bluuebunny/crossref_metadata_2025 huggingface dataset:
Source of the 2023 Morocco Earthquake (Mw6.8) inferred by analysis of Seismic and Geodetic Data
Authors: Caldeira Bento , Buforn Elisa , Oliveira Rui , Bezzeghoud Mourad , Borges José , Hamak Ines
Published: March 2024

On September 8, 2023, at 22:11 UTC, a seismic event of magnitude Mw6.8 (according to the USGS) occurred near the village of Talat N’Yaaqoub, Al Haouz province, in the High Atlas region of Morocco. This earthquake had a profound impact, violently shaking the entire area within a radius of over 70km from the epicentre. More than 78,000 buildings were severely damaged, resulting in approximately 5,600 injuries and around 3,000 fatalities. A considerable portion of the affected population resides in buildings seismically vulnerable and limited access to resources for mitigating such risks. This incident stands out as a significant earthquake in a region characterized by a low deformation rate and generally considered to have low seismic activity. Testimonies collected by CSEM reveal that the seismic vibrations were felt not only in the High Atlas but also by people in a wider area extending to Algeria, southern Spain, and Portugal.This study presents the preliminary results obtained from a comprehensive investigation of the earthquake's source. The analysis is based on the interpretation of seismic and geodetic data, employing a combination of the following methods: (1) inversion of the seismic moment tensor to determine fault plane geometry and hypocenter depth, (2) waveform inversion using a finite source model to assess spatiotemporal slip distribution, (3) modeling of surface strain field produced by the slip distribution model. The validation of the rupture model was performed by comparing the synthetic surface deformation field with the observed field obtained through the geospatial InSAR method.Acknowledgement: The work was supported by the Portuguese Foundation for Science and Technology (FCT) project UIDB/04683/2020 - ICT (Institute of Earth Sciences).
Ice-marginal lava delta in Iceland found on a nondescript shallow slope: An unexpected record of ice thickness late in deglaciation
Authors: Putnam Audrey , Siebach Kirsten , Bedford Candice , Simpson Sarah , Rampe Elizabeth , Tamborski Joseph , Thorpe Michael
Published: March 2024

Volcanism increases when glaciers melt because isostatic rebound during deglaciation decreases the pressure on the mantle, which enhances decompression melting. Anthropogenic climate change is now causing ice sheets and valley glaciers to melt around the world and this deglaciation could stimulate volcanic activity and associated hazards in Iceland, Antarctica, Alaska, and Patagonia. However, current model predictions for volcanic activity associated with anthropogenic deglaciation in Iceland are poorly constrained, in part due to uncertainties in past volcanic output over time compared to ice sheet arrangements. Further work specifically characterizing glaciovolcanic and ice-marginal volcanoes in Iceland is needed to reconstruct volcanic output during time periods with changing ice cover. Here, we describe a previously unrecognized ice-marginal volcanic lava delta on a broad, shallow slope southeast of Langjökull and the Jarlhettur volcanic chain in Iceland’s Western Volcanic Zone. Although previously mapped as interglacial lavas and sediments, canyons in this area revealed two ~20-30 meter-thick southwest-dipping sequences of pillow-bearing tuff-breccias between pāhoehoe lava flows above modern lake Sandvatn. Clasts within the tuff-breccias include a mixture of pillow lavas and pāhoehoe fragments, requiring that the subaqueous tuff-breccia facies were derived from subaerial flows. The upper subaqueous to subaerial transition in this sequence occurs around 400 m above sea level, much higher than any local topography that could dam water or the highest Icelandic marine transgression, necessitating ice damming. Quenched meter-scale cavities in coherent lava and cube-jointed facies show lava-ice contact, supporting evidence for an ice dam. We propose that an eruption melted through thin ice near Skálpanes during a deglacial period and lavas flowed downslope to the south, melting ice and forming an englacial lake. We constrain that the local ice thickness was tens of meters to a few hundred meters thick. This would represent a similar ice configuration as some interpretations of the ice extent at the time of formation of the Buði moraines around 11.2 ka, with higher ice flow down the valley of the Hvita river than off Langjökull, although it occurred during an earlier deglaciation. Importantly, this finding demonstrates that ice-marginal deposits that can provide paleo-environmental constraints may be hidden in terrains that do not conform to existing classifications of glaciovolcanic edifices.
Tropical cyclone intensity estimation using two geostationary satellite data and deep learning
Authors: Jung Hyeyoon , Moon Il-Ju , Kim Dong-Hoon
Published: March 2024

Tropical cyclones (TCs) are among the most severe and destructive natural events, and they have a major detrimental impact on both the economy and society. This study used Geo-KOMPSAT-2A (GK2A) satellite data to estimate TC intensity in the western North Pacific based on a convolutional neural network (CNN) model. Given that the GK2A data cover only the period since 2019, we applied transfer learning to the model using information learned from previous Communication, Ocean, and Meteorological Satellite (COMS) data, which cover a considerably longer period (2011–2019). Transfer learning is a powerful technique that can improve the performance of a model even if the target task is based on a small amount of data. Experiments with various transfer learning methods using the GK2A and COMS data showed that the frozen–fine-tuning method had the best performance due to the high similarity between the two datasets. The test results for 2021 showed that employing transfer learning led to a 20% reduction in the root mean square error (RMSE) compared to models using only GK2A data. For the operational model, which additionally used TC images and intensities from six hours earlier, transfer learning reduced the RMSE by 5.5%. Because continuous long-term data are not always available for TC intensity estimation based on geostationary satellite images, these results imply that transfer learning may constitute a new advance in this area.
Acknowledgement. This research was supported by Korea Institute of Marine Science & Technology Promotion (KIMST) funded by the Korea Coast Guard (RS-2023-00238652, Integrated Satellite-based Applications Development for Korea Coast Guard).
 
Evidence of magnetic reconnection observed in the heliosheath by Voyager-2
Authors: Turner Drew , Zhao Lingling , Eriksson Stefan , Lavraud Benoit , Richardson John , Opher Merav
Published: March 2024

We present new evidence of active magnetic reconnection observed by Voyager-2 in the heliosheath region beyond the termination shock in the outer heliosphere. Multiple cases have been identified in which significant plasma jets are present during heliospheric current sheet crossings, or sector reversals. Using a combination of the plasma and magnetic field measurements from Voyager-2, candidate events are identified by rotating the magnetic field and plasma velocity vector data into a minimum-variance, LMN-coordinate frame, prior to checking consistency with the Walen relation on the corresponding plasma jet. In the LMN frame, the candidate events are selected based on consistency with the expected geometry of current sheets undergoing magnetic reconnection. The Walen relation further supports consistency with the physics of magnetic reconnection, in which the outflow jets of reconnected field and plasma are ejected from the reconnection site at the Alfvén speed. Error analysis based on limitations of the Voyager-2 data is accounted for throughout the process. In this presentation, we detail the event identification and walk through an example case before presenting several other cases. All combined, confirmation of active magnetic reconnection ongoing in the heliosheath has important implications concerning the heating of plasma in the outer heliosphere and the acceleration of pickup ions and possibly even anomalous cosmic rays.
The risk to global coffee supply from synchronous climate hazards
Authors: Richardson Doug
Published: March 2024

Global coffee production is at risk from synchronous crop failures, characterised by widespread reductions in yield occurring in multiple regions at the same time. For other crops, we know that these synchronous failures can be forced by spatially compounding climate anomalies, which in turn may be driven by large-scale climate modes like the El Niño Southern Oscillation (ENSO).This talk will discuss the extent to which climate hazards occur and co-occur across the world’s major coffee-growing regions. These climate hazards include temperature and rainfall anomalies and are selected to cover two coffee species and different periods of the crop growing cycle. The talk will show that regional and global risk posed from spatially compounding hazards has increased over recent decades. There is a clear shift in the profile of this risk. Temperature-based hazards are now much more likely to exceed thresholds for optimal growing conditions, rather than being overly cold as observed during the 1980s.Through multiple lines of evidence we find relationships between spatially compounding hazards and six tropical climate modes such as ENSO and the Madden Julian Oscillation. Individual regions exhibit differing relationships with these modes. ENSO is found to have the strongest links with multiple regions during the same crop cycle, posing implications for ENSO-driven global impacts to supply.
Assessment of thermal noise impact on sea ice classification using Sentinel-1 images and U-Net
Authors: Huang Yan , Yang Xiaofeng
Published: March 2024

Sea ice poses a significant threat to high-latitude navigation and offshore operations. Accurate and timely classification of sea ice is crucial for ensuring the safety of maritime activities in polar regions. Synthetic aperture radar (SAR) is widely used for sea ice classification due to its high resolution and all-weather observation capability. However, the Sentinel-1 extra-wide (EW) swath mode images, which are commonly used to monitor sea ice in the polar region, exhibit thermal noise in the cross-polarization images, and it is thought to affect the accuracy of sea ice classification models. In this study, we used Sentinel-1 EW mode images and a deep learning (DL) model, U-Net, to investigate the impact of thermal noise on sea ice classification. Sensitivity experiments were conducted for the U-Net and the comparison models, such as support vector machine (SVM), random forest (RF), and convolutional neural network (CNN), with or without using a denoising method for cross-polarization images. Both co-polarization and cross-polarization images were used to train these models. The experimental results indicate that SVM, RF, CNN, and U-Net achieved classification accuracies of 67.98%, 77.96%, 86.49%, and 90.00% respectively, using undenoised images. The classification accuracies improved to 71.69%, 80.75%, 86.65%, and 90.73% respectively after the denoising method was used. The SVM and RF models show an increase in accuracy of about 3%, while the CNN and U-Net models show an improvement of less than 1%, suggesting that CNN and U-Net are more tolerant to noise when used for sea ice classification.
Role of Vegetation in mitigating urban heat risk in Twelve American Cities - Applying the ARIES Modelling Approach
Authors: Kumar Sudeshna , Marquez Alba , Aznarez Celina , Jenerette G Darrel , Bidoia Marco , Ibsen Peter C , Bagstad Ken , Balbi Stefano , Villa Ferdinando
Published: March 2024

The anthropogenic urban realm exacerbates surface urban heat island (UHI) effects, triggering health hazards, such as mortality attributable to heat exposure in cities. The study makes a concerted effort to unravel the complex interplay between various spatial, quantitative, and qualitative attributes of vegetation, aiming to comprehend its pivotal role in mitigating urban heat risks within urban environments. The UHI risk is related to land surface temperature (LST). The study models UHI risk in twelve American cities in diverse Köppen-Geiger Climate zones spanning the contiguous USA. To address this, the Integrated Modelling approach by the ARtificial Intelligence for Environment & Sustainability (ARIES) initiative has been adopted in the study. This approach based on FAIR (Findable, Accessible, Interoperable, and Reusable) principles is accessible at https://aries.integratedmodelling.org/. Utilizing the k.LAB software with semantic reasoning our modeling approach assesses the UHI risk. It maps the spatial distribution of UHI considering hotspots of anthropogenic heat, vegetation, land cover, and land surface temperature. UHI risk is assessed at a resolution of 30 meters alongside census tract-level data using an ordered weighted approach. The study found variations in the relationship between greenness, as indicated by the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST) across 12 different cities. The findings highlight the cooling effect of the water bodies, especially in areas near the port and green spaces. Linear parks such as roadside tree plantations typically feature uniform tree species and often lack smaller trees and shrubs, making them susceptible to heat infiltration from surrounding areas and resulting in a lesser overall temperature reduction. It identifies at least 30 percent of census tracts across 12 cities necessitate urban greening intervention. The study provides scientific insight into the cooling effects of urban parks, offering valuable guidance for urban planning and aiding decision-makers in addressing the UHI effect and enhancing overall urban sustainability. The study also underscores the significance of open science in developing environmental models addressing global sustainability challenges concerning the pressing issue of assessing urban climate risks. Models and scientific artifacts often face challenges in reusability, transferability, and sharing across diverse programming languages or modeling systems, revealing a significant lack of interoperability. By delving into the factors of LAI, NDVI, and Landscape Shape Index (LSI), the study aims to enhance understanding of the role of vegetation in ameliorating the adverse effects associated with UHI, thus paving the way for more effective urban heat management strategies. 
Ecosystem engineers impact marine biodiversity during the Phanerozoic
Authors: Cribb Alison , Darroch Simon , Ezard Thomas
Published: March 2024

Ecosystem engineers are keystone taxa whose behaviours alter the habitability of their environments for themselves and other organisms by directly influencing the availability of resources in their ecosystems. From a deep time perspective, ecosystem engineers are hypothesized to have played a major role in the co-evolution of life and the Earth systems, as many major ecosystem engineering activities directly modulate the cycling of key nutrients. Moreover, ecosystem engineers are thought to have impacted diversity by increasing environmental heterogeneity, and so their evolution may drive some of the biodiversity dynamics observed in the fossil record. Here, we investigate the impact of two groups of marine ecosystem engineers – bioturbators and reef-builders – on biodiversity through the Phanerozoic. Using fossil occurrence data from the Paleobiology Database, we calculate the effect size of bioturbating and reef-building ecosystem engineers on various biodiversity metrics for each stage through the Phanerozoic. Most broadly, we find that ecosystem engineers had a positive impact on biodiversity within the environments where they live during the Phanerozoic. We also find clear taxonomic differences between environments with and without ecosystem engineers, suggesting ecosystem engineers create a unique set of environmental characteristics to which taxa of specific ecological characteristics become adapted. These results emphasize the important role of ecosystem engineers in influencing key aspects of the Earth systems on a variety of scales that manifest in changes in biodiversity.
Multiphase inclusions in HP rocks (Western Mongolia): Remnants of high saline–CO2 fluids released during deep subduction
Authors: Bayarbold Manzshir , Okamoto Atsushi , Uno Masaoki , Kotov Alexey , Agroli Geri , Tsuchiya Noriyoshi
Published: March 2024

Subduction zone fluids play a critical role in the global element cycle. During subduction and progressive heating of the subducting slab, hydrous minerals become unstable, which releases water (Schmidt and Poli 1998). The released water is the trigger for element transport within the subducting slab, along the plate interface, and in the overlying mantle wedge (Bebout 2007). Such released fluid composition has been changed due to fluid-rock interaction during the metamorphism, which has been provided by fluid inclusion behavior in high-pressure (HP) minerals in eclogite facies rock (Bayarbold et al., 2023). Moreover, element mobility along the subduction might be highly dependent on volatile compounds in the metamorphic fluid (Tanis et al. 2016). Related to the size of the trapped fluid and fluid-mineral interaction after being trapped in HP minerals, the reconstructed fluid composition from eclogite facies has not yet been properly quantified. In this study, we report the results of our investigation of fluid inclusions (FIs) in the Khungui eclogite, found in western Mongolia.Based on the main mineral assemblages of the Khungui eclogite, it can be classified into two types: (i) dry eclogite (45 vol.% for hydrous minerals). Numerous primary FIs are present in the omphacite (Omp) from dry eclogite. Omp in dry eclogite is clearly distinguished into two types (Omp1 and Omp2) by their textures. Omp1 occurs within large (up to 100 µm) elongated quartz crystals in the matrix. The fractured Omp1 contains mineral inclusions (amphibole and quartz) and abundant primary FIs. In contrast to Omp1, Omp2 shows an equilibrium boundary with barroisite and garnet in the matrix. Furthermore, no mineral inclusion or FIs occur in Omp2, which is partially replaced by hornblende and plagioclase, whereas Omp1 is not.  FIs in Omp1 consist of variable phases such as liquid, vapor, and several solid phases with various phase ratios. The solid phases in FI within Omp consist of halite (Hl), amphibole, and calcite. These observations reveal that (1) the peak pressure-temperature (P-T) of dry eclogite is higher than the eclogite facies P-T condition of wet eclogite (2.1–2.2 GPa, 580–610°C); (2) high-saline and CO2 saturated fluid interacted with rock at eclogite facies; and (3) Hl in primary FIs in Omp suggests that the salinity of fluid might be up to 26.3 wt.% NaCl equivalent.
Cyclical continental extension reworks and destructs the cratonic lithosphere of South China
Authors: Chu Yang , Liu Tanjie , Lin Wei , Michel Faure , Meng Lingtong , Wei Wei , Ji Weibin , Xue Zhenhua
Published: March 2024

Continents with cratonic cores can resist deformation, and thus survive billions of years in the geological record. Tectono-thermal reworking is a key process in continental evolution because it alters composition and structure of some continents, weakens, and finally destructs or even dismembers them. Typical examples of reworked continents develop in subduction or collision settings, mostly situating in East Asia, Western North America, or the Tethyan collisional zones. In western Pacific, East Asian continental margins suffered extensive continental reworking and lost part of their continental lithosphere and developed a wide (>1000 km) extensional province. Across the South China Block, Mesozoic cyclical tectonics destructed a large portion of its cratonic lithosphere. Such strongly modified continent represents an ideal target to reveal the process and mechanism of continental reworking.We analyzed and synthesized the structural evolution of extensional domes and illustrated the process of lithospheric thinning of Mesozoic South China before Cenozoic rifting of the large marginal seas. Structural and geochronology data of the extensional domes in the SCB indicate Cretaceous two-stage extension, a weaker extension during the early extension, and a faster and stronger extension in the later extension. Unlike the previous rapid, one-cycle delamination model occurred in the North China Craton, the destruction process of South China operates in a cyclical, progressive manner in which compression destabilized the edge of the cratonic lithosphere and the following extension destructs the unstable part to thin the lithosphere. This process, as an endmember of lithospheric destruction mechanisms, requires cyclical tectonics of the subduction zone and the overriding plate, which has been widely reported in the Cordilleras of the eastern Pacific margin. The progressive lithosphere destruction model may also explain how ancient cratons shrink by subduction-related tectonics.
Deep blue artificial intelligencefor knowledge discovery of theintermediate ocean
Authors: Huang Baoxiang
Published: March 2024

Oceans at a depth ranging from ~100 to ~1000-m (defined as the intermediate water here), though poorly understood compared to the sea surface, are a critical layer of the Earth system where many important oceanographic processes take place. Advances in ocean observation and computer technology have allowed ocean science to enter the era of big data (to be precise, big data for the surface layer, small data for the bottom layer, and the intermediate layer sits in between) and greatly promoted our understanding of near-surface ocean phenomena. During the past few decades, however, the intermediate ocean has also undergone profound changes because of global warming, the research and prediction of which are of intensive concern. Due to the lack of three-dimensional ocean theories and field observations, how to remotely sense the intermediate ocean from space becomes a very attractive but challenging scientific issue. With the rapid development of the next generation of information technology, artificial intelligence (AI) has built a new bridge from data science to marine science (called Deep Blue AI, DBAI), which acts as a powerful weapon to extend the paradigm of modern oceanography in the era of the metaverse. This review first introduces the basic prior knowledge of water movement in the ~100 m ocean and vertical stratification within the ~1000-m depths as well as the data resources provided by satellite remote sensing, field observation, and model reanalysis for DBAI. Then, three universal DBAI methodologies, namely, associative statistical, physically informed, and mathematically driven neural networks, are elucidated in the context of intermediate ocean remote sensing. Finally, the unique advantages and potentials of DBAI in data mining and knowledge discovery are demonstrated in a top-down way of “surface-to-interior” via several typical examples in physical and biological oceanography.
Effect of ambient temperature fluctuation on DAS observation with a submarine cable
Authors: Matsumoto Hiroyuki , Araki Eiichiro , Yokobiki Takashi
Published: March 2024

Long-term Distributed Acoustic Sensing (DAS) using a submarine cable is being conducted in the Nankai Trough, Japan. The first long-term DAS observation shows that the apparent strain is observed along the relatively shallow water depth section (i.e., < water depth 1000 m) on the submarine cable, suggesting a periodic temperature fluctuation up to about 6 degrees Celsius associated with the ocean tide takes place in this region (Ide et al., 2021). However, it is difficult to discuss how the ambient temperature changes, or how the ambient temperature affects the submarine cabled DAS observation because of the lack of the in-situ observation. For this reason, we installed temperature sensors near the submarine cable by a Remotely Operation Vehicle (ROV). We did not discover the submarine cable at the seafloor, and therefore the detailed location of the temperature sensors, i.e., the accurate cable position could not be constraint so far. Simultaneous observations of the DAS and the long-term ambient temperature were conducted for a period from 16 August 2021 to 04 October 2021, i.e. about 50 days. A cross-correlation analysis between the DAS and the ambient temperature by dividing into the 5-day dataset has speculated the position of the temperature sensors to be 24.75 km of the submarine cable. Additionally, the strain coefficient of the optical fiber w.r.t. the temperature change has been determined to be 7 micro-strain per 1 degree Celsius, which is comparable to the previous experimental study (Zumberge et al., 2018). Finally, the temperature correction was performed, but the phase delay still remains, suggesting that the thermal measurement should be conducted beside the submarine cable.
Impact of Flood Inundation on Local Weather Patterns
Authors: Roose Shinto , Sushama Laxmi , John Jeenu
Published: March 2024

The impact of flood inundation on local weather pattens are investigated in this study, for the case of the flood event that impacted the Canadian regions of Ottawa, Gatineau, Montreal and surroundings during the spring of 2017 using high-resolution (4 km) regional climate model simulations, with and without flood inundation regions. In the absence of an interactive inundation parameterization in the regional climate model, flood inundated regions/grid cells are prescribed based on flood extent polygons derived from Radarsat-2 satellite imagery in the simulation that includes inundation. The flood event for most of the regions of interest was caused by rain-on-snow events, with the heavy rainfall in May being associated with a mid-latitude cyclone.The control simulation, without inundation, driven by ERA5, accurately depicts the overall regional patterns of precipitation observed compared to Daymet, but exhibits large overestimation locally, i.e., in the vicinity of the flooded regions, during the 24 hours following the peak rainfall period. However, simulations with flood inundation reveal discernible variations in precipitation over the flood inundation regions, when compared to the control simulation, reducing the precipitation biases locally. This is brought by the temperature modulations and thereby temperature gradients in the simulation with inundation leading to circulation changes locally. Sensitivity experiments reveal robust results, i.e., improved precipitation with inundation representation, despite the small changes in precipitation associated with circulation changes for small changes in flood inundation fractions. The results suggest the need to incorporate dynamic flood inundation module in climate model simulations, especially at high resolutions, to improve the realism of simulations, which in addition to facilitating process understanding can also aid in adaptation planning of inundated regions.
AI-CCTV Model for Real-time Flood Monitoring: Outland River Discharge and Inland Flood Depth Estimation
Authors: Kim Sohee , Jung Donghwi , Jun Sanghoon , Oh Jeongseok , Kim Seon Woo
Published: March 2024

Recently, flood damages have increased due to torrential rains driven by climate changes. In order to overcome the limitation of traditional manpower-dependent river monitoring approaches (low level of automation and system rapidity), CCTV-based digitalized monitoring techniques should be developed for promptly monitoring, predicting, and responding to flood damages. This study introduces an integrated AI-CCTV model for both outland and inland flood monitoring in real-time: Optical-Flow-based Flow Estimation Model (OF2EM) for outland river discharge estimation and Multi-Object-based Segmentation for Flood Depth Estimation Model (MOSDEM) for inland flood inundation. The two sub-modules of the integrated model were demonstrated independently to each domain, (1) the former OF2EM in a laboratory flume with various hydraulic and optical conditions (e.g., different brightness contrast, optical interference, with hydraulic structure that generates eddy flows) and (2) the latter MOSDEM to identify each different group of objects in a CCTV frame and finally to quantify the extent and depth of inundated area. Finally, the proposed integrated AI-CCTV model is verified to confirm the benefit of integrating the dual sub-models of real-time flood monitoring (e.g., inundated water propagation prediction with OF2EM in one corner of a frame and inundation boundary and severity determination with MOSDEM in another corner of the frame).
 Assessing the rate of ice fracture using co-located geophysical surveys on the Brunt Ice Shelf, Antarctica
Authors: Pearce Emma , Marsh Oliver , Brisbourne Alex , Hudson Thomas
Published: March 2024

The rate of fracture-induced ice instability is an important factor contributing to uncertainties in sea level projections used for global flood mitigation planning. While the occurrence of ice fracturing at critical stress thresholds is well-documented, the detailed mechanisms controlling fracture timing, rate, and orientation are not fully understood. This gap is particularly evident in differences in fracture behaviour across varying ice types, such as meteoric ice and ice mélange. Observations on the Brunt Ice Shelf reveal a unique behaviour, where rifts deviate from the pathway predicted by the principal stresses to avoid thick blocks of meteoric ice. Their growth rate is significantly reduced when required to cross through these blocks. This stands in contrast to observations on other ice shelves, such as Larsen C, where rift propagation is slower in marine ice bands.Here we use co-located geophysical methods, seismic and ground-penetrating radar (GPR), to assess the fracture pattern and dynamics and the relationship to ice properties at the leading edge of two active rifts, Halloween Crack and Chasm 2, on the Brunt Ice Shelf.By determining the depth of seismic events using P to Rayleigh wave amplitude ratios, we estimate a theoretical maximum dry crevasse depth—the depth at which fracturing can occur without the presence of englacial water. Additionally, GPR data are used to precisely locate rift terminations and identify refrozen layers associated with seawater intrusion into the firn layer. Combining these data, we provide new insight into the mechanisms controlling fracture propagation within the Brunt Ice shelf. The synthesis of observations from Chasm 2 and Halloween Crack contributes to a comprehensive understanding of fracture mechanics, enhancing our knowledge of regional-scale ice dynamics.
Impacts of Diverse Vehicle Emissions on Ozone Levels in Beijing: Insights into Source Apportionment and Formation Mechanism
Authors: Cao Jingyuan
Published: March 2024

Beijing, with the highest number of motor vehicles in China, significantly contributes to O3 pollution through substantial NOx and VOC emissions. Understanding the unique impact of different vehicle emissions on O3 levels is crucial for developing targeted strategies against O3 pollution. This study applied the Community Multiscale Air Quality model to comprehensively investigate the impacts of different types of vehicle emissions on O3 levels in various regions of Beijing, providing valuable insights into source apportionment and formation mechanisms. The results revealed that various types of vehicles exhibited different spatial-temporal emission patterns, with medium-heavy duty trucks (HDT) and mini-light passenger vehicles (LDPV) emerging as the primary contributors to NOx (36.1%) and VOCs (57.6%) emissions, respectively. Total vehicle emissions were found to contribute to over 20% of daily maximum 8–h average O3 (MDA8 O3) concentration, ranking as the second largest contributor in Beijing after regional transport. LDPV and medium-large passenger vehicles (MDPV) contributions were mainly concentrated in urban areas reaching 2.6‒3.4 and 4.1‒6.8 ppb, respectively, while the contributions from mini-light duty trucks (LDT) and HDT were mainly concentrated in suburban areas reaching 3.5‒4.8 and 3.7‒6.2 ppb, respectively. Through scenario analysis that excluded specific vehicular emission components, we found removing LDPV emissions led to sustainable decreases in daytime O3 concentration by 0.3‒3.8 ppb. In contrast, removing MDPV emissions significantly increased O3 levels at 08:00 and 20:00 in urban areas with 4.0‒11.8 ppb. Excluding LDT and HDT emissions resulted in notable increases in nocturnal O3 concentrations while decreases during 13:00‒18:00 period. This study offered valuable insights into the implications of vehicle emissions on O3 levels, providing useful information for decision-makers to devise control strategies targeting vehicle management in the future.
Deployment of Doppler lidar within forests: Advancing our understanding of canopy-atmospheric boundary layer processes 
Authors: Wharton Sonia , Puccioni Matteo , Oldroyd Holly , Miksch Matthew , Falk Matthias , de Wekker Stephan , Arthur Robert , Fast Jerome
Published: March 2024

The atmospheric boundary layer above forest canopies is difficult to measure in practice, and our understanding of its flow physics usually is still limited to tall tower measurements which have limited reach above the canopy, or vertically-profiling remote sensing measurements which are usually taken outside of the canopy. We present a recent 5-month study of wind flow measurements taken above a 50-m tall forest in Washington state, USA, using two Doppler lidars. One vertical-profiling lidar was placed directly on top of the 70-m tall Wind River National Ecological Observatory Network (NEON) tower and took measurements of wind velocity, direction and turbulence up to 220 m above ground level. A scanning lidar was placed in a nearby clearing and programmed to scan the wind field over the forest canopy, including overlapping its scans with the profiling lidar on top of the tower. The scanning lidar also captured terrain induced flows across the surrounding mountain-valley terrain. Both lidars captured wind jets and periods of intermittent turbulence over the forest canopy. How and when these mechanically-forced turbulence events penetrate the high leaf area index (LAI) forest canopy are studied using NEON’s eddy covariance flux exchange measurements and the tower profile measurements of air temperature, pressure, moisture, and wind velocity within the forest. Applications of studying wind flow over the forest canopy are broad and vary from a better characterization of the wind profile for wind energy resource assessment to improving our understanding of vertical exchange processes by studying how “top-down” forced turbulence events influence mass and energy fluxes between the forest canopy and atmosphere. Special consideration of how above canopy processes influence canopy coupling/decoupling, including top-down turbulent sweep events, will be presented for the tall Wind River forest. We will also discuss upcoming experiments including 1) the deployment of 3-d sonic anemometers in the Wind River subcanopy (as part of a larger Integrated Carbon Observation System (ICOS) below-canopy study) to advance our understanding of canopy mixing processes and 2) a new campaign planned for the deciduous Mountain Lake Biological Station NEON tower in the mountains of Virginia, USA. The latter study is designed to observe changes in the above-canopy wind profile and its interactions with below-canopy flows and vertical flux exchanges across a summer-to-winter LAI transition. 
NASA’s Geospace Dynamics Constellation—Providing the first Systematic Measurements of Global Magnetospheric Energy Inputs and Ionosphere-Thermosphere Responses
Authors: Kepko Larry , Rowland Douglas ,   GDC Instrument and IDS teams
Published: March 2024

The Geospace Dynamics Constellation (GDC) is NASA's next strategic Living With a Star mission. GDC's goals are: 1) Understand how the high-latitude ionosphere-thermosphere system responds to variable solar wind/magnetosphere forcing; and 2) Understand how internal processes in the global ionosphere-thermosphere system redistribute mass, momentum, and energy. Planned for launch by the end of the decade, GDC will use six identical observatories, each identically instrumented to fully characterize the magnetospheric drivers of the I-T system as well as the global response of the ionized and neutral gases. GDC will do this with a series of orbital configurations that will enable it to study the widest range of spatial and temporal scales to date, ranging from hundreds of kilometers and several seconds to tens of minutes, and extending through the regional to the global scale. This talk presents GDC's current status, measurement capabilities, sampling scheme, and model development efforts and show how GDC will fit into the larger Heliophysics ecosystem, by 1) obtaining critically needed scientific observations; 2) providing a source for real-time space weather and situational awareness, as well as retrospective studies to further the science of space weather; 3) serving as a "strategic hub" for other space-based and ground-based efforts that want to leverage GDC to perform complementary science.To get the most benefit from GDC’s observations, it will be critical to identify partnerships with other research efforts in the ITM and Geospace arenas, including those utilizing space-based, ground-based, or theoretical investigations. We particularly would like to discuss with groups who are planning or considering observational campaigns during the GDC era, to find ways to leverage GDC observations to do synergistic science that could not be done otherwise.
Planetary Boundary layer flow over complex terrain during a cold surge event: a case study
Authors: Lee Young-Hee , Lim Hee-Jeong , Lee Gyuwon
Published: March 2024

The planetary boundary layer (PBL) flows over complex terrain during a cold surge event were investigated using 3-hourly radiosonde measurements in the upwind, near ridge, and downwind of mountains in the northeastern part of South Korea and high-resolution (333-m) numerical simulation. A cold surge occurred on 23 January 2018 and lasted for 4 days. We analyzed onset day of the cold surge when air temperature dropped rapidly. Analysis of the radiosonde data shows that the PBL is characterized by an adiabatic layer with strong capping inversion in early morning and evening as well as during daytime in the upwind and near-ridge sites. The PBL flow at the near-ridge site was strongest among three sites except at 0600 local standard time (LST) when the PBL flow in the lee was strongest. We performed high-resolution (333-m) numerical simulations using the Weather Research and Forecasting (WRF) model. The adiabatic PBL in the upwind site at 0600 LST was simulated, although its depth was underestimated. The model reproduced the strong low-level wind at 0600 LST and large wind shear during the daytime in the lee, but it did not capture the exact timing of the large wind shear. Model showed an overall good performance in simulating the vertical profile of the virtual potential temperature and wind below 2 km above sea level at the three sites, with a high index of agreement (IOA) except for the wind at 1200 and 1500 LST in the lee. To examine the cause for the different behavior of PBL flow in the lee of mountains between 0600 LST and the daytime, we calculated the Froude number for PBL flow using radiosonde measurements based on reduced gravity shallow water (RGSW) theory. At 0600 LST, the upwind Froude number F0was close to 1, while during the daytime, it was much lower than 1. The observed lee flow behavior was consistent with the flow regime change of a single layer over an obstacle with changing F0; the flow with a propagating lee jump changes into that with a stationary lee jump with decreasing F0. Numerical simulation shows that the steepening of streamlines of lee-wave field leads to a jump-like structure in the lee of mountains during the daytime.
“GENIUS: Satellite Monitoring Platform for City Management and Planning”
Authors: Medina Javier , Hernández-Duarte Ana , Saavedra Freddy , Contreras Valentina , Leguía Marcelo , Romero Carlos
Published: March 2024

More than 50% of people worldwide live in cities with upward projections. Ensuring health, public safety, and maintaining a high quality of life is a challenge within cities due to the accelerated growth of urbanization, climate change, and the limited resources available for urban management and planning. Strategies for sustainable urban planning are a need that has become relevant worldwide. The concept of a Smart City is presented as an approach that integrates many inputs from different sources to make decisions based on reliable and updated information, considering, for example, environmental monitoring. However, capturing the spatiotemporal variability of processes within the city requires a significant investment in time and resources, especially for medium-sized cities in Latin America, where little information is available. Earth Observation based on open-access information offers essential opportunities to obtain information of interest, contributing to cities' physical and environmental characterization. Satellite sensors allow cities to be characterized in terms of the presence and state of vegetation, surface temperature, changes in the urban footprint, level of luminosity, and atmospheric pollution, among other parameters. This ongoing project is progressing with a web platform containing urban-environmental indicators derived from satellite images to support intelligent planning and management of sustainable development strategies in the city. The platform is currently undergoing pilot development in the city of Quilpué, Valparaíso Region, with the potential for scaling to other territories at the regional and national levels. Preliminary findings with satellite data reveal adverse trends in surface temperature, vegetation health, and air quality in Quilpué City, which are currently undergoing validation with on-site data. Efforts were focused on merging socio-economic and environmental data to pinpoint areas with vulnerable populations. Despite the emphasis on environmental variables, gaps exist in analyzing population exposure to these factors due to outdated demographic information. This underscores the importance of nature-based solutions to exposure variables such as air quality, surface temperature, and proximity of green areas, which could be addressed by governance risk management and public policy planning. This approach offers substantial potential for informed decision-making and risk mitigation strategies.
Investigation of Cloud Simulations of a Low-echo Centroid Storm Using Cloud-Resolving Model Based on Satellite and Radar Observations
Authors: Yang Nan , Zhu Kefeng , Xue Ming
Published: March 2024

The low-echo centroid (LEC) storm, characterized by the dominance of warm-rain processes and high precipitation efficiency (Vitale & Ryan, 2013), is generally associated with high-intensity rainfall events in tropical and subtropical regions (Hamada et al. 2015). While many double-moment microphysical parameterization schemes are primarily designed for deep convection or cold-rain processes, research on their performance in simulating LEC warm-cloud precipitation systems is limited.
In this study, we investigate an extreme rainfall case that occurred on 20 July 2016 in northern China, resulting in over 600 mm of maximum 24-hour accumulated rainfall. According to radar observations, the case is characterized by LEC structure. Using the Weather Research and Forecasting (WRF) model with 4 km grid spacing, we simulate this event employing the Morrison, Thompson, and Milbrandt-Yau double-moment microphysics schemes. Evaluation based on simulated infrared brightness temperature (BT) using a radiative transfer model and simulated reflectivity reveals that while different microphysics schemes generally predict rainfall amount, location, and propagation accurately, they fail to replicate the three-dimensional cloud structures. The simulated convective cores (>35dBZ) are higher than -10 °C, indicating active cold-cloud processes, while the observed LEC suggests the dominance of warm-cloud processes. The model produces an excessive number of upper-level clouds and overshooting clouds, also overpredict the cloud-top height.
Sensitivity experiments show that simulated brightness temperatures are primarily influenced by the concentration of cloud ice particles. Morrison and Milbrandt-Yau microphysics schemes produces an overabundance of cloud ice particles in the upper layer, leading to the overproduction of uppe-level cloud and incorrect representation of cloud top height. Warm-rain processes are not fully developed, and the cold-rain processes are not effectively restrained, resulting in unrealistic cloud structure. By adjusting microphysical processes in the schemes, such as increasing cloud water number concentration, the simulated convective cores align more closely with the observed ones.
In summary, while the current microphysics schemes effectively simulate rainfall intensity and propagation, there is a clear need for improvement in simulating the cloud particle distribution and vertical structure of LEC storms. Our findings underscore the importance of refining microphysical parameterization schemes for accurate simulation of extreme rainfall events.
Testing four Sentinel (1 and 2) and MODIS Fractional Snow Cover products for the evaluation of five Alpine Cosmic Ray Neutron Sensing sites
Authors: Krebs Nora , Schattan Paul , Premier Valentina , Mejia-Aguilar Abraham , Rutzinger Martin
Published: March 2024

Above-ground cosmic ray neutron sensing (CRNS) is an emerging technique for the investigation of dynamics in soil moisture, snow water equivalent (SWE), and vegetation at a spatial scale of several hectares. The measurement principle is based on the moderation of natural secondary cosmogenic neutrons by hydrogen atoms. On the earth surface hydrogen atoms are mainly bound in water molecules. However, at complex research sites the signal distinction between various water sources remains challenging. Especially in alpine terrain and at elevated topography, hydrological features are linked in an intricate patchwork, hampering signal discrimination. Satellite observations offer valuable complementary surface information and are commonly provided at a spatial resolution that meets the integrated footprint area of the CRNS detector. In this study we investigate if the interpretation of the CRNS signal can be enhanced by the use of remote sensing products. We compare three readily available fractional snow cover (FSC) products based on Sentinel (1 and 2) and MODIS and one reference FSC Sentinel-2 scene-based machine learning product at the approximate footprint resolution of CRNS, comprising a circular area of 250 m radius. The performance of all four products is assessed at five CRNS sites in the Austrian and Italian Alps that represent a variety of environmental properties, ranging from flat to steep topography, from low to high elevation and from sparse to abundant vegetation cover. At three sites, the presence and absence of snow can be validated by local snow height measurements. The analysis shows that remote sensing snow cover information can be extracted on around 80% of the analyzed days, demonstrating the use of FSC products for the estimation of snow cover duration and timing. Comparing the four products shows overall agreements and allows to deduce product-specific thresholds for the distinction of snow-covered and snow-free situations. Further, pairing remote FSC observations with neutron count measurements provides a first indication on the complexity of local hydrogen pool dynamics and consequent requirements on the calibration routine for ambient water monitoring with CRNS. We conclude that satellite-based FSC products can be used to fortify the choice of CRNS observation location and period prior to the detector installation and for a robust and viable first-order assessment of expected CRNS site conditions. Remote sensing FSC products and CRNS measurements hold complementary data that can mutually benefit snow observations and should be explored further in the future.