bluuebunny/crossref_metadata_2025 huggingface dataset:
Meteorological Tools for Assessing Mantle Flow-related Dynamic Topography Maps
Authors: Taiwo Ayodeji , Bunge Hans-Peter , Craig George
Published: February 2023

Construction of robust mantle flow trajectories plays an important role in understanding the parameters that govern mantle convection and relating them to geologic observables. In the past, the assessment of constructed trajectories focused majorly on metrics targeted at the mantle volume whilst neglecting the surface manifestations of mantle convection in the form of dynamic topography. However, an increasing amount of interest is being built around linking convection to surface effects, including dynamic topography. As such, it is vital to study ways in which mantle flow trajectories can be assessed via their dynamic topography predictions. Commonly used assessment and comparison metrics such as root-mean-square errors, suffer from the so-called double penalty problem --- a dynamic topography prediction that does not match a reference observation one-to-one is penalized twice: first as a miss and second as a false alarm. It is therefore attractive to investigate metrics that overcome this problem. Here, we introduce an object-based approach, first applied in meteorology, and show that this approach is not only amenable to studying dynamic topography, but that it also overcomes the double penalty problem whilst providing accurate model assessment.
Investigating the change of hydrological patterns of streamflow by using HDCE method
Authors: Wen ChunTa , You Jiing-Yun
Published: February 2023

The change of streamflow patterns is one of the important information to water resources management. Especially, in the last few years, climate changes have not only caused increases in the intensity and frequency of extreme hydrological events, but also disrupted the monotony of climate which could lead to unexpected consequences and economic losses to our society. However, only a little research has paid attention to the change in patterns or schemes of the hydrological cycle. The issue is even more serious in Taiwan due to the uneven spatial-temporal distribution of rainfall. This research aims to discover the change in patterns in Taiwan. We proposed a HDCE framework which is composed of Hierarchical cluster, Dynamic time warping, Change point detection, and Empirical mode decomposition. With this framework, we apply the hierarchical cluster with different distance matrices, and obtain the optimal clustering number and linkage method according to clustering valid indexes. Dynamic time warping is used as the measure of distance to investigate the pattern of time series By this way, this framework determines the optimal cluster of patterns for the historical inflow data. After clustering, the AMOC (At Most One Change) is used to analyze the structure of the pattern. With AMOC, the change time point in each period is examined under the structure of each cluster. In the end, the empirical mode decomposition is adopted to determine the trend of the pattern change. With the proposed framework, this research applies these schemes to main inflow observation gage stations in Taiwan, and the results demonstrate that the groups and activities of positions of the stations indirectly affect the pattern of the inflow values, instead, the clusters formed are mainly affected by the region and geographical area of the locations. Furthermore, we will explain the results showing the different trends in changing time in each region and the correlation of breaks at each station. In this way, the results of HDCE not only examine the occurrence of droughts but provide information that is useful to develop the strategy to reduce the loss through better water management.
A Transformer Model for Ionospheric TEC Prediction Using GNSS Observations
Authors: Kaselimi Maria , Doulamis Nikolaos , Doulamis Anastasios , Delikaraoglou Demitris
Published: February 2023

Precise modeling of the ionospheric Total Electron Content (TEC) is critical for reliable and accurate GNSS applications. TEC is the integral of the location-dependent electron density along the signal path and is a crucial parameter that is often used to describe ionospheric variability, as it is strongly affected by solar activity. TEC is highly depended on local time (temporal variability), latitude, longitude (spatial variability), solar and geomagnetic conditions. The propagation of the signals from GNSS (Global Navigation Satellite System) satellites throughout the ionosphere is strongly influenced by temporal changes and ionospheric regular or irregular variations. Here, we leverage transformer as an effective and scalable structure with self-attention mechanisms, for modeling long-range temporal dependencies for ionospheric TEC modelling based on GNSS data. The proposed transformer model is capable of learning long-range temporal dependencies. In seq2seq models, learning temporal dependencies is a demanding task, and often the model forgets the first part, once it completes processing the whole sequence input. Our model utilizes attention mechanisms and identifies complex dependencies between input sequence elements throughout the whole sequence.Our model handles imbalanced datasets. Our work demonstrates that combining the unsupervised pre-training process with downstream task fine-tuning, offers a practical solution for ionospheric TEC modelling. This is a comparative advantage against the existing state-of-the-art works which, in most cases, fail to sufficiently model intense ionospheric variability conditions.
Valuing seasonal streamflow forecasts in power system operations
Authors: Galelli Stefano , Koh Rachel
Published: February 2023

The value of seasonal streamflow forecasts for the hydropower industry has long been assessed by considering metrics related to hydropower production. However, this current approach overlooks the role played by hydropower dams within the power grid, therefore providing a myopic view of how forecasts could improve the operations of large-scale power systems. There are, in particular, two points worth stressing. First, the inherent uncertainty of streamflow forecasts could be easily propagated into the grid, especially if the power system is highly reliant on hydropower. Second, the relationship between water and power systems is not unidirectional: failing to capture feedback mechanisms may add uncertainty to exercises aimed at characterizing the value of seasonal forecasts. To fill in this gap, we developed a novel modelling framework that (i) hard-couples a reservoir system model with a power system model, and (ii) is subject to reservoir inflow forecasts with different levels of accuracy. We implement the framework on a real-world case study based on the Cambodian grid, which relies on hydropower, coal, oil, and imports from neighboring countries. In particular, we evaluate the performance of both systems in terms of power production costs, CO2 emissions, and the amount of curtailed hydropower. Through this framework, we demonstrate that the value of streamflow forecasts is affected not only by their skill, but also by the dynamic behavior of the coupled water-power system.
Exploring the Depth of Planetary-Scale Changes in Jupiter from Juno Microwave Radiometer Observations
Authors: Orton Glenn , Fletcher Leigh , Oyafuso Fabiano , Li Cheng , Zhang Zhimeng , Brueshaber Shawn , Wong Michael H. , Momary Thomas , Levin Steven , Bolton Scott , Baines Kevin , Dahl Emma , Sinclair James
Published: February 2023

The Juno Microwave Radiometer (MWR) has extended our knowledge of the structure and composition of the atmosphere down to several hundred bars, revealing meridional variability to great depth (e.g. Li et al. 2017 Geophys. Res. Lett. 44, 5317; Fletcher et al. 2021. J. Geophys. Res. 126, E06858). The MWR has revealed that some cyclonic and anticyclonic vortices may have roots at depths of tens of bars of pressure (Bolton, et al. 2021. Science 374, 968.), but 5-µm hot spots and associated plumes appear to be restricted to shallow depths above the water cloud (Fletcher et al. 2020, J. Geophys. Res. 125, e06399). We report ongoing work on evolution of the microwave brightness of Jupiter’s axisymmetric bands over 2016-2022. We have examined the regions where changes have taken place at visible wavelengths, as documented by images from professional and amateur observers, to judge their depth. Preliminary results show that microwave brightness variability from channels sensitive to depths corresponding to 9-50 bars of atmospheric pressure are generally much lower than those at pressures of 0.7-3 bars. One exception to this is in the northern component of Jupiter’s Equatorial Zone (2°N-6°N), whose measured variability at depth does not correspond to any visible or infrared feature in the upper atmosphere, although it might be considered a precursor to the short-lived 2018-2019 Equatorial Zone disturbance. At the lower pressures, a decrease in the antenna temperature in the northern component of the North Equatorial Belt (12°N-15°N) is coincident with its visible brightening and drop of 5.1-µm radiance, both implying increased cloud and NH3 opacity in 2021. Even though the visibly dark North Equatorial Belt expanded northward into latitudes more typically associated with visibly bright regions that are cold at 5.1 µm (16°N-19°N), known as the North Tropical Zone (Fletcher, et al. 2017. Geophys. Res. Lett. 44, 7140), we do not detect any corresponding change of the MWR antenna temperature.  Although there are substantial changes in the visible and 5.1-µm appearance of the northern component of the North Temperate Belt (24°N-26°N) as well as in the MWR antenna temperatures, the two do not appear to be correlated with one another. An important part of our next steps in this research will be to examine which of the MWR variabilities in the zonal-mean microwave brightness are the result of zonally discrete features in the atmosphere, particularly the North Equatorial Belt (6°N-15°N). 
Estimation of rainfall interception from merged drone and terrestrial LiDAR data by modeling 3D canopy structure in plantation forest
Authors: Zhang Yupan , Onda Yuichi , Tan Yiliu , You Hangkai , Pham Thuy Linh , Hashimoto Asahi , Chiu Chenwei , Gomi Takashi , Takamura Shiori
Published: February 2023

The multidimensional arrangement of upper canopy features is a physical driver of energy and water balance under various canopies, and standard modeling approaches integrate leaf area index (LAI) and canopy closure (CC) to describe canopies. However, it is unclear how the canopy affects the component and interception of rainfall within the forest system. We generated multi-layered forest point clouds from trunk to canopy using fusion of drone and terrestrial LiDAR data then classified wood and foliage elements using a clustering algorithm to build a high precision physical model for describing throughfall, stemflow and interception. The experiment was conducted in the thinning plantation forest located in Tochigi prefecture, Japan. Rainfall observation for the three components is important for model development. Throughfall was computed from 20 rain gauges distributed on a grid under the forest canopy, 3 stemflow collectors was set up around the tree trunks connected to a bucket with water level sensor. We developed a capacity model to describe canopy saturation with foliage points, a voxel-based method was used to create 3D representations of forest canopies, and an analysis of these point-derived canopy structures and volume were performed to assess the canopy's capacity to contain rainfall. For stemflow modeling, we use a runoff model to simulate the additional rainfall accumulates to the tree trunk through branches when the tree canopy is saturated. Preliminary simulation results show that: (1) fusion and registration of drone and terrestrial LiDAR data can greatly improve the point cloud accuracy and enrich the information contents such as coordinate geo-reference and filling of missing structures; (2) a strong correlation between the rainfall observed canopy interception results and the estimated canopy volume, and the volume-based interception prediction model has a high accuracy, with an R2 from 0.84 to 0.91 compared to past observations. (3) stemflow is related to the projected volume of the canopy and the proportion of wooden structure point clouds, and as the runoff path increases, there is a greater probability that oversaturated precipitation will concentrate on the trunk rather than drip off. High accuracy physical model of tree canopy can well describe the interactions between the rainfall to canopy and illustrate the mechanism. 
Molecular signatures of soil-derived dissolved organic matter constrained by mineral weathering
Authors: Wang Yinghui , Zhang Peng , He Chen , Shi Quan , Dahlgren Randy , Spencer Robert , Wang Junjian
Published: February 2023

  Dissolved organic matter (DOM) in soil consists of a diverse mixture of water-soluble soil organic matter (SOM) molecules that are highly mobile and reactive. These molecules play various roles with different capacities in biogeochemical processes. Theoretically, the persistence of DOM molecules in soils is controlled by interactions between i) DOM leaching and desorption that release DOM from plant residues and SOM and ii) sorption and decomposition that remove DOM. However, there is still no consensus on the dominant factor(s) or dimension(s) driving the yield and molecular signatures of DOM in soil environments.  Molecular variations of soil DOM from distinct geographical regions are primarily attributed to variations in geographical climate conditions and soil clay content. Soil weathering condition is highly related to geographical climate conditions, such as temperature and precipitation, and could be a reflection of the soil mineral characteristics. However, there is a distinct paucity of information concerning how the molecular signatures of soil DOM vary with different degrees of weathering across wide geographic scales.  Herein, we resolved the DOM molecular signatures from 22 diverse Chinese reference soils and linked them with soil organic matter and weathering-related mineralogical properties. The mixed-effects models revealed that the yields of DOM were determined by soil organic carbon content, whereas the molecular signature of DOM was primarily constrained by the weathering-related dimension. The soil weathering index showed a positive effect on the lability and a negative effect on the aromaticity of DOM. Specifically, DOM in highly weathered acidic soils featured more amino sugars, carbohydrates, and aliphatics, as well as less O-rich polyphenols and condensed aromatics, thereby conferring a higher DOM biolability and lower DOM aromaticity. This study highlights the dominance of the weathering-related dimension in constraining the molecular signatures and potential functions of DOM in soils across a wide geographic scale.
An electric circuit model of the Earth's polar electrojets and field-aligned currents for the estimation of magnetospheric magnetic field from along-track Swarm magnetic data
Authors: Martinec Zdeněk , Velímský Jakub
Published: February 2023

We deal with the analysis of Swarm vector magnetic data to create a circuit model of electric currents flowing in the Earth’s polar ionosphere and the inner magnetosphere. The model is composed of a system of two-dimensional electric currents representing the magnetic fields of three-dimensional ionospheric polar electrojets (PEJs), the field-aligned currents (FACs), magnetospheric ring currents (MRCs) and magnetospherically induced electric currents inside the Earth (MICs) for each Swarm track. We aim to model PEJ and FAC magnetic fields in terms of electric currents on a track-by-track base, subtract those magnetic fields from along-track Swarm magnetic data and estimate the magnetospheric magnetic field (MMF) in discrete time bins. The final model of MMF, named MMC, is represented by the two-circular loop model. Reliability of the approach is demonstrated by the scatter plots of model MMC showing a significantly better agreement with Swarm magnetic field residuals than the existing MMFs. A novelty of the proposed electric circuit model is that it approximately accommodates the known topology of the electric currents flowing in the polar ionosphere and inner magnetosphere at magnetically disturbed times. The proposed method is primarily intended to apply to Swarm signals recorded during magnetic storms.
Fluvial land cover classification by using CSC deep learning method with UAV airborne images
Authors: Miyamoto Hitoshi , Ishii Ryusei
Published: February 2023

This study investigated a deep learning method for fluvial land cover classification using aerial imagery of the UAV (Unmanned Aerial Vehicles). The deep learning used in this study was the CNN-Supervised Classification (CSC) developed by Carbonneau et al. (Remote Sensing of Environment, 2020). The analysis was based on 51 river sections of RGB orthorectified images taken aerially in 2015-2019 in several river channels of the Kinu River in Japan. They were obtained by applying the SfM (Structure from Motion) processing to the UAV aerial images acquired during field observations. The spatial resolution of the images was approximately 4 cm per pixel. The seven land cover types classified by CSC were water surface, gravel, sand, grass, tree, farmland, and artificial land. The deep learning algorithm CSC in this study was a classification model combining two-stage Convolution Neural Networks (CNNs). The first stage of the CSC classified the input image into 200 x 200-pixel image tiles and created a training dataset to be used in the second stage. Then, the training dataset was used to train a second-stage small-scale CNN (hereafter called mini-CNN) to optimise the model hyper-parameters. Finally, the trained CSC performed pixel-based land cover classification of the RGB orthoimages. In the first stage, this study used an existing CNN architecture, VGG16. The fine-tuning dataset had more than 2,500 images for each land cover class, resulting in a total of 85,800 through data augmentation. The hyper-parameters examined were the learning rate, patch size and the number of frozen layers. The F-measures for the CSC first stage with the optimised parameters were 99.1, 96.9, 92.6, 91.4, 93.6, 95.7 and 96.1% for water surface, gravel, sand, grass, tree, farmland, and artificial land, respectively. Then, the architecture of the mini-CNN, learning rate, patch size, patch number and filter size were optimised for the CSC second stage. The weighted average F-measure for the optimised CSC model was 90.4%. This confirmed that the optimised CSC could reproduce the land cover classes with enough accuracy. The CSC application to the RGB orthorectified images of the Kinu River in Japan showed that the CSC deep learning method could accurately classify temporal changes in fluvial geomorphologies such as gravel beds and sandbars as well as riparian vegetation, including the significant differences before and after the severe floods in 2015 and 2019. Future work would be needed to verify the applicability of the proposed CSC deep learning method to other rivers with different fluvial characteristics.
Nexus research for sustainability and inclusiveness in practice
Authors: Brouwer Floor
Published: February 2023

Nexus research is advancing from knowledge creation towards public awareness and inclusiveness for civil society, public-private partnerships, and knowledge partners. Nexus research was mainly focused on a better understanding of interlinkages between the relevant resources at stake (e.g., water, energy, food, and ecosystems), the focus is increasingly searching for building communities, training, and career development. Research on the WEFE nexus increasingly aims to create platforms building capacity among institutions, knowledge partners, and capacity development. Educational and learning programs are developed by hot spots of the nexus. Expanding transdisciplinary research methods could facilitate building a community and network of nexus professionals. Capacity development and awareness are also critical for the successful planning and implementation of nexus practices. Some successful examples of knowledge creation for inclusiveness are shared.  The presentation will identify some key enablers and measures to advance the nexus in practice. Nexus research benefits from advancing along this route. 
Geoturism in a volcanic sites: El Hierro UNESCO Global geopark (Canary Islands, Spain)
Authors: Hernández William , Dóniz-Páez Javier , Beltrán-Yanes Esther , Becerra-Ramírez Rafael , Hernández Pedro A. , Pérez Nemesio M.
Published: February 2023

El Hierro Island is the westernmost and the smallest of the Canary Islands. It is the youngest volcanic island in the archipelago and has a rich and diverse heritage related to volcanic forms and processes, in which geomorphology is the main value, receiving in 2014 the designation of Global Geopark by UNESCO. El Hierro receives every year thousands of tourists mainly motivated by diving and trekking. For this reason, the aim of this work is the inventory, selection and quantitative evaluation of well preserved and accessible volcanic geomorphosites with a geoturistic interest, in order to promote the geotourism and to diversify the leisure offer on the island. In this work we applied the geomorphosites assessment methodology elaborated by Serrano and González (2014). This methodology involves a three-way comparison of the different values of the geomorphosites: the scientific or intrinsic values, cultural values and use and management values. The values of geomorphological heritage are expressed from 1 to 5. The results reveal the existence of twenty geomorphosites with potential use for geoturism. These sites include cinder cones, lava fields, lava deltas, faults, giant landslides, valleys, cliffs and beaches. The geomorphosites with highest geomorphological heritage are El Golfo and El Julan giant landslides and those with the lowest are Hoya Fileba and Tanganasoga volcanoes. In general, the twenty selected sites show average values between 1.6 to 2.0. Valuable information provided by this study and knowledge of these twenty geomorphosites are important for promotion of tourism activities in the Geopark. The selection of these geomorphosites can contribute geotourism as an important leisure activity in the island and can assist planners and authorities to formulate suitable plans for sustained development of the El Hierro UNESCO Global Geopark by the creation of geo-routes. (Volturmac-MAC2/4.6c/298).
Climatic micro-zonation of Naples (Italy) through Landsat and machine learning
Authors: Flocco Daniela , Piegari Ester , Scafetta Nicola
Published: February 2023

The area of Naples, in southern Italy, is densely populated and seriously affected by a variety of environmental hazards related to meteorological conditions. The city is characterized by a complex topography therefore the meteorological risks sensibly vary throughout its territory.

In the past decade, heat waves have been increasingly frequent: the production of heat maps would help the comprehension of the differential risks in town and would allow more accurate information on the related health risks to be available to the population.

At present, maps of heat wave vulnerability show the spatial distribution of single factors, whereas vulnerability is governed by several competing or additive factors, so ambiguities about the identification of the most vulnerable areas currently remain.

In the attempt to overcome this limit and identify areas more vulnerable to the effects of heat waves not only confined in Naples city centre, but also in suburban areas, we will apply unsupervised machine learning algorithms to integrate information from different factors and provide detailed heat wave vulnerability maps.
Extracting Magnetic Dipole field variations from cosmogenic 10Be records
Authors: Savranskaia Tatiana , Egli Ramon , Panovska Sanja , Korte Monika
Published: February 2023

Sedimentary records of the Earth’s magnetic field often contain unwanted climatic overprints, distorting the reconstruction of paleomagnetic field intensity variations.  In case of field reconstructions based on the cosmogenic isotope 10Be, whose production is modulated by the solar activity and the dipolar component of the geomagnetic field, environmental overprints arise from climatic modulations of the source distribution, transport, and sediment scavenging efficiencies. Although the lithological dependence of the scavenging efficiency is supposed to be removed by normalizing 10Be with the stable isotope 9Be, this normalization can introduce its own environmental effects, caused by changes in source, distribution and transport of two isotopes. These processes lead to inter-sites differences observed between 10Be/9Be and corresponding relative paleointensity records, limiting use for global magnetic field models constructions. Principal component analysis (PCA) and independent component analysis (ICA) of four 10Be/9Be records from West Pacific and North Atlantic Ocean sites, characterized by different environmental settings, allowed us to extract the common pattern controlled by the evolution of the dipole field. These observations are made on records covering the last 380 ka, including seven geomagnetic excursions.While the first component of cosmogenic 10Be records clearly reflects geomagnetic dipole changes, it seems that the second and third components are dominated by 100- and 23-ka periodic oscillations respectively, corresponding to Earth’s orbital forcing. PCA and ICA methods are shown to be a powerful tool for disentangling and assessing different components of cosmogenic beryllium records. The geomagnetic component can serve to better understand the long-term geomagnetic field evolution, thus improving our knowledge of driving mechanisms sustaining the geodynamo.
A global analysis of the timing of changes in water extents using Google Earth Engine and Landsat Time Series.
Authors: Nagel Gustavo , Darby Stephen , Leyland Julian
Published: February 2023

Coastal and inland surface water resources are affected by complex and overlapping processes such as climate change, droughts, flooding, river damming, coastal expansion, dredging, river meander migration, and so on. The use of satellite-acquired imagery, combined with recent advances in cloud computing, is enabling the monitoring on a global scale of areas where water limits have advanced or receded (Donchyts et al., 2016; Donchyts et al., 2022; Pekel et al., 2016). However, previous studies have not estimated an important aspect: the precise timing at which changes in water extents happened. Here we present preliminary results of an analysis using 38 years of Landsat time series and the cloud platform Google Earth Engine (GEE) in which we  monitor areas where water has advanced and receded and the year that this change happened. The developed algorithm detects only permanent changes in water features and thus avoids seasonal or higher-frequency fluctuations caused by short-lived events. The method employs a two-step algorithm. The first step detects areas of permanent change using the Modified Normalized Different Water Index (mNDWI), which effectively detects water and non-water features. In the areas of detected permanent change, the second step uses a Green-Red Normalized Different Water Index (GR_NDWI), which has a smoother value transition from water to land, to identify the year that the change happened. The thresholds of mNDWI and GR_NDWI used to determine if a pixel is water or not were estimated using the Otsu method. Furthermore, an additional novel algorithm was developed to fill in cloud holes in the time series, allowing the monitoring of cloudy regions, such as the Amazon Basin. The final product will be a World Map of the year that the water advanced or receded. A preliminary result for the American continent (excluding Canada)  can be visualized in this app: https://gustavoonagel.users.earthengine.app/view/americawaterdetection . The product will be available in a public GEE dataset, for open access use by researchers, governments, and private companies working on oceans, rivers and water lakes, helping to improve water management on a global scale. Donchyts, G., Baart, F., Winsemius, H., Gorelick, N., Kwadijk, J., & van de Giesen, N. (2016). Earth's surface water change over the past 30 years. Nature Climate Change, 6(9), 810-813. https://doi.org/10.1038/nclimate3111Donchyts, G., Winsemius, H., Baart, F., Dahm, R., Schellekens, J., Gorelick, N., Iceland, C., & Schmeier, S. (2022). High-resolution surface water dynamics in Earth’s small and medium-sized reservoirs. Scientific Reports, 12(1), 13776. https://doi.org/10.1038/s41598-022-17074-6Pekel, J.-F., Cottam, A., Gorelick, N., & Belward, A. S. (2016). High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633), 418-422. https://doi.org/10.1038/nature20584
The Fractional Macro Evolution Model: A simple quantitative scaling macroevolution model
Authors: Lovejoy Shaun , Spiridinov Andrej
Published: February 2023

Scaling fluctuation analyses of the marine animal diversity, extinction and origination rates based on the Paleobiology Database occurrence data have opened new perspectives on macroevolution, supporting the hypothesis that the environment (climate proxies) and life (extinction and origination rates) are scaling over the “megaclimate” biogeological regime (from ≈ 1 Myr to at least 400Myrs).   In the emerging picture, biodiversity is a scaling “cross-over” phenomenon being dominated by the environment at short time scales and by life at long times scales with a cross-over at ≈40Myrs.  These findings provide the empirical basis for constructing the Fractional MacroEvolution Model (FMEM), a simple stochastic model combining destabilizing and stabilizing tendencies in macroevolutionary dynamics.  The FMEM is driven by two scaling processes: temperature and turnover rates. Macroevolution models are typically deterministic (albeit sometimes perturbed by random noises), and based on integer ordered differential equations.  In contrast, the FMEM is stochastic and based on fractional ordered equations.   Stochastic models are natural for systems with large numbers of degrees of freedom and fractional equations naturally give rise to scaling processes. The basic FMEM drivers are fractional Brownian motions (temperature, T) and fractional Gaussian noises (turnover rates E+) and the responses (solutions), are fractionally integrated fractional Relaxation processes (diversity (D), extinction (E), origination (O) and E- = O - E).  We discuss the impulse response (itself a model for impulse perturbations such as bolide impacts) and derive the full statistical properties including cross covariances.  By numerically solving the model, we verified the mathematical analysis and compared both uniformly and irregularly sampled model outputs to paleobiology series. The six series (T, E+, D, E-, O, E) had fluctuation statistics that varied realistically with time scales Δt (lags) over the observed range (≈3 Myrs to ≈ 400 Myrs).  In addition, the 15 pairwise fluctuation correlations (of the six variables) as functions of Δt were also very close to observations even though only two correlations were specified in the model (TE+and TD).  The ability to simulate the effects of irregular temporal sampling was important since model – data agreement was much better with realistic (irregular) sampling than with uniform sampling.  Although the model could easily be made more complex, this may not be warranted until much higher resolution series become available.
 Well...Well...Well...:  Using sparse data to do preliminary modeling and numerical simulations for subsurface storage in Western Nebraska
Authors: Fleagle Samuel , Burberry Cara , Kim Seunghee , Lawal Lateef
Published: February 2023

In Nebraska, carbon dioxide emissions come from burning fossil fuels, (~15 million tons of CO2 per year) and from ethanol plants (~4 million tons of CO2 per year). Carbon capture and storage (CCS) is therefore vital to improve the air quality in Nebraska and to enable these industries to operate. The study area for this project covers that region of Western Nebraska not fully evaluated to date, wherein we postulate that there is extensive storage space specifically in the stacked carbonates of the Pennsylvanian cyclothems.  There is evidence of strong primary and secondary seals overlying the potential reservoir units. 

We use existing well call outs (available through the Nebraska Oil and Gas Conservation Commission) and wireline logs to construct a framework 3D subsurface model. We have also logged and sampled core at the USGS Core Research Center to further understand the stratigraphy and validity of wireline data; as well as conducting geomechanical tests on core samples to evaluate porosity, permeability, and storage efficiency properties. Using volumes extracted from the model and the geomechanical data, numerical simulations will be run using the National Energy Transition Lab’s (NETL) CO2-Screen, a Monte Carlo-based package that generates a probabilistic range of storage volumes. 

We demonstrate that the study region is viable and promising for a further stage of data gathering, including seismic surveys and the drilling of a stratigraphic test well to completely evaluate the reservoir units. The aim is to define a reservoir space with 50 million tons of storage capacity injected over the span of a decade, i.e., the CarbonSAFE goal. The subsurface storage of CO2 is critical to global efforts to reduce the effects of greenhouse gas-induced climate change. Reducing emissions will improve local air quality and aid in the larger goal of curtailing emissions of greenhouse gases to mitigate the impacts of climate change. 

 

 
No chance for doubts: a multidisciplinary approach for solving a criminal case.
Authors: Baldino Gennaro , Ventura Spagnolo Elvira , Vanin Stefano , Somma Roberta , Cucinotta Filippo , Mondello Cristina , Gualniera Patrizia , Gaeta Michele , Asmundo Alessio , Sapienza Daniela
Published: February 2023

In a forensic context, the criminal case evaluation is often challenging, and the only autopsy may not be exhaustive to determine the cause and the time of death, mainly when the corpse is dismembered, charred, or putrefied. Moreover, the conditions of an altered corpse and the recovered places of the cadaver (countryside, forests, rivers, beaches, etc.), outdoors, or in burnt buildings and ruins, can raise challenges not only in terms of victim identification but also in terms of acquisition of additional information aimed at elucidating the dynamics of death, like the detection of the corpse transfer after the death, especially in cases of suspected homicides. In such complex cases, it is, therefore, of paramount importance to provide a multidisciplinary approach involving the collaboration of ultra-specialized forensic experts. In this context, experts in criminalistic disciplines, such as forensic geology, botany, and entomology, may provide their contribution, as well as the engineers applying to medicine new technologies for the 2D and 3D reconstructions of crime scenes and evidence. We consider helpful to report a court case that came to our attention, involving forensic pathology experts together with forensic biologists, geologists, botanists, naturalists, entomologists, veterinarians, physicists, computer scientists, and engineers whose collaboration based on a multidisciplinary approach contributed to the management and the solving of a suspect crime.
Identification of precipitation and maximum temperature patterns in Spain during 1951 to 2021 using clustering based on multiscale analysis of time series
Authors: Palacios Gutiérrez Arnobio , Valencia Delfa Jose Luis
Published: February 2023

Spain is a territory with spatial variations highly influenced by its distance from the sea and its complex orography, where it is possible to note an uneven distribution of both temperature and precipitation. This study presents an analysis of trends in maximum temperature and precipitation by zone over the period 1951-2021 using monthly data. The database used includes 16156 multivariate time series (maximum temperatures and precipitation) corresponding to different areas of the Spanish territory, distributed over a grid of 5x5km2. The methodology used starts by reducing the dimensionality of the time series and with this version are clustered using an approach based on multiscale analysis using a clustering algorithm. In the following, the prototypes of each group are defined, which allows to identify and analyse patterns of change in maximum temperatures and precipitation by zones. An increase in average maximum temperature has been identified in eight zones distributed in Spain from 1951 to 2021. The rate of change of maximum temperature was between 0.060ºC and 0.2155ºC per decade. Areas further south showed a higher rate of increase than areas found in the north. It has been observed that May was the month with the highest variation for all areas in maximum temperature, nevertheless, differences in seasonal variation are evident when passing from one zone to other, as in some there is greater variation in spring months and in others in winter months. An analysis of trends and seasonal variations of precipitation in the identified zones will be carried out and the correlation between patterns of maximum temperature and precipitation will be studied in each of the eight zones.
Quantifying the Contribution of Nonlinear Resonant Effects to Diffusion Rates
Authors: Vainchtein Dmitri , Artemyev Anton , Mourenas Didier , Zhang Xiaojia
Published: February 2023

The wave-particle resonant interaction is a key process controlling energetic electron flux dynamics in the Earth’s radiation belts. All existing radiation belt codes are Fokker-Planck models relying on the quasi-linear diffusion theory to describe the impact of wave-particle interactions. However, in the outer radiation belt, spacecraft often detect waves sufficiently intense to interact resonantly with electrons in the nonlinear regime.We propose an approach to (1) estimate the contribution of such nonlinear resonant interactions, and (2) include them into diffusion-based radiation belt models. Using statistics of chorus wave-packet amplitudes and sizes (number of wave periods within one packet), we provide a rescaling factor for the quasi-linear diffusion rates to account for the contribution of nonlinear interactions in long-term electron flux dynamics. Such nonlinear effects may speed up 0.1-1 MeV electron diffusive acceleration by a factor of x2-3 during disturbed periods.
Application of the Self-calibrated Palmer Drought Severity Index for Estimation of Drought Impact on Maize Grain Yield in Pannonian Part of Croatia
Authors: Pandžić Krešo , Likso Tanja , Pejić Ivan , Šarčević Hrvoje
Published: February 2023

Ten-day self-calibrating Palmer Drought Severity Index (scPDSI) has been computed, based on observed 10-day mean air temperature, relative humidity and precipitation totals, as a parameter of drought impact on grain yield of 32 marketleading maize hybrids in 2017 and 2018 over 8 experimental locations in Pannonian part of Croatia. In addition, time series of the same climate variables for the closest “official” weather stations of Croatian Meteorological and Hydrological Service (DHMZ) for the period 1981-2018 have been used for scPDSI calibration and calculation. According to 10-day scPDSI, 2018 showed to be a „regular year“ while 2017 had a „moderate drought“ causing a maize grain yield reduction of 13%, compared to 2018. In spite some differences in climate aridity of central and eastern Croatia, a significant correlation between summer months’10-day scPDSI and maize grain yield has been determined. The highest average correlation coefficients across all maize hybrids for three summer months were determined for the last decade (10-day period) of July and consecutive three decades in August. The dependence of grain yield on scPDSI value is not the same for all hybrids indicating various tolerances of different hybrids to drought stress. The grain yield reduction was primarily affected by insufficient grain filling (smaller 1000-kernel weight) and to some extent by reduction of number of grains. For practical use, within the set of given 32 tested hybrids, the level of determined drought tolerance of a hybrid has to be considered along with its relative grain yield performance.
2D hydraulic modelling of the ancient paleolake in Gusev Crater, Mars.
Authors: Perez Carazo Marco Antonio , Vazquez Tarrio Daniel , Anangono Tutasig Ronny Steveen , Fernandez Menendez Susana del Carmen
Published: February 2023

The application of hydraulic models on Mars is still a scarcely discussed topic in the scientific literature, despite the interest of  these models to study paleofloods and to understand the geological past of the planet. In this work, we present the application of a 2D-hydraulic model (using HECRAS) in Gusev crater aiming to study the hydrodynamics of a paleolake that would have been formed in the crater about 3,5 Ga ago.Using a corrected and optimized 100m resolution Digital Elevation Model derived from MOLA ( Mars Orbiter Altimeter) data, we first identify and map the different evidences of water marks. Different flow rates and commonly used friction values were combined to obtain several flow hypotheses, which in turn were simulated with the 2D model. Our main aim was to study the flow patterns inside the crater and the inlet and outlet conditions in order to check if the water levels obtained with our simulations correspond to what the mapped benchmarks may suggest.The Ma’adim valley feeding Gusev crater ends in a fluvial-lake delta. The flat top morphology  of this delta suggests that streamflow processes must have occurred on its top during its formation. Then, one of our major research assumptions is based on finding flow rates consistent with a fully submerged. In this regard, model outcomes obtained with flow rates covering the whole delta are consistent with previous discharge estimations compiled from the scientific bibliography.Moreover, we also took advantage of the last capabilities of the hydraulic modeling software to go further than just simulating water flows. That said, we varied the concentration of sediments within the fluid and other fluid parameters such as internal shear stress and dynamic viscosity to model a hyperconcentrated flow, which has been already proposed  as forming flow conditions for the delta. At the same time, we also analyzed turbulence and flow recirculation processes trying to stablish a relation with the sediment distribution within the crater.Based on our work, we conclude that the downstream boundary conditions in the hydraulic model is the main source of uncertainty in the modelling of Gusev crater,while changes in roughness has a minor influence on model outcomes. Finally, we raised the question on how low gravity in Mars may have affected sediment transport by water and how the nature of this process may have been different than in the Earth.
The energetic ion environment around Ganymede to be investigated with JUICE
Authors: Plainaki Christina , Massetti Stefano , Jia Xianzhe , Mura Alessandro , Roussos Elias , Milillo Anna , Grassi Davide
Published: February 2023

In this work the radiation environment around Ganymede is investigated. We apply a single-particle Monte Carlo model to obtain 3-D distribution maps of the H+, O++, and S+++ populations at the altitude of ~500 km and to deduce surface precipitation maps. We perform these simulations for three distinct configurations between Ganymede’s magnetic field and Jupiter’s plasma sheet (JPS), characterized by magnetic and electric field conditions similar to those during the NASA Galileo G2, G8, and G28 flybys (i.e., when the moon was above, inside, and below the centre of Jupiter’s plasma sheet). Our results provide a reference frame for future studies of planetary space weather phenomena in the near-Ganymede region and surface evolution mechanisms. For ions with energies up to some tens of iloelectronvolts, we find an increased and spatially extended flow in the anti-Jupiter low-latitude and equatorial regions above Ganymede’s leading hemisphere. Our results also show that the ion flux incident at 500 km altitude is not a good approximation of the surface’s precipitating flux. To study, therefore, Ganymede’s surface erosion processes it may be best to consider also low-altitude orbits as part of future space missions. This study is relevant to the ESA JUpiter ICy moons Explorer mission, which will allow a detailed investigation of the Ganymede environment and its implications on the moon’s surface evolution.
Imaging Spectroscopy Observations from NASA’s Earth Surface Mineral Dust Source Investigation launched in 2022 and Connections to Imaging Spectrometers for Greenhouse Gas Measurement, Europa, the Moon
Authors: Green Robert
Published: February 2023

NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer was launched to the International Space Station (ISS) on the 14th of July 2022.  EMIT measures the spectral range from 380 to 2500 nm with 285 contiguous spectral channels with 60 m spatial sampling and an 80 km swath.  The EMIT imaging spectrometer is optically fast at F/1.8 to deliver high signal-to-noise ratio observations.  Novel methods are used for on-orbit calibration, dark signal measurement, and geolocation.  The EMIT measurement characteristics and processing results through calibration, atmospheric corrections, and surface mineralogy retrievals are reported.  The EMIT science team will use these new comprehensive observations of surface mineralogy across the Earth’s arid land dust source regions to update the initial conditions of Earth System Models to understand and reduce uncertainties in mineral dust radiative forcing at the regional and global scale now and in the future.  EMIT’s measurements, products, and results with be available to other investigators for the broad set of science and applications they enable through the NASA Land Processes Data Active Archive Center.  The connection between EMIT, Carbon Plume Mapper, the Mapping Imaging Spectrometer for Europa, and the High-resolution Volatiles and Minerals Moon Mapper on Lunar Trailblazer is also described.