The interpretation of the microstructural analysis indicates the coexistence of ductile pressure-solution within the massive lens with fracturing, veining and frictional slip along the faults bounding the lenses. This fault zone rock assemblage and microstructural association suggests that cycles of high fluid pressures are limited by dilatant slip along the faults.To determine the frictional properties and deformation mechanisms of these serpentinite-bearing faults we performed experiments with a rotary shear apparatus equipped with an hydrothermal vessel (ROSA-HYDROS, Padua University, Italy). We conducted slide-hold-slide (SHS) experiments at an effective normal stress of 20 MPa, a fluid pressure of 6 MPa, constant sliding velocity of 10 µm/s and at four different temperatures (room, 100°C, 200°C and 400°C). Friction experiments allowed to determine the rheological difference between the massive lens and the bounding faults, which represents favorable sites for slip nucleation.  The frictional healing properties document how the strength of these heterogeneous brittle-ductile shear zones evolve during the interseismic period.The combination of natural and experimental observation in our project aims at the understanding of the mechanical behaviour of such lithologically and geometrically complex fault zones and to elucidate slip processes during earthquakes and slow slip events.
Multi-angular airborne observations for simulating thermal directionality at the satellite scale
Authors: Langsdale Mary , Wooster Martin , Schuettemeyer Dirk , Hook Simon , Middleton Callum , Grosvenor Mark , Eng Bjorn , Colombo Roberto , Miglietta Franco , Genesio Lorenzo , Sobrino Jose , Rivera Gerardo , Beeden Daniel , Jay William
Published: March 2024

Viewing and illumination geometry are known to have significant impacts on remotely sensed retrieval of land surface temperature (LST), particularly for heterogeneous regions with mixed components. Disregarding directional effects can have significant impacts on both the stability and accuracy of satellite datasets, for example when harmonising datasets from different sensors with different viewing geometries. However, it is difficult to accurately quantify these impacts, in part due to the challenges of retrieving high-quality data for the different components in a scene at a variety of different viewing and illumination geometries over a time period where the real surface temperature and sun-sensor geometries are invariant. With LST an Essential Climate Variable and the development of high resolution future thermal infrared missions (e.g. LSTM, SBG, TRISHNA), it is essential that further work is done to redress this.With this in mind, a joint NASA-ESA airborne campaign focused on directionality was conducted in Italy in the summer of 2023, led by the National Centre for Earth Observation at King’s College London. This campaign involved concurrent acquisition across longwave infrared (LWIR) wavelengths at both nadir and off-nadir viewing angles through the deployment of two aircraft flying simultaneously, each equipped with state-of-the-art LWIR hyperspectral instrumentation. Data was collected to enable simulation of angular effects at the satellite scale over both agricultural and urban surfaces, with the aim of understanding and potentially developing adjustments for wide view angle satellite-based LST retrievals and remotely sensed evapotranspiration estimates. In-situ observations were collected additionally to enable accuracy assessment of the airborne datasets.This presentation first details the airborne campaign, including the unique and novel data collection strategies and design modifications to enable evaluation of directional effects for thermal satellites. Preliminary results from the campaign are then presented as well as plans for further analysis related to future satellite thermal missions. 
A data-driven sea-ice model with generative deep learning
Authors: Finn Tobias Sebastian , Durand Charlotte , Porro Flavia , Farchi Alban , Bocquet Marc , Chen Yumeng , Carrassi Alberto
Published: March 2024

The current generation of sea-ice models with Brittle rheologies can represent the observed temporal and spatial scaling of the sea-ice dynamics at resolutions of around 10 km. However, running those models is expensive, which can prohibit their use in coupled Earth system models. The promising results of neural networks for the fast prediction of the sea-ice extent or sea-ice thickness offer an opportunity to remedy this shortcoming. Here, we present the development of a data-driven sea-ice model based on generative deep learning that predicts together the sea-ice velocities, concentration, thickness, and damage. Trained with more than twenty years of simulation data from neXtSIM, the model can extrapolate to previously unseen conditions, thereby exceeding the performance of baseline models.Relying on deterministic data-driven models can lead to overly smoothed predictions, caused by a loss of small-scale information. This is why the ability to perform stochastic predictions can be instrumental to the success of data-driven sea-ice models. To generate stochastic predictions with neural networks, we employ denoising diffusion models. We show that they can predict the uncertainty that remains unexplained by deterministic models. Furthermore, diffusion models can recover the information at all scales. This resolves the issues with the smoothing effects and results in sharp predictions even for longer horizons. Therefore, we see a huge potential of generative deep learning for sea-ice modelling, which can pave the way towards the use of data-driven models within coupled Earth system models.
The thermal and aqueous evolution of CM carbonaceous chondrite meteorites revealed by triple oxygen and clumped isotope compositions of their carbonates
Authors: Clog Matthieu , Lindgren Paula , Lee Martin R , Modestou Sevasti
Published: March 2024

Carbonates (calcite, aragonite, dolomite) are a minor component (often below 4 vol. %) of CM carbonaceous chondrites and formed during the aqueous alteration of their asteroidal parent bodies in the first few million years of Solar System history. The chemical and isotopic composition of these minerals are a valuable source of information on the conditions of alteration, potentially providing information on the composition and temperature of asteroidal fluids.We report the carbon triple oxygen and carbonate clumped isotope compositions of six CM chondrites (Allan Hills 83100, Cold Bokkeveld, LaPaz Icefield 031166, Lonewolf Nunataks 94101, Murchison, Scott Glacier 06043), which span a range of degrees of aqueous alteration. To avoid issues due to the brecciated nature of these meteorites, gas aliquots produced by a single acid digestion were used to measure both the clumped isotopes and the triple oxygen isotope compositions. Where both calcite and dolomite are present, stepped acid dissolution allows us to measure their isotopic compositions separately.We found that the Δ17O values range from -1 to -2.6‰, with a 0.6‰ difference between coexisting calcite and dolomite that indicates precipitation from distinct fluids. Crystallization temperatures range from 5 to 50⁰C for calcite and 75 to 100⁰C for dolomite. CM chondrites often contain several generations of carbonates with ranges in isotopic compositions that can be determined by ion probe. Because our method relies on the bulk extraction of carbonate phases, the measured values are the modes of the distributions for each meteorite, which has to be considered carefully in their interpretation. The isotopic composition of the alteration fluids can also be calculated for each meteorite and carbonate phase. We find that their δ18OvsSMOW ranges from -6.6 to +2.3‰, with no clear relationship with temperature or the δ13C of the carbonates, indicating a variety of starting isotopic compositions for the alteration fluids.The main pattern that emerges is that chondrites with a higher degree of alteration (based on their petrology) have carbonates with lower Δ17O and higher crystallization temperatures, which is consistent with a prograde reaction in a largely closed system, and with dolomite forming after calcite in our samples.
Atlantic Water warming increases melt below Northeast Greenland's last floating ice tongue
Authors: Wekerle Claudia , McPherson Rebecca , von Appen Wilken-Jon , Wang Qiang , Timmermann Ralph , Scholz Patrick , Danilov Sergey , Kanzow Torsten
Published: March 2024

Rising sea level poses a significant challenge and threat to our societies, given that coastal regions are densely populated. The Greenland ice sheet has been a major contributor to global sea level rise in the last decades, particularly its marine-terminating glaciers and their extensions into the ocean. The 79 North Glacier (79NG) features Greenland's largest floating ice tongue, stretching over 80 km in length in a 20 km wide fjord. The 79NG and its neighboring glacier, the Zachariæ Isstrøm, drain the Northeast Greenland Ice Stream which covers 12% of the Greenland Ice Sheet area. Its complete melt would lead to a 1.1-m global sea level rise. Though the extent of the 79NG has not changed significantly in recent years, observations have indicated a major thinning of its ice tongue from below.  Both ocean warming and an increase in subglacial discharge from the ice sheet induced by atmospheric warming could increase the basal melt; however, available observations alone cannot tell which of these is the main driver.In this study, we present a setup of the Finite-volumE Sea ice-Ocean Model (FESOM2.1) which explicitly resolves the ocean circulation in the cavity of the 79NG with 700 m resolution. With this novel methodology, we seamlessly connect the global and regional ocean circulation to the circulation in the cavity. Our simulation with realistic bathymetry and ice shelf geometry covers the period 1970-2021, allowing us to disentangle the drivers of the upward trend and interannual variability of basal melt. We find that ocean warming in the subsurface Atlantic Intermediate Water layer that enters the cavity below the 79NG has played a dominant role in the basal melt rate over the past 50 years. The temperature variability can be traced back across the continental shelf of Northeast Greenland to the eastern Fram Strait with a lag of 3 years, implying a predictability of the basal melt of the 79NG. In contrast, subglacial discharge has a relatively small contribution to the interannual variation of the basal melt.
Impact of Hindu Kush Himalayan snow cover change on Monsoon Circulation
Authors: Blau Manuel Tobias , Kad Pratik , Turton Jenny V. , Ha Kyung-Ja
Published: March 2024

Mountain snow cover is an integral part of our climate system that impacts ecosystems and the biosphere that rely on river systems. In recent years, the Hindu Kush-Himalayan regions have experienced a significant decline in snow cover, which is primarily attributed to global warming. However, understanding the nonlinear trends associated with these changes remains a challenge. Here, we explore the relationship between snow cover change and monsoon dynamics within the context of a changing climate, specifically examining the role of land-atmosphere interaction. The study's findings reveal a clear connection between the declining snow cover and monsoon circulation, which is explained through multiple models and grounded in mean state changes. This result highlights the crucial role of snow cover in the dynamics of monsoon.
Hydrogen and oxygen isotopes in tree-ring cellulose as indicators of source water variations
Authors: Lehmann Marco , Diao Haoyu , Holloway-Phillips Meisha , Bernhard Fabian , Meusburger Katrin , von Arx Georg , Gessler Arthur , Saurer Matthias
Published: March 2024

Although the hydrogen (δ2H) and oxygen (δ18O) isotopic signature of tree rings is dependent on the environmental water, such as precipitation and soil water that trees have taken up (i.e. “source water”), estimating the spatio-temporal origin of water sources through analysis of water stable isotopes in tree rings is not a straightforward approach. This is because 1) our knowledge on the contribution and the variability of individual isotopic fractionation steps between source water and tree rings is limited, and 2) in situ measurements that consider the seasonality of the isotopic composition of source water and cellulose synthesis are rare.Within the framework of the EU Cost Action WATSON (#CA19120 - WATer isotopeS in the critical zONe), we analyzed (1) δ2H and δ18O in tree-ring cellulose and stem sugar, (2) δ2H and δ18O in soil water at shallower (15 cm) and deeper (80 cm) depths in up to bi-weekly resolution and (3) modelled isotopic variations in precipitation, soil water, stem xylem water, and leaf water using mechanistic and process-based models for three long-term forest monitoring sites in Switzerland over 20 years. We used this data to explain intra-annual (2021-2022) and inter-annual (2003-2022) δ2H and δ18O variations in tree-ring cellulose of beech (Fagus sylvatica) and spruce (Picea abies).At the intra-annual scale, preliminary findings indicate a pronounced isotopic enrichment in the second half of the growing season and marked seasonal variations in the isotopic composition of soil water at shallower depths compared to deeper layers. However, such fluctuations were strongly dampenend in the intra-annual δ2H and δ18O variations observed in the tree-ring cellulose and stem sugars of both tree species, which may indicate the use of deeper soil water sources or scrambling of the source water isotope signal because of isotope fractionation before cellulose synthesis. In further analyses at the inter-annual scale, we will investigate how well δ2H and δ18O in tree rings can function as indicators of source water through time-window correlation analysis between water and tree-ring stable isotopes and comparisons between measured and modelled data.Our study aims to enhance models of hydrogen and oxygen isotope fractionation. This will improve the use of both elements in tree rings as innovative ecohydrological proxies for retrospectively reconstructing environmental water sources.
Modelling phytoplankton light availability under aggregation-induced buoyancy changes in the Elbe estuary from a Lagrangian Perspective
Authors: Steidle Laurin , Pein Johannes
Published: March 2024

We present a Lagrangian modelling study focusing on the loss of phytoplankton observed in the Elbe estuary, where an estimated 95% of the upstream population is lost in the dredged harbour channel before reaching the North Sea. The collapse has often been attributed to factors such as light limitation and zooplankton grazing; however these explanations lack evidence. Current Eulerian models, while producing reasonable results in predicting phytoplankton population dynamics, fall short in explaining the causes of the loss by tuning the mortality parameters to fit the observed data.A recent study by Walter et al. (2017) suggests that light limitation alone does not fully explain the phytoplankton collapse. Our study explores an alternative hypothesis. We propose that high turbidity in the estuary may increase the coagulation rate of phytoplankton with inorganic sediments. Our approach involves modelling these coagulation interactions from a Lagrangian perspective. We combine schism hydrodynamics from Pein et al (2021), suspended particle concentrations based on the SediMorph model with the Lagrangian model OceanTracker to calculate collision and coagulation frequencies based on Burd (2013). This allows us to track changes in buoyancy and investigate their effects on light availability, providing a new approach to estimate phytoplankton losses due to sinking.The poster presents our methodology and preliminary results on the potential influence of aggregation-induced sinking on phytoplankton light availability and its subsequent impact on population dynamics. This research aims to contribute to a more nuanced understanding of the factors driving phytoplankton loss in turbid estuarine systems and to refine the modelling approaches used in such ecological studies.
Seasonal prediction of solar energy resources in the United States
Authors: Yang Xiaosong , Delworth Thomas , Jia Liwei , Johnson Nathaniel , Lu Feiyu , McHugh Colleen
Published: March 2024

Solar energy plays a crucial role in the transition towards a sustainable and resilient energy future. One challenge that remains is the considerable year-to-year variation in solar energy resources. As a result, precise seasonal solar energy predictions become pivotal for effective energy system planning and operation.  This study employs GFDL’s GFDL’s Seamless System for Prediction and Earth System (SPEAR) to evaluate seasonal solar irradiance prediction across the United States.  Notably, SPEAR demonstrates high skill in predicting solar irradiance particularly in the western United States. Furthermore, we conduct an advanced predictability analysis to pinpoint the underlying physical drivers contributing to this skillful solar energy prediction.  The outcomes of this research offer substantial potential benefits to stakeholders within the energy sector by providing predictable information regarding year-to-year fluctuations in solar energy resources.
The dynamics of field soil water retention curves predicted by autoencoder neural network
Authors: Aqel Nedal , Carminati Andrea , Lehmann Peter
Published: March 2024

The matric potential plays a pivotal role in understanding of water movement, plant water availability, and mechanical stability. In lack of direct measurements, the matric potential dynamics must be deduced from soil water content values, using the soil water retention curve. This approach is of particular importance at larger scales where only the water content (but not the potential) can be deduced from satellite data. However, because the relationship between water content and matric potential in natural field soils is highly ambiguous, not unique and dynamic, the prediction of matric potential from water content data is a big challenge. This ambiguity is related to different structures controlling drainage and wetting, dynamic effects, and seasonal changes of structures controlling the water distribution. In this study we present an autoencoder neural network as a new approach to analyze the soil moisture dynamics and to predict matric potential from water content data. The autoencoder compresses the water content time series into a site-specific feature (denoted as autoencoder value, AUV) that is representative of the underlying soil moisture dynamics. The AUV can then be used as predictor of the matric potential and the highly hysteretic soil water retention curve. The approach was tested successfully for nine soil profiles in the region of Solothurn (Switzerland). Three sites were chosen to establish the connection between AUV and the ambiguous soil water retention curve using a deep neural network, that was then applied to predict the matric potential dynamics of the other six sites. This method offers the potential to (i) deduce matric potential dynamics by relying solely on soil water content measurements (including satellite data), even when strong seasonal effects challenge standard methods, and (ii) serves as a warning system for changes in soil properties and in the intricate relationship between soil water content and matric potential dynamics.
A global empirical system for probabilistic seasonal climate prediction based on generative AI and CMIP6 models 
Authors: Palma Lluís , Peraza Alejandro , Duarte Amanda , Civantos David , Materia Stefano , Nandi Arijit , Peña-Izquierdo Jesús , Tufis Mihnea , Vilella Gonzalo , Romero Laia , Soret Albert , Donat Markus
Published: March 2024

Reliable probabilistic information at the seasonal time scale is essential across various societal sectors, such as agriculture, energy, or water management. Current applications of seasonal predictions rely on General Circulation Models (GCMs) that represent dynamical processes in the atmosphere, land surface, and ocean while capturing their linear and nonlinear interactions. However, GCMs come with an inherent high computational cost. In an operational setup, they are typically run once a month and at a lower temporal and spatial resolution than the ones needed for regional applications. Moreover, GCMs suffer from significant drifts and biases and can miss relevant teleconnections, resulting in low skill for particular regions or seasons. In this context, the use of generative AI methods that can model complex nonlinear relationships can be a viable alternative for producing probabilistic predictions with low computational demand. Such models have already demonstrated their effectiveness in different domains, i.e. computer vision, natural language processing, and weather prediction. However, although requiring less computational power, these techniques still rely on big datasets in order to be efficiently trained. Under this scenario, and with sufficiently high-quality global observational datasets spanning at most 70 years, the research trend has evolved into training these models using climate model output. In this work, we build upon the work presented by Pan et al., 2022, which introduced a conditional Variational Autoencoder (cVAE) to predict global temperature and precipitation fields for the October to March season starting from July initial conditions. We adopt several pre-processing changes to account for different biases and trends across the CMIP6 models. Additionally, we explore different architecture modifications to improve the model's performance and stability. We study the benefits of our model in predicting three-month anomalies on top of the climate change trend. Finally, we compare our results with a state-of-the-art GCM (SEAS5) and a simple empirical system based on the linear regression of classical seasonal indices based on Eden et al., 2015. Pan, Baoxiang, Gemma J. Anderson, André Goncalves, Donald D. Lucas, Céline J.W. Bonfils, and Jiwoo Lee. 'Improving Seasonal Forecast Using Probabilistic Deep Learning'. Journal of Advances in Modeling Earth Systems 14, no. 3 (1 March 2022). https://doi.org/10.1029/2021MS002766.Eden, J. M., G. J. van Oldenborgh, E. Hawkins, and E. B. Suckling. 'A Global Empirical System for Probabilistic Seasonal Climate Prediction'. Geoscientific Model Development 8, no. 12 (11 December 2015): 3947–73. https://doi.org/10.5194/gmd-8-3947-2015.
Communicating the KNMI’23 Climate Scenarios for the Dutch Caribbean  
Authors: Keizer Iris , Bloemendaal Nadia , Siegmund Peter , Haarsma Rein
Published: March 2024

We share insights from the communication efforts surrounding the KNMI`23 climate scenarios for the Dutch Caribbean islands of Bonaire, Sint Eustatius, and Saba (the BES islands). The scenarios were published by the Royal Netherlands Meteorological Institute (KNMI) in October 2023. We focus on the approach used, lessons learned, and insights gained. We communicate our scenarios through various approaches, including a report aimed at the general public, active engagement with stakeholders, end-users, policy and decision makers, and local communities through presentations, workshops, and discussions. These interactions aim to increase awareness, understanding, and cooperation. We aim to provide valuable insights for policy and decision makers and scientists across disciplines. As a government institute, we are committed to conducting policy-relevant research that supports the development of climate plans tailored to each BES island. This presentation examines the challenges, successes and lessons learned from our communication initiatives.
Structural Complexity Revealed by Frictional Afterslip Models and InSAR Observations Following the 2017 Mw 7.3 Sarpol- e Zahab (Iran-Iraq) Earthquake: Insights from Numerical Modeling
Authors: Guo Zelong , Motagh Mahdi , Baes Marzieh
Published: March 2024

The fault structures of the 12 November 2017 Sarpol-e Zahab earthquake in Iran, as inferred from geodetic and geological data, exhibit significant distinctions, indicating intricate interactions between the crystalline basement and sedimentary cover. To further investigate this phenomenon, we employ interferometric synthetic aperture radar (InSAR) observations and 2-D Finite Element Models (FEM) with various fault geometries, such as planar, ramp-flat, and splay faults, to analyze mechanical (stress-driven) afterslip models for postseismic deformation. The kinematic coseismic slip model support a planar fault dipping at 15º, which is in good agreement with previously published results. Based on the coseismic model, we vary the fault geometries and explore the relationship between afterslip fault geometries and fault friction properties. We show that the planar frictional afterslip model fails to completely explain the long-wavelength postseismic deformation field. Instead, a ramp-flat fault model explains well the majority of the postseismic observations, with a maximum afterslip of approximately 1.0 m. The friction variations after fault strengthening are estimated to be about 0.001 and 0.0002 for the up-dip and down-dip portions, respectively. Expanding on the optimal ramp-flat fault model, we introduce an additional splay fault, which further improves the model fit, although the splay fault's frictional slip was limited to less than 0.2 m, and there is a trade-off between the splay fault geometries and their friction variations. Considering our results in conjunction with relocated aftershocks and geological cross-sections, we propose that a splay fault may have been weakly triggered after the mainshock, indicating more complex fault interactions than a simple decoupling layer between the basement and sedimentary cover.
Landsat-based ET to assess illicit groundwater use: The Ica Valley, Peru
Authors: Thomas Brian
Published: March 2024

Rapid agricultural development in the Ica Valley of Peru has translated to historic and on-going unsustainable use of groundwater.  Decades of ineffective water resources management threatens the future of agricultural production, requiring an overhaul of water management decisions and actions, particularly for groundwater sustainability.  A key measure of robust groundwater management is an accurate estimate of groundwater use, particularly if groundwater use is thought to exceed regulatory abstraction limits.  In this study, remote sensing estimates of evapotranspiration are combined with precipitation and water use permit databases to quantify groundwater use that exceeds regulatory limits, termed illicit use.  We apply two energy balance approaches, METRIC and SEBAL, combined with gridded climate information to robustly quantify agricultural water use.  Our findings document that illicit groundwater use is approximately twice that of regulation abstraction rates, suggesting current management strategies are failing to mitigate unsustainable groundwater use.  The remote sensing workflow can be applied to quantify groundwater use to inform efficacy of future groundwater management decisions and aid to identify regions for future interventions.
CO2-Plume Geothermal (CPG) in Austria? Tackling the CCS dilemma
Authors: Kulich Jakob , Onishi Tsubasa , Saar Martin O. , Ott Holger
Published: March 2024

Austria is committed to becoming climate net-neutral by 2040, no later than 2050. Reducing the country’s hard-to-abate Carbon Dioxide (CO2) emissions will require substantial deployments of CO2 Capture Utilization and Sequestration (CCUS) to reach this challenging goal. Due to legal regulation and missing public acceptance across Europe, CO2 sequestration sites for CCUS hubs are typically being developed offshore. This is especially challenging for inland countries, such as Austria, where domestic CO2 sequestration is currently not in development and export of CO2 can only take off once CO2 transport infrastructure is completed. At the same time, geothermal energy production is seen as a key technology to provide green base-load energy to decarbonize the heating sector in cities with huge district heating networks. Utilizing CO2 as the subsurface energy extraction working fluid in future geothermal projects, called CO2-Plume Geothermal (CPG), can contribute to both storing hard-to-abate CO2 emissions until proper transport infrastructures across Europe have been developed and complementing the development of geothermal energy production. In this work, we assess the Austrian potential for using CO2 as the geothermal working fluid in depleted hydrocarbon fields. We screened 59 hydrocarbon reservoirs in Austria to assess their CCS and CPG suitability. Furthermore, we distinguish between hydrocarbon fields, suitable for heat and/or electricity production, and compute the levelized cost of energy (LCOE) production as well as the potential net energy produced by CPG. While Austria’s CO2 sequestration capacities in depleted hydrocarbon reservoirs are small, compared to saline formations in offshore Europe, developing national onshore CO2 storage sites can bridge crucial periods until the CO2 can be shipped offshore, promoting the country’s climate goals. We believe that adding CPG to CCS, resulting in CCUS, increases the acceptance of CCS in general and in particular in onshore countries. Additionally, cooling the CO2 due to energy extraction, i.e. reducing the reservoir temperature, increases the reservoir’s CO2 sequestration/storage capacity and is expected to decrease CO2 injection risks by controlling/reducing the pore-fluid pressure in the CCS/CPG reservoir.
A comparison of exfoliation joint formation mechanisms: what is the role of surface processes?
Authors: Reynolds Aislin , Lang Karl , Arson Chloé
Published: March 2024

The formation of granitic domes via exfoliation jointing produces some of the most celebrated and hazardous landforms on Earth. In 1904, G.K. Gilbert outlined three mechanisms to explain exfoliation jointing as: (1) related to the original cooling of the rock body, (2) related to decompression of the rock body as it is exhumed to the surface of the Earth, or (3) related to processes at Earth’s surface - a hypothesis recently supported by observations of thermal cycling in crack initiation and propagation. Despite more than a century of study, our understanding of the mechanisms driving exfoliation jointing remains incomplete. This research seeks to address the question: is the formation of exfoliation joints more sensitive to surface processes (e.g., biotite weathering, thermal cycling), topographic, or regional (i.e. tectonic) stresses? To test this hypothesis, we predicted the orientation of fractures subject to variable geologic conditions with a multi-scale weathering model of damage and fracture propagation implemented in the finite element method. We present predictions resulting from thermal contraction during cooling of the rock body, depressurization during rock exhumation, and regional tectonic compression. We then compare fractures generated under variable topographic stresses, surface weathering processes, and rock geochemistry (i.e., biotite fraction and orientation). By improving our understanding of how significantly pre-existing geologic conditions and rock fabrics influence fracturing, we can work towards disentangling this effect on observed fracture orientations and better interpret paleo-stresses for major tectonic events or potentially paleo-topography. Additionally, enhancing models for weathering mechanics and fracturing in granitic bodies may reveal sensitivities to changes in climate and critical zone evolution, with implications for the forecasting of rockfall hazards in relation to projected temperature and climatic changes.