bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of scientific literature on the use of globally available remote sensed data products for distributed hydrological modelling.
Authors: Ali M. Haris , Popescu Ioana , Jonoski Andreja , Solomatine Dimitri
Published: March 2022

To assess the capability of globally available satellite or remote sensed data products (GASRSDP) for distributed hydrological modelling and expedite their widespread uptake require a comprehensive knowledge-base related to their efficiency, temporal and spatial specifications and extents. Moreover, it is important to assess their performance in setting up hydrological models, their use as forcing data of models or for calibration, validation or evaluation of the model itself, along with an assessment of their limitation.

Hydrological models are the key tools for sustainable water management decision-making process. In order to capture the spatio-temporal variation in hydrological fluxes, the input data and representation of physical parameters in hydrological models plays an important role in their credibility. Models require rich amounts of data, which is mostly not readily available in data scare regions. The remotely sensed or satellite derived globally available data products are a vast and rich source of data with continuous addition to daily inventory. This data is widely in use for setting up hydrological models, their calibration, validation, evaluation and improvement.

Each day new data products are being released by different agencies. The scientific community is continuously mentioning the use of these data products in scientific articles. Present article does a systematic literature review of the articles over the last 5 years (2016 to 2021) in order to analyse the use of remote sensed / satellite globally available data products for detailed distributed hydrological modelling so that the progress in this context can be ascertain and future directions can be established. The review process was started by sourcing 179 articles from Scopus and 206 articles from Web of Science. After excluding the common and out of scope articles, the full analysis has been performed on about 100 articles. We conclude that the use of GASRSDP for the hydrological modelling of macro-scaled catchments has extensively explored and their performance is being evaluated by many authors while their worth for setting up physically based distributed hydrological model for catchment at meso-scale still need exploration, evaluation and assessments.
Remote sensing tools for monitoring supraglacial debris cover features and their fluctuations
Authors: Racoviteanu Adina E.
Published: March 2022

High mountain environments are characterized by highly glacierized, complex, dynamic topography, often exhibiting a heterogeneous debris mantle comprising ponds and exposed ice cliffs, associated with differing ice ablation rates. These has been an increased interest in understanding these supraglacial surface features, i.e., the formation and expansion of supraglacial ponds and implications for glacier hydrology and glacier-related hazards, notably glacier lake outburst flood (GLOF) events. Until recently, supraglacial debris surfaces and their features have received less attention compared to mapping of debris-cover extents due to methodological challenges posed by their ephemeral nature. As a result, they remain poorly quantified in global glacier databases including the Global Land Ice Measurements from Space (GLIMS) and the Randolph Glacier Inventory (RGI). Furthermore, remote sensing studies used to generate these datasets generally rely on traditional “whole pixel” image classification techniques, which do not allow decomposition of a pixel into constituting materials. In this talk I summarize the state-of-art remote sensing techniques to characterize supraglacial features, such as debris material, ice cliffs, supraglacial ponds and vegetation. I particularly highlight the potential of spectral unmixing routines multi-temporal Landsat and Sentinel data combined with high-resolution multispectral imagery to quantify the composition of debris cover at multiple scales across the Himalaya with an emphasis on supraglacial ponds. I summarize the current strengths and limitations of these methods and discuss steps needed such as automation and open-source tools.
Mapping, monitoring and modelling past, present and potential future channel changes in an Alpine River system in Austria
Authors: Pamminger Jakob , Pöppl Ronald
Published: March 2022

A flooding event in 2014 caused a prominent bank erosion along the Salza River in Styria, Austria. The bank became instable and its further development was uncertain, which raised concern for further progressing bank erosion at this location, as well as in other sections in the entire studied river reach. The major aim of this study was to monitor bank erosion rates at this specific bank erosion hotspot as well as to survey the entire study area for past, present and potential future channel changes. Past river changes have been mapped using historical maps and orthophotos. For a geomorphological evaluation of the current system state field mapping has been applied using the approach developed by Wheaton et al. 2015. Bank erosion monitoring was done by using erosion pins and photogrammetry, while potential future channel changes have been assessed via landscape evolution modelling using CAESAR-Lisflood developed by Coulthard et al. 2013.

Historical map (1678 - 1887) and orthophoto (2004 - 2017) analyses have shown that the Salza River has altered noticeably throughout the past through anthropogenic impacts and natural processes, with two prominent natural changes in the recent years one being the prominent bank erosion which initiated this study. Mapping the river course in the field in May 2017 has shown, that the most common in-channel river shapes are in descending order transition zones, planar, concave and convex. Monitoring the bank erosion hotspot using erosion pins has shown a mean change of the whole bank of -1.63 cm from 15.06.2017 - 11.07.2017. The photogrammetric approach, a 2D distance analysis to the erosion hotspot for the timeframe 06.05.2017 - 11.06.2018, resulted a mean change of roughly -2 m for the whole bank, while a 2.5D volume change analysis for the same timeframe has shown an eroded volume of 319 m³. Modelling the Salza River using four different discharge scenarios with the landscape evolution model CAESAR-Lisflood has shown four potential hot spot areas for a lateral shift of 20 m to 130 m from 2019 to 2050.
Thermolab: a thermodynamics laboratory for non-linear transport processes in open systems
Authors: Vrijmoed Johannes C. , Podladchikov Yury Y.
Published: March 2022

We developed a numerical thermodynamics laboratory called “Thermolab” to study the effects of the thermodynamic behavior of non-ideal solution models on reactive transport processes in open systems. The equations of state of internally consistent thermodynamic datasets are implemented in MATLAB functions and form the basis for calculating Gibbs energy. A linear algebraic approach is used in Thermolab to compute Gibbs energy of mixing for multi-component phases to study the impact of the non-ideality of solution models on transport processes. The Gibbs energies are benchmarked with experimental data, phase diagrams and other thermodynamic software. Constrained Gibbs minimization is exemplified with MATLAB codes and iterative refinement of composition of mixtures may be used to increase precision and accuracy. All needed transport variables such as densities, phase compositions, and chemical potentials are obtained from Gibbs energy of the stable phases after the minimization in Thermolab. We demonstrate the use of precomputed local equilibrium data obtained with Thermolab in reactive transport models. In reactive fluid flow the shape and the velocity of the reaction front vary depending on the non-linearity of the partitioning of a component in fluid and solid. We argue that non-ideality of solution models has to be taken into account and further explored in reactive transport models. Thermolab Gibbs energies can be used in Cahn-Hilliard models for non-linear diffusion and phase growth. This presents a transient process towards equilibrium and avoids computational problems arising during precomputing of equilibrium data.
Dynamic risk scenarios for single and multi-hazards in the Global South: Nairobi, Istanbul and Kathmandu
Authors: Malamud Bruce D. , Šakić Trogrlić Robert , Hussain Ekbal , Thompson Harriet , Yahya Menteşe Emin , Öner Emine , Yolcu Aslıhan , Mwangi Emmah , Gill Joel
Published: March 2022

Single natural hazards, multi-hazards, and anthropogenic processes all contribute to dynamic risk due to the changing nature of the hazard, exposure, and vulnerability over time. Here we discuss the development of dynamic risk scenarios for single and multi-hazards, including multi-hazard interrelationships, in the context of three urban areas, Istanbul, Kathmandu, and Nairobi, all foci of the UK GCRF funded “Tomorrow’s Cities” Research Hub. We first do systematic overviews of multiple sources of evidence (academic and grey literature, online media, social media) to produce a profile of single hazards and multi-hazard interrelationships for each urban area, from which we produce dynamic risk scenarios. Then, we further developed dynamic risk scenarios through co-production with relevant local hazard stakeholders in facilitated workshops and semi-structured interviews in Nairobi and Istanbul. The dynamic risk scenarios include multiple types of single hazards, three different hazard interrelationships (i.e., triggering, increased probability, and compound hazards) and anthropogenic processes. These dynamic risk scenarios are relevant for short-term considerations (e.g., days or weeks, such as an earthquake triggering landslides and blocking rivers) or longer-term (such as climate change influencing the hazard, or anthropogenic processes of urban growth influence the hazard, exposure, and vulnerability). Examples of challenges identified by stakeholders include governance-related issues, such as siloed approaches to hazards which are often single-hazard focused, lack of enforcement of regulations, translation of planning to implementation, centralised policy-making, needs beyond electoral cycles, lack of financial and human resources, and disconnect between scientific and policy-making communities. Other challenges stakeholders identified include a lack of existing data and research in their region on multi-hazard interrelationships, anthropogenic processes and risk, and other components that make up dynamic risk scenarios. Opportunities identified by stakeholders include increased awareness of the factors that might influence risk dynamically in their urban region and integration of these factors into existing urban regeneration project planning. As identified by local stakeholders, these scenarios have a vast array of potential benefits for disaster risk management in their cities, especially in terms of enhanced preparedness and risk-informed planning.
HF scintillation in the high-latitude ionosphere
Authors: Perry Gareth , Lamarche Leslie , Liu Binjie
Published: March 2022

In this presentation we will report on the first results of a multi-year study of high frequency (HF; 3-30 MHz) radio scintillation in the North American sector of the high-latitude ionosphere. We will focus on HF signals collected by the Radio Receiver Instrument (RRI) onboard the CASSIOPE spacecraft (also known as Swarm-E) during coordinated experiments between RRI the Super Dual Auroral Radar Network (SuperDARN) systems located at Saskatoon, Rankin Inlet, and Clyde River (all in Canada). The investigation's goals are to use the RRI data from the SuperDARN experiments to specify the nature of HF scintillation in the region, diagnose scintillation caused by ionospheric irregularities and distinguish it from scintillation resulting from HF radio propagation effects, identify geophysical phenomena responsible for HF scintillation, and ascertain the relationship (if any) between HF scintillation and backscatter measured by the SuperDARN systems.
The coastal protection function of Managed Realignments – a review of the available evidence
Authors: Schuerch Mark , Mossman Hannah , Christie Elizabeth , Moore Harriet
Published: March 2022

Globally, increased coastal flooding is considered as one of the main consequences of climate change in coastal zones. To mitigate coastal flood risks nature-based solutions that complement traditional engineering approaches are increasingly considered as a key adaptation strategy. A widespread form of a coastal nature-based solution is managed realignment (MR), i.e. the inland realignment of coastal defences and the creation of coastal ecosystems (mostly saltmarshes) in the intervening space. However, these approaches involve giving-up previously reclaimed, now agricultural, land to the sea, often resulting in low local-community support. This is not only because coastal retreat may conflict with community values and interests, but also due to low public trust in the success of nature-based adaptation.

Here, we show that the available evidence underlining the coastal protection function of MRs is primarily based on research from natural, mostly large, saltmarshes, where wave heights during storms and tidal surges are effectively attenuated, while available evidence for the effectiveness of MRs is very limited. This means that often local communities have no conclusive evidence of the schemes’ actual flood-risk reduction potential. Indeed, the little available evidence on the coastal protection function of MRs suggests that only MRs exceeding a particular size may be effective in reducing coastal flood risks, hence local community support is becoming even more important. We therefore propose a novel co-production process for the planning and implementation of MRs, where coastal communities are involved in the production of knowledge to establish the coastal protection function of MRs.
Improving early warning of droughts near onset and middle of a growing season
Authors: Shukla Shraddhanand , Turner William , Husak Greg , McEvoy Daniel , Tinni Seydou , Alkhalil Adoum , Ali Abdou , Mamne Bako , Sanda Ibrah , Grace Kathryn , Cherrington Emil , Muench Rebekke
Published: March 2022

Early warning of drought is crucial for mitigation of the most adverse impacts of water and food insecurity to lives and livelihoods. Recent advances in routine production (i.e., weekly) and open access to NMME SubX—subseasonal climate forecasts—provide an unprecedented opportunity to improve drought early warning near the onset and middle of the crop-growing season. Near the onset of a season, subseasonal precipitation forecasts have the potential to provide early indication of delay in rain onset, which, as shown in a recent study (Shukla et al., 2021, PLOS ONE), can be a reliable indicator of agricultural drought development. This is particularly relevant for some of the most food-insecure regions in East Africa. Additionally, subseasonal forecasts have the potential to improve drought forecasting during the middle of the season—several months before the harvests—when they are used in combination with to-date observations. Integration of near-real-time observations with subseasonal climate forecasts can enhance drought detection capabilities by leveraging the skill that is derived from initial conditions (as of middle of the season) and complementing it with the skill of subseasonal climate forecasts. Here, we first describe how onset of the rainy season is a reliable indicator of agricultural droughts. The results indicate that in the administrative units in sub-Saharan Africa, which  have the highest risk of acute food insecurity, a delay of about 20 days in the rainy season onset can double the probability of agricultural droughts. We then describe the results of an analysis examining the performance of subseasonal climate forecasts in identifying the timing of the onset of the rainy season in those administrative units. Next, we describe a SERVIR-AST-supported project, which uses subseasonal climate forecasts to develop a West Africa-focused water-deficit forecasting system in collaboration with AGRHYMET, primarily  for agropastoral usage. Here, we make  use of a widely used crop water balance model, the Water Requirement Satisfaction Index (WRSI), to generate improved forecasts of crop water stress, and hence, crop production outcomes, during the middle of the rainy season in West Africa (June through September). We compare the performance of these forecasts with the forecasts generated using climatology only. Finally, we briefly describe how these subseasonal climate forecasting products are being disseminated, communicated, and used in the focus regions.
Robotics for raw material: the importance of data collection in the design of the appropriate equipments for exploring abandoned mines 
Authors: Tucci Emanuele , Ruggeri Rudi
Published: March 2022

In Europe there are a lot of abandoned mines that could be reopened with the use of innovative techniques; this is one of the aims of the ROBOMINERS project.

The use of the mining robots will especially be relevant for mineral deposits that are small or difficult to access.

Knowledge of type and dimensions of this mines is fundamental aiming to design and plan on-site tests of this robot.

In this article are explained the selection criteria of some mines in Italy among all the abandoned mines available at national level that could be investigated with robot miner.

In Italy there are about 3000 abandoned mining sites. Among these, eleven sites distributed throughout the national territory were selected.

Starting from a national public database containing all the abandoned mining sites and using an ad hoc KPI-matrix, some pilot sites were selected that met the required features.

The selection was carried out, according to the objectives of the project, preferring mining sites in urban areas, located at great depths or considered not economically relevant by traditional mining.

Among these, preference was given to metal-bearing ore deposits that could be better excavated with robot.

In order to characterize the selected sites, the following data have been collected for every site:

Geographic informations;

Historic time range of exploration ;

Deposit type;

Commodities available;

Main host rock.

Data collection was performed starting from the national database and subsequently integrating the informations with further data from bibliographic sources.

Data collection for the selected mines is of primary importance because the type of deposits can affect the correct functioning of the robot.

In order to design robot tools correctly is therefore essential to know in advance the geographic and geological features of the mine in order to carry out on-site tests.
Flash flood susceptibility modelling using advanced machine learning algorithms. Case study of the Rheraya watershed,Morocco
Authors: Elghouat Akram , Algouti Ahmed , Algouti Abdellah
Published: March 2022

A flash flood is a very rapid and surprising rise in water level affecting any part of a watershed. It is considered to be one of the most dynamic natural disasters for which action should be taken to minimize economic damage, negative effects and consequences. Flash flood susceptibility maps are important for a range of applications, including land use planning and the development of risks reducing strategies and early warning systems.

In the present study, the Rheraya watershed in Morocco was chosen to develop the modeling of flash flood susceptibility and subsequently to detect the areas most vulnerable to flooding.

For the development of this work, new advanced machine learning algorithms were adopted. Thus, four models were applied: Naïve Bayes (NB), K Nearest neighbor (KNN), Extreme Gradient Boosting (XGB) and Random Forest (RF). Twelve independent topographic, climatic and geo-environmental variables (elevation, slope, aspect, curvature…) and one dependent variable (flash-flood inventory) were used as inputs to our flash flood sensitivity models.

The results showed that RF is the most optimal model with an area under the curve (AUC) value of 0.86. The other AUC values of the models, i.e., XGB, NB, KNN, were 0.85, 0.76, 0.76 respectively. In the optimal model, areas with very high susceptibility to flash floods are well localized and specific, which will play an essential role in the planning and implementation of flood mitigation strategies in the region.

Keywords: Flash floods, Rheraya watershed, Machine Learning, GIS, remote sensing.
UAV-based precision mapping techniques for disease and pest identification
Authors: Mejia-Aguilar Abraham , Barthel Dana , Chuprikova Ekaterina , McLeod Ben Alexander , Trenti Massimiliano , Kerschbamer Christine , Prechsl Ulrich , Janik Katrin
Published: March 2022

Mountain agriculture is a vital social-economic activity in Europe, including the alpine Province of South Tyrol, Italy. Here, apple orchards and vineyards are extensively cultivated. Besides the difficulty to cultivate in mountain terrain (steep slopes, difficult accessibility, extreme weather conditions), the plants are exposed to a combination of biotic and abiotic stresses that can result in diseases caused by pathogens. It results in the loss of the yield and quality of products, economic losses, reducing food security with severe ecological impacts, and affects many ecosystem services (such as agrotourism).

This work presents a proximal sensing technique based on an unmanned aerial platform with a payload consisting of multi and hyperspectral optical cameras. Such platforms are suitable to access rugged terrains in a short time to map the presence of diseases and pests, as well they provide imagery for the optimal management of farms. We study three different experiments: apple orchard, vineyard, and forestry, observing Apple proliferation, Flavescence dorée, and Pine processionary, respectively. We aim at a non-invasive and non-destructive method to monitor plant diseases in the direction of high-precision mapping agriculture applications by exploring supervised classification methods based on ground data to distinguish healthy and unhealthy trees.
A Discontinuous-Galerkin approach to model non-classical nonlinearity observed from lab to global scales
Authors: Niu Zihua , Gabriel Alice-Agnes , May Dave , Sens-Schönfelder Christoph , Igel Heiner
Published: March 2022

Under dynamic perturbations, it has been observed that materials like sedimentary rocks show complex mechanical behaviors. They include the simultaneous dependence of the elastic moduli and attenuation on strain at the same time scale of the perturbations, as well as the conditioning and recovery of the elastic moduli that may happen at time scales that are much larger. The latter cases were recently referred to as non-classical nonlinearity. Aside from laboratory experiments, comparable observations of the non-classical nonlinearity have been made in the field over the past two decades with the development of long-term continuous monitoring of the velocity field inside the Earth using methods such as ambient noise interferometry.

 

A variety of mathematical models that can potentially quantify the non-classical nonlinearity have already been proposed, e.g., the Damage–Breakage Rheology Model, the Internal Variable Model and the Godunov–Peshkov–Romenski model. However, implementing them in numerical schemes suitable to reproduce nonlinear effects in wave propagation on the local, regional, or global scale is challenging. This can be of interest for constraining a more realistic dynamic rheology for the Earth with the field observations.

 

In this work, wave propagation in different non-classical nonlinear models is implemented in FEniCS using the discontinuous Galerkin (DG) method in 1D. Behaviors of the different models are systematically studied and quantitatively compared against measurements. This work lays the foundation for an extension to the simulation of 2D/3D wave propagation in the Earth on the large-scale DG simulation frameworks, e.g., SeisSol and ExaHyPE.
Greenhouse gas fluxes and nutrients availability in Portuguese drylands and their sensitivity to climate change
Authors: Serôdio Joana , Férnandez-Alonso María José , Fangueiro David , Freitas Helena , Durán Jorge , Rodríguez Alexandra
Published: March 2022

Drylands are unique and diverse ecosystems that occupy more than 40% of the terrestrial surface. These areas are inhabited by more than 35% of the world population. In the case of Portugal, drylands represent 37% of its territory. In many areas worldwide, climate change (CCh) is increasing the aridity leading to an expansion of drylands. However, the joint effects of different CCh drivers on the features, functions, and services of drylands remain largely unknown. Further, there is large uncertainty on how CCh-driven alterations in biotic and abiotic soil attributes will feedback CCh through greenhouse gas (GHG) fluxes.

This study aims to assess (1) the soil-atmosphere GHG exchange and soil nutrients availability and (2) their response to different CCh scenarios along an aridity gradient made up of 8 humid, arid, and semiarid-natural parks in Portugal. In winter 2019, we installed open top chambers and rainfall shelters (both separately and combined) in 24 plots to simulate the forecasted increase in temperatures (~3 °C) and reduction in precipitation (~35%), respectively. Since then, seasonal field campaigns to collect gas and soil samples as well as to measure in situ nutrients availability have been performed.

Our first data show that soil organic matter and nutrients (N and P) availability decrease along the aridity gradient whereas methanogenesis seems to be constrained along the gradient and there is not a clear response from other GHG to the aridity gradient. Soil respiration was mainly driven by the seasonal variability of soil moisture and temperature. Finally, the different CCh scenarios had their biggest effect on variables with faster turnover and the response of GHG fluxes to different CCh scenarios varied among sites, which highlights the importance of considering other site-dependent ecosystem features when trying to assess the effects of climate change on GHG fluxes.
Temporal trends of radio-cesium concentration in the marine environment after the Chernobyl and Fukushima Dai-ichi Nuclear Power Plant accidents
Authors: Takata Hyoe
Published: March 2022

European seas such as, Baltic, North, and Norwegian Seas are mostly affected areas by the accident at the Chernobyl nuclear power plant (CNPP) in 1986. Since Fukushima Daiichi nuclear power plant (FDNPP) is located on the coast of the North Pacific Ocean in east Japan, its accident resulted in the release of large amounts of radiocesium to the surrounding coastal marine environment (i.e. the waters off Fukushima and neighboring prefectures). The temporal change of radiocaesium concentration in seawater after both accidents was largely dependent on their submarine topography: The Baltic Sea is a semi-closed basin, while Norwegian and North Seas, and the waters off Fukushima and neighboring prefectures is directly connected to open-water. Although concentration of radioacesium (137Cs) in the surface water of the Baltic Sea (central part) continuously decreased, the values in 1996, ten years after the accident, were even higher than pre-accident level in 1985. On the other hand, in the waters off Fukushima and neighboring prefectures 137Cs concentrations in 2020, nine years after the accident, are approaching the pre-accident levels of 2010. The quick decrease is attributable to the intrusion or mixing of water masses with low 137Cs.
Uncertainty assessment with Bluecat: Recognising randomness as a fundamental component of physics
Authors: Montanari Alberto , Koutsoyiannis Demetris
Published: March 2022

We present a new method for simulating and predicting hydrologic variables and in particular river flows, which is rooted in the probability theory and conceived in order to provide a reliable quantification of its uncertainty for operational applications. In fact, recent practical experience during extreme events has shown that simulation and prediction uncertainty is essential information for decision makers and the public. A reliable and transparent uncertainty assessment has also been shown to be essential to gain public and institutional trust in real science. Our approach, that we term with the acronym "Bluecat", assumes that randomness is a fundamental component of physics and results from a theoretical and numerical development. Bluecat is conceived to make a transparent and intuitive use of uncertain observations which in turn mirror the observed reality. Therefore, Bluecat makes use of a rigorous theory while at the same time proofing the concept that environmental resources should be managed by making the best use of empirical evidence and experience and recognising randomness as an intrinsic property of hydrological systems. We provide an open and user friendly software to apply the method to the simulation and prediction of river flows and test Bluecat's reliability for operational applications.
From datasets to decisions – a repeatable workflow for groundwater decision support
Authors: Fienen Michael , Corson-Dosch Nicholas , White Jeremy , Leaf Andrew , Hunt Randall
Published: March 2022

Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real-world application of delineating risk-based (probabilistic) sources of water to abstraction wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking, and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries to build the model. The workflow performs ensemble-based history matching and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing areas that contribute recharge to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems. The specific data are available in the United States but the tools can be applied to similar datasets worldwide.
A Global Perspective on Martian Meteoric Mg+
Authors: Crismani Matteo , Tyo Robert , Schneider Nicholas , Plane John , Feng Wuhu , Villanueva Geronimo , Jain Sonal , Deighan Justin
Published: March 2022

Interplanetary dust particles, liberated from the surfaces of comets and asteroids, are ubiquitous in interplanetary space within the solar system. These particles travel at orbital velocities and ablate upon entry into planetary atmospheres, where they are the sole explanation for high altitude atmospheric metal layers. On Earth, such layers inform us of the dynamics of the upper atmosphere, and we use the abundance of relative species to investigate the origin of these particles from various potential sources (Jupiter family comets, asteroids, etc.). Since the discovery of atmospheric Mg+ at Mars in 2015, there have been almost continuous observations of this layer in a variety of seasons, local times, and latitudes. Here we present the most comprehensive set of observations of the persistent metal ion layer at Mars, constructing the first grand average maps of metal ions species. Such maps can be compared to current and future modeling efforts, which attempt to track mesospheric transport, chemistry and interplanetary dust particle sources. This work confirms some previous model predictions and observations, such as the relatively long lifetime of Mg+, but also presents counter-intuitive results, such as a paucity of Mg+ ions in the northern hemisphere during Northern Winter in an apparent correlation with dust aerosols. Previous discrepancies between model predictions and metal ion observations led to the development of a novel nucleation scheme for mesospheric clouds, and we revisit these ideas on a global and seasonally varying scale. Overall, this represents the broadest investigation of meteoric metal ions, summarizes the first order behavior and outlines new model challenges for the future.
Exploration of spectral energy from marine and modeled magnetic anomalies
Authors: Garcia-Reyes Andreina , Dyment Jérôme
Published: March 2022

The spectral method has been widely used in various branches of science since it simplifies the analysis of periodic signals. In the case of geophysics, Fourier transform is used to decompose the signal into different wavelengths, and to associate the gradient of the spectral energy to the depth of the source (after Spector and Grant, 1970). This last association is mostly applied in gravity and magnetism, that is, from sources that produce a contrast of density or magnetic susceptibility with respect to the medium. Large part of the mathematical operators used in geophysics rely on the Fourier analysis.

In this work, we set out an analysis of the spectral energy of the magnetic signal in three and two dimensions. We apply this analysis to three cases: the first case, the classical approach, corresponds to the spectral energy calculated from synthetic magnetic anomalies, produced by bodies of simple geometry. In the second case, we use marine magnetic anomalies on a regional scale, specifically of the Caribbean plate, and finally, a third case, where we apply the method on a marine area covering a few square kilometers. Our objective was primarily to explore and characterize the spectral response from another perspective: that of the spectral cube and to estimate depths of magnetic sources from methods previously used to derive only the depth of the Curie isotherm. A first trial in the application of this method was carried out by Garcia-Reyes and Dyment (2020). However, the application of this in other areas allows evaluating its sensitivity to factors such as scale, resolution and quality of the data, the proximity of the source and geometry of the source. This exercise allows us to validate the approach in estimating depths of sources in the subsurface, and in turn, it is a step forward in understanding the spectral cube and the information it provides.

Our results allow us to offer a mapping of the depth of the magnetic sources (detectable in the spectra), and in turn, a three-dimensional view of their spectral energy. These sources are generally correlated with geological structures, as is the case with the results obtained for the Caribbean plate. Beyond the major developments of the spectral method in geophysics, we suggest that the information inscribed in the spectral signature of magnetic anomalies can still be further explored.

 

References:

GARCIA-REYES, Andreina and DYMENT, Jérôme (2020). Spatial Power Spectral Density Distribution of Magnetic Sources in the Gulf of Mexico and Caribbean Plate. In : AGU Fall Meeting Abstracts. p. GP012-0009.

Spector, A., & Grant, F. S. (1970). Statistical models for interpreting aeromagnetic data. Geophysics, 35(2), 293-302.
Comparing different versions of the continuous ranked probability score to account for forecast or observation uncertainty
Authors: Askarinejad Alireza , Trudel Mélanie , Boucher Marie-Amélie
Published: March 2022

Recent studies have shown that probabilistic forecasts are superior to
deterministic forecasts in terms of quality, reliability, and representing the
uncertainty of future states. One of the most well-known and widely used
tools for assessing the performance of (probabilistic) forecast systems is the
continuous ranked probability score (CRPS). This metric is employed to
evaluate the forecasting system when only forecast uncertainty is
considered. In addition to multiple sources of uncertainty in a forecasting
system (such as initial conditions, model structure and parameters, and
boundary conditions), the uncertainty can also originate from observations
(e.g., streamflow). However, this uncertainty, which has rarely been
explored in previous research, should also be regarded in evaluating the
forecasting system. A version of the CPRS is redefined and analyzed to
overcome this important flaw, considering the observation's uncertainty. To
estimate the uncertainty associated with streamflow observations, the
Bayesian Rating curve method (BaRatin) is utilized. This study focuses on
comparing the different versions of the CRPS in considering the
uncertainties of forecasts and observations. Three types of streamflow
forecasting systems are used in this study: deterministic forecasts, raw
ensemble forecasts (applying meteorological ensemble forecasts as inputs to
the hydrological model), and post-processed ensemble forecasts (postprocessing
of hydrological model outputs using weighted ensemble dressing
method). The assessment is performed for short-term forecasts (lead times of
1 to 5 days) for the Au Saumon watershed in southern central Quebec,
Canada. It is found that considering observation uncertainty has a significant
effect on the values of CRPS compared to when only forecast uncertainty is
considered. In addition, CRPS changes in probabilistic forecasts are more
than deterministic ones. Our results also point out that using the modified
version of the CRPS can help end-users better understand and evaluate their
forecasting system.
The Effect of Undrained Fluid Boundary Conditions on Fault Stability
Authors: Affinito Raphael , Wood Clay , Marty Samson , Marone Chris
Published: March 2022

Pore fluids are ubiquitous throughout the lithosphere and are a major part of the stress distribution along faults. Elevated pore fluid pressure reduces the effective normal stress, allowing slip and potentially changing the mode of faulting.  Mature brittle faults are characterized by deca- to hecto-meter damage zones composed of gouge and complex shear localization fabrics that can host zones of low, anisotropic permeability. Such zones can include undrained pore fluid conditions that may result in a spectrum of slip behaviors including slow slip events. Despite the obvious importance of pore fluids for fault mechanics, their role in dictating fault stability is poorly constrained. Early results for rate-strengthening accretionary wedge materials suggest pore fluid has a stabilizing effect, as the friction parameter (a - b) increases in response to increased pore fluid pressure (Pf ). Here, we describe early stages of a laboratory investigation of the role of fluid pressure on friction rate and memory effects. We present experimental results from rate-weakening synthetic gouge samples at a range of pore fluid pressure conditions. Experiments use a servo-controlled biaxial load frame enclosing a pressure vessel to apply a true triaxial stress-state with pore fluid pressures. Samples are assembled in a double-direct shear configuration with two uniform 3-millimeter-thick gouge layers. Sample forcing blocks include shear wave piezoelectric transducers for ultrasonic monitoring of shear wave amplitude and velocity. We conducted stable sliding experiments at both drained and undrained conditions to explore role of pore fluids on the RSF parameters. Undrained stick-slip experiments were also done at a range of pore fluid pressures to investigate the role of fluid pressure on the nature of fault slip. We explore differences between the drained and undrained conditions with particular attention on changes from rate-weakening to rate-strengthing friction behavior due to localized overpressure. Additionally, we evaluate interplay between the modes of fault slip, due to poroelastic processes which will result in changes in the transmitted shear wave amplitude and velocity. In subduction environments pore fluid pressure can approach lithostatic pressures leading to localized overpressure. Therefore, it is important to understand the contributions of fluids and effective stress state on frictional stability and the mode of fault slip, whether it be aseismic creep, slow slip, or earthquake rupture.
The Culture of Open Science: Building an Ethos that Feels like Home across the Earth, Space and Environmental Sciences -- One Step at a Time
Authors: Stall Shelley , Erdmann Chris
Published: March 2022

As a researcher, having access to well-documented research datasets and software relevant to your work can vary in difficulty based on your discipline and other factors. When it works well, you benefit from the ability to easily analyze and perhaps use those data and software.  When it works poorly, you are sending emails to get access to datasets, asking for more information, hoping you will get responses, and then maybe trusting that you understand the data or software well enough to integrate, rework, or explore further. 

How do we create more of the “beneficial” experience?   How do we create a culture where having better tools, practices, and methods helps us achieve this goal?  Well, it takes deliberate intent and patience in taking those initial first steps.  Many of the difficult scientific questions still in front of us require access to more usable data and software, in easier ways, enabling us to “see” the complex systems of the universe better. 

In this talk, we will share the work happening in AGU, their collaborators, and the broader community to take those initial steps, and support the culture of the future.
Sea state dependent Doppler spread as a limit of coherent GNSS reflectometry from an airborne platform
Authors: Moreno Mario , Semmling Maximilian , Stienne Georges , Dalil Wafa , Hoque Mainul , Wickert Jens , Reboul Serge
Published: March 2022

Sea level rise and sea state variability due to climate change and global warming are major research topics in the scientific community. Wind speed (WS) and significant wave height (SWH) are usable parameters to monitor the sea state threats and the impact of the ocean weather conditions in coastal areas. GNSS reflectometry (GNSS-R) has shown considerable promise as a remote sensing technique for ocean parameters estimation. Multiple studies have been successfully conducted in the recent two decades by using GNSS-R ground-based, airborne and spaceborne data to retrieve geophysical properties of the sea surface.

The focus of this study is to investigate the Doppler shift of the reflected signal as observable to estimate the Doppler spread (DS) and determine its correlation with sea state changes, making use of GNSS-R airborne data in coastal areas. An additional aim is to study the possibility of using the Doppler spread as a metric for coherent GNSS reflectometry for applications such as precise altimetry and precise total electron content (TEC) estimates. An experiment was conducted from the 12th to the 19th of July 2019 along Opal Coast, between the cities of Calais and Boulogne-sur-Mer, France. The experiment consisted of multiple flights at an altitude of ~780m (a.m.s.l). The direct and reflected signals were received by dual-polarized (Right-Handed and Left-Handed Circular Polarizations) antenna mounted on a gyrocopter.

A software receiver is used to process the direct and reflected signals from the right-hand channel. The resulting in-phase (I) and quadrature (Q) components (at 50 Hz rate) of the reflected signals are analyzed in the spectral domain every ten seconds to obtain the relative Doppler shift and power estimates. The coherence is established by analyzing the phase observations obtained from I and Q. The sensitivity of the reflected signal estimates and the sea state is determined by the correlation between the Doppler Spread with wind speed and significant wave height. The latter two were obtained from the atmospheric, land and oceanic climate model, ERA5, provided by the European Centre for Medium-Range Weather Forecasts (ECMWF).

Initial results have shown promising performance at a calm sea (WS: 2.9 m/s and SWH: 0.26 m) and grazing angles. Satellites with low elevations (E < 10°) present a Doppler Spread of 0.3 Hz and its Pearson correlations with respect to WS and SHW are 0.89 and 0.75, respectively. The performance is relatively poor for high elevation events (E > 30°). The DS increases up to 2.1 Hz and the correlation decrease to 0.55 and 0.42 respectively. Coherence conditions are still under study; however, preliminary phase analysis reveals coherent observations at events with elevations below 15° and sea state with a significant wave height of 0.26 m.
Backarc rifting as a response to a crustal collapse at the western Gondwana margin: The Triassic tectonic setting of the Sierra Nevada de Santa Marta, Northern Andes of Colombia
Authors: Avila Paez Michael Andrés , Kammer Andreas , Conde Carvajal Camilo Andres , Piraquive Bermudez Alejandro , Gomez Plata Cristhian Nicolas
Published: March 2022

Since the middle Triassic the long-lived convergent margin of western Gondwana evolved from a relatively steeply inclined into a flat lying slab setting that combined an extensional regime on the backarc side with the telescoping of crustal slices at the continental margin. In the Northern Andes the opening of Late Triassic basins is practically contemporaneous with the outwedging of lower crustal slices, that often alternate with intrusive sheets of S-type granites and mark the limit to a  non-metamorphic roof. A tectonic coupling between backarc collapse and the escape of lower crustal slices can be examined in detail in the northwestern flank of the Sierra Nevada de Santa Marta, a northern-most outlier of the North Andean basement. Remnants of a Late Triassic graben fill attest here to a block tilted toward the hinterland. Its tri-partite sedimentary sequence recycled material sourced from external parts of the continental margin. The basement of a more foreland-oriented block of the Sevilla belt is affected by outward-verging folds, which have formed under greenschist facies conditions in its upper and lower amphibolite conditions in its lower part. The succeeding Inner Santa Marta Metamorphic Belt consists of a stack of high-grade metamorphic basement slices separated by siliciclastic wedges metamorphosed under lower amphibolite conditions. The soles of the basement slices consist of migmatites with remobilized granitic pods and resulting folds oriented in a dip-slip direction. These structures are overprinted by a flattening and a second migmatitic event, which records peak P-T conditions of a lowest crustal level. Accordingly, they contain inclusions of ultramafic rocks. The time-equivalent correspondence between a supracrustal  backarc extension and a foreland-directed stacking of crustal slices suggests some similarity to the model  of a low-viscosity channel of a thickened orogenic crust. An important difference of this flat-slab setting resides, however, in a wholesale mobility of a strongly heated crust that constitutes the backarc and frontal position of this active margin.