bluuebunny/crossref_metadata_2025 huggingface dataset:
Shifts in in High-Mountain Asia’s mountain-specific climate indicators derived with large ensemble modelling
Authors: Bonekamp Pleun , Wanders Niko , van der Wiel Karin , Lutz Arthur , Immerzeel Walter
Published: March 2020

Natural disasters in High Mountain Asia (HMA) are largely induced by precipitation and temperatures extremes. Precipitation extremes will change due to global warming, but these low frequency events are often difficult to analyse using (short) observed time series. In this study we analysed large  ensembles (2000 year) of present day climate and of a 2 °C and 3 °C warmer world produced with the EC-EARTH model. We performed a regional assessment of climate indicators related to temperature and precipitation (positive degree days, accumulated precipitation, (pre- and post-) monsoon precipitation), their sensitivity to temperature change and the change in return periods of extreme temperature and precipitation in a 2 and 3 °C warmer climate.

In general, the 2°C warmer world shows a rather homogeneous response of changes in climate indicators and return periods, while distinct differences between regions are present in a 3C warmer world and it no longer follows a general trend. This non-linear effect can indicate the presence of a tipping point in the climate system. The most affected regions are located in monsoon-dominated regions, where precipitation amounts, positive degree days, extreme temperature, extreme precipitation and compound events are projected to increase the most. Largest changes in climate indicators are found in the Hindu Kush and Himalaya regions. We also found that precipitation increases in HMA in a 3°C warmer world are substantially larger (13%) compared to the global average (5.9%). Additionally, the increase in weather extremes will exacerbate natural hazards with large possible impacts for the mountain people. The results of this study could provide importance guidance for formulating climate change adaptation strategies in HMA.
GeneSys Doublet: setup and test of a geothermal well doublet in Lower Cretaceous sandstones of northern Germany – an outlook.
Authors: Stechern André , Torsten Tischner , Prevedel Bernhard
Published: March 2020

The Federal Institute for Geosciences and Natural Resources (BGR) has drilled the approx. 3,900m deep geothermal well Groß Buchholz Gt1 as part of the GeneSys geothermal project. The Bunter sandstone (Lower Triassic) was initially recovered as the target formation for the borehole. Due to the difficult geological conditions found, it was decided to abandon the Bunter sandstones. It is now intended to heat the properties of the GEOZENTRUM Hannover (GZH) using a geothermal doublet. In addition to the direct benefit for the GZH from the utilization of this regenerative energy source and the associated relief for the environment, the demonstration of the use of multiple, low thickness sandstone layers is of particular importance in this project. It should be proven that the sandstones of the Wealden formation (Lower Cretaceous / Berriasian) at a depth of approximately 1200m are suitable for geothermal usage. Moreover, a reference site for locations with similar geological conditions will be created.

As a requirement for further technical work in the borehole, a bottom cementation will be carried out at the final depth of the wellbore. This seals the perforation at a depth of approx. 3,700m and the access to the Bunter sandstones. A sidetrack is then drilled out of the existing hole into the Wealden sandstones. For this, a window is milled at a depth of approx. 750m and the sidetrack is drilled down to a depth of approx. 1300m. The determination of the landing point of the sidetrack is the subject of current investigations, as the Wealden sandstones are spatially heterogeneous. The reinterpretation of existing seismic profiles is of great importance for this. After successful completion of the sidetrack and evaluating the production tests and after a successful production test a second well is drilled from the same drilling site to a target depth of approx. 1300 m. The calculated distance of the two holes at the target depth is approx. 500 m.

In the previous project, the sandstone layers of the Lower Cretaceous were examined for their suitability for geothermal use. A maximum expected transmissibility can be estimated from the sum of six suitable sandstone units (total 46m), as well as the average permeability of these units of approx. 75mD. This results in a maximum transmissibility to be expected of approx. 3.5Dm. The measured temperature at a depth of 1200m is exceptionally high with 69°C.

In order to further increase the productivity of the drilling, it is planned to open up or stimulate the target horizons with different drilling techniques: for example, radial jet drilling and / or acid stimulation.
Effects of earthquakes and antecedent droughts on landslide initiation in Italy
Authors: Zhu Xuehong , Dai Qiang , Zhuo Lu , Han Dawei , Zhang Shuliang
Published: March 2020

Earthquake and antecedent drought (drought for short) play important roles in triggering landslides, which change the formation condition of landslides by affecting topography, loose solid materials and water content. However, in most cases, landslide early warnings rely on rainfall thresholds or(/and) soil moisture conditions, without considering the effects of earthquake and drought. In this study, an analysis has been carried out on the latest version of Parametric Catalogue of Italian Earthquakes (Italian acronym CPTI15) and standardized precipitation index (SPI) (to represent droughts) and the landslide events in a northern Italian region in the past 116-years period 1901-2016. Based on the quantitative analysis on the relationship in time between landslides, earthquake activities and drought events, the interacting relationship between landslides, seismic activities and droughts were explored. It has been found that the impacts from earthquakes and droughts on landslides do exist. The impacts from earthquakes in the study area was less significant comparing with other regions (such as Wenchuan, China), and droughts play a complementarily minor role on landslides. Finally, a method is proposed for predicting the landslides based on early earthquake and drought monitoring and used on some cases. We expect this study can provide useful information for combining earthquake and drought in the landslide early warnings.
What explains the elevational upward shifts at the treeline ecotone?
Authors: Manrique-Alba Àngela , Beguería Santiago
Published: March 2020

Temperatures have increased worldwide in the last decades, with the most pronounced and rapid changes occurring at high altitudes and latitudes. Climate change has played an important role in modifying the altitudinal location of the treeline ecotone, i.e. the transition from timber line (the upper forest limit, defined by the presence of a continuous forest cover) to the treeline (the last upright trees reaching 2 or 3 m in height). Moreover, the influence of recent land use change (e.g., changes in pastoral use, tourism development) in treeline dynamics is increasingly acknowledged. We have compiled a dataset of treeline changes over the Pyrenees mountain range, extending over more than 12000 linear kilometres, representing a large study area that extends across a broad range of environmental conditions. The main objective was to assess the effects of climate change, past land uses and physiography on the treeline dynamics between 1956 and 2015. To explore the variation in treeline shifts we used pairs of aerial photographs taken in 1956 and 2015 and we identified the position of the tree line using a criterion based on canopy cover thresholds. Our findings show significant differences between tree line dynamics for the two analysed periods and allow us to infer the relative importance of climatic factors, land use change, and local anthropogenic influence modulating the treeline structure and its dynamics.
Design considerations for a dust collector on mesospheric rocket
Authors: Trollvik Henriette , Mann Ingrid , Havnes Ove , Olsen Sveinung , Eilertsen Yngve
Published: March 2020

Meteors ablation is a source of dust particles in the upper atmosphere. The remnants of meteor ablation that prevail in the mesosphere condense to nm-sized particles, denoted as Meteoric Smoke Particles (MSPs). Theory suggest that MSPs act as condensation nuclei for ice particles in the summer mesosphere, which form during summer months around the mesopause at high and mid latitudes. They are related to mesospheric phenomena such as the Noctilucent Clouds, Polar Mesospheric Summer and Winter Echoes (PMSE/PMWE). However, due to their altitude location, the only means of in situ measurement is with rocket experiments. There have been several attempts to collect these MSP particles with probes on rockets over the years, but no conclusive results have been reported so far.

UiT have proposed a new sample collector, the MEteoric Smoke Sampler (MESS). We report on the progress of the work that has focused on the design of the detector and simulation of the entry and impact of dust onto the detector. The focus of the planned measurements is on collecting ice particles, since the airflow affect them less than smaller MSPs. Estimations of the collection surface properties and impact energy are presented. An estimate of the expected mass in the traversed volume of one collecting plate, diameter of 3 mm diameter over 1 km, suggest that the volume contains ~1e8 particles. This corresponds to a mass of 7e16 amu. These estimates are made assuming spherical particles with average density 2.8 g per m3 and radius 1 nm, and an MSP density of 1e10 per m3. 
Processing waste from feldspar raw material as a potential source of certain strategic elements
Authors: Vrbický Tomáš , Přikryl Richard
Published: March 2020

Feldspar-rich leucogranite formed by metasomatic / hydrothermal alteration of original granite makes one of the key resources of feldspar raw material for ceramic / glass industries in the Czech Republic. Studied material is composed by prevailing albite and quartz accompanied with small amounts of minor / accessory phases which represent the major harmful components responsible for colour changes in final product. To improve quality of marketed feldspar, part of exploited raw material started to be processed by using magnetic separation in recent years.

To increase efficiency of processing, trials on usage of additional processing / separation methods have been applied in recent study. The approach involves three successive steps: (1) laboratory, (2) small-scale, and (3) full-scale separation schemes.

Concerning laboratory separation, several grams of input material were processed by using magnetic separation and gravity separation. This helped in separation of major harmful components (Fe-, Mn-, Ti-rich phases partly with complex mineralogical binding with Nb–Ta, Li-micas, and apatite).

Small-scale separation as a second step attempted to find optimized processing flow-chart usable for separation of some potentially interesting phases (Li-rich and Nb-Ta minerals). Control of the best granulometry presented one of the challenges. By studying various separation techniques, combination of dry magnetic separation and air gravity concentrating table proved to be very effective.

During full-scale separation several tons of input material were processed by magnetic separation followed by air-gravity concentrating table. The chemical composition of separation end-products was tested by XRF. Properties important for ceramic / glass industry (specifically experimental burning and colorimetric measurements) were checked as well. Such an approach allowed for realistic evaluation of the beneficiation flow-chart prior to its implementation on the industrial scale of processing of feldspar raw material.
Comparison between the sea-breeze circulation day and normal day Reynolds stress anisotropy in the lower atmospheric region
Authors: Roy Sayahnya , Sentchev Alexei , Schmitt François G. , Augustin Patrick , Fourmentin Marc
Published: March 2020

This study shows the comparison between the sea-breeze circulation (SBC) day and normal day turbulent characteristics and the Reynolds stress anisotropy in the lower atmospheric region. The Reynolds stress tensor is responsible for the dissipation and transport of mean kinetic energy. The variability of the turbulent kinetic energy due to the Reynolds stress anisotropy modulates the air quality. A 20 Hz Ultrasonic anemometer was deployed in the coastal area of northern France to measure the temporal wind variability for the duration of one year five months.

The SBC was detected by a change in wind direction from the West to the East during the day time. We found that the axial component of the turbulent kinetic energy is higher than the other two through an axisymmetric expansion, and energy ellipsoid has a cigar shape due to SBC. During this time the dominance of small scale zonal turbulent motions was observed. Also, the probability of a higher degree of wind anisotropy due to SBC generates large mean kinetic energy within the lower troposphere. Moreover, the production of larger negative turbulent kinetic energy due to SBC was evident.
The impact of SST on the weather forecast quality in the Bulgarian Antarctic Base area on Livingstone Island
Authors: Chtirkova Boriana , Peneva Elisaveta
Published: March 2020

The weather forecast of good quality is essential for the humans living and operating in the Bulgarian Antarctic Base. The numerical weather prediction models in southern high latitude regions still need improvement as the user community is limited, little test cases are documented and validation data are scarce. Not lastly, the challenge of distributing the output results under poor internet conditions has to be addressed.

The Bulgarian Antarctic Base (BAB) is located on the Livingstone Island coast at 62⁰S and 60⁰W. The influence of the Southern ocean is significant, thus important to be correctly taken into account in the numerical forecast. The modeling system is based on the WRF model, configured in three nested domains down to 1 km horizontal resolution, centered in BAB. The main objective of the study is to quantify the Sea Surface Temperature (SST) impact and to recommend the frequency and way to perform measurements of the SST near the base. The focus is on prediction of right initial time and period of “bad” weather events like storms, frontal zones, and severe winds. Several test cases are considered with available measurements of temperature, pressure and wind speed in BAB during the summer season in 2017. The numerical 3 days forecast is performed and the model skill to capture the basic meteorological events in this period is discussed. Sensitivity experiments to SST values in the nearby marine area are concluded and the SST influence on the model forecast quality is analyzed.
Meeting our future mineral resource needs sustainably – a socio-technical transitions perspective
Authors: Bilham Nic
Published: March 2020

We rely on minerals for almost everything we do in our lives – from metals of all kinds, used in bulk or in tiny quantities in a huge range of technologies, to construction materials and fertilisers.  Sourcing this ever-growing range of raw minerals depends on a global mining industry, which has historically caused great social and environmental harm, and all too often continues to do so (not least because it is so energy- and water-intensive), despite progress towards addressing these impacts.

The circular economy (CE) promises more sustainable alternatives to conventional linear production and consumption models in which raw materials are extracted, used and ultimately discarded as waste.  It seeks to minimise waste and environmental harm throughout the supply chain while optimising resource efficiency, and recognises the need to transform the design of products, services and technologies in order to reduce resource use and maximise recoverability for recycling, remanufacture and reuse.  Nonetheless, however rapidly a CE transition is implemented, society will still require significant quantities of primary mined resources.  For instance, many of the elements required for low-carbon energy technologies have not previously been mined and used in significant quantities, so they are simply not (yet) available to recycle.  A transition to a more sustainable and socially just ‘new minerals economy’ must therefore encompass both the emergent circular economy and the mining sector. 

Although there is an urgent need for the mineral resource consumption and production system to undergo a sustainability transition, and despite its deep entanglement with other such socio-technical systems (energy, but also water, food and transport, for instance), it has yet to be addressed in the transitions literature.  Indeed, there has been very little research from any perspective that has considered CE and mining together, or taken a system-level view including both responsible sourcing (by manufacturers) and responsible supply (by mining companies or through CE routes). 

This presentation outlines my ongoing PhD project to develop a preliminary conceptual framework for a socio-technical transition to a ‘new minerals economy’, and to undertake three case studies of actors across the mineral resources system seeking to take a more responsible and sustainable approach encompassing both mined and CE resources – a manufacturer, a mining company and a material stewardship scheme operator.  The research will take an iterative, abductive approach, to develop the preliminary framework while drawing on relevant concepts from the transitions literature to maximise learning opportunities from the case studies. 
Periodicity disruption of a model quasi-biennial oscillation of equatorial winds
Authors: Renaud Antoine , Nadeau Louis-Philippe , Venaille Antoine
Published: March 2020

In the Earth's atmosphere, fast propagating equatorial waves generate slow reversals of the large scale stratospheric winds with a  period of about 28 months. This quasi-biennial oscillation is a spectacular manifestation of wave-mean flow interactions in stratified fluids, with analogues in other planetary atmospheres and laboratory experiments. Recent observations of a disruption of this periodic behavior have been attributed to external perturbations, but the mechanism explaining the disrupted response has remained elusive. We show the existence of secondary bifurcations and a quasiperiodic route to chaos in simplified models of the equatorial atmosphere ranging from the classical Holton-Lindzen-Plumb model to fully nonlinear simulations of stratified fluids. Perturbations of the slow oscillations are widely amplified in the proximity of the secondary bifurcation point. This suggests that intrinsic dynamics may be equally influential as external variability in explaining disruptions of regular wind reversals  [1].

[1] Renaud, A., Nadeau, L. P., & Venaille, A. (2019). Periodicity Disruption of a Model Quasibiennial Oscillation of Equatorial Winds. Physical Review Letters, 122(21), 214504.
 
The stratospheric ozone rich cold intrusion during El-Nino over the Indian region: implication during the Indian summer monsoon
Authors: Roy Chaitri , Fadnavis Suvarna , Thazhe Purayil Sabin
Published: March 2020

Ozone in the upper troposphere is a dominant radiative constituent.  In this study, we investigate ozone variability due to stratospheric intrusions in the upper troposphere over India, and its associated radiative impacts during monsoon breaks co-occurring with El Niño. For this purpose, we use the ECHAM5-HAMMOZ, Global-Chemistry-climate model simulations, and ERA-Interim reanalysis data. Our analysis shows that during El Niño deep stratospheric intrusions, occurring at the North India - Tibetan Plateau (NI-TP) region and the western edge of the monsoon anticyclone, lead to an enormous increase in ozone amounts (~160 ppb) in the upper troposphere over India. These intrusions elevate the surface ozone levels by ~20 ppb and ozone radiative forcing by ~0.33 W m-2 at the top of the atmosphere (TOA). 

Interestingly, the stratospheric intrusions are associated with a wave train composed of cyclonic and anticyclonic circulation in the upper troposphere, emanating from El-Niño region in the east Pacific, traversing towards NI-TP locale. The wave train transports extra-tropical cold air mass, producing an anomalous cooling of ~2 - 3 K in the upper troposphere over NI-TP. The cold wave train induces Rossby wave breaking (RWB), which facilitates stratospheric intrusions, thereby enhancing subsidence over NI-TP region. Additionally, this severe cold subsidence over North India during break days may further intensify the deficit rainfall condition during break days.
Assessment of the empirical matched field processing algorithm for autonomous tracking of aftershock sequences
Authors: Köhler Andreas , Kværna Tormod , Gibbons Steven J.
Published: March 2020

Autonomous algorithms can improve the processing of aftershock sequences, for example by reducing the analyst workload. We present a system for automatic detection and location of aftershocks in a specific region following a large earthquake. The system seeks to identify all signals generated by seismic events in the target region, while passing over signals generated by sources in all other regions. For a given station, we can generate a sensitive empirical matched field (EMF) detector for the target region using only an empirical template from the mainshock signal. These EMF detectors perform much better on seismic arrays than on 3-component stations. For each selected station in the network, a multivariate detector combines the EMF detector with an optimized continuous AR-AIC detector to generate a target-optimized detection list. For arrays, an additional continuous calibrated f-k process reliably screens out likely signals from other sources. A region-specific phase association algorithm takes the screened detection lists from each station and generates a preliminary aftershock bulletin. We have processed aftershock sequences from four major earthquakes: the Tohoku event in 2011 (Japan), the Illapel event in 2015 (Chile), the Papua New Guinea event in 2018 and the Gorkha event in 2015 (Nepal).

We evaluate the results in detail by comparing the automatically generated origins and corresponding phase arrival times with matching events and associated arrivals in the analyst reviewed (REB) and automatic (SEL3) bulletins issued by the CTBTO Preparatory Commission. Between 40% and 65% of all events in the REB are found to closely match the locations and origin times of the events found by our EMF-based procedure. The resulting discrepancies are assessed with respect to signal-to-noise ratio, number of defining stations, and epicentral distance. Furthermore, the REB events not detected by the EMF method are analyzed and a few phase misidentifications (i.e., P vs. pP) are assessed to better understand the limitations of the autonomous procedure. In general, we find that our EMF solutions are closer to the matching REB events than the corresponding SEL3 events. The analyst is helped both by the improved location estimates and a lower number of qualitatively incorrect event hypotheses. A key factor in the performance is the number of contributing seismic arrays. Aftershock sequences in the southern hemisphere performed the worst given the poorer array coverage.
How does pretreatment of dry steppe soils affect particle size analysis by laser diffraction?
Authors: Koza Moritz , Prays Aleksey , Bondarovich Andrej , Akshalov Kanat , Conrad Christopher , Schmidt Gerd
Published: March 2020

After extensive research on different methods to measure particle size distribution (PSD), soil scientists are proposing the laser diffraction method (LDM) as a standard method for soil texture analysis. However, the effects of different pretreatments on particle size analysis of dry steppe soils with LDM has not been tested so far. This study aims to evaluate different pretreatment methods with the purpose to disperse aggregates and remove binding agents in Chernozem and Kastanozem soils. To cover a wide range of different land-use types and farming methods, 112 surface soil samples were taken from 13 fields on four different test sites in Kazakhstan. Before LDM analysis, all samples were pretreated with either H2O2 to remove organic carbon or HCl to remove carbonates. The results showed that removing organic matter with H2O2 led to complete sample dispersion while HCl pretreatment caused incomplete dispersion, likely due to aggregation by calcium ions released by the dissolution of carbonates.
Next-generation community ecology: Exploring ecological and evolutionary drivers of planktonic foraminifera diversity using the Endless Forams database and a supervised machine learning classifier
Authors: Hsiang Allison , Hull Pincelli
Published: March 2020

The rich fossil record of planktonic foraminifera makes them an indispensable group for understanding interactions between climatic, oceanic, and biological dynamics through time and space. Over the past few years, we have been working to provide databases and informatics resources to standardize and speed up the generation of large datasets for community-scale analyses of planktonic foraminifera. Our public database Endless Forams Most Beautiful (www.endlessforams.org), which currently contains >34,000 unique images of individual planktonic foraminifera comprising 35 species, is an important new resource for taxonomic training and standardization, supervised machine learning, and large-scale analyses of community ecology and morphological evolution. Here, we present one such application using both the individuals in the Endless Forams database and an additional ~26,000 specimens from across the North Atlantic, identified using a supervised machine learning classifier trained using the Endless Foram data. We combine taxonomic information from these ~60,000 individuals with morphometric measurements extracted using our open source software AutoMorph to explore ecological and evolutionary drivers of modern planktonic foraminifera diversity and size.
New approaches to radiocarbon calibration arising from statistical developments in IntCal20
Authors: Bronk Ramsey Christopher , Heaton Timothy , Blaauw Maarten , Blackwell Paul , Reimer Paula , Scott Marian
Published: March 2020

Calibration is a key element of the radiocarbon dating methodology and the underlying Bayesian statistical approach taken, and algorithms used, are well established and used in calibration software and associated analysis packages.  These calibration methods are based on a calibration curve which provides a mean estimate for the radiocarbon isotope ratio (fractionation corrected) expected in samples, and the associated standard uncertainty, both as a function of time (or calendar age).  The measured samples also have their radiocarbon isotope ratio reported in the same form and so the calibration process involves comparison of the sample radiocarbon measurements with the calibration curve at different points on the calendar age scale.  This then yields a probability distribution function, with associated highest probability density ranges, for the sample calendar age.  We discuss here how improvements in the construction of the IntCal20 curve offer new opportunities, enabling users to obtain more from the calibration curve than previously possible and address some of the limitations of previous calibration approaches.

Previous approaches to calibration assumed that the values of the calibration curves at any time were normally distributed around their estimated mean. However, there are time periods where the distribution of these curves are not well represented by such a normal distribution. This is potentially significant even for calibrations of single samples. The new IntCal20 curve generates multiple possible calibration curves, providing us with the opportunity to identify and adapt to such non-normality.  A second limitation of previous approaches to calibration arises when multiple determinations are used within a broader chronological model. In such cases the usual assumption is that the calibrated uncertainties are independent.  This is certainly not the case if all the samples are the same age (which is currently addressed by combination before calibration) but also is potentially wrong if the samples are close enough in age for there to be correlated uncertainty in the calibration curve.  Again, using the collection of possible curves provided in the construction of IntCal20, rather than just the summary curve, we look at possible solutions to this challenge.  The implications for high-precision chronologies are also discussed.
A fast surrogate model to simulate flooding due to heavy rainfall events
Authors: Cioffi Francesco , Tieghi Lorenzo , pirozzoli Sergio , giannini mario , scotti vincenzo
Published: March 2020

Recent disasters stress the demand of fast and reliable tools for flooding forecasting, where the real-time prediction of extreme events becomes essential to avoid potential hazards for the population. In this work, we focus on the flash flooding phenomenon, given by the combination of temporally concentrated rainfall and steep slopes. Such configuration is typical in the St. Lucia island, in the eastern Caribbean Sea, that we exploit as a case study. It is possible to simulate the full evolution of rainfall by numerically solving the Shallow Waters equations (SW) on a computational domain. A preliminary comparison with historical events proved that an accurate solution is achieved only when the Digital Elevation Model (DEM) presents a resolution equal or inferior to 5 meters. With this grid resolution the whole island is discretized in over 60M cells at best, forbidding a real-time application of the SW solvers in flash flooding events.

 In this work we present a machine-learning surrogate model for a SW solver to estimate the level of the flooding danger. It is evaluated through a synthetic parameter, hereafter referred as flag, that takes in account both the water depth and its velocity. Therefore, flooding patterns in the island are represented through high-resolution maps with discrete values of flags, varying from 0 – safe to 4 – extremely dangerous.

The final aim is to solve a supervised regression, training a Multi-Layer Perceptron Neural Network (MLPNN) to map sequences of time- and spatial-varying rainfall (input features) to the corresponding previsions of flags (output features) shifted ahead of time. To do so, we first generate a rough database by simulating more than 30 flash flooding events, using an in-house validated code, whose input is the temporal and spatial rainfall distribution obtained by radar measurements of events occurred in the past. DEM resolution is set to 5 meters and SW solver solutions is sampled every 6 mins. Given the high dimensionality of the problem, both the inputs and the outputs of the simulations are preprocessed using an Incremental Principal Component Analysis (IPCA) to extract the scores and loadings. The elbow charts indicate the correct number of principal components, set to 8, that explains the 95% of the cumulative explained variance. The scores given by IPCA processing of rainfall are built into sequences of five elements, endowing the algorithm a memory. The min/max regularization are applied to the database. The MLPNN training phase is fastened through batch feeding and monitored to prevent overfitting, relying on Tensorflow library. To test the generalization capability of the synthetic model was verified by forwarding events that were not included in the original database.
Solar wind re-acceleration in local current sheets and their diagnostics from observations
Authors: Xia Qian , Zharkova Valentina
Published: March 2020

We explore solar wind re-acceleration during their passage through reconnecting current sheets in the interplanetary space using the particle-in-cell approach. We investigate particle acceleration in 3D Harris-type reconnecting current sheets with a single or multiple X-nullpoints taking into account the ambient plasma feedback to the presence of accelerated particles. We also consider coalescent and squashed magnetic islands formed in the current sheets with different magnetic field topologies, thickness, ambient density, and mass ratios. With the PIC approach, we detected distinct populations of two groups of particles, transit and bounced ones, which have very different energy and asymmetric pitch-angle distributions associated with the magnetic field parameters. We present a few cross-sections of the simulated pitch-angle distributions of accelerated particles and compare them with the in-situ observations of solar wind particles. This comparison indicates that locally generated superthermal electrons can account for the counter-streaming ‘strahls’ often observed in pitch-angle distribution spectrograms of the satellites crossing heliospheric current sheets.
Mechanistic modelling of the influence of temperature on the wood anatomy of Scots pine
Authors: Friend Andrew
Published: March 2020

Despite its importance for the study of past climates, as well as its significance for carbon sequestration, we lack a mechanistic explanation for how temperature controls wood anatomy. A model of xylogenesis is presented and used to analyse observed tree ring anatomy-temperature relationships in Scots pine (Pinus sylvestris). The model treats the daily proliferation of new cells in the cambium and their subequent differentiation through expansion and secondary wall thickening phases. Control on size at division in the cambium follows recent work on the Arabidopsis shoot apical meristem, and cell enlargement rates in the cambium and enlargement zone are controlled by temperature. The duration of post-cambial enlargement is partially controlled by the rate at which cells pass through the enlargement zone, and partially by the size of this zone, which is controlled by daylength. This set of assumptions is sufficient to generate observed profiles of cell sizes across radial files, with characteristic transitions from earlywood to latewood. After they leave the enlarging zone, cells enter the wall thickening zone, the width of which is also dependent on daylength. A temperature-dependent rate of wall material deposition is insufficient to reproduce the observed gradient in mass density across the radial file, and fails to fully capture the observed seasonality of the correlation between maximum latewood density and temperature. Inclusion of a control on the rate of wall deposition from substrate (sugar) supply, diffusing from the phloem across the radial file, corrects these deficiencies. The resulting model provides a mechanistic explanation of temperature-tree ring relationships, and has the potential to underpin understanding of how climate and CO2 interact in determining the amount of carbon sequestered in trees.
Implications of intrinsic variability for economic assessments of climate change
Authors: Stainforth David , Calel Raphael , Chapman Sandra , Watkins Nicholas
Published: March 2020

Integrated Assessment Models (IAMs) are widely used to evaluate the economic costs of climate change, the social cost of carbon and the value of mitigation policies. These IAMs include simple energy balance models (EBMs) to represent the physical climate system and to calculate the timeseries of global mean temperature in response to changing radiative forcing[1]. The EBMs are deterministic in nature which leads to smoothly varying GMT trajectories so for simple monotonically increasing forcing scenarios (e.g. representative concentration pathways (RCPs) 8.5, 6.0 and 4.5) the GMT trajectories are also monotonically increasing. By contrast real world, and global-climate-model-derived, timeseries show substantial inter-annual and inter-decadal variability. Here we present an analysis of the implications of this intrinsic variability for the economic consequences of climate change.

We use a simple stochastic EBM to generate large ensembles of GMT trajectories under each of the RCP forcing scenarios. The damages implied by each trajectory are calculated using the Weitzman damage function. This provides a conditional estimate of the unavoidable uncertainty in implied damages. It turns out to be large and positively skewed due to the shape of the damage function. Under RCP2.6 we calculate a 5-95% range of -30% to +52% of the deterministic value; -13% to +16% under RCP 8.5. The risk premia associated with such unavoidable uncertainty are also significant. Under our economic assumptions a social planner would be willing to pay 32 trillion dollars to avoid just the intrinsic uncertainty in RCP8.5. This figure rises further when allowance is made for epistemic uncertainty in relation to climate sensitivity. We conclude that appropriate representation of stochastic variability in the climate system is important to include in future economic assessments of climate change.

[1] Calel, R. and Stainforth D.A., “On the Physics of Three Integrated Assessment Models”, Bulletin of the American Meteorological Society, 2017.

 
A New Approach to Quantify the Transport of Extreme Aerosol Events in Southeast Asia by Combining WRF-CHEM with Various Models and Remotely Sensed Measurements
Authors: Wang Shuo , Cohen Jason Blake
Published: March 2020

Southeast Asia has a far-reaching influence on the atmospheric distribution of aerosols and co-emitted trace gasses due to the high amount of emissions, the large contribution from co-emitted heat (i.e. biomass burning and urbanization), the highly variable topography, and intense and variable meteorology. We aim to quantify the pathways and constrain the impact of long-range transport on the measured increase in aerosol loading and variability. When the dry season comes in January through April, a large number of aerosols are discharged into the atmosphere from Myanmar, Thailand, Cambodia and Vietnam, which in theory, should transport them to the East under the influence of the Indian monsoon. What we observe is that first, this eastward transport is much larger in area than expected, with measurements clearly showing aerosols and long-lived trace gasses passing Taiwan and winding up in the Central Pacific, or passing around Taiwan and winding up in Northeastern China, Korea, and Japan. Secondly, we observe a significant although smaller transport of aerosols far to the south, breaching the equator, even though the climatology at this time of year indicates a Monsoon belt from 7oN southward.

We first employ a new emissions spatial-temporal distribution, forced by remotely sensed measurements of trace gasses, and second we consider meteorology associated with both fire plumes and mountain slopes. The combination of these forcings we argue is essential to reconstruct the observations. We second use observations from dozens of AERONET sites located in Southeast Asia from 2010 to 2018, to obtain the distribution of extreme events of AOD and AAOD. In addition, we combine precipitation from TRMM. These are used in tandem to establish the structural observational relationship between emissions, rainfall, transport, and diffusion.

We run these new emissions in the WRF-CHEM framework and observe a strong improvement in comparison with the measured means and variability of aerosols from MODIS and MISR, gasses from MOPITT. Furthermore, we observe a change in the vertical distribution and location of the large-scale meteorology itself, indicating that there is a possible important two-way feedback at work. We specifically note that there are significant changes induced in the high rainfall days, and in the loadings of aerosols and wind in the region from 800 to 950 hPa, with different sized particles segregated into different height levels.
Greenhouse gas emissions of European croplands
Authors: Kuhnert Matthias , Martin Michael , Leip Adrian , McGrath Matthew , Smith Pete
Published: March 2020

Agriculture is a significant source of greenhouse gas (GHG) emissions in Europe. Croplands contribute to this source, but these contributions are difficult to estimate, as the influencing factors are complex. Human management actions are even more important than environmental drivers for agricultural emissions, but spatially-explicit datasets are scarce. This causes a high uncertainty for GHG emission simulations. We simulated GHG emissions (2010-2015) for selected crops (wheat and maize) in Europe with the biogeochemical model platform SPATIAL ECOSSE, using spatially-explicit management data from the model CAPRI used by JRC and model approaches based on Waha et al. (2012) to derive spatial management data (grid maps) for EU27. First results reveal that emissions estimates are highly sensitive to soil organic carbon (SOC), which results in hotspots of GHG emissions in northern Europe where SOC content is high. This effect is stronger for wheat than for maize. The first results show changes in SOC ranging from 374 --456 g C m2 yr-1 and 317 to 399 C m2 yr-1 across Europe (EU27) for wheat and maize, respectively, which are larger than the values reported in previous studies (e.g., 299 g C m2 yr-1 by Ciais et al., 2010).

Ciais, P., Wattenbach, M., Vuichard, N., Smith, P., Piao, S.L., Don, A., Luyssaert, S.,Janssens, I., Bondeau, A., Dechow, R., Leip, A., Smith, P., Beer, C., van der Werf,G.R., Gervois, S., Van Oost, K., Tomelleri, E., Freibauer, A., Schulze, E.D., 2010. The European greenhouse gas balance. Part 2: croplands. Global Change Biology 16,1409–1428.

Waha, K., van Bussel, L. G. J., Müller, C., & Bondeau, A. (2012). Climate-driven simulation of global crop sowing dates. Global Ecology and Biogeography, 21(2), 247–259. https://doi.org/10.1111/j.1466-8238.2011.00678.x
Current structures and reconnection events analysis in hybrid-kinetic turbulence simulations using unsupervised machine learning
Authors: Sisti Manuela , Califano Francesco , Faganello Matteo , Pedrazzi Giorgio , Delli Ponti Francesca , Hu Andong , Teunissen Jannis
Published: March 2020

Kinetic turbulence in magnetized space plasmas has been extensively studied via in situ observations, numerical simulations and theoretical models. In this context, a key point concerns the formation of coherent current structures and their disruption through magnetic reconnection. As of today, reconnection can only be accurately identified by human analysis. We are setting-up a machine learning unsupervised technique aimed at automatically detecting the presence of current sheet (CS) magnetic structures where reconnection is occurring. We make use of anomaly detection and clustering techniques. We are applying these techniques to 2D kinetic HVM (Hybrid Vlasov Maxwell) plasma turbulence simulations, where ions evolve by solving the Vlasov equation and the electrons are treated as a fluid. Electron inertia is included. The final goal is to build up an algorithm able to select data subsets starting from big data sets where potentially interesting physical processes are at play. After that, we intend to extend the technique to space data and to 3D simulation data.

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776262 (AIDA, www.aida-space.eu).
Displacement prediction of Shengjibao landslide based on an ensemble model in Three Gorges Reservoir Area, China
Authors: Jiang HongWei , Yin Kunlong , Glade Thomas
Published: March 2020

The Three Gorges Reservoir area (TGRA) is one of the most landslide-prone areas in China. Landslide prediction is important for the mitigating of geohazards and it is also an essential component for developing landslide early warning systems. In the TGRA, the preparatory, triggering and controlling factors of landslides are very diverse. The local geological conditions and variations in the controlling factors result in pulsed movements of landslides, the so-called “step-like” deformation of landslides. Most of the existing predictive models are based on a single algorithm including static models and dynamic models. This study proposes an Ensemble model combined with a static model and a dynamic model which combined the advantages of the two models for landslide displacement prediction.

Based on displacement monitoring data of the Shengjibao landslide in the Three Gorges Reservoir area(TGRA), which is not a typical “step-like” landslide but with the “step-like” characteristic in its displacement-monitoring curve, long short-term memory neural networks (LSTM) model, support vector regression (SVR) model and an Ensemble model based on LSTM model and SVR model were proposed to predict its displacement. Moving average methods (MAM), were used to decompose the cumulative displacement into two parts: trend and periodic terms. The single-factor LSTM model and the single factor SVR model were proposed to predict the trend terms of displacement. Multi-factors LSTM model and multi-factors SVR model were proposed to predict the periodic terms of displacement. Precipitation, reservoir water level, and previous displacement are considered as the candidate factors for the multi-factors LSTM model and the multi-factors SVR model predictions. Meanwhile, an Ensemble model combined with the LSTM model and the SVR model was also proposed to predict the decompositions of displacement.

The results show that the LSTM model and the SVR model display good performance, the Ensemble model outperforms the other models, and the prediction accuracy can be improved by considering advantages from different models.
Microaggregation of goethite and illite: Linking mechanistic modeling and laboratory experiments
Authors: Prechtel Alexander , Zech Simon , Dultz Stefan , Guggenberger Georg , Ray Nadja
Published: March 2020

Microaggregates are the fundamental building blocks of soils and thus important for their structure, properties, and functions. Hence, experimental aggregate formation studies (Dultz et al. 2019) were conducted to reveal the mechanisms leading to the establishment of soil microaggregates from mixtures of the mineral building units goethite and illite. Mathematically based modeling can further illuminate the mechanisms and factors behind structure formation as well as facilitate this understanding, even if the experimental capability is limited.

To this end, we present and extend a mechanistic modeling approach (Rupp et al. 2018, Rupp et al. 2019) which is based on a cellular automaton method that resolves explicitely particles at the micrometer scale. Thus it is capable to represent structural changes originating from (electrostatic) interaction of building units (aggregate forming materials). As prototypic building units goethite and illite with needle like and platy shapes of different size and charge are implemented. The operational, comprehensive model allows studying structure formation as a function of composition and charge of such mineral mixtures. Along this line, homoaggregation as well as heteroaggregation scenarios are investigated. The resulting microaggregates are investigated with respect to size, structure, and stability. Moreover, the role of the aspect ratio for stability, the point of zero charge for aggregation, and the amount of excess particles with respect to time is illustrated. Finally, the results are evaluated and compared to experimental data given in Dultz et al. (2019), and extend the scenarios studied there

S. Dultz, S.K. Woche, R. Mikutta, M. Schrapel, G. Guggenberger (2019): Size and charge constraints in microaggregation: Model experiments with mineral particle size fractions. Applied Clay Science 170, 29-40.

A. Rupp and K. Totsche and A. Prechtel and N. Ray (2018): Discrete-continuum multiphase model for structure formation in soils including electrostatic effects. Frontiers in Environmental Science, 6, 96.

A. Rupp, T. Guhra, A. Meier, A. Prechtel, T. Ritschel, N. Ray, K.U. Totsche (2019): Application of a cellular automaton method to model the structure formation in soils under saturated conditions: A mechanistic approach. Frontiers in Environmental Science 7, 170.