bluuebunny/crossref_metadata_2025 huggingface dataset:
Electric self-potential and electro-magnetic monitoring of hydraulic fracturing experiments in the Äspö Hard Rock Laboratoy, Sweden. 
Authors: Haaf Nadine , Schill Eva
Published: March 2022

At the Äspö hard rock underground laboratory in Sweden, six in situ hydraulic fracturing experiments took place at 410 m depth. A multistage hydraulic fracturing approach is tested with a low environmental impact, e.g., induced seismicity. The idea is to mitigate induced seismicity and preserve the permeability enhancement process under safe conditions. The fractures are initiated by two different injection systems (conventional and progressive). An extensive sensor array is installed at level 410 m, including simultaneous measurements of acoustic emissions, electric self-potential, and electromagnetic radiation sensors. The monitoring catalog includes more than 4300 acoustic emission events with estimated magnitudes from the continuous monitoring setup (in-situ sensors between 1-100 kHz). The experiment borehole F1 is drilled in the direction of Shmin, perpendicular to the expected fracture plane. Two electromagnetic radiation sensors are installed and aligned to (i) Shmin and (ii) the expected fracture plane with a sampling rate of 1 Hz and a frequency range between 35-50 kHz. The self-potential sensors are installed at level 410 with a distance of 50-75 m from the borehole F1, including nine measuring probes and one base probe. A second self-potential setup is deployed at level 280 m in the far-field with a distance of 150-200 m from F1. The self-potential data were measured with a sampling rate of 1 Hz. For the first time (to our knowledge), the results of electric and electromagnetic monitoring of two hydraulic stimulation at meter-scale are presented.
Emergence of compound events: quantifying the importance of marginal and dependence properties changes
Authors: François Bastien , Vrac Mathieu
Published: March 2022

Many climate-related disasters often result from a combination of several climate drivers, also referred to as "compound events''. By interacting with each other, these hazards can lead to huge environmental and societal impacts, at a scale potentially far greater than any of these climate drivers could have caused separately. Marginal and dependence properties of climate drivers, as well as their changes over time, are key statistical properties influencing the probabilities of compound events. A better understanding of how the statistical properties of variables leading to compound events evolve and contribute to the change of their occurences is a crucial step towards risk assessments. Here, based on copula theory, we develop a new methodology to quantify the contribution of marginal and dependence properties to the overall probability of compound events. For illustration purposes, the methodology is applied to analyse changes of probability for compound precipitation and wind extremes, and their potential time of emergence, in a 13-member multi-model ensemble (CMIP6) over the region of Brittany (France). Results show that compound precipitation and wind extremes probabilities from CMIP6 ensembles mostly increase for the end of the 21st century. Yet, the contribution of marginal and dependence properties to these changes of probabilities can be very different from one model to another, reflecting a large uncertainty in climate modelling. These results highlight the importance of both marginal and dependence properties changes for future risk assessments due to compound events, and the need to understand the differences' sources of statistical properties between climate models.  
Dynamic process, influence and triggering mechanism of remolding landform by landslide clusters in South Jingyang Tableland, China
Authors: Hu Sheng , Wang Xingang , Wang Ninglian
Published: March 2022

In recent decades, loess landslides (clusters) induced by agricultural irrigation activities are accelerating the evolution of the loess tableland. However, how loess landslides (clusters) remodel the tableland has not been fully discussed in the previous studies. The lack of such research hinders people’s understanding of the role and mechanism of landslides in the geomorphological evolution of the modern Loess Plateau. In this paper, taking South Jingyang Tableland, Shaanxi Province, China as an example, through remote sensing interpretation, landslide monitoring (including remote sensing satellite monitoring, remote online monitoring and 3D laser scanning), electrical resistivity tomography (ERT) survey, field survey and sampling, geomorphic change detection (GCD) and numerical simulation, we try to conduct multidisciplinary study to reveal the dynamic evolution of landslides (groups) in South Jingyang Tableland and their influence on the tableland landform. This study revealed the temporal and spatial distribution of landslides in the study area and the dynamic change of the tableland edge. It is found that since 1974, the area of the tableland eroded by landslides has reached 221, 320 m2, and the maximum retreat of the tableland edge is 139.6m and the maximum retreat rate is 2.97m/yr. The hydrogeological structure of five profiles was found out by means of ERT surveys, which provides important evidence for identifying the distribution and migration channels of the groundwater. We successfully monitored the processes of three landslides using multi-temporal data of terrestrial laser scanner (TLS) surveys and estimated the impact of these landslides on geomorphic changes. Using the on-line monitoring equipment installed at the top of L3 landslide, we realize that the tilt deformation process of L3 landslide top is not a single linear trend, but a complex deformation process. Finally, we use Massflow software to simulate the movement process of L3 landslide and reconstruct the likely stages of the L3 landslide development. On the one hand, this study provides a reference for the monitoring of landslides in loess tableland, on the other hand, it provides a scientific support for the study of interaction between loess landslides and geomorphic evolution. 
Determination of CME orientation and consequences for their propagation
Authors: Martinic Karmen , Dumbovic Mateja , Temmer Manuela , Veronig Astrid , Vrsnak Bojan
Published: March 2022

The configuration of the interplanetary magnetic field and features of the related ambient solar wind in the ecliptic and meridional plane are different. Therefore, one can expect that the orientation of the flux rope axis of a coronal mass ejection (CME) influences the propagation of the CME itself. However, the determination of the CME orientation remains a challenging task to perform. This study aims to provide a reference to different CME orientation determination methods in the near-Sun environment. Also, it aims to investigate the non-radial flow in the sheath region of the interplanetary CME (ICME) in order to provide the first proxy to relate the ICME orientation with its propagation. We investigated 22 isolated CME-ICME events in the period 2008-2015. We first determined the CME orientation in the near-Sun environment using a 3D reconstruction of the CME with the graduated cylindrical shell (GCS) model applied to coronagraphic images provided by the STEREO and SOHO missions. The CME orientation in the near-Sun environment was determined using an ellipse fitting technique to the CME outer front as determined from the SOHO/LASCO coronagraph. In the near-Earth environment, we obtained the orientation of the corresponding ICME using in-situ plasma and field data and also investigated the non-radial flow in its sheath region. The ability of GCS and ellipse fitting to determine the CME orientation is found to be limited to only distinguishing between the high or low inclination of the events. Most of the CME-ICME pairs under investigation were found to be characterized by a low inclination, and regardless of whether their inclination was high or low, the CME-ICME pairs maintained their inclination during interplanetary propagation. The observed non-radial flows in the sheath region show a greater y-direction to z-direction flow ratio for low-inclination events which suggests that there is a connection between the orientation and propagation of the observed CME-ICME pairs.
Diurnal Variation of Clouds Overshooting Tops Detected by Himawari-8 Satellite and Typhoon Intensity
Authors: Tang Xiaodong , Sun Liangxiao , Zhuge Xiaoyong , Tan Zhe-Min , Fang Juan
Published: March 2022

The diurnal variation of tropical oceanic convection has been recognized for decades. Recent observational studies have also documented a diurnal cycle associated with the upper-level cirrus canopy of tropical cyclone (TC) measured using the infrared brightness temperature from satellites. However, TC canopy clouds are not always coupled tightly with deep convection. The overshooting top (OT) is an appropriate proxy for deep convection with an intense updraft that can penetrate the tropopause, which has an important influence on typhoon intensification. So far, there are no observational evidences for the relationship between diurnal intensity variation and OT occurrences in TC.

We analyze the diurnal variation of OTs within 45 western North Pacific typhoons, using 9003 Himawari-8 satellite images and a unique OT detection algorithm. We examine the distribution of OTs in different types of typhoons in terms of both intensity and intensity change and the relationship between the OTs and typhoon intensification on a diurnal scale. Our results show that a greater OT density occurs in strong typhoons and rapid intensification (RI) typhoons. Moreover, RI typhoons showed greater diurnal variation than non-RI typhoons. The diurnal cycle of OT density in RI typhoons was in phase with the intensification of the typhoon, with the maximum in the early morning. These observational results are consistent with recently published case study simulations of the diurnal radiation effects on TC in both realistic and idealized scenarios. Therefore, OT density can become a potentially effective indicator to estimate diurnal changes in typhoon intensity.
Mapping Ireland’s Surface Water from Space: Comparison of three remote sensing platforms  
Authors: Zhao MinYan , O'Loughlin Fiachra
Published: March 2022

Water plays a vital role in Earth’s ecosystems, hence, the management and monitoring of water resources are significantly important. Ireland has more than 12200 lakes, 3,192 river water bodies including rivers, streams, and tributaries that exceed in total 70,000 km. However, few of them are currently monitored (2% of lake and 1.8% of river). Earth observation (EO) has shown promise in understanding and monitoring water resources. However, the sizes of Ireland’s water bodies have remained a challenge for EO monitoring.

In this research, three different platforms (Landsat 8-OLI, Sentinel-2A and PlanetScope Ortho Scene 3B product) are used to calculate their individual spatial coverage of water bodies across Ireland and quantity their usefulness for water quality monitoring. To explore if water extraction methods impact the results, four different water extract methods (NDWI, NDVI, MNDWI, and AWE have been used to create water masks for Ireland. These water masks created for each platform were then compared with existing map of river network, lakes, and water monitoring stations. The results indicated that AWE’s water mask is the best performing extraction method compared to the existing maps, while the high-resolution platforms (Planetscope and Sentinel-2) clearly outperforms Landsat, Landsat is still able to detect at least 51.90% and 1.63% of rivers. This shows that even the coarser resolution Landsat imagery is useful in monitoring water quality across Ireland.
Compound drought and heatwave identification: daily-scale independent extreme events based on 120-year observations
Authors: Shan Baoying , De Baets Bernard , Verhoest Niko
Published: March 2022

Under the challenge of climate change, the extremes, especially for extreme temperature, are observed at an increasing pace and are expected to be more severe in the future. It is critical to study heatwaves concurrently with droughts because of the intensification of negative impacts, such as exacerbating water shortage, crop failure and GPP reduction, wildfire and tree mortality, etc. This research focuses on compound events of droughts and heatwaves and presents a framework for the identification of drought or heatwave events and their compounds.

While most studies only look at the summer season, we also consider compound drought and heatwave events in the winter season, as these are also important in view of their significant influence on wildfires, insect outbreaks, seed germination, etc.

We introduce the notion of "relative heatwave" as being an extreme event compared with the average of the previous 30-year temperatures for that period. Drought and heatwave events are then identified based on SPI (standardized precipitation index) and SHI (standardized heatwave index). To overcome limitations arising from the scale inconsistency (monthly drought with daily heatwave) and coarse resolution (monthly or weekly drought), we apply the daily SPI and daily SHI, bringing a more accurate measure of the start and end dates, and severity. We also propose an objective, convenient and robust method to identify the statistically extreme and independent drought and heatwave events. Thresholds for removing small-scale events and merging proximate events are found by assuming the severity of the events to follow a generalized extreme value distribution and their arrivals to follow a Poisson process. Finally, we introduce four possible ways of identifying compound events (union, conditioned on drought, conditioned on heatwave, and intersection).

To demonstrate our methodology, we made use of 120 years of daily precipitation and daily average temperature observed at the Belgian meteorological institute in Uccle, near Brussels.
Detection of internal gravity waves by high-pass filtering
Authors: Procházková Zuzana , Kruse Christopher , Kuchař Aleš , Pišoft Petr , Šácha Petr
Published: March 2022

Terrestrial atmosphere supports propagation of various wave types. An important component of the dynamics especially in the middle atmosphere are the internal gravity waves (GWs) that are incessantly being generated from initial perturbations in a stably stratified atmosphere. Horizontal GW wavelengths range from a few to thousands of kilometres. Together with a wide range of temporal and vertical scales, this complicates their global observations and modeling, requiring high resolution model simulations. Subsequent analyses, nevertheless, contain a significant margin of uncertainty originating in the separation of GWs from the background flow, which is often performed by statistical means. In our work, we explore properties of a Gaussian high-pass filter method, using a deep WRF simulation with the horizontal resolution of 3 km in the region of the Drake Passage. Due to the revealed sensitivity of momentum flux and drag estimates to a filter cutoff parameter, we propose a new method that sets the value of the parameter on the basis of the horizontal spectra of horizontal kinetic energy.
The scenic tour of the Venusian magnetosheath by BepiColombo
Authors: Persson Moa ,   BepiColombo and Solar Orbiter Venus subsolar region investigation team
Published: March 2022

The Mercury-bound BepiColombo mission passed by Venus for a second gravity assist maneuver (GAM) on the 10th of August, 2021. During the GAM, the plasma instrumentation on board the two spacecraft Mercury Magnetosphere Orbiter (MMO, JAXA), and Mercury Planetary Orbiter (MPO, ESA), which are stacked together during cruise before orbit insertion at Mercury in 2025, made measurements of the Venusian plasma environment. The entire passage was spent in the Venusian magnetosheath; from the entering of the inbound bow shock at around 12:30 UT, near 8 Rv from the planet, to the exit though the outbound bow shock near the subsolar point at 14:00 UT. This meant that it crossed several different subregions of the magnetosheath, which could be successfully measured and characterised by a combination of the many different plasma instruments on board the MMO and MPO spacecrafts of the BepiColombo mission.

In addition, one day before the Venus GAM for BepiColombo, the Solar Orbiter spacecraft performed a GAM at Venus, with a trajectory after the gravity assist leading upstream of Venus. As a result, the Solar Orbiter provided measurements of the solar wind conditions upstream of Venus during the BepiColombo GAM. Shifting the Solar Orbiter measurements with one hour showed a good correlation between the measurements of the Interplanetary Magnetic Field (IMF) by the two missions (when both were outside of the Venusian bow shock). Therefore, we conclude that Solar Orbiter was connected along the same Parker Spiral arm as Venus during the BepiColombo GAM, and the Solar Orbiter can be used as an upstream solar wind monitor.

Through the combination of the MPPE (Mercury Plasma/Particle Experiment) instrument package onboard MMO, the SERENA (Search for Exospheric Refilling and Emitted Natural Abundances) instrument package and magnetometer onboard MPO, together with the upstream monitor by Solar Orbiter PAS (Proton Alpha Spectrometer) and magnetic field instruments, we have characterized and analysed the subregions of the Venusian magnetosheath. In this presentation we will give an overview of these observations and discuss the larger context of the results.
Earthquake detection in time-series of laser strainmeter measurements as a first step towards automatic signal classification.
Authors: Kasburg Valentin , Breuer Alexander , Bücker Martin , Kukowski Nina
Published: March 2022

Geophysical observatories around the world collect data on various natural phenomena within the Earth and on its surface. Many of these measurements are made automatically, sometimes at high sampling rates, so that enormous amounts of data accumulate over the years. Continuous analysis is important to classify current phenomena and decide which data are important and which can be downsampled later.

At Moxa Geodynamic Observatory, located in central Germany, several laser strainmeters have been installed in subsurface galleries in order to measure strain of the Earth's crust. These instruments run in north-south, east-west, and northwest-southeast directions. Nano-strain rates are determined with a sampling rate of 0.1 Hz almost continuously over distances of 26 and 38 m, respectively, since summer 2011.

Signals of tectonically induced crustal deformation are superimposed by other signals of greater amplitude, e.g., tides, changes in atmospheric pressure, hydrologic events such as heavy rainfall, and earthquakes. Classification of these events is important to better associate jumps in the temporal vicinity and to distinguish anomalies from instrument failures. To avoid time-consuming pattern recognition by hand, algorithms are required to do most of the work automatically. Due to recent advances in the field of artificial intelligence, it is possible to implement time series algorithms that are capable of unifying and automating many steps of data analysis. Although artificial intelligence applications are increasingly used to support data analysis, their use for time series of geophysical origin so far is not widespread outside of seismology.

In this contribution, an approach to automatically detect earthquakes in the strain data using 1D Convolutional Neural Networks is presented, including the generation of artificial training data with time series data augmentation. Also the training process and generation of new training data, based on classification by hand and false predictions of the trained model is described. The 1D Convolutional Neural Networks are able to identify almost all earthquakes in the strain data and have F1 values > 0.99, showing that their application has the potential to significantly reduce the time required in signal classification of observatory time series data.
Performance and limits of a shallow model for landslide generated tsunamis: from lab experiments to simulations of flank collapses at La Montagne Pelée (Martinique)
Authors: Poulain Pablo , Le Friant Anne , Mangeney Anne , Viroulet Sylvain , Fernandez-Nieto Enrique , Castro Diaz Manuel , Peruzzetto Marc , Grandjean Gilles , Bouchut François , Pedreros Rodrigo , Komorowski Jean-Christophe
Published: March 2022

We investigate the dynamics and deposits of granular flows and the amplitude of the generated water waves using the depth-averaged shallow numerical model HySEA, both at the lab- and field scales. We investigate the different sources of errors by quantitatively comparing the simulations with (i) six new laboratory experiments of granular collapses in different conditions (dry, immersed, dry flow entering water) and slope angles, and (ii) numerical simulations made with the code SHALTOP that describes topography effects better than most landslide-tsunami models. In the laboratory configurations, at the limit of the shallow-approximation in such models, we show that topography and non-hydrostatic effects are crucial. However, when empirically accounting for topography effects by artificially increasing the friction coefficient and performing non-hydrostatic simulations, the model is able to reproduce the granular mass deposit and the waves recorded at gauges located at a distance of more than 2-3 times the characteristic dimension of the slide, with an error ranging from 1 % to 25 % depending on the scenario, without any further calibration. Taking into account this error estimation, we simulate landslides that occurred on Montagne Pelée volcano, Martinique, Petites Antilles as well as the generated waves. Results support the hypothesis that large flank collapse events in Montagne Pelée likely occurred in several successive sub-events. This result has a strong impact on the amplitude of the generated waves, and thus on the associated hazards. In the context of the on-going seismic volcanic unrest at Montagne Pelée volcano, we calculate the debris avalanche and associated tsunami for two potential flank-collapse scenarios.
Turbulent intermittency as a consequence of stationarity of the energy balance
Authors: Aumaitre Sébastien , Fauve Stéphan
Published: March 2022

In his seminal work on turbulence, Kolmogorov made use of the stationary hypothesis to determine the Power Density Spectra of velocity field in turbulent flows. However to our knowledge, the constraints that stationary processes impose on the fluctuations of power have never been used in the context of turbulence. Here we recall that the Power Density Spectra of the fluctuations of the injected power, the dissipated power and the energy flux have to converge to a common value at vanishing frequency. Hence, we show that the intermittent GOY-shell model fulfills these constraints on the power as well as on the energy fluxes. We argue that they can be related to intermittency. Indeed, we find that the constraints on the power fluctuations imply a relation between scaling exponents, which is consistent with the GOY-shell model and in agreement with the She-Leveque formula. It also fixes the intermittent parameter of the log-normal model at a realistic value. The relevance of these results for real turbulence is drawn in the concluding remarks.
Multidimensional flood analysis challenges and similarities utilizing linear and non-linear approaches
Authors: Modiri Ehsan , Bárdossy András
Published: March 2022

Partitioning a dataset in multivariate analysis is one of the key points to better understanding the hydrological process. Different regions of a catchment may bring floods variously due to distinct types of floods or their simultaneous occurrence. Therefore, it is needed to determine the spatial extent floods brought together. In a multidimensional space, it is demanding to investigate floods. It is not clear which kind of clustering methods or dimension reduction techniques are appropriate for visualizing initial similarities among measured peaks. Two methods are applied to reduce dimensions and compare their differences in this research. Multidimensional scaling (MDS) and t-distributed Stochastic Neighbor Embedding (tSNE) are the employed models for 55 years of extreme floods in the Neckar catchment. MDS is based on Principal Component Analysis (PCA), which is a linear technique. While tSNE is a non-linear dimensionality reduction method. In theory, tSNE can handle outliers and perplexity and preserve the local structure of data. As a result, compared to the MDS, both methods react similarly in soliciting an additional algorithm to cluster data in 2D space. It is another challenge that has to be investigated in future research. Due to the fatter and heavier tails, the t-student distributions have a greater chance for extreme values than normal distributions. Therefore, tSNE can better visualize data in a high-dimensional space for assessing extreme events. However, these algorithms must be run in different climates and deal with distinct hydrometeorological variables.
Dating individual rainfall-triggered landslides with Sentinel-1 SAR time series: Application to the Nepal monsoon
Authors: Burrows Katy , Marc Odin , Remy Dominique
Published: March 2022

Heavy rainfall events in mountainous areas can trigger thousands of destructive landslides, which pose a risk to people and infrastructure and significantly affect the landscape. Inventories of these landslides are used to assess their impact on the landscape and in hazard mitigation strategies and modelling. Optical and multi-spectral satellite imagery can be used to generate rainfall-triggered landslide inventories over wide areas, but cloud cover associated with the rainfall event can obscure this imagery. This delay means that for long rainfall events, such as the monsoon or successive typhoons, landslide timing is often poorly constrained. This lack of information on landslide timing limits both hazard mitigation strategies and our ability to model the physical landslide triggering processes.

Synthetic aperture radar (SAR) data represent an alternative source of information on landslides and can be acquired in all weather conditions. The removal of vegetation and movement of material caused by a landslide alters the radar scattering properties of the Earth’s surface. Landslides therefore have a signal in SAR imagery and the Sentinel-1 satellite constellation acquires SAR images every 12 days on two tracks globally, offering an opportunity to greatly improve the temporal resolution of individual landslides within an inventory whose trigger is poorly constrained in time, typical in regions with long periods of cloud cover. Here we present methods of using Sentinel-1 SAR amplitude time series to constrain landslide timing. Our approach combines three methods based on the change within the mapped landslide in (i) median amplitude versus the background,  (ii) amplitude spatial variability and  (iii) surface geometry. When applied to triggered landslides of known timing in Japan, Nepal and Zimbabwe, we achieved an overall accuracy of 80% when combining ascending and descending SAR tracks.

Further we apply our methods to inventories of monsoon-triggered landslides in Nepal (from 2015, 2016 and 2017) to decipher the relationship between landsliding and  local hydrometeorological conditions. Specifically, we first analysed the spatial and temporal clustering of timed landslides. Then we calibrated satellite-based rainfall with rainfall and/or river discharge gauges to understand the rainfall intensity over various timescales preceding the landslide occurrence retrieved by our method. We conclude with implications for empirical and physical modelling of monsoon-induced landsliding.
How does North Atlantic Oscillation modify summer urban heat load in Zagreb (Croatia)?
Authors: Nimac Irena , Herceg-Bulić Ivana , Žuvela-Aloise Maja , Žgela Matej
Published: March 2022

Combined with global warming, urban areas are in additional danger of extreme heat due to the well-known urban heat island (UHI) phenomenon. In this study, the effect of the North Atlantic Oscillation (NAO) on urban heat load in Zagreb (Croatia) is investigated using ground measurements from meteorological station Zagreb-Maksimir, as well as an urban climate model MUKLIMO_3. NAO impact in both winter (wNAO) and summer (sNAO) seasons are analysed in terms of indirect (lagged) and direct effects on the urban heat load. The strongest increase in heat load is detected when positive wNAO is followed by negative sNAO, while the opposite situation is associated with heat load decrease. NAO impact is the weakest for situations with the same wNAO and sNAO polarity due to their opposing effects on climate parameters over investigated area. Besides changes in the total heat load, differences in UHI intensity are also found. Results indicate soil moisture as one of potential physical links between NAO and the heat load. The combination of positive wNAO and negative sNAO supports dry and warm conditions over the Zagreb area and vice versa. In situations with extended dry period, green areas experience stronger increase in heat load than densely built-up regions. Therefore, cooling efficiency of vegetation can be modified with NAO through the processes that include precipitation, temperature and soil moisture. This was confirmed by additional modelling experiments considering standardized precipitation evapotranspiration index (SPEI). These findings are additionally confirmed using land surface temperature data from Landsat-8 satellite. Results of this study demonstrate that irrigation of green urban areas should be included in UHI mitigation measures, particularly for situations when seasonal forecasts indicate long-lasting warm and dry conditions.

Nimac, I., Herceg-Bulić, I., Žuvela-Aloise, M. and Žgela, M. (2022), Impact of NAO and SPEI conditions on summer urban heat load – a case study for Zagreb. Int J Climatol. Accepted Author Manuscript. https://doi.org/10.1002/joc.7507
Paleo-gas hydrate distribution associated with hill-hole pair formation in the SW Barents Sea
Authors: Argentino Claudio , Waghorn Kate Alyse , Winsborrow Monica , Bünz Stefan , Panieri Giuliana
Published: March 2022

Today, gas hydrates are predicted to be stable only in the deepest parts of the Barents Sea, however under past glaciations, low pressure, high temperature subglacial conditions would have been an ideal setting for their formation. Multiple studies have documented the storage of methane beneath the Late Weichselian Barents Sea Ice Sheet, and its subsequent release following deglaciation. Furthermore, it has been hypothesised that localised subglacial gas hydrate formation increases frictional resistance at base of the ice and thus may regulate the flow of overlying ice (Winsborrow et al. 2016). This hypothesis has however, never been tested against sedimentological records of paleo-fluid flow and sediment properties.  

Here we present preliminary results on sediment and pore fluid geochemistry from nine gravity cores collected from Ingøydjupet in the SW Barents Sea. These were collected around a hill-hole pair, a glacial landform indicative of variations in subglacial frictional resistance. One of several suggested formation processes is gas hydrate stiffening of subglacial sediments.  

At present, there is a clear difference in methane fluxes between the areas inside the seafloor hole (high fluxes) and the adjacent hill (low fluxes), matching the distribution of a localized subsurface shallow gas accumulation visible in seismic data. Sediment geochemistry revealed a past episode of enhanced upward methane fluxes only recorded in sediments from the hole, resulted in the shoaling of the sulfate-methane transition and precipitation of methane-derived authigenic carbonates (MDAC) with δ13C= -35 ‰. Although the oxygen isotopic composition (δ18O) of MDACs collected from a sediment core in the hole did not show direct evidence for past gas hydrate destabilization, the reconstructed history of methane fluxes as well as the present-day fluxes and subsurface gas distribution support the hypothesis of a differential distribution of subglacial paleo-gas hydrates across the hill-hole pair, possibly controlled by stratigraphic and structural preconditioning.

This research is part of the Centre for Arctic Gas Hydrate, Environment and Climate (CAGE) supported by the Research Council of Norway through its Centres of Excellence funding scheme grant No. 223259.

Winsborrow, M., Andreassen, K., Hubbard, A., Plaza-Faverola, A., Gudlaugsson, E. and Patton, H., 2016. Regulation of ice stream flow through subglacial formation of gas hydrates. Nat. Geosci., 9(5), 370-374.
Five years of ground-based MAX-DOAS measurements in Vienna, Austria: Overview and highlights of the VINDOBONA project
Authors: Schreier Stefan , Richter Andreas , Weihs Philipp , Schmalwieser Alois , Burrows John ,   VINDOBONA Contributors
Published: March 2022

Satellite observations of tropospheric nitrogen dioxide (NO2) form an important basis for estimating the environmental impact of nitrogen oxide emissions and for assessing the impact of atmospheric pollution on human health. There is a great need to evaluate the accuracy of satellite tropospheric NO2 vertical columns by validating these data products against other measurements, for example ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations. Moreover, the conversion of tropospheric NO2 vertical columns to surface NO2 concentrations, which is of great interest for exposure studies, requires new scientific approaches to reduce existing uncertainties.

From 2016 to 2021, the VINDOBONA (VIenna horizontal aNd vertical Distribution OBservations Of Nitrogen dioxide and Aerosols) project was carried out in Vienna, Austria. One major goal of the VINDOBONA project was to improve the spatial representativeness of ground-based MAX-DOAS observations in urban environments by making use of measurements taken simultaneously at three locations in Vienna, each covering a range of azimuth directions. By comparing MAX-DOAS integrated NO2 concentrations along horizontal columns with each other as well as with in-situ NO2 data from local air quality measuring stations, interesting insights into the spatial distribution of NO2 in Vienna was gained. Even more insights and in fact, a higher spatial variability of NO2 on the scale of the city was found from case study-based DOAS horizontal measurements taken on the rotating Café of the Danube Tower. These results highlight the need to refine the colocation of ground-based MAX-DOAS with satellite pixels in future validation activities.

The impact of lockdowns on ambient NO2 pollution during the COVID-19 pandemic as well as the value of MAX-DOAS measurements of other species (formaldehyde, glyoxal, and aerosols), which form the basis of past and ongoing research activities, will also be highlighted.

 

 

 

Acknowledgements: This research has been financially supported by the Austrian Science Fund (grant no. I 2296-N29), the German Research Foundation (grant no. Ri 1800/6-1), and A1 Telekom Austria.
Plasma water quality treatment for SuDS development
Authors: Erfani Rasool , Ciric Lena , Erfani Tohid
Published: March 2022

Sustainable drainage systems (SuDS) design and management can contribute to a healthier and greener urban development. We show how the inclusion of innovative approaches to SuDS namely the plasma engineering can lead to a more effective and less detrimental water quality treatment. The treatment method using Dielectric Barrier Discharge Plasma actuator, can be retrofitted to the current urban setting, it is cheap and provides efficient alternative for water purification and pollution treatment. We present its environmental benefits causing minimal impact to the surroundings while controlling and managing the pollution. We investigate this in both the city and catchment scale contexts.
The new GESLA-3 tide gauge data set and its quality control for tidal studies
Authors: Marcos Marta , Haigh Ivan D. , Talke Stefan A. , Hart-Davis Michael , Dettmering Denise , Woodworth Philip L. , Hunter John R.
Published: March 2022

The Global Extreme Sea Level Analysis (GESLA) dataset contains, in its recently released version 3, a total of 5199 tide gauge records of hourly (or higher) temporal resolution, globally distributed and totalling more than 91000 years of data (www.gesla.org). This represents twice the number of observations compared to the former version of the database. The tide gauge records have been compiled from multiple data providers and so they have different levels of quality controls. Here we describe a set of tools to homogenise and quality control sea level observations from raw GESLA files, including adjustments of datum jumps and time shifts in the time series. We apply these tools to estimate tidal constituents from the extended in-situ dataset. The results are used to identify the river influences on coastal tide gauges and to map the spatial patterns of mean tidal ranges along densely monitored coastlines.
Graph Neural Networks for Reservoir Level Forecasting and Draught Identification 
Authors: Durrant Aiden , Haro David , Leontidis Georgios
Published: March 2022

The management of water resource systems is a longstanding and inherently complex problem, balancing an increasing number of interests to meet short- and long-term objectives sustainably. The difficulty of analyzing large-scale, multi-reservoir water systems is compounded by the scale and interpretation of the historic data. Therefore, to assist in the decision-making processes for water allocation we propose the use of machine learning, specifically deep learning to uncover and interpret relationships in high-dimensional data that can enable more accurate forecasting.   

We explore the problem of reservoir level prediction as a pilot study, comparing traditional machine learning approaches to our proposal of spatial-temporal graph neural networks that embed the topological nature of the water system. The graph convolutional neural network explicitly captures spatial interaction among segments of river within the system. The construction of the graph is as follows: nodes represent the reservoir and river monitoring stations; edges define the characteristics of the river sections connecting these stations (i.e. distance, flow, etc.); multiple states of the aforementioned graph, each at different measurement intervals. We then train the network to predict the water level of a node (reservoir measurement station) from previous time intervals. The proposed network is trained on historic data of the EBRO basin, Spain, from 1981 to 2018, specifically utilizing river and reservoir gauging station flow rate and fill level respectively, with the addition of characteristics defining each component of the water system. 

We validate our approaches over a 4-year period, making predictions across various time frames, showing the robustness to various circumstances, and meeting necessary objective requirements ranging from daily to monthly forecasting. As an extension, we also investigate the use of our predictions to allow for drought identification, demonstrating just one of many use-cases where machine learning can uncover vital information that can lead to better management and planning decisions. 
Soil organic matter as a key controlling variable for methane oxidation in forest soils – microbial analysis and global estimation
Authors: Kang Hojeong , Lee Jaehyun , Oh Youmi
Published: March 2022

Methane (CH4) is over 25 times stronger greenhouse gas than CO2 on a molar basis, and its concentration increases continuously. Its global budget, however, is yet to be constrained, and the greatest uncertainty is associated with natural sources and sinks. Terrestrial ecosystems are known to uptake atmospheric CH4 by a group of microbes known as methanotrophs. Previous studies have noted that the controlling variables for methane oxidation in forest soils are moisture content, temperature and nutrient availability. However, previous estimation on CH4 oxidation in terrestrial soils exhibit great discrepancy between model estimates and field observations. In this study, we measured CH4 uptake rates monthly in temperate pine forests and seasonally in subtropical forests in Korea for 2 years. In addition, soil chemical properties and microbial composition were monitored to reveal the key controlling variable for the uptake rates. Deciduous forests showed the highest CH4 uptake rate followed by mixed forests and the lowest was observed in coniferous forests. Air-filled porosity and the abundance of methanotrophs were correlated with CH4 uptake rate. Our results as well as meta-analysis of 207 measurements from 84 literature showed that soil organic matter (SOM) content significantly correlated with soil CH4 uptake rate at both regional and global scales, indicating that SOM can be a robust controlling factor for CH4 oxidation. We speculate that SOM content affects soil CH4 oxidation via alters air-filled porosity and available carbon source for facultative methanotrophs. The amount of CH4 oxidation in global forests estimated by a model based on SOM content is 22.22 Tg, which far exceeds previous estimation of 17.46 Tg.
On the stability of carbonate-bearing faults at the brittle-to-ductile transition
Authors: Figura Francesco , Giorgetti Carolina , Meyer Gabriel , Violay Marie
Published: March 2022

The majority of the seismic events in the Mediterranean region are hosted in carbonate-bearing rocks at depths representative of the semi-brittle regime. Within this regime, both brittle behavior (i.e. deformation is localized on the fractures and on the faults) and ductile one (i.e. deformation is distributed and accommodated in the rock core) coexist. The influence of this interplay on the nucleation and propagation of seismic events is poorly studied. Up to now, most experimental work has been conducted far from in-situ conditions, mostly at room temperature and low confining pressure.

Here we constrain the frictional behavior of faults in carbonate rocks under conditions relevant for their brittle-to-ductile transition. Velocity-step experiments are performed through the HighSTEPS (Strain, TEmperature, Pressure, Speed) biaxial apparatus installed at EPFL, investigating sliding velocities from 10-6 m/s to 10-2 m/s. Experiments are conducted under different values of confining pressure (Pc 15 MPa and Pc 50 MPa) and normal stress (σn 29 MPa and σn 95 MPa) on the experimental faults, keeping the ratio between them constant (around 2). The local strain field along the fault was measured with strain gauges. The collected data were modeled with rate-and-state friction laws (RSFLs) to define the rate and state parameters relate to the critical condition for fault stability. Moreover, microstructural observations of the post mortem sample were conducted at the SEM, to investigate the deformation mechanisms active during the experiments.

These results shed light on the evolution of rate-and-state frictional parameters with depth, as well as their dependence on the strain partitioning between on-fault slip and bulk-accommodated deformation with increasing depth.
Learning quasi-geostrophic turbulence parametrizations from a posteriori metrics
Authors: Frezat Hugo , Le Sommer Julien , Fablet Ronan , Balarac Guillaume , Lguensat Redouane
Published: March 2022

Machine learning techniques are now ubiquitous in the geophysical science community. They have been applied in particular to the prediction of subgrid-scale parametrizations using data that describes small scale dynamics from large scale states. However, these models are then used to predict temporal trajectories, which is not covered by this instantaneous mapping. Following the model trajectory during training can be done using an end-to-end approach, where temporal integration is performed using a neural network. As a consequence, the approach is shown to optimize a posteriori metrics, whereas the classical instantaneous training is limited to a priori ones. When applied on a specific energy backscatter problem, found in quasi-geostrophic turbulent flows, the strategy demonstrates long-term stability and high fidelity statistical performance, without any increase in computational complexity during rollout. These improvements may question the future development of realistic subgrid-scale parametrizations in favor of differentiable solvers, required by the a posteriori strategy.
The role of fines in the dynamics of just-saturated, inertial column collapses
Authors: Webb William , Turnbull Barbara
Published: March 2022

Debris flows are subaerial, gravity-driven mass movements of water, soil and rocks.  High fluid volume fractions and the presence of a wide particle-size distribution lead to highly heterogeneous flow states, and the mechanisms giving rise to this phenomenology open to debate. For tractable modelling, assumptions around the interaction between grains and fluid must be made, but it is not clear whether those assumptions are reasonable across the wide range of length-scales observed. For example, recent studies have shown that the inclusion of a significant proportion of fine granular material within the flow’s composition limits the dissipation of excess pore pressures. Here we explore the possibility that these crucial pore pressure processes are governed at length scales that might otherwise seem insignificant to the macroscopic flow behaviour. Hence, we aim to provide insight on the underlying mechanisms controlling pore pressure through a scaling analysis describing the idealised scenario of sub-aerial axisymmetric column collapses of just-saturated fluid-grain mixtures. Glass beads provide the prototype for inertial particles within the debris flow, and Newtonian fluids carrying varying mass concentrations of fine kaolin clay particles provide the microscopic processes that can control the pore spaces. A geotechnical centrifuge permits elevated gravitational acceleration that when varied alongside particle size, fluid viscosity and mass concentration of fines, allows a wide parameter space to be explored. Pore pressure measurements from these collapses indicate two competing mechanisms, stemming from drainage related pore pressure dissipation and inertial collision related pore pressure generation. An empirical description of these processes is proposed based on our experimental data. This expression is then implemented to describe the fluid-particle coupling within a multiphase Saint-Venant inspired central-upwind scheme in an attempt to simulate the experimental observations.