bluuebunny/crossref_metadata_2025 huggingface dataset:
RISKNOUGHT: Stress-testing platform for cyber-physical water distribution networks
Authors: Nikolopoulos Dionysios , Moraitis Georgios , Bouziotas Dimitrios , Lykou Archontia , Karavokiros George , Makropoulos Christos
Published: March 2020

Emergent threats in the water sector have the form of cyber-physical attacks that target SCADA systems of water utilities. Examples of attacks include chemical/biological contamination, disruption of communications between network elements and manipulating sensor data. RISKNOUGHT is an innovative cyber-physical stress testing platform, capable of modelling water distribution networks as cyber-physical systems. The platform simulates information flow of the cyber layer’s networking and computational elements and the feedback interactions with the physical processes under control. RISKNOUGHT utilizes an EPANET-based solver with pressure-driven analysis functionality for the physical process and a customizable network model for the SCADA system representation, which is capable of implementing complex control logic schemes within a simulation. The platform enables the development of composite cyber-physical attacks on various elements of the SCADA including sensors, actuators and PLCs, assessing the impact they have on the hydraulic response of the distribution network, the quality of supplied water and the level of service to consumers. It is envisaged that this platform could help water utilities navigate the ever-changing risk landscape of the digital era and help address some of the modern challenges due to the ongoing transformation of water infrastructure into cyber-physical systems.
Radiocarbon dating of various pyrogenic carbon pools in series of buried Podzols (case study from the north of European Russia)
Authors: Zazovskaya Elya , Petrov Dmitry , Dolgikh Andrey , Mergelov Nikita
Published: March 2020

Pyrogenic carbon constitutes a significant portion of organic carbon in soils of the planet, and in some soils its share raises to 30%. The charcoal-rich archives of forest paleofires are often localized in the geomorphological traps that reveal numerous profiles of pyrogenic soils buried due to the repeated post-fire episodes of erosion and accumulation. The paleokarst and active karst landscapes provide a unique matrix that records pyrogenic and depositional events of the past at the local scale. Polypyrocyclical Podzols of the karst landscapes at the north of the Arkhangelsk region (Russia) are the objects of this study. The fields of closed karst funnels (n x 10 m in diameter, 1–5 m elevation difference) demonstrate accumulative and denudation models of soil formation that are realized at the close distance with the pyrogenic soil archives of the bottoms, slopes and high flat sides of the funnels complementary to each other. This regular grid of archives contains information on pyrogenic events and stages of soil formation throughout the Holocene. We report and discuss here 42 radiocarbon dates (AMS) obtained both for the charcoal material and the total organic carbon (TOC) of the soil organic matter. The 14C age (conventional) of charcoal from the lowest horizons was as old as 9115±30 BP - 8770±30 BP, and the charcoal material of the top pyrogenic horizons was as young as 325±20 BP - 45±20 BP. The 14C age of the soil TOC was in general younger than the age of charcoal enclosed in this soil material. We combine the study of soil horizons morphology and stratigraphy with the set of 14C data to experiment with the several age-depth models explaining post-pyrogenic sedimentation rates on various geomorphological elements of the karst landscape. This study is supported by the Russian Foundation for Basic Research, Project No. 19-29-05238.
River morphological changes detection from drone and radar satellite data
Authors: Marchetti Giulia , Asaro Francesco , Bizzi Simone , Mariani Stefano , Lastoria Barbara , Comiti Francesco , Prati Claudio
Published: March 2020

The identification and quantification of morphological changes occurring in the river channel over time are essential to understand rivers behaviour, assess sediment budgets, evaluate effectiveness of river management strategies and support the production of natural risk map. Recently, river science has made a breakthrough thanks to emerging remote sensing technologies and today we can rely on an unparalleled amount of data, at spatial and temporal resolution not available in the past. This has opened new perspectives for river monitoring and fluvial survey practices, allowing to cover areas up to the catchment scale and get information almost in continuum. This research aims to investigate the potential of radar satellite data collected from Sentinel 1 mission to infer information about rivers morphodynamics processes (such as erosion and deposition), that may occur on medium-large river (e.g., active channel width > 50 m) after a flood that caused significant morphological adjustments. Drone and satellite data were collected in September 2017 and September 2018 on a selected site along the Po river, in northern Italy, characterized by a large exposed sediment bar. In March 2018 a flood caused an avulsion and a new secondary channel was opened. We used the sequential drone acquisitions to generate a Dem of Difference, that revealed geomorphic changes of the monitored sediment bar up to 2 m erosion and 1.5 m deposition. We then exploited the radar data of Sentinel 1 and conducted a seasonal analysis using both the coherence data between image pairs and the backscattered radar signal, by investigating the variability of the radar signals through the year and the correspondent condition of the bar. Results show that there is a significant correlation between morphological changes occurred in the site and the associated values of both the amplitude and the coherence of the radar data pre and post the event that caused the morphological changes measured. Further studies are needed to better discriminate the different contributions to changes in amplitude and coherence driven by soil water content, vegetation, sediment size, atmospheric condition for the various time windows analysed. Despite that, these initial evidences are encouraging and new applications to other sites and flood events are planned because these results prove the sensitiveness of the radar signal to geomorphic events. Even simply the ability to detect where channel morphological processes are occurring and their expected intensity through Sentinel 1 data would allow to prioritize more detailed field campaigns by, for instance, UAV technology providing a notable advance compared to the current ability to monitor river morphological changes on large scale.
Self-limiting atmospheric lifetime of environmentally reactive elements in volcanic plumes
Authors: Ilyinskaya Evgenia , Mason Emily , Wieser Penny , Holland Lacey , Liu Emma , Mather Tamsin A. , Edmonds Marie , Whitty Rachel , Elias Tamar , Nadeau Patricia , Schneider David , McQuaid Jim , Allen Sarah , Oppenheimer Clive , Kern Christoph , Damby David
Published: March 2020

Volcanoes are a large global source of almost every element, including ~20 environmentally reactive trace elements classified as metal pollutants (e.g. selenium, cadmium and lead). Fluxes of metal pollutants from individual eruptions can be comparable to total anthropogenic emissions from large countries such as China.

The 2018 Lower East Rift Zone eruption of Kīlauea, Hawaii produced exceptionally high emission rates of major and trace chemical species compared to other basaltic eruptions over 3 months (200 kt/day of SO2; Kern et al. 2019). We tracked the volcanic plume from vent to exposed communities over 0-240 km distance using in-situ sampling and atmospheric dispersion modelling. This is the first time that trace elements in volcanic emissions (~60 species) are mapped over such distances. In 2019, we repeated the field campaign during a no-eruption period and showed that volcanic emissions had caused 3-5 orders of magnitude increase in airborne metal pollutant concentrations across the Island of Hawai’i.

We show that the volatility of the elements (the ease with which they are degassed from the magma) controls their particle-phase speciation, which in turn determines how fast they are depleted from the plume after emission. Elements with high magmatic volatilities (e.g. selenium, cadmium and lead) have up to 6 orders of magnitude higher depletion rates compared to non-volatile elements (e.g. magnesium, aluminium and rare earth metals).

Previous research and hazard mitigation efforts on volcanic emissions have focussed on sulphur and it has been assumed that other pollutants follow the same dispersion patterns. Our results show that the atmospheric fate of sulphur, and therefore the associated hazard distribution, does not represent an accurate guide to the behaviour and potential impacts of other species in volcanic emissions. Metal pollutants are predominantly volatile in volcanic plumes, and their rapid deposition (self-limited by their volatility) places disproportionate environmental burdens on the populated areas in the immediate vicinity of the active and, in turn, reduces the impacts on far-field communities.

Reference: Kern, C., T. Elias, P. Nadeau, A. H. Lerner, C. A. Werner, M. Cappos, L. E. Clor, P. J. Kelly, V. J. Realmuto, N. Theys, S. A. Carn, AGU, 2019; https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/507140.
Soils of abandoned industrial wastes disposal sites: properties, processes, functioning
Authors: Zamotaev Igor , Telnova Natalia , Alexandrovskiy Alexander , Gracheva Raisa , Dolgikh Andrey , Karelin Dmitry , Konoplyanikova Yulia , Mikheev Pavel , Dobrianskiy Alexander , Belova Eleonora
Published: March 2020

Soils formed at once abandoned and recultivated industrial waste dumping sites are key research objects both as models of soil-forming processes in underdeveloped soils and indicators of persistent or potential environmental hazards of dumps themselves. Our studies of technogenic surface-like soil formations (TSF) and soils were conducted on a closed landfill and two abandoned filtration fields from sugar factories  in Kursk region, central part of European Russia.

Key properties of TSF and soils were defined with the assessments of their ecological, microbiological state and gas-geochemical condition. Set of methods (mesomorphological and micromorphological analysis, soil chemical and physico-chemical analysis, comparatively geographical method) was used for the detection of current elementary soil processes. Seasonal dynamics of carbon dioxide, methane and nitrous oxide emissions from soils to the atmosphere was also under consideration. Main used methodology is a research of sustainable properties of soil solid-phase (“soil memory”) together with soil functioning.

Long-term time series of high-detailed remote sensing data (from archive aerial photos of 1950s to actual satellite images and UAV optical photogrammetry) provided the possibility for the retrospective remote monitoring of the all abandoned dumps in study and reconstruction of their life cycles and land cover patterns.

As a result for the three industrial waste dumping sites of different types and the varying age of abandonment and recultivation history there were elaborated schemes of chrono-functional zoning. Each chrono-functional zone is characterized by the specific set of TSF and soils. Among them, it was described technogenic surface-like soil formations of closed landfill, calcareous technosols with several thick organic layers at the bottom of abandoned field filtration cells, calcic anthrosols of field filtration cells spontaneously used for agriculture after the abandonment of sugar factories.

The study is financially supported by RFBR project № 19–29–05025–mk.
Aerosol Chemistry and Effects in the Anthropocene
Authors: Carmichael Gregory
Published: March 2020

Atmospheric aerosols impact air quality and human health. They also play a key role in the Earth’s weather and climate systems.  Aerosol amounts and physical and chemical properties determine their toxicity, radiative and microphysical impacts. Recent advances in observations and models are significantly enhancing our ability to quantify the distribution and properties of aerosols, understand their impacts on atmospheric radiation and cloud distributions and properties, and their presence near the Earth’s surface and the resulting impacts to human health. There is a need for closer integration of aerosols into numerical prediction systems. The World Meteorological Organization has set a strategic goal to advance earth systems modeling to enhance seamless prediction of environmental, weather and climate services across spatial and temporal scales. In this talk the need for this approach and the opportunities and advances will be discussed.
Ice-jam floods modeling in frameworks of intelligent system for river monitoring
Authors: Krylenko Inna , Alabyan Andrey , Zelentsov Viacheslav , Belikov Vitaly , Sazonov Alexey , Pimanov Ilya , Potriasaev Semyon
Published: March 2020

This paper presents the research results related to the development of an intelligent system for monitoring and assessing the state of natural systems (PROSTOR), which was tested in the area from the city of Velikiy Ustyug to the city of Kotlas on the Northern Dvina River. It is one of the most vulnerable places in Russia to spring snow-melt and ice-jams induced floods.

The proposed automated flood forecasting technology is based on the concept of a multi-model description of complex natural objects implementing a mechanism of the selection and adaptation of parameters of the most adequate model for each specific situation. The computational core of PROSTOR is the two-dimensional hydrodynamic model STREAM_2D and its newer version STREAM_2D_CUDA based on the numerical solution of the shallow water equations with discontinuous bottom. Additional hydraulic resistance due to the ice roughness and decrease in the flow cross-section due to ice-caused congestion were taken into account for modeling the ice-jams water levels. The forecasting capabilities of the system are secured by the prediction of water levels at the gauging stations located upstream from Velikiy Ustyug basing either on neural networks, or by means of linking with the runoff formation model ECOMAG and using prognostic meteorological information.

The system was built with the use of a service-oriented architecture, that provides flexible interaction between software modules, implementing hydrodynamic and hydrological models; modules of collecting and processing of heterogeneous data, including data from gauging stations and remote sensing data; control modules, etc. All system components are realized as web services and can be geographically distributed and localized in various organizations, cities and countries. All results of the system implementation, including the results of flooded zones calculations, flow parameters there, as well as satellite images are available via the geoportal.

Models parameters were justified on the base of numerical experiments and simulations of the floods of 1980-2016 period, including more than 18 significant cases of ice-jamming. Grouping of model parameters according to the height of the ice-jam induced water levels suggested for the implementation of the hydrodynamic model incorporated into intelligent information system of river floods monitoring. Operational flood forecasting mode of the system was tested during 2017 – 2019 years under support of Russian Science Foundation project № 17-11-01254.
MoMo’s prediction of Mars’ ionosphere contribution to InSight RISE Doppler data
Authors: Le Maistre sebastien , Bergeot Nicolas , Witasse Olivier , Blelly Pierre-Louis , Kofman Wlodek , Peter Kerstin , Dehant Veronique , Chevalier Jean-Marie , Karatekin Ozgur
Published: March 2020

The NASA InSight mission is operating from the surface of Mars for more than a year. RISE (for Rotation and Interior Structure Experiment) is one of the scientific payloads of InSight. This radio-science experiment consisting in an X-band transponder and two horn-antennas enabling two-way coherent radio-link between Mars and the Earth [Folkner et al., 2018]. The main goal of RISE is to measure the slight modulations of the nutational motion of the spin axis of Mars induced by the liquid core of the planet in order to constrain its interior structure and core properties. To increase our chance to achieve this challenging goal, we must calibrate the RISE Doppler data by accounting to 2nd order effects like the Mars atmospheric noise.

This study shows the predicted contribution of the Martian ionosphere to the RISE data collected so far. To do so, we use a new empirical model of the Mars’ ionosphere called MoMo [Bergeot et al. 2019]. This model is based on the large database of Total Electron Content (TEC) derived from the subsurface mode of the Mars Express MARSIS radar. The model provides the vertical TEC as a function of solar zenith angle, solar activity, solar longitude and the location. Using MoMo, we produce vTEC maps for Mars that are then used to estimate the slant TEC in the Earth line of sight, enabling to infer the phase delay and Doppler shift affecting the RISE X-band measurements. These computed effects are shown to be of the order of 10-3mm.s-1 in Doppler observables, with a larger effect around sunrise and sunset. This is about one order of magnitude below the typical measurement noise of RISE, but it is comparable to the contribution of the liquid core in the Doppler (~10-3-10-2mm.s-1).

The MoMo model is suitable for any Mars radio-science data calibration, and in particular the forthcoming ExoMars 2020 LaRa measurements [Dehant et al. 2019]. The predictions made with MoMo will be of great use either for the data corrections or to define the timing of observations in order to avoid operating when the TEC rapidly varies (i.e. close to sunrise and sunset). The model output is further discussed here in terms of climatologic behavior of the Mars’ ionosphere. For comparison, we also investigate the contribution of the Earth ionosphere using Global Ionospheric Maps (GIMs) based on GNSS data.
Spatial heterogeneity of CO2 emission in Hungarian and Croatian arable fields – preliminary results
Authors: Toth Eszter , Dencső Márton , Gelybó Györgyi , Mészáros János , Bakacsi Zsófia , Horel Ágota , Josip Telak Leon , Galic Marija , Kisic Ivica , Bogunovic Igor
Published: March 2020

The aim of this study was to investigate the spatial heterogeneity of CO2 emission of two different croplands in Croatia (Šašinovec, 45° 50´ N; 16° 11´ E; soil type - Stagnosols) and in Hungary (Józsefmajor, 47° 40´ N; 19° 36´ E; Chernozems). The measurements of the soil water content (SWC), soil temperature (Ts), organic matter (OM) and CO2 flux was executed after the harvest of the soybean in both fields. In a regular grid (2 x 2 m and 2 x 3 m) 44 and 170 samples were collected from Croatian and Hungarian site, respectively. At Hungarian site Ts and SWC showed relatively high spatial heterogeneity, ranging from 19.4 to 24.6 oC, and from 7.5 to 34.1%, respectively. Content of soil OM had lower variability ranging from 2.0 to 2.4 % at Croatian and from 3.2 to 4.5 % at Hungarian site, respectively. CO2 efflux was 0.125 ± 0.078 and 0.060 ± 0.088 mg m- 2 s-1 in average at Croatian and Hungarian field, respectively. Investigated properties did not follow normal distribution, so logarithm transformation were applied before modelling. Kriging interpolation model for mapping soil properties is tested to compare the prediction accuracy. Soil maps showed sufficient concentrations of soil OM at Hungarian site and insufficient concentrations of OM at Croatian site. Soil CO2 efflux map showed that the largest part of the investigated area in Hungary have low loss of C, while loss of C at Croatian site is high. There are areas, especially wheeled rows, where CO2 emission is lower than the average value of the field at both investigated site. These low CO2 emission areas coincide with the compacted row of wheel tracks. For future management it is necessary to provide better conditioning of soil at Croatian site and adopt environmental friendly soil management at both sites. 

 

This work is supported by the Croatian-Hungarian Bilateral Project (2018-2.1.12-TÉT-HR-2018-00007) and the PD116084  and NKFIH131792 reseach project.
Understanding Sahelian rainfall skill in the NMME seasonal forecast
Authors: Martin-Gomez Veronica , Mohino Elsa , Rodriguez-Fonseca Belén
Published: March 2020

Sahelian rainfall presents variability from internannual to interdecadal timescales, which is influenced by the sea surface temperature anomalies (SSTa) in different basins. At interannual times scales it has been shown that this variability depends on the SSTa over the equatorial Pacific, Atlantic and eastern Mediterranean. In this work we consider the set of models from the North American Multi-model ensemble (NMME) in order to analyze their skill in reproducing the Sahelian precipitation variability and relate it to their skill in reproducing the variability of the SSTa over the equatorial Pacific, equatorial Atlantic and eastern Mediterranean as well as their ability to simulate their teleconnections with Sahel rainfall.

Results show that the skill in predicting Sahel rainfall is low, decreases rapidly with lead time and is highly model dependent. Skill is improved for those models that are able to correctly simulate the Pacific SST - Sahel rainfall teleconnection.  Models present a good ability to reproduce the Mediterranean SST – Sahel teleconnection, and skill in Sahel rainfall prediction is more dependent on the correct prediction of the Mediterranean SST anomalies. These results suggest a path to increase skill in Sahel rainfall prediction.
Transform/oblique rift system : what have we learned from numerical modelling and what's next ?
Authors: Le Pourhiet Laetitia , Jourdon Anthony
Published: March 2020

For very long time, transform margins have been treated and described  based on oceanic transform fault concepts. Their was no change in kinematics nor structures with time and thermally speaking, it was hypothesed that the margin was reheated as the mid-oceanic ridge translated passively along the margin.  In the last 10 years, 3D numerical modelling has been made available and numbers of studies have challenged this view. It is time to review the concepts that have emerge. Interrestingly, many modelling contributions have tackled the obliquity at very different scales, with initial conditions varying from simple flat layered homogeneous lithosphere to subduction of opposite vergence. Moreover some contributions have focus on rheological aspect and other on inheritance at different scale and different physical coupling have been used. Some models were targeting at reproducing the oceanic transform concepts, other at exploring how large scale structure can emerge.  I will therefore try to review  the state of art in numerical modelling of transform margin and oblique extensional system based on my own work and literature review. I will try to emphize the important differences and similarities used in the different modelling. Using different models with different boundary conditions and scale I will try to introduce a new conceptual model of transform margin which captures important characteristics like the delay in continental break-up highlighted by the tracing of sediments and water-depth as well as the obliquity between syn-rift and post-rift subsidence.  Some models of oblique extension have also been producing new type of strike slip ocean continent transition which somehow could be interpreted as steep transform margins but appears to be mainly strike slip and have no conjugate margins. To conclude, all these 3D numerical modelling  allow us today to present a very different view of transform margins than 10 years ago. Some of the new concepts that have emerged  mendate to re assess our interpretation of exisiting datasets.
Hydro-climatic and anthropic determinants of spatio-temporal variability of crop water footprint
Authors: Tamea Stefania , Tuninetti Marta , Rolle Matteo
Published: March 2020

Multidisciplinary analyses of the water-food nexus are often based on the water footprint indicator. The water footprint measures the volume of water necessary to produce a good, and its unit counterpart (water footprint per unit weight of good) can be interpreted as an indicator of efficiency in the use of water resources. Crop water footprint refers to the unit water footprint of crops and it is defined as the volume of water evapotranspired during crop growth divided by the agricultural yield.

This contribution focuses on the spatial variability (at global scale) and temporal evolution (in the period 1961-2004) of the crop water footprint of four crops: wheat, rice, maize and soybean. In particular, we investigate the role of hydro-climatic and anthropic factors in determining the spatial and temporal variability. First, a sensitivity analysis is used to quantify the influence of precipitation, reference evapotranspiration, and agricultural yield  on crop water footprint, separating between green water (precipitation) and blue water (irrigation). Second, an analysis of agricultural yield is presented that separates the effects of hydro-climatic and anthropic determinants on yield, with a special focus on temporal trends.

Results highlight the important role played by hydro-climatic variables in the separation of green and blue water, despite the limited sensitivity of total water footprint to such variables. In the temporal analysis, hydro-climatic variables are found to contribute to the inter-annual fluctuations of yield (and thus of crop water footprint) but the temporal trends are dominated by anthropic determinants. In conclusion, both hydro-climatic and anthropic variables have a role in spatio-temporal variability of crop water footprint, although their influence is different if considering different aspects of such variability.
Rainfall as the major driver of plant Si availability in gibbsitic Andosols
Authors: Vander Linden Charles , Li Zimin , Iserentant Anne , Delvaux Bruno
Published: March 2020

The amount of water available to leach solutes from soil is one of the major features determining mineral weathering, secondary mineral synthesis and soil properties. The occurrence of gibbsite in soils denotes strong desilication.

Here, we quantify the reservoirs of bioavailable Si and phytolithic Si in wet tropical Andosols rich in gibbsite along a topoclimosequence where mean annual rainfall (MAR) increases from 2650 to 4400 mm with increasing altitude (65-375m above sea level) in Basse-Terre, Guadeloupe. We assessed bioavailable Si through CaCl2 extraction in soil and the pool of soil phytoliths through Na2CO3 extraction and heavy liquid (hl) separation (followed by XRD quantification). The Na2CO3 extraction was performed on both the bulk soil and oxalate–treated soil (ox-Na2CO3) cleared of its amorphous aluminosilicates.

The Andosols have reached an advanced weathering stage. Their secondary products included (Al, Fe)-humus complexes, ferrihydrite, gibbsite and aluminous allophanic substances. The contents of organic C, metal-humus, ferrihydrite and gibbsite increased in wettest conditions (>3000mm) whereas allophane content concomitantly decreased. Ox-Na2CO3 Si (2-7 g kg-1) contents were below hl Si contents (2-22 g kg-1), and were negatively correlated to each other (r = -0.88) suggesting the occurrence of two pools of phytoliths: (i) free and fresh phytoliths, (ii) aged phytoliths entrapped in soil aggregates. Yet, bioavailable Si content in soil decreased from 63 to 12 mg kg-1 with increasing MAR (r = -0.92), and was strongly correlated (r = +0.95) to that of phytolithic Si as assessed after ox-Na2CO3 extraction. The Si/Al ratio of the ox-Na2CO3 extract regularly decreased from 1.06 to 0.37 with increasing MAR, hence corroborating strongest desilication in wettest conditions. In these highly leached, gibbsitic Andosols, rainfall is thus the major driver of plant Si availability.
Life, but not as we know it: exploring RNA viral diversity in soils through viromics
Authors: Hillary Luke , Adriaenssens Evelien , Jones Davey , McDonald James
Published: March 2020

Viruses play a crucial and underexplored role in soil microbial ecosystems, but soil viral ecology has focused exclusively on DNA viruses. The role of RNA viruses in soil ecosystems has therefore been largely overlooked, despite their significant impact on public health and food security. Here, we report the first ever study to apply viromics to survey soil RNA viral communities from five sites along an altitudinal primary productivity gradient in the UK. We identified over 3,000 viral sequences, of which over half were unclassified, and newly identified viruses were placed in a global context by the phylogenetic comparison of their RNA-dependent RNA polymerase genes. Unlike DNA viral communities, the RNA viromes were heavily dominated by viruses of eukaryotes, including pathogens of plants, fungi, vertebrates and invertebrates. Sampling sites showed minimal similarity in viral community composition, suggesting that we have just scratched the surface of soil RNA viral diversity. Wider sequencing efforts and method development are required to further explore soil RNA viromes and understand their ecological function; however, this study represents an important step towards the characterisation of soil viral communities and interactions with their microbial hosts, which will provide a more holistic view of the biology of economically and ecologically important soils.
The continuing inflation of Montserrat – and the end of the intrusion
Authors: Neuberg Jurgen , Pascal Karen
Published: March 2020

Soufrière Hills volcano on Montserrat in the West Indies showed five episodes of magma extrusion and as many pauses in its 25years of volcanic activity. This eruptive behaviour exhibited cyclic deformation pattern where extrusive “phases” showed island-wide deflation and all “pauses” have been linked to inflation, the last of which remains ongoing. Several models have been developed over the years; all based on magma intrusion and extrusion, into, or from one or several reservoirs, respectively. Using the entire eruptive history, we demonstrate that both, pauses and phases can be linked to a single magma body. Through extensive numerical modelling, we explore in this presentation some alternative routes to magma intrusion, considering several magmatic processes. These range from crystallisation of magma (second boiling) to pressurisation through a free gas phase, to the extreme case where intrusion of fresh magma has ceased years ago, while the inflation is continuing. 
NEW ANALYTICAL FORMULAS FOR PHASE EQUILIBRIUM RATIOS (K-values)
Authors: Koldoba Elena
Published: March 2020

One of the most important  problems for reservoir simulation is the computation of a multicomponent flow of compressible fluids in porous media with mass exchange between phases. Phase equilibrium ratios (K-values) play a fundamental role in such calculating. Current work proposes the new analytical formulas for K-values. The theory takes into account not only the dependence on pressure, temperature and composition, but also takes into account the conditions formation of real fluid in a porous medium. Such accounting is performed with application of the integral fluid parameters, rather than with application individual characteristics of each component. For calculation of these parameters it is necessary to know dependence volumes of gas and liquid phases in some pressure range (in two phase region) and values of compositions at one pressure.

If combine a compositional model and this K-values approach, it is possible to create an effective model for numerically modeling the complex phase state of solutions. The technique of thermodynamic potentials makes it possible to construct a thermodynamically consistent model of a real solution in an analytical form. The proposed formulas properly describe phase behavior of real solutions in some practically important pressure range for volatile and black oil. The approach can be used for several phases (not only for two phase). Newly developed methods will be added to open source thermo-hydromechanical matlab codes.
Setting the tree-ring record straight
Authors: Ludescher Josef , Bunde Armin , Büntgen Ulf , Schellnhuber Hans Joachim
Published: March 2020

Tree-ring chronologies are the main source for annually resolved and absolutely dated temperature reconstructions of the last millennia and thus for studying the intriguing problem of climate impacts. Here we focus on central Europe and compare the tree-ring based temperature reconstruction with reconstructions from harvest dates, long meteorological measurements, and historical model data. We find that all data are long term persistent, but in the tree-ring based reconstruction the strength of the persistence quantified by the Hurst exponent is remarkably larger (h = 1.02) than in the other data (h = 0.52 − 0.69), indicating an unrealistic exaggeration of the historical temperature variations. We show how to correct the tree-ring based reconstruction by a mathematical transformation that adjusts the persistence and leads to reduced amplitudes of the warm and cold periods. The new transformed record agrees well with both the observational data and the harvest dates-based reconstructions and allows more realistic studies of climate impacts. It confirms that the present warming is unprecedented.
Deep Learning for image based weather estimation: a focus on the snow
Authors: Lepetit Pierre , Mallet Cécile , Barthes laurent
Published: March 2020

The road traffic is highly sensitive to weather conditions. Accumulation of snow on the road can cause important safety problems. But road conditions monitoring is as hard as critical: in mid-latitude countries, on the one hand, the spatial variability of snowfall is high and on the other hand, accurate characterization of snow accumulation mainly relies on costly sensors.

In recent decades, webcams have become ubiquitous along the road network. The quality of these webcams is variable but even low-resolution images capture information about the extent and the thickness of the snow layer. Their images are also currently used by forecasters to refine their analysis. The automatic extraction of relevant meteorological information is hence very useful.

Recently, generic and efficient computer vision methods have emerged. Their application to image-based weather estimation has become an attractive field of research. However, the scope of existing work is generally limited to high-resolution images from one or a few cameras.

In this study, we show that for a moderate effort of labelling, recent Machine Learning approaches allow us to predict quantitative indices of the snow depth for a large variety of webcam settings and illumination.

Our approach is based on two datasets. The smallest one contains about 2.000 images coming from ten webcams that were set up near sensors devoted to snow depth measurements.

The largest one contains 20,000 images coming from 200 cameras of the AMOS dataset. Meteorological standard rules of human observation and the specifics of the webcams have been taken into account to manually label each image. These labels are not only about the thickness and the extent of the snow layer but also describe the precipitation (rain or snow, presence of streaks), the optical range and the foreground noise. Both datasets contain night images (45%) and at least 15% of images corrupted by foreground noise (filth, droplets, and snowflakes on the lens).

 

The labels of the AMOS subset allowed us to train ranking models for snow depth and visibility using a multi-task setting. The models are then calibrated on the smallest dataset. We tested several versions, built from pre-trained CNNs (ResNet152, DenseNet161, and VGG16).

Results are promising with up to 85% accuracy for comparison tasks, but a 10% decrease can be observed when the test webcams have not been used during the training phase.

A case study based on a widespread snow event over the French territory will be presented. We will show the potential of our method through a comparison with operational model forecasts.
The dynamical composition of the Madden-Julian oscillation
Authors: Castanheira José M. , Marques Carlos A. F.
Published: March 2020

The Madden-Julian oscillation (MJO) is a major intraseasonal tropical atmospheric mode which modulates the precipitation in the Tropical Indian and Pacific  oceans. It is a large atmospheric convective system, dominated the zonal wave number one scale, that moves eastward from the east coast of Africa to eastern Pacific in a time scale of  30-70 days.

The MJO can have impact in global weather but is yet poorly simulated in most atmospheric circulation models. Therefore, it is important to understand the convective-dynamical nature of the MJO to understand the reasons for its poor representation in models.

Here we present a diagnostic study of the MJO by decomposing the circulation associated with a multivariate MJO index onto 3-Dimensional inertio-gravitic and Rossby modes, based on the ERA-I reanalysis. Results show that the main dynamical features of MJO are represented by  a combination of  Kelvin and the first (lr = 1) equatorial Rossby modes with zonal wavenumbers 1 to 4. The vertical structures of the waves correspond to a first baroclinic mode in the troposphere. Moreover, a space–time spectral analysis confirmed the existence of an eastward moving MJO signal in the equatorial Rossby modes.

Nonlinear interactions between the westward moving equatorial Rossby waves and eastward moving Kelvin waves may be the cause for the slow eastward progression of the MJO. 
Testing the use of crowdsourced data for supporting post-event understanding and simulation of flooding impacts in ungauged basins
Authors: Castelli Fabio , Annis Antonio , Nardi Fernando
Published: March 2020

The post-event understanding and reconstruction of flooding dynamics and impacts is not trivial task. This is especially critical for ungauged basins, lacking river flow monitoring networks, that are characterized by inundation dynamics falling outside specifications of Earth Observation (EO) and large-scale disaster emergency management systems. Satellite data provide, in fact, radar and multi-spectral images supporting inundation extent rapid mapping, but the coverage and quality of EO-based flood mapping is often not adequate for effective riverine inundation assessments in many complex urban, coastal and rural ecosystems where important flood damages occur. Rainfall-driven flash flooding occurring in most cities provide further cases with temporal (e.g. fast hydrologic response to extreme rainfall events) and spatial scales (e.g. floodplain landscape feature complex morphologies; urban micro-features like walls and culverts) determining an increased level of un-observed and uncertain, yet crucial, flood modelling variables. As a result, while technological progresses of remote sensing and flood modelling data and tools create advanced opportunities and support numerical simulations for real time or post event analysis, it is still often challenging to understand, reconstruct and accurately simulate flooding dynamics and related effects.  Distributed and timely flood event observations are always taken by citizens fostering new means for real time or post event analysis of extreme events. This wealth of “new data”, namely Volunteer Geographic Information (VGI) or crowdsourced data, are surely a value for flood risk management, but several and diverse technical, administrative and procedural barriers are impacting their uptake. This work illustrates preliminary tests developed in using crowdsourced data for post-event simulation of flooding impacts in ungauged basins. Videos and images from social networks are used for calibrating both a detailed 2D hydraulic model and a cost-effective geomorphic floodplain extent rapid mapping algorithm to investigate on novel procedures, methods and tools of post-event flood hazard assessment and impact mapping.
Seismic attenuation tomography using body-wave energy normalised by the heterogeneous coda
Authors: Sketsiou Panayiota , De Siena Luca , Gabrielli Simona , Napolitano Ferdinando
Published: March 2020

Seismic waves lose energy during propagation in heterogeneous Earth media. Their decrease of amplitude, defined as seismic attenuation, is central in the description of seismic wave propagation. The attenuation of coherent waves can be described by the total quality factor, Q, and it is defined as the fractional energy lost per cycle, controlling the decay of the energy density spectrum with lapse time. The coda normalization (CN) method is a method to measure the attenuation of P- or S-waves by taking the ratio of the direct wave energy and late coda wave energy in order to remove the source and site effects from P- and S-wave spectra. One of the main assumptions of the CN method is that coda attenuation, i.e. the decay of coda energy with lapse time measured by the coda quality factor Qc is constant. However, several studies showed that Qc is not uniform in the crust for the lapse times considered in most attenuation studies. In this work, we propose a method to overcome this assumption, measuring coda attenuation for each source-station path and evaluating the effect of different scattering regimes on the corresponding imaging. The data consists of passive waveforms from the fault network in the Pollino Area (Southern Italy) and Mount St. Helens volcano (USA).
Evaluation of CMIP6 Model Precipitation Variability Through Compositing in Cloud-defined Weather States
Authors: Tselioudis George , Remillard Jasmine
Published: March 2020

In order to understand the mechanisms determining precipitation variability and to evaluate model skill in simulating those mechanisms, it is important to partition the precipitation field into regimes that include distinct sets of processes. In the past, dynamic fields like omega and SLP have been used to define regimes and study cloud, radiation, and precipitation variability. More recently, cloud-defined weather states were derived and used for similar analyses. Here, we apply a new cloud-defined Weather State dataset derived from the higher-resolution ISCCP-H data to examine precipitation variability at global scales and evaluate CMIP6 model precipitation simulations . In addition, precipitation partitioning using mid-tropospheric vertical velocity is performed, and the differences between the results of the two compositing methodologies are discussed.
Maximum latewood density records of the oldest trees in the world: Great Basin Bristlecone pine (Pinus Longaeva)
Authors: De Mil Tom , Salzer Matthew , Pearson Charlotte , Trouet Valerie , Van den Bulcke Jan
Published: March 2020

Great Basin Bristlecone pine (Pinus longaeva) is known for its trees that attain old age. The longest chronology is more than 9000 years long, and the temperature-sensitive upper treeline chronology extends back to 5000 years. The ring width pattern of upper treeline bristlecone pine trees are strongly influenced by temperature variability at decadal to centennial scales. To infer a climate signal on annual scales, MXD is shown to be a better temperature proxy. Here, we present a preliminary Maximum Latewood Density (MXD) chronology of bristlecone pine to investigate the temperature signal in upper treeline and below. Maximum latewood density (MXD) from 24 dated cores (from various sites ranging from the upper treeline and below, oldest sample dates back to 776 AD) was determined with an X-ray CT toolchain. Ring and fibre angles were corrected and a MXD chronology was constructed. The resulting MXD chronology will be correlated to summer temperature. Future scanning will allow constructing a + 5000 year MXD chronology and could reveal the cooling effect of volcanic eruptions through this period.
Importance of Northern Hemisphere Vertical Land Motion for Geodesy and Coastal Sea Levels
Authors: Ludwigsen Carsten Ankjær , Andersen Ole Baltazar , Khan Shfaqat Abbas , Marzeion Ben
Published: March 2020

Vertical Land Motion (VLM) is a composite of several earth dynamics caused by changes of earth’s surface load or tectonics. In most of the Northern Hemisphere mainly two dynamics are causing large scale vertical land motion – Glacial Isostatic Adjustment (GIA), which is the rebound from the loading of the latest glacial cycle (10-30 kyr ago) and elastic rebound from contemporary land ice changes, that happens immediately when loading is removed from the surface.

With glacial mass balance data and observations of the Greenland Ice Sheet we have created an Northern Hemisphere ice history from 1996-2015 that is used to make a model for elastic VLM caused by ice mass loss that varies in time.

It shows that, in most cases, the elastic VLM model is able to close gaps between GIA induced VLM and GNSS-measured VLM, giving confidence that the combined GIA + elastic VLM-model is a better alternative to adjust relative sea level measurements from tide-gauges (where no (reliable) GNSS-data is available) to absolute sea level than 'just' a GIA-model. In particular for Arctic Sea Level, where elastic uplifts are prominent and large coastal regions have limited in-situ data available, the VLM-model is useful for correcting Tide Gauge measurements and thereby validate satellite altimetry observed sea levels, which is challenged by sea ice in the coastal Arctic.

Furthermore, our elastic VLM-model shows, that the uplift caused by the melt of the Greenland Ice Sheet (GIS) is far-reaching and even in the North Sea region or along the North American coast show uplift rates in the order of 0.4-0.7 mm/yr from 1996-2015. Interestingly, this is roughly equivalent to Greenland’s sea level contribution in the same period, thereby 'neutralizing' the melt of GIS. As GIS ice mass loss continues to accelerate, the elastic uplift will have increased importance for coastal regions and future relative sea level projections. Unfortunately, the opposite effect is true for the southern hemisphere or vice versa if Antarctic ice sheet mass loss would increase.
Short Term Hydrological Forecasting for a Cascade Dam System: A Case Study of Euphrates Basin in Turkey
Authors: Onen Alper , H. Afshar Mehdi , Bulut Burak
Published: March 2020

This study investigates the performance of short term daily hydrological forecasts utilizing Global Forecast System (GFS) and Hydrologiska Byrans Vattenbalansavdelning (HBV) model over a major sub-region (~25000 km2) located in Euphrates River Basin, Turkey. The test basin, over which the forecast algorithm is implemented, is home to five (four operational and another almost-complete) dams with 3 three more planned; all eight located within last 300 km reach of 730 km-long Murat River. The algorithm is aimed to operate through a user-friendly and reliable commercially available forecast interface for decision makers working on fields such as energy production scheme optimization and flood mitigation. In the development of this forecast strategy, the main basin was divided into multiple subbasins that are bordered with corresponding facilities and each subbasin is independently modelled & calibrated by HBV model and meteorological records using available stream gauge and weather station data collected in the region. The Global Forecast System (GFS) that provides 16-day meteorological forecast is then applied to model as the input for hydrological predictions. By implementing and clustering daily operation records of inflow and outflow data received directly from related regional SCADA system, volumetric hydrograph corrections are applied on the model output as a final corrective filter to maximize the temporal performance over the 16-day forecast period. As the system has been in use for nearly 20 months (as of January 2020), our results have shown that a calibrated data cluster performance nearing 0.98 has been reached in correlation and 0.90 in Nash-Sutcliffe index:  cluster-independent average weekly inspected forecast performance of almost 0.87 in correlation and 0.85 in Nash-Sutcliffe index has been obtained.