bluuebunny/crossref_metadata_2025 huggingface dataset:
High summer precipitation reduces soil methane sink capacity and alters decomposition processes in a mature temperate forest
Authors: Faulkner Katy , Oakley Simon , Hilton Sally , Mason Kelly , Ullah Sami , van der Gast Christopher , McNamara Niall , Bending Gary
Published: March 2022

Climate change is expected to alter global precipitation patterns, with unknown impacts on biodiversity and ecosystem functioning. Temperate forests are one of the largest terrestrial carbon stocks, acting as sinks for greenhouse gases such as carbon dioxide and methane thus playing a major role in ameliorating global warming. Predicted changes to precipitation intensity, duration and timing under future climates are likely to result in the alteration of soil moisture dynamics in forest soils. This will impact soil microbial functions, with shifts from oxic to hypoxic or anoxic conditions which could affect microbial metabolism and microbially-mediated nutrient cycling. The impacts of these changes on the terrestrial carbon balance under current and future atmospheric carbon dioxide levels is currently not known. Here, we use a novel in situ approach to simulate high rainfall in soil mesocosms within a mature temperate oak-dominated (Quercus robur) forest in Staffordshire, UK (Birmingham Institute of Forest Research Free-Air Carbon Dioxide Enrichment facility) where atmospheric CO2 levels are elevated 150 ppm above ambient levels. We show that an 8-week period of elevated rainfall and volumetric soil moisture (~ 30% increase in amended mesocosms vs controls) had significant impacts on soil functioning. The forest soil methane sink was significantly reduced in the high rainfall treated soils by ~ 21-67%, resulting in greater methane accumulation in the atmosphere, with no recovery 4 weeks post-event. Using 16S rRNA amplicon sequencing and qPCR approaches, we show how bacterial and archaeal diversity respond to altered precipitation regimes and show significant changes in the abundance of methanotrophic and methanogenic communities. The activities of soil extracellular enzymes, involved in the breakdown of organic carbon, nitrogen, and phosphorus compounds, were reduced during the high rainfall treatment. Our results demonstrate that important climate feedbacks could occur during modest alterations in precipitation which should be considered in climate models and forestry management plans.
Combination of IGS Real-Time Global Ionospheric Maps at CAS: Method and Analysis
Authors: Wang Ningbo , Zhang Yan , Li Zishen , Li Yang , Krankowski Andrzej
Published: March 2022

Benefiting from the global multi-frequency and multi-constellation GNSS measurements provided by the International GNSS Real-Time Service (IGS-RTS), real-time global ionospheric maps (RT-GIMs) have been generated by the Chinese Academy of Science (CAS), Centre National d’Etudes Spatiales (CNES) and Universitat Politècnica de Catalunya (UPC) since 2017, and late by Wuhan University (WHU) since late 2020. To provide a more stable real-time ionospheric correction stream for precise GNSS application and ionospheric space weather monitoring, an experimental combined RT-GIM has been generated at CAS since late-2021 using real-time streams from CNES, UPC, WHU, and CAS itself. CAS combined RT-GIM streams are transmitted in both RTCM-SSR (IONO01IGS0) and IGS-SSR (IONO01IGS1) standards, which are freely accessible from IGS (products.igs-ip.net:2101) and CAS (cas-ip.gipp.org.cn:2101) casters. Following the motivation for the RT-GIM combination, the method used to generate the CAS combined RT-GIM is described in detail. The performance of CAS combined RT-GIM is validated in both RT-GPS dSTEC and single-frequency precise point positioning (SF-PPP) domains by comparison with the existing combined RT-GIM provided by UPC. CAS combined RT-GIM is presently validated and analyzed for a short period (2-3 months), and the analysis covering different time spans (e.g., different seasons) is being done together with the RT-GIM combination.
Understanding the morphology of Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs)
Authors: Bawaji Shabbir , Alam Ujjaini , Mondal Surajit , Oberoi Divya
Published: March 2022

The solar coronal heating problem has been around for several decades. While it has been well established that magnetic fields are responsible for transporting the energy from the photosphere to the corona, it has been a challenge to understand the details of the energy dissipation processes. One such process was proposed by Parker, who hypothesized that this dissipation occurs through small scale magnetic reconnections happening throughout the corona. While there are several indications that this mechanism may be active, till date direct observation of these small reconnections have not been possible. Hence searching for indirect signatures of these events is very important. One such probable signature was discovered by Mondal et al. (2020), where they demonstrated the presence of ubiquitous impulsive radio emissions in the solar corona during a very quiet time. These emissions are now named Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs). Due to the potential importance of this discovery and its implications, it is crucial that the detection techniques are improved and that we search for these transients in more datasets to confirm/reject their ubiquitous nature. In this work, we have developed a machine learning (ML) algorithm suitable for identifying and characterising the spatial distribution and morphology  of WINQSEs. For morphological characterisation we use 2D Gaussians which are found to  describe the brightness distribution of the majority of these transients very well. Since WINQSEs are expected to be the radio counterparts of the weak reconnections, we expected them to  be essentially unresolved at an angular resolution of 3.5 arcminutes. We find, however, that most of the WINQSEs are resolved by the instrument, though the distribution of their area is very steep. We hypothesise that while intrinsically unresolved, the area of WINQSEs becomes large due to coronal scattering effects. This then also presents the exciting possibility of using WINQSEs to regularly study the nature of scattering close to the Sun, which currently is only possible during solar radio bursts. Here we present a quick overview of our ML algorithm, along with a summary of our results about the morphological properties of WINQSEs, and explore the possibility of using them to study coronal scattering. 
Investigating soil quality indicators of German soils under agriculture using soil information on different spatial scales
Authors: Säurich Annelie , Gerighausen Heike , Möller Markus
Published: March 2022

Soils are effective storage, filter, buffer and transformation systems that remove water, nutrients and pollutants from natural sources and anthropogenic emissions. Due to the habitat, regulatory and utilisation functions, soils are most worthy of protection. Among other things, the United Nations Sustainable Development Goals aim to protect soil and stop and reverse global soil degradation. In Germany alone around 56 ha of soil are damaged partly or completely in their soil functions daily, however, there is a lack of spatially explicit resolution information on the quality of German soils and its losses.

Therefore, the objective of this study is to explore and utilize new sources of information to adapt and improve multiple existing soil quality evaluations and associated indicators. Furthermore, the SDG indicator 15.3.1 ‘Proportion of land that is degraded over total land area’ is to be supported and assessed. Here, the focus lies on land cover, including information on land use, land productivity and soil loss due to land use change, built-up areas and infrastructure expansion. A combination of basic soil, climate, and site-specific data, as well as recent land use data derived from remote sensing (Sentinel-1/2), will be used. The soil quality indicators are determined using different scales of soil data to detect and evaluate possible discrepancies as well as assets and drawbacks of the respective spatial resolution.

The soil quality assessment is based on the estimation of the performance of the landscape budget using six different soil indicators: biotic potential yield, resistance to water and wind erosion, mechanical and physico-chemical filter function and runoff regulation function. Required comprehensive soil information are obtained from three soil maps at different spatial scales: the soil map 1:50,000 of Lower Saxony and the freely available nationwide soil maps of Germany on the scale of 1:200,000 and 1:1,000,000 (BÜK200, BÜK1000). Information of the CORINE CLC 2018 (100 m x 100 m) from the Copernicus Land Monitoring Service are used for land use data. All relevant climatic data originate from the German weather survey (DWD, 1 km x 1 km) and relief parameters are derived from the digital elevation model (DEM, 10 m x 10 m). Subsequently, the high resolution soil indicators (10 m x 10 m) are aggregated with the Site Comparison Method (SICOM) to spatially display the results and identify vulnerable regions. Thereby an area-weighted comparison index is determined for a defined reference unit (e.g. municipality, county) using the area share of comparison levels per reference unit. Results of the soil quality evaluation and their influence by the soil data will be presented for the federal state of Lower Saxony.
The Increase of Sardinian Coastal Erosion and the Historical Climate Change Effects on Wind and Wave Height 
Authors: Piras Riccardo , Montaldo Nicola , Corona Roberto
Published: March 2022

Climate change effects on wave regime are affecting Sardinian beaches and coasts. Sardinia island is in the centre of western Mediterranean basin, and its coasts are mainly under two main opposite winds, the mistral and the sirocco, which affect north-west and south-east coasts of the island respectively. We analysed historical wind intensities and wave heights in Sardinian coasts, for detecting historical trends which can explain the alarming increase of coastal erosion of the island. In this sense, we investigated two case studies located in the two opposite quadrants of Sardinia, the Gulf of Alghero and in the Gulf of Cagliari that are in the North-West and South-East quadrants, respectively. For the wind analysis we used the values of speed and direction of the anemometer stations of Alghero and Elmas (Cagliari), for which long series of data are available. The wind most frequently detected by the station of Elmas is the sirocco, with a linear growth for the period of analysis (1943-2021) with higher values of 3, 4 and 5 m/s for 2 consecutive days of sirocco. On the other hand, in Alghero, for 2 consecutive days of mistral, there is a linear decrease for the analysis period (1957-2021) with values greater than 3, 4 and 5 m/s. For the analysis of wave data in the quadrants of Sardinian coasts we compared the ECMWF, the Copernicus and the SIMAR database. The direction and wave height values from the models were validated with observed data of the buoy wavemeters in the Gulf of Alghero and in the Gulf of Cagliari, which data are available for shorter periods.to. Annual maximum significant wave heights are increasing in both the Gulf of Cagliari and the Gulf of Alghero. In particular, the increase in wave heights is more evident in the last two decades (from 1998 to 2019). The increase of the average sea level and the intensification of extreme events in the South-East quadrant of Sardinia is accelerating the erosion of the wonderful beaches of Nora, Capoterra, Sarroch and Poetto in the Gulf of Cagliari, which reduction was dramatic (up to 70 m). Climate change effects on wind frequency and intensity and wave can affect island tourism, an important source of income for Sardinia, and in the extreme cases is leading to damage to housing, alarming resident population.
Nanoscale apatite inclusions in xenotime: witness of Pb mobility
Authors: Joseph Cilva
Published: March 2022

Nanoscale apatite inclusions in xenotime: witness of Pb mobility

Cilva Joseph1, 2, Denis Fougerouse1, 2, Steven M. Reddy1, 2, Aaron Dodd3, Steven Denyszyn4, David W. Saxey2, William D.A. Rickard2

1School of Earth and Planetary Sciences, Curtin University, Perth, Australia

2Geoscience Atom Probe Facility, John de Laeter Centre, Curtin University, Perth, Australia

3Microscopy and Microanalysis Facility, John De Laeter Centre, Curtin University, Perth, Australia

4School of Earth Sciences, University of Western Australia, Perth, Australia

Discordant ages as measured by 206Pb/238U and 207Pb/235U ratios in various geochronometers are common. Several mechanisms have been proposed to explain discordant ages in different minerals. These include loss of radiogenic Pb, mixing of different age domains within a mineral, and intermediate daughter radioisotope disequilibrium. Xenotime (YPO4) is a geochronometer used to date different geological processes, such as diagenesis, metamorphism, and hydrothermal events. However, xenotime commonly yields small degrees of discordancy (<3%) by high precision geochronology techniques. To investigate the mechanism responsible for slightly discordant xenotime analyses, two ~1000 Ma crystals (z6413 and Y1) from Ontario and Western Australia were analysed using atom probe tomography (APT) and transmission electron microscopy (TEM) which provide sub-nanometre scale chemical and crystallographic analysis of minerals. Both samples have not undergone significant metamorphism (T < 300°C) after crystallisation. Combined APT and TEM results revealed the presence of nanoscale apatite [Ca5(PO4)3(F,Cl,OH)] inclusions and crystal dislocations in the xenotime grains. APT data indicates that the apatite inclusions are rich in radiogenic Pb and that the dislocations are decorated with Ca, Cl and H. Nanogeochronology of xenotime by APT indicate that the apatite inclusions likely formed by exsolution during the cooling of crystals, capturing radiogenic Pb. Dislocations in the crystals may have acted as fast diffusion pathways leading to radiogenic Pb-loss and caused the U-Pb system disturbance.
Cross-validation of a GPU-based wave propagation solver and application to seismic waveform modeling of an M4.6 earthquake in Linthal, Switzerland
Authors: Alvizuri Celso , Alkhimenkov Yury , Podladchikov Yury
Published: March 2022

We cross validate a numerical solver for wave propagation in 3-D elastic media written on Graphical Processing Units (GPUs) against the semi-analytical solver for earthquakes in axisymmetric media, using seismic full moment tensors as earthquakes sources, variable earthquake source durations, and comparing observed with synthetic seismograms. The GPU-based solver is based on a numerical formulation of elastodynamic wave equation and can capture isotropic and anisotropic media. The algorithm simulates wave propagation in elastic media in three dimensions and at very high spatial and temporal resolution, and can compute entire wavefields within seconds (Alkhimenkov et al., 2021). For example, the multi-GPU code for elastic wave propagation can compute the entire wavefield of a 1000^3 model (1 billion grid cells) in 40 seconds. We achieve a close-to-ideal parallel efficiency (98% and 96%) on weak scaling tests up to 128 GPUs by overlapping MPI communication and computations. Seismic full moment tensors are routinely used to model a range of seismic processes, natural and anthropogenic, including earthquakes (shear slip), volcanic events, explosions, cavity collapses, landslides, etc. The analytical solver is based on a Thompson-Haskell propagator matrix for layered axisymmetric media (Zhu and Rivera, 2002), with moment tensors as seismic sources, with seismic sources at depths 10s of km below the surface and seismic stations at distances over 2000 km, and has been successfully used in various earthquake source studies (e.g. Alvizuri et al 2018). We validate the GPU-based wave propagation solver through numerical experiments in homogeneous and in layered media, and with observed and synthetic seismograms for an M4.6 earthquake in Linthal, Switzerland on 2017-03-06 with seismic stations at distances up to 30 km. The seismograms from the numerical solver match the analytic and observed seismograms (within frequencies 0.02-0.10 Hz). In future work we will apply the solver to study earthquake source generation, wave propagation in anisotropic media, and seismic source determination.

References
Alkhimenkov, Y., Räss, L., Khakimova, L., Quintal, B., & Podladchikov, Y., 2021. Resolving wave propagation in anisotropic poroelastic media using graphical processing units (CPUs), J. Geophys. Res., 126, doi:10.1029/2020JB021175.
Alvizuri, C., Silwal, V., Krischer, L., & Tape, C., 2018. Estimation of full moment tensors, including uncertainties, for nuclear explosions, volcanic events, and earthquakes, J. Geophys. Res. Solid Earth, 123, 5099–5119, doi:10.1029/2017JB015325.
Zhu, L. & Rivera, L. A., 2002. A note on the dynamic and static displacements from a point source in multilayered media, Geophys. J. Int., 148, 619–627, doi:10.1046/j.1365-246X.2002.01610.x.
Clarifying the importance of serial correlation and field significance in detection of trends in extreme rainfall
Authors: Farris Stefano , Deidda Roberto , Viola Francesco , Mascaro Giuseppe
Published: March 2022

Rainfall extremes are expected to intensify in a warmer environment according to theoretical arguments and climate model projections. Inferential analysis involving statistical trend testing procedures are frequently used to validate this scenario by investigating whether significant changes in precipitation measurements can be detected. Recent studies have shown that statistical trend tests applied to hydrological data might be misinterpreted if (1) the analyzed time series exhibit autocorrelation, and (2) field significance is not considered when tests are applied multiple times. In this study, these aspects have been investigated using time series of frequencies (or counts) of rainfall extremes derived from long-term (100 years) daily rainfall records of 1087 gauges of the Global Historical Climate Network (GHCN) database. Monte Carlo experiments are carried out by generating random synthetic count time series with the Poisson first-order Integer-valued AutoRegressive model (Poisson-INAR(1)) characterized by different sample size, level of autocorrelation, and trend magnitude. The main results are as follows. (1) Empirical autocorrelations are highly consistent with those exhibited by uncorrelated and non-stationary count time series, while empirical trends cannot be explained as the exclusive effect of autocorrelation; moreover, accounting for the impact of serial correlation has a limited impact on tests’ performance. (2) Accounting for field significance prevents wrong interpretations of results of multiple tests by limiting type-I errors, but it may reduce test power; a careful use of local test outcomes could help identify regions with potentially significant changes where clusters of multiple trends with coherent signs are detected. (3) Statistical trend tests based on linear and Poisson regressions are more powerful than nonparametric tests (e.g., Mann-Kendall) when applied to count time series. Finally, using these methodological insights, spatial patterns of statistically significant increasing (decreasing) trends emerge in central and eastern North America, northern Europe, part of northern Asia, and central regions of Australia (southwestern North America, part of southern Europe, and southwestern and southeastern regions of Australia).
Using Genetic Algorithms to Optimise Genesis Potential Indices for Tropical Cyclone Genesis
Authors: Ascenso Guido , Cavicchia Leone , Scoccimarro Enrico , Castelletti Andrea
Published: March 2022

Tropical cyclones (TCs) are one of the most devastating natural disasters worldwide, in terms of both economic damage ($1100 billion in the last 20 years) and fatalities (210,000 in the last 20 years). The accuracy of TC track and intensity forecasts has been increasing steadily since the 1980s, but it remains difficult to predict how many TCs will form each year and where, as the physical processes that lead to the formation of TCs are still poorly understood. Several Genesis Potential Indexes (GPIs) have been proposed that predict the likelihood of formation and distribution of TC genesis given large-scale factors such as sea surface temperature and air humidity. These indices are constructed as the product of a number (typically 3-5) of dynamic and thermodynamic variables, each of which is assigned a coefficient and an exponent. Such indices serve not only to improve our understanding of TC formation by isolating the variables most linked to it, but also as a guideline for insurance companies and governments of how severe a TC season will be, and to predict how climate change will affect the frequency and severity of TCs in climate model simulations. Nevertheless, current GPIs have large margins of error, especially at the local scale and in terms of interannual variability.

In this work, we explore the search space for this type of index, intended as the space of variables are relative coefficients and exponents that can be used to structure a GPI. We begin by optimizing the coefficients and exponents of the well-known GPI developed by Emanuel and Nolan (ENGPI), and show that a simple genetic algorithm can lead to substantial improvements in spatial correlation between the index and observed data. However, we also show that interannual and spatial correlation may be conflicting objectives which cannot be optimized simultaneously. We then modify the structure of the ENGPI by introducing new variables used in other similar indices, some of which seem to lead to improvements. We then repeat the above experiments using different genetic algorithms, and find that different algorithms converge to different solutions with similar performance, indicating that there are many valid ways to structure a GPI; we offer an interpretation of this finding, which we believe to be relevant for future research. Finally, we show that thermodynamic variables tend to be discarded when optimizing interannual correlation, but not when optimizing spatial correlation; we offer a possible explanation of why this may be.
ML/FOS detection system for drought induced cracks on dikes 
Authors: Aguilar-López Juan Pablo , Duarte-Campos Leonardo
Published: March 2022

Manmade soil-based flood defences are conceived and designed for containing water outside flood prone areas during extreme wet events. However, their reliability is reduced in time due to extreme drought events due to formation of drought induced cracks. While monitoring and maintenance are robustly done by visual expert inspections, they are not sufficiently efficient given the length and heterogeneity of soil retaining defences such as dikes and dams. In the present study, we explore the feasibility of a machine learning based fiber optic sensing system for detecting cracks over heterogeneous soil dikes. The system consists in generating detailed output training datasets from thermal imagery of both cracked and healthy dike soil and combining it with FOS thermal signal for the same exact locations. These datasets were collected during the summer of 2021 in the dike lab testing facility (Flood Proof Holland) from TU Delft in the Netherlands. If successful, the system will allow to use the FOS distributed signal in long dike stretches to detect un-observed cracked locations that present similar FOS signal in space and time. The preliminary results show great potential but it still remains to test it in significantly larger dike stretches and during dryer periods.                 
A time-dependent sliding law for granular till
Authors: Warburton Kasia , Hewitt Duncan , Neufeld Jerome
Published: March 2022

The dynamics of soft-bedded glacial sliding over water-saturated tills are poorly constrained and difficult to realistically capture in large scale models. While experiments characterise till as a plastic material with a pressure dependent yield stress, large scale models rely on a viscous or power-law description of the subglacial environment to efficiently constrain the basal sliding rate of the ice. Further, the subglacial water pressure may fluctuate on annual to daily timescales, leading to transient adjustment of the till.

Here, we construct a continuum two-phase model of coupled fluid and solid flows, using Darcy flow to describe the movement of water through the pore space of the till that deforms according to a granular-inspired rheology. After calibrating our model against steady-state experiments, we force the model with a fluctuating effective pressure at the ice-till interface to infer the resulting relationships between basal traction, solid fraction, rate of deformation, and till flux. Shear dilation introduces internal pressure variations and transient dilatant strengthening emerges, leading to hysteretic behaviour in low-permeability materials.

Our model predicts a time-dependent effective sliding law, with permeability-dependent lag between changes in effective pressure and the sliding speed. This deviation from traditional steady-state sliding laws may play an important role in a wide range of transient ice-sheet phenomena, from glacier surges to the tidal response of ice streams. 
Evaluating the next generation of global flood models in the Central Highlands of Vietnam
Authors: Neal Jeffrey , Hawker Laurence , Savage James , Kirkpatrick Tom , Zylberberg Yanos , Nam Pham Khanh
Published: March 2022

Global flood models have undergone rapid development over the past decade. However, with each new generation of model it is essential to systematically evaluate simulation performance for a range of tests and against multiple sources of data. It is also important to take stock, document lessons learnt and contribute to the formation of better practice and modelling standards in the field. Here we illustrate some of the progress being made in global flood modelling by evaluating the latest 30 m resolution implementation of the LISFLOOD-FP/Fathom global flood model over the Central Highlands of Vietnam, and benchmark it against several previous incarnations of the model.

Two independent data sources are used to evaluate the model. The first of these maps recent flood extents using remotely sensed data from the Sentinal-1 missions and compares them to global flood model outputs of commensurate return periods. The second data set identifies land parcels (properties and agricultural fields) that flooded during the same events from a household survey, where uniquely all household land parcels in four villages were sampled. The independence of the date sets also allowed for cross-validation of the observations.

Substantial simulation enhancements are associated with the transition from SRTM and MERIT DEM’s at 90 m resolution to FABDEM, a version of Copernicus DEM at 30 m with forests and buildings removed. In addition to improvements derived from the DEM, more accurate river location, river width and discharge estimates combined with the inversion of river bathymetry via gradually varied rather than uniform flow theory also have an impact on performance.
Methane point source detection and quantification from high-resolution satellite observations and deep learning methods
Authors: Ruiz Villena Cristina , Boesch Hartmut , Parker Rob , Webb Alex , Barrio Guilló Rocío , Sembhi Harjinder , Joyce Peter , Huang Yahui , Chipperfield Martyn , Gloor Emanuel , Wilson Christopher , Palmer Paul , Lunt Mark
Published: March 2022

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG) in terms of its overall effect on climate radiative forcing. The atmospheric residence time of methane is considerably shorter than that of carbon dioxide, but its warming potential significantly stronger. Methane is produced from natural sources such as wetlands, and as a result of human activities, such as the oil and gas industry. A small number of anomalously large anthropogenic point sources are a major contribution to the total global anthropogenic methane emission budget, thus early detection of such sources has great potential for climate mitigation.

Methane satellite observations are now possible from a number of instruments with very high spatial resolution which allow to map methane emission plumes from individual emission sources.  In this work, we explore the capabilities of three satellites with different specifications, spatial coverage and spatial resolutions ranging from metres (WorldView-3; multi-spectral) to tens of metres (PRISMA; hyperspectral) to kilometres (TROPOMI; hyperspectral). This leads to different capabilities for detecting and quantifying methane point sources that can complement each other.  Thanks to its good coverage, TROPOMI Level 2 XCH4 data (from IUP Bremen) allows to locate areas with methane anomalies which can then be further analysed with targeted PRISMA and WorldView-3 (WV-3) observations to quantify methane emissions from small point sources.

In our work, we use a fast data-driven retrieval algorithm to derive methane column enhancements from PRISMA and Worldview-3, combined with a statistical method to identify methane plumes and the well-established Integrated Mass Enhancement (IME) method to derive emission flux rates. We developed a simulation framework to characterise and test our approach. This makes use of synthetic methane plumes generated with the Large Eddy Simulation extension of the Weather Research and Forecasting model (WRF-LES) that have been embedded into WV-3 or PRISMA images. To further advance the plume detection methods and to allow automatisation, we have developed a deep learning model for WV-3 or PRISMA based on the WRF-LES simulations.

In this presentation, we will describe and characterise our plume detection method for three satellite systems covering a wide range of spatial resolutions and we will introduce our deep learning approach. Both methods have been applied to case studies with a focus on emissions from coal mining in South Africa and Australia which we will use to discuss and contrast the different methods and satellite systems.
A potential near real-time algorithm for CME propagation utilizing heliospheric imaging observations
Authors: Paouris Evangelos , Vourlidas Angelos
Published: March 2022

The estimation of the Coronal Mass Ejection (CME) arrival at Earth is an open issue in the field of Space Weather. We present a new near real-time algorithm based on heliospheric imaging (HI) observations of the CME front as a function of time. First, we transform the front elongation angle into radial distance using basic stereoscopic techniques (i.e. fixed-phi, harmonic mean and self-similar expansion). Then we adopt the assumptions that (1) CME accelerate (or decelerate) from the Sun up to some distance and (2) they move with a constant speed past that distance. This “two-phase kinematics” behavior forms the core of our algorithm. The resulting kinematic profiles provide estimates of the CME Time-of-Arrival (ToA) and Speed-on-Arrival (SoA) at 1 AU. This new tool is tested on a sample of CMEs where stereoscopic views were possible, from the STEREO-A and -B HIs were available. The algorithm is promising with predictions for the ToA of CMEs of the order of ±1 hour and for SoA of ±100 km/s. Our approach is in preparation for a possible future combination of HI data from missions at L5. We will test our method further for cases beyond the 1 AU studying ICMEs which has been spotted also on Mars (1.52 AUs).
Towards a world of machine-readable belowground data: technological innovation brings new challenges to root terminology
Authors: Ostonen Ivika , Burdun Iuliia
Published: March 2022

The estimation of root traits and root growth dynamics is still a major challenge in plant belowground ecology. The urgent need for root data has stimulated the development of methodologies that led to an explosive increase in root trait data in recent years. To understand the challenges raising from rapid innovation, we did a systematic review 157 articles, published from 2000 to 2021, where the root traits measurements were performed using RGB images.  Our goal was to explore 1) how the imaging technologies used in root research have progressed in recent 20-years, 2) what are the dominating sensors and software used for imaging and image processing, 3) what are the challenges on our way towards machine readability of root traits. We discussed our results of the timeline dynamics analysis of root traits measurements based on RGB images, utilised sensors, type of root images and software used for image processing, but also the developments in the national and international collaborations in root research. Finally, and most importantly, we explored what are the most examined functional groups of plants, average number of species included in the study and the age of plants which roots were studied. We identified the most measured root traits and analysed the variety of terms used for definition of root traits. In the light of this, we discussed the challenges in root trait terminology on our way towards machine-readable root data.
Climatology and some dynamic features of inversions in Iceland
Authors: Jónsdóttir Lilja Steinunn , Ólafsson Haraldur
Published: March 2022

It is well known that atmospheric inversions may be decisive for the response of the atmospheric flow to an encounter with mountains.  In the literature, there has indeed been focus on this impact of inversions on the flow, but less focus on the inversions themselves; when, where and why the occur.  In this study, a large set of upper-air data from Iceland is explored to assess the climatology of inversions, and to some extent, the characteristics of the flow associated with statically stable layers in the troposphere.  The data reveal high frequency of tropospheric inversions, typically at 800-900 hPa.  The maximum frequency is from late winter until late autumn, with a minimum in mid-winter.  In the summer, the mean elevation of the inversions is lower than in the late winter and in the autumn.  Inversions in southerly flow are typically associated with moderate baroclinicity and advection of relatively warm airmasses above the inversion.  Inversions in northerly flow do not show this characteristic.   Case studies indicate substantial variability in synoptic-scale flow patterns leading to inversions.
On the statistical analysis of explosive-cyclogenesis over the Mediterranean Sea using ERA5 dataset 
Authors: Carniel Cosimo Enrico , Ferretti Rossella , Ricchi Antonio , Zardi Dino
Published: March 2022

The Mediterranean Sea is a semi-enclosed, fairly temperate, mid-latitude marine basin, strongly influenced by the North-Atlantic atmospheric circulations. A wide variety of cyclogenesis mechanisms are known to develop within this basin, including baroclinic waves coming from the Atlantic, Mediterranean cyclogenesis originating from the cut-off of baroclinic waves, Tropical-Like Cyclones (TLC) and explosive-cyclogenesis (EC). Depending on the cyclone type, the frequency of appearance can vary, ranging from tens per month to 1.5 per year, as in the TLC case. ECs are among the rarest and probably most intense and destructive cyclogenesis events that can develop within the Mediterranean basin; they usually originate at high latitudes, during wintertime, and mainly over the sea, preferring areas with high Sea Surface Temperature (SST) gradients. These events are determined by 12 different parameters, among which the main one is the quick drop of pressure, close to 1hPa/hr for 24 hours, within the eye of the cyclone. ECs formation is an extremely complicated process, and in the Mediterranean basin it is probably driven by air intrusions from the stratosphere and by the presence of Atmospheric Rivers. Starting from the analysis of the EC event called “Vaia Storm”, occurred in the Central Mediterranean Basin on October 29th 2018, and using ERA5 dataset, we firstly conducted a physical and dynamical analysis of the event, by pointing out some recurring characteristics previously highlighted in other works, on both local and synoptic scale. Secondly, we analyzed the results given by the reanalysis model ERA5 regarding the period January 1st 1950 – January 1st 2020, identifying other cyclogeneses with the same features, such as the event on November 4th 1966. On the basis of these information, the return period of the EC events was defined, as well as its statistical distribution and seasonality and correlation with NAO and EA indexes (both strongly negative). Further analysis are currently undertaken to determine correlations with SCAND index and possible SST anomalies in the Central Mediterranean Basin.
Profiling Martian Dust Using PIXL Images
Authors: Henneke Jesper , Pedersen David A. K. , Jørgensen John Leif , Liu Yang , Allwood Abigail C. , Hurowitz Joel , Schmidt Mariek E. , VanBommel Scott J.
Published: March 2022

The Planetary Instrument of X-ray Lithochemistry (PIXL), onboard the Mars 2020 rover Perseverance, is designed to measure the chemical composition of Martian materials with a spatial resolution of around 100 µm. The surface of Mars is notoriously dusty and even thin layers of dust within the measurement frame will impact the instrument signal, potentially leading to misinterpretation of an underlying chemical composition if not appropriately accounted for. Therefore, knowledge about the dust composition, concentration and distribution is important, both when deciding where to perform measurements and in data analyses.

Herein we present methods for generating high precision dust profiles of Martian surfaces by utilizing the Optical Fiducial System (OFS) component of the PIXL instrument. The OFS consist of a Micro Context Camera (MCC) and a FloodLight Illuminator (FLI). The MCC captures images with a resolution better than 50 µm/pixel at the instrument’s nominal distance of 25 mm, directly enabling the optical characterization of dust, and other components, on these surfaces. The FLI is equipped with a total of 24 light emitting diodes (LEDs), in four groups centered at UV (385 nm), Blue (450 nm), Green (530 nm), and NIR (735 nm), enabling multispectral capabilities. This multispectral floodlight capability directly facilitates dust detection by the MCC, and utilizing the precision of the MCC, the spatial distribution of dust is better constrained.

We present dust profile maps acquired by the PIXL OFS on Martian surfaces and present similar results derived from the rover-mounted calibration targets. In demonstrating the quality of the maps produced, we can improve future scientific analyses while furthermore improving the operational efficiency and data quality of the Perseverance mission through the potential future implementation of a closed-loop autonomous dust-avoidance routine, utilizing the macro capabilities of the PIXL OFS.

 

The author recognises the great contribution made by the PIXL Team and the broader Mars 2020 Team.
An Interaction between flood and economy of Yangjae River in socio-hydrology perspective
Authors: Kang Subin , Uranchimeg Sumiya , Cho Hemie , Kwon Hyun-Han
Published: March 2022

Over several years, flood management was concentrated on a physical solution such as building flood control structures like levees or dikes. However, with the increasing term of  “socio-hydrology” within the scientific community, the importance of analyzing the feedback between socio and hydrological systems is drawing attention for effective flood management. Many studies(Di Baldassarre, G et al., 2013; Green, C et al., 2011) have warned about the levee effect, which means increasing vulnerability due to non-occurrence of frequent flooding as a result of flood control structure system. Research to understand such interactions from a sociohydrology perspective is mostly conceptual and limited to qualitative analysis. In this study, we quantitively evaluate the dynamic behavior of a system composed of flood-economy-infrastructure. Sociohydrology model based on the differential equation for dynamic analysis system was used to interpret the Yangjae river flood plain numerically. The results confirmed that excessively built flood control structure systems increased flood risk and hindered economic growth.
Multi-analytical approach to investigate sources of dissolved organic matter in a peri-urban watershed
Authors: Boukra Amine , Masson Matthieu , Brosse Corinne , Richard Loïc , Sourzac Mahaut , Parlanti Edith , Miège Cécile
Published: March 2022

Dissolved organic matter DOM corresponds to a complex mixture of molecules and macromolecules playing a major role in terrestrial and aquatic biogeochemical process. DOM heterogeneous composition allows it to have innumerable interactions with organic and inorganic compounds, affecting both their bioavailability and mobility in the environment. At the watershed scale, there are many sources of DOM towards the river such as diffuse inputs by leaching of different types of soils (e.g. forest, meadows, crops, urban impermeable areas...) or urban point inputs (storm overflows, WWTP discharges, stormwater discharges....). However, the influence of of all these sources on the composition of the aquatic DOM remains poorly understood to this day.

In this context, the main objective of this study was to build a methodology to detect the different sources of DOM in the rivers. Using a detailed characterization of DOM, the aim was to identify physicochemical markers and construct source-specific fingerprints. For this purpose, approximately 150 samples were collected from natural and anthropogenic sources of DOM (forest, agricultural, wastewater and urban runoff). All samples were analyzed using an innovative approach based on the use of a wide range of analytical techniques: dissolved organic carbon measurement, optical properties (UV-Visible, 3D fluorescence, size exclusion chromatography coupled with UV-fluorescence detection) and molecular composition (high-resolution mass spectrometry coupled with liquid chromatography). A large amount of data has been generated, and processed by classical (Anova, TukeyHSD) and multivariate (PCA, MFA, DFA) statistical approaches.

The results obtained allowed highlighting optical and molecular markers relevant for the identification of the selected sources. These markers inform on specific characteristics of DOM, such as the size of the molecules, the aromaticity content, the degree of humification, polarity and reactivity. In addition, complementarities and redundancies between optical and molecular characterization techniques is investigated. This research also contributes to select relevant markers for geochemical tracing models.
Geomorphology of the Mabahiss Deep area, Northern Red Sea: New insights from high-resolution multibeam bathymetric mapping
Authors: Fittipaldi Margherita , Trippanera Daniele , Augustin Nico , van der Zwan Froukje M. , Petrovic Alexander , Metz Dirk , Jónsson Sigurjon
Published: March 2022

The Red Sea is a unique place to study a young oceanic rift basin and the interplay between magma and tectonics at a young divergent plate boundary. The spreading rate of the Red Sea rift changes from ~17 mm/yr in the south to ~7 mm/yr in the north, and so does the morphology. The southern Red Sea is a continuous and well-developed oceanic rift, whereas the so-called deeps characterize the central portion with oceanic crust separated by shallower inter-trough zones, and the northern part contains more widely spaced deeps with extensive areas covered by sediments in between. While the central Red Sea morphology has been extensively studied, the structure of the northern Red Sea and its link to the central Red Sea are less clear. Indeed, the northern Red Sea rift, marked at its southern end by Mabahiss Deep, is offset by about 60 km to the central Red Sea axis by the still poorly understood Zabargad Fracture Zone.

Here we aim to improve the understanding of the volcano-tectonic setting of the Mabahiss Deep area with new high-resolution bathymetric data from multiple multibeam surveys with R/V Thuwal and R/V Pelagia. Our results show that the 15 km long, 9 km wide, and 2250 m deep Mabahiss Deep, and the 800 m high and 5 km wide central volcano, are the most prominent structures of the area. The deep is bordered by a series of Red Sea parallel normal faults on both sides, forming a graben-like structure and thus suggesting a rift-like morphology. The central volcano has a 2 km wide summit caldera containing several volcanic cones. Several normal faults cut its southern flank, and radial fractures are present on its summit. In the multibeam backscatter data, several recent lava flows (<10 kyrs) are visible on the northern and southern flanks of the volcano. Even if the ocean floor outside the deep is mainly covered by salt flows, limiting structural analysis of the surrounding areas, the Mabahiss Deep area and the central Red Sea have similar rift-like structures with stable axial MORB-volcanism, showing typical features found at other (ultra-)slow-spreading ridges, such as magma focusing on the segment centers. This suggests that although the Mabahiss Deep appears to be offset from the central Red Sea rift, the same processes are probably taking place in this area.

Our new high-resolution bathymetric mapping allows a more precise structural and geomorphological analysis of the Mabahiss Deep area that represents a starting point for understanding the overall structure of the poorly studied northern Red Sea.
Effect of regional heterogeneities on inversion stability and estimated hydraulic properties field
Authors: Jourde Hervé , Aliouache Mohammed , Fischer Pierre , Wang Xiaoguang , Massonnat Gerard
Published: March 2022

Hydraulic tomography showed great potential on estimating the spatial distribution of heterogeneous aquifer properties in the last decade.  Though this method is highly performant on synthetic studies, the transition from an application to synthetic models to real field applications is often associated to numerical instabilities. Inversion techniques can also suffer from ill-posedness and non-uniqueness of the estimates since several solutions might correctly mimic the observed hydraulic data. In this work, we investigate the origin of the instabilities observed when trying to perform HT using real field drawdown data. We firstly identify the cause of these instabilities. We then use different approaches, where one is proposed, in order to regain inverse model stability, which also allows to estimate different hydraulic property fields at local and regional scales. Results show that ill-posed models can lead into inversion instability while different approaches that limit these instabilities may lead into different estimates. The study also shows that the late time hydraulic responses are strongly linked to the boundary conditions and thus to the regional heterogeneity. Accordingly, the use on these late-time data in inversion might require a larger dimension of the inverted domain, so that it is recommended to position the boundary conditions of the forward model far away from the wells. Also, the use of the proposed technique might provide a performant tool to obtain a satisfying fitting of observation, but also to assess both the site scale heterogeneity and the surrounding variabilities.