bluuebunny/crossref_metadata_2025 huggingface dataset:
Ionospheric VTEC Forecasting using Machine Learning
Authors: Natras Randa , Schmidt Michael
Published: March 2021

The accuracy and reliability of Global Navigation Satellite System (GNSS) applications are affected by the state of the Earth‘s ionosphere, especially when using single frequency observations, which are employed mostly in mass-market GNSS receivers. In addition, space weather can be the cause of strong sudden disturbances in the ionosphere, representing a major risk for GNSS performance and reliability. Accurate corrections of ionospheric effects and early warning information in the presence of space weather are therefore crucial for GNSS applications. This correction information can be obtained by employing a model that describes the complex relation of space weather processes with the non-linear spatial and temporal variability of the Vertical Total Electron Content (VTEC) within the ionosphere and includes a forecast component considering space weather events to provide an early warning system. To develop such a model is challenging but an important task and of high interest for the GNSS community.

To model the impact of space weather, a complex chain of physical dynamical processes between the Sun, the interplanetary magnetic field, the Earth's magnetic field and the ionosphere need to be taken into account. Machine learning techniques are suitable in finding patterns and relationships from historical data to solve problems that are too complex for a traditional approach requiring an extensive set of rules (equations) or for which there is no acceptable solution available yet.

The main objective of this study is to develop a model for forecasting the ionospheric VTEC taking into account physical processes and utilizing state-of-art machine learning techniques to learn complex non-linear relationships from the data. In this work, supervised learning is applied to forecast VTEC. This means that the model is provided by a set of (input) variables that have some influence on the VTEC forecast (output). To be more specific, data of solar activity, solar wind, interplanetary and geomagnetic field and other information connected to the VTEC variability are used as input to predict VTEC values in the future. Different machine learning algorithms are applied, such as decision tree regression, random forest regression and gradient boosting. The decision trees are the simplest and easiest to interpret machine learning algorithms, but the forecasted VTEC lacks smoothness. On the other hand, random forest and gradient boosting use a combination of multiple regression trees, which lead to improvements in the prediction accuracy and smoothness. However, the results show that the overall performance of the algorithms, measured by the root mean square error, does not differ much from each other and improves when the data are well prepared, i.e. cleaned and transformed to remove trends. Preliminary results of this study will be presented including the methodology, goals, challenges and perspectives of developing the machine learning model.
Depth-dependent Clustering Analysis of Fractures in Crystalline Basement Rocks
Authors: Afshari Moein Mohammad Javad , Evans Keith , Valley Benoît , Bär Kristian , Genter Albert
Published: March 2021

Understanding the complex seismic, thermal, hydraulic and mechanical processes active during the hydraulic stimulation or continuous operation of Enhanced Geothermal Systems (EGS) requires an accurate description of the pre-existing fractures and faults. However, the three-dimensional characterization of the fracture network is challenging, as direct observation of the discontinuity network at great depth is limited. Fracture image logs and continuous core, which provide line samples through the fracture network, are most valuable in this regard as they provide the most precise option to place constraints on network attributes in stochastic realizations of the fractured rock mass. Among various geometrical attributes, the spatial clustering of fractures plays a critical role on the rock mass properties. 

Here, we analyzed the spatial distribution of fractures derived from image log runs in six deep boreholes in crystalline basement rock. In one well, the fracture distribution from continuous core was also available. The wells were drilled to depths between 2-5 km, and were all located in the same tectonic setting of the Upper Rhine Graben, which is recognized for its high geothermal potential. The normalized correlation integral method was employed to define the scaling relationships of fracture patterns. This methodology is demonstrated to be less affected by the finite size effects, delivering reliable estimates of scaling laws.

Detailed analyses of image log datasets revealed fractal scaling with similar fractal dimensions (between 0.85 and 0.96), prevailed over almost two orders of magnitude of scale. The same was true for the fracture distribution derived from the continuous core, although this distribution was found to be more clustered than that derived from image logs in the same well (i.e. the fractal dimension was lower, which may be due to the partial fracture sampling of image logs which have a coarser resolution than continuous core analyses). Analysis of fractures in sub-sections of the core dataset from progressively increasing depths revealed no systematic depth-dependency for the fractal dimension, although a local variation at a scale of hundreds of meters was identified.
Evidence for Holocene ice sheet history from geomorphology, cosmogenic isotopes, and bird vomit, East Antarctica.
Authors: Bentley Mike , Hodgson Dominic , Hein Andy , Binnie Steve , Moreton Steve
Published: March 2021

The post-LGM thinning history of the East Antarctic Ice Sheet is not yet well constrained. Here we report some integrated observations and analyses that constrain the ice sheet thinning history in Western Dronning Maud Land and Coats Land, adjacent to the easternmost Weddell Sea, which is a key area of uncertainty in ice sheet reconstructions. Geomorphological observations show a distinct series of weathering zones with fresh erratics only found in a relatively narrow zone above the present ice sheet margin. We report cosmogenic surface exposure dates of erratics in the different weathering zones, using 10Be and in situ 14C. We further report a large number of radiocarbon ages on sub-fossil bird vomit (regurgitated proventricular stomach oil, sometimes termed ‘mumiyo’) from nesting snow petrels (Pagodroma nivea) which record periods of ice sheet absence. Together these analyses allow us to determine a more tightly constrained thinning history of the ice sheet in this sector. We discuss the implications of this thinning history for geologically-based ice sheet reconstructions and for ice sheet models.
Extending established soil hydraulic property models by non-capillary water: A comprehensive model performance test
Authors: Hohenbrink Tobias L. , Peters Andre , Iden Sascha C. , Durner Wolfgang
Published: March 2021

Understanding and describing the hydrologic function of soils requires adequate models of soil hydraulic properties. Established models for hydraulic properties implicitly assume that water flow occurs only in completely filled soil pores. This simplification is questionable in cases where soils become dry.  Lab measurements have repeatedly shown that under dry conditions, water retention and hydraulic conductivity are dominated by water in thin films. Today, there are some modelling approaches that take into account this so-called non-capillary water. One of these is the simple Peters-Durner-Iden model system (PDI), which extends any basic model of capillary retention and conductivity by a non-capillary counterpart. In the original form, this requires one additional fitting parameter to characterize the magnitude of non-capillary conductivity. Peters et al. (2021) have recently updated the model system (PDIc) to predict the non-capillary conductivity from the water retention curve without increasing the number of adjustable parameters compared to the established models.

In this contribution we present a comprehensive model performance test of the established capillary models, the original PDI model, and the new PDIc model. The performance test is based on a data collection of soil hydrological variables measured at 500 undisturbed soil samples. The collection contains soil water retention and conductivity data, determined in the laboratory by the evaporation method, supplemented by dew point method data and measurements of saturated conductivity. For each data set we estimated the soil hydraulic parameters for any combination of the three basic models: van Genuchten with m=1-1/n, van Genuchten with a free parameter m, and Fredlund & Xing and the three considerations of non-capillary water: not considered (no PDI), PDI, and PDIc.

The results showed that the most flexible basic functions generally yielded the best model fits. For example, the Fredlund & Xing model outperformed the two van Genuchten models. Considering non-capillary water by the PDI model system also clearly increased the model performance. The root mean squared errors (RMSE) for the fits of both the retention and the conductivity curve were clearly reduced in the order from no PDI to PDIc to PDI. Remarkably, the PDIc model generally achieved better fits than the established models although it has exactly the same free parameters.

 

References
Peters, A., T.L. Hohenbrink, S.C. Iden, and W. Durner. A simple model to predict hydraulic conductivity in medium to dry soil from the water retention curve. Geophysical Research Abstracts Vol. 23, EGU21-8717, 2021.
A preliminary investigation of dynamical complexity in Swarm Dst-like time series using information theory techniques
Authors: Balasis Georgios , Papadimitriou Constantinos , Potirakis Stelios M. , Boutsi Adamantia Zoe , Daglis Ioannis A. , Giannakis Omiros , De Michelis Paola , Consolini Giuseppe
Published: March 2021

For 7 years now, the European Space Agency’s Swarm fleet of satellites surveys the Earth’s magnetic field, measuring magnetic and electric fields at low-Earth orbit (LEO) with unprecedented detail. We have recently demonstrated the feasibility of Swarm measurements to derive a Swarm Dst-like index for the intense magnetic storms of solar cycle 24. We have shown that the newly proposed Swarm Dst-like index monitors magnetic storm activity at least as good as the standard Dst index. The Swarm derived Dst index can be used to (1) supplement the standard Dst index in near-real-time geomagnetic applications and (2) replace the ‘prompt’ Dst index during periods of unavailability. Herein, we employ a series of information theory methods, namely Hurst exponent and various entropy measures, for analyzing Swarm Dst-like time series. The results show that information theory techniques can effectively detect the dissimilarity of complexity between the pre-storm activity and intense magnetic storms (Dst < 150 nT), which is convenient for space weather applications.
The Nonlinear Nature of Atmospheric Chemistry
Authors: Prather Michael
Published: March 2021

When scientific or policy-relevant questions involve atmospheric chemistry, one often hears "nonlinear" being invoked, but the precise nature of the nonlinearity is never delineated, and we are left with the fuzzy impression that nonlinear problems are difficult, with no simple answer.  I have even seen it used to avoid including indirect greenhouse gases in the Kyoto Protocol.  For differentiable systems, nonlinear behavior can be expressed through a Taylor expansion whereby any of the 2nd order terms (x2, y2 or xy) are the first nonlinear parts.  In this lecture I explore a range of scientific discoveries or developments in atmospheric chemistry where the nonlinear nature was critical to understanding the problem.  I select a set of problems worked on by many colleagues and myself over the last four decades.  These include:  multiple solutions in stratospheric chemistry; catastrophic depletion of ozone; numerical methods for tracer transport; our developing understanding of methane; chemical feedbacks and indirect greenhouse gases; and finally the rich heterogeneity of gases that drives tropospheric chemistry. I hope to convince you that by recognizing the nonlinear nature of atmospheric chemistry and understanding when it is important and when it is not, we can advance the field.   
Can high-frequency data enable better parameterization of water quality models and disentangling of DO processes?
Authors: Huang Jingshui , Merchan-Rivera Pablo , Chiogna Gabriele , Disse Markus , Rode Michael
Published: March 2021

Water quality models offer to study dissolved oxygen (DO) dynamics and resulting DO balances. However, the infrequent temporal resolution of measurement data commonly limits the reliability of disentangling and quantifying instream DO process fluxes using models. These limitations of the temporal data resolution can result in the equifinality of model parameter sets. In this study, we aim to quantify the effect of the combination of emerging high-frequency monitoring techniques and water quality modelling for 1) improving the estimation of the model parameters and 2) reducing the forward uncertainty of the continuous quantification of instream DO balance pathways.

To this end, synthetic measurements for calibration with a given series of frequencies are used to estimate the model parameters of a conceptual water quality model of an agricultural river in Germany. The frequencies vary from the 15-min interval, daily, weekly, to monthly. A Bayesian inference approach using the DREAM algorithm is adopted to perform the uncertainty analysis of DO simulation. Furthermore, the propagated uncertainties in daily fluxes of different DO processes, including reaeration, phytoplankton metabolism, benthic algae metabolism, nitrification, and organic matter deoxygenation, are quantified.

We hypothesize that the uncertainty will be larger when the measurement frequency of calibrated data was limited. We also expect that the high-frequency measurements significantly reduce the uncertainty of flux estimations of different DO balance components. This study highlights the critical role of high-frequency data supporting model parameter estimation and its significant value in disentangling DO processes.
Analysis of determinants of forest - savanna transition in the northern South America
Authors: Valencia Santiago , Villegas Juan Camilo , Salazar Juan F.
Published: March 2021

Forest - savanna transition is the most widespread and perhaps more dynamic ecotone in the tropics, and extremely sensitive to climate and environmental change. Both kinds of tropical ecosystems are globally strategic and their presence and dynamics have important ecological, climatic and biogeochemical implications, even at the global scale. However, the processes and mechanisms that control this transition vary among regions and remain not fully understood. In general, this transition is influenced by multiple interactions between vegetation and environmental factors such as climate, soil properties, fire, and herbivory. However, the magnitude of these effects can vary substantially across continents, which can result in different responses to environmental change. For this reason, more regional studies are needed to describe and understand the factors and interactions that control forest - savanna transition, particularly in Northern South America, where climate alone has failed to explain this transition. Based on a combination of LiDAR and satellite-derived data, we developed a statistical analysis on the interactive effects of rainfall, soil properties, and fire on the forest - savanna transition in Northern South America, in the savanna region between Colombia and Venezuela, using tree cover as an indicator variable that differentiates forest from savanna. Specifically, we analyze the relationships of tree cover (from GEDI) with soil sand content (from SoilGrids), fire frequency (from Fire_CCI v5.1) as well as three rainfall variability components (from CHIRPS): mean dry-season rainfall, length of the dry season, and frequency of rainy days within the dry season. Our results show that tree cover increased with mean dry-season rainfall and frequency of rainy days within the dry season, whereas it decreased with increased fire frequency. In particular, mean dry-season rainfall followed by fire frequency are the most important predictors of tree cover gradient in the transition. Importantly, our results also suggest that areas with high annual rainfall (2000 to 2800 mm) have low tree cover (i.e. savanna) if the local rainfall climatology consists of infrequent (< 0.35) and low total rainfall (< 650 mm) in the dry season. This highlights the role of water availability and fire disturbance in determining the limits between forest and the second largest area of savanna in South America. Further, our results support that future projections for forest - savanna transition should include not only changes in mean annual rainfall but also changes in rainfall variability, which is expected to be more impacted by climate change. 
Latest instrument and algorithm developments from the GeoCarb mission
Authors: Somkuti Peter , O'Dell Christopher , McGarragh Gregory , Crowell Sean , Burgh Eric , Adamkovics Mate , Crisp David
Published: March 2021

Since its selection as a NASA Earth Venture mission in late 2016, the Geostationary Carbon Cycle Observatory (GeoCarb) has been in steady development. Launch is planned for 2024, and the instrument will be hosted on a commercial platform in geostationary orbit. Featuring a geostationary view over the western hemisphere, GeoCarb will be able to provide atmospheric total-column trace gas amounts to help answer scientific questions related to the carbon cycle of North and South America such as the quantification of regional- and urban-scale carbon dioxide emissions.

GeoCarb’s instrument design features a two-arm grating-type spectrometer with four separate bands at wavelengths 0.765 µm, 1.606 µm, 2.065 µm and 2.323 µm in order to measure atmospheric absorption features of oxygen (O2), carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO). With the spacecraft position being fixed relative to Earth and the instrument’s scan mirror assembly, GeoCarb will be able to selectively point at locations visible from its position over the American continents. As a result, very different sampling strategies can be employed,  compared to polar orbiting instruments which are generally limited to revisit periods of days and weeks. For routine operations, the North and South American land masses will be scanned at least once per day – depending on the final choice of scanning strategy, large portions of the American continents could be measured twice per day. Thanks to the flexible scanning capability, there is also the possibility for special campaigns which can feature many repeated measurements over targets of special interest throughout a single day.

In this presentation, we summarize the most recent development status of the GeoCarb instrument and the various retrieval algorithms that will be used for data product generation. We will share updates on the impact of sub-slit scene inhomogeneity on retrieval results, and how a slit homogenizer can mitigate those effects. Further, we report on our analyses regarding the correction of the so-called keystone optical aberration. Finally, we provide a detailed overview of GeoCarb’s capabilities for the retrieval of solar-induced chlorophyll fluorescence.
Joint Distribution of Rainfall Characteristics: Intensity, Total Depth, Spatial and Temporal Moments
Authors: Quaglia Roberto , Woods Ross , Han Dawei
Published: March 2021

Determination of peak flow or flow hydrograph in ungauged basins can be affected by considerable degree of uncertainty. Despite the considerable efforts to overcome this challenge, current methods provide design flood estimates that are still highly uncertain in ungauged catchments, even in the UK where the gauged network is relatively dense. A possible solution may be found in stochastic approaches and more specifically in the Derived Flood Frequency method, which gives the possibility to decompose runoff response effects dictated by the dominant hydrological processes for a catchment under study. Data scarcity can be then circumvented by application of UK-specific stochastic models, from which rainfall events and their relevant features are sampled. In this work, the latter rainfall model will be presented as a joint distribution function of spatial and temporal moments of catchment rainfall, along with their Intensity and Total Depth. The marginal distributions for each rainfall characteristic are studied through the L-moment method, which was previously developed for regional frequency analysis. The multivariate distribution of these rainfall characteristics will be described through the Vine Copula method, which can account for dependence very flexibly among several variables. Parameterisation procedures still require more development to allow application over ungauged case of studies.
Towards A Global Landslide Forecast
Authors: Khan Sana , Kirschbaum Dalia B. , Stanley Thomas , Amatya Pukar , Emberson Robert
Published: March 2021

Numerical weather models are used in a variety of applications, including a growing body of landslide hazard assessment models. Heretofore, these applications have not included global landslide forecasts but this remains an important gap in better understanding the future spatiotemporal impact that landslides can have on populations and infrastructure. We explore the feasibility of using a precipitation forecast within the Landslide Hazard Assessment for Situational Awareness (LHASA) v2.0 model, which is designed to provide estimates of potential landslide hazard for rainfall triggers. Data on precipitation, soil moisture, and snow mass is available from NASA’s Goddard Earth Observing System Forward Processing product (GEOS-FP), which provides global scale products in both forecast and assimilation modes. These variables are incorporated into the LHASA Forecast model by replacing satellite rainfall estimates from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) with forecasted rainfall from GEOS-FP. The LHASA Forecast model also uses soil moisture and snow mass estimates from GEOS-FP rather than soil moisture and snow mass data from the Soil Moisture Active-Passive (SMAP) level 4 product. The LHASA Forecast model was run retrospectively at a daily scale with forecasted precipitation with up to a 3 day lead time. Results are compared with the LHASA v2.0 model that uses SMAP and IMERG data. Analysis of the LHASA Forecast system was conducted in several different ways. First, performance was assessed with categorical and continuous statics to determine how closely the forecasted probabilities match that of the LHASA v2.0 nowcast landslide probabilities. The outputs of LHASA v2.0 and LHASA Forecast are also compared for several high impact rainfall events that triggered landslides to determine the skill in identifying the potential high hazard areas. Preliminary results suggest that for large precipitation events (e.g. tropical storms), the same general hazard areas are identified; however, this can vary largely by geography and precipitation regime, owing to differences in spatial resolution and phase errors of the forecasted precipitation. This presentation outlines the preliminary work to address forecasted landslide hazard globally and discusses next steps towards improving landslide forecast skill.

 
Land Cover Change: Does it affect temperature variability?
Authors: Lagos Aristoklis , Sigourou Stavroula , Dimitriadis Panayiotis , Iliopoulou Theano , Koutsoyiannis Demetris
Published: March 2021

Changes in the land cover occur all the time at the surface of the Earth both naturally and anthropogenically. In the last decades, certain types of land cover change, including urbanization, have been correlated to local temperature increase, but the general dynamics of this relationship are still not well understood. This work examines whether land cover is a parameter affecting temperature increase by employing global datasets of land cover change, i.e. the Historical Land-Cover Change Global Dataset, and daily temperature from the NOAA database. We thoroughly investigate the temperature variability and its possible correlation to the different types of land-cover changes. A comparison is specifically made between the rate of temperature increase measured in urban areas, and the same rate measured in nearby non-urban areas.
Mapping of the environmental impact linked to clandestine sites for the final disposal of solid waste using remote sensors
Authors: García Cruzado Sergio , Delgado Ayala Daniela , Ramirez Serrato Nelly Lucero
Published: March 2021

Throughout Mexico, there is an alarming situation due to the contamination generated by solid waste, because many of the final disposal sites do not have adequate measures to avoid contamination, and that waste when decomposing or burning releases a large number of toxins that severely affect soil and air pollution. Also, not all the waste that is generated ends up in the final disposal sites. In Puebla city, 300 of the 1,700 tons of municipal solid waste generated per day are deposited daily in streets, vacant lots, rivers, and ravines, severely affecting the environment and the health of the nearest population. The study area is part of the metropolitan area of ​​the Puebla city, southeast of Mexico City, capital of the Mexican Republic. At an altitude of 2,137 meters above sea level, where most of the year it has a temperate subhumid climate and with rains from June to October. Around 2,322,686 people live within the study area, which represents 37.6% of the total population of Puebla state. In the study area, cases have been observed where solid waste, such as plastic, cardboard, etc. accumulates near kilns for the manufacture of bricks, which means the use of this waste as fuel for the kilns. Besides, a large number of old quarries have been found where construction material was extracted, which have become clandestine landfills, which accumulate a great diversity of waste, especially waste from construction. These cases were mostly found in the northern part of the city, where the main industrial zones are located. Therefore, the inadequate disposal of solid waste enhances the environmental impact, increases the vulnerability to present greater environmental pollution of the air and soil. Map the environmental impact factors and the location of misplaced waste and evaluated the correlation between them. This mapping will also serve to make zoning of places of priority attention towards management policies of the sites. For this, some environmental factors affected by the presence of solid waste in Puebla city were evaluated. Using remote sensing and geographic information systems, the water stress of the vegetation, change in land use, air pollution, soil temperature was evaluated, and the results were correlated with the location of the residues through an analysis of principal components. The result is a zoning map of priority attention areas. Where the highest areas correspond to a severe environmental impact, containing poorly located solid waste and coinciding with socioeconomic factors of high vulnerability.
Hydrodynamic behaviour of a semiarid Mediterranean watershed, under changing hydrological conditions
Authors: Palacios Cabrera Teresa Alejandra , Valdés Abellán Javier , Jódar Abellán Antonio , Alulema Rafael
Published: March 2021

ABSTRACT

The study analyzes the changes in the rainfall-runoff process as a result of land cover changes occurred between 1990-2018 in the Guadalest Reservoir basin with an area of 122.5 km2, using the model of the HEC-HMS model at daily scale and  to capture the complex hydrological dynamics based on GIS information . The purpose is to analyze the spatial-temporal evolution of the hydrological response in 12 sub-basins and the dynamics of land use/land cover changes for the years 1990, 2000, 2006, 2012 and 2018. 

The findings reveal a change in the type of sclerophyll vegetation (forests of Quercus (calliprinos, ilex, rotundifolia, suber, etc.)from 81.56% in the 1990 initial  stage, to natural grasslands by 81.55% in the 2018 stage; a decrease in agricultural areas and their conversion into coniferous forests and natural grasslands by approximately 60% in the same period; if exists an increase of coniferous forest to the detriment of the agriculture, implies that the evapotranspiration  will increase and the run-off will decrease   with an increase in runoff in principle but as time goes by it decreases bringing as a consequence a deficit in water supply. The results of land use  change detection between the years 1990-2018 were corroborated with the values of the curve numbers obtained.

The cyclical and trend analysis of the historical series of precipitation allows evidencing a five-year cycle and a decreasing trend from 1984 to 2018.

The HEC-HMS model implementation at a daily scale and GIS-based tools have proven to be useful in achieving the study objectives. Within the HEC-HMS, the SCS Curve Number model and the Muskingum method were suitable for solving the rainfall-runoff conversion and flood propagation equations, respectively.

The researching work debeloped  is intended to identify the impact derived by the anthropic action in the change of land use and Its vegetable coverage, and how this may impact on the evotranspiration, surface run-off, and the post hydropical drainage of The Guadalest Reservoir which will use for the Integral Management of the Basin. These findings provide to the water management planners very useful information about the effects of flash floods, which have human lives cost in the ravine basin studied in recent years.

 
KEYWORDS
Land use change, evapotranspiration, runoff, HEC-HMS hydrological model, basin, Mediterranean
Synthesis of palaeomagnetic datasets suggests that the geomagnetic field was persistently non-uniformitarian in the Devonian
Authors: van der Boon Annique , Biggin Andy , Thallner Daniele , Hounslow Mark , Nawrocki Jerzy , Wójcik Kristyan , Paszkowski Mariusz , Königshof Peter , de Backer Tim , Kabanov Pavel , Gouwy Sofie , Vandenberg Richard
Published: March 2021

The Devonian has long been a problematic era for paleomagnetism. Devonian data are generally difficult to interpret and have complex partial or full overprints. These problems arise from paleomagnetic data obtained from both sedimentary and igneous rocks. As a result, the reconstruction of motions of tectonic plates is often troubling, as these rely on apparent polar wander paths constructed from Devonian paleomagnetic poles. Also the geomagnetic polarity time scale for this time period is poorly constrained. Paleointensity studies suggest that the field was much weaker than the field of today, and it has been hypothesised that this was accompanied by many polarity reversals (a hyperreversing field). We review studies on Devonian paleopoles, magnetostratigraphy and paleointensity. We tentatively suggest that the field during the Devonian might have been so weak and perhaps of a non-dipolar configuration, that obtaining reliable paleomagnetic data from Devonian rocks is extremely difficult.  In order to push forward the understanding of the Devonian field, we emphasise the need for studies to provide fully accessible data down to specimen level demagnetisation diagrams. Incorporating all data, no matter how complex or bad they might seem, is the only way to advance the understanding of the Devonian magnetic field. Recent paleointensity studies appear to suggest that the Devonian and Ediacaran were both extreme weak field intervals. For the Ediacaran, it has been hypothesised that the field had an impact on life on earth. A fundamentally weak and perhaps non-dipolar field during the Devonian might have had an influence on evolution and extinctions. As there is a large number of biological crises in the Devonian, we here pose the question whether the Earth’s magnetic field was a contributing factor to these crises. New independent evidence from the Devonian-Carboniferous boundary suggests that the Hangenberg event was caused by increased UV-B radiation, which is in line with a weak magnetic field.
Crystallization via non-classical pathways: Nanoscale imaging of mineral surfaces 
Authors: Putnis Christine V. , Wang Lijun , Ruiz-Agudo Encarnación , Ruiz-Agudo Cristina , Renard François
Published: March 2021

The advancement in analytical imaging techniques, including atomic force microscopy (AFM) and scanning and transmission electron microscopies (SEM and TEM), has allowed us to observe processes occurring at mineral surfaces in situ at a nanoscale in real space and time and hence giving the possibility to elucidate reaction mechanisms. Classical crystal growth theories have been established for well over 100 years and while they can still be applied to explain crystal growth in many growth scenarios, we now know that these models are not always an accurate description of the mechanism of all crystal/mineral growth processes, especially where nanoparticle formation is observed. Consequently there is a current challenge at the forefront of understanding crystal/mineral growth mechanisms. This work describes experimental observations of non-classical crystallization processes at the nanoscale. Using AFM as well as SEM and TEM imaging, we demonstrate that many minerals commonly grow by the attachment of nanoparticles on an existing mineral surface, often resulting from the coupling of dissolution of a parent phase and the precipitation of a new product mineral. Through varied examples of crystal/mineral growth, including calcite and other carbonates, barite, brucite, and apatite, we define the importance of the mineral-fluid interface and the aqueous fluid interfacial (boundary) layer in the control of crystal growth. Whether a crystal will grow by classical monomer attachment resulting in step advancement or by the formation, aggregation and merging of nanoparticles, will be controlled by the aqueous fluid composition at the mineral-fluid interface. The processes described also allow for the development of porosity within the new mineral and hence have important consequences for fluid movement and element mobility within the Earth. Additionally an understanding of natural mineral growth has implications for geomimetic applications for the manufacture of functional engineered materials.
Spatial variability and changes in storage-discharge relationships of crystalline catchments: implications for resilience and water resources management
Authors: Abhervé Ronan , Roques Clément , Longuevergne Laurent , Louaisil Stéphane , de Dreuzy Jean-Raynald , Aquilina Luc
Published: March 2021

While it is well understood and accepted that climate change and growing water needs affect the availability of water resources, the identification of the main physical processes involved remains challenging. It notably requires to filter interannual to interdecadal fluctuations and extreme events to isolate the underlying trends. Metropolitan areas are specifically subject to growing pressures because of the significant and increasing demand, combined with the strong anthropization of land uses.

The Meu-Chèze-Canut catchment supplies the city of Rennes with drinking water (680 km² - 500 000 users, Brittany, France). In this field laboratory, we explore the dynamics of the water cycle and water resources availability. In this context, water supply is mostly coming from reservoir storage for which levels shows a medium-term vulnerability in response to frequent relatively dry years. Based on retrospective data analysis, we describe the relationship between climatic forcing (precipitation, temperature) and water availability (aquifer storage, river discharge and reservoir storage) in different parts of the catchment that are characterized by distinct lithological and topographical settings. We then evaluate the resilience of both surface and groundwater resources, their past evolution and their resilience to climate change and increasing societal needs.

Water resources availability in these catchments relies on two geological formations with distinct hydrodynamics properties: the Armorican sandstone and Brioverian schist. To assess the resilience of the system, we specifically analyzed the relationships between monthly effective precipitation and stream discharge within nine sub-catchments over the past 30 years. We observe annual hysteresis relationships - that is, a time lag between precipitation and discharge highlighting the capacity of the landscape to temporarily store water - with significant variability in shapes across the catchments. We argue that topographic and lithological factors play key roles in controlling this variability through their impacts on subsurface storage capacity and characteristic drainage timescales. We propose perspectives based on the complementary use of calibrated groundwater models to leverage these results and provide adaptive water management strategies.
Effect of surface heterogeneity on hyper-resolution simulation of soil moisture
Authors: Zeng Junhan , Yuan Xing , Ji Peng
Published: March 2021

Due to the land surface complexity, soil moisture immensely varies both spatially and temporally. However, the combined effects of land surface complexity and key hydrological processes (e.g., subsurface lateral flow) on fine-scale soil moisture heterogeneity remain elusive due to the scarcity of observations. Benefit from improvements in hyper-resolution land surface modeling, it provides an unprecedented opportunity to investigate the fine-scale soil moisture heterogeneity over a large region. Here, we use the Conjunctive Surface-Subsurface Process model version 2 (CSSPv2), which considers subsurface lateral flow, to perform hyperresolution (100-m) simulations over ten selected regions with different climate. We find that the heterogeneities of vegetation, soil texture, precipitation or their combinations increase soil moisture heterogeneity significantly (p<0.01). If only the topography heterogeneity presents, subsurface lateral flow increases the soil moisture heterogeneity significantly (p<0.01). However, the effect of subsurface lateral flow has been reduced by combining topography heterogeneity with other surface heterogeneities, with a few regions showing decreased soil moisture heterogeneity mainly because of the combined effect of subsurface lateral flow and soil texture heterogeneity. This study suggests that soil texture heterogeneity does not necessarily interact synergistically with physical processes (e.g., subsurface lateral flow) for increasing soil moisture heterogeneity, although they can increase the heterogeneity separately.
The role of small-scale topographic features on inundation dynamics: potential impacts on large-scale investigations
Authors: Domeneghetti Alessio , Leonardi Antonio , Wing Oliver E. J. , Carisi Francesca , Brath Armando
Published: March 2021

The execution of large-scale (i.e., continental or global) hydraulic modeling is nowadays a reality thanks to the increasing computational capacity, data availability, as well as understanding of essential physical dynamics. Such achievements are typically associated to a compromise in terms of model resolutions (the finer being of few tens of meters, with a coarsened representation of the terrain) and, thus, accuracy on representing the topographic peculiarities of the flood-prone areas. Nevertheless, the experience gained observing the dynamics of past inundations highlights the role of small-scale topographic features (e.g., minor embankments, road deck, railways, etc.) in driving the flow paths. Recent advances on automated identification of flood defense from high resolution digital elevation model paved the way to include hydraulically relevant features (e.g., main levees) while preserving the model resolution suitable for large-scale applications (Wing et al, 2020).
The present study extends this approach to flood-prone areas by investigating how the automatic detection of minor topographic discontinuities can enhance the estimation of flood dynamics of large-scale models. Taking advantage of high-resolution topographic data (i.e., 1-2 m) the approach automatically detects hydraulically relevant features and preserves their height while coarsening the resolution of the terrain used into the hydraulic model. The impact of such approach on the inundation dynamic is tested referring to three different case-studies that recently experienced riverine flooding: Secchia and Enza rivers (2014, 2017, respectively; Italy), Des Moines (Iowa, USA). The results confirm the relevance of small-scale topographic features, which, when considered, ensure a high correspondence to observations and local models. The element of strength of the presented approach is that such performances are ensured without requiring the adoption of high grid resolutions, and thus, not affecting the overall computational costs.
Mapping plastic greenhouses with satellite imagery in Valparaiso, Chile: development of a new methodology through data cloud platform
Authors: Aguirre Ignacio , Lozano-Parra Javier
Published: March 2021

During the last decades, there has been a strong increase around the globe in the use of plastic greenhouses (PGs) which respond to the need to provide better water security, overcome adverse weather events, or elude pests. The central valley of Chile has not been an exception and the surface covered by greenhouses has also experienced an increase over the years. In the Valparaiso region, the surface increased from 1122 ha to 1180 ha throughout the decade 1997-2007. However, on one hand, there has not been a new PGs census since 2007 and, on the other hand, its spatial distribution has not ever been mapped. Considering that agriculture in this region employs more than 60000 people and moves 4% of regional GPD, this information should be available to be included in land planning and to be incorporated into hydrological, economic, and food security models. To overcome this, we propose a new method for monitoring the variations of the surface covered by PGs based on the intersection of normalized difference indexes and areas excludes by masks. For this, free Landsat 8 multi-temporal cloud-free images were used, from which five indexes were obtained (Modified Soil-adjusted Vegetation Index, Temperature Brightness Index, Normalized Difference Vegetation Index - Green, Normalized Difference Built-up Index, and Plastic Surface Index). These indexes were then reclassified in binary form and added up. Finally, urban areas and high slope zones were excluded to obtain the final output. This procedure was run in Google Earth Engine, which allowed easy replication and automation for longer time series or in other study sites. Results proved this methodology was able to successfully discriminate the 86% of PG, which suppose 1410 ha. This surface is consistent with the agricultural census developed in 2007 and with the increase of more than 900 subsidies granted by the government for installing PGs. Its performance also supports our confidence to discriminate PGs in areas with different land covers such as reservoirs, rural areas, open crops, bare soil, and roads. Future studies will allow us to estimate the surface of plastic greenhouses in Chile, mapping its spatial distribution in all the country, and monitor changes over time.
A novel identification and tracking method of weather-relevant 3D Potential vorticity streamers
Authors: Fischer Christoph , Schömer Elmar , Fink Andreas H. , Riemer Michael , Maier-Gerber Michael
Published: March 2021

Potential vorticity streamers (PVSs) are elongated quasi-horizontal filaments of stratospheric air in the upper troposphere related to, for example, Rossby wave breaking events. They are known to be related to partly extreme weather events in the midlatitudes and subtropics and can also be involved in (sub-)tropical cyclogenesis. While several algorithms have been developed to identify and track PVSs on planar isentropic surfaces, less is known about the evolution of these streamers in 3D, both climatologically but also for a better understanding of individual weather events. Furthermore, characteristics of their 3D shape have barely been considered as a predictor for high impact weather events like (sub-)tropical cyclones.

We introduce a novel algorithm for detection and identification of PVSs based on image processing techniques which can be applied to 2D and 3D gridded datasets. The potential vorticity was taken from high resolution isentropic analyses based on the ERA5 dataset. The algorithm uses the 2 PVU (Potential Vorticity Unit) threshold to identify and extract anomalies in the PV field using signed distance functions. This is accomplished by using a stereographic projection to eliminate singularities and keeping track of the reduced distortions by storing precomputed distance maps. This approach is computationally efficient and detects more interesting structures that exhibit the general behavior of PVSs compared to existing 2D techniques.

For each identified object a feature vector is computed, containing the individual characteristics of the streamers. In the 3D case, the algorithm looks at the structure en bloc instead of operating individually on multiple 2D levels. This also makes the identification stable regarding the seasonal cycle. Feature vectors contain parameters about quality, intensity and shape. In the case of 2D datasets, best-fitting ellipses computed from the statistical moments are regarded as a description of their shape. For 3D datasets, recent visualizations show that the boundary of these structures could be approximated by quadric surfaces . The feature vectors are also amended by tracking information, for example splitting and merging events. This low-dimensional representation serves as base for ERA5 climatologies. The data will be correlated with (sub-)tropical cyclone occurrence to spot useful and novel predictors for cyclone activity and preceding Rossby Wave Breaking events.

Overall, this new type of PVS identification algorithm, applicable in 2D or 3D, allows to diagnose the role of PVS in extreme weather events, including their predictability in ensemble forecasts.