bluuebunny/crossref_metadata_2025 huggingface dataset:
Can we parameterise Subsurface Stormflow in a conceptual simulation model using flow duration curve percentiles for calibration?
Authors: Leins Tamara , Späth Nikolai , Reinhardt-Imjela Christian , Hartmann Andreas
Published: March 2024

Subsurface stormflow (SSF) is an important runoff-generation process, especially in humid, mountainous regions. It can play a major role in flood generation and contaminant transport at the catchment scale. However, as it is a subsurface and heterogeneous process, its monitoring can be very challenging. In turn, the identification of SSF parameters in hydrological models is a difficult task and is often affected by equifinality.  Our study uses the HBV-light model, a conceptual model at the catchment scale, to simulate SSF (and catchment discharge) at a catchment in the Ore Mountains in Saxony, Germany. To see whether it is possible to improve the identifiability of SSF parameters by looking at different flow conditions separately, we divide discharge data according to flow duration curve (FDC) percentiles. We then calibrate the conceptual model several times, each time using only discharge data within one percentile of the FDC. Using a Monte Carlo based calibration, we select the same number of behavioural parameter sets for every FDC percentile based on the Kling-Gupta-Efficiency as an objective function. With a regional sensitivity analysis as well as a GLUE uncertainty estimation, we analyse and compare the parameter sets and discharge simulations of the different percentile calibrations. In this way, we analyse whether there is more information content on SSF hidden in a specific part of the FDC and thus, SSF parameters and processes become better quantifiable.
Accounting for spatial variability when combining fluxes and proximal sensing techniques.
Authors: Julitta Tommaso , Burkart Andreas , Bower Sam , Metzger Stefan
Published: March 2024

The continuous observation of ecosystems fluxes between the biosphere and atmosphere provides a much-needed foundation for effective real-world management of our geo-ecological life support systems. Over a thousand flux measurement sites globally use sophisticated eddy-covariance (EC) instruments and are organized in international monitoring networks, e.g. FLUXNET, NEON, ICOS. The integration of automated spectrometers measuring irradiance, reflectance and sun-induced chlorophyll fluorescence (SIF) adds valuable optical proxies for photosynthesis and carbon fixation at top-of-canopy level:  field spectroscopy provides  a powerful tool for understanding measurements of plant carbon uptake, thus providing a link between fluxes and satellite remote sensing and enabling local information to be scaled up to the globe. In the last years many efforts have been made for merging these two types of measurements. Nevertheless, when combining these two sources of information one major limitation is to match the different areas seen by the EC flux measurements and field spectroscopy. Typically the proximal sensing instruments have a fixed field of view (FOV) which limits the measured area to a portion of the underlying canopy. The FOV depends on the set up defined and can vary between a few degrees and 180 degrees, and, alongside the mounting height, determines the size of the monitored area. On the contrary, classical EC flux measurements provide data that typically refer to a larger and variable FOV, also referred to as footprint. The footprint of EC data varies spatially according to meteorological conditions, so – unless a site is perfectly homogenous – the comparison between proximal sensing and EC is always flawed by the footprint mismatch. Additionally, the results of a classical EC time series are difficult to attribute to individual sources and sinks within an upwind source area due to spatial aggregation. Recently the FluxMapper EC approach has been shown to transcribe high-frequency temporal information onto half-hourly Flux Maps around the tower which resolve fluxes spatially through signal disaggregation. Analogous to the proximal sensing techniques, the spatial resolution of the Flux Map depends on the sensor distance from the canopy. In this contribution, for the first time, we provide preliminary results of combining field spectroscopy techniques and Flux Mapper EC, and evaluate spatial heterogeneity effects on the interpretability relative to classical EC. Broader impacts include cost-effective measurement, reporting, and verification of nature-based and technological climate solutions in support of the Glasgow Climate Pact and the Dubai Climate Summit net-zero commitments.
Exploring cloud fraction adjustments in the South Pacific marine stratocumulus cloud deck using 3 years of GOES 16 retrievals
Authors: Vieira Fischer Frederik , Possner Anna
Published: March 2024

Marine stratocumulus clouds contribute a significant cooling effect to the Earth's climate, but their role in global climate change hasn't been well quantified. Aerosols from anthropogenic and natural sources alter the characteristics of stratocumulus clouds, although the extend of all cloud adjustments is not yet fully quantified. In particular the cloud fraction adjustment is associated with potentially large radiative forcings, but also high uncertainties.We used cloud retrievals from the GOES-East satellite to explore cloud fraction adjustments in raining stratocumuli structures, and MERRA-2 aerosol reanalysis data as a proxy for the aerosol-dependent cloud droplet size.We found that increases in aerosol loading coincide with both increases and decreases in cloud fraction relative to the climatological mean. Decreases in aerosol loading coincide with increases in the fraction of optically thin cloud features which were calculated for various maximum thresholds of optical depth.For cloud covers with cloud fractions and optically thin cloud areas close to the climatological mean, increased aerosol loading tends to coincide with increases in both of these properties. This is not the case for cloud covers that differ significantly from the climatological mean.A better understanding of the link between how cloud fraction and optical density respond to aerosol loading could help to improve our knowledge of the effects of aerosols on the radiative properties of stratocumuli.
Mantle hydration and implications for Earth and exoplanetary research
Authors: Moccetti Bardi Nickolas , Tackley Paul J. , Metternich Marla A.
Published: March 2024

So far, most numerical models focused on understanding different aspects of the Earth’s system, such as mantle convection, tectonics, or atmospheric dynamics, have typically adopted a limited perspective constrained to the specific region of interest. Recently, efforts have been made to couple these simulations, enabling them to interact seamlessly with one another. Abstaining from doing so may lead to results that don't accurately represent how the various systems interact.Achieving the successful integration of the deep carbon cycle and water transport into our mantle dynamics code (StagYY) represents a crucial step towards this goal - a comprehensive, large-scale model of our planet, encompassing phenomena from the Earth's core to the uppermost layers of the atmosphere resulting from a collaborative effort between different research groups. We adopt a thermodynamic approach to quantify the H2O solubility of important water-carrying minerals within the mantle, with the goal of faithfully coupling geodynamic models and realistic transport/incorporation of water across the silicate part of our planet. The details of the numerical implementation are yet the subject of ongoing discussion; however, several crucial considerations must be thoroughly evaluated. These include the assessment of density variations resulting from water integration into nominally anhydrous minerals, the complex multi-stage degassing process of subducting slabs, and the inclusion of exotic phases that are currently absent from the thermodynamic databases being utilized.The anticipated effects of a water-bearing mantle on the overarching dynamics are still under investigation. Nevertheless in-gassing, degassing, and the internal transport of water within the mantle exert a direct influence on various aspects. These include the governing viscosity field, the extent of H2O-induced melting, and atmospheric CO2 concentrations, among others. If water can, in fact, permeate deep into the mantle, it has the potential to introduce significant deviations in the dynamics of lower mantle convection compared to what current models predict. Furthermore, recent considerations of the stability regime of hydrous phases also point towards interesting implications in the study of water-rich exoplanets as stronger gravity profiles should result in colder geotherms, significantly expanding the thermodynamical stability of water-transporting phases across the P-T parameter space.Quantifying this process will provide valuable insights for the geodynamic modeling community and help advance our understanding of the deep-Earth system. Furthermore, the distinct chemical exchange dynamics arising from our applications can be investigated further and prove advantageous for the study of exoplanetary atmospheres, especially those around bodies characterized by abundant water, such as water worlds and hycean planets.
Dynamics of large-scale THM simulations: numerical considerations for the simulation of nuclear waste repositories in rock salt during glacial cycles
Authors: Zill Florian , Meisel Tobias , Silbermann Christian B. , Nagel Thomas
Published: March 2024

This study addresses the coupled thermo-hydro-mechanical (THM) modelling of large-scale nuclear waste repositories situated in rock salt. We consider the competing stability requirements arising from different physical processes, such as advection and diffusion in the rock mass surrounding the saline barrier, as well as viscoplastic creep of the latter. Our focus extends to examining potential conflicts between spatial and temporal discretization demands, balancing performance, stability and accuracy. We systematically investigate the applicability of these considerations to a model implemented in OpenGeoSys, aiming to enhance its robustness. An essential aspect of evaluating simulation results is analyzing the convergence behavior in the absence of an analytical solution. Several methods exist to extrapolate model results of different discretization to a reference set, such as the Richardson extrapolation. Here, we use such a technique to scrutinize our results, providing a comprehensive assessment of the model's convergence characteristics and the accuracy of the results.Finally, detailed comparisons across various coupling schemes are conducted for our model, highlighting the impact of implicit process coupling on the model results.
Two Methods for Constraining Neural Differential Equations
Authors: White Alistair , Kilbertus Niki , Gelbrecht Maximilian , Boers Niklas
Published: March 2024

Neural differential equations (NDEs) provide a powerful and general framework for interfacing machine learning with numerical modeling. However, constraining NDE solutions to obey known physical priors, such as conservation laws or restrictions on the allowed state of the system, has been a challenging problem in general. We present stabilized NDEs (SNDEs) [1], the first method for imposing arbitrary explicit constraints in NDE models. Alongside robust theoretical guarantees, we demonstrate the effectiveness of SNDEs across a variety of settings and using diverse classes of constraints. In particular, SNDEs exhibit vastly improved generalization and stability compared to unconstrained baselines. Building on this work, we also present constrained NDEs (CNDEs), a novel and complementary method with fewer hyperparameters and stricter constraints. We compare and contrast the two methods, highlighting their relative merits and offering an intuitive guide to choosing the best method for a given application.[1] Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers. Stabilized neural differential equations for learning dynamics with explicit constraints. In Advances in Neural Information Processing Systems, 2023.
Transient aseismic vertical deformation during the interseismic cycle across the Pisia-Skinos normal fault (Gulf of Corinth, Greece)
Authors: Mildon Zoe , Diercks Manuel , Roberts Gerald , Faure Walker Joanna , Ganas Athanassios , Papanikolaou Ioannis , Sakas Vassilis , Robertson Jennifer , Sgambato Claudia , Mitchell Sam
Published: March 2024

Loading and deformation during the interseismic period of the earthquake cycle is often considered to be constant for continental faults, therefore assuming that the short-term (annual-decadal) deformation is representative of longer-term deformation. Based on this assumption, geodetically-derived deformation rates are sometimes used to infer the slip-rates and thus seismic hazard of faults. However geological observations indicate that deformation and slip rates are variable over a range of timescales, and we present an observation of variable deformation across an active normal fault occurring on an annual timescale. The Pisia-Skinos normal fault in the Gulf of Corinth, Greece, is a well-known fault which slipped most recently during a sequence of damaging earthquakes in 1981. Using vertical deformation data, available from the European Ground Motion Service (EGMS), we observe uplift/subsidence of the footwall/hangingwall of the Pisia fault between 2016-2021. Of particular interest is our observation that the deformation is not uniform over the 6 year time period, instead there is an up to 7-fold increase in the vertical deformation rate in mid-2019. We hypothesise that this deformation is aseismic as there is no temporally correlated increase in the earthquake activity (M>1). We explore four possible causative mechanisms  for observed deformation; shallow slip, post-seismic after-slip, deep slip on an underlying shear zone, and post-seismic visco-elastic rebound. Our preferred hypothesis is that the transient deformation is caused by centimetre-scale slip in the upper 5km of the Pisia fault zone, based on the magnitude and spatial extent of the deformation. Our results suggest that continental normal faults can exhibit variable deformation over shorter timescales than previously observed, implying that the interseismic period of the earthquake cycle on continental faults may be more variable than previously hypothesised. This also highlights potential pitfalls of using slip rates measured over short-timescales to infer seismic hazard.
Unraveling the moisture transport in the North Atlantic trade-wind region using passive tracers and stable water isotopes
Authors: Botsyun Svetlana , Pfahl Stephan , Aemisegger Franziska , Villiger Leonie , Kirchner Ingo
Published: March 2024

The atmospheric hydrologic cycle and the formation of shallow cumulus clouds in the marine trade-wind region are important for the Earth’s radiative budget and climate sensitivity. Furthermore, the understanding of air mixing and transport processes in the atmosphere is crucial for interpreting measurements and records of stable water isotopes. However, the representation of these processes in climate models is subject to large uncertainties. Here we investigate moisture transport and its impact on the isotopic signature in the North Atlantic trade-wind region. We use the regional COSMO model equipped with stable water isotopes and passive water tracers to quantify the contributions of the different evaporation sources to moisture contents and their isotope signals in the free troposphere of the western tropical Atlantic. For the time period of the EUREC4A field campaign (January-February 2020), convection-resolving high-resolution (5 km) nudged simulations are performed, allowing a comparison with field data. Passive tracers (water tagging) are combined with prognostic water isotope simulations to determine the specific isotopic fingerprints of the diagnosed moisture pathways. In January and February 2020, the tropical Atlantic region is characterized by alternating large-scale circulation regimes with distinct isotopic signatures. Humid conditions in the middle troposphere (300-650 hPa) over the island of Barbados are related to easterly and south-easterly moisture transport, while dry conditions correspond to extratropical transport from the north and west. Our modeling approach, together with the unprecedented observational data from the EUREC4A campaign, offers exciting new opportunities to evaluate and ultimately improve the representation of the tropical water cycle in climate models.
Enhancing Renewable Energy Forecasting: A Comprehensive Evaluation of Weather Forecast Models and Post-Processing Methods for Belgium
Authors: Meng Ruoke , Van Poecke Aaron , Smet Geert , Demaeyer Jonathan , Tabari Hossein , Hellinckx Peter , Van den Bergh Joris , Termonia Piet
Published: March 2024

As renewable energy sources continue to account for an increasing proportion of Belgium's energy production, decision making in renewable energy production increasingly relies on accurate numerical weather prediction forecasts. For general applications, forecast validation often focuses on direct comparisons to observations for the whole domains of interest, while in this study we assess model performance specifically related to renewable energy productions. We perform extended verification of relevant variables (wind speed, temperature, solar radiation, etc.) from multiple high-resolution deterministic and ensemble weather forecast models operated in Belgium for the period of May 2021 - June 2023. The forecasts are verified with observational datasets collected from on- and offshore weather stations, masts, lidars, and wind farm observations to comprehensively understand the capabilities of the models, making use of various deterministic and probabilistic skill scores. The results show that during lead times up to two days, although verification metrics differ among models, there are systematic errors in their forecasts for different observation sites. Such errors can often be eliminated by post-processing techniques. Therefore, we extend our verification dataset, with post-processed forecasts corrected by several methods including member-by-member and AI-based approaches. The results of this work will lead to an enhanced understanding of current forecasting skills of the operational models, help to evaluate the effectiveness of goal-oriented post-processing methods, and provide a reference for Belgian sustainable energy stakeholders.
A new method for weekly sub-kilometer mapping of deep snow in mountainous regions using ICESat-2 and Sentinel-
Authors: Meyer Rasmus , Schødt Mathias , Rasmussen Mikkel Lydholm , Andersen Jonas Kvist , Bjørk Anders Anker
Published: March 2024

The following abstract is based on a master thesis project in Geography from University of Copenhagen. It relies on freely available satellite data and uses Google Earth Engine and python for large scale analysis of deep snow in the Southern Scandinavian Mountains of Norway.Knowledge about seasonal snow accumulation is key for managing water resources, especially in mountainous regions. However, accurate measurements of snow depth or SWE at a high spatiotemporal resolution are sparse. In this study, we investigate the effectiveness of a multi-satellite approach to mapping the depth of large-scale deep snow in the Southern Scandinavian Mountains of Norway. First, snow depths are measured using geolocated photons from the ICESat-2 satellite. These snow depths are matched spatio-temporally with the nearest Sentinel-1 scene, where an index based on the ratio between VV and VH polarization has been proven to be correlating partially with snow depth. Using a simple regression analysis, we model this relationship using a new sampling method, to further investigate the relationship between Sentinel-1 index and snow depths. The model is used to predict snow depths at 500m resolution every 6/12 days. When compared to in situ measurements from weather stations within the study area, our model has an RMSE of 36 cm.
Building an agent-based model to assess multi-risk caused by climate change in coastal areas: the case study of the Jesolo municipality (Italy)
Authors: Dal Barco Maria Katherina , Vascon Sebastiano , Torresan Silvia , Critto Andrea
Published: March 2024

Over the past three decades, the global climate has experienced a significant and unprecedented increase of temperature, leading to the occurrence of many extreme events worldwide. Coastal areas are particularly vulnerable to the impacts of climate change, due to the high population density, interconnected economic activities and the presence of fragile habitats and ecosystems. The interactions between multiple hazards, acting at different temporal and spatial scales, can amplify the effects on dynamic vulnerability and exposure patterns.In order to address these complex challenges, an integrated approach becomes crucial, considering the relationships among all risk factors (hazard, exposure, and vulnerability) at the land-sea interface.Agent-based model (ABM) approaches are able to simulate the interactions between different individuals, households or communities, playing a vital role in the analysis of their responses to environmental hazards (e.g., sea-level rise, heavy precipitation, extreme wind) and adaptation strategies (e.g., beach nourishment, nature-based solutions).Here we present the development of a local-scale ABM to assess coastal risks caused by climate change on various sectors, such as local communities, tourism, and ecosystems. In particular, the model aims at exploring the interactions among atmospheric and marine hazards (e.g., sea-level rise, extreme precipitation, and wind), exposure and vulnerability factors (e.g., land-use, population) to simulate coastal risks for the municipality of Jesolo (Italy). The ABM will be trained with local-scale records over the 2009-2020 baseline timeframe, and then used to project future climate risk until 2100, under the climate change scenarios (e.g., RCP2.6, 4.5, and 8.5), as well as the potential effect induced by different coastal protection measures and nature-based adaptation strategies (e.g., beach nourishment, groins).The resulting outcomes could represent a valuable tool to inform stakeholders and decision-makers on climate change adaptation, in line with EU, national and local adaptation strategies. Furthermore, they can be used to improve disaster risk preparedness as well as raise awareness in local communities.
Volatile degassing at Stromboli Volcano: Continuous soil CO2 fluxes monitoring network and soils discrete measurements. Volcanic implications
Authors: Vita Fabio , Inguaggiato Claudio , Mazot Agnes , Corrao Marco , Cangemi Marianna , Inguaggiato Salvatore
Published: March 2024

The Stromboli volcano, Aeolian Islands, Italy, is characterized by persistent Strombolian activity. It is a perfect case study to investigate the relationship between outgassing activity and paroxysmal events.The discrete soil CO2 degassing measurements, performed with the portable flux meter based on the accumulation chamber method, were carried out in the summit and peripheral zones. These measurements surveys allowed us to individuate the anomalous degassing areas (Scari, Piscità, and Pizzo Sopra La Fossa), coincident with the main structural faults respectively N64° and N41° as preferential paths for the rising of deep fluids.Based on the information resulting from the discrete measurements a near-continuous (hourly frequency) geochemical network was installed on Stromboli Island and consists of three stations, one located in the summit part of the Pizzo Sopra La Fossa area (STR02), and two located in the peripheral zone STR01 and STR03 in the Scari and Piscità areas respectively. This network allowed us to acquire a large amount of soil CO2 flux data to investigate and model the plumbing volcanic system. The analysis of a large dataset of soil CO2 fluxes collected in the summit crater area (STR02), from 2000 to 2023, showed significant changes in degassing values and style before and in coincidence with major volcanic events like paroxysmal explosions caused by the rapid rise of volatile-rich magma and the changes from explosive to effusive eruptions. In particular, the soil degassing processes of CO2 peaks showed three main and peculiar behaviors:A long-lasting modification, characterized by a slow and continuous increase in CO2 flux;
Transient changes, characterized by abrupt changes in the rate of CO2 outgassing;
Strong Increase in the Natural Daily Variation, highlighting drastic changes in the degassing style, a few months before the major paroxysmal events.
Designing and delivering user-driven products and services through Copernicus Marine Service 
Authors: Giunta Valentina , Derval Corinne , Crosnier Laurence , Lux Muriel
Published: March 2024

The Copernicus Marine Service is one of the six pillar services of the Copernicus program. It follows a user-driven process by taking into consideration user feedback to consistently improve its portfolio of products and services. Mercator Ocean International (here MOi) is entrusted by the European Union to implement the Copernicus Marine Service over the 2021-2027 period. Consequently, MOi is maintaining a permanent dialogue with users to collect their requirements and support them in the use of the service. Public Core users, such as policy stakeholders and regional sea conventions, are the main target, but Copernicus Marine Service is open to all communities (Core and non-Core users). Thus, MOi manages and analyses feedback from all users on the current service and their requirements for the service evolution. The user feedback process is dynamic and constantly evolving to target specific audiences and expertise. Currently, user needs are being collected through diverse channels and sources, such as through the User Support team, but also through training and surveys. To plan the service evolution, feedback from groups with specific expertise is needed to help fill the gap in what is being offered and to improve the data quality. As an example of these target audiences, the Champion User Advisory Group (CUAG), formed by active users of Copernicus Marine Service, and the National Marine Stakeholders Group, formed by member states, were consolidated. These groups allow regular interactions and communication among expert users and policymakers, which have been proven to be resourceful sources of feedback that help towards better services and data products. Among the main needs expressed by users, increasing spatial and temporal resolution of global models and reanalysis products, having longer ocean forecasts, and improving quality data are the top priorities.  With the added value of feasibility studies, these inputs are considered and evaluated internally and discussed with the producer's centers to ensure that the planned roadmap is aligned with the user requirements. Additionally, knowledge gaps and cutting-edge scientific developments are identified to plan the service evolution activities in the short, intermediate, and long term to better serve marine policy implementation and scientific research. In conclusion, the goal of this user-driven approach is to give Copernicus Marine Service the capacity to effectively answer users’ needs on ocean monitoring and forecasting at European and global levels. 
Infrasound signals generated by production blasts in a nearby quarry
Authors: Mitterbauer Ulrike , Brückl Ewald , Carniel Peter , Mertl Stefan
Published: March 2024

The mobile Infrasound Array ISCO of the Austrian National Data Center at GeoSphere Austria is a part of the Central and Eastern European Infrasound Network (CEEIN). It was installed early 2021 at the Trafelberg, with the premises of the Conrad Observatory in Lower Austria. In 2022 and 2023 a multitude of signals caused by production blasts of a quarry in a distance of 16 km to the array were detected at the station ISCO. Approximately 20 signals were selected, analyzed and compared not only with the data of the seismic station CONA at the Conrad Observatory but also with the recordings of the Macro Seismic Sensor Network, a local low cost sensor network. Blasting parameters were provided by the operator. In addition, video recordings for the blast process and photogrammetric surveys of the blasted rock mass are available for selected events. This data provides information about the source mechanism for the recorded infrasound signals. Analysis of waveform showed that envelopes of the investigated signals are bell-shaped. Values of peak-to-peak amplitudes range between 0.16 and 0.38 Pascal, the half widths of the envelopes vary from 1 to 3 seconds and the frequency range covers 0.25 to 6.35 Hertz. Products of the peak-to-peak amplitudes and half widths show a significant correlation (R2 = 0.6) with the total explosive charge of the blasts.Data assessment indicates that the change of rock volume caused by the explosion generates the infrasound signal. The videos of the blasting process show an initial expansion of the blasted rock mass, followed by the deposition in front of the blasting area. We interpret the primary increase of volume and the subsequent compaction during the deposition as the source mechanism of the infrasound signal. Numerical modelling of the volume changes during the overall blasting process allows for the calculation of the infrasound source and Green’s functions.
Operationalising ecological resilience
Authors: Corstanje Ronald , Toumasis Nikolaos , Stojanovic Marko , Simms Daniel , Harris JIm , White John
Published: March 2024

Given the increasing pressures and perturbations on ecosystem due to climatic variability, there has been a developing interest in determining the resilience of ecosystems, particularly given the potential of abrupt and possibly irreversible shifts between alternative ecosystem states. There are numerous conceptual definitions of resilience in environmental systems and, even when resilience is clearly described for a particular ecosystem, it can challenging to quantify a priori to a state change in the ecosystem of interest. Ecosystems that approach transition exhibit generic changes in dynamical behaviour that can be used to signal the approach of a critical transition. When an ecosystem approaches a critical transition, its dynamics “slowdown”, and start exhibiting properties associated to the process critical slowing down (CSD), such as increased recovery time, variance, and autocorrelation. Here we develop a set of analytical methods based on measures of variance and autocorrelation to determine the current state of ecosystem and their likelihood to be at CSD, so to demonstrate how to operationalise what to date has been developed as a theoretical framework. We use wavelets as a measure of identifying changes in the variance term, and autocorrelation was modelled using an Bayesian dynamic linear model. We illustrate this on three case studies; i) on an experimental soil system subjected to dry wet cycles; ii) on an intensely managed ecological system in the Everglades and iii) on extensively managed grassland systems in the UK. We illustrate that although any of the resilience characteristics can be used to define resilience, the identified properties of a resilient response must be described for different contexts.
SoilMoist: A global network of soil moisture observations based on emerging low-cost technologies.
Authors: Lekarkar Katoria Lesaalon , Lembrechts Jonas , Dondeyne Stefaan , van Griensven Ann
Published: March 2024

Soil moisture plays a crucial role in the earth's system cycle by connecting the water, energy, and carbon cycles. It actively influences hydrological processes and affects the occurrence of climate-related hazards, such as droughts, heatwaves, and wildfires.This places soil moisture at the centre of agro- and biometeorological monitoring and forecasting. Despite its crucial role, the global network of soil moisture observations remains the least developed among the major land-based components of the hydrological cycle, with strong regional imbalances in coverage. Remote sensing products provide spatially and time-continuous alternatives to in-situ soil moisture data. However, these products remain coarse in spatial resolution and the lack of in-situ validation data in data-scarce regions such as Africa undermines the application of such products.The emergence of low-cost technologies has enabled the deployment of monitoring networks that provide large spatial coverage at a fraction of the cost of traditional monitoring networks, offering unique opportunities to upscale coverage and address data scarcity. One such device is the TMS-4 logger from TOMST which has found wide application globally due to its robustness, high temporal resolution, large data storage, and long battery life, guaranteeing independent data collection over an extended period. TMS loggers also offer the advantage that a large amount of georeferenced timeseries data from these devices has already been compiled into the global SoilTemp-database (a database currently largely focused on temperature data). The available timeseries of observations from these devices already covers all the continents (including Antarctica) and comprise observations from close to 10,000 locations that are currently hosted within SoilTemp, with ongoing deployment in at least 9 African countries. Our mission is thus firstly, to consolidate this data as submitted in its raw form to the SoilTemp database, adequately calibrate it, and ultimately avail it as an open-access resource. This global coordination and standardization offer the opportunity to integrate this data into the existing global database of soil moisture monitoring (the International Soil Moisture Network). Secondly, we aim to increase global coverage of soil moisture monitoring using the low-cost TOMST TMS-4, and further facilitate its use by non-scientists in citizen science projects across the globe. The result of this initiative should be a drastic increase in the global coverage of soil moisture data, especially in data-scarce areas such as Africa, which would provide an indispensable resource for validating satellite products, improving drought monitoring, and countless other environmental applications.
Modelling Water and Biodiversity: Coupling a dynamic eco-evolution trait-based vegetation model with a community water model 
Authors: Stefaniak Elisa , de Bruijn Jens , Smilovic Mikhail , Artuso Silvia , Martin Juliette , Maxwell Tania , Joshi Jaideep , Hofhansl Florian
Published: March 2024

The recently developed Plant-FATE (Plant Functional Acclimation and Trait Evolution) model is a trait-size-structured eco-evolutionary population model derived from the ‘Plant’ model. It includes a McKendrick-von Foerster partial differential equation (PDE) describing how the size distribution of each species evolves through time. The trait structure allows for modelling functional diversity and adaptations, whereas size structure allows for modelling competition for light. Plant-FATE also includes a new P-hydro model for optimal photosynthesis, the ‘perfect plasticity approximation’ for modelling optimal crown placement, and an extended version of the T-model for biomass allocation. Forced with climatic variables and soil-water availability, Plant-FATE can predict emergent species compositions, size-distributions, and ecosystem services such as leaf area, productivity, evapotranspiration, living biomass, and seed output. 

Plant-FATE currently predicts vegetation properties and associated ecosystem functions of areas under forest cover. To analyse the -water-biodiversity nexus, it is necessary to cover additional aspects of areas under different land-use, such as croplands, plantations, and urban areas. To that end, we have coupled PlantFATE with a Community Water Model (CWatM) that captures ground water discharge and simulates basin-wide water circulation. CWatM is an open-source model to examine how future water demand will evolve in response to socioeconomic change and how water availability will change in response to climate.  

As a case study, we apply this coupled model to the Bhima Basin to examine the feedback between forest management and land-use. This coupling will enable us to better represent nexus issues, such as the feedback between biodiversity and ecosystem functioning that affect vegetation carbon storage and water provisioning under future land-use and projected climate change scenarios.
Copernicus POD Service – Impact of ITRF2020 Modelling Changes on Orbit and Validation Results
Authors: Muñoz de la Torre Miguel Angel , Fernández Carlos , Fernández Marc , Peter Heike , Féménias Pierre , Nogueira Lodd Carolina
Published: March 2024

The new ITRF20 includes a geocenter motion (GCM) model and seasonal station corrections, both with annual and semi-annual periods. The GCM model is recommended to be applied when processing space-geodetic observation data and the seasonal station corrections should be applied if no non-tidal modelling is applied for the station coordinates. In the case of the Copernicus Precise Orbit Determination (CPOD) Service this applies to the processing of GNSS data of the Sentinel satellites for precise orbit determination (POD) and to the processing of Satellite Laser Ranging (SLR) tracking data for validation of the estimated Sentinel orbits.The CPOD Service delivers, as part of the Ground Segment of the Copernicus Sentinel-1, -2, -3, and -6 missions, orbital products and auxiliary data files for their use in the corresponding Payload Data Ground Segment (PDGS) processing chains at ESA and EUMETSAT, and to external users through the newly available Copernicus Data Space Ecosystem (https://dataspace.copernicus.eu/). It generates routinely several types of orbital products for Sentinel-1, -2, -3 and -6: predictions, near-real time (< 10 min), short-time critical (< 1.5 days) and non-time critical (< 25 days).The POD quality control within the service is based on comparing the CPOD orbit products to orbit solutions provided by members of the accompanying Copernicus POD Quality Working Group (QWG). A combined orbit generated by CPOD from all available orbit solutions serves as reference for the comparisons. The new ITRF20 modelling opens the door to different Centre-of-Network (CoN) or Centre-of-Mass (CoM) frame realisations, so in order to avoid inconsistencies between the solutions when doing the combination and comparisons, special care must be taken.This study aims to analyse the impact of the new ITRF20 GCM model and the seasonal station corrections on the CPOD Service products. Sentinel orbit comparisons and the corresponding processing metrics are analysed when applying the GCM model or not, with a focus on the geocenter motion modelling used by the different CPOD QWG centres.In the SLR validation, station range biases are routinely estimated as part of the residuals analysis. Preliminary results reveal that the estimates of these range biases show smaller seasonal variations when applying the seasonal station corrections. Detailed analyses will be shown and discussed.
Parametrizing the number of formed ice crystals in contrails from hydrogen combustion
Authors: Zink Josef , Unterstrasser Simon
Published: March 2024

Hydrogen-powered aircraft have the potential to reduce CO2 emissions to zero. However, a significant portion of the global warming attributed to aviation arises from non-CO2 effects, including contrails. The thermodynamic state and microphysical pathways that form these contrails differ substantially between hydrogen and conventional kerosene combustion. Therefore, the overall climate impact of contrails formed by hydrogen combustion is not yet known and needs to be assessed by Global Circulation Models (GCMs). The contrail parametrization in a GCM cannot resolve the contrail formation processes. However, these early processes have a large influence on the contrail life cycle and should therefore be included in the contrail initialization of a GCM. Here, a crucial ingredient is the number of ice crystals formed during the jet phase.In this study, we present a parametrization that provides a link between the outcome of a high-resolution model and the contrail initialization in a GCM. For that, we performed contrail formation simulations with the particle-based Lagrangian Cloud Module (LCM) in a box model approach. We assume that contrail droplets and ice crystals form solely on entrained ambient aerosols. With our simulation setup, we aim to cover the entire parameter space relevant for contrail formation in the case of hydrogen combustion. This involves varying background meteorological conditions, ambient aerosol properties, and engine exit conditions, resulting in more than 20,000 simulations.The simulation results show that the number of formed ice crystals is mostly sensitive to a variation of the ambient aerosol background concentration, followed by a variation of the ambient temperature. We identify a parameter subspace where the number of ice crystals becomes almost independent of the size and chemical composition of the ambient aerosols.Furthermore, we performed simulations with two coexisting background aerosol ensembles differing in mean size and/or solubility. The simulation results show that coarse mode particles have neither a direct nor an indirect influence on the number of formed ice crystals if their number concentration is 2-3 orders of magnitude lower than that of a coexisting Aitken/accumulation mode. Furthermore, the ice crystal number from simulations with the two coexisting background aerosol ensembles can be reconstructed by a weighted mean of two single simulations, each containing only one of the two aerosol ensembles. This allows to construct a simpler parametrization still covering the case of two coexisting aerosol ensembles.We used the simulation results to train a shallow feed-forward neural network that maps the box model input parameters to the number of formed ice crystals. This neural network serves as a fit function of our simulation results, which can be implemented in a GCM for contrail initialization.This work contributes to the collaborative effort of the German Aerospace Center (DLR) and Airbus in assessing the climate impact of H2 contrails.
A data-driven reconstruction of spatially contiguous daily small catchment runoff for flood and drought monitoring in Switzerland
Authors: Kraft Basil , Aeberhard William , Schirmer Michael , Seneviratne Sonia I. , Zappa Massimilano , Gudmundsson Lukas
Published: March 2024

Runoff observations are critical for the monitoring and understanding of droughts and floods. Traditional methods for estimating runoff rely on physically-based hydrological models, which, while detailed, are often complex and computationally intensive. In contrast, recent advancements in deep learning have shown potential for more efficient and accurate runoff modeling. This study explores the efficacy of temporal neural networks for daily catchment-level runoff reconstruction in Switzerland from 1962 to 2023.Our model, based on the long short-term memory (LSTM) architecture, is optimized on 87 catchments minimally affected by human activities. It is evaluated in an 8-fold cross validation setup and demonstrates similar performance compared to PREVAH, a distributed hydrological model that is used operationally in Switzerland. Notably, our model requires only precipitation and temperature as meteorological inputs, allowing for an extended reconstruction period back to 1962, unlike PREVAH's 1980 limitation due to its dependency on additional atmospheric forcings. In terms of Kling-Gupta efficiency, our model matches PREVAH's performance, despite its reduced data needs. We evaluate the quality of our reconstruction in terms of extreme events and trends based on the available observations and in comparison to the PREVAH simulations on the national level.A key advantage of our neural network approach is its computational efficiency, enabling the reconstruction of daily runoff for 307 catchments that cover the entirety of Switzerland in under a minute on a high-performance GPU. This would facilitate real-time droughts and floods monitoring and support environmental scenario simulations. The findings underscore the potential of data-driven models in environmental monitoring and point towards future research in refining these models for broader applications in climate change impact assessments.
Improve The Simulation of Radiation Interception andDistribution of The Strip-Intercropping System by Considering The Geometric Light Transmission
Authors: Dong Liming , Zeng Wenzhi , Lei Guoqing , Ao Chang
Published: March 2024

Intercropping radiation interception model is a promising tool for quantifying the solar energy utilization in the intercropping system. However, few models have been proposed that can simulate the intercropping radiation interception accurately and with simplicity. This study proposed a new statistical model (DRT model), which enables the simulation of daily radiation distribution by considering the geometric light transmission in the intercropping system. To evaluate model performance, the radiation interception and distribution in two wheat/maize strip intercropping experiments (A and B) were simulated with the DRT model and other two statistical models, including the horizontal homogeneous canopy model (HHC model) and the Gou Fang model (GF model). Experiment A conducted in different intercropping configurations, while Experiment B was conducted in soils with different salinity levels. In both experiments, the HHC model exhibited the poorest performance (0.120<RMSE<0.172), while the DRT model obtained a higher simulation accuracy in the fraction of photosynthetically active radiation (PAR) interception, with RMSE lower by 0.008-0.022 and 0.022-0.125 than the GF and the HHC models. Especially, the DRT model showed stronger stability than the other two models under soil salinity stress, with R2 higher by 0.129-0.354 and RMSE lower by 0.011-0.094. Moreover, the DRT model demonstrated a relatively ideal simulation of the daily radiation distribution in Experiment A (0.840<R2<0.893, 0.105<RMSE<0.140) and Experiment B (0.683<R2<0.772, 0.111<RMSE<0.143), especially when the continuous canopy formed during the later crop growth stages. These results indicate the superiority of the DRT model and could improve our understanding of the radiation utilization in the intercropping system.