bluuebunny/crossref_metadata_2025 huggingface dataset:
Geochemistry of basic magmatism of Western Antarctic Rift: implications for volatiles storage and recycling in the mantle
Authors: Giacomoni Pier Paolo , Ferlito Carmelo , Bonadiman Costanza , Casetta Federico , Ottolini Luisa , Zanetti Alberto , Coltorti Massimo
Published: March 2020

The petrologic study of olivine-hosted melt inclusions (MIs) from alkaline primary Cenozoic basalts of Northern Victoria Land (Antarctica) provide new insights on the role of volatiles in the onset of rift-related magmatism. The concentration of volatile species (H2O, CO2, F, Cl) have been determined by Secondary Ion Mass Spectrometry (SIMS) on a selection of MIs which have been previously re-homogenized at high pressure and temperature conditions in order to avoid any heterogeneity and reducing the H diffusion. The least differentiated MIs vary in composition from basanitic to alkaline basalts, analogously to what is found in McMurdo volcanics, while their volatile concentrations reach up to 2.64 wt% H2O, 3900 ppm CO2, 1377 ppm F and 1336 Cl. Taking into account the most undegassed MIs a H2O/(H2O+CO2) ratio equal to 0.88 was determined, which in turn brings the CO2 content in the basanitic melt with the highest water content up to 8800 ppm.

Major and trace element melting modelling indicate that basanite and alkali basalt composition can be reproduced by 3 and 7% of partial melting of an amphibole-bearing spinel lherzolite respectively. Assuming a perfect incompatible behavior for H2O and CO2 these melting proportions allow to constrain the water and CO2 contents in the mantle source in the range 780-840 and 264-273 ppm respectively. The resulting CO2/Nb, CO2/Ba and H2O/Ce ratio are lower than those estimated for Depleted MORB Mantle (DMM), suggesting that the NVL Cenozoic alkaline magmatism could be originated by an enriched mantle source composed by a range from 70% to 60% of Enriched Mantle (EM) and from 30% to 40% of Depleted Morb Mantle (DMM).

A global comparison of fluid-related, highly incompatible and immobile/low incompatible elements such as Li, K, Cl, Ba, Nb, Dy and Yb allow to put forward that the prolonged (~500 to 100 Ma) Ross subduction event played a fundamental role in  providing the volatile budget into the lithospheric mantle before the onset of the Cenozoic continental rifting.
Electrodynamic Coupling and Dissipation of Thermospheric Winds
Authors: Buchert Stephan C.
Published: March 2020

A so far simplified model considers the response of the magnetized ionosphere
to neutral winds and the so created effective electrodynamic coupling in
neutral atmosphere dynamics.  The effect resembels viscosity, but the
geomagnetic field couples winds also over large distances.  As a prominent
example the Sq variations are presented as a system that couples the winds
between hemispheres at magnetically conjugate points. The interaction between
hemispheres tends to force the large scale wind systems towards alignment with
magnetic coordinates and towards mirror symmetry with respect to the magnetic
equator. This is, however, for the Earth's thermosphere, never completed
because the time constant exceeds the 24 hours over which dynamics driven by
the energy input from solar radiation creates new winds.

Wind differences are so reduced and kinetic energy gets dissipated. From
observed magnetic Sq variations we estimate that a typical average dissipation
rate by interhemisphere electrodynamic coupling is roughly 0.1 to 1 % of the
heating rate resulting from the absorption of EUV solar radiation.

The same model applies when a neutral wind varies along the geomagnetic field
within the dynamo layer of the ionosphere, for example due to tides and gravity
waves. As a result such neutral wind variations also tend to get evened out and
Joule heat is produced. At mid and high latitudes so upward propagating gravity
waves get damped when they reach to ionospheric dynamo region.
Real-world rogue wave probabilities
Authors: Häfner Dion , Gemmrich Johannes , Jochum Markus
Published: March 2020

Despite several strong hypotheses on how rogue waves can be generated in idealized conditions, the actual real-world causes of these waves are still largely unknown. We credit this to insufficient amounts of observational data and a missing robust probabilistic framework to analyze the available data.

We adress these issues by processing over 1 billion waves measured in the North Pacific and organizing them into a comprehensive catalogue. Through a robust, machine-learning driven analysis, we then identify several characteristic sea conditions that lead to significantly higher risks to encounter a rogue wave. This, in turn, yields quantitative evidence on the relative importance of the underlying physical mechanisms.
Spatial and temporal variability of benzo[a]pyrene over Poland based on modelling and observations
Authors: Kaminski Jacek W. , Struzewska Joanna , Durka Pawel , Jeleniewicz Grzegorz , Kawka Marcin
Published: March 2020

Benzo[a]pyrene is relatively stable in the atmosphere and can be transported on a regional scale. Benzo[a]pyrene concentrations exceed standard limits in many regions of the world. It is proved that this compound is harmful to the environment and human health.

According to the CAFÉ Directive (2008/50/EC), the objective is to achieve a concentration of B[a]P below 1ng/m3 in PM10 aerosol. Observed B[a]P concentration in Poland is among the highest in Europe. These exceedances are attributed to the emission from individual heating, where many old installations are still in operation. Major B[a]P emissions are due to low-quality fuels and non-reported municipal waste burning.

To support the Chief Inspectorate of Environmental Protection in the frame of the annual assessment for 2018 and five-year assessment for the period 2014-2018, the spatial distribution of B[a]P was calculated using the GEM-AQ model (Kaminski et al. 2008). A new national high-resolution bottom-up emission inventory was used for the entire area of Poland. The results at the resolution of 2.5 km were compared with observations from over 100 stations from the National Measurement Network. We will discuss the spatial and seasonal variability od B[a]P concentrations as well as year-to-year changes related to meteorological conditions.

 
Changes in the relationship between the East Asian winter monsoon and ENSO under global warming
Authors: Jia Zixuan , Bollasina Massimo , Li Chaofan , Doherty Ruth , Wild Oliver
Published: March 2020

The East Asian winter monsoon (EAWM) is a prominent feature of the northern hemisphere atmospheric circulation during boreal winter, which has a large influence on weather and climate of the Asian-Pacific region. At interannual time scales, the strength of the EAWM is strongly influenced by the El Niño-Southern Oscillation (ENSO), while the ENSO-EAWM relationship displays pronounced interdecadal variations associated with changes in the ENSO teleconnection pathways to East Asia. Using future transient simulations from the Max Planck Institute-Grand Ensemble (MPI-GE), changes in the ENSO-EAWM relationship are examined at various global warming levels during the 21st-century. Results indicate that this relationship will enhance from present-day to +1.5°C, and then weaken until +3°C, strongly impacted by changes in anthropogenic forcing with internal variability playing a negligible role. The ENSO-EAWM relationship is strongly related to the background mean state of both the EAWM and ENSO under global warming. Both the climatological EAWM strength and the ENSO-related anomalies across the Asian-Pacific region contribute to changes in the ENSO-EAWM relationship. Furthermore, anthropogenic aerosols are also found to play a major role in influencing the ENSO-EAWM relationship under moderate warming (up to 1.5°C).
Microclimatic effects on spring budburst and autumn leaf coloration of four temperate tree species
Authors: Vitasse Yann , Kaewthongrach Rungnapa , Baumgarten Frederik
Published: March 2020

Recent study highlighted large microclimatic variation occurring within forests, especially concerning light and temperature. In this study we aimed to quantify to what extent variation in light, soil humidity, nutrient availability and bud temperature alter the phenology of four tree species (Fagus sylvatica, Quercus robur, Prunus avium and Fraxinus excelsior). Various treatments were applied to seedlings grown in large wooden boxes in situ conditions near Zurich. The different treatments included shade (~60% of light transmission), reduced precipitation using rain shelters, fertilizer, additional watering during summer, as well as painting buds in black or white to alter bud temperature via albedo change. Budburst timing and leaf coloration were observed twice a week during the spring and autumn 2019.

Preliminary results show that the time of budburst was delayed when seedlings were grown under shade conditions (from +3 to +11 days for Quercus and Fagus respectively) or when buds are painted in white compared to black (from +4 to +11 days from Quercus and Prunus respectively), whereas no significant effect was found under reduced precipitation for any species. For the timing of leaf coloring, a very significant effect of light was found with a delay of +22, +39 and +42 days observed under shade conditions for Fraxinus, Prunus and Fagus. Preliminary results based on the temperature recorded within the buds or close to the plants suggest that bud temperature explain the differences observed in the time of bud burst among the different treatments, though light intensity may have also directly influenced bud development of Fagus in spring. Regarding leaf coloration, our results suggest that light intensity has a strong influence on most of temperate trees whereas soil water and nutrient content has only a minor species-specific effect. Overall, our results underline the importance of microclimatic variation to explain phenological variation among trees within or among nearby sites, especially in topographically complex regions as in mountains or in forests with varying vertical structure.
Continuous hydrogen production facilitates handling of climatic extreme events in a fully renewable Swedish power system
Authors: Mikovits Christian , Schmidt Johannes , Wetterlund Elisabeth
Published: March 2020

Hydrogen produced from renewable electricity can play an important role in deep decarbonisation of industry such as steel-production. Steady, full capacity hydrogen production can also be a source of negative balancing capacity to increase flexibility of fully renewable power systems. However, there is a trade-off between attaining economically favorable high-full load hours for the electrolyzer and the provision of system flexibility. To better understand this trade-off, we apply a dispatch model for the Swedish power system with long-term time series 29 years of electricity generation (hydro and wind) and demand at hourly temporal resolution, thus being able to represent climate extreme events.

In our hydrogen demand scenarios for Sweden we limit the hydrogen usage options to two pathways that are currently under development: for hydrotreatment of different bio-based feedstocks in biofuel production, and as use as reductant in fossil-free primary steel-making according to the HYBRIT (Hydrogen Breakthrough Ironmaking Technology) route. We applied three different scenarios that can be seen to represent either different ambition levels for decarbonization, or different time perspectives, and which result in different electrolysis loads on the system:

    • 850 MW electrolyzer capacity, corresponding to 5 TWh·a-1 hydrogen production for biofuels
    • 1700 MW electrolyzer capacity, corresponding to 10 TWh·a-1 hydrogen production for biofuels
    • 3500 MW electrolyzer capacity, corresponding to 10 TWh·a-1 hydrogen production for biofuels and 10.5 TWh·a-1 hydrogen for steel-making.

In comparison to the baseline scenario, more wind power is available in the system, as wind power is scaled accordingly to the average electrolyzer demand.

Results very well present the seasonal differences in demand and how hydro power and partly thermal power are used to balance seasonal differences i.e. extreme events are only observed in the winter months. Also, significant curtailment of wind power capacity is present at some points but less so in the winter months. Extreme events are considerably decreased when increasing electrolyzer capacity, as the electrolyzers are operated flexibly and therefore provide significant positive balancing energy to the system in times of low generation events. In particular, longer events are reduced, creating shorter events to some extent.
Even under the assumption of very low electrolyzer ramping capacities and no dispatch of thermal power for hydrogen production, electrolyzers operate at about 90% of full load and still provide sufficient flexibility to reduce the impact of climatic extreme events on the Swedish power system significantly.
Human influence strengthens the contrast between tropical wet and dry regions
Authors: Schurer Andrew , Hegerl Gabriele , Ballinger Andrew , Friedman Andrew
Published: March 2020

Climate models predict a strengthening contrast between wet and dry regions in the tropics and subtropics (30°S-30°N), and data from the latest model intercomparison project (CMIP6) support this expectation. Rainfall in ascending regions increases, and in descending regions decreases in both climate model and reanalysis data. This strengthening contrast can be captured by tracking rainfall change each month in the wettest and driest third of the tropics and subtropics combined. Since wet and dry regions are selected individually for each model ensemble member, and the observations, and for each month, this analysis is largely unaffected by biases in location of precipitation features. Blended satellite and in situ data support the model-simulated tendency to sharpening contrasts between wet and dry regions, with rainfall in wet regions increasing substantially contrasted by a slight decrease in dry regions. These new datasets allow us to detect with more confidence the effect of external forcings on these changes, attribute them for the first time to the response to anthropogenic and natural forcings separately, and determine that the observed trends are statistically larger than the model responses. Our results show that the observed change is best explained by increasing greenhouse gases with natural forcing contributing some increase following the drop in wet region precipitation after Mount Pinatubo, while anthropogenic aerosol effects are expected to show a weak tropic-wide trend at the present time of flat global aerosol forcing. As expected from climate models, the observed signal strengthens further when focusing on the wet tail of spatial distributions in both models and data.
Machine learning technique for the quantitative evaluation of tight sandstone reservoirs using high-pressure mercury-injection data
Authors: Liu JingJing , Liu JianChao
Published: March 2020

In recent years, China's unconventional oil and gas exploration and development has developed rapidly and has entered a strategic breakthrough period. At the same time, tight sandstone reservoirs have become a highlight of unconventional oil and gas development in the Ordos Basin in China due to its industrial and strategic value. As a digital representation of storage capacity, reservoir evaluation is a vital component of tight-oil exploration and development. Previous work on reservoir evaluation indicated that achieving satisfactory results is difficult because of reservoir heterogeneity and considerable risk of subjective or technical errors. In the data-driven era, this paper proposes a machine learning quantitative evaluation method for tight sandstone reservoirs based on K-means and random forests using high-pressure mercury-injection data. This method can not only provide new ideas for reservoir evaluation, but also be used for prediction and evaluation of other aspects in the field of oil and gas exploration and production, and then provide a more comprehensive parameter basis for “intelligent oil fields”. The results show that the reservoirs could be divided into three types, and the quantitative reservoir-evaluation criteria were established. This method has strong applicability, evident reservoir characteristics, and observable discrimination. The implications of these findings regarding ultra-low permeability and complex pore structures are practical.
Reconstructing 10 years of spatio-temporal aseismic slip history along the San Andreas Fault
Authors: Michel Sylvain , Jolivet Romain , Gualandi Adriano , Guardonio Blandine , Lengliné Olivier , Dalaison Manon , Benoit Angélique
Published: March 2020

The San Andreas Fault creeping section is generally considered as slipping continuously and aseismically, at a rate of about 35 mm/yr. However, recent studies, using either Global Positioning System (GPS) network or Interferometric Synthetic Aperture Radar (InSAR) data, have highlighted spatial and temporal variations of slip rate. Here, we combine GPS, InSAR, creepmeter and seismicity data over the 2008-2018 period, taking advantage of their complementary spatial and temporal resolutions, to detail a comprehensive picture of episodic acceleration and deceleration slip patterns. For this purpose, we use a variational Bayesian Independent Component Analysis (vbICA) decomposition to separate geodetic deformation due to non-tectonic sources from signals of tectonic origin. The fault slip kinematics is reconstructed by linear inversion of each Independent Component related to transient tectonic activity. We document aseismic slip acceleration transients and discuss their origin.
Identifying seismically active blind thrusts by geomorphology and seismic reflection profiles in a reactivated back-arc failed rift basin, Northeast Japan
Authors: Ishiyama Tatsuya , Sato Hiroshi , Kato Naoko , Abe Susumu , Yokoi Satoru , Shimizu Hidehiko , Okuda Mao
Published: March 2020

Back-arc failed rifts in many subduction zones are recognized as mechanically and thermally weak zones that possibly play important roles in strain accommodation at later post-rift stages within the overriding plates. In case of Miocene back-arc failed rift structures in the Sea of Japan in the Eurasian-Pacific subduction system, Quaternary activity of post-rift positive inversion of normal faults are predominant, part of which are blurred by fast subsidence in alluvial plains above densified lower crust associated with mafic intrusion into rift axis. To define such active fault-related structures in alluvial plain with subtle geomorphic signatures, we collected new high-resolution seismic reflection data across the alluvial plain (Shonai plain) in Northeast Japan, where an enigmatic 1894 earthquake event (M7.0) caused devastating damages on local communities. We deployed hundreds of portable offline seismic recorders covering whole seismic lines and provided seismic shots using Vibroseis trucks at all nearby receivers, to create high-resolution, depth-converted cross sections based on seismic reflection data. Depth-converted sections to 2-3 km depth clearly illuminate pairs of west-vergent, thrust-related folds that deformed Miocene to Pleistocene sedimentary and volcaniclastic rocks. Among them, we defined previously unrecognized, west-dipping blind thrust structures beneath coastal plains that deform Pleistocene and Holocene basin-fill units. Structures of these blind thrusts are consistent with distribution of earthquake-damaged houses and, at least partly, might activate during the 1894 seismic event. Interestingly, upward extension of synclinal axial surfaces are consistent with very subtle west-facing fold scarps that deform alluvial plain deposits illuminated by DEM, suggesting recent fault activities and related structural growth of thrust-related folds. These examples nicely demonstrate that combining subtle geomorphology of constrained by DEM and high resolution seismic reflection profiling is an effective tool to define recent structural growth and activity of otherwise inaccessible blind thrust structures and mitigating their elusive seismic hazards.
ANIR, a tool for analysis of Infrared spectra
Authors: Ródenas Mila , Picquet-Varrault Bénédicte , Munoz Amalia
Published: March 2020

In recent years, the miniaturization of the instruments and the environmental concern has led to a wider usage of spectroscopic techniques to characterize harmful compounds in many research centres. These techniques, which benefits include high temporal resolution, non-invasiveness and good sensitivity, allow to simultaneously analyze a number of compounds in the gas phase.

This work presents a tool for the analysis of Fourier Transform Infra-Red (FTIR) developed within the frame of EUROCHAMP projects to evaluate compounds contained in a complex gas mixture. Based on Multiple Linear Regression, the analysis method has been improved with an algorithm to locally filter the spectra, removing unwanted overlapping broadband curves due to aerosols, optical misalignment or broad absorptions of unknown compounds. This software is widely used among FTIR users within the simulation chambers community and beyond. Tests on complex air masses versus other methods typically used have proven its suitability in the determination of compounds even in the presence of unidentified interfering compounds. In fact, it improves the signal to noise ratio by reducing interferences, which results in a better data quality. It can be used for the analysis of absorption spectra from different instrumental approaches (e.g. FTIR, FTIR-ATR) and extended to other spectral regions (e.g. UV/Vis). The software is available as @ANIR and includes a Graphical User Interface (GUI), which is a user-friendly tool that provides the temporal profile of the analysed compounds and allows traceability of the analysis setup parameters. This tool can be downloaded for free upon registering in the Eurochamp-2020 webpage (www.eurochamp.org). Together with @ANIR, a Library of Analytical Resources (LAR) containing nearly 400 calibrated IR spectra of gas compounds at a good spectral resolution can be accessed through the same website. These complementary tools can ease the analysis of FTIR spectra by the users, improving the quality and reliability of the data.

Acknowledgements

This project/work has received funding from the European Union’s Horizon 2020 research and innovation programme through the EUROCHAMP-2020 Infrastructure Activity under grant agreement No 730997. CAPOX from the Spanish R+D program, Ref RTU2018-097768-B-C21 is acknowledged. F. CEAM is partly supported by Generalitat Valenciana

References

Analysis software, EUROCHAMP-2020 Data Center, https://data.eurochamp.org/anasoft/

Library of Analytical Resources, EUROCHAMP-2020 Data Center, https://data.eurochamp.org/library-of-analytical-resources/

M. Ródenas, A. Muñoz, GUI for the use with FTIR analysis software. D3.5 of the EUROCHAMP-2020 project.
The Spatial Pattern of Ski Areas and Its Driving Factors in China: A Strategy for Healthy Development of the Ski Industry
Authors: An Hongmin , Xiao Cunde , Ding Minghu
Published: March 2020

The development of ski areas would bring socio-economic benefits to mountain regions. At present, the ski industry in China is developing rapidly, and the number of ski areas is increasing dramatically. However, the understanding of the spatial pattern and driving factors for these ski areas is limited. This study collected detailed data about ski areas and their surrounding natural and economic factors in China. Criteria for classification of ski areas were proposed, and a total of 589 alpine ski areas in China were classified into three types: ski resorts for vacationing (va-ski resorts), ski areas for learning (le-ski areas) and ski parks to experience skiing (ex-ski parks), with proportions of 2.1%, 15.4% and 82.5%, respectively, which indicated that the Chinese ski industry was still dominated by small-sized ski areas. The overall spatial patterns of ski areas were clustered with a nearest neighbor indicator (NNI) of 0.424, in which ex-ski parks and le-ski areas exhibited clustered distributions with NNIs of 0.44 and 0.51, respectively, and va-ski resorts were randomly distributed with an NNI of 1.04. The theory and method of spatial autocorrelation were first used to analyze the spatial pattern and driving factors of ski areas. The results showed that ski areas in cities had a positive spatial autocorrelation with a Moran’s index value of 0.25. The results of Local Indications of Spatial Association (LISA) showed that ski areas were mainly concentrated in 3 regions: the Beijing-centered Yanshan-Taihang Mountains and Shandong Hill areas, the Harbin-centered Changbai Mountain areas and the Urumqi-centered Tianshan-Altay Mountain areas. The first location was mainly driven by socio-economic factors, and the latter two locations were mainly driven by natural factors. Ski tourism in China still faces many challenges. The government sector should strengthen supervision, develop a ski industry alliance, and promote the healthy and sustainable development of the ski industry in the future.
Determination of aerosol size and microphiysical proprierties based on multi-wavelength raman lidar measurements in the framework of HyMeX-SOP1
Authors: De Rosa Benedetto , Di Girolamo Paolo , Summa Donato
Published: March 2020

Tropospheric aerosols  are a fundamental component of the Earth’s radiation budget. In order to properly estimate their direct and indirect effect, accurate measurements of aerosol size and microphysical properties are required.A limited number of techniques are presently available and capable to provide these measurements.

Multi-wavelength Raman lidars Raman lidars have strong potential. However,theireffectiveness and reliability of need to be assessed and verified against independent measurements.

This abstract reports measurements that were carried out by the Raman lidar system BASIL in the frame of the Hydrological Cycle in the Mediterranean Experiment – Special Observation Period 1 (HyMeX-SOP1).The considered dataset represents a good opportunity to verify the quality of retrievals in terms of size and microphysical properties obtained from multi-wavelength Raman lidars.

A specific case study was selected revealing the presence of variable aerosol properties at different altitudes. Specifically, Raman lidar measurements on 02 October 2012 show the presence of two distinct aerosol layers, a lower one extending up to ~3 km and an upper one extending from 3.5 km to 4.7 km. Aerosol and size microphysical properties are determined from multi-wavelength measurements of particle backscattering and extinction profiles based on the application of  a retrieval scheme which employs Tikhonov’s inversion with regularization. Inversion results suggest a size distribution with the presence, in both the lower and upper aerosol layer, of two particle modes (a fine mode, with a radius of ~0.2 mm, and a coarse mode, with radii in the range 2-4 mm), volume concentration values of 2-4 mm3cm-3and effective radii in the  range 0.2-0.6 mm.

This effort benefited from the dedicated flights of the French research aircraft ATR42, equipped with a variety of in situ sensors for measuring aerosol/cloud size and microphysical properties. Aerosol size and microphysical properties retrieved from multi-wavelength Raman lidar measurements were compared with simultaneous and co-located in-situ measurements.
Miniaturized, Lightweight, Cost-effective and Fast Response Particle Classifier
Authors: Lekaki Nikoleta , Costi Marinos , Biskos George , Maisser Anne
Published: March 2020

Aerosol particles properties depend strongly on their particle size and they have significant effects on both, human health and environment. Nanometer sized particles possess special electrical, optical, and/or magnetic properties. This is one of the reasons which started the interest towards studying aerosol particles in the nanometer size range (Chen and Pui, 1995). The most efficient tool for determining the size of aerosol particle in the sub-micrometer and nanometer range is the differential mobility analyzer (DMA). This popular tool has two coaxial cylindrical electrodes between of them a potential difference is applied and forces the charged polydisperse aerosol to migrate from one electrode to another. Only those particles which have an electrical mobility in a narrow range, the will pass through the classifier (Stolzenburg, 1988).   Classifying aerosols according to their electrical mobility dates back to the first half of the 20th century and from that time plethora different DMAs have been build and their performances have been tested according to their transfer function and size resolution. One major limitation of classical DMAs is the time it takes to scan over the entire size range to get the size distribution of the aerosol. This is especially leading to the loss of information if the aerosol is changing its size and/or concentration rapidly. This happens for instance during new particle formation events, or also when the measurement takes place on fast moving platforms, such as cars, or airplanes.

The present work evaluates the performance of two different, newly developed DMA types, that aim towards overcoming this limitation. This is done by replacing the classic design of a single monodisperse outlet DMA to a multiple monodisperse outlet DMA. In our case the DMAs have three monodisperse outlets and are 3D-printed (namely, the 3MO-DMA) (Chen et al., 2007; Giamarelou et al., 2012; Barmpounis et al., 2016; Bezantakos et al., 2016). The 3MO-DMA is not only a fast response instrument able to sizing three different sizes ranges at the same time but also is a cost-effective and lightweight instrument suitable to get measurements not only ground based but also on Unmanned Aerial Vehicles or balloons.
Ergodicity of a stochastic Two Layer Quasi Geostrophic Model
Authors: Carigi Giulia , Bröcker Jochen , Kuna Tobias
Published: March 2020

In the Climate Sciences, there is great interest in understanding the long term average behaviour of the climate system. In the context of climate models, this behaviour can be expressed intrinsically by concepts from the theory of dynamical systems such as attractors and invariant measures. In particular to ensure long term statistics of the model are well defined from a mathematical perspective, the model needs to admit a unique ergodic invariant probability measure.

In this work we consider a classic two layer quasi geostrophic model, with the upper layer perturbed by additive noise, white in time and coloured in space, in order to account for random forcing, for instance through wind shear. Existence and uniqueness of an ergodic invariant measure is established using a technique from stochastic analysis called asymptotic coupling as described in [1]. The main difficulty in the proof is to show that two copies of the system that are driven by the same noise realisation can be synchronised through a coupling. This coupling has to be finite dimensional and act only on the upper layer. 

Our results will be a key step to allow rigorous investigation of the response theory for the system under concern.

 

[1] Glatt-Holtz, N., Mattingly, J.C. & Richards, G. J Stat Phys (2017) 166: 618.  
Producing solar flare predictions using support vector machine (SVM) applied with ionospheric total electron content (TEC) global maps
Authors: Asaly Saed , Gottlieb Lee-Ad , Reuveni Yuval
Published: March 2020

Ground and space-based remote sensing technology is one of the most useful tools for near-space environment studies and space weather research. During the last decade, a considerable amount of efforts in space weather research is being devoted for developing the ability to predict the exact time and location of space weather events such as solar flares and X-rays bursts. Despite the fact that most of the natural factors of such events can be modeled numerically, it is still a challenging task to produce accurate predications due to insufficient detailed and real‐time data. Hence, space weather scientists are trying to learn patterns of previous data distribution using data mining and machine learning (ML) tools in order to accurately predict future space weather events. Here, we present a new methodology based on support vector machines (SVM) approach applied with ionospheric Total Electron Content (TEC) data, derived from worldwide GPS geodetic receiver network that predict B, C, M and X-class solar flare events. Experimental results indicate that the proposed method has the ability to predict solar flare events of X and M-class with 80-94% and 78-93% accuracy, respectively. However, it does not succeed in producing similar promising results for the small-size C and B-class flares.
Rethinking large scale river routing by leveraging a field-scale resolving land surface model
Authors: Chaney Nathaniel , Vergopolan Noemi , Fisher Colby
Published: March 2020

Over the past decade there has been important progress towards modeling the water, energy, and carbon cycles at field scales (10-100 meter) over continental extents. One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via sub-grid hydrologic response units (HRUs); these HRUs are defined via cluster analysis of available field-scale environmental datasets (e.g., elevation). However, until now, there has yet to be complementary advances in river routing schemes that are able to fully harness HydroBlocks’ approach to sub-grid heterogeneity, thus limiting the added value of field-scale resolving land surface models (e.g., riparian zone dynamics, irrigation from surface water, and interactive floodplains). In this presentation, we will introduce a novel large scale river routing scheme that leverages the modeled field-scale heterogeneity in HydroBlocks through more realistic sub-grid stream network topologies, reach-based river routing, and the simulation of floodplain dynamics.

The primary features of the novel river routing scheme include: 1) each macroscale grid cell is assigned its own river network delineated from field-scale DEMs; 2) similar sub-grid reaches (e.g., Shreve order) are grouped/clustered to ensure computational tractability; 3) the fine-scale inlet/outlet reaches of the macroscale grid cells are linked to assemble the continental river networks; 4) river dynamics are solved at the reach-level via an implicit solution of the Kinematic wave with floodplain dynamics; 5) two way connectivity is established between each cell’s sub-grid HRUs and the river network. The resulting routing scheme is able to effectively represent sub-100 meter-delineated stream networks within Earth system models with relatively minor increases in computation with respect to existing approaches. To illustrate the scheme’s novelty when coupled to the HydroBlocks land surface model, we will present simulation results over the Yellowstone river in the United States between 2002 and 2018. We will show the added value of the scheme when compared to existing approaches with regards to floodplain dynamics, water management, and riparian corridors. Furthermore, we will present results regarding the scheme’s computational tractability to ensure the feasibility of its use within Earth system models. Finally, we will discuss the potential of this approach to enhance flood and drought monitoring tools, numerical weather prediction, and climate models.
Application of diffraction wavefront tomography to GPR data from a glacier
Authors: Bauer Alexander , Schwarz Benjamin , Delf Richard , Gajewski Dirk
Published: March 2020

In the recent years, the diffracted wavefield has gained increasing attention in the field of applied seismics. While classical seismic imaging and inversion schemes mainly focus on high-amplitude reflected measurements, the faint and often masked diffracted wavefield is neglected or even treated as noise. In order to be able to extract depth-velocity models from seismic reflection data, sufficiently large source-receiver offsets are needed. However, the acquisition of such multi-channel seismic data is expensive and often only feasible for the hydrocarbon industry, while academia has to cope with low-fold or zero-offset data. The diffracted wavefield is the key for extracting depth velocities from such data, as the moveout of diffractions – in contrast to reflections – can be measured in the zero-offset domain. Recently, we have demonstrated on multi-channel, single-channel and passive seismic data that by means of wavefront tomography depth-velocity models can be retrieved solely based on diffractions or passive seismic events along with the localizations of these scatterers. The input for wavefront tomography are so-called wavefront attributes, which can be extracted from the data in an unsupervised fashion by means of coherence analysis. In order to obtain the required diffraction-only data, we use a recently proposed scheme that adaptively subtracts the high-amplitude reflected wavefield from the raw data. Due to their most common acquisition geometry, most ground-penetrating-radar (GPR) data inherently lack offsets. In addition, GPR data generally contain a rich diffracted wavefield, which in turn contains information about sought-after structures, as diffractions are caused by small-scale heterogeneities such as faults, tips or edges. In this work, we show an application of the suggested workflow – coherence analysis, diffraction separation and diffraction wavefront tomography – to GPR data acquired at a glacier, resulting in a depth-velocity model and the localizations of the scatterers, both obtained in a fully unsupervised fashion. While the resulting  velocity model may be used for depth migration of the raw data, the localizations of the scatterers may in addition provide important information on the inner structure of the glacier in order to, for instance, localize water intrusions or fractures.
Comparison of univariate and multivariate bias-adjusting methods for hydrological impact assessment under climate change conditions
Authors: Van de Velde Jorn , De Baets Bernard , Demuzere Matthias , Verhoest Niko
Published: March 2020

Climate change is one of the largest challenges currently faced by society, with an impact on many systems, such as hydrology. To locally assess this impact, Regional Climate Model (RCM) data are often used as an input for hydrological rainfall-runoff models. However, RCMs are still biased in comparison with the observations. Many methods have been developed to adjust this, but only during the last few years, methods to adjust biases in the variable correlation have become available. This is especially important for hydrological impact assessment, as the hydrological models often need multiple locally correct input variables. In contrast to univariate bias-adjusting methods, the multivariate methods have not yet been thoroughly compared. In this study, two univariate and three multivariate bias-adjusting methods are compared with respect to their performance under climate change conditions. To do this, the methods are calibrated in the late 20th century (1970-1989) and validated in the early 21st century (1998-2017), in which the effect of climate change is already visible. The variables adjusted are precipitation, evaporation and temperature, of which the resulting evaporation and precipitation are used as an input for a rainfall-runoff model, to allow for the validation of the methods on discharge. The methods are also evaluated using indices based on the calibrated variables, the temporal structure, and the multivariate correlation. For precipitation, all methods decrease the bias in a comparable manner. However, for many other indices the results differ considerable between the bias-adjusting methods. The multivariate methods often perform worse than the univariate methods, a result that is especially pronounced for temperature and evaporation.
Filtering tide-generated internal waves using Convolutional Neural Networks
Authors: Lguensat Redouane , Fablet Ronan , Le Sommer Julien , Metref Sammy , Cosme Emmanuel
Published: March 2020

Starting from 2021, Surface  Water Ocean Topography (SWOT) satellite altimetry mission will provide an unprecedented amount of Sea Surface Height (SSH) measurements. In addition to allowing for a higher spatial resolution, SWOT will deliver two-dimensional horizontal SSH data thanks to its wide swath capacities, which is a remarkable leap compared to conventional current altimeters.

With the aim of extracting a clean SSH signal from the SWOT measurements, several challenges are expected to be encountered. In this work, we focus on filtering the footprints of Internal Gravity Waves (IGWs), this is of high interest for physical oceanographers who seek to better understand mesoscale and submesoscale ocean physics.

Thanks to recent developments in ocean numerical simulation, we can now have access to a considerable amount of simulation data with exceptional high spatial resolutions up to 1/60° and hourly temporal resolution. Here, we benefit from an advanced North Atlantic simulation of the ocean circulation (eNATL60) that models tidal motions, and design a supervised machine learning experiment that aims to test several techniques for filtering IGWs.

In particular, we show that deep convolutional neural networks are a relevant candidates for this task and presents promising results with regard to conventional linear filtering techniques. We also show how our method can be adapted to the context of the fast-sampling phase of SWOT, and can also take advantage from the presence of additional data such as Sea Surface Temperature.
The influence of volcanic eruptions on circulation regimes over the North Atlantic and their impact on European climate
Authors: Feng Yang , Khodri Myriam , Li Laurent , Sicre Marie-Alexandrine , Lebas Nicolas
Published: March 2020

Large volcanic eruptions influence climate on both annual and decadal time scales due to dynamical interactions of different climate components in the Earth's system. It is well established that the North Atlantic Oscillation (NAO) tends to shift towards its positive phase during the winter season in the first 1–2 years after large tropical volcanic eruptions, causing warming over Europe. However, other North Atlantic circulation regimes such as Atlantic Ridge or zonal regime have received less attention. This study explores the volcanic fingerprint in terms of patterns and mechanisms on the North Atlantic atmospheric circulation in IPSL-CM6A-LR model simulations for tropical eruptions of the last millennium using dedicated sensitivity experiments and observations.
Improved isotopic characterisation of methane emissions from biomass burning
Authors: Fisher Rebecca , Nisbet Euan , France James , Riddle Amber , Lowry David , Lanoiselle Mathias , Lu Xinyi , Kelly Bryce
Published: March 2020

Emissions of methane from combustion sources are typically distinguished by being enriched in 13C and 2H, causing a large isotopic shift to atmospheric methane δ13C and δD measurements downwind of fires.

The isotopic composition of the plant material being burnt has a strong effect on the isotopic composition of methane, with combustion of C4 plant material producing methane more enriched in 13C than C3 plant combustion. Characterisation of the bulk isotopic signature of methane emitted from large areas of biomass burning is required to improve our ability to use isotopes in global models and ascertain the extent to which fire emissions influence interannual variations in the methane budget.

Two approaches have been used to collect air samples from large areas of biomass burning for isotopic characterisation of methane emitted from the fires. In campaigns in Senegal, Uganda, Zambia and Finland, the UK’s FAAM research aircraft flew through fire plumes and onboard measurement of methane concentration allowed targeted sampling within the plumes. This work was carried out as part of the NERC highlight Global Methane Budget project (MOYA). Ground based sampling downwind of fires around Sydney, New South Wales in late 2019/early 2020 has allowed isotopic characterisation of those plumes. All air samples were measured by isotope ratio mass spectrometry at Royal Holloway University of London and Keeling plots used to identify source signatures, e.g. δ13C for fires in Senegal in March 2017 was -28.5 ± 0,8 , typical of C3 burning.

In this work we compare the isotopic signatures of methane from burning in these particular regions and discuss the extent to which the regional variability of the isotopic composition of fire emissions should be taken into account in global models using isotopes to constrain the global methane budget.
Harmonizing, merging and publishing hydropedological data for the Czech Republic
Authors: Strouhal Luděk , Kavka Petr , Beitlerová Hana , Žížala Daniel
Published: March 2020

Czech soil data is a mess. Modelling infiltration, or its probably most watched companion - runoff, has been quite a painful process for any researcher or practitioner studying any site larger or more heterogeneous than a few parcels of arable land. There are at least three main national soil databases in the Czech Republic, each of different age, scope, classification system and - most unfortunately - different administrator. So far Research Institute for Soil and Water Conservation has taken good care of data for agricultural land, while The Forest Management Institute did his job considering forest soils. A few other research institutes manage their own specific databases. There has been no service available providing consistent data for the whole country, nor methodology giving some guidelines on how to cope with differences in existing datasets, though a few large-scale applications and studies do exist. This contribution presents preliminary results of a running project TJ02000234 - Physical and hydropedological soil properties of the Czech Republic. It aims at harmonizing and combining available datasets and deriving layers of soil texture and hydropedological properties. Next the project aims at gathering available measurements of hydraulic properties of Czech soil types and their partial validation and extending with field measurements in the scope limited by the 2-years of project duration. The derived database and data products will be published in the form of a certified map as well as offered to professionals through an online GIS portal. Design planners in the Land consolidation, flood and soil erosion mitigation projects as well as professionals in public administration and researchers in environmental disciplines will benefit from the publication of this consistent data.