bluuebunny/crossref_metadata_2025 huggingface dataset:
Constraints on the latitudinal structure of the deep zonal flows of Jupiter and Saturn
Authors: Kaspi Yohai , Galanti Eli ,   Juno Science Team
Published: March 2021

The atmospheres of the gas giants are dominated by strong alternating east-west zonal flows at the cloud-level. Jupiter’s flows have a significant asymmetry between the northern and southern hemispheres, while on Saturn the wind pattern is more symmetric with a wide eastward flow at the equatorial region, and smaller scale jets extending to high latitudes. How deep these winds penetrate into the planets' interior and what is their latitudinal structure has remained a fundamental open question until recently, when both Juno at Jupiter and Cassini at Saturn enabled addressing these questions, through accurate gravity measurements performed by both spacecraft.

For Jupiter, the zonal winds at the cloud level have been shown to be closely linked to the asymmetric part of the planet's measured gravity field, implying that the flow extend ~3000  km deep. However, measurements coming from several sources (e.g., Juno microwave radiometer measurements) suggest that in some latitudinal regions the flow below the clouds might be somewhat different from that observed there. Here we use the measured gravity field, both asymmetric and symmetric, to examine which latitudinal range of the observed cloud-level winds is most likely to extend deep below the clouds. We find that the winds between latitude 25S and 25N dominate the wind-induced gravity field, with contribution also coming from the winds at latitudes 25 to 50 north and south. These findings are also consistent with magnetohydrodynamics constraints. We also find, that in order to match the gravity data, the winds must be projected inward in the direction parallel to Jupiter's spin axis, and that the decay of the winds should occur in the radial direction. The Saturn case is less constrained, as the gravity signal is more symmetric and the symmetric part of the gravity field is strongly affected by the internal structure of the planet. Nonetheless, the gravity field implies that the cloud-level winds extend ~9000  km deep and westward flows, which differ somewhat from those at the cloud-level, must exist poleward of the equatorial superrotating region.
Uncertainty in debris flow rainfall thresholds
Authors: Berti Matteo , Simoni Alessandro
Published: March 2021

Rainfall is the most significant factor for debris flows triggering. Water is needed to saturate the soil, initiate the sediment motion (regardless of the mobilization mechanism) and transform the solid debris into a fluid mass that can move rapidly downslope. This water is commonly provided by rainfall or rainfall and snowmelt. Consequently, most warning systems rely on the use of rainfall thresholds to predict debris flow occurrence. Debris flows thresholds are usually empirically-derived from the rainfall records that caused past debris flows in a certain area, using a combination of selected precipitation measurements (such as event rainfall P, duration D, or average intensity I) that describe critical rainfall conditions. Recent years have also seen a growing interest in the use of coupled hydrological and slope stability models to derive physically-based thresholds for shallow landslide initiation.

In both cases, rainfall thresholds are affected by significant uncertainty. Sources of uncertainty include: measurement errors; spatial variability of the rainfall field; incomplete or uncertain debris flow inventory; subjective definition of the “rainfall event”; use of subjective criteria to define the critical conditions; uncertainty in model parameters (for physically-based approaches). Rainfall measurement is widely recognized as a main source of uncertainty due to the extreme time-space variability that characterize intense rainfall events in mountain areas. However, significant errors can also arise by inaccurate information reported in landslide inventories on the timing of debris flows, or by the criterion used to define triggering intensities.

This study analyzes the common sources of uncertainty associated to rainfall thresholds for debris flow occurrence and discusses different methods to quantify them. First, we give an overview of the various approaches used in the literature to measure the uncertainty caused by random errors or procedural defects. These approaches are then applied to debris flows using real data collected in the Dolomites (Northen Alps, Itay), in order to estimate the variabilty of each single factor (precipitation, triggering timing, triggering intensity..). Individual uncertainties are then combined to obtain the overall uncertain of the rainfall threshold, which can be calculated using the classical method of “summation in quadrature” or a more effective approach based on Monte Carlo simulations. The uncertainty budget allows to identify the biggest contributors to the final variability and it is also useful to understand if this variability can be reduced to make our thresholds more precise.

 
The Miocene warmth from the North Sea Basin perspective
Authors: Sliwinska Kasia K. , Bojesen-Koefoed Jørgen , Dybkjær Karen , Herbert Timothy , Lear Caroline H. , Rasmussen Erik Skovbjerg , Soltau Emil Munck , Thibault Nicolas Rudolph , Vickers Madeleine L.
Published: March 2021

The Miocene climate was dynamic, oscillating between major glaciation events and greenhouse conditions (the so-called Miocene Climatic Optimum or MCO). However, forcing factors responsible for climatic transitions from one state to another are not fully understood, partly because palaeoclimatological records from northern mid to high latitudes are scarce.

To better resolve climatic changes of the Miocene epoch in the northern middle latitudes we studied a unique, nearly complete sedimentary record (Sdr. Vium borehole) spanning the upper Aquitanian to the Tortonian of the North Sea Basin. Newly obtained sea surface temperatures (SSTs) from our Miocene core revealed that the North Sea Basin was up to 20°C warmer than today, reaching the temperature maximum during the worldwide MCO (Herbert et al. 2020). Our high-resolution δ13C, TOC and C/N records, as well as elemental detrital ratios (Si/Al, Zr/Rb, Zr/Al) derived from XRF reveal important changes in the source of organic matter and detrital coarse fraction of the sediment. During the Miocene the location of the Sdr. Vium borehole was situated in a proximal setting, with water depths varying between 0 and ~200 m, partly due to advancing and retreating delta lobes and partly due to relative sea level changes. We observe that the depositional environment had a large impact on our record. By far the most important of these changes is a condensed interval associated with phosphatization, pyritization, and glauconite, associated with a major shift from a dark brown, organic-rich, bioturbated silty clay with thin sand lenses (the Hodde Formation) towards a green and brown clay with high concentrations of green glaucony pellets of fine sand grade (the Ørnhøj Formation). This shift is related to the subsidence of the North Sea Basin and marks the onset of a sediment-starvation in the basin.
The Comet Interceptor Mission
Authors: Jones Geraint H. , Snodgrass Colin , Tubiana Cecilia ,   The Comet Interceptor Team
Published: March 2021

Comet Interceptor was selected in 2019 as the European Space Agency's next planetary mission, to which the Japanese space agency, JAXA, will make a major contribution. The mission is ESA's first Fast (F) project, and its primary science goal is to characterise, for the first time, a long period comet, preferably dynamically-new, or an interstellar object. An encounter with one of these objects for the first time will provide valuable data to complement that from all previous comet missions, which have by necessity studied short-period comets that have evolved during their time orbiting near the Sun from their original condition. Planned measurements of the target include its surface composition, shape, and structure, its dust environment, and the composition of the gas coma. A unique, multi-point ‘snapshot’ measurement of the comet- solar wind interaction region is to be obtained, complementing single spacecraft observations made at other comets. The spacecraft will be delivered to Sun-Earth Lagrange Point L2 with the ESA Ariel mission in 2029, a relatively stable location suitable for later injection onto an interplanetary trajectory to intersect the path of its target. A suitable new comet would be searched for from Earth prior to launch, and after launch if necessary, with short period comets serving as a backup destinations. With the advent of powerful facilities such as the Vera Rubin Observatory, the prospects of finding a suitable comet nearing the Sun are very promising. The possibility may exist for the spacecraft to encounter an interstellar object if one is found on a suitable trajectory. When approaching the target, two sub-spacecraft – one provided by ESA, the other by JAXA, would be released from the primary craft. The main spacecraft, which would act as the primary communication point for the whole constellation, would be targeted to pass outside the hazardous inner coma, making remote and in situ observations on the sunward side of the comet. The two sub-spacecraft will be targeted closer to the nucleus and inner coma region. We shall describe the science drivers, planned observations, and the mission’s instrument complement, to be provided by consortia of institutions in Europe and Japan.
Identifying distributions of response times in karst aquifers
Authors: Boano Fulvio , Viglione Alberto , Vigna Bartolomeo
Published: March 2021

In karst catchments, aquifer recharge occurs through a composite mosaic of subsurface flow paths. Precipitation infiltrates in the subsurface and flows along a complex network of fractures – that are characterized by different sizes and degrees of saturation –  before eventually reaching the catchment outlet. The discharge of a karst spring is the result of the contributions of these flow paths, that may differ widely in terms of lengths, velocities, and travel times. Monitoring the spring discharge can thus provide information about flow within the aquifer. In particular, the spring discharge signal can be interpreted as the lagged response of the aquifer to precipitation inputs over the catchment, with the aquifer being characterized by a distribution of response times that relates input (precipitation) to output (discharge). Identifying these response times is not a trivial task as the input-output problem is often mathematically ill-posed, which leads to amplification of the errors and may prevent finding a physically meaningful solution.

In this work we propose a method to evaluate the distribution of response times of a karst aquifer. The method, that was originally developed to deal with ill-posed problems in geostatistical applications, relies on a probabilistic description of precipitation inputs and discharge outputs, and it provides an estimate of the response time distribution and of its uncertainty. The method is here tested through the application to two datasets collected in two cave systems in Northern Italy (the Bossea system and the Vene/Fuse system) with different hydrogeological properties. The results demonstrate that the method successfully identifies different response time distributions that reflect the differences in aquifer characteristics of the two systems. Furthermore, differences among response time distributions relative to different precipitation events in each system provide valuable insights on seasonal variations in aquifer recharge and fracture saturation. The method can hence be applied as a tool for the indirect investigation of karst systems.
Using machine learning to model the distribution of Vegetation Types across Norway
Authors: Keetz Lasse Torben , Bryn Anders , Horvath Peter , Skarpaas Olav , Tallaksen Lena Merete , Žliobaitė Indrė
Published: March 2021

Machine learning (ML) provides a powerful set of tools that can improve the accuracy of distribution models by automatically representing underlying ecological relationships empirically captured from large sets of data. However, more recent methodological advances in ML that have been less frequently applied, e.g. in the field of deep learning, may yield additional potential for Distribution Modeling. In this project, we use two ML algorithms, Random Forest (RF) and multi-layer feed-forward artificial neural networks (ANN), to predict the occurrences of Vegetation Types (VT) across Norway. Accurate predictions may support environmental management or the validation of earth system models. The VT data (derived from the AR18x18 data set; n=31 classes) covers the entire spatial scope in 0.9 ha plots on a systematically sampled 18 km grid (n = 1,081 plots, n = 22,154 observations). It was obtained through a field-based survey by a group of trained experts between 2004 and 2014. We use the cloud-based platform "Google Earth Engine" to generate a set of remotely sensed predictor variables based on SENTINEL-2 satellite imagery (i.e. surface reflectance from 12 spectral bands and six vegetation indices). These are then combined with ancillary environmental rasters used previously to model Norwegian VT distribution, e.g. representing climate, land cover, or geological properties (n=55, before one-hot encoding). Preliminary results suggest that in both modeling approaches, the generated SENTINEL-2 variables, particularly the Normalized Difference Vegetation Index (NDVI), have the highest predictive power as measured by permutation importance. The mean overall accuracy using 5-fold cross-validation shows only minor differences between the two methods (approx. 0.45 for ANN vs. 0.44 for RF; the respective F1-scores are 0.35 for ANN and 0.34 for RF; most frequent class baseline accuracy = 0.136). The modeling challenges we currently face include a class imbalance in the VT data set, reconciling the different spatial resolutions of the environmental predictors, and discrepancies in the timing of data acquisition. The next steps in the project will be to incorporate spatial cross-validation into the workflow and to analyze the differences between the ML methods in detail (e.g. regarding the ability to model rare VTs or differences in variable importance). Moreover, we will evaluate the possibility to include additional satellite data sources. This work is a contribution to the Strategic Research Initiative ‘Land Atmosphere Interaction in Cold Environments’ (LATICE) of the University of Oslo.
Estimation of photovoltaic energy generated in urban environments, case: Medellín Metropolitan Area (MMA) (Colombia)
Authors: Correa Sánchez Nathalia , Mesa Sánchez Oscar José , Hoyos Ortíz Carlos David
Published: March 2021

This work considers photovoltaic solar energy as an alternative to promote the diversification of the energy matrix and contribute to improving access to the citizens of Medellín (MMA) Metropolitan Area,  Colombia. The objective is a more sustainable and resilient energy use.  To achieve this, we assess how much of the energy demand can be generated within the city, integrated into the urban morphology at the roofs of existing buildings. We use meteorological information and power measurements from three experimental solar panels. We analyze the photovoltaic energy potential in these Representative Urban Areas (RUA) and provide information relevant to the whole Valley's context to guide sustainable and resilient energy planning.  One particular result is about the energy reduction factor due to cloudiness, which quantifies how energy would vary under the region's cloud conditions.
Minimal setup for neutron background measurements - summary of the BSUIN project
Authors: Jedrzejczak Karol , Szabelski jacek , Kasztelan Marcin , Przybylak Marika , Tokarski Przemysław , Orzechowski Jerzy , Marszał Włodzimierz
Published: March 2021

The BSUIN project conducted pilot measurements to test methods for characterizing underground laboratories for natural background radioactivity (NRB). One of the components of NRB that requires specific measurement methods is the neutron background.
The goal of our team was to developing a reference setup for neutron background measurements.

Our idea was to build a setup for measuring neutrons as simple as possible, but not simpler. The price and
universality of the measurement setup are important parameters, but the reliability of the result is also very
important. It is because the neutron flux in underground laboratories is usually very low and it is easy to
make a mistake in interpreting of the results.

The basics of our method will be presented, as well as the assessment of possible measurement errors and the transactional experience gained during measurements at six different locations in four mines.
How prediction statistics can help us cope when we are shaken, scared and irrational
Authors: Kamer Yavor , Nandan Shyam , Hiemer Stefan , Ouillon Guy , Sornette Didier
Published: March 2021

Nature is scary. You can be sitting at your home and next thing you know you are trapped under the ruble of your own house or sucked into a sinkhole. For millions of years we have been the figurines of this precarious scene and we have found our own ways of dealing with the anxiety. It is natural that we create and consume prophecies, conspiracies and false predictions. Information technologies amplify not only our rational but also irrational deeds. Social media algorithms, tuned to maximize attention, make sure that misinformation spreads much faster than its counterpart.

What can we do to minimize the adverse effects of misinformation, especially in the case of earthquakes? One option could be to designate one authoritative institute, set up a big surveillance network and cancel or ban every source of misinformation before it spreads. This might have worked a few centuries ago but not in this day and age. Instead we propose a more inclusive option: embrace all voices and channel them into an actual, prospective earthquake prediction platform (Kamer et al. 2020). The platform is powered by a global state-of-the-art statistical earthquake forecasting model that provides near real-time earthquake occurrence probabilities anywhere on the globe (Nandan et al. 2020). Using this model as a benchmark in statistical metrics specifically tailored to the prediction problem, we are able to distill all these voices and quantify the essence of predictive skill. This approach has several advantages. Rather than trying to silence or denounce, we listen and evaluate each claim and report the predictive skill of the source. We engage the public and allow them to take part in a scientific experiment that will increase their risk awareness. We effectively demonstrate that anybody with an internet connected device can make an earthquake prediction, but that it is not so trivial to achieve skillful predictive performance.

Here we shall present initial results from our global earthquake prediction experiment that we have been conducting on www.richterx.com for the past two years, yielding more than 10,000 predictions. These results will hopefully demystify the act of predicting an earthquake in the eyes of the public, and next time someone forwards a prediction message it would arouse more scrutiny than panic or distaste.

Nandan, S., Kamer, Y., Ouillon, G., Hiemer, S., Sornette, D. (2020). Global models for short-term earthquake forecasting and predictive skill assessment. European Physical Journal ST. doi: 10.1140/epjst/e2020-000259-3
Kamer, Y., Nandan, S., Ouillon, G., Hiemer, S., Sornette, D. (2020). Democratizing earthquake predictability research: introducing the RichterX platform. European Physical Journal ST. doi: 10.1140/epjst/e2020-000260-2 
Bacterial communities in shallow fractured-rock groundwater evolve over time, exhibiting cyclic patterns in response to multi-annual recharge events.
Authors: Hermans Syrie , Yan Lijuan , Totsche Kai Uwe , Lehmann Robert , Herrmann Martina , Küsel Kirsten
Published: March 2021

Groundwater is an important component of the Earth’s critical zone and within this ecosystem, microbial communities play an important role, interacting with, and contributing to, the geology and hydrology of these systems; understanding how microbial communities in this dynamic zone change over time is therefore crucial. However, subsurface aquatic environments are lacking high-resolution temporal data over long time periods. Based on 16S rRNA gene sequences collected monthly over a six-year period (n=230) in groundwater from fractured Triassic limestone-mudstone alternations of the Hainich Critical Zone Exploratory (central Germany), we, therefore, aimed to disentangle the temporal dynamics of bacterial communities. The bacterial communities in the shallow bedrock groundwater showed multi-annual cyclic dissimilarity patterns which corresponded to groundwater level fluctuation and, thus, recharge discharge periods. The impact of groundwater fluctuation and linked cross-stratal exchange on the groundwater microbial communities was associated with the recharge strength and local environmental selection strength. Sampling period was able to explain up to 29.5% of the variability in bacterial community composition (based on a 2-factorial PERMANOVA model). We observed an increase in dissimilarity over time (Mantel P > 0.001) indicating that the successive recharge events result in bacterial communities that are increasingly more dissimilar to the communities at the start of the sampling period. Most bacteria in the groundwater originated from the recharge-related sources (mean = 66.5%, SD = 15.1%) and specific bacterial taxa were identified as being either enriched or repressed during recharge events. Overall, we show that seasonal recharge patterns are important for shaping bacterial communities in shallow fractured-rock groundwater and act as drivers of cyclical patterns. Furthermore, the recharge events are successive shocks that perturbed the bacterial communities, leading to decreased similarity to the original state over time. These revelations highlight the importance of high temporal resolution research in the Critical Zone for investigating the complex interplay between surface/subsurface environmental dynamics and the biology of groundwater ecosystems.
From climate models to informing policy decisions: the end-to-end importance of an effective research infrastructure
Authors: Adloff Fanny , Lawrence Bryan , Joussaume Sylvie , Lautenschlager Michael , Bessembinder Janette , Biercamp Joachim , Cofiño Antonio , D’Anca Alessandro , Fladrich Uwe , Hines Adrian , Juckes Martin , Kazeroni Rémi , Kershaw Philip , Kindermann Stephan , Nassisi Paola , Pagé Christian , Serradell Kim , Valcke Sophie
Published: March 2021

The last few decades have seen a range of advances in climate science and consequential policy initiatives at both national and international levels. These advances have been built on the back of progress in modelling and in part been enabled by the global data sharing initiative - the Earth System Grid Federation (ESGF) - which has underpinned recent phases of the World Climate Research Programme's Coupled Model Intercomparison Projects.  

The ESGF itself consists of data nodes deployed by individual modelling centres and a backbone of software development and services delivered by a few core institutions. Within Europe, along with some shared development of model components, these core ESGF software development and services are coordinated by the European Network on Earth System Modelling (ENES) and supported by the H2020 IS-ENES Phase 3 research infrastructure project.  

We provide an historical overview on advances in policy-relevant science, such as the Intergovernmental Panel for Climate Change (IPCC), that have been enabled by long-term underpinning development and funding of the ENES and ESGF infrastructure. We illustrate the recent shift of research funding from physical science objectives alone towards funding services to society (and the necessary underpinning research). We stress the potential dangers of underfunding research infrastructures that need to be simultaneously flexible and reliable enough to serve both ongoing basic research and the growing societal objectives, as emphasised by the development of climate services such as Copernicus Climate Change Service. We conclude by presenting some steps towards sustaining such research infrastructure in the context of the ENES and the possible futures of climate science.
Hydraulic tomography using joint inversion of head and flux data 
Authors: Pouladiborj Behzad , Bour Olivier , Linde Niklas , Longuevergne Laurent
Published: March 2021

Hydraulic tomography is a state of the art method for inferring hydraulic conductivity fields using head data. Here, a numerical model is used to simulate a steady-state hydraulic tomography experiment by assuming a Gaussian hydraulic conductivity field (also constant storativity) and generating the head and flux data in different observation points. We employed geostatistical inversion using head and flux data individually and jointly to better understand the relative merits of each data type. For the typical case of a small number of observation points, we find that flux data provide a better resolved hydraulic conductivity field compared to head data when considering data with similar signal-to-noise ratios. In the case of a high number of observation points, we find the estimated fields to be of similar quality regardless of the data type. A resolution analysis for a small number of observations reveals that head data averages over a broader region than flux data, and flux data can better resolve the hydraulic conductivity field than head data. The inversions' performance depends on borehole boundary conditions, with the best performing setting for flux data and head data are constant head and constant rate, respectively. However, the joint inversion results of both data types are insensitive to the borehole boundary type. Considering the same number of observations, the joint inversion of head and flux data does not offer advantages over individual inversions. By increasing the hydraulic conductivity field variance, we find that the resulting increased non-linearity makes it more challenging to recover high-quality estimates of the reference hydraulic conductivity field. Our findings would be useful for future planning and design of hydraulic tomography tests comprising the flux and head data.
Heat-mass transfer simulation of fluid media in the magma channel
Authors: Vasilev Georgii , Perepechko Yury
Published: March 2021

The paper presents a non-stationary model of heat-mass transfer of heterophase media in application to the study of the intrusion processes of magmatic melts in permeable zones of the lithospheric mantle and crust. Special emphasis is given to the study of the change in rheological properties of the fluido-magmatic mixture in the process of magmatic channel formation. The increased compressibility of the fluid phase is taken into account in the model by setting the Van der Waals equation of state. The calculated values of thermodynamic parameters of the fluid-magmatic system such as pressure, temperature, volumetric phase content, are the basis for the analysis of metasomatic changes in mantle matter. The Numerical model is based on the Runge-Kutta-TVD method. Verification of the numerical model on standard tests shows good accuracy of the program code and the possibility of using it for investigations of the currents of fluid-magmatic flows. The study of variation in interphase interaction parameters during melt movement in permeable zone, including change in interphase viscous friction, demonstrates a significant change in temperature distribution in the section of fluid-magmatic system. The work was financially supported by the Russian Foundation for Basic Research, grants No. 19-05-00788.
Induced glide-snow avalanches with low friction geotextiles
Authors: Glover James , Althoff Sebastian , Witek Max , Seupel Christine , Braun Seraina , Lifa Imad
Published: March 2021

Gliding snow avalanches are of growing concern for the management of ski areas, transport corridors and spatial planning. With a warming climate there appear to be increasing reports of gliding snow hazards in alpine regions. The management of gliding snow avalanches can be achieved through either stabilization or artificially triggering a slide. Triggering sliding is attractive because it has the potential to remove the hazard entirely. In this research, we investigate the potential of managing gliding snow avalanches through the early release of snow accumulations using low friction geotextiles.

A series of geotextiles have been installed on slopes between 25 and 35° during the autumn months and the behavior of snow accumulations observed during the winter. Initial findings indicate that reducing the basal friction can be effective in inducing early release of gliding snow avalanches. However, the interaction of the flanking snow pack and stauchwall appear dominant in the behavior of the system. This contribution reports on the initial findings of these experiments and discusses the potential applications to managing gliding snow avalanches.  
Exceptionally rich sedaDNA record from a subalpine lake in the Central Alps reveals plant responses to climate change and human land use
Authors: Garces Pastor Sandra , Lammers Youri , Heintzman Peter D. , Gavin Brown Antony , Tinner Willy , Schwörer Christoph , Heiri Oliver , Rey Fabian , Heer Martina , Rutzer Astrid , Lavergne Sébastien , Coissac Eric , Taberlet Pierre , Theurillat Jean-Paul , G. Alsos Inger
Published: March 2021

The increase in plant species richness in the Alps over the last century has been described as a direct response to climate warming. Alpine ecosystems are expected to have an upward displacement of vegetation, resulting in shifts of species ranges, high replacement rates, and species loss. To apply proper management measures, it is necessary to understand how drivers of change affect species and ecosystem tipping points. Palaeoecological studies allow us to understand how species responded to similar situations in the past. However, such studies are often challenged by proxy preservation and taxonomic resolution. Metabarcoding approaches based on sedimentary ancient DNA (sedaDNA) can overcome these caveats. 

Here we use plant sedaDNA and the new PhyloAlps taxonomic reference database, which covers 4500 plant taxa from the Alps, to explore alpine floral diversity of Sulseewlii, a subalpine lake in the Central Alps (Switzerland). We present a 12,000 year record of vegetational composition and structural changes in a subalpine ecosystem. To disentangle the relationship between climate and vegetation, we used a novel local temperature reconstruction inferred from chironomids of the same lake. We also used coprophilous fungal spores and charcoal, together with pastoral and arable indicators, to infer human pressure. 

With 377 identified taxa, including 140 at species level, Sulseewlii has yielded the richest dataset of plant sedaDNA to date and emphasizes the Alps as an important biodiversity hotspot in Europe. Out of the identified taxa, 91 are indicators that allowed us to reconstruct the vegetation stages and altitudinal shifts of the main vegetation groups. Total taxonomic richness increases from the onset of the Holocene and has a similar pattern to subalpine-montane DNA taxa, with three marked drops at 8200, 3200, and ~500 cal yr BP. Plant sedaDNA registered a marked transition from alpine to subalpine communities at the onset of the Holocene. The highest proportions of montane taxa occurred during the Holocene climatic optimum (9,000-6,000 cal yr BP). Finally, a shift back to subalpine-montane species with some lowland influence occurs as we approach the present.
Role of the Crustal deformation processes on the seismicity: An approach, using combined dense GNSS velocity field in Europe
Authors: Piña-Valdés Jesus , Socquet Anne , Beauval Céline , Bard Pierre-Yves , Doin Marie-Pierre , D’Agostino Nicola , Shen Zhengkang
Published: March 2021

The impact of the crust deformation on the processes that control the seismic activity is still controversial. The seismic activity is usually thought to be associated with the active tectonic deformation as estimated from the horizontal displacements field: seismic active regions are usually dominated by important horizontal deformation controlled by tectonic activity. But this is not so clear on regions of low to moderate seismicity, where small horizontal deformation rates are commonly observed, similar to the rates detected for regions of no seismicity. In those regions, the non-tectonic processes such as the Glacial Isostatic Adjustment (GIA), may have a significant impact on the seismicity.

Since the deformation of low tectonic activity in Europe is usually piecewise, we combined 10 different GNSS velocity field solution to generate a dense GNSS solution to derive the 3D strain rate at continental scale: using the velocity solutions of common stations, the different datasets were converted to a common reference frame. Their uncertainties were homogenized, and a combined velocity field was computed considering the homogenized uncertainty of each independent solution. Finally, an automatized criterion of identification and outliers removal was applied, as well an adaptive smoothing scheme that depends on the station density, the noise, and the local tectonic deformation rate

The resulting 3D combined GNSS velocity field was interpolated and the horizontal strain rate was derived. Then, assuming the Hooke law for the earth crust, we decompose the vertical velocity field into a component due to tectonic deformation and a component due to isostatic rebound. To better understand the effects of horizontal tectonic deformation versus the flexure generated by GIA on the seismicity, the spatial distribution of the seismicity is compared to the strain rate map and the vertical velocity fields.
Performance and sensitivity of a spatially distributed hydrological conceptual flood model with snow components.
Authors: Colleoni François , Fouchier Catherine , Garambois Pierre-André , Javelle Pierre , Jay-Allemand Maxime , Organde Didier
Published: March 2021

In France, flash floods are responsible for a significant proportion of damages caused by natural hazards, either human or material. Hence, advanced modeling tools are needed to perform effective predictions. However for mountainous catchments snow modeling components may be required to correctly simulate river discharge.

This contribution investigates the implementation and constrain of snow components in the spatially distributed SMASH* platform (Jay-Allemand et al. 2020). The goal is to upgrade model structure and spatially distributed calibration strategies for snow-influenced catchments, as well as to investigate parametric sensitivity and equifinality issues. First, the implementation of snow modules of varying complexity is addressed based on Cemaneige (Valery et al. 2010) in the spatially distributed framework. Next, tests are performed on a sample of 55 catchments in the French North Alps. Numerical experiments and global sensitivity analysis enable to determine pertinent combinations of flow components (including a slow flow one) and calibration parameters. Spatially uniform or distributed calibrations using a variational method (Jay-Allemand 2020) are performed and compared on the dataset, for different model structures and constrains. These tests show critical improvements in outlet discharge modeling by adding slow flow and snow modules, especially considering spatially varying parameters. Current and future works focus on testing and improving the constrains of snow modules and calibration strategy, as well as potential validation and multiobjective calibration with snow signatures gained from in situ or satellite data. 

*SMASH: Spatially-distributed Modelling and ASsimilation for Hydrology, platform developped by INRAE-Hydris corp. for operational applications in the french flood forecast system VigicruesFlash
Formation features of river underground runoff under global warming conditions
Authors: Osadchyi Volodymyr , Shevchenko Oleksii , Krasovs’ka Anastasiya
Published: March 2021

According to the results of processing long-term data series of hydrological and hydrogeological monitoring in the upper part of the Southern Bug river basin, it has been found that meteorological or climatic changes affect both terrestrial hydrosphere and shallow groundwater aquifer (level = 0.5…7.0 m). There are two stages of different effects of temperature changes on the groundwater regime: the first stage (1974-1998) had a positive impact, with an increased infiltration recharge and large-scale flooding, while the second stage (1999-2020) is characterized by increasing drought. The average annual infiltration recharge of groundwater on the first terrace above the flood-plain at the first stage has reached 191.6 mm that is quite high for this climatic zone, while at the second stage – 115.0 mm. The highest groundwater runoff to the river was recorded in 1987-1989 (the first terrace above the flood-plain), 1996-1998, 2005, and 2014 (from the left-bank catchment). By seasonal distribution, the spring runoff mostly prevailed in 1981-1986; starting from 1996-1999 (in different areas) – summer runoff, especially in years with maximum underground runoff; the winter runoff to the river slightly prevailed in certain years (1994, 1998, 2000, 2008, 2015).

With the transition from a low-water cycle of years to a water-rich cycle (and vice versa), the dominant cyclicity in the regime of groundwater and surface water changes from 5-6 years to 7-8 years.

1974-1975 and 1987-1989 had certain temperature limits that caused significant changes in the groundwater level regime: firstly, at long-term annual average depths of 1.5-1.8 m under the surface, and later at depths of 3.0-4.4 m having led to the transition and consolidation of levels at higher grades. At the second stage, the trends of precipitation, groundwater and surface runoff change significantly (surface runoff decreases most rapidly, while the intensity of groundwater runoff has slowed down), but the temperature rises with almost the same intensity. The dependence of the total river runoff on the underground increases.

In the long-term plan (40 years), groundwater and river runoffs change in opposite directions, as the regime-forming factors (temperature and precipitation) have different effects on them: rising temperatures at the first stage have led to increased groundwater runoff; at the same time, the intensity of the decrease in river runoff under the influence of temperature as well as the decrease in precipitation at the second stage increase. The difference in the rate of reactions of groundwater and surface water levels to precipitation still provides an increase in groundwater runoff by increasing the flow gradient to the river. With decreasing rainfall, this scenario will certainly lead to the depletion of groundwater reserves.
Rapid Ecohydrological Response of a Mountaintop Peatland to Recent Climate Warming in Northeast China
Authors: Yang Tingwan , Zhao Hongyan , Xia Zhengyu , Yu Zicheng , Li Hongkai , Bu Zhaojun , Wang Shengzhong
Published: March 2021

Montane bogs—peat-forming ecosystems located in high elevation and receiving their water supply mostly from meteoric waters—are unique archives of past environmental changes. Studying these ecosystems and their responses to recent climate warming will help improve our understanding of the sensitivity of high-elevation peatlands to regional climate dynamics. Here, we report a post-bomb radiocarbon-dated, high-resolution, and multi-proxy record in Laobaishan bog (LBS), a mountaintop bog from the Changbai Mountains Range in Northeast China. We analyzed plant macrofossils and testate amoebae of a 41-cm peat core dated between 1970 and 2009 to document the ecohydrological response of peatland to the anthropogenic warming in recent decades. We quantitatively reconstruct the surface wetness changes of LBS bog using the first axis of the detrended correspondence analysis (DCA) of plant macrofossil assemblages and depth to water table (DWT) inferred by transfer function of testate amoebae assemblages. We distinguished two hydroclimate stages: the moist stage before the 1990s and the rapidly drying stage since the 1990s. During the moist stage, plant macrofossils were characterized by the low abundance of Sphagnum capitifolium and Polytrichum strichum that prefer dry habitats, and testate amoebae assemblages were dominated by low abundance of dry-adapted Assulina muscorum and Corythion dubium. High score of first axis and low DWT also suggested a moist habitat at LBS. After the transition into the drying stage, the abundance of S. capitifolium and P. strichum increased and that of A. muscorum and C. dubium showed similar trend. Score of first axis and DWT reconstructions show that LBS have experienced rapid surface desiccation since the 1990s. Based on the high-resolution gridded reanalysis data, these ecohydrological changes occurred with a rapid increase in temperature (~1°C) but without notable change in total precipitation during the growing season (May–September) since the 1990s. Besides, backward trajectory analysis showed no apparent changes in atmospheric circulation pattern since the 1990s, supporting our interpretation that the ecohydrological changes in LBS bog were induced by climate warming. These results demonstrate that the plant communities, microbial assemblages, and peatland hydrology of montane peatland show a sensitive response to climate warming that might be in larger amplitude than the low-elevation areas.
Major weather-related risks to crop performance along the Australian wheat belt for recent past and longer-term historical weather records
Authors: Bracho Mujica Gennady , Hayman Peter , Sadras Victor , Ostendorf Bertram , Ferreira C. R. Nicole , Abdulai Issaka , Rötter Reimund
Published: March 2021

Extreme events, such as drought, heat and/or frost are among the major weather-related causes of yield reduction and crop failure worldwide. Changes in the frequency and intensity of such weather extremes affect the shape and scale of yield distributions. Wheat growers, in Australia, are particularly vulnerable to climate due to its high variability. Risks of both, extremely high or low temperatures and water stress occurring simultaneously or at different crop stages within the growing season (May-October, e.g. frost mid-season, drought during the season and heat towards the end) often lead to yield reductions, or sometimes even to crop failure. In this study, we focused on assessing the frequency and impact of these relevant extreme weather events (i.e. drought, heat and frost) affecting wheat production in Australia. Specifically, we used a widely used and calibrated crop model (APSIM) to simulate wheat grain yield, and determine probability density functions (PDFs) of grain yield and crop failure. Chances of crop failure due to these extreme events are explored for the recent past (1991-2020) and the longer-term historical past (1901-1990). Key adaption strategies to minimise the impacts of these extreme events, and reduce crop failure risk are assessed in this study, including early sowing and cultivar choice. Our findings are in line with recent studies, indicating that drought and heat are major risk factors contributing to reduced yields or crop failure. However, due to the timing, frequency and impacts of frost events on wheat productivity, frost also remains a relevant risk for the wheat industry in Australia.
Quantification of clay content using the transient electromagnetic and spectral induced polarization method
Authors: Aigner Lukas , Katona Timea , Michel Hadrien , Ahmed Arsalan , Hermans Thomas , Flores Orozco Adrián
Published: March 2021

Detailed information on the clay content of the subsurface and its spatial distribution plays a critical role in the interaction between surface- and groundwater. In this study, we investigate a new methodology to integrate data measured with electromagnetic and electrical geophysical methods, namely, the transient electromagnetic (TEM) and the spectral induced polarization (SIP) to quantify subsurface clay content in an imaging framework. The methodology is tested in data sets collected at a quarry close to Vienna and consists of a ca. 10 m thick clay layer below a ca. 8 m thick overburden of sandy silts. Our data set includes SIP data collected along a 315 m long profile with an electrode separation of 5 m in a frequency range from 0.1 to 225 Hz. Along this profile, we measured 26 TEM soundings using a 12.5 m loop with 24 windows recording in a time range between 4 and 140 μs. Ground truth information corresponds to grain size analysis conducted in 25 soil samples collected in a depth from 5 to 28 m. SIP inversion results at a single frequency provided structural a-priori information to improve the inversion of the TEM data. The inverted TEM conductivity model, nearest to the position of soil sample collection, was correlated to the grain size distribution and the resulting positive exponential relationship was used to obtain vertical 1D variations of clay content with depth. All sounding positions were interpolated to obtain a 2D image of subsurface clay content. This clay content variations were then compared to images of the Cole-Cole parameters, describing the frequency dependence of SIP imaging results. To evaluate the uncertainty in our clay estimations, we applied the Bayesian evidential learning 1D imaging (BEL1D). We obtained uncertainties of layer thickness, resistivity, and clay content by integrating the clay-conductivity relationship derived from TEM data into the BEL1D framework.
 On spatial patterns of heat waves and cold spells from a large deviations perspective
Authors: Galfi Vera Melinda , Lucarini Valerio
Published: March 2021

We analyse persistent temperature events, like heat waves or cold spells, by applying large deviation theory (LDT), and show that events with a long duration have also a substantial spatial extension. We point out that by using LDT one finds typical spatial patterns related to the persistent temperature extremes. Based on the output of a state-of-the-art climate model, we define the climatology of persistent heatwaves and cold spells in some key target regions of the planet by constructing empirically the corresponding rate functions for the surface temperature, and we assess the impact of increasing CO2 concentration on such persistent anomalies. In particular, we notice the increasing hazard associated to heatwaves in a warmer climate. We show that two 2010 high impact events - summer Russian heatwave and winter Dzud in Mongolia – are associated with extended atmospheric patterns that are exceptional compared to the typical ones, but typical compared to the climatology of extreme events.