bluuebunny/crossref_metadata_2025 huggingface dataset:
Future northern peatland responses and its climate feedback under overshoot scenarios
Authors: Zhu Biqing , Qiu Chunjing , Gasser Thomas , Tanaka Katsumasa , Ciais Philippe
Published: February 2023

Northern peatlands store 300~600 Pg carbon, with approximately half underlain by permafrost. Climate change is progressively threatening this large carbon stock. Future temperature rise is likely to trigger changes in this already vulnerable system and can cause irreversibility or strong hysteresis, increasing natural CO2 and CH4 emissions. However, the role of northern peatlands in carbon cycle under various future emission scenarios is still unclear. Elevated temperature and atmospheric CO2 level may enhance the carbon sink in northern peatlands, while increased decomposition may lead to higher CO2 emissions. At the same time, massive amount of CH4 may be released due to permafrost thaw and other processes induced by future climate change.The large carbon pool, as well as the often-delayed responses of northern peatlands, is an essential component in evaluating future climate responses, especially under overshoot scenarios. Ignoring the climate impact on this carbon pool may lead to misestimations of the carbon fluxes of terrestrial systems under future emission scenarios. Furthermore, it is critical to fully understand its feedback, which may make a significant contribution to the future carbon budget. Therefore, the role of peat carbon feedback in meeting the Paris Agreement goals must be investigated and quantified.Significant progresses have been made in representing the northern peatlands with process-based complex land surface models. These results have laid a solid foundation to allow the development of our new peat carbon emulator. Compared to the extended run time required for complex land surface models, our emulator allows for running a large number of scenarios within a short time frame. The parameterizations of the peat carbon cycle, such as vegetation growth, soil carbon accumulation, organic matter decomposition, and CO2 and CH4 emissions are calibrated on five state-of-the-art complex land surface models that specifically represent high-latitude peatlands. By coupling the peat carbon emulator into the compact Earth System Model OSCAR, we incorporated the peatland feedback into global carbon-climate system and explored interactions between multiple feedbacks. Under a series of overshoot scenarios, we show that effective climate change mitigations are needed to prevent peat C loss and consequently positive climate feedback in the future.
Sub-cloud layer winds in the vicinity of trade-wind cumulus
Authors: Nuijens Louise , Koning Mariska
Published: February 2023

Sailors have long used cumulus clouds to guide their ships into areas of favourable winds. On the upwind side of cumulus clouds, the clouds’ thermal circulation would add momentum to the prevailing flow, while on the downwind side, the opposing branch of the circulation would reduce the flow. In this study, we take a simple approach to evaluating this sailors’ theorem and visualise the winds in the sub-cloud layer in the vicinity of shallow cumulus clouds. This is done by collocating cloud radar and wind lidar profiling measurements during EUREC4A on board the RV Meteor and at the BCO for a six-month period. Is there evidence for a thermal circulation in the wind surrounding clouds, or for plume-like structures that support a mass-flux approach? We will discuss our findings for clouds of increasing depth, for which clustered convection and cold pool gustiness become increasingly important.
Correction of River Bathymetry Parameters Using the Stage–Discharge Rating Curve
Authors: Zhou Xudong , Revel Menaka , Modi Prakat , Shiozawa Takuto , Yamazaki Dai
Published: February 2023

River bathymetry is an important parameter for hydrodynamic modeling; however, it is associated with large bias because direct large-scale measurements are impractical. Recent studies adjusted river bathymetry data based on assessment of the difference between modeled and observed water surface elevation (WSE); however, model uncertainties in river discharge can lead to unintended errors in correcting river bathymetry. In this study, we propose a simple but robust and rational correction method of river bathymetry using the bias between stage–discharge rating curves rather than WSE time series data. The rating curve represents the internal characteristics of the river section, and is not sensitive to the instantaneous simulated discharge errors. Our results showed that the corrected river bathymetry are robust to bias in runoff as they converged among experiments driven by noise-corrupted or multimodel runoff forcing. Evaluation with the corrected river bathymetry against virtual truth demonstrated that the new method reduced 0.85–1.12 m of the absolute bias than the result from the conventional method. The deviation among the results reduced by more than 70% particularly in river sections with no backwater effects. Evaluation of the corrected river model output also showed the advantage of rating-curve bias correction, as the simulated WSE is reasonably better only with better runoff and it does not conceal errors in runoff inputs. Given the difficulty of eliminating discharge errors and bias in runoff, a method for correcting river bathymetry that is free from discharge and runoff errors is important for improving hydrodynamic modeling.
A transdisciplinary chain to assess the risk of direct and indirect impacts linked to extreme climate events from regional to local scale
Authors: Arosio Marcello , Caiani Alessandro , Fosser Giorgia , Di Noia Jlenia
Published: February 2023

Climate change is causing increased risks linked to extreme weather events. In order to develop effective adaptation strategies and policies, there is an urgent need for methodologies able to assess how the socio-economic risks associated with extreme climate-related events will change in the coming decades especially at local scale. The development of these methodologies require the expertise from many different scientific disciplines, including: modelling of global and local climatic phenomena, assessment of the intensity and probability of extreme events, representation of their impacts on the society and quantification of the associated risk.In this work we propose a methodological chain linking the risk of extreme events in a changing climate with both direct and indirect impacts on the socio-economic sector from regional to local scale. The proposed chain integrates the knowledge of three scientific fields: climatologists, engineers and macro-economist. Here, we present agreements and differences between communities (e.g., aim, terminology, methodology, etc.), and evaluate advantages and constrains of the combined used of high-resolution regional climate models, engineering risk assessment models and economic input-output models compared to the state of the art in this field.To illustrate the advantages of the proposed methodology and its practical feasibility, we present preliminary results from an applied pilot study in the Italian context.
An Empirical Model of Whistler Mode Waves in the Radiation Belt Region
Authors: Santolik Ondrej , Kolmasova Ivana , Taubenschuss Ulrich , Turcicova Marie , Hanzelka Miroslav
Published: February 2023

Whistler mode waves interact with different magnetospheric particle populations in the inner magnetosphere and significantly influence particle fluxes in the Earth's radiation belts. Using recently acquired large databases of spacecraft measurements from the Van Allen Probes and Cluster missions we construct new empirical models of whistler mode waves in the inner magnetosphere. We pay special attention to the off-equatorial region, which is often under-sampled in the currently existing models, and to the inter-calibration of data from different spacecraft missions. We take into account the effects of instrumental noise and other artifacts which influence the quality of data at the input of the modeling procedure. Our results show that dawn chorus occurs most often around noon, while its peak average amplitudes are observed during the local night. We also show that off-equatorial plasmaspheric hiss has a strong obliquely propagating component. We further confirm the influence of low plasma density regions on the intensity of chorus.
Tibetan Plateau increases the snowfall in southern China: a refutation to some trending views
Authors: Wang Liping , Yang Haijun
Published: February 2023

The Tibetan Plateau (TP) plays a vital role in Asian hydrological climate. However, there is a lack of quantitative estimate on TP’s effect on snowfall over China. Some trending views include that the TP acts as a giant wall, blocking cold outbreaks and protecting southern China from severe snowstorm. Here, through topography experiments with and without the TP, we demonstrate that, compared to the world without the TP, the presence of the TP decreases snowfall in northern China by 60% due to drastically reduced moisture, while it promotes snowfall in southern China by 1500%, especially from November to March, through attracting cold air from the north and moisture from the south to southern China. The presence of the TP increases winter relative humidity substantially in southern China, which reduces human comfort. This work refutes some trending views and helps us correctly recognize TP’s role in China’s winter climate.
Mechanical controls on caldera slope morphology and failure
Authors: Harnett Claire , Watson Robert , Holohan Eoghan , Schöpfer Martin
Published: February 2023

Volcanic calderas are delimited by a ‘caldera wall’ which can be several hundred meters in height. This represents the degraded scarp of a fault that accommodates roof subsidence. Here, we assess the roles of friction and cohesion on caldera wall morphology by: (i) analysing the slope properties of several young natural calderas in the ALOS-3D global digital surface model (DSM), and (ii) comparing those observations to the results of a text-book analytical solution and of new Distinct Element Method (DEM) modelling.Our analysis of the DSM suggest that caldera wall heights are not as closely linked to slope angle as previously suggested. Slope angles range from 20 – 65° and slope heights range from 99 m - 1085 m. We find that the smaller slope heights are not robustly tied to greater slope angle. When compared to analytical predictions, these slope-height data yield expected rock mass cohesion values of less than 0.25 MPa for all calderas, which is 2-3 orders of magnitude less than typical laboratory-scale values.The DEM models explicitly simulated the process of progressive caldera collapse, wall formation and destabilisation, enabling exploration of the emergence of slope morphology as a function of increasing subsidence and of mechanical properties. Results confirm that low bulk cohesion values <0.5 MPa are required to reproduce the observed ranges of slope angles and slope heights, and they indicate that friction is the dominant control on slope evolution. Different failure mechanisms resulted as a function of cohesion and friction during early collapse: (1) granular flow with low friction and cohesion, and (2) block toppling at high friction and cohesion. During later collapse, shear failure dominates regardless of cohesion. At higher cohesion and/or friction values, the models resulted in non-linear concave-upward slope profiles that are seen at many natural calderas.
Virtual Earth Cloud: a multi-cloud framework for improving replicability of scientific models
Authors: Santoro Mattia , Mazzetti Paolo , Nativi Stefano
Published: February 2023

Humankind is facing unprecedented global environmental and social challenges in terms of food, water and energy security, resilience to natural hazards, etc. To address these challenges, international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan (e.g., the UN SDGs). The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions and avoid potentially negative impacts on society and the environment.Scientific models are key tools to transform into information and knowledge the huge amount of data currently available online. Executing a scientific model (implemented as an analytical software) commonly requires the discovery and use of different types of digital resources (i.e. data, services, and infrastructural resources). In the present geoscience technological landscape, these resources are generally provided by different systems (working independently from one another) by utilizing Web technologies (e.g. Internet APIs, Web Services, etc.). In addition, a given scientific model is often designed and developed for execution in a specific computing environment. These are important barriers to enable reproducibility, replicability, and reusability of scientific models –becoming key interoperability requirements for a transparent decision-making process.This presentation introduces the Virtual Earth Cloud concept, a multi-cloud framework for the generation of information/knowledge from Big Earth Data analytics. The Virtual Earth Cloud allows the execution of computational models to process and extract knowledge from Big Earth Data, in a multi-cloud environment, and thus improving their reproducibility, replicability and reusability.The development and prototyping of the Virtual Earth Cloud is carried out in the context of the GEOSS Platform Plus (GPP) project, funded by the European Union’s Horizon 2020 Framework Programme, aims to contribute to the implementation of the Global Earth Observation System of Systems (GEOSS) by evolving the European GEOSS Platform components to allow access to tailor-made information and actionable knowledge.
Surface temperature retrieval at mid-infrared band using a combination of low-orbit and geostationary orbit satellite imagery
Authors: Lee Kwonho , Kim Heeseob , Pyo Seonghun , Park Seunghan
Published: February 2023

Infrared remote sensing technique has been widely used for the characteristics of objects since ithas the advantage of higher atmospheric transmittance than visible wavelengths. However, theMid-Wave InfraRed (MWIR) region close to the visible band can be partially affected by solarradiation, so the solar radiation and attenuation in the atmosphere cause errors in the targetdetecting. In this study, an algorithm for retrieval of the mid-infrared surface temperature wasdeveloped by using a combination of the GEO-KOMPSAT-2A (GK-2A) satellite and Landsat data.Through the comparison with ground observations, it was found that the surface temperatures atMWIR band retrieved are less than 3K, and a statistically significant level of mutual comparisonwas obtained. Therefore, despite the limitations of the MWIR band, the new methodology can beapplied to determine the surface-level temperature through the coupling between the twodifferent orbit satellites.AcknowledgementThis research was supported by the Korea Aerospace Research Institute (FR22H00W01) in2022-2023.
Electron-induced radiolysis of water ice and the buildup of O2
Authors: Tinner Chantal , Galli André , Bär Fiona , Pommerol Antoine , Rubin Martin , Vorburger Audrey , Wurz Peter
Published: February 2023

Irradiation by energetic ions, electrons, and UV photons induces sputtering and chemical processes (radiolysis) on the surfaces of icy moons and comets. Radiolysis of water ice has important implications for the chemistry and evolution of these celestial bodies. In this work, we carried out a series of laboratory experiments to investigate the products of radiolysis and the retention of O2 in porous water ice samples when irradiated with high-energy electrons.To conduct our experiments, we irradiated two types of water ice samples with high energy electrons (0.5 keV to 5 keV ) and measured the resulting chemical species using time of flight mass spectrometry. The experiments were performed under conditions replicating the icy moons’ surface conditions ( K and -7 mbar). Our results showed production of H2 and O2 radicals, but other predicted radiolysis species, such as H2O2 and O3, were not detected so far; their abundances remain below 0.005 by number compared to the release of O2. This is in contrast to previous studies, which have reported the production of OH and H2O2 through the radiolysis of water ice.We also studied the retention of oxygen in the ice. By computing the timescales of rise for the O2 signal upon irradiation, we observed that it rises faster for non-pristine (follow-up) ice irradiations. This suggests that O2 (or an O2 precursor) produced during the first irradiation can be retained in the ice.For some irradiations, the electron energy and current were chosen higher to provoke the water ice's sublimation. The water release showed different properties depending on the porosity and grain size of the irradiated ice.Overall, our results contribute to our understanding of the radiolysis of water ice and its role in the chemistry and evolution of ice-covered bodies in the solar system. Further studies will be needed to fully understand the factors that influence the production and retention of different chemical species during the radiolysis of water ice.
Periodical behaviour of air CO2 time series after Cumbre Vieja volcanic eruption
Authors: Oliveira Sérgio , Viveiros Fátima , Pacheco José , Henriques Diogo , Moutinho Alexandra , Pèrez Nemesio , Hernández Pedro
Published: February 2023

In the aftermath of the 2021 eruption of Cumbre Vieja volcano, a network of four low-cost air sensors was installed at four different sites in the village of Puerto Naos in La Palma, Canary Islands. These sensors measure CO2, temperature, and relative humidity every one minute.The measurements made between January and December of 2022 showed that all sensors frequently overpassed the 0.5 vol.%, defined by several organizations as the Permissible Exposure Limit (PEL) for safety in work environments. In addition, three of the sensors reached the instrument’s full scale (4.0 vol. %), a concentration above the STEL (short-term exposure limit) that can cause symptoms such as headache, weakness and breathing acceleration.The Lomb-Scargle power spectral density estimate, obtained applying the plomb function of Matlab R2021a to the data, revealed diurnal cycles on the atmospheric CO2 concentration time series in all monitored sites. All sites showed at least one cycle per day, with two of the sites having two cycles per day. One site, with an outdoor sensor, showed three cycles per day during the monitored period. Air temperature and relative humidity at the same sites showed similar periodicity, suggesting that the gas concentrations are correlated with the meteorological parameters. These observations, as far as we know, are the first to highlight the cyclic behaviour on volcanic air CO2 time series.This work was partially funded by FCT – Fundação para a Ciência e Tecnologia, under project SONDA - Synchronous Oceanic and Atmospheric Data Acquisition (PTDC/EME-SIS/1960/2020), and VOLRISKMAC II - Fortalecimiento de las capacidades de I+D+i para el desarrollo de la resiliencia frente a emergencias volcánicas en la Macaronesia (INTERREG MAC2/3.5b/328). 
The Water, Land, and Carbon Intensity of Electricity Production: The Case of South Africa
Authors: van Huyssteen Thomas , Thiam Djiby , Nonhebel Sanderine
Published: February 2023

Electricity production has a significant impact on the Water-Energy-Food (WEF) nexus sectors as it requires substantial amounts of water and land, whilst also being a primary polluter of these resources. In addition, electricity production is a key contributor to global CO2 emissions.  With electricity production predicted to increase by over 50% by 2050, the impact of electricity production on water and land resources, as well as the environment, will need to be significantly reduced This is particularly important in countries facing water, energy, and food scarcity and insecurity such as South Africa. This paper therefore investigates the impact of electricity production on the WEF nexus sectors and environment in South Africa. To do this, this paper conducts a lifecycle assessment of the water footprint (WF), land footprint (LF), and carbon footprint (CF) of electricity production in South Africa, by electricity source, and under key scenarios. The results from the IRP 2030 scenario showed that despite a 63% increase in electricity production targeted from 2018-2030 in South Africa, the water, land, and carbon footprints of electricity production would decrease by 29%, 9%, and 5.5% respectively. Compared to the BAU 2030 scenario, it was shown that the water, land, and carbon footprints would be 55.5%, 42.6%, and 41.5% lower in the IRP 2030 scenario, respectively. Overall, the results show that to reduce the impact of electricity production on the WEF nexus sectors and the environment, integrated resource planning, switching away from fossil fuels, particularly coal, and promoting the use of non-hydro and non-biomass renewables is required.
Beyond growth? The significance of microbial maintenance for carbon-use efficiency in the light of soil carbon storage
Authors: Bölscher Tobias , Brunn Melanie , Colombi Tino , Domeignoz-Horta Luiz A. , Herrmann Anke M. , Meurer Katharina H.E. , Olagoke Folasade K. , Vogel Cordula
Published: February 2023

During decomposition of organic matter, soil microbes determine the fate of C. They partition C between anabolic biosynthesis of various new microbial metabolites (i.e. C reuse) and catabolic C emissions (i.e. C waste, mainly through respiration). This partitioning is commonly referred to as microbial carbon-use efficiency (CUE). The reuse of C during biosynthesis provides a potential for the accumulation of microbial metabolic residues in soil. The microbial metabolic performance is a key factor in soil C dynamics, because the vast majority of C inputs to soil will – sooner or later – be processed by soil microorganisms. Soil C inputs will thus be subjected to microbial allocation of C towards reuse or emitted waste, with the former leading to C remaining in soil. Recognized as a crucial control in C cycling, microbial CUE is implemented – implicitly or explicitly – in soil C models, which react highly sensitive to even small changes in CUE. Due to the models’ high sensitivity, reliable soil C projections demand accurate CUE quantifications, capturing unambiguously all metabolic C fluxes.The current concept of microbial CUE neglects microbial maintenance which could make up considerable parts of the microbially processed C. Commonly, CUE is quantified from C incorporated into biomass or used for growth and C released as CO2. Extracellular metabolites, such as polymeric substances (EPS), exoenzymes or nutrient mobilizing compounds, as well as intracellular maintenance metabolites, such as storage compounds or endoenzymes, are ignored although they represent microbial metabolic C reuse and thus C remaining in soil.Based on theoretical considerations and a case study for EPS production, we will demonstrate that neglecting microbial maintenance can have severe impact on estimation of terrestrial C storage. For instance, ignoring measured EPS production (of a quantity of C which equals 37 % of the C used for growth) causes a substantial underestimation of CUE. Here, current approaches of CUE provide an apparent CUE of 0.20 while disregard an actual CUE of 0.25 (i.e. CUE is 25 % higher when maintenance metabolism is considered). Based on our findings, we suggest an adjustment of how we conceptualize and calculate microbial CUE in soils.
Examining Possible Retreat Scenarios for the Greenland Ice Sheet during the MIS-11c Interglacial
Authors: Crow Brian , Tarasov Lev , Prange Matthias , Schulz Michael
Published: February 2023

The interglacial period spanning ca. 423 to 398 ka and known as Marine Isotope Stage (MIS) 11c has been the subject of much study, due largely to the unique evolution of global temperatures, greenhouse gas levels, and sea levels relative to other interglacials of the late Pleistocene. Particularly concerning is some geological evidence and prior modeling studies which have suggested that a large majority of the Greenland ice sheet (GrIS) disappeared during this period, despite global mean air temperatures only modestly higher than those of the preindustrial period. However, uncertainty is high as to the extent and spatiotemporal evolution of this melt due to a dearth of direct geological constraints. Our study therefore endeavors to better constrain these large uncertainties by using spatiotemporally interpolated climate forcing from CESM v1.2 time slice simulations and an ensemble of ice sheet model parameter vectors derived from a GrIS history matching over the most recent glacial cycle from the Glacial Systems Model (GSM). The use of different ice sheet initialization states from simulations of the previous glacial-interglacial transition helps to capture the large initial condition uncertainty. Two different regional present-day climate modeling datasets are utilized for anomaly correction of CESM precipitation and temperature fields. Preliminary analysis indicates that the most robust retreat across most ensemble members happens in the northern, western, and central portions of the ice sheet, while the higher terrain of the south and east retain substantial amounts of ice. This is broadly consistent with indications that ice may have survived the MIS-11c interglacial at the Summit ice core location, but not at DYE-3. Simulations indicate a maximum MIS-11c sea level contribution from the GrIS centered between 408 and 403 ka, with minimum GrIS volumes reaching between 25% and 70% of modern-day values. In part due to the prior constraint of ice-sheet model ensemble parameters from history matching, ensemble parameters controlling downscaling and climate forcing bias correction are the largest parametric sources of output variance in our simulations.  Though CESM uncertainties are unassessed in this study, it is likely they dominate given that the choice of present-day reference temperature climatology for anomaly correction of the climate model output has the largest effect on the GrIS melt response in our simulations.
Rapid Flood inundation mapping using SAR data with Google Earth Engine cloud platform
Authors: Wang Qin , Zhuo Lu , Li Chen , Rico-Ramirez Miguel , Wen Zitong , Han Dawei
Published: February 2023

Flood events are becoming increasingly common with the increase in the frequency of extreme weather driven by climate change. The present state of the technologies for flood risk mapping is typically tested on small geographical regions due to limitation of flood inundation observations, which hinders the implementation of flood risk management activities. Synthetic aperture radar (SAR) measurements represent an indispensable data source for flood disaster planners and managers, given their ability to scan the Earth's surface nearly independently of weather conditions and the time of day. The decision by the European Space Agency (ESA) Copernicus program to open data from its Sentinel-1 SAR satellites to the public marks the first time of global, operational SAR data freely available. Combined with the emergence of cloud computing platforms like the Google Earth Engine (GEE), this development presents a tremendous opportunity to the disaster response community, for whom rapid access to analysis-ready data is needed to inform effective flood disaster response interventions and management plans. Here, we present an algorithm that exploits available Sentinel-1 SAR images in combination with historical Landsat and other auxiliary data sources hosted on the GEE to rapidly map surface inundation during flood events. Our algorithm relies on multi-temporal SAR statistics to identify historical floods. Additionally, historical Landsat-based surface water class probabilities are used to distinguish floods from permanent or seasonally occurring surface water. Using this algorithm, we can get a flood inundation map of the region of interest in less than 10 seconds. We tested the algorithm over Houston, Texas following the Hurricane Harvey in late August 2017 and the results showed an accuracy of 89.9%. The flexibility of our algorithm will allow for the rapid processing of future open-access SAR data, including data from future Sentinel-1 missions.
Concept for Numerical THM Integrity Analysis of a Generic Repository in Clayey Rock in Germany
Authors: Maßmann Jobst , Thiedau Jan , Bittens Maximilian , Kumar Vinay , Tran Tuong Vi
Published: February 2023

Within the ANSICHT project, BGE Technology, BGR, and the Gesellschaft für Anlagen- und Reaktorsicherheit (GRS) developed a safety assessment methodology for a high-level radioactive waste repository in clay formations based on German legal requirements. This included the quantification of integrity criteria and their exemplary numerical evaluation by THM-modeling. In the project's second phase, the modeling concept was extended by a detailed near-field model and initial attempts were made to quantify uncertainty. For the safety assessment of a repository system, detailed knowledge of the processes in the nearfield, the processes in the host rock, and the evolution of the whole system up to the surface is equally important. Concerning the prediction period of 1 million years and the complex coupled processes triggered by the construction and operation of an underground repository, the computational effort for numerical modeling is enormous. To cope with this effort, the proposed concept consists of models with different resolutions, dimensions, considered processes, and local coverages: a detailed 3D model of the near-field, a 2D and a 3D model of the whole domain, with the 2D model allowing a much higher resolution. The associated mathematical models are solved using OpenGeoSys 6, a finite-element-simulator allowing fully implicit process couplings. A statement about the integrity criteria and the general THM behavior is made integrally by all three models. Furthermore, a simplified 2D model is used to quantify the effect of variations in material parameters on the uncertainty of the results with manageable effort. Various geological setups have been used to investigate the influence of large inhomogeneities, such as sand lenses or layers in meter- to kilometer-scale, on the integrity of the host rock.In this contribution, the updated modeling concept is presented and applied illustratively to a generic but typical geological situation in northern Germany. 
Deep Learning guided statistical downscaling of climate projections for use in hydrological impact modeling in Danish peatlands
Authors: Quistgaard Thea , Langen Peter L. , Denager Tanja , Schneider Raphael , Stisen Simon
Published: February 2023

A course of action to combat the emission of greenhouse gasses (GHG) in a Danish context is to re-wet previously drained peatlands and thereby return them to their natural hydrological state acting as GHG sinks. GHG emissions from peatlands are known to be closely coupled to the hydrological dynamics through the groundwater table depth (WTD). To understand the effect of a changing and variable climate on the spatio-temporal dynamics of hydrological processes and the associated uncertainties, we aim to produce a high-resolution local-scale climate projection ensemble from the global-scale CMIP6 projections.With focus on hydrological impacts, uncertainties and possible extreme endmembers, this study aims to span the full ensemble of local-scale climate projections in the Danish geographical area corresponding to the CMIP6-ensemble of Global Climate Models (GCMs). Deep learning founded statistical downscaling methods are applied bridge the gap from GCMs to local-scale climate change and variability, which in turn will be used in field-scale hydrological modeling. The approach is developed to specifically accommodate the resolutions, event types and conditions relevant for assessing the impacts on peatland GHG emissions through their relationship with WTD dynamics by applying stacked conditional generative adversarial networks (CGANs) to best downscale precipitation, temperature, and evaporation. In the future, the approach is anticipated to be extended to directly assess the impacts of climate change and ensemble uncertainty on peatland hydrology variability and extremes.
TwistPy: An open-source Python toolbox for wavefield inertial sensing techniques
Authors: Sollberger David , Heimann Sebastian , Bernauer Felix , Eibl Eva P. S. , Donner Stefanie , Hadziioannou Céline , Igel Heiner , Yuan Shihao , Wassermann Joachim
Published: February 2023

In the past decade, significant progress has been made in the acquisition and processing of seismic wavefield gradient data (e.g., recordings of ground strain and rotation). When combined with conventional multicomponent seismic data, wavefield gradients enable the estimation of local wavefield properties (e.g., the local wave speed, the propagation direction, and the wave type) and the reconstruction of spatially under-sampled seismic wavefields. However, the seismological community has yet to embrace wavefield gradient data as a new observable.We present TwistPy (Toolbox for Wavefield Inertial Sensing Techniques), an open-source software package for seismic data processing written in Python. It includes routines for single-station polarization analysis and filtering, as well as array processing tools. A special focus lies on innovative techniques to process spatial wavefield gradient data and, in particular, rotational seismic data obtained from dedicated rotational seismometers or small-aperture arrays of three-component sensors. Routines currently included in the package comprise polarization analysis and filtering in both the time domain and the time-frequency domain (for three-component and six-component data), dynamic tilt corrections, and beamforming (Bartlett, Capon, and MUSIC beamformers).  With TwistPy, we attempt to lower the barrier of entry for the seismological community to use state-of-the art multicomponent and wavefield gradient analysis techniques by providing a user-friendly software interface.Extensive documentation of the software and examples in the form of Jupyter notebooks can be found at https://twistpy.org.
Areal extremes from a different perspective: rainfall as 2D and 3D connected objects.
Authors: El Hachem Abbas , Seidel Jochen , Bárdossy András
Published: February 2023

Using the German weather radar data for the last 20 years with a high spatial and temporal resolution, the occurrence of rainfall extremes was analysed. By extracting and examining connected rainfall areas, several research questions were investigated: (1) How many extremes occur in a given area independent of their location? (2) To what extent is their occurrence in space a random and to what extent a structured process? (3) How are the connected volumes behaving in space and time? (4) How does the areal extent relate to event duration, rainfall volume, and discharge volume? The first two research questions were investigated for all of Germany, the last two by analysing rainfall and run-off data in several small and medium size headwater catchments in southern and western Germany.
The results show that the occurrence of events in space is related to their areal extent; there are regions where the frequency of occurrence of large spatially distributed events is greater than that of smaller ones. Moreover, there are interesting relationships between the spatial extent of an event, the event duration, and the event rainfall volumes. For high discharge values, not only does the rainfall intensity matter but also the event duration and spatial distribution of rainfall within a catchment. Many discharge peaks are not necessarily caused by high-intensity events (hourly or daily maxima) but by the accumulation of rainfall cells in space and time.
Assessing the effect of climate change trends on the effectiveness of climate adaptation measures: A simulation approach
Authors: Nasrazadani Hossein , Adey Bryan
Published: February 2023

Our infrastructure systems are subject to climatic hazards which disrupt their provided service causing discomfort for their users as well as direct and indirect losses for their stakeholders to restore their service. This requires infrastructure managers to regularly assess the resilience of their system under potential hazard scenarios and plan and execute climate adaptation interventions to enhance the resilience of their system. To this aim, the common practice is to plan interventions based on data from past occurred events, while in essence, interventions are to protect infrastructure systems against future hazard scenarios. In fact, studies have shown that, due to climate change, hazards such as flooding are projected to occur more frequently and severely. In particular, a 30-100% increase in extreme rainfall intensities, as well as flood magnitudes, are projected by 2100 in many European countries. Hence, measures that are planned to meet the requirements of past events are not necessarily sufficient to withstand future events. However, except for few studies that focused on climate-adaptable interventions against future scenarios of sea level rise, the existing body of flood mitigation research lacks quantitative analysis of the impact of climate change trends in evaluating and planning interventions, particularly for assessing the effect of inland flooding on transportation networks. The goal of this study is to investigate how the future evolutions of the climatic hazards due to climate change affect the planning and evaluation of climate adaptation interventions to enhance the resilience of infrastructure systems. In particular, it will be studied how the ongoing trend of climate change in increasing the frequency and severity of flood events can be incorporated into planning and evaluating resilience-enhancing interventions. To this aim, a simulation methodology is proposed that generates a host of stochastic scenarios with and without considering the effect of climate change, as well as with and without the effect of candidate interventions. Each scenario represents a random realization of the entire system starting from random scenarios of heavy rainfall leading to flooding, physical and functional impacts on infrastructure components as well as their performance as a network, and lastly, the ensuing direct and indirect consequences due to restoration efforts and loss of service. The analysis provides insight for infrastructure managers into how each candidate intervention, designed based on past events, should be modified in order to remain sufficiently effective against future scenarios of hazard under climate change.
RASTOOL project, tools for the Copernicus European Ground Motion Service exploitation
Authors: Barra Anna , Cuevas-González María , Palamà Riccardo , Gao Qi , Shahbazi Saeedeh , Béjar Pizarro Marta , Ezquerro Pablo , Bru Cruz Guadalupe , Crosetto Michele , Monserrat Oriol
Published: February 2023

The aim of this work is to present RASTOOL (EGMS RASTOOL: European ground motion risk assessment tool), a project co-financed by the EU-Union Civil Protection Mechanism. The Copernicus European Ground Motion Service (EGMS) represents a remarkable source of knowledge for the geohazard community. It provides consistent, regular, and reliable information on natural and anthropogenic ground motion phenomena over Europe, with millimetric accuracy (https://land.copernicus.eu/pan-european/european-ground-motion-service). The EGMS provides satellite interferometric products, with an annual updating, and a free and open policy. The availability of this vast amount of data is valuable for the scientific community but difficult to be exploited in the regular activities of territorial managers or Civil Protection Authorities. In fact, interferometric data interpretation might be challenging and time consuming, demanding a high level of expertise and a specific background. In this context, RASTOOL aims to develop a set of tools for simplifying the usage of the EGMS products, to automatically analyse them and to generate maps to support hazard, exposure, and risk-assessment against geohazards (both natural and anthropogenic). The tools developed in the frame of previous projects (Safety, U-Geohaz, Momit) will be improved to be easily applied to the EGMS products and integrated with new ones.
Lithospheric control on the Paleogene uplift and volcanism in Ireland and Britain
Authors: Bonadio Raffaele , Lebedev Sergei , Chew David
Published: February 2023

Spectacular Paleogene uplift and volcanism in Ireland and Britain are thought to be associated with the Iceland Plume but their mechanisms are still unclear, considering, in particular, that the Iceland Hotspot was many hundred kilometres away from the volcanism. We obtain new insights into the mechanisms by combining new evidence from seismic tomography, petrological inversion of seismic data, and the geological data on uplift and volcanism. Optimal resolution tomography is a new approach, developed for surface wave tomography, that allows us to find the optimal resolving length at every point of a tomographic model grid. With this approach we evaluate the posterior model error at a point of the model grid empirically, estimating it by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure. We apply this method to the region of Ireland and Britain, using more than 11,000 interstation phase-velocity curves measured at station pairs recording simultaneously, to image the lithosphere and underlying mantle beneath the area. The use of cross-correlation of teleseismic earthquakes and waveform inversion produces measurements in a very broad period range, leads to an unprecedented data coverage of the region, and allows us to unveil exciting new insights into the structure and evolution of the area, from the crust to the deep asthenosphere at a unprecedented level of detail.The composite, optimal resolution phase-velocity maps are inverted for a 3-D VS model, which reveals pronounced, previously unknown variations in the lithospheric thickness beneath the area. The model shows evidence of a robust, low-velocity anomaly beneath the Irish Sea and its surroundings that persists in the models from ~60 to at least 140 km depth, indicating an anomalously thin lithosphere and demonstrating that the assumption of a nearly constant lithospheric thickness across the area, previously adopted, is not valid. Phase velocity data at key locations are inverted using integrated geophysical-petrological inversion, to estimate the thermal structure of the lithosphere-asthenosphere system consistent with the seismic data, surface elevation, and heat-flow. The circum-Irish Sea area reveals a pronounced lithospheric thinning and matches the region of the Paleogene uplift previously suggested to be caused by a lateral branch of the Iceland mantle plume, which may have flowed into thin lithosphere areas surrounded by continental lithosphere during the evolution of the North Atlantic Ocean over the past 60 M.y. Our results show a striking correlation between lithospheric thickness and exhumation thermochronological measurements (as well as proposed underplating thickness, denudation, and the locations of the intraplate volcanism of the enigmatic North Atlantic Igneous Province) suggesting a significant lithospheric control on the volcanism of the area.
Seasonal and intraseasonal oscillations in a monsoonal estuary
Authors: Safin Iyyath Pareed pillai , Vijith Vijayakumaran , Sajeev Raveendran , Anup Nambiathody , Vasudevan Shankar , Shehsin Naduvilakath Mohamed Iqbal , Saji Parolil Kuttan , Anoop Kavil Anand , Shameem Kareekunnan
Published: February 2023

Estuaries on the Indian subcontinent are influenced by the Asian Summer Monsoon and show strong seasonality. As a result, these estuaries are often referred to as monsoonal estuaries (Vijith et al., 2009).  The seasonal cycle is superposed with intra-seasonal oscillations (ISO) with periods ranging from 10 to 90 days. Due to the lack of high-resolution data in Indian estuaries, even while the seasonal cycle of monsoonal estuaries is comparatively well understood, the intra-seasonal variability has not yet been examined. The active-break monsoon spells drive quasi-biweekly oscillations (10--20 days) within the ISO, and oscillations of 30–60 days are present due to northward-moving cloud bands.  In this study, we use high-resolution salinity, temperature and sea level measurements from the Cochin estuary, located on the southwestern coastal plain of India, to investigate the ISO-related variability. The spectral analysis of the sub-tidal signals of salinity, temperature and sea level shows that ISO exists year round (December 2019 to May 2021). During the dry season (December to April), the salinity was on an average of 30 PSU, and the amplitude of ISO was from 3 to 5 PSU. In the wet monsoon season, the amplitude of ISO varies around 5 to 10 PSU. The temperature, sea level, and precipitation spectrum also exhibited similar patterns in the wet season. The coherence of salinity with sea level and precipitation is also quantified.  ReferenceVijith, V., Sundar, D., Shetye, S.R., 2009. Time-dependence of salinity in monsoonal estuaries. Estuar. Coast. Shelf Sci. 85, 601-608. . http://dx.doi.org/10.1016/j.ecss.2009.10.003
Stratigraphic Data Calibrates Predictive Modeling of Holocene-Present Floodplain Sediment Storage In the Mid-Atlantic U.S.
Authors: Pizzuto James
Published: February 2023

Storage of sediment on floodplains delays downstream sediment delivery, increasing the timescale of catchment responses to forcing by tectonics, climate changes, and watershed sediment management practices.  Including floodplain storage in catchment sediment routing models, however, is challenging because the long timescales involved exceed the duration of stream gaging station and other observational data sources.  As a result, floodplain storage is typically ignored in catchment sediment modeling.  To quantify timescales of sediment storage for mid-Atlantic U.S. floodplains since the early Holocene, floodplain sediment thickness distributions are defined for three time periods by analyzing stratigraphic data: presettlement (deposited before 1750), legacy (deposited 1750-1950), and modern (deposited after 1950).  These data are used to calibrate a model that predicts the thickness, age, and storage time distributions of floodplain deposits through time.  The model uses empirical equations to estimate changes in flood magnitude and duration caused by changes in forest cover and urban development.  Simple hydraulic models predict the occurrence of overbank flow based on channel geometry (which changes through time as floodplains accrete) and the potential for backwater induced by nearby milldams during the 19th Century. Overbank deposition during overbank flows is predicted based on sediment concentration, sediment settling velocity, and overbank flow duration.  Sediment erosion is predicted based on the age distribution of stored sediment and a power law function that specifies the exposure of sediment to erosion by age category, an approach that is similar to the StorAge Selection Functions often used in catchment hydrologic modeling.   The calibrated model, “tuned” to reproduce observed stratigraphic data, predicts monotonically increasing fluvial sediment concentrations from presettlement to modern time periods, and sediment budget components (input and output fluxes and rates of sedimentation and erosion) that also increase through time.  Predicted sediment residence times (mean age of stored sediment) vary from ~450 years in 1750 to ~300 years in 2017, and the model accurately reproduces the full age distribution (0 to > 5000 yr) of stored sediment documented by contemporary stratigraphic data.  This calibrated model can accurately represent floodplain storage for improved watershed scale sediment routing computations in the mid-Atlantic region, improving our ability to manage Chesapeake Bay restoration and other important watershed sediment management issues.