bluuebunny/crossref_metadata_2025 huggingface dataset:
Using measured and modelled shear-wave velocity profiles for the assessement of site response in Groningen, the Netherlands
Authors: Kruiver Pauline , Pefkos Manos , Campman Xander , Meijles Erik , van Elk Jan
Published: February 2023

The site response input in the Groningen seismic hazard assessment is based on modelled shear-wave velocity (VS) profiles. Two sets of data were used to compare in situ (field) and model data of VS. The first set consists of data from several blocks of ~ 400 nodes. Inversion of passive seismic data from a coarse grid of ~ 6 km x 10 km resulted in VS profiles to a depth of 800 m and from a denser grid of ~ 1 km x 1 km more detail to a depth of 100 m. The field VS profiles were a combination these two depth ranges. The site response analysis based on either the field or model VS profiles showed on average similar amplification factors over periods relevant for seismic risk. The model VS profiles are therefore a good representation. The second set consists of VS data from MASW surveys on dwelling mounds. The local detailed field VS profiles reach a depth of 18 m. Site response analyses using the full model VS profiles or profiles with the top 18 m replaced by field VS showed that the amplification on dwelling mounds is underestimated significantly, on average by 7 to 28 %. Because of this, a frequency-dependent Penalty Factor has been derived. In the risk calculations, this Factor is to be applied to buildings on dwelling mounds to transform the estimated motions at the ground surface (based on model VS) into motions at the top of the dwelling mound.
Identifying the source of multi-spacecraft SEP events
Authors: Bruedern Maximilian , Dresing Nina , Heber Bernd , Kartavykh Yulia , Kollhoff Alexander , Kühl Patrick , Strauss Du Toit
Published: February 2023

With the launch of Solar Orbiter (SolO) together with STEREO A, and Wind it is again possible to study  multi-spacecraft Solar Energetic Particle (SEP) events within 1 AU. Over the timespan from July 2020 up to June 2022, we identify 44 events for which a significant increase of ∼100 keV electrons has been observed for at least two spacecraft. The maximum longitudinal separation of the two furthest spacecraft ranges from ∼17 to ∼217 degree. SEPs are expected to follow the Interplanetary Magnetic Field (IMF) which in zero-order approximation has the shape of Parker spirals. We investigate two different scenarios to identify the source of the widespread particle observation: (a) Particles are injected over a broad range of longitudes at the source surface without any perpendicular transport, hence by propagating along the IMF SEPs can be detected for distant observers. (b) Particles are injected over a narrow range of longitudes, but are distributed perpendicular to the nominal IMF by perpendicular diffusion. We discard events for which no unambiguously source location (e.g., flare) can be identified, or where an interplanetary coronal mass ejection is present. In order to investigate these scenarios a 2d  SEP transport model is utilized. The simulated data are compared to selected SEP observations. We developed a χ2 minimization code in order to determine the most probable injection and transport parameters.Here, we present our first modeling results for a selected number of multi-spacecraft SEP events involving SolO. Furthermore, we note that the multi-spacecraft event observation can be a result of a combination of case (a) and (b).
Temperature-induced disturbances of the stress-strain equilibrium and their effects on seismic velocities
Authors: Fokker Eldert , Ruigrok Elmer , Trampert Jeannot
Published: February 2023

Subsurface temperature measurements are key to optimizing geothermal power plants and monitoring heat-storage systems. Previous studies showed that time-lapse variations in temperature can be correlated to variations in seismic velocity. Therefore, temperature monitoring through seismic velocity changes should be feasible. In this study, we provide a physical background for the correlation between temperature and seismic velocity changes. We model how temperature changes can disturb the equilibrium between stress and strain, and for specific boundary conditions, we can make a connection to changes in seismic velocity. Ultimately, we can construct a physics-based model of seismic velocity changes due to temperature variations.
Seismic tomography software tools at Barcelona Center for Subsurface Imaging
Authors: Jimenez Tejero Clara Estela , R. Ranero Cesar , Sallares Valenti
Published: February 2023

Seismic methods are one of the most powerful existing geophysical tools to extract information on the structure of the Earth’s subsurface. These techniques continue to be widely used to obtain images of the sediments and crust and to map the variations in physical properties. Particularly the P-wave velocity (Vp) distribution is the most commonly modelled property. The most widely applied seismic method to retrieve velocity models is seismic tomography, using either travel-time information as in travel-time tomography (TTT) or a more complete set of waveform attributes in full-waveform inversion (FWI). Whereas TTT is a robust, moderately non-linear technique providing coarse models, FWI is strongly non-linear and computationally demanding, but with the potential to provide higher resolution models. TTT and FWI are considered to be complementary, so that they are often combined and applied together. TTT is applied first to get a moderate-resolution model, which is then used as an initial model for FWI. In fact, the key to successfully apply FWI to seismic data, is the usage of a kinematically correct initial model, in which simulated and recorded waveforms are not cycle-skipped at the lowest frequency available. On this basis, it is crucial to extract the travel-time information of the refracted waves as accurate as possible. Particularly for marine multichannel reflection seismic (MCS) acquisition systems, where most refractions are masked by reflections and noise, data processing techniques like Downward Continuation (DC) allows to better retrieve refractions, and this is achieved by virtually redatuming streamer field data to the seafloor.  We aim at showing the different user-friendly open source HPC software designed and built in the Barcelona Center for Subsurface Image (BCSI) to process seismic data from marine experiments, recorded by ocean bottom seismometers (OBS) and/or multichannel seismic (MCS) data recorded by towed streamers. The three tools, DC, TTT, and FWI, which can be used independently and/or combined together for a better performance, have the potential to produce high resolution models of the physical properties of the subsurface. While DC software is designed for 2D seismic data, the TTT tool also read 3D data, and allows the joint inversion of Vp, Vs and anisotropic properties for active and passive data, including earthquake relocation. At present, DC and TTT software tools are freely available and the last version updated at GitHub repositories and the FWI tool for 2D data is under development.
Monitoring of atmospheric ammonia (NH3) in Auvergne-Rhône-Alpes region (France): comparison between satellite, ground-based observations, and simulations from a chemistry-transport model
Authors: Tournadre Benoît , Dupont Harry , Pontet Sabrina , Vagnot Marie-Pierre , Cozic Julie , Chappaz Claire , Socquet-Juglard Stéphane
Published: February 2023

Atmospheric ammonia (NH3) is a gaseous precursor of secondary inorganic aerosols, which represent a significant part of concentrations of fine particulate matter PM2.5 measured in the French region Auvergne-Rhône-Alpes (AuRA). Although French State gives an objective for reducing territorial NH3 emissions, ammonia concentrations in ambient air are not regulated. Very few continuous measurement stations exist in France and cover a time range of a few years at most. Ammonia can also be monitored by satellite remote sensing, which offers a better spatial coverage over more than a decade. 

Atmo Auvergne-Rhône-Alpes (Atmo AuRA) is a regional observatory of air quality approved by the French State. Atmo AuRA extends its activities to the use of satellite remote sensing data as an external source of information to test the consistency of its emission cadastres, air quality forecasts and hindcasts and potentially improve them. 

Since 2015, Amo AuRA maintains a station in Lyon with an analyzer measuring continuously NH3 mixing ratios. The association also builds regional emission inventories of air pollutants, including NH3, and runs routinely CHIMERE chemistry-transport model to evaluate and forecast regional air quality. The chemistry-transport modeling can be used to simulate NH3 atmospheric content for given emissions from inventories and be compared with actual measurements. 

In this study, we compare different datasets describing NH3 atmospheric content in AuRA region. Morning in situ measurements in Lyon are compared with NH3 level 2 data of total columns retrieved from the Infrared Atmospheric Sounding Interferometer (IASI), to evaluate their covariations on the period 2016-2021. The temporal consistency between ground measurements and simulations from CHIMERE is also investigated over the same period. Finally, a comparative analysis on CHIMERE and IASI data is done both in terms of spatial distribution and temporal evolution. 
Recent Changes in the Magnitude of Flood-Generation Mechanisms across Africa: Relative Contributions of Climate Change and Decadal Variability
Authors: Eden Jonathan , Dieppois Bastien , Tramblay Yves , Villarini Gabriele
Published: February 2023

African countries are highly vulnerable to floods, with several studies reporting an increase in mortality rate and exposure in recent decades. Therefore, to improve flood forecasting and associated resilience to such natural hazards, a better understanding of the dominant flood-generating mechanisms and their evolution across Africa is of paramount importance. According to a recent study, excess rains on saturated soils in western Africa, and long rains for catchments in northern and southern Africa, are the two dominant mechanisms, contributing to more than 75% of all flood events. While the dominance of flood-generating mechanisms was not reported to change significantly in recent decades, the magnitude of those events may have changed in response to changing rainfall patterns (wetter or drier average conditions) across Africa. Here, we first estimate how much the magnitude of events with excess rainfall on saturated soils and long rains have changed over the last 65 years, before examining the statistical relationship between these changes, globally warming temperatures, and “natural” modes of decadal climate variability (e.g., Atlantic Multidecadal Variability [AMV], Pacific Decadal Variability [PDV]). To do so, we use a non-linear extreme value modelling approach with multiple covariates, applied to multiple observational datasets (e.g., ERA5, REGEN) and large ensembles from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). This study, therefore, contributes to further the understanding of recent flood hazards in Africa, and identifies regions that will likely become more vulnerable to climate change and its decadal variability over the decades to come.
Asynchronous phenological dynamics in a deciduous plantation and their implications for the seasonal and annual carbon dynamics
Authors: Pappas Christoforos , Fatichi Simone , Markos Nikos , Radoglou Kalliopi
Published: February 2023

Forest phenological dynamics shape the underlying biogeophysical processes and impact the carbon balance from the seasonal to inter-annual time scales. Disentangling the phenological phases of the forest components (e.g., overstory and understory), could provide novel insights on ecosystem response to climate change. This quantitative description is particularly important not only for natural ecosystems but could also assist in the design of restoration and reclamation projects. Here, focusing on a deciduous plantation (black locust, Robinia pseudoacacia L.) in a degraded land of Northern Greece and combining multiyear field observations with detailed ecohydrological modeling, we assessed the ecosystem-level carbon dynamics and its individual components from seasonal to decadal time scales. Site-level long-term (>10 yr) biophysical processes were characterized with eddy covariance measurements together with detailed meteorological and soil data. In addition, ecosystem-level phenological dynamics were quantified with timelapse imagery available at the site and satellite remote sensing. These observations were used to parameterize and validate the ecohydrological model T&C which was then used for numerical experiments. Numerical simulations allowed us to disentangle the contribution of the overstory and understory to the overall carbon dynamics at the site, a separation hard to be done by field measurements alone. The phenological phases of the understory (perennial grass) and the canopy (black locust) were found to be asynchronous, with the former reaching its peak in late winter and the latter in late summer. Ground shading by black locust together with drying of the upper soil layer during the summer months lead to the observed mismatch, with grass activity only in winter and early spring. Yet, the asynchrony in the phenological phases of understory and canopy vegetation results in overall ecosystem-dynamics that are non-negligible over winter, despite the deciduous phenology of black locust. Quantitative description of the interplay between phenological cycles of the forest components enhances our process understanding including their interactions and intra- and inter-annual dynamics. Moreover, for species widely used in forest restoration projects, like the black locust, quantifying such interplays, where the forest is more than the tree, it is important for robust carbon balance estimations.
Scenarios for adaptive flood protection alongside the SSPs for improved climate risk assessment
Authors: van Maanen Nicole , Möller Tessa , Lissner Tabea , Schleussner Carl-Friedrich , Lall Upmanu
Published: February 2023

Floods are one of many climate change extremes causing massive economic and non-economic losses and damages. The recent 6th Assessment Report of the IPCC highlights that flooding will be more widespread at 2°C compared to 1.5°C and even more pronounced at higher levels of global warming. To prevent or reduce impacts from flooding, structural measures for flood protection through hard infrastructure are the most common intervention, as they directly manage flood hazards by controlling flow through streams and prevent water overflow. Adaptation options specifically include dikes, flood control gates, weirs, dams, storage and proper waste management. While flood protection could substantially reduce the economic costs of flood events and counts as the most effective adaptation strategy in the water sector to climate change, scenarios for future flood protection are still in their infancy. Consequently, quantitative assessments of climate change (i.e., impact models), which themselves include numerous uncertainties, cannot adequately account for adaptative flood protection in current risk assessments. We propose a Flood Protection Index (FPI) that captures the current level of flood protection across the globe using various data sources. By identifying adaptation-relevant quantitative socioeconomic variables within the framework of the Shared Socioeconomic Pathways (SSPs) and accounting for future climatic risk, we will be able to project five scenarios for flood protection alongside the SSPs. For the first time, we will show how different socioeconomic trajectories could modulate future flood impacts. These scenarios can be included in quantitative assessments of climate change and improve risk assessments in the 21st century.
Lateral and radial viscosity variations beneath Fennoscandia inferred from seismic and MT observations
Authors: Ramirez Florence , Selway Kate , Conrad Clinton , Smirnov Maxim , Maupin Valerie
Published: February 2023

Fennoscandia is continuously uplifting in response to past deglaciation, a process known as glacial isostatic adjustment or GIA. One of the factors that controls the uplift rates is the viscosity of the upper mantle, which is difficult to constrain. Here, we reconstruct the upper mantle viscosity structure of Fennoscandia by inferring temperature and water content from seismic and magnetotelluric (MT) data. Using a 1-D MT model for Fennoscandian cratons together with a global seismic model, we infer an upper mantle viscosity range of ~1019 - 1024 Pa·s for 1 – 10 mm grain size, which encompasses the GIA-constrained viscosities of 1020 - 1021 Pa·s. The associated viscosity uncertainties of our calculation are attributed to the uncertainties associated with the geophysical data and unknown grain size. We can obtain tighter constraints if we assume that the Fennoscandian upper mantle is either a wet harzburgite (1019.2 - 1023.5 Pa·s) or a dry pyrolite (1020.0 - 1023.6 Pa·s) below 250 km, where pyrolite is ~10 times more viscous than harzburgite. Furthermore, assuming a constant grain size of either 1 mm or 10 mm reduces the viscosity range by approximately 2 orders of magnitude. In northwestern Fennoscandia, where a high-resolution 2-D resistivity model is available, the calculated viscosities are ~10 - 100  times lower than those for the Fennoscandian craton because the mantle has a higher water content, and both pyrolite and harzburgite must be wet. Overall, our calculated viscosities for Fennoscandia that are constrained from seismic and MT observations agree with the mantle viscosities constrained from GIA. This suggests that geophysical observations can usefully constrain upper mantle viscosity, and its lateral variations, for other parts of the world without GIA constraints.
Effect of residue management and nitrification inhibitor on N2O and N2 emissions from an intensive sugarcane cropping system in sub-tropical Australia
Authors: Scheer Clemens , Friedl Johannes , Warner Daniel , Rowlings David , Wang Weijin , Grace Peter
Published: February 2023

Sugarcane is typically produced under conditions that are known to stimulate soil denitrification, i.e. high fertiliser inputs in combination with high levels of crop residue (trash) retention and a warm and humid climate, and high levels of fertiliser N losses from intensive sugarcane systems have been reported. However, there is still insufficient reliable data on N2 losses from sugarcane soils based on field measurements since it is inherently challenging to measure N2 emissions against the high atmospheric N2 background. This study investigated the effect of cane trash removal and the use of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) on N2 and N2O emissions on a commercial sugarcane farm in sub-tropical Australia using the 15N gas flux method. Substantial gaseous N losses were observed under current management practice where cane trash retention and N fertiliser application (145 kg N ha-1 as urea) resulted in elevated losses of N2O and N2 from a subsurface N fertiliser band, with more than 50% of these gaseous N losses emitted as N2O. Cane trash retention increased the magnitude of N2O and N2 emissions reflecting overlapping effects of increased soil water content and labile C supply from residues, but had no effect on the N2O/(N2+N2O) ratio. The NI DMPP was extremely effective in reducing overall N2O and N2 losses and also promoted complete denitrification of N2O to environmentally benign N2, with only 4% of total N2O and N2 losses emitted as N2O. This shows that DMPP might be especially effective in reducing N2O emissions from banded fertiliser were localized zones of high NO3- concentration around the fertiliser band are created that are particularly vulnerable to denitrification. Consequently, the use of DMPP in sugarcane systems with banded fertiliser does not only offer environmental benefits by reducing N2O emissions but also substantially reduces overall denitrification losses, providing an effective strategy to improve NUE and reduce N2O emissions for the Australian sugarcane industry.
Towards an automatic segmentation and classification of multi-source point clouds for Arctic to boreal permafrost ecosystem analysis
Authors: Döpper Veronika , Jackisch Robert , Gloy Josias , Rettelbach Tabea , Boike Julia , Grünberg Inge , Nitze Ingmar , Runge Alexandra , Inauen Cornelia , Barth Sophia , Helm Veit , Enguehard Léa , Kleinschmit Birgit , Herzschuh Ulrike , Heim Birgit , Grosse Guido , Kruse Stefan
Published: February 2023

Remotely sensed point clouds provide detailed structural data of landscapes and ecosystem characteristics. Especially in the analysis of forests and topography, this data type has proven its ability to derive relevant quantitative parameters such as biomass or subsidence rates. Arctic and boreal permafrost ecosystems are severely affected by climate change and resulting vegetation shifts, environmental disturbances, and permafrost thaw which lead to rapid changes in these northern environments that can be detected and characterized with point cloud datasets. In recent decades, the amount of point clouds acquired and generated in high-latitude regions by terrestrial (TLS), mobile (MLS), unmanned aerial system (UAS) based (ULS), up to airborne-based (ALS) LiDAR (Light detection and ranging) and Structure from Motion (SfM) has steadily increased. Multi-temporal datasets are available for a wide range of observation targets.The characteristics of the point clouds such as the extent of the area covered as well as the point density and thus the level of detail differ depending on the sensor, method, and the acquisition specifications. To use point cloud data for topographic, morphological, and forestry analysis, segmentation and classification of the point cloud into specific components such as individual trees, stems, foliage, or terrain features is essential. This is a time-consuming manual process and not feasible when addressing large datasets. Several previous analyses showed the potential for machine learning-based semantic segmentation of a single point cloud type, e.g., terrestrial LiDAR (TLS) with identical acquisition mode and sensor. We aim at an automated segmentation of different point cloud types generated by i) TLS, MLS, ULS and ALS as well as ii) SfM using (multi)spectral UAS and airborne image data to enable an analysis of Arctic and boreal permafrost ecosystems. Thereby, we will focus on the following questions:1) How can we reduce the time consuming process of labeling the point clouds?2) Can we train a model for segmentation using all point clouds or does transfer learning lead to better results?3) To what level of detail can we accurately segment and classify the different point cloud types?With this automated segmentation and classification, we aim to open up the possibility of exploiting the information contained in the multitude of point cloud data for a variety of ecological research applications.
Differences in microphysical properties of cirrus at high and mid latitudes from airborne measurements
Authors: De La Torre Castro Elena , Jurkat-Witschas Tina , Afchine Armin , Hahn Valerian , Kirschler Simon , Krämer Martina , Lucke Johannes , Spelten Nicole , Wernli Heini , Zöger Martin , Voigt Christiane
Published: February 2023

Cirrus in mid latitudes (<= 60° N) are often affected by aviation and pollution while cirrus in high latitudes (> 60° N) develop in a more pristine atmosphere. In this study, we compare the microphysical properties of cirrus measured in mid latitudes and cirrus measured in high latitudes. The analyzed properties are: the ice crystal number concentration (N), effective diameter (ED) and ice water content (IWC) of cirrus from in situ measurements during the CIRRUS-HL campaign in June and July 2021. We use a combination of cloud probes covering ice crystals sizes between 2 and 6400 µm. The differences in cirrus properties are investigated with dependence on altitude and latitude and we show that there exist differences between mid-latitude and high-latitude cirrus. An increase in ED and a reduction in N is observed in high-latitude cirrus compared to mid-latitude cirrus.In order to investigate the cirrus properties in relation to the region of formation, we also combine our measurements with 10-day backward trajectories to identify the location of cirrus formation and the cirrus type: in situ or liquid origin cirrus. According to the latitude of cloud formation and latitude of the measurement, we classify the cirrus in three groups: cirrus formed and measured at mid latitudes (M-M), cirrus formed at mid latitudes and measured at high latitudes (M-H) and cirrus formed and measured at high latitudes (H-H). This analysis shows that part of the cirrus measured at high latitudes are actually formed at mid latitudes and therefore influenced by mid-latitude air masses. We discuss the differences of the cirrus properties under this new classification. Our study helps to advance the understanding of upper-tropospheric cirrus properties at mid and high latitudes in summer and the influence of anthropogenic perturbations.
Forecasting discharges through explainable machine learning approaches at an alpine karst spring
Authors: Pölz Anna , Derx Julia , Farnleitner Andreas , Blaschke Alfred Paul
Published: February 2023

Karst springs provide drinking water for approximately 700 million people worldwide. Complex subsurface flow processes lead to challenges for modelling spring discharges. Machine learning (ML) models possess the ability to learn non-linear patterns and show promising results in forecasting dynamic spring discharge. We compare the performance of three ML models of varying complexity in forecasting karst spring discharges: the multivariate adaptive regression spline model (MARS), a feed-forward neural network (ANN) and a long short-term memory model (LSTM). The well-studied alpine karst spring LKAS2 in Austria is used as test case. We provide model explanations including feature attribution through Shapley additive explanations (SHAP), a method based on Shapley values. Our results show that the higher the model complexity, the higher the accuracy, based on the evaluated symmetric mean absolute percentage error of the three investigated models. With SHAP every prediction can be explained through each feature in each input time step. We found seasonal model differences. For example, snow influenced the model mostly in winter and spring. Analyzing the combinations of input time steps and features provided further insights into the model performance. For instance, the SHAP results showed that a high electrical conductivity in recent time steps, which indicates that the karst water is less diluted with precipitation, leads to a reduced discharge forecast. These feature attribution results coincide with physical processes within karst systems. Therefore, the introduced SHAP method can increase the confidence in ML model forecasts and emphasizes the raison d’être of complex and accurate deep learning models in hydrology. This allows the operator to better understand and evaluate the model’s output, which is essential for drinking water management.
Effects of earthworm functional traits on CO2 and N2O emissions from casts
Authors: Zi Yacouba , Dignac Marie-France , Bottinelli Nicolas , Capowiez Yvan , Florio Alessandro , Rumpel1 Cornelia
Published: February 2023

Earthworm species are grouped into three ecological categories, endogeic, epigeic and anecic from their nutritional behaviors, their strategies of morpho-functional adaptations and localization in the soil profile. These earthworms play a major role in the biogeochemical cycling of carbon and nitrogen through their bioturbation activity and cast production that have specific physical, chemical and biological characteristics. They affect the sequestration of soil C through their influence on soil organic matter (SOM) protection processes. However, CO2 and N2O emissions from cast depend on earthworm species with different physical, chemical and microbiological properties even when these species belong to the same ecological category. Hence the importance of investigating their functional traits to see how they affect greenhouse gas emissions. To do this, we measured the emissions of N2O and CO2 in earthworm cast, then we characterized the physical-chemical properties from elemental and spectroscopic analyses. Finally, these results were related to different morphological (pigmentation, color, size), anatomical (gizzard, pharynx, morren's gland size) and physiological traits. Our hypothesis is that the casts of pigmented and colored earthworms, with a large pharynx and gizzard, morren's gland, secreting a lot of mucus and water produce more CO2, N2O.
Hydrological modelling of July 2021 floods in Vesdre and Amblève catchments
Authors: Dessers Christophe , Archambeau Pierre , Dewals Benjamin , Erpicum Sébastien , Pirotton Michel
Published: February 2023

Extreme events as the ones which occurred in July 2021 mostly in Belgium, Germany and the south of the Netherlands are causing important human and material losses. This event broke many records in a meteorological point of view as well as in the behaviour of the rivers, hence it urges several procedures of water and flood management to be revisited or better understood. However, hydrological modelling of such phenomena is challenging as it should cope with historical rain and discharge flow intensities never recorded before in the region but also deal with human construction and behaviour such as dams. Furthermore, most of the measurement devices in the Vesdre river were swept away or damaged during this flood engendering a paucity of reliable data for this catchment.This presentation will focus on the hydrological simulation and a model comparison in the Vesdre and Amblève catchments in Belgium during the episode of July 2021. Both neighbour catchments were among the most damaged and displays anthropogenic characteristics. The former lacks accurate data along the watercourse but chronicles of the water depths and the manoeuvres of the sluice gates in the dams are exploitable to reconstruct the inputs and outputs. While the latter contains a rich database of flow measurements during that period and spatially well distributed to capture all main tributaries in the Amblève.The Amblève river was favoured to perform a calibration of the models and analysis of the evolution of the flow properties along its stream. With this aim in mind, the modular structure of the hydrology package in the WOLF software, developed by the HECE team at the University of Liège, was employed to carry out distributed event hydrology simulations. Semi-distributed optimisations were performed, considering the functioning of the dams. The impact of an increasing complexity of the models and a comparison with celebrated models such as GR4H and VHM was investigated, as well as the effect of the source of rain data and their quality on the results.This study emphasised that, for all models, most of the flow in the surface drained by the dams in the Vesdre was mainly caused by runoff/overland flows. This effect was observed in some subbasins in the Amblève displaying the same types of land uses, but also in more urban areas. Nonetheless, head catchments in the Ambève were mostly composed of groundwater flow. Moreover, it shows the importance of accurately distributed rain and confirms the local character of the phenomenon and its effect on the hydrological properties evolution
The effect of magnetic reconnection on ICME-related GCR modulation
Authors: Davies Emma , Scolini Camilla , Winslow Réka , Jordan Andrew
Published: February 2023

The large-scale magnetic structure of interplanetary coronal mass ejections (ICMEs) has been shown to cause temporary decreases in the galactic cosmic ray (GCR) flux measured in situ by spacecraft, known as Forbush decreases (Fds). In some ICMEs, the magnetic ejecta exhibits a magnetic flux rope structure; the strong magnetic field strength and closed field line geometry of such ICME magnetic flux ropes has been proposed to act as a shield to GCR transport. However, as ICMEs propagate, they undergo many processes including interactions and magnetic reconnection with the interplanetary magnetic field (IMF) in large-scale solar wind structures and other solar transients. In this study, we investigate how ICME interaction and reconnection during propagation affects Fd size, shape, and duration. We hypothesize that the alteration of the ICME magnetic topology due to reconnection (specifically the opening of the closed magnetic field configuration in the ICME flux rope) will have a strong effect on the ICME’s ability to modulate GCRs. To test this hypothesis, we compare the Fds of ICMEs that likely underwent reconnection during propagation with ones that likely did not.To this end, we identify ICMEs that exhibited open magnetic field line topologies (i.e., ones that likely underwent reconnection) and we compare their effects on GCRs with those of ICMEs that exhibited closed topologies (both ends connected to the Sun). We use magnetic field, solar wind plasma, and suprathermal electron pitch angle distribution data at ACE and Wind to select the ICMEs. Furthermore, we use data by the SOPO and McMurdo neutron monitors at Earth to investigate how the magnetic structure of the ICME ejecta modulates the GCRs by comparing the resulting Fds for the selected ICMEs. The results of our study yield new insights into how the modulation of GCRs is affected by ICME evolution and interaction during propagation and whether reconnection of the ICME flux rope weakens its modulation of GCRs.
Wind-driven currents and sea-level variability of the northwest European shelf
Authors: Diabaté Samuel T. , Fraser Neil J. , McCarthy Gerard D.
Published: February 2023

The shelf northwest of Europe is home to subinertial fluctuations in sea level, whose peak-to-peak amplitude reach several tens of centimetres. These weekly-to-monthly shelf-wide sea-level variations feature at the coast, and therefore understanding their drivers is of prime importance for coastal adaptation. These sea-level changes have been previously hypothesized to reflect the strength of the European slope current (Chafik et al., 2017), a wind and density driven quasi-barotropic circulation lying in the region of the 500 to 1000 m isobaths (Huthnance & Gould, 1989). This interpretation has however not yet been validated by in-situ observations. Using data from single-point current-meters and acoustic Doppler current profilers moored west of France, Ireland and Scotland, we show that the common mode of northwest European sea-level changes covaries with along-isobath currents on the shelf and on the upper part of the slope (< 400 m of water depth). However, the pattern of variability is different in the slope current and further off-shelf, , with the correlations between shelf sea levels and in-situ currents decreasing moving down-slope (> 400m of water depth).  We discuss whether or not the relationship between European sea levels and shelf and slope currents emerges from momentum balance associated with the slope current existence (joint effect of winds, baroclinicity and bathymetry). We also discuss the relevance for coastal sea levels and associated coastal vulnerability. Chafik, L., Nilsen, J. E. Ø., & Dangendorf, S. (2017). Impact of North Atlantic teleconnection patterns on Northern European sea level. Journal of Marine Science and Engineering, 5(3), 43.Huthnance, J. M., & Gould, W. J. (1989). On the northeast Atlantic slope current. In Poleward flows along eastern ocean boundaries (pp. 76-81). Springer, New York, NY.
Towards a subgrid momentum closure via stochastic backscatter and its linkages with the Gent-McWilliams parametrization
Authors: Bagaeva Ekaterina , Juricke Stephan , Danilov Sergey , Oliver Marcel
Published: February 2023

Parametrizing physical processes in the ocean is a universal approach to overcome resolution limitations across different scales. Parametrizations represent the mean effect of processes occurring on the scales less than the grid scale (i.e. on the subgrid) on the resolved mean flow through parametric equations. In this work, a viscous momentum closure, equipped with a backscatter operator that returns excessively dissipated energy back to the system, is used to parametrize mesoscale range processes on eddy-permitting mesh resolutions.The part of the variability that is not represented by the deterministic backscatter operator is modelled stochastically. We propose a stochastic field component, based on the patterns of variability extracted from the output of model simulations with different grid resolutions.As a continuation of this work, we propose an interaction of the backscatter parametrization with the Gent-McWilliams parametrization which is generally applied for coarser grids corresponding to non-eddy resolving resolutions. This connection is relevant to link kinetic and potential energy backscatter.The implementations are tested on two intermediate complexity setups of the global ocean model FESOM2: a doubly-periodic channel and a double-gyre box model. In this contribution, we present an increase of eddy activity and show that a greater complexity of setup enhances response to the implementation.  Keywords: mesoscale eddies, parametrization, backscatter, stochastic parametrization, GM parametrization.
Peak Hydrological Event Simulation with Deep Learning Algorithm
Authors: Scherer Nicole Tatjana , Usmann Muhammad Nabeel , Disse Markus , Huang Jingshui
Published: February 2023

Most floods are caused by heavy rainfall events, including the disaster in the Simbach catchment in 2016. For the Simbach catchment, a study was already carried out using the conceptual Hydrologiska Byråns Vattenbalansavdelning (HBV) model to simulate the extreme event of 2016. While the calibration model performance is classified as very good, the overall validation is classified as unsatisfactory. Recent studies showed that data-driven models outperform benchmark rainfall-runoff models. A widely used data-driven model is the Long-Short-Term-Memory algorithm (LSTM). The main advantage of this algorithm is the ability to learn short-term as well as long term dependencies.The objective of this work is to determine if a data-driven model outperforms the conceptual model. For this purpose, in a first step a LSTM model is setup and its results are compared with the results of the HBV model. It is assumed that the LSTM model outperforms the HBV model in training and validation but is not able to simulate the extreme event, because the extrapolation capabilities of Neuronal Networks are poor if they operate outside of their training range. In a second step, it is studied if the model performance can be improved by providing more features to the model. Therefore, different feature combinations are provided to the model. Furthermore, it is assumed that providing more data to the model will improve its performance. Therefore, in a third step more events are used for training and validation.It was concluded that the LSTM model is able to simulate the rainfall-runoff process. A satisfactory overall model performance can be achieved using only precipitation as input data and a small training dataset of four events. But, as the HBV model, the LSTM model is not able to simulate the extreme event, because no extreme event is present within the training dataset. However, the LSTM model outperforms the HBV model, because the LSTM generalizes better. Furthermore, the model performance of the LSTM model using six events can be improved by providing additionally the soil moisture class as input data. Whereas providing more features to the model results in worse model performance. Providing more events to the model does not significantly improve its performance. However, the model improved especially for the event in June 2015. If the model is trained with more events having higher magnitude than the 2015 event, the event in 2015 is no longer classified as an out-of-sample event, resulting in better model performance. Providing the model more events and more input features does not significantly improve the model performance. The results show the potential and limitations using the LSTM model in modeling extreme events.
Result-based carbon farming and multifunctionality
Authors: Thorsøe Martin
Published: February 2023

Enhancing the potential of soils to store more carbon while maintaining existing SOC levels, especially on peatlands and other agricultural soils, is a key lever for mitigating climate change in the LULUCF sector. In late 2022, the European Commission announced a framework for a regulatory framework on carbon removals, which will set standards for future carbon farming activities. To meet the ambitions, the European Commission also emphasises that the forthcoming Common Agricultural Policy (CAP) that comes into effect from January 2023 should increasingly reward farmers environmental- and climate friendly performance through a more result-oriented model. In result-based schemes, payment levels reflect the actual impact of the management practices on carbon stocks (relative to a benchmark), may thus reduce the cost to attain a given environmental benefit.However, designing effective schemes is a complex process, particularly in terms of (1) minimizing costs (of incentives and MRV), (2) and ensuring environmental performance (effectiveness, additionality and additional ecosystem services) and (3) social (fairness, legitimacy and land-user engagement). Further, optimizing schemes only according to the ability to sequester carbon or prevent emissions may lead to sub-optimal outcomes, rather it may be important to move beyond schemes that only optimize on one parameter. The EJP SOIL Road4Schemes project has gathered an inventory containing 170 European carbon farming schemes. While some of the identified schemes focus exclusively on carbon sequestration while other scheme designs support a wider number of ecosystem services. This presentation synthesizes the experience from these 170 schemes regarding opportunities and barriers for designing successful result-based carbon farming schemes that also include additional ecosystem services.
The impact of CO2 and ice sheet changes on the deglacial AMOC sensitivity to freshwater perturbations in three different Earth System Models
Authors: Knorr Gregor , Kapsch Marie , Prange Matthias , Mikolajewicz Uwe , Latinovic Dragan , Merkel Ute , Niu Lu , Ackermann Lars , Shi Xiaoxu , Lohmann Gerrit
Published: February 2023

During deglaciation disintegration of large-scale continental ice sheets represents a continuous threat to reduce the strength of the Atlantic meridional overturning circulation (AMOC) via meltwater perturbations to the northern high latitudes. Nevertheless, an abrupt AMOC recovery is detected half-way through the last deglaciation and  a growing number of studies using Earth System Models (ESMs) of varying complexity have shown that atmospheric CO2 concentrations and ice sheet volume can influence the operational mode of the AMOC, eventually including the coexistence of multiple states and associated threshold behavior for intermediate climate states between full glacial (e.g. Last Glacial Maximum, LGM) and full interglacial (e.g. pre-industrial, PD)  conditions. In this study we present results from coordinated sensitivity experiments conducted as part of the German climate modeling initiative (PalMod), using three complex ESMs (AWI-ESM, CESM and MPI-ESM). Besides differences in the impact of CO2 and ice volume changes, we also investigate how variations in these boundary conditions control the AMOC sensitivity to deglacial meltwater injections in the North Atlantic. We find that the AMOC strength responds to ice sheet and/or CO2 changes in all models, with partly opposing effects.  A similar AMOC strength for PD and LGM conditions is detected in AWI-ESM and MPI-ESM, while CESM shows a weaker LGM AMOC. This weaker LGM state is also characterized by a relatively pronounced AMOC sensitivity to freshwater perturbations. Our inter-comparison experiments suggest that this specific behavior in CESM can be detected for atmospheric concentrations between LGM and intermediate levels of ~220 ppm. This further corroborates in particular the impact of CO2 changes to modulate the trajectory of deglacial climate changes by an alteration of the AMOC susceptibility to meltwater injections as recently suggested (Sun et al., Glob. Planet. Change, 2021; Barker & Knorr, Nat. Commun., 2021).   References:Sun, Y., Knorr, G., Zhang, X., Tarasov, L., Barker, S., Werner, M. and G. Lohmann (2022): Ice sheet decline and rising atmospheric CO2 control AMOC sensitivity to deglacial meltwater discharge. Global and Planetary Change 210. https://doi.org/10.1016/j.gloplacha.2022.10375Barker, S. and G.  Knorr (2021): Millennial scale feedbacks determine the shape and rapidity of glacial termination. Nature Communications 12, 2273. https://doi.org/10.1038/s41467-021-22388-
CO2Image retrieval studies and performance analysis
Authors: Hochstaffl Philipp , Baumgartner Andreas , Slijkhuis Sander , Lichtenberg Guenter , Koehler Claas H. , Schreier Franz , Roiger Anke , Feist Dietrich G. , Marshall Julia , Butz André , Trautmann Thomas
Published: February 2023

Current and planned satellite missions such as the Japanese GOSAT (Greenhouse Gases Observing Satellite) and NASA’s OCO (Orbiting Carbon Observatory) series and the upcoming Copernicus Carbon Dioxide Monitoring (CO2M) mission aim to constrain national and regional-scale emissions down to scales of urban agglomerations and large point sources. The CO2Image demonstrator mission of the German Aerospace Center (DLR) is specifically designed to detect and quantify carbon dioxide (CO2) and methane (CH4) emissions from medium-size point sources. To this end its COSIS (Carbon dioxide Sensing Imaging Spectrometer) push-broom grating spectrometer measures reflected solar radiation with a high spatial resolution of 50x50 m2, covering tiles of ~50x50 km2 extent. The instrument has a moderate spectral resolution of approximately ~1 nm and observes in a single spectral window in the 2 µm region.Here we present and discuss the impact of the expected COSIS performance on the retrieved level-2 data. The level-1 data (spectra) are generated using the Py4CAtS (Python for Computational ATmospheric Spectroscopy) line-by-line radiative transfer model and the COSIS SIMulator (COSIS-SIM). Based on the COSIS instrument parameters the analysis examines the retrieval errors related to noise which allows to estimate the detection and quantification limit of CO2 and CH4 emission rates at the instrument’s spatial and spectral resolution. We further discuss the effect of heterogeneous scenes, i.e. high contrast surfaces that cause an effective distortion of the spectral response function by non-uniform illumination of the entrance slit. Finally, we assess the influence of initial guess values for the plume's vertical extent and shape on the retrieval.