bluuebunny/crossref_metadata_2025 huggingface dataset:
Infrastructure stability diagnosis via postseismic deformation: A case study of 2016 Meinong earthquake in southwestern Taiwan using multitemporal Sentinel-1 satellite
Authors: Lu Chih-Heng , Chuang Ray , Chiang Ping-Chen , Yen Jiun-Yee , Ching Kuo-En , Chen Yue-Gua
Published: February 2023

Compared with obvious records of coseismic surface ruptures and displacements, the postseismic surface deformation is often to be omitted. On the other hand, the deformation rate of the postseismic deformation is much faster than of the interseismic surface deformation. Therefore, how to efficiently assess the hazard potential of the infrastructures induced by postseismic displacements is of practical to the societal security. In this study, we processed multi-temporal images taken by Sentinel-1 satellite via using the persistent scatterer InSAR (PSI) technique. With the constraints of continuous GNSS data, we estimated 2D (E-W and vertical) postseismic deformation rates for 3 years after the 2016 Meinong earthquake. An annual deformation tolerance ratio (ADTR), converted by the 2D displacement rates based on the maximum deformation tolerance of public infrastructure , was proposed for the assessment on public transportation systems, to highlight the segment with high hazard potential. We picked up each pixel on the high-hazard potential segments of high-speed railway (HSR) with time-series variation analysis to characterize spatiotemporal behaviors of the fault systems after the seismic event. The 2D postseismc deformation rate in E-W direction and vertical direction are 1.5 and 2-3 times respectively higher than of the interseismic duration, respectively. The ADTR results indicated that the high-hazard potential segment of HSR in the vertical direction was located on Tainan City with 22–33‰, and that in the E-W direction was located on Kaohsiung City with 5–7.5‰. The time-series variation results presented that the hazard potential gradually decreased after mid-2017. Our observations combined the geological settings and the environmental conditions that can effectively assess the degrees of hazard potential of infrastructures during the postseismic period. The postsesimic deformation should be included into the seismic hazard assessment of urban area where high seismic risk exists, and the results of ADTR and time-series variation could be considered into the seismic hazard assessment in the engineering scale for the public transportation system.
Using interactive object segmentation to derive avalanche outlines from webcam imagery
Authors: Hafner Elisabeth , Oberson Lucien , Kontogianni Theodora , Daudt Rodrigo Caye , Wegner Jan Dirk , Schindler Konrad , Bühler Yves
Published: February 2023

Safety related applications like avalanche warning or risk management depend on timely information on avalanche occurrences. Today, this is gathered in a non-systematic way by observers in the field, even though remote sensing already proved capable of providing spatially continuous information on avalanche occurrences over large regions. Satellite imagery has the big advantage of large coverage, however the information is available only on selected dates. Depending on the application, a better temporal resolution is necessary. Webcams are ubiquitous and capture numerous avalanche prone slopes several times a day. The cameras mounted in a stable position may even be georeferenced to allow for an exact transfer of the location from the image to a map. To complement the knowledge about avalanche occurrences with more precise release time information, we propose making use of this webcam imagery for avalanche mapping.For humans, avalanches are relatively easy to identify in imagery, but the manual mapping of their outlines is cumbersome and time intensive. To counter this, we propose automating the process with deep learning. Relying on interactive object segmentation we want to extract the avalanche outlines from those images in a time efficient manner with feedback from human experts (in the form of few corrective clicks on an image). We test existing models, searching for the best fit for avalanche outline segmentation. By adapting the best model where necessary we are aiming for outlines of good quality with a low number of clicks. For imagery we rely on current and archive data from our 14 webcams covering the Dischma valley near Davos, Switzerland with imagery available every 30 minutes during the day. Since the images are georeferenced, we may import identified avalanches directly into designated databases and therefore make them available for the relevant stakeholders.On a more long-term perspective, the resulting avalanche outlines will enlarge the webcam training, test and validation dataset and consequently help to fully automate the avalanche outline identification from webcam imagery with object segmentation.
Crustal Structure of the Macquarie Ridge Complex Constrained by the Ambient Noise and Earthquake Autocorrelograms
Authors: Ma Xiaolong , Tkalčić Hrvoje , Eakin Caroline , Rawlinson Nicholas , Pham Thanh-Son , Winder Tom , Pickle Robert , Coffin Millard , Stock Joann ,   Macquarie Ridge 3D Team
Published: February 2023

The Macquarie Ridge Complex (MRC) constitutes the boundary between the Indo-Australian and Pacific plates in the southwest Pacific Ocean. It accommodates the world’s most potent sub-marine earthquakes that are not associated with ongoing subduction. To better understand the nature of MRC and its associated earthquakes, we aim to explore the crustal structures using recordings from island-based stations and ocean bottom seismometers (OBS). In particular, these OBSs, which are deployed in the surroundings of Macquarie Island from October 2020 to November 2021, enable us to image the refined oceanic structures beneath the study area. In this study, we obtain the body-wave reflections by computing phase coherence autocorrelations of both ambient noise and earthquake data. Our preliminary reflection profiles by both methods reveal coherent reflected P waves that may be related to Moho and additional structures within the crust and upper mantle.
Increasing climate awareness through science/communication collaboration: the CMCC multi-platform approach
Authors: Buonocore Mauro , Santin Selvaggia , Carlon Ottavia , Mazzai Alessandra , Michielin Davide , Acierno Arianna , Glauda Agnese , Bassetti Francesco
Published: February 2023

Climate awareness is the starting point for understanding how climate change triggers and contributes to the climate crisis. A public that is aware is made up of citizens who are able to manage the best way to learn about the climate system and its changes and to understand how climate interacts with the individual and collective sphere of each person. Climate awareness provides everything citizens need to play an active role in addressing the negative impacts of climate change on people's lives, seize opportunities and be conscious actors in the present we are living and the future we shape for younger generations. Given the multidisciplinary, cross-cutting and all-comprehensive dimension of the interaction between climate and socio-economic systems (both on a local and global scale), improving Climate awareness requires more than just making reliable information and data available. There is an urgent need for strategic perspectives, critical thinking, and innovative outreach platforms and tools. 
To answer this challenge, the CMCC is implementing an outreach and communication strategy that addresses the complexity of the issue by implementing a multi-platform approach to climate literacy. The target audiences for this approach are as diverse as many social actors are involved in the process of improving their own climate literacy and, thus, contribute to the spread of more advanced climate awareness. These include public opinion as a whole, but specific initiatives and languages should be used to target specific audiences, such as students, journalists, policymakers, and civil society. Thus, the CMCC multi-platform approach addresses the climate crisis in the relationships between target audiences and media in their cultural, social, historical, economic and technological contexts. We present a series of concrete and ongoing initiatives that make up an integrated climate literacy strategy combining storytelling of climate impacts and adaptation solutions, the journalistic vision of a magazine, visual storytelling, podcast, art/science dialogue, science/communication collaboration about IPCC reports and the building of a community/network of climate communication initiatives through a climate communication international award.
Frictional properties and rheological structure at the Ecuadorian subduction zone revealed by the postseismic deformation due to the 2016 Mw 7.8 Pedernales (Ecuador) earthquake
Authors: tian zhen , Freymueller Jeffrey , Yang Zhiqiang , Li Zhenhong , Sun Heping
Published: February 2023

Postseismic deformation following subduction earthquakes includes the combined effects of afterslip surrounding the coseismic rupture areas and viscoelastic relaxation in the asthenosphere and provides unique and valuable information for understanding the rheological structure. Because the two postseismic mechanisms are usually spatiotemporally intertwined, we developed an integrated model combining their contributions, based on 5 years of observations following the 2016 Pedernales (Ecuador) earthquake. The results show that the early, near-field postseismic deformation is dominated by afterslip, both updip and downdip of the coseismic rupture, and requires heterogeneous interface frictional properties. Viscoelastic relaxation contributes more to far-field displacements at later time periods. The best-fit integrated model favors a 45-km thick lithosphere overlying a Burgers body viscoelastic asthenosphere with a Maxwell viscosity of 3 × 1019 Pa s (0.9 - 5 × 1019 Pa s at 95% confidence), assuming the Kelvin viscosity equal to 10% of that value. In addition to the postseismic afterslip, the coastal displacements of sites north and south of the rupture clearly require extra slip in the plate motion direction due to slow slip events that may be triggered by the coseismic stress changes (CSC), but are not purely driven by the CSC. Spatially variable afterslip following the Pedernales event, combined with the SSEs during the interseismic period, demonstrate that spatial frictional variability persists throughout the whole earthquake cycle. The interaction of adjacent fault patches with heterogeneous properties may contribute to the clustered large earthquakes in this area.
The effect of meteorological parameters on PM2.5 pollutant by CCM method in Tehran megacity, Iran
Authors: Roozitalab Soroosh , Ashrafi Khosro , Yahyazadeh Shourabi Kiana
Published: February 2023

Tehran, the capital and most populous city of Iran, is always listed as one of the most air-polluted cities in the world. Nevertheless, it has not received much attention until recent years. Tehran’s PM2.5 (i.e., particulate matters with diameter smaller than 2.5 µm) annual mean concentration in 2022 was 40 µg/m3 and it experienced less than 10 days with clean air. While high emissions are the main reason of air pollution in Tehran, some studies have suggested that meteorology is also another major driver of its air pollution. Here, we investigate the correlation between PM2.5 and different meteorological parameters such as temperature, wind speed, visibility, relative, humidity, and dew point temperature. In particular, we use Multiple Linear Regression and CCM (Convergent Cross Mapping) statistical methods to analyze the ground measurements data for one year. Our primary results show that, several meteorological parameters have a significant impact on PM2.5 concentrations. The findings of this study helps characterizing the source of air pollution in Tehran.
Towards the next generation of tropospheric composition sounding: the NASA TRopospheric Ozone and its Precursors from Earth System Sounding (TROPESS)
Authors: Bowman Kevin
Published: February 2023

The past two decades have been the golden age of tropospheric composition sounding with instruments like the Tropospheric Emission Spectrometer (TES), the Infrared Atmospheric Sounding Interferometer (IASI), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY),  the Ozone Mapping Interferometer (OMI) harnessing spectral radiation from the thermal infrared to the ultraviolet to pioneer new products such as tropospheric ozone, ammonia, methane, nitrogen dioxide, and water vapor deuterium.  As a new generation of sounders that include both geostationary and low earth orbiting satellites become the anchor of a global air quality monitoring system, there is an urgent need to shift away from an instrument focus, which is a confined to a  band of frequencies,  to a measurement focus, which incorporates the best available information.  The TROPESS project is a new measurement focused approach that uses a common retrieval algorithm applied to a suite of instruments either singularly or in combination.  Building on the heritage of TES, we show how the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES) algorithm has been applied to produce ozone from TES, AIRS, and OMI as well as its potential to combine CrIS and TROPOMI radiances.  Employing proven optimal estimation techniques, we further show how data produced from MUSES can be ingested into chemical data assimilation providing a comprehensive understanding of global atmospheric chemistry and its evolution.  The suite of products and their scientific impact on atmospheric composition are surveyed.  TROPESS points to a new paradigm that can effectively harness a constellation of data to quantify the rapid changes in the landscape of emissions and their impact on air quality and climate. 
Spatial Variability of Leaf Area Index from Drone Imaging of Two Irrigated Wheat Fields
Authors: Hopkins Austin , Hansen Neil , Jensen Ryan , Flint Elisa
Published: February 2023

Leaf Area Index (LAI) is an indicator of crop and plant growth in agricultural and ecological research. LAI can be used to monitor nitrogen status or estimate crop yield and evapotranspiration (ET). The aim of this study was to evaluate use of a remotely sensed visible vegetation index to characterize the spatial variability of LAI within irrigated wheat fields. Variation of LAI was measured with a ceptometer on random nested grids at two sites with pre-determined management zones in 2019 and 2020. Coincident digital imagery was collected using a consumer-grade unmanned aerial vehicle (UAV). A visible atmospherically resistant index (VARI) LAI estimation model was applied to red, green, blue (RGB) UAV imagery using a ladder resampling approach from 0.06 m to 3 m spatial resolution. There was significant within-field spatial and temporal variation of mean LAI. For example, in May at one of the sites, measured LAI ranged from 0.21 to 2.58 and in June from 1.68 to 4.15. The relationship of measured and estimated LAI among management zones was strong (R2=0.84), validating the remote sensing approach to characterize LAI differences among management zones. There were statistically significant differences in estimated LAI among zones for all sampling dates (P=0.05).  We assumed a minimum difference of 15% between zone LAI and the field mean for justifying variable rate irrigation among zones, a threshold that corresponds with approximately a 10% difference in evapotranspiration rate. Three of the five sampling dates had LAI differences that exceeded the threshold for at least one zone, with all three having mean LAI of less than 2.5. The VARI model for estimating LAI remotely is more effective at identifying LAI differences among management zones at lower LAI.
Studying air pollution and weather feedbacks from wildfires over Greece using WRF-Chem
Authors: Rovithakis Anastasios , Voulgarakis Apostolos
Published: February 2023

Wildfires are a major source of atmospheric aerosols and can have significant impacts on air quality and radiative forcing. In our work, we have utilized the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to study the impact of wildfires on aerosol pollution and meteorological feedbacks, focusing on the geographical area of Greece as a test case. We focus on the summer season of 2021, during which intense wildfire activity occurred in the country. We have performed sensitivity experiments with and without emissions from fires as a way to quantify the impact of such emissions on atmospheric pollutants, AOD, radiative forcing and weather variables (temperature, humidity, winds). Our results show that wildfires can have a significant impact on AOD, with the magnitude of the effect depending on the size and intensity of the wildfire and the meteorological conditions. Our recent work has shown that fire prone areas determined using the FWI index seem to link closely with the areas in Greece with the highest burnt area. Since the emitted aerosols are an important parameter, we test how well the emissions correlate to the FWI. Overall, our work demonstrates the potential role of wildfires in the evolution of short-term weather conditions via fire pollution radiative forcing, and provides new insights into the mechanisms leading to such effects.
Inundation and water quality assessment of the Karun river before and after flooding using remote sensing
Authors: Yahyazadeh Shourabi Kiana , Niksokhan Mohammad Hossein , Roozitalab Soroosh
Published: February 2023

Natural hydrological phenomena such as floods are among the most crucial hazards, damaging both urban and rural areas. River floods not only result in human and financial losses, but also alter the quality parameters and biological diversity of the river. Karun is one of the largest and wettest rivers in Iran, and its basin experiences numerous floods every year. In this work, satellite data are used to examine how floods affect the Karun River's quality. Specifically, we use NDWI (Normalized Difference Water Index), NDCI (Normalized Difference Chlorophyll Index), and NDTI (Normalized Difference Turbidity Index) data from Sentinel-2 Optical satellite to assess the water quality before and immediately after flooding. Additionally, Sentinel-1 Synthetic-aperture radar (SAR) satellite data are used to observe changes in the river bed and its inundation. This study demonstrates how Sentinel-2 and Sentinel-1 satellites could be effectively used to study variations in water quality and waterbodies at various periods. The results also show how the waterbody and water quality change before and after the flood.
Towards a new era in giant exoplanet characterisation
Authors: Müller Simon , Helled Ravit
Published: February 2023

Determining the composition of giant exoplanets is crucial for understanding their origin and evolution. However, the planetary bulk composition is not measured directly but must be deduced from a combination of mass-radius measurements, knowledge of the planetary age and evolution simulations. Accurate determinations of stellar ages, mass-radius, and atmospheric compositions from upcoming missions can significantly improve the determination of the heavy-element mass in giant planets. In this talk, we first demonstrate the importance of an accurate age measurement, as expected from Plato, in constraining the planetary properties. Well-determined stellar ages can reduce the bulk-metallicity uncertainty up to about a factor of two. We next infer the bulk metallicity of warm giants from the Ariel mission reference sample and identify the Ariel high-priority targets for which a measured atmospheric metallicity can clearly break the degeneracy in the inferred composition. We show that a knowledge of the atmospheric metallicity can broadly reduce the bulk-metallicity uncertainty by a factor of four to eight. We conclude that the accurate age determination from Plato and atmospheric measurements by Ariel and the James Webb Space Telescope will play a key role in revealing the composition of giant exoplanets.
Uncertainty quantification with a physics-based machine learning method for geothermal-well targeting: A case study of The Hague, Netherlands
Authors: Santoso Ryan Kurniawan , Degen Denise , Knapp Dominique , Pechnig Renate , Wellmann Florian
Published: February 2023

Drilling of production and injection wells for geothermal exploitation requires accurate knowledge of subsurface structures and processes related to fluid flow and heat transport, reactive transport, and mechanical processes. Since the number of exploration wells is limited, proper characterization of subsurface properties and structures is challenging. Therefore, quantifying uncertainties is essential for estimating the risk in selecting the location of suitable production and injection wells to increase the chance of profitable outcomes.Uncertainty quantification is often conducted within a probabilistic framework which demands numerous forward model runs. It poses a computational challenge for geothermal applications since many geothermal subsurface models are high-dimensional due to covering a wide range of parameters and utilizing fine meshes to capture complex structures and address coupled processes. In this study, we introduce the use of the non-intrusive reduced-basis method (NI-RB), a physics-based machine learning method, to enable uncertainty quantification also for high-dimensional models. The NI-RB is a model-order reduction (MOR) technique that expresses a physical solution in a linear combination of basis functions and weights. The NI-RB preserves the structure of the physics in the basis functions and uses a machine-learning model to calculate the weight for each basis function. With this method, we can guarantee physical consistency with respect to a full Finite Element simulation in the prediction phase and gain significant speed-ups to enable probabilistic uncertainty quantification analyses.As a test of feasibility, we use the model of The Hague case (in the Netherlands) to illustrate an uncertainty quantification with a physics-based machine learning method. With the use of this approach, we gain a significant computational speed-up for predicting a new temperature state, from 10 minutes in High-Performance Computing (HPC) infrastructures with 48 cores to 1 millisecond on a conventional laptop with a single core. It, therefore, enables performing a robust uncertainty quantification on such a high-dimensional model in only 30 minutes with 3 million realizations. The trade-off is on time required for preparing training samples for training the machine learning model. The selected training samples must be representative for the desired parameter ranges. We can, then, characterize the temperature distribution at any location with its uncertainty level. This information is valuable for a careful selection of the location of suitable production and injection wells and estimate the possible economic loss.    
Probing the foreshock wave boundary
Authors: Dorfman Seth , Zhang Kun , Turc Lucile , Ganse Urs , Palmroth Minna
Published: February 2023

Foreshock ultralow frequency (ULF) waves play an important role in the dynamics upstream of planetary bow shocks and can affect the downstream magnetosheath region.  Due to limited available spacecraft measurements, the waves are often analyzed with incomplete information about their overall spacial structure. Common wave vector analysis techniques built around these limitations often invoke the divergence free condition of the magnetic field without considering the possibility that the wave amplitude profile could have a strong spacial dependence.  We explore the consequences of this assumption in the Earth's ion foreshock using both ARTEMIS spacecraft data and a 2-D hybrid Vlasov simulation conducted using the Vlasiator code.  The observed foreshock ULF waves have a finite extent in the direction perpendicular to the Interplanetary Magnetic Field, and incorrect application of standard techniques at the boundary yields a false wave vector orientation that may be used as a novel edge detection method.  Our results stand as a cautionary tale for wave analysis in other space physics contexts where the wave geometry is less clear.Supported by NASA Grant 80NSSC20K0801. Vlasiator is developed by the European Research Council Starting grant 200141-QuESpace, and Consolidator grant GA682068-PRESTISSIMO received by the Vlasiator PI. Vlasiator has also received funding from the Academy of Finland. See www.helsinki.fi/vlasiator
Characteristics of Large-Scale and Localized Droughts in the Gangetic Plains
Authors: Chandra Chamarthi Sarat , Vuruputur Veungopal , Muddu Sekhar
Published: February 2023

The groundwater depletion over the past two decades in the Indo-Gangetic Plains has been extensively documented. On a smaller scale, the Bundelkhand sub-region (rectangular box in the Figure) has been experiencing an extended period of meteorological drought. In this region, as with a majority of the Gangetic Plains, the contribution of local evaporation is comparable to the moisture brought in from afar.  It is unclear whether the below-normal rainfall in this region is due to low-frequency climate variability or a result of a "negative" feedback loop in the regional hydrologic cycle where less rain leads to less soil wetness, which in turn leads to lower evaporation and less moisture available for rain. An analysis of this region's daily rainfall records from the past century shows that while most droughts in and around Bundelkhand coincide with larger-scale Indian monsoon droughts (Type-1 in the Figure), some appear to be localized (Type-2 in the Figure). In addition, our analysis shows that while north central India typically experiences a rainfall deficit in early July, western India often sees more than normal rainfall. We present our assessment of the causes of these droughts, including the role of local hydrology and potential large-scale drivers. 
A Missing Dusk-side Loss Process in the Electron Ring Current
Authors: Haas Bernhard , Shprits Yuri Y. , Wutzig Michael , Wang Dedong , Szabó-Roberts Mátyás
Published: February 2023

The Earth’s magnetic field traps charged particles which are transported longitudinally around Earth, generating a near-circular current, known as the ring current. While the ring current has been measured on the ground and space for many decades, the enhancement of the ring current during geomagnetic storms is still not well understood, due to many processes contributing to its dynamics on different time scales. The low energy part of the ring current of 10-50 keV is responsible for surface charging effects on spacecraft, potentially causing satellite anomalies.Here, we show that existing ring current models systematically overestimate the in-situ satellite measurements of the Earth’s night side electron ring current during geomagnetic storms. By analyzing electron drift trajectories during the storm onset, we show that this systematic overestimation of flux can be explained through a missing loss process which operates in the pre-midnight sector. Quantifying this loss reveals that the theoretical upper limit of strong diffusion has to be reached in a broad region of space in order to reproduce the observed flux. We include this missing loss process and show that predictions of electron flux can be significantly improved. Identifying missing loss processes in ring current models is vital to accurately predict storm time dynamics and the associated hazards, that result from a delicate balance of source and loss processes.
Personal air pollution exposure assessment using wearable sensors
Authors: Ye Sheng , Ziemann Melanie , Wenig Mark
Published: February 2023

Air quality have become a global issue with increasing attention. There is a growing concern in the public about both in- and outdoor air quality. In order to monitor individual air pollutants exposure in real-time, we developed several wearable air quality monitoring devices to study personal exposure to different pollutants in different environments. The devices are equipped with different type of sensors to measure NO2, aerosols, CO2, etc, in addition to environmental parameters sensor to measure temperature, relative humidity and pressure. In order to optimize the accuracy, we compared different retrieval approaches such as multiple linear regression, generalized linear model, neural network, etc. This allows us to perform the personal exposure study with a high temporal resolution in the order of seconds. We classified daily activities into different categories: different ways of commuting such as bus, tram, subway, bicycle, on foot; indoor activities like cooking, lighting candles, etc.; outdoor exercises next to busy street, in a park, etc. In this presentation, we will present our first result of this personal exposure study.
Mediterranean Sea Crustal Structure from Potential Fields, Results of XORN Project
Authors: Sampietro Daniele , Capponi Martina , Thébault Erwan , Gailler Lydie
Published: February 2023

The Mediterranean Sea crust has been intensely studied both for scientific reasons and for economic activities such as natural resources exploration and exploitation. However, a complete high-resolution numerical model of the crust over the whole region is still missing. In fact, from the one hand, we have global crustal models, which however are usually too coarse to accurately describe this complex area, while on the other hand we have continental scale models, which are obtained by merging different datasets, without an homogeneous analysis.In the current study we perform a joint inversion of gravity and magnetic field measurements, constrained with seismic profiles, on the whole Mediterranean Sea Area with a spatial resolution of about 15 km in the planar direction and ranging from 200 m to 1200 m in the vertical one, for a total of more than 2-million cells.The inversion has been carried out within the XORN project (https://xorn-project.eu/) funded by the European Space Agency. The result of the study is a complete three-dimensional (3D) model of the crust beneath the Mediterranean Sea region in terms of density and magnetic susceptibility distributions and geological horizons, completed by an estimate of the predicted accuracy.Several maps, such as depth of main geological horizons (namely the base of Plio-Quaternary and Messinian sediments, the basement, the Curie isotherm, and the Moho), have been derived, from the 3D model.The model has been validated through comparisons with local studies, seismic information, heat flow data not used within the inversion.
Effects of groundwater fluctuations on nutrient transformation in riparian sediments in a Mediterranean catchment - Column study
Authors: Willert Fabian , Roumelis Christian , Scaccia Maria , Carrera Jesús , Folch Albert , Bernal Susana , Salgot Miquel , Insalaco Alycia , Welch Susan , Gabor Rachel , Sawyer Audrey H.
Published: February 2023

A clear need exists to understand the role that water table fluctuations play in mobilizing nutrients in soils and shallow groundwater near streams, particularly in dry Mediterranean watersheds, which experience marked wetting and drying seasonal patterns. As groundwater level varies, so does the supply of inorganic nitrogen and organic carbon from different soil layers, which affects processes such as coupled nitrification-denitrification and the chemistry of groundwater that flows to streams. Along discharging groundwater flow paths, carbon-rich soils release dissolved organic carbon (DOC), which biogeochemically reacts with nitrogen (N) and oxygen (O) as groundwater levels rise and become saturated. For understanding the biogeochemical dynamics in N at the interface between soils and groundwater, a cylindrical, meter-long polyvinyl chloride (PVC) soil column was constructed and filled with heterogeneous soil and aquifer layers of decreasing organic matter with depth. A cyclical water level cycle was imposed for 16 days using influent to the column from local groundwater at the experimental site with < 1 mg nitrate-N/L. Water table dynamics were monitored with a pressure sensor, tensiometer, and two soil moisture sensors. Vertical arrays of redox sensors and pore water samplers were used to observe changes in pore water chemistry. Water samples were analysed for pH, ammonium-N (NH4-N), nitrate-N (NO3-N), nitrite-N (NO2-N), and DOC. Soil samples were taken for microbial activity and solid chemistry analysis. Near the soil-aquifer transition, nitrate accumulates under aerobic conditions and DOC from organic matter is mobilized under anaerobic conditions. Preliminary pore water analysis shows that during wetting cycles, there is an increase in dissolved inorganic N (NO3+NO2) near the surface (57 mg N/L at 40 cm depth) but a decrease in DIN concentrations in deeper layers (0.92 mg N/L at 55-100 cm depth), suggesting that nitrification and denitrification processes stratified with depth. The results illustrate the significance of groundwater level fluctuations on DIN and DOC cycling and mobilization in Mediterranean riparian soils during wetting events.
McPrA - a new trace gas profile retrieval algorithm for MAX-DOAS
Authors: Zheng Jiangyi , Xie Pinhua , Tian Xin , Xu Jin , Li Ang , Ren Bo , Hu Feng , Hu Zhaokun , Lv Yinsheng , Zhang Zhidong
Published: February 2023

Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) has been widely used in the three-dimensional monitoring of air pollutants. It is of great significance for MAX-DOAS to reconstruct the state of air pollutants by establishing an accurate vertical profile retrieval algorithm. At present, the profile retrieval algorithm of MAX-DOAS mainly adopts the iterative method based on a priori profile, which leads to strong dependence on priori profiles. We try to reduce the dependence on priori profiles by first calculating the vertical column density and then calculating the vertical distribution from observation. Therefore, we propose a new MAX-DOAS trace gas profile inversion algorithm - McPrA (Monte Carlo profile inversion algorithm by Anhui Institute of Optics and Fine Mechanics (AIOFM)). The algorithm uses Monte Carlo method to solve the optimal estimation problem of the gas profile. Firstly, the gas vertical column density is obtained through the air mass factor calculated by the radiative transfer model SCIATRAN. Secondly, the vertical distribution of trace gas is retrieved by combining the weight function with the a priori profile. Besides, we introduce the normalization process in the vertical distribution solution to make the prior profile better match the weight function. McPrA can set the vertical resolution of profile by modifying the grid, and we increase the vertical resolution of gas profile to 50m. By conducting sensitivity experiments on parameters such as Monte Carlo sampling, covariance matrix and the priori profiles, the optimal configuration of retrieval parameter is obtained. At the same time, the degree of freedom is more than 3.0. Finally, comparative verification experiments were carried out to compare with in situ data from LP-DOAS and National Air Quality Monitoring Station. The correlation coefficient for NO2 VMR at the first layer retrieved by McPrA in 50 m grid reached above 0.89. The comparison of NO2 profiles retrieval by McPrA with that from WRF-Chem and simulation of synthetic data also shows that McPrA algorithm can retrieve trace gas profiles accurately.
Building and road segment scale fossil fuel CO2 emissions estimation across multiple US cities spanning the 2010-2021 time period
Authors: Gurney Kevin , Dass Pawlok , Kato Anna , Mitra Bhaskar , Roest Geoffrey
Published: February 2023

The Hestia Project estimates fossil fuel carbon dioxide (FFCO2) emissions to the scale of buildings, factories, and road segments for whole cities every hour. Recent updates to the Vulcan Project (version 4) are now realized in 3 large urban domains in the US: the LA Megacity, the NE corridor (Washington DC to Baltimore and beyond) and the city of Indianapolis. Here, we present the latest developments in the estimation from these 3 urban areas and apply a series of hypothetical mitigation efforts, demonstrating the enabling features of high space/time resolution urban FFCO2 emissions estimation. Furthermore, we analyze the spatial patterns of emissions and place them in the context of indicators of social and environmental justice.
High-resolution 3-D geophysical imaging across a seismogenic fault: the TEst Site IRpinia fAult (TESIRA) project
Authors: Bruno Pier Paolo Gennaro , Ferrara Giuseppe , Improta Luigi , Maraio Stefano , Di Fiore Vincenzo , Iacopini David , Fusco Mario , Punzo Michele , Paoletti Valeria , Cavuoto Giuseppe , De Martini Paolo Marco
Published: February 2023

The scientific project TESIRA (TEst Site IRpinia fAult), funded in 2021 by the University of Naples “Federico II”, aims at acquiring multidisciplinary geophysical data above an active fault in an intramontane basin of the Southern Apennines and to achieve, through the integration of this multivariate dataset, an accurate 3D geophysical imaging of the shallow structure of the fault zone in order to understand the link between shallow faulting and petrophysical changes, which affect rock permeability and surface degassing. The target structure is the southern branch of the Irpinia Fault, one of the structures with highest seismogenic potential in the Mediterranean region, causing the 4th Italian earthquake of last century (1980, Ms=6.9, Pantosti & Valensise, 1990) and generating a modest surface throw at Pantano San Gregorio Magno (Salerno).A microgravimetric survey and a 3D and 2D Electrical Resistivity measurements survey were acquired between September 2021 and January 2022. 3D seismic data were acquired in July 2022, using two overlapping arrays with a dense geophone distribution covering an area of about four hectares, with a detail of 2.5x2.5m. Moreover, four 2D seismic profiles intersect the 3D volume. An aeromagnetic survey, an extension of the gravimetric survey and a sampling of the CO2 surface degassing will be completed within this year. We will show the preliminary results of the individual surveys. Later, the different geophysical and geochemical measurements will be integrated using cooperative inversion and machine learning techniques.  We hope that this multidisciplinary approach will provide a more comprehensive understanding of the interaction between surface faulting and basin development in this key area of the Southern Apennines. ReferencesPantosti, D.; Valensise, G.; [1990] Faulting Mechanism and Complexity of the November 23, 1980, Campania-Lucania Earthquake, Inferred From Surface Observations, JGR, 95, 319-34
Monitoring surface flow velocities at hydraulic barriers in a bedrock canyon
Authors: Saletti Matteo , Wright Morgan , Hurson Max , Byrnes Evan , Robinson Kendra A. , Patterson David A. , Venditti Jeremy G.
Published: February 2023

Several species of Pacific Salmon migrate upstream every year in the Fraser River (British Columbia, Canada) to reach their spawning grounds. A large portion of the fish get delayed in specific sections of the river, where the morphology and the flow create sections with high flow velocity, high turbulence and jumps in bed elevation that constitute hydraulic barriers. Several fish populations migrate along the Fraser River and any barrier for their passage (created by the river morphology, the flow structure or a localized landslide) can severely endanger the survival of such species, while also impacting indigenous communities for which fish is a fundamental element. In the Fraser River those hydraulic barriers have been identified but not yet thoroughly studied. Here we present results from an extensive monitoring campaign conducted in the last 3 years to measure surface flow velocities in previously identified hydraulic barriers. We selected segments of the Fraser Canyon where distributions of surface flow velocities due to specific river morphologies are potentially impacting fish passage. These include areas where series of constriction-pool-widenings create plunging flows, bedrock step rapids and overfalls. In such areas we collected video of surface flows (with fixed field cameras and drones) at high frequency during the freshet season and obtained surface flow velocity maps using Large Scale Particle Image Velocimetry (LSPIV) for different values of flow discharge. Using this extensive dataset, we can detect how stable coherent flow structures are for different flow depths and flow discharges and we are also able to identify which areas are most problematic for fish passage (and for which values of flow), helping fish management agencies and public authorities to better protect the survival of vital species in British Columbia.  
Exploring and modeling the formation of desiccation cracks in Opalinus Clay at field scale
Authors: Cajuhi Tuanny , Ziefle Gesa , Maßmann Jobst , Yoshioka Keita
Published: February 2023

Opalinus Clay (OPA) has been one of the main focuses of international geoscientific research due to its potential use as a host rock for the storage of heat-generating radioactive waste. In-situ experiments taking place in the Mont Terri Rock Laboratory in Switzerland provide valuable insights into the material properties and behavior of OPA. The Cyclic Deformation (CD-A) experiment has been conducted since October 2019 in the rock laboratory to investigate hydro-mechanical effects through long-term direct and indirect measurements such as resistivity, water content, suction, and crack development. Desaturation effects due to variations in relative air humidity induced by ventilation and seasonal changes, drive the formation of desiccation cracks at the walls of the CD-A niches.We use a mathematical model based on a macroscopic poromechanical and on the phase-field approaches to compute desiccation. The formulation consists of the balance equations of the solid and liquid phases and of the crack phase-field evolution equation. Within this combined framework, we are able to account for the drying of the niche and for desiccation cracks. Our solution scheme is implemented in the open-source finite element software OpenGeoSys (OGS 6).In this contribution, we discuss the practical steps for applying the poromechanical phase-field approach at in-situ scale. The basic steps consist of determining the material properties and computing the fracture energy and characteristic length. Moreover, we use field data concerning the crack aperture to deduce the crack resolution for the simulations. The model setup consists of a quarter cross-section of a CD-A niche. We compare the modeled crack response with the monitored cracks at field scale and evaluate whether they initiate and propagate according to the monitored relative air humidity range. Furthermore, we assess the impact of randomly distributed material properties, e.g. fracture energy, and changes in permeability due to cracking.
Future drought prediction using time-series of drought factors and the US drought monitor data based on deep learning over CONUS
Authors: Son Bokyung , Lee Jaese , Im Jungho , Park Sumin
Published: February 2023

Predicting future drought conditions is crucial for preventing massive agricultural and/or hydrological resource damage caused by drought. This study predicts future (in this case, 3-month forecast lead time) drought conditions in the contiguous United States, especially focusing on five different dry and drought severity classes indicated by the United States Drought Monitor (USDM) during 2000-2020. A deep learning model was trained using the time-series of USDM and four different types of drought-related variables (i.e., hydro-meteorological variables) such as precipitation and temperature from Phase 2 of the North American Land Data Assimilation System. UNet, one of the image-to-image translation techniques, was used as a basic deep learning architecture to consider the spatial characteristics (extents of each drought severity class) of drought across the continent. As drought classes in USDM are ordinal, the loss function of the deep learning model was set to be able to consider ordinal problems utilizing the cross-entropy loss function. The results of the proposed model were compared to the existing seasonal drought outlooks provided by the National Oceanic and Atmospheric Administration Climate Prediction Center. The performance for the validation period (2 years) showed an overall accuracy of about 65%. When compared to the seasonal outlooks, it demonstrated about a 6% improvement in terms of overall accuracy for changing drought conditions. Future research will further discuss the performance of the proposed model with other comparable reference data and the impact of each input variable to predict future drought conditions.
Attributing heatwaves to climate change in mountainous areas. An analysis of the summer 2022 heatwaves in the Pyrenees
Authors: Lemus-Canovas Marc , Gonzalez-Herrero Sergi , Trapero Laura , Albalat Anna , Insua-Costa Damian , Senande-Rivera Martin , Miguez-Macho Gonzalo
Published: February 2023

The field of extreme event attribution (EEA) seeks to quantify how recent extreme events are directly exacerbated by ongoing climate change. As this is a relatively new field in climate science, there is a noticeable knowledge gap in EEA analysis in mountain areas. Precisely, this work performs an attribution to climate change of the two greatest heatwaves (HWs) occurred during June and July 2022, both hitting the Iberian Peninsula and southern France, and therefore, the Pyrenees Mountain range. We used the analogues technique on 500 hPa geopotential height composites to identify the 30 days closer to the dynamical structure of both heatwaves for the counterfactual (1950-1985) and factual (1986-2021) period, using ERA5 daily data. Results showed that factual HWs analogues in the factual period have a spatial structure closer to the 2022 HWs events than those analogues extracted from the counterfactual period. At the Pyrenean scale, we observed that 2-meter air temperature differences consisted of a positive non-uniform pattern in a factual world, with a significant increase in the southern slope of the mountain range and in the nearby depressed areas. However, most of the mountain range exhibited a small increase of the HW air temperature in a factual world. We also provided an explanation of the physical process involving the abovementioned 2-meter air temperature differences. In this study, we revealed the complexity of conducting the attribution of extreme heatwaves to climate change in mountain areas, both because of the scarcity of in-situ data, as well as due to the physical processes involved during these extreme events in an area of complex terrain.