bluuebunny/crossref_metadata_2025 huggingface dataset:
Empirical optimal vertical localization derived from large ensembles
Authors: Necker Tobias , Griewank Philipp , Miyoshi Takemasa , Weissmann Martin
Published: February 2023

Ensemble-based estimates of error covariances suffer from limited ensemble size due to computational restrictions in data assimilation systems for numerical weather prediction. Localization of error covariances can mitigate sampling errors and is crucial for ensemble-based data assimilation. However, finding optimal localization methods, functions, or scales is challenging. We present a new approach to derive an empirical optimal localization (EOL) from a large ensemble dataset. The EOL allows for a better understanding of localization requirements and can guide toward improved localization.Our study presents EOL estimates using 40-member subsamples assuming a 1000-member ensemble covariance as truth. The EOL is derived from a 5-day training period. In the presentation, we cover both model and observation space vertical localization and discuss:
vertical error correlations and EOL estimates for different variables and settings;

the effect of the EOL compared to common localization approaches, such as distance-dependent localization with a Gaspari-Cohn function;

and vertical localization of infrared and visible satellite observations in the context of observation space localization.

Proper observation space localization of error covariances between non-local satellite observations and state space is non-trivial and still an open research question. First, we evaluate requirements for optimal localization for different variables and spectral channels. And secondly, we investigate the situation dependence of vertical localization in convection-permitting NWP simulations, which suggests an advantage of using adaptive situation-dependent localization approaches.
Heavy tail controls along the flood process cascade
Authors: Macdonald Elena , Merz Bruno , Guse Björn , Nguyen Viet Dung , Guan Xiaoxiang , Vorogushyn Sergiy
Published: February 2023

Many observed precipitation and streamflow time series show heavy tail behaviour. This means that the occurrence probability of extreme events is higher than for distributions with an exponentially receding tail. Neglecting heavy tail behaviour can therefore lead to an underestimation of rarely observed, high-impact events. Using long time series and a better understanding of the relevant process controls can help with more robust estimation of upper tail behaviour. Here, a conceptual rainfall-runoff model is used to analyse how precipitation and runoff generation characteristics affect the upper tail of flood peak distributions. Long, synthetic precipitation time series with different tail behaviour are produced by a stochastic weather generator and used as input for a rainfall-runoff model. In addition, catchment characteristics linked to a threshold process in the runoff generation are varied between model runs. The upper tail behaviour of the simulated discharge times series is characterized with the shape parameter of the generalized extreme value distribution (GEV).Our analysis shows that the rainfall distributions asymptotically govern the flood peak distributions above a certain, catchment-specific return period. Below this return period, threshold processes in the runoff generation lead to heavier tails of flood peak distributions. We conclude that, for return periods that are mostly of interest to flood risk management, runoff generation is often a more pronounced control of flood heavy tails than precipitation.
Laboratory calibration of low-energy ENA instruments for space science
Authors: Gasser Jonathan , Galli André , Wurz Peter
Published: February 2023

Imaging space plasmas via Energetic Neutral Atoms (ENA) is a widely used technique to study space plasma population ranging from the Earth’s magnetosphere all the way to the interstellar medium. Laboratory calibration against a known ENA beam source is a key element in the development and testing of spaceborne ENA imaging instruments. For ENA instruments operating at energies below about 1 keV, an ion beam source cannot be used for the instrument calibration, as ion trajectories are distorted through electromagnetic fields inside the ENA instrument whereas neutrals are not. The MEFISTO laboratory test facility at the University of Bern is well suited to carry out such ENA instrument calibrations: It provides neutral atom beams of any species from H to heavy elements at the relevant low-energy range from 3 keV down to 10 eV. MEFISTO is equipped with a large vacuum test chamber and an electron-cyclotron resonance ion source (ECRIS) for the production of a primary ion beam. Ion beam neutralization is performed with a dedicated neutralization stage via grazing scattering surface neutralization. This neutralization method introduces some uncertainty to the neutral beam energy and comes with species and energy dependent throughput.Therefore, neutral beam calibrations have been conducted against a novel Absolute Beam Monitor (ABM), which serves as a primary calibration standard in the low-energy ENA range. Calibrated neutral beam fluxes and energies have been obtained for species of interest to interstellar, heliosphere and planetary science, including H, D, He, O, Ne neutral beams. The recently upgraded 5-axis movable hexapod table in the test chamber allows for precise motion and rotation of instrument under test relative to ENA calibration beam. These measures allow us to carry out thorough ENA instrument calibrations against a well-characterized low-energy neutral atoms beam source.
Application of a highly reconfigurable surface robotic platform for freshwater plume characterization and sampling near tidewater glacier front in Arctic critical environment.
Authors: Ferretti Roberta , Aracri Simona , Bibuli Marco , Bruzzone Gabriele , Bruzzone Giorgio , Caccia Massimo , Motta Corrado , Odetti Angelo
Published: February 2023

Marine environmental observation is a broad topic that becomes crucial when considering critical environments, like the Arctic region which is particularly vulnerable to contamination due to the amplified effects of climate change in this area. The melting of tidewater glaciers, which has intensified in the last years, can generate a delivery of freshwater and suspended sediment into the fjord water. These phenomena can release contaminants that have accumulated in the ice over the past century, affecting fjords’ ecosystems. Despite the importance of these processes, there is no regular monitoring in place to precisely locate and sample freshwater outflows from glaciers and to track the environmental changes they trigger. The lack of data is, very often, a penalizing factor on the one hand to understand the processes and the phenomena that are occurring and on the other to implement possible mitigation actions for the conservation of the ecosystems. The use of autonomous robotic systems as fundamental data-gathering tools allows new perspectives and a greater understanding of glacier-melting related processes thanks to the possibility of collecting data not otherwise obtainable, with unique spatio-temporal resolutions.This contribution describes the technological enhancements to enable the use of a highly reconfigurable surface robotic platform (SWAMP ASV) as part of a data acquisition campaign that took place in July/August 2022 in cooperation with Institute of Oceanology, Polish Academy of Sciences (IO PAN), in semi-enclosed glacial bays that characterize the Hornsund fjord. Sampling were performed at three glacier fronts (Storbreen, Hornbreen and Hansbreen) with the purpose of identifying the position of the freshwater outflows, sending the robotic platform to the place where the plumes were present (otherwise not possible given the proximity to the glacier front and the significant calving activity in progress), collecting water samples for the subsequent analyses and evaluating the presence of heavy metals of anthropogenic origin, and simultaneously recording the chemical-physical and bathymetric parameters for a 3D characterization of the water masses and the environment. Preliminary results obtained from the acquired data will be discussed, together with the data management procedure implemented in a perspective of contributing to the global observation effort, also promoted by the United Nations.Acknowledgments: the authors thank Prof. Agata Zaborska (IO PAN) and the Reload project for organizing the acquisition campaign and for the logistical support in Svalbard. The authors wish to thank Mauro Giacopelli and Edoardo Spirandelli (CNR-INM) for their fundamental contribution to SWAMP design and development.
Comparison of spatio-temporal low-flow models for predicting remobilization of water pollutants
Authors: Laimighofer Johannes , Pressl Alexander , Langergraber Günter , Weigelhofer Gabriele , Laaha Gregor
Published: February 2023

Droughts are significant hydrological and environmental hazards that threaten the ecological functioning of water bodies. Low flow with increased water temperature leads to a cascade of hydrochemical processes. This is a particular cause of concern for regions like eastern Austria, where agricultural land use and the projected risk of low flows and increased water temperatures due to climate change are particularly high. Under these scenarios, nutrient release from river sediments may become the dominant factor for the water quality of Iotic ecosystems. The role of this remobilization-potential for water quality is assessed in the project DIRT based on a combination of laboratory experiments with at-site water quality monitoring and regionalized streamflow observations.Here we focus on space-time models of low flow and stream temperature, which are crucial for upscaling the remobilization potential along the river network. We present a study that compares different models for spatio-temporal low flow regionalization at the monthly scale in eastern Austria.We evaluate three different statistical models: (i) a tree-based boosting model, (ii) a simple linear regression model with 3-way interactions, and (iii) a combination of a non-linear boosting approach and Top-kriging. Our results show a very high performance for all models, with an overall R² of 0.88 and a median R² of 0.70. The best performance is reached by the combination of Top-kriging with a non-linear boosting approach. However, accuracy of the model is somewhat lower in headwater gauges, whereas non-headwater catchments are even better modeled by a simple spatio-temporal Top-kriging approach. In a next step, the model shall be integrated with laboratory experiments and water-quality monitoring to develop space-time models that can predict the remobilization of pollutants from river sediments.
Predicting coastline changes under human and climate drivers : GLOB-COAST MODEL
Authors: Amélie Arias , Rafael Almar , Vincent Regard , Sebastien Carretier , Julien Boucharel , Fabrice Papa , Marcan Graffin
Published: February 2023

A major challenge facing climate change and sea level rise is to predict coastal evolution and in particular coastal erosion, which seems likely to increase in the next century. Coastal erosion affects many regions of the world, often highly populated. In addition to natural processes, coastal erosion is closely interrelated with anthropic activities such as sea defence building or the modification of river sediment supply (e.g. river dam sediment trapping and land use changes). Several studies have already focused on predicting coastal change using more or less complex models on local scales. However, the majority of these models don't take into account one of the main components: the input of sediment from rivers. There are also difficulties in adequately representing the shoreline evolution by a partial understanding of processes and the difficulty of obtaining detailed and long-term data. We present simplified dynamic model on a global scale fed with new satellite observations of coastal ocean hydrology and morphology. The main objective of this study is to explore, thanks to this new model, future scenarios of shoreline change with the identification of potentially vulnerable hotspots. It will help in improving sustainable coastal management strategies.
Re-heating of rhyolitic leftovers in the Halle Volcanic Complex: an insight from zircon ages and composition.
Authors: Pietranik Anna , Słodczyk Elżbieta , Przybyło Arkadiusz
Published: February 2023

The Halle Volcanic Complex is composed of rhyolites interpreted as intrusive-extrusive complexes that pierced host sedimentary cover during their vertical growth. Zircon ages from several units vary from 291.7 ± 1.8 Ma to 301 ± 3 Ma suggesting the prolonged evolution of this subvolcanic-volcanic system. In this study, we sampled the Landsberg (301 ± 3 Ma) and the Petersberg (292 ± 3 Ma) laccoliths to better identify the magmatic processes involved in silicic magma formation and their duration.  Altogether seven depths have been analyzed from these two laccoliths including electron microprobe analyses of zircon and apatite and U-Pb SHRIMP dating of zircon. At the first sight, zircon is chemically similar within and between laccoliths. Additionally, SHRIMP ages are scattered over 30 Ma for each sample in Landsberg. These ages overlap with two Concordia ages obtained for the uppermost horizon (289.7±2.8 Ma) and the lowermost horizon (297.1±1.7 Ma) in the Petersberg laccolith. The ages suggest that the volcanic system was active for at least 10 Ma and similar age range is recorded in both laccoliths. The scatter of ages seems to indicate the formation of the laccoliths over a prolonged period of time with periodic reactivation of the magma chamber, but the lead loss cannot be excluded. Also, prolonged formation may indicate either younger pulses reactivating previously formed parts of the magma chamber or multiple unrelated  magma injections amalgamated separately within the system.The processes involved in the prolonged evolution of the magmatic system in Halle are evident from petrographic analyses of thin sections, where zircon can be imagined in association with other phases. Both zircon and apatite occur almost exclusively within complex glomerocrysts, an assemblage of major phases (variably altered biotite, feldspar, pyroxene). Such glomerocrysts were described in the literature and interpreted as remnants of crystal mush, probably re-mobilized at the final stage (heating episode) before laccoliths emplacement. The glomerocrysts in Petersberg and Landsberg laccoliths are similar leftovers of previous magmatic episodes, but they are special in that they contain abundant zircon and apatite. Such a picture is consistent with the evolution of magma in a long-lived magmatic system that underwent at least one reactivation. The major implication is that in some systems large proportion of zircon may represent the early stages of magma evolution, this context may be missed without detailed textural observations of zircon occurrence and associations.Acknowledgements: Christoph Breitkreuz is thanked for his constant help with our rhyolitic research. The research has been funded by the NCN research project to AP no. UMO-2017/25/B/ST10/0018
Using machine learning to emulate the hydrodynamic model for flood inundation modelling
Authors: Sasanapuri Santosh Kumar , Chadrika Thulaseedharan Dhanya , Ashwini Kumar Gosain
Published: February 2023

Floods are one of the most devastating natural disasters in the world causing loss of human lives and property across the world. These losses can be minimized by accurate prediction of floods well in advance. However, 2D hydrodynamic models which are used for flood inundation modelling require high computational time and hence are unsuitable for development of real-time flood monitoring system in most cases. Therefore, a surrogate machine learning model named XGBoost Regressor (XBGR) is developed for flood inundation modelling. The developed model overcomes the constraint of high computational time required by 2D hydrodynamic models. The XGBR is developed to predict maximum flood depth map and is evaluated with the LISFLOOD-FP hydrodynamic model. The training data for the XGBR model is generated using the LISFLOOD-FP model. The surrogate model is trained on 21 flood events, tested on 4 and validated for 1 flood event. For better development of the surrogate model, physical characteristics of the study area are considered in the form of nine indices referred here as topographic variables along with the flood characteristic variables. However, to refrain the XGBR model from overfitting and decrease the training time, a feed forward feature selection method is used to select the best predictive topographic variables. Four topographic variables are selected after which there is no significant improvement in the model was found. Number of trees and learning rate parameters of XGBR model are parameterized which are having highest impact on the model performance. Mean absolute error (MAE) and root mean square error (RMSE) are used for evaluating model accuracy. For testing period, the average MAE and RMSE are 0.433 m and 0.780 m, respectively and for the validation event MAE and RMSE are 0.595 m and 0.960 m respectively. For evaluating the accuracy of the surrogate model on flood inundation extent, F1 score is used which is the harmonic mean of precision and recall. The F1 score is 0.908 for the testing events and is 0.931 for validation events. The higher value of F1 score (>0.9) indicates good accuracy of the XGBR model when validated using the hydrodynamic model.
High resolution maps of the sub-ice platelet layer in Atka Bay from electromagnetic induction sounding
Authors: Neudert Mara , Arndt Stefanie , Schulze Markus , Hendricks Stefan , Haas Christian
Published: February 2023

We present maps of the sub-ice platelet layer (SIPL) thickness and ice volume fraction beneath the land-fast sea ice in Atka Bay adjacent to the Ekström Ice Shelf (southeastern Weddell Sea, Antarctica). The widespread SIPL beneath Antarctic fast ice is indicative of basal melt of nearby ice shelves, contributes to the sea ice mass balance and provides a unique ecological habitat. Where plumes of supercooled Ice Shelf Water (ISW) rise to the surface rapid formation of platelet ice can lead to the presence of a semi-consolidated SIPL beneath consolidated fast ice.Here we present data from extensive electromagnetic (EM) induction surveying with the multi-frequency EM sounder GEM-2 between May and December, 2022. It includes monthly survey data along a fixed transect line across Atka Bay between May and October, as well as comprehensive mapping across the entire bay in November and December. The GEM-2 surveys were supplemented by drill hole thickness measurements, ice coring and CTD profiles. A new data processing and inversion scheme was successfully applied to over 1000 km of EM profiles with a horizontal resolution of one meter. We obtained layer thicknesses of the consolidated ice plus snow layer, the SIPL, and the respective layer conductivities. The latter were used to derive SIPL ice volume fraction and an indicator for flooding at the snow-ice interface. The robustness of the method was validated by drill hole transects and CTD profiles.Our results support conclusions about the spatial variability of the ocean heat flux linked to outflow of ISW from beneath the ice shelf cavity. Temporally, we found that the end of SIPL growth and the onset of its thinning in summer can be linked to the disappearance of supercooled water in the upper water column.
Changes in snow accumulation and snow depth in Slovakia in the 1921 – 2021 period
Authors: Fasko Pavel , Markovič Ladislav , Bochníček Oliver
Published: February 2023

Warming surface temperatures have driven a substantial reduction in the extent and duration of Northern Hemisphere snow cover. Analysis of the long-term snow cover data can provide an exact picture on the climate change induces changes. Slovak Hydrometeorological Institute maintains a network of 113 precipitation measuring stations with daily observations of the snow cover depth since 1921. This paper presents analysis of the cumulative snow cover depth in the territory of Slovakia in the period 1921 - 2021. Such an approach to processing can effectively point to changes in the seasonal development of the snow cover. The results show that, in general, we observe a decrease in the snow cover, which began to become more pronounced especially in the course of the 21st century. The magnitude and speed of the detected change is significantly influenced not only by the altitude of the precipitation gauge, but also by its geographical location.
An integral way to stratigraphy – Are there global climate signals in the North Alpine Foreland Basin?
Authors: Hofmayer Felix , Hadler Boggiani Beatriz , Ćoric Stjepan , Soman Rohit , Andrade Juan David , Reichenbacher Bettina
Published: February 2023

Observed paleoenvironmental fluctuations in the North Alpine Foreland Basin, as one of the largest sedimentary archives of the Oligocene and Miocene are mainly controlled by regional factors. Global climate signals are usually less prominent than local tectonics and sedimentary input, caused by the enclosed paleogeographic setting of the Paratethys. Moreover are stratigraphic concepts still under debate, disabling a precise correlation of observed regional environmental changes to global climate patterns. In this study, a multi-proxy approach is used to achieve an accurate chronostratigraphy of regional formations and to verify whether global signals can be detected in the North Alpine Foreland Basin. Therefore, a detailed paleoenvironmental and biostratigraphic study of an 18 m-thick section of marine Miocene deposits (Neuhofen Formation) was carried out, using micropaleontology, sedimentology and geochemistry. In total 39 samples, yielding 68 foraminifera species and 47 ostracod species were processed together with 32 nannoplankton samples. Additionally, 34 ostracods and 49 benthic foraminifera were used for the analysis Oxygen and Carbon isotopes. Furthermore, 50 samples of six different sites in the Neuhofen Formation were used for statistical analyses of benthic foraminifera to assess supra-regional environmental correlations. Finally, the chronostratigraphic concept of the Neuhofen Formation was revised using magnetostratigraphic data from four sections, nannoplankton biostratigraphy and Sr-Isotope stratigraphy from previous studies as well as 3D-modelling using previous data additionally to 29 drillings. For the hypothesis that regional environmental patterns are correlating with global climate signals, environmental indices of the Neuhofen Formation (Isotopes, Diversity, Infaunalisation, Abundancy) were compared with global isotope values and Milankovic Cycles. The new stratigraphic concept of the Neuhofen Formation yielded an age of 18.1 – 17.6 Ma with a depositional time of 500,000 years. It was shown by a cluster analysis that strong faunal differences exist between the single localities, indicating separate paleoenvironments. These environmental differences are rather caused by regional factors. Occasionally, e.g. at 17.67 Ma, throughout the deposition of shallow marine sediments in the Neuhofen Formation the influence of global climate change can be inferred.
From vulnerability to vulnerabilities for a probabilistic flood displacement risk model: the case study of Fiji and Vanuatu.
Authors: Trasforini Eva , Rossi Lauro , Ponserre Sylvain , Campo Lorenzo , Libertino Andrea , Ottonelli Daria , Rudari Roberto
Published: February 2023

Floods have triggered about 166 million displacements globally since 2008, according to the Internal Displacement Monitoring Center (IDMC). Since 2008, most of the displacements triggered by floods have been localized in Asia and the Pacific and with an overall estimate of 129 million displacements. Small Island Developing States (SIDS) states bear the greatest displacement risk relative to their population size. Climate change combined with vulnerability of exposed infrastructure, and housing poses an existential threat for some Pacific islands that could see their populations move not only internally but also across borders. These magnitudes of forced movement highlight the importance of the phenomenon. In this context, we present a first attempt to estimate present and future riverine flood displacement risk at the national and sub-national level for two countries in the Pacific Ocean: Fiji and Vanuatu. This work proposes a new methodology that provides a more comprehensive assessment of vulnerability in the context of disaster displacement risk and recognizes that people’s vulnerability depends on several physical and social factors. Such elements, however, are not yet included in standard risk models because difficultly quantifiable. While quantitative approaches to disaster displacement risk assessment generally consider the likelihood of housing rendered unhabitable as a proxy for displacement, this new methodology expands this concept by taking into account different elements that may trigger displacements or may increase the susceptibility to forced movement: 1) impact on houses; 2) impact on livelihoods; 3) impact on critical facilities and services.A probabilistic risk assessment was performed at building scale in present and future climate conditions: under current climate conditions (1979-2016); under medium-term projected climate conditions (2016 - 2060); under long-term projected climate conditions (2061 – 2100). As results, displacement risk information - expressed in annual average displacement (AAD) and probable maximum displacement (PMD) - were calculated at national and subnational (NUTS2) scales, allowing for a geographic and quantitative comparison both within and between countries. The computation performed at building scale also allowed for result aggregation by sectors.The outputs of the probabilistic model  show an important role of climate change in determining future likelihood to displacement due to riverine floods in the area. Flood displacement risk is likely to double by 2060 in both countries, and under the pessimistic long-term scenarios AAD is expected to triple in Fiji and quadruple in Vanuatu. These analyses are an important step in risk awareness processes and key to pushing for risk reduction, adaptation, and management mechanisms to be put in place.  
Flood Modelling and Simulation using HEC-RAS
Authors: Khan Mohd. Usman Saeed , Abdullah Maaz , Khan Arisha Aslam
Published: February 2023

Natural disasters are one of the main causes of worry for the majority of nations because they severely harm the global economy. One of the natural disasters that occur on a global scale that seriously damages infrastructure and claims thousands of lives is flooding. Due to its geographical location, India is one of the high-risk nations that is negatively impacted by floods every year. It ranks in the top 20% of countries worldwide for the number of flood-related fatalities. A natural tragedy cannot be prevented. However, if some preventative actions were taken in advance, a sizable portion of the potential damage may be prevented. Professionals and authorities need accurate figures regarding flood depth, amount of flow, scale, and distinct datasets in order to reduce and manage the effects of such catastrophes. The management of flood risk is heavily dependent on flood modelling. One of the many software tools that assists in computing the discharge, depth, magnitude, and statistics of rivers located in high-risk flood zones is HEC-RAS (Hydrologic Engineering Centre-River Analysis System).This study employed the Purna River's 1D hydrodynamic floods modelling (50 and 100 years out) on HEC-RAS and it has been found that the great portion of populated area will be affected in future. The goal of this study is to assess the prediction power and carry out a sensitivity analysis to identify the sensitive zones. This research project would enable different flood modelling and risk zone delineation for diverse flood-affected areas in India and around the world. In places affected by flooding, these technologies can also be used to create emergency response protocols.
A probabilistic approach for detection and classification of PRV malfunctions in the water distribution network of the city of Patras in western Greece
Authors: Perdios Anastasios , Kokosalakis George , Fourniotis Nikolaos Th. , Pantzalis Demetris , Langousis Andreas
Published: February 2023

Effective management of water losses in water distribution networks (WDNs) still remains a demanding task, as the temporal and spatial variability of water resources under changing climatic conditions and the increasing needs for drinking water may lead to freshwater shortages. In this context, pressure management strategies are widely adopted in an effort to reduce the water losses in the supply and distribution parts of water networks and, consequently, deescalate their environmental footprint. Installation of pressure reducing valves (PRVs) at critical locations of WDNs plays a central role in pressure regulation strategies, as PRVs reduce the upstream pressure to a set outlet pressure (i.e., downstream of the PRV), usually referred to as set point. Perdios et al. (2022) developed a novel statistical framework and applied it to an existing pressure management area (PMA) of the city of Patras in western Greece, aiming at early detection of PRV malfunctions that may significantly influence network’s operation and the corresponding lifetime of related infrastructure. The results showed that the suggested methodology allows reliable detection of critical malfunctions at least 2 days prior to flow disruptions. Ιn this study, we calibrate and implement Perdios et al. (2022) statistical framework, using pressure data for a 4-year period from 01/Jan./2017 to 26/Nov./2020 from several important PMAs of the WDN of the city of Patras, aiming towards better understanding of the causes of the malfunctions, by decomposing the observed pressure deviations from the set point to systematic and random error components.Acknowledgements The research work has been conducted within the project PerManeNt, which has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation under the call RESEARCH – CREATE – INNOVATE (project code: T2EDK-04177).ReferencePerdios A., G. Kokosalakis, N. Th. Fourniotis, I. Karathanasi and A. Langousis (2022) Statistical framework for the detection of pressure regulation malfunctions and issuance of alerts in water distribution networks, Stoch. Env. Res. Risk Asses., https://doi.org/10.1007/s00477-022-02256-5
Decarbonising conference travel: testing a multi-hub approach
Authors: Zechlau Sabrina , Kremser Stefanie , Charlton-Perez Andrew , Richter Jadwiga , Santos Jose , Danzer Julia , Hölbling Stefanie
Published: February 2023

As the global research enterprise grapples with the challenge of a low carbon future, a key challenge is the future of international conferences. An emerging initiative which combines elements of the traditional in-person and virtual conference is a multi-hub approach. Here we report on one of the first real-world trials of a multi-hub approach, the World Climate Research Programme/Stratosphere-troposphere Processes And their Role in Climate (WCRP/SPARC) General Assembly held in Qingdao-Reading-Boulder during the last week of October 2022. Based on travel surveys of participants, we estimate that the multi-hub approach reduced the carbon footprint from travel of between a factor of 2.3 and 4.1 times the footprint when hosting the conference in a single location. This resulted in a saving of at least 288 tCO2eq and perhaps as much as 683 tCO2eq, compared to having the conference in one location only. Feedback from participants, collected immediately after the conference, showed that the majority (85%) would again attend another conference in a similar format. There are many ways that the format of the SPARC General Assembly could have been improved, but this proof-of-concept provides an inspiration to other groups to give the multi-hub format a try.
Regional modeling of water storage variations in a Kalman filter framework
Authors: Woehnke Viviana , Eicker Annette , Weigelt Matthias , Güntner Andreas , Reich Marvin
Published: February 2023

Water mass changes at and below the surface of the Earth cause changes in the Earth’s gravity field which can be observed by at least three geodetic observation techniques: ground-based point measurements using terrestrial gravimeters, space-borne gravimetric satellite missions (GRACE and GRACE-FO) and geometrical deformations of the Earth’s crust observed by GNSS. Combining these techniques promises the opportunity to compute the most accurate (regional) water mass change time series with the highest possible spatial and temporal resolution, which is the goal of a joint project with the interdisciplinary DFG Collaborative Research Centre (SFB 1464) "TerraQ – Relativistic and Quantum-based Geodesy".A method well suited for data combination of time-variable quantities is the Kalman filter algorithm, which sequentially updates water storage changes by combining a prediction step with observations from the next time step. As opposed to the standard way of describing gravity field variations by global spherical harmonics, we introduced space-localizing radial basis functions as a more suitable parameterization of high-resolution regional water storage change. A closed-loop simulation environment has been set up to allow the testing of the setup and the tuning of the algorithm. Simulated GRACE and GNSS data together with realistic correlated observation errors will be used in the Kalman filter to sequentially update the parameters of a regional gravity field model. The implementation was designed to flexibly include further observation techniques (terrestrial gravimetry) at a later stage. This presentation will outline the Kalman filter framework and regional parameterization approach, and address challenges related to, e.g., ill-conditioned matrices and the proper choice of the radial basis function parameterization.
A novel machine learning based bias correctionmethod and its application to sea level in an ensemble of downscaled climate projections
Authors: Hieronymus Magnus
Published: February 2023

A new machine learning based bias correction method is presented and applied to sea level in a regional climate model for the Baltic and the North Sea. The bias corrections introduced by the method depend on the state of the model it corrects. This contrasts with conventional bias correction methods that operate on distributions of output variables. That is, while conventional correction methods adjusts all modelled sea levels of the same height by the same amount, this method instead adjusts all sea level that occur under the same meteorological conditions by the same amount. Model state dependent corrections allow for better performance on classical skill scores, like correction coefficients, but it also limits the applicability of the method to models that can perform hindcasts. This constrain occurs because the method requires observations and model data from an overlapping time period.The bias correction method is applied to a large ensemble of dynamically downscaled climate scenario data encompassing many different driving global climate models and representative concentration pathways. The prevalence of significant trends in yearly sea level maximum is found to be independent of emission scenario in our ensemble. This suggests that anthropogenic climate change is not a strong driver of storm surge variability in the area. Moreover, it also suggests that very long datasets of corrected sea levels can be created by merging data from different emission scenarios. A dataset is thus produced that contains over 2600 model years and exists for seven different tide-gauge stations on the Swedish Baltic Sea coast. This dataset is used to estimate return levels for very long return periods by fitting generalized extreme value distributions to block maxima sea level time series. At some stations it is found that the block length used in the return level computation affect the result. This suggests that the commonly used annual maximum approach (i.e. having a block length of one year) is not always applicable for determining return levels for sea level in the area.
Developing generic reservoir operating rules for inclusion in the national-scale hydrological modelling of Great Britain
Authors: Salwey Saskia , Coxon Gemma , Pianosi Francesca , Lane Rosanna , Bliss Singer Michael , Hutton Chris
Published: February 2023

To meet growing water demand and to satisfy an increasing population, reservoirs are continually being integrated into river systems across the world. The presence of a reservoir can dictate the downstream flow regime, such that in many locations, understanding reservoir operations can be crucial to understanding the hydrological functioning of an impacted catchment. Consequently, over the last two decades, correctly representing reservoirs, and their operations, in hydrological modelling frameworks has become a key area of research for simulating water availability. Although substantial progress has been made in modelling reservoir operations (which control how water volumes are distributed across space and time), there is still no consensus on the best way to define, calibrate and evaluate operating rules within hydrological models. In most locations, data describing reservoir operating rules are not available, and timeseries of reservoir inflow, outflow and storage are often unpublished. Consequently, modelers must simplify and generalize sets of release rules from very little information, particularly where they are to be applied across large scales (e.g. across hundreds of reservoirs). Generic reservoir operating rules have typically been tested and developed using the Global Reservoir and Dam (GranD) database and thus are biased towards large irrigation reservoirs (which make up the majority of the dataset). Whilst operating rules have also been tested across many hydropower and multipurpose reservoirs, a gap remains for the definition of generic reservoir operating rules designed for smaller water supply reservoirs that can be applied nationally in countries such as Great Britain (GB).In this study, we integrate a new generic reservoir simulation component into a national-scale hydrological model of Great Britain and compare simulation results from two modelling scenarios (with and without the new reservoir component). The first scenario, where reservoirs are omitted, is used as a benchmark representative of current modelling practices in GB (where none of the national-scale hydrological models include reservoirs), whilst the second uses a set of generic operating rules focused on simulating small, water resource reservoirs. In both scenarios, we use Multiscale Parameter Regionalisation (MPR) for model calibration. To assess the suitability of our operating rules for simulating future conditions and evaluating water availability during hydrological extremes, we test the consistency of model performance across the onset, duration and recovery from droughts. This study will demonstrate the importance of including reservoir representation in hydrological models of Great Britain, and will introduce a set of operating rules suitable for smaller reservoirs with a focus on water supply.
Exploitation of post-fit residuals in global GNSS network processing
Authors: Dumitraschkewitz Patrick , Mayer-Gürr Torsten , Suesser-Rechberger Barbara , Öhlinger Felix
Published: February 2023

Global navigation satellite systems (GNSS) products are integral to a wide array of scientific and commercial applications such as pecise orbit determination of low Earth orbit satellites, earthquake monitoring, GNSS reflectomrety, tropospheric and ionospheric research, surveying and much more. These products consisting of GNSS orbit, clock, phase biases and more are generated by the analysis centres of the International GNSS Service (IGS) by processing observations from a global network of ground stations to one or more GNSS constellations. The processing consists of a combined station position and GNSS satellite orbit determination through a least squares approach donated as global multi-GNSS processing.Within global multi-GNSS processing it is assumed that the observation noise is elevation-dependent and any spatial and temporal correlations are disregarded. Within numerous studies it has been shown that this assumption is incorrect while several studies additional pointed out that a sophisticated stochastic modelling has a positiv impact on GNSS processing and resulting products. In past reseach we have shown to exploit the post-fit residuals to derive temporal correlations for a sophisticated stochastic modeling. However, there have not been any large-scale investigations regarding the impact of stochastic modelling of observation noise on global GNSS processing products. Furthermore, to guarantee the quality of the GNSS products global multi-GNSS processing requires a sophisticated cycle slip detection and repairing algorithm. Cycle slips are discontinuities in the phase observations and if not corrected can lead to degrading quality of GNSS products.   We present our advancements in global multi-GNSS processing by exploiting post-fit residuals for stochastic modeling and cycle slip detection. We used several years of observations and a selected IGS network of ground stations to generate GNSS products. Based on this data we analysed the impact our newly integrated approaches have on GNSS products such as orbits, clocks, phase biases and station coordinate time series.  
Improved alternative GRACE-FO accelerometer transplant product computed at TU Graz
Authors: Öhlinger Felix , Mayer-Gürr Torsten
Published: February 2023

For GRACE-FO gravity field recovery synthetic accelerometer data is required to replace the GRACE-D measurements due to their high noise level. Official transplant products published by the Jet Propulsion Laboratory (JPL) are the calibrated acceleration product (ACT) and the updated hybrid accelerometer transplant (ACX). At TU Graz an alternative in-house transplant product is generated using a remove-restore method. Based on the work from Behzadpur, 2021 the transplant product was further optimized. Improvements in the force modeling comprise an adjusted satellite macro model and a self-shadowing model as well as the consideration of thermal re-radiation. To account for the different orientations of the satellites in relative pointing mode, an additional step was introduced in the transplant processing by determining the thermospheric density along the orbit. Investigations were carried out to further improve the accelerometer transplant by incorporating data from the GRACE-D accelerometer.   
Empirical modelling of SSUSI-derived auroral ionization rates
Authors: Bender Stefan , Espy Patrick , Paxton Larry
Published: February 2023

Solar, auroral, and radiation belt electrons enter the atmosphere at polar regions leading to ionization and affecting its chemistry. Climate models with interactive chemistry in the upper atmosphere, such as WACCM-X or EDITh, usually parametrize this ionization and calculate the related changes in chemistry based on satellite particle measurements. Widely used particle data are derived from the POES and GOES satellite measurements which provide electron and proton spectra. These satellites provide in-situ measurements of the particle populations at the satellite altitude, but require interpolation and modelling to infer the actual input into the upper atmosphere.Here we use the electron energy and flux data products from the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) instruments on board the Defense Meteorological Satellite Program (DMSP) satellites. This formation of currently three operating satellites observes both auroral zones in the far UV from (115--180 nm) with a 3000 km wide swath and 10 x 10 km (nadir) pixel resolution during each orbit. From the N2 LBH emissions, the precipitating electron energies and fluxes are inferred in the range from 2 keV to 20 keV. We use these observed electron energies and fluxes to calculate auroral ionization rates in the lower thermosphere (≈ 90–150 km), which have been validated previously against ground-based electron density measurementsfrom EISCAT. We present an empirical model of these ionization rates derived for the entire satellite operating time and sorted according to magnetic local time and geomagnetic latitude. The model is based on geomagnetic and solar flux indices, and the coefficients indicate where certain drivers have the largest influence. The model will be particularly targeted for use in climate models that include the upper atmosphere, such as the aforementioned WACCM-X or EDITh models, and we present an initial comparison to current implementations for ionization rates used in high-top whole-atmosphere models. Further applications include the derived conductances in the auroral region, as well as modelling and forecasting E-region disturbances related to Space Weather.
Remediation of toxic contaminants from groundwater using low-cost adsorbent
Authors: Boraah Nekita , Chakma Sumedha , Kaushal Priyanka
Published: February 2023

Water, being the most important resource in the world, has become a cause of concern in the present time. About one-fifth of the population on earth lack access to safe drinking water. Access to safe drinking water has been a grave problem for India, especially in rural areas where the lack of usable water has resulted in decades-old sanitation and health problems. The main access to potable water is generally surface water and groundwater. However, with the increasing population and emerging demands, there is a possibility of a threat to groundwater in terms of both contamination and depletion. The potential sources of groundwater contamination include storage tanks, septic systems, uncontrolled hazardous waste, landfills, chemicals and road salts, and atmospheric contaminants. Among the contaminants, heavy metals contamination in water is a major concern worldwide- wide and it adversely affects human health. The major problem with heavy metals is their non-biodegradable nature, because of which their persistence is likely to be for a longer time. Toxic heavy metals like Cr, Pb, Cd, Hg, Ni, Cu, and Zn pose a threat to the ecology even at their lowest concentrations.
            This study takes into account the contamination problem of Northeast India. Among the toxic heavy metals, contamination by iron (Fe), arsenic (As) and fluoride (F-) is found to create much of problems for the people of the region due to their toxicity to many life forms. According to the groundwater yearbook 2020-2021, the amount of arsenic and iron in groundwater is noted to be 71.29µg/l and 12.93mg/l. Most of the treatment processes like, electrocoagulation, adsorption, membrane processes, ion exchange, precipitation, and chemical oxidation processes are employed for the removal of heavy metals from water, the majority of which are either challenging or need high maintenance costs. This paper focuses on developing a low-cost and efficient adsorbent that can remediate the toxic heavy metals from groundwater. In this study, wood biochar is used as the low-cost adsorbent for remediation. The study takes into account the effect of physicochemical parameters like pH, dosage, and initial concentration along with a thorough study of the characteristics of biochar to examine the removal efficiency and the optimum was found to be 99.5% in the case of both iron (Fe) and arsenic (As) respectively.