bluuebunny/crossref_metadata_2025 huggingface dataset:
Substorm related patterns of electron density and conductance changes in the auroral zone.
Authors: Stepanov Nikita , Victor Sergeev , Maria Shukhtina , Yasunobu Ogava , Xiangning Chu
Published: March 2021

Enhanced precipitation of magnetospheric energetic particles during substorms increases ionospheric electron density and conductance. Such enhancements, which have timescales of a few hours, are not reproduced by the current ionospheric models. We use linear prediction filter technique to reconstruct the substorm-related response of electron densities at different altitudes and ionospheric conductances from long-term observations made by the European Incoherent SCATer (EISCAT) radar located at Tromso. To characterise the intensity of substorm injection at a 5min time step we use the midlatitude positive bay (MPB) index which basically responds to the substorm current wedge variations. We build response functions (LPF filters) between T0-1h and T0+4hrs (T0 is a substorm onset time) in different MLT sectors to estimate the magnitude and delays of the ionospheric density response at different altitudes. The systematic and largest relative substorm related changes are mostly observed in the lowest part of E and in D regions. The duration of the response is about 3 hours. It starts and reaches maximum magnitude near midnight, from which it mainly propagates toward east, where it decays when passing into the noon-evening sector. Such MLT structure corresponds to the drift motion of the injected high energy electron cloud in the magnetosphere. Model performance is better at the midnight-morning sectors (CC~0.6-0.65), where the response is larger, and it is getting worse at the noon-evening sector (CC~0.3-0.5). We also discuss the changes of effective electron energy spectra with the substorm time and MLT and compare the behaviors of global ionization, auroral absorption and conductance patterns as it propagates azimuthally from midnight along the auroral zone following after T0 time. Research was supported by RFBR grants №19-35-90054 and №19-05-00072 and MON grant №2020-220-08-6949.
A mechanistic interpretation of potential CO2 leakage through shaly caprocks
Authors: Rahimzadeh Kivi Iman , Vilarrasa Victor , Makhnenko Roman
Published: March 2021

Global warming brought upon by anthropogenic CO2 emissions into the atmosphere is causing significant impacts on the Earth and represents one of the major concerns of the current century. To be controlled, it is widely accepted that huge amounts of CO2 at the gigatonne scale have to be captured and injected back into the underground in a process known as Carbon Capture and Storage (CCS). As CO2 is less dense than the in-situ brine, it tends to flow upward out of the storage reservoir by buoyancy and the injection overpressure. A laterally-extensive and thick non-fractured caprock possessing low permeability and high entry capillary pressure is commonly expected to keep CO2 within the host reservoir. However, the potential risks of CO2 leakage through the intact caprock need thorough assessment. This contribution brings together experimental observations and numerical simulations to inspect the sealing capacity of an intact shaly caprock and render an in-depth understanding of the governing flow mechanisms. Reproducing the subsurface conditions of CO2 intrusion and flow through the caprock, breakthrough experiments are conducted on Opalinus Clay as a representative caprock for CO2 storage. The adopted approach consists of injecting supercritical CO2 into the caprock sample lying between two permeable porous disks, all initially saturated with brine. Supplementary experiments are also performed to characterize the pore structure and hydromechanical properties of the specimen. The extracted properties are used to parameterize a two-phase flow model in deformable porous media and simulate the breakthrough experiment carried out on Opalinus Clay to make a mechanistic interpretation of the experimental observations. Simulation results reveal three concomitant CO2 flow mechanisms into and through the caprock: molecular diffusion, bulk volumetric advection, and transported CO2 dissolved in the advected brine. It is inferred that the high entry pressure and low effective permeability prevents free phase CO2 penetration deep into the caprock. The drainage path is followed by the imbibition of brine back into the pores from the downstream until recovering the initial state of being completely saturated with brine. While the contribution of brine advection to CO2 transport is found to be negligible, we find that CO2 flow through the caprock is mainly governed by molecular diffusion, whose effects on the potential leakage of CO2 during geological time scales have to be taken into account.
Skip high-volume data transfer and access free computing resources for your CMIP6 multi-model analyses
Authors: Moreno de Castro Maria , Kulüke Marco , Wachsmann Fabian , Kwee-Hinzmann Regina , Kindermann Stephan , Nassisi Paola , Levavasseur Guillaume , Fiore Sandro , Pascoe Charlotte , Juckes Martin , Morellon Sophie , Joussaume Sylvie
Published: March 2021

Tired of downloading tons of model results? Is your internet connection flakey? Are you about to overload your computer’s memory with the constant increase of data volume and you need more computing resources? You can request free of charge computing time at one of the supercomputers of the Infrastructure of the European Network of Earth System modelling (IS-ENES)1, the European part of Earth System Grid Federation (ESGF)2, which also hosts and maintains more than 6 Petabytes of CMIP6 and CORDEX data.

Thanks to this new EU Comission funded service, you can run your own scripts in your favorite programming language and straightforward pre- and post-process model data. There is no need for heavy data transfer, just load with one line of code the data slice you need because your script will directly access the data pool. Therefore, days-lasting calculations will be done in seconds. You can test the service, we very easily provide pre-access activities.

In this session we will run Jupyter notebooks directly on the German Climate Computing Center (DKRZ)3, one of the ENES high performance computers and a ESGF data center, showing how to load, filter, concatenate, take means, and plot several CMIP6 models to compare their results, use some CMIP6 models to calculate some climate indexes for any location and period, and evaluate model skills with observational data. We will use Climate Data Operators (cdo)4 and Python packages for Big Data manipulation, as Intake5, to easily extract the data from the huge catalog, and Xarray6, to easily read NetDCF files and scale to parallel computing. We are continuously creating more use cases for multi-model evaluation, mechanisms of variability, and impact analysis, visit the demos, find more information, and apply here: https://portal.enes.org/data/data-metadata-service/analysis-platforms.

[1] https://is.enes.org/
[2] https://esgf.llnl.gov/
[3] https://www.dkrz.de/
[4] https://code.mpimet.mpg.de/projects/cdo/
[5] https://intake.readthedocs.io/en/latest/
[6] http://xarray.pydata.org/en/stable/
Structure of the freshened surface layer in the Eastern Arctic during ice-free periods
Authors: Osadchiev Alexander , Frey Dmitry
Published: March 2021

Discharges from the largest rivers of the World to coastal sea form sea-wide freshened surface layers which areas have order of hundred thousands of square kilometers. Large freshened surface layers (which are among the largest in the World Ocean) are located in the Kara, Laptev, and East-Siberian seas in the Eastern Arctic. This work is focused on the structure and inter-annual variability of these freshened water masses during ice-free periods. The freshened surface layer in the Laptev and East-Siberian seas is formed mainly by deltaic rives among which the Lena River contributes about two thirds of the inflowing freshwater volume. Based on in situ measurements, we show that the area of this freshened surface layer is much greater than the area of the freshened surface layer in the neighboring Kara Sea, while the total annual freshwater discharge to the Laptev and East-Siberian seas is 1.5 times less than to the Kara Sea (mainly from the estuaries of the Ob and Yenisei rivers). This feature is caused by differences in morphology of the estuaries and deltas. Shallow and narrow channels of the Lena Delta are limitedly affected by sea water. As a result, undiluted Lena discharge inflows to sea from multiple channels and forms relatively shallow plume, as compared to the Ob-Yenisei plumes which mix with subjacent saline sea water in deep and wide estuaries. The shallow Lena plume spreads over wide area (up to 500 000 km2) in the Laptev and East-Siberian seas during and shortly after freshet period in summer and then transforms to the Laptev/East-Siberian ROFI in autumn. Area and position of the relatively shallow freshened surface layer in the Laptev and East-Siberian seas have large inter-annual variability governed by local wind forcing conditions, however, do not show any dependence on significant variability of the annual volume of discharge rate from the Lena River. The deep freshened surface layer in the Kara Sea also has distinct seasonal varability of area and position, however, is stable on inter-annual time scale.
Using machine learning to generate high-resolution soil wetness maps for planning forest management
Authors: Lidberg William , Larson Johannes , Paul siddhartho , Laudon Hjalmar , Ågren Anneli
Published: March 2021

Open peatlands are a recognizable feature in the boreal landscape that are commonly mapped from aerial photographs. However, wet soils also occur on tree covered peatlands and in the riparian zones of forest streams and surrounding lakes. Comparisons between field data and available maps show that only 36 % of wet soils in the boreal landscape are marked on maps, making them difficult to manage. Wet soils have lower bearing capacity than dry soils and are more susceptible to soil disturbance from land-use management with heavy machinery. Topographical modelling of wet area indices has been suggested as a solution to this problem and high-resolution digital elevation models (DEM) derived from airborne LiDAR are becoming accessible in many countries. However, most of these topographical methods relies on the user to define appropriate threshold values in order to define wet areas. Soil textures, topography and climatic differences make any application difficult on a large scale. This complex landscape variability can be captured by utilizing machine learners that uses automated data mining methods to discover patterns in large data sets. By using soil moisture data from 20 000 field plots from the National Forest Inventory of Sweden, we combined information from 24 indices and ancillary environmental features using a machine learning known as extreme gradient boosting. Extreme gradient boosting used the field data to learn how to classify soil moisture and delivered high performance compared to many traditional single algorithm methods. With this method we mapped soil moisture at 2 m spatial resolution across the Swedish forest landscape in five days using a workstation with 32 cores. This new map captured 79 % (kappa 0.69) of all wet soils compared to only 36 % (kappa 0.39) captured by current maps. In addition to capture open wetlands this new map also capture riparian zones and previously unmapped cryptic wetlands underneath the forest canopy. The new maps can, for example, be used to plan hydrologically adapted buffer zones, suggest machine free zones near streams and lakes in order to prevent rutting from forestry machines to reduce sediment, mercury and nutrient loads to downstream streams, lakes and sea.
High-resolution Ensemble Kalman Fiter with a low-resolution model using a machine learning super-resolution approach.
Authors: Barthélémy Sébastien , Brajard Julien , Bertino Laurent
Published: March 2021

Going from low- to high-resolution models is an efficient way to improve the data assimilation process in three ways: it makes better use of high-resolution observations, it represents more accurately the small scale features of the dynamics and it provides a high-resolution field that can further be used as an initial condition of a forecast. Of course, the pitfall of such an approach is the cost of computing a forecast with a high-resolution numerical model. This drawback is even more acute when using an ensemble data assimilation approach, such as the ensemble Kalman filter, for which an ensemble of forecasts is to be issued by the numerical model.

In our approach, we propose to use a cheap low-resolution model to provide the forecast while still performing the assimilation step in a high-resolution space. The principle of the algorithm is based on a machine learning approach: from a low-resolution forecast, a neural network (NN) emulates a high-resolution field that can then be used to assimilate high-resolution observations. This NN super-resolution operator is trained on one high-resolution simulation. This new data assimilation approach denoted "Super-resolution data assimilation" (SRDA), is built on an ensemble Kalman filter (EnKF) algorithm.

We applied SRDA to a quasi-geostrophic model representing simplified ocean dynamics of the surface layer, with a low-resolution up to four times smaller than the reference high-resolution (so the cost of the model is divided by 64). We show that this approach outperforms the standard low-resolution data assimilation approach and the SRDA method using standard interpolation instead of a neural network as a super-resolution operator. For the reduced cost of a low-resolution model, SRDA provides a high-resolution field with an error close to that of the field that would be obtained using a high-resolution model.
Predator-prey plankton dynamics in turbulent wakes behind islands
Authors: Jaccod Alice , Berti Stefano , Calzavarini Enrico , Chibbaro Sergio
Published: March 2021

Plankton constitutes the productive base of marine ecosystems and plays an important role in the global carbon dioxide cycle through the process of photosynthesis. The impact of ocean hydrodynamic conditions on the biological activity of plankton species has been a subject attracting the interest of researchers during several decades. In the present study, we perform a well-resolved direct numerical simulation of a turbulent flow around an island, coupled to a predator–prey model of planktonic population dynamics, with the aim of investigating the conditions under which an algal bloom is observed.  The impact on the plankton dynamics of the turbulent regime as well as of the island shape is studied, through the investigation of spectra of velocity and plankton population density. Moreover, we focus on the correlation between the flow structures and the plankton patchiness, particularly by analyzing the effect of the sub-grid scale dynamics. The main outcome is that the response and the spatial distribution of plankton depend crucially on the relation between the time scale associated to the flow and the time related to biological growth, while they are fairly independent on the geometrical details of the obstacle. 
Early Miocene mollusc and fish biodiversity at the Proto-Mediterranean–Paratethys marine corridor
Authors: Koskeridou Efterpi , Agiadi Konstantina , Thivaiou Danae
Published: March 2021

Marine biodiversity is controlled by depth, climate, and ocean connectivity. The early Miocene marine fauna of the proto-Mediterranean is particularly important because this is the time when the connection with the Indo-Pacific realm was disrupted , and the marine biodiversity hotspot shifted toward the southeast, marking the onset of a subtropical gradually oligotrophic regime in the proto-Mediterranean Sea. The Mesohellenic basin in particular, at the northern part of the proto-Mediterranean, was located at the intersection with the Paratethys epicontinental sea. Therefore, the fauna in this area was influenced by the conditions in both basins. In this study, we present the mollusc and fish fauna of the Aquitanian Mesohellenic basin and discuss its paleobiogeographic and evolutionary implications. Comparisons and assessment of faunal similarities of the proto-Mediterranean and adjacent provinces is carried out using ordination methods to treat available data from relevant publications and the Paleobiology Database (PBDB).

This research has been co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme “Human Resources Development, Education and Lifelong Learning 2014–2020” in the context of the project “Mollusc and fish migrations in the dynamic environments of the early to middle Miocene in the Mediterranean” (MIS 5047960). 
Modelling the second wave of COVID-19 infections in France and Italy via a Stochastic SEIR model
Authors: Faranda Davide , Alberti Tommaso
Published: March 2021

COVID-19 has forced quarantine measures in several countries across the world. These measures have proven to be effective in significantly reducing the prevalence of the virus. To date, no effective treatment or vaccine is available. In the effort of preserving both public health as well as the economical and social textures, France and Italy governments have partially released lockdown measures. Here we extrapolate the long-term behavior of the epidemics in both countries using a Susceptible-Exposed-Infected-Recovered (SEIR) model where parameters are stochastically perturbed with a log-normal distribution to handle the uncertainty in the estimates of COVID-19 prevalence and to simulate the presence of super-spreaders. Our results suggest that uncertainties in both parameters and initial conditions rapidly propagate in the model and can result in different outcomes of the epidemics leading or not to a second wave of infections. Furthermore, the presence of super-spreaders adds instability to the dynamics, making the control of the epidemics more difficult. Using actual knowledge, asymptotic estimates of COVID-19 prevalence can fluctuate of order of ten millions units in both countries.
Reducing agricultural peatland CO2 emissions with hydrological conservation measures
Authors: Boonman Jim , Hefting Mariet , van Huissteden Ko , Dolman Han , van der Velde Ype
Published: March 2021

Peat soils are an important carbon stock in the global carbon cycle containing more than two third of the atmospheric carbon amount (600 GtC of 760 GtC) despite their relatively small landmass of 3% worldwide. Drainage of peatlands contributes significantly to the enhanced global warming, as it allows oxygen to intrude the soil, intensifying aerobic microbial decomposition associated with carbon dioxide emission. Water management strategies that result in a raise in (summer) groundwater tables can have the opposite effect. These measures, such as raising the surface water level and/or the application of submerged drain subsurface irrigation systems, are already being applied. However, the outcome of these strategies remains debated and is still largely to be tested. We aim to explore the potential effects of these water management strategies on reducing GHG emission in peatlands.

We simulated the effects of several water management strategies on potential aerobic peat decomposition in a managed Dutch grassland on sedge peat under various hydrological and climatological conditions. To estimate potential microbial activity in the unsaturated zone two main drivers, temperature and water filled pore space (WFPS) were used. We found that increasing ditch water levels yields a decrease in potential aerobic peat decomposition independent of summer drought, hydrological regime and peat hydrological conductivity. Furthermore, we found that submerged drainage-irrigation systems tend to establish a stable moist zone relatively close to the warm soil surface in which potential microbial activity can remain high over the complete summer period. Due to these stable conditions, we expect peat decomposition in this layer to be high, possibly counteracting the effects of decreased aeration depth due to higher water tables. Submerged drainage-irrigation systems generally decrease potential microbial activity in environments with downward flow, but increase the activity in environments with upward flow. Increased benefits of the submerged systems are found for dry years, with high surface water levels and/or decreasing hydrological conductivity of the intact peat.
A NEMO-based model of Sargassum distribution in the Tropical Atlantic 
Authors: Benshila Rachid , Jouanno Julien , Berline Léo , Soulié Antonin , Marie-Hélène Marie-Hélène , Morvan Guillaume , Diaz Frédéric , Sheinbaum Julio , Chevalier Cristele , Thibaut Thierry , Changeux Thomas , Menard Frédéric , Berthet Sarah , Aumont Olivier , Ethé Christian , Nabat Pierre , Mallet Marc
Published: March 2021

The Tropical Atlantic is facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. The development of Sargassum modelling is essential to clarify the link between Sargassum distribution and environmental conditions, and to lay the groundwork for a seasonal forecast on the scale of the Tropical Atlantic basin. We present here a modelling framework based on the NEMO ocean model which integrates transport by currents and waves, stranding at the coast, and physiology of Sargassum with varying internal nutrients quota. The model is initialized from basin scale satellite observations and performance was assessed over the Sargassum year 2017. Model parameters are calibrated through the analysis of large ensembles of simulations, and the sensitivity to forcing fields like riverine nutrients inputs, atmospheric deposition, and waves is investigated. Overall, results demonstrate the ability of the model to reproduce the seasonal cycle and large-scale distribution of Sargassum biomass.
The Dutch research infrastructure EPOS-NL: Access to Earth scientific research facilities and data 
Authors: Pijnenburg Ronald , Laumann Susanne , Wessels Richard , ter Maat Geertje , Armstrong Lora , Bieńkowski Jarek , Lange Otto , Sleeman Reinoud , Vardon Philip , Bruhn David , Barnhoorn Auke , Niemeijer André , Willingshofer Ernst , Plümper Oliver , Wapenaar Kees , Trampert Jeannot , Drury Martyn
Published: March 2021

In response to the growing geo-societal challenges of our densely populated planet, current research frequently requires convergence of multiple research disciplines, and optimized use of openly available data, research facilities and funds. Such optimization is the main aim of many research infrastructures developing both at the national and international level. In the Netherlands, the European Plate Observing System – Netherlands (EPOS-NL) was formed, as the Dutch research infrastructure for solid Earth sciences. EPOS-NL aims to further develop world-class facilities for research into georesources and hazards, and to provide international access to these facilities and derived data. It is a partnership between Utrecht University, Delft University of Technology and the Royal Netherlands Meteorological Institute (KNMI) and is funded by the Dutch Research Council. EPOS-NL facilities include: 1) The Earth Simulation Lab at Utrecht University, 2) The Groningen gas field seismological network and the ORFEUS Data Center at KNMI, 3) The deep geothermal doublet (DAPwell), to be installed on the Delft university campus, and 4) A distributed facility for multi-scale imaging and tomography (MINT), shared between the Utrecht and Delft universities. EPOS-NL provides financial, technical and scientific support for access to these facilities. To get facility access, researchers can apply to a bi-annual call, with 2021 calls planned in Q1 and Q3. EPOS-NL further works with researchers, data centers and industry to provide access to essential data and models (e.g. pertaining to the seismogenic Groningen gas field) within the framework of the European infrastructure EPOS, conforming to FAIR (Findable, Accessible, Interoperable and Reusable) data principles. In that way, EPOS-NL contributes directly to a globally developing trend to make research facilities and data openly accessible to the international community. This supports cost-effective and multi-disciplinary research into the geo-societal challenges faced by our densely populated planet. See www.EPOS-NL.nl for more information.
Deep Learning on the sphere for weather/climate applications
Authors: Defferrard Michaël , Feng Wentao , Bolón Brun Natalie , Lloréns Jover Icíar , Ghiggi Gionata
Published: March 2021

Deep Learning (DL) has the potential to revolutionize numerical weather predictions (NWP) and climate simulations by improving model components and reducing computing time, which could then be used to increase the resolution or the number of simulations. Unfortunately, major progress has been hindered by difficulties in interfacing DL with conventional models because of i) programming language barriers, ii) difficulties in reaching stable online coupling with models, and iii) the inability to exploit the horizontal spatial information as classical convolutional neural networks can’t be used on spherical unstructured grids.

We present a solution to perform spatial convolutions directly on the unstructured grids of NWP models. Our convolution and pooling operations work on any pixelization of the sphere (e.g., Gauss-Legendre, icosahedral, cubed-sphere) provided a mesh or the pixel’s locations. Moreover, our solution allows mixing data from different grids and scales linearly with the number of pixels, allowing it to ingest millions of inputs from 3D spherical fields.

We show that a proper treatment of the spherical topology and geometry of the Earth (as opposed to a projection to the plane, cylinder, or cube) i) yields geometric constraints that provide generalization guarantees (i.e., the learned function does not depend on its localization on the Earth), and ii) induces prior biases that facilitate learning. We demonstrate that doing so improves prediction performance at no computational overhead for data-driven weather forecasting. We trained autoregressive ResUNets on five spherical samplings, covering those adopted by the major meteorological centers.

We believe that the proposed solution can find immediate use for post-processing (e.g., bias correction and downscaling), model error corrections, linear solvers pre-conditioning, model components emulation, sub-grid parameterizations, and many more applications. To that end, we provide open-source and easy-to-use code accompanied by tutorials.
On Downward Continuing Airborne Gravity Data for Local Geoid Modeling
Authors: Li Xiaopeng , Huang Jianliang , Willberg Martin , Pail Roland , Slobbe Cornelis , Klees Roland , Forsberg René , Hwang Cheinway , Hilla Steve
Published: March 2021

The theories of downward continuation (DC) have been extensively studied for many decades, during which many different approaches were developed. In real applications, however, researchers often just use one method, probably due to resource limitations or to finish their work, without a rigorous head-to-head comparison with other alternatives. Considering that different methods perform quite differently under various conditions, comparing results from different methods can help a lot for identifying potential problems when dramatic differences occur, and for confirming the correctness of the solutions when results converge together, which is extremely important for real applications such as building official national vertical datums. This paper gives exactly such a case study by recording the collective wisdom recently developed within  the IAG’s study group SC2.4.1. A total of six normally used DC methods, which are SHA (NGS), LSC (DTU Space), Poisson and ADC (NRCan), RBF (DU Delft), and RLSC (TUM), are applied to both simulated data (in the combination of two sampling strategies with three noise levels) and real data in a Colorado-area test bed. The data are downward continued to both surface points and to the reference ellipsoid surface. The surface points are directly evaluated with the observed gravity data on the topography. The ellipsoid points are then transformed into geoid heights according to NRCan’s Stokes-Helmert’s scheme and eventually evaluated at the GNSS/Leveling benchmarks. In this presentation, we will summarize the work done and results obtained by the aforementioned workgroup.
WEIR-P: An Information Extraction Pipeline for the Wastewater Domain
Authors: Chahinian Nanée , Bonnabaud La Bruyère Thierry , Conrad Serge , Delenne Carole , Frontini Francesca , Julien Marin , Panckhurst Rachel , Roche Mathieu , Sautot Lucile , Deruelle Laurent , Teisseire Maguelonne
Published: March 2021

Urbanization has been an increasing trend over the past century (UN, 2018) and city managers have had to constantly extend water access and sanitation services to new peripheral areas. Originally these networks were installed, operated, and repaired by their owners (Rogers et al. 2012). However, as concessions were increasingly granted to private companies and new tenders requested regularly by public authorities, archives were sometimes misplaced and event logs were lost. Thus, part of the networks’ operational history was thought to be permanently erased. The advent of Web big data and text-mining techniques may offer the possibility of recovering some of this knowledge by crawling secondary information sources, i.e. documents available on the Web. Thus, insight might be gained on the wastewater collection scheme, the treatment processes, the network’s geometry and events (accidents, shortages) which may have affected these facilities and amenities. The primary aim of the "Megadata, Linked Data and Data Mining for Wastewater Networks" (MeDo) project (http://webmedo.msem.univ-montp2.fr/?page_id=223&lang=en), is to develop resources for text mining and information extraction in the wastewater domain. We developed a specific Natural Language Processing (NLP) pipeline named WEIR-P (WastewatEr InfoRmation extraction Platform) which allows users to retrieve relevant documents for a given network, process them to extract potentially new information, assess this information also by using an interactive visualization and add it to a pre-existing knowledge base. The system identifies the entities and relations to be extracted from texts, pertaining network information, wastewater treatment, accidents and works, organizations, spatio-temporal information, measures and water quality. We present and evaluate the first version of the NLP system. The preliminary results obtained on the Montpellier corpus (1,557 HTML and PDF documents in French) are encouraging and show how a mix of Machine Learning approaches and rule-based techniques can be used to extract useful information and reconstruct the various phases of the extension of a given wastewater network. While the NLP and Information Extraction (IE) methods used are state of the art, the novelty of our work lies in their adaptation to the domain, and in particular in the wastewater management conceptual model, which defines the relations between entities.
Identifying causal links between tectono-geomorphic processes and biodiversity with a coupled landscape-biodiversity evolution model
Authors: Beeson Helen , Willett Sean , Pellissier Loïc
Published: March 2021

Landscapes and their associated ecosystems coevolve over geologic time. Correlative approaches have elucidated the importance of topographic diversity and tectonic history but have not identified specific causal links between tectono-geomorphic processes and biodiversity metrics. To address this issue, we coupled the numerical landscape evolution model DAC (Divide and Capture) with a mechanistic model for biodiversity that simulates dispersal, allopatric speciation, and extinction to develop hypothetical biological signatures of different functional groups to a variety of landscape histories. In our coupled model, DAC-BIO, suitable habitat for terrestrial species is defined using a combination of elevation, slope, and aspect, which are measured at sub-grid scale from the simulated landscape and meant to represent more complex physical parameters such as temperature, precipitation, soil properties, and hydrologic environment. In addition to habitability requirements, species are assigned dispersal characteristics (rate and ability to cross uninhabitable terrain) and speciation rate (isolation time needed to form new species). We test whether distinct trends in the size and number of contiguous habitat patches emerge in response to various tectono-geomorphic processes, including a step change in uplift rate, a shift from uniform uplift to an uplift gradient, steady shortening (horizontal advection), and escarpment retreat. We find that these tectono-geomorphic processes do yield distinct trends in the size and number of habitat patches and that the resulting changes in habitat connectivity across the landscape leaves distinct biological signatures in diversification rates, species richness, and endemic richness.
Next-Generation Time Integration targeting Weather and Climate Simulations
Authors: Schreiber Martin
Published: March 2021

Running simulations on high-performance computers faces new challenges due to e.g. the stagnating or even decreasing per-core speed. This poses new restrictions and therefore challenges on solving PDEs within a particular time frame in the strong scaling case. Here, disruptive mathematical reformulations, which e.g. exploit additional degrees of parallelism also along the time dimension, gained increasing interest over the last two decades.

This talk will cover various examples of our current research on (parallel-in-)time integration methods in the context of weather and climate simulations such as rational approximation of exponential integrators, multi-level time integration of spectral deferred correction (PFASST) as well as other methods.

These methods are realized and studied with numerics similar to the ones used by the European Centre for Medium-Range Weather Forecasts (ECMWF). Our results motivate further investigation for operational weather/climate systems in order to cope with the hardware imposed restrictions of future super computer architectures.

I gratefully acknowledge contributions and more from Jed Brown, Francois Hamon, Terry S. Haut, Richard Loft, Michael L. Minion, Pedro S. Peixoto, Nathanaël Schaeffer, Raphael Schilling
Combining multi-sensor infrared satellite and laboratory measurements to estimate the lava discharge rate of 2018 Kilauea Volcano, Hawai'i eruption
Authors: Plank Simon , Massimetti Francesco , Soldati Arianna , Hess Kai-Uwe , Nolde Michael , Martinis Sandro , Dingwell Donald B.
Published: March 2021

Kīlauea Volcano, Hawai’i, is one of the world’s most active volcanoes. From 1983 to 2018 the magmatic system was in near continuous eruptions. This eruption ended on 30 April 2018 when the deflation of Kīlauea caldera began and a dike intrusion from the Middle East Rift Zone of Kīlauea Volcano downrift towards the Lower East Rift Zone (LERZ) was observed in seismic data. On 3 May 2018, the first of final 24 eruptive fissures opened at the LERZ. This was the beginning of the largest effusive event of the last two centuries at the LERZ. Here, we present Time-Averaged Discharge Rate (TADR) and lava eruption volume estimations based on a joint analysis of multi-sensor infrared (IR) Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Earth observation data together with laboratory viscosity measurements to investigate this large eruption event at the LERZ. First, the TADR measurements were performed independently for each sensor data to cross-check the results against each other. Second, a joint timeseries of the VIIRS and MODIS TADR estimates was created to obtain more frequent measurements. This joint analysis of VIIRS and MODIS data resulted in an erupted lava volume of 0.924 ± 0.462 km³. Independent measurements based on airborne Synthetic Aperture Radar Interferometry (InSAR) and LIDAR topography changes are within the range of the IR data-based estimates of the erupted lava volume. The 2018 LERZ eruption could be differentiated into four main phases based on major element compositions of the eruptive products. The VIIRS and MODIS-based TADR estimation showed a relatively low Mean Output Rate (MOR) of 2.82 ± 1.41 m³/s during early Phase I. MOR then almost doubled to 4.94 ± 2.47 m³/s in late Phase I. A strong increase of MOR to 64.97 ± 32.48 m³/s occurred during Phase II. In Phase III, MOR again doubled to 137.67 ± 68.83 m³/s. This strong increase of the MOR during the different phases of the 2018 LERZ eruption agrees well with the evolution of the lava from low-temperature, highly differentiated sluggish ‘a‘ā lava flows in the beginning to high-temperature mafic more fluid pāhoehoe lava from Phase II onwards, as observed in the field by the USGS.
Stratospheric drivers of extreme events at the Earth’s surface
Authors: Domeisen Daniela I.V. , Butler Amy H.
Published: March 2021

The stratosphere, the layer of the atmosphere at heights between 10-50 km, is an important source of variability for the weather and climate at the Earth’s surface on timescales of weeks to decades. Since the stratospheric circulation evolves more slowly than that of the troposphere below, it can contribute to predictability at the surface. Our synthesis of studies on the coupling between the stratosphere and the troposphere reveals that the stratosphere also contributes substantially to a wide range of climate-related extreme events. These extreme events include cold air outbreaks and extreme heat, air pollution, wildfires, wind extremes, and storm clusters, as well as changes in tropical cyclones and sea ice cover, and they can have devastating consequences for human health, infrastructure, and ecosystems. A better understanding of the vertical coupling in the atmosphere, along with improved representation in numerical models, is therefore expected to help predict extreme events on timescales from weeks to decades in terms of the event type, magnitude, frequency, location, and timing. With a better understanding of stratosphere-troposphere coupling, it may be possible to link more tropospheric extremes to stratospheric forcing, which will be crucial for emergency planning and management.
The Marine Geophysical Record of Past Ice Sheets
Authors: Batchelor Christine
Published: March 2021

An understanding of the former configuration and dynamics of ice sheets is essential to constrain numerical models of past environmental conditions and predict the likely future responses of ice sheets to climate change. Evidence of past ice-sheet activity is often well-preserved on and beneath the seafloor of glaciated continental margins, where it can be analysed using a variety of marine geophysical techniques. In this presentation, I will describe how marine geophysical data can be used to investigate former ice-sheet behaviour at different temporal scales, drawing on recent examples from my research. First, 2D and 3D seismic data show how mid- and high-latitude continental margins have been shaped by the repeated advance and retreat of ice sheets during the last three million years. Secondly, bathymetric data enable the interpretation of glacial landforms preserved on the seafloor, revealing the dynamic behaviour of ice masses since the Last Glacial Maximum. Finally, the recent application of autonomous underwater vehicles to acquire high-resolution geophysical data provides a step-change in our ability to image submarine landforms and facilitates new interpretations about ice dynamics at fine temporal and spatial scales.
Using thermo-mechanical models to bridge scales between experimental rheology and large-scale observational constraints on mantle and plate dynamics
Authors: Garel Fanny , Thoraval Catherine , Tommasi Andrea , Demouchy Sylvie , Davies D. Rhodri
Published: March 2021

Mantle convection and plate dynamics transfer and deform solid material on scales of hundreds to thousands of km. However, viscoplastic deformation of rocks arises from motions of defects at sub-crystal scale, such as vacancies or dislocations. In this study, results from numerical experiments of dislocation dynamics in olivine for temperatures and stresses relevant for both lithospheric and asthenospheric mantle (800–1700 K and 50–500 MPa; ) are used to derive three sigmoid parameterizations (erf, tanh, algebraic), which express stress evolution as a function of temperature and strain rate. The three parameterizations fit well the results of dislocation dynamics models and may be easily incorporated into geodynamical models. Here, they are used in an upper mantle thermo-mechanical model of subduction, in association with diffusion creep and pseudo-brittle flow laws. Simulations using different dislocation creep parameterizations exhibit distinct dynamics, from unrealistically fast-sinking slabs in the erf case to very slowly-sinking slabs in the algebraic case. These differences could not have been predicted a priori from comparison with experimentally determined mechanical data, since they principally arise from feedbacks between slab sinking velocity, temperature, drag, and buoyancy, which are controlled by the strain rate dependence of the effective asthenosphere viscosity. Comparison of model predictions to geophysical observations and to upper-mantle viscosity inferred from glacial isostatic adjustment shows that the tanh parameterization best fits both crystal-scale and Earth-scale constraints. However, the parameterization of diffusion creep is also important for subduction bulk dynamics since it sets the viscosity of slowly deforming domains in the convecting mantle. Within the range of uncertainties of experimental data and, most importantly, of the actual rheological parameters prevailing in the upper mantle (e.g. grain size, chemistry), viscosity enabling realistic mantle properties and plate dynamics may be reproduced by several combinations of parameterizations for different deformation mechanisms. Deriving mantle rheology cannot therefore rely solely on the extrapolation of semi-empirical flow laws. The present study shows that thermo-mechanical models of plate and mantle dynamics can be used to constrain the effective rheology of Earth's mantle in the presence of multiple deformation mechanisms.
Joint design of floating solar plant and dam operating policies for waterborne epidemics control: an assessment on the Kariba dam
Authors: Amaranto Alessandro , Castelletti Andrea
Published: March 2021

With more than 200 dams currently under construction in the Sub-Saharan region, hydropower is expected to dominate the African renewable energy market in the coming decades. Even though the construction of new dams has been widely recognized as a key factor in promoting energy security, damming rivers also augments the volume of stagnant water, inevitably enhancing the transmission of malaria by creating new vector breeding habitats. The interdependence between large dams and malaria transmission constitutes an extremely critical public health challenge in Africa. Nowadays, managing drawdown rates into reservoir operation as a malaria control measure appears a viable solution to reduce the spread of the virus near large reservoirs, notwithstanding undesirable outcomes in terms of hydropower generation. In this regard, recent technological developments in the field of floating solar photovoltaic installations open the path for flexible hydropower operation by boosting photovoltaic energy generation using the same electricity transmission infrastructure. The aim of this study is to propose an integrated framework, where the optimal floating solar sizing and reservoir operations are jointly designed for minimizing malaria diffusion without compromising the ability of the energy sector to fulfill energy demands. The framework employs Evolutionary Multiobjective Direct Policy Search into a novel approach to floating solar photovoltaic size planning, which internalizes the operation design problem. The potential of the proposed framework is tested in the Zambezi river basin, where the Kariba dam is mainly operated for hydropower production, with considerable negative health effects in the proximity of the reservoir. Numerical results show that design alternatives coupling reservoir operation with floating solar photovoltaic largely dominates pure management solutions in terms of malaria spread and energy generation. Besides, the relatively limited (from 0.2 to 1.5% of the total lake area) optimal extent of the photovoltaic plant highlights the potential economic benefits of increasing the penetration of this technology in Sub-Saharan Africa, with capital costs balanced by boosted energy income within the first seven years from the initial investment.
Water transport in European Beech roots (<5mm) under drought in the south of Lower Saxony
Authors: Messinger Eva , Coners Heinz , Hertel Dietrich , Leuschner Christoph
Published: March 2021

Climate models predict hotter and dryer summers in Germany, with longer periods of extreme droughts like in summer 2018. How does this affect the water uptake and transport in tree roots growing in the top- and subsoil?

In summer 2018 and 2019 we measured the water transport in fine roots (<5mm) of European Beech on tertiary sand and triassic sandstone up to 2 m depth. We adapted the well-established HRM technique to enable measurements of very small sap flow rates in small roots. Thus, we measured the water transport as a temperature ratio of a stretching heat pulse.

Relating sap flow to root surface area, root depth, anatomy, soil moisture, and VPD allows for interesting insights in tree water uptake rates: Where are the limits of drought intensity and duration, for water uptake and recovery of small roots? Are there differences in the function of top- and subsoil roots? Are roots specialized for water transport or nutrient uptake? The investigated data gives a first hint on how the water transport in Beech roots differs with changes in the soil moisture and VPD under changing climate.
CMIP6 data documentation and citation in IPCC's Sixth Assessment Report (AR6)
Authors: Stockhause Martina , Matthews Robin , Pirani Anna , Treguier Anne Marie , Yelekci Ozge
Published: March 2021

The the amount of work and resources invested by the modelling centers to provide CMIP6 (Coupled Model Intercomparison Project Phase 6) experiments and climate projection datasets is huge, and therefore it is extremely important that the teams receive proper credit for their work. The Citation Service makes CMIP6 data citable with DOI references for the evolving CMIP6 model data published in the Earth System Grid Federation (ESGF). The Citation Service as a new piece of the CMIP6 infrastructure was developed upon the request from the CMIP Panel.

CMIP6 provides new global climate model data assessed in the IPCC's (Intergovernmental Panel on Climate Change) Sixth Assessment Report (AR6). Led by the Technical Support Unit of IPCC Working Group I (WGI TSU), the IPCC Task Group on Data Support for Climate Change Assessment (TG-Data) developed FAIR data guidelines, for implementation by the TSUs of the three IPCC WGs and the IPCC Data Distribution Centre (DDC) Partners. A central part of the FAIR data guidelines are the documentation and citation of data used in the report.

The contribution will show how CMIP6 data usage is documented in IPCC WGI AR6 from three angles: technical implementation, collection of CMIP6 data usage information from the IPCC authors, and a report users’ perspective.

 

Links:

CMIP6 Citation Service: http://cmip6cite.wdc-climate.de

CMIP6: https://pcmdi.llnl.gov/CMIP6/

IPCC AR6: https://www.ipcc.ch/assessment-report/ar6/

IPCC AR6 WGI report: https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/

IPCC TG-Data: https://www.ipcc.ch/data/