bluuebunny/crossref_metadata_2025 huggingface dataset:
Spherical geometry convection in a fluid with an Arrhenius thermal viscosity dependence: the impact of core size and surface temperature on the scaling of stagnant-lid thickness and internal temperature
Authors: Javaheri Pejvak , Lowman Julian , Tackley Paul
Published: March 2024

The rock and rock-ice mixtures of the core-enveloping spherical shells comprising terrestrial body interiors have thermally determined viscosities well described by an Arrhenius dependence. Accordingly, the implied viscosity contrasts determined from the activation energies (E) characterizing such bodies can reach values exceeding 1040, for a temperature range that spans the conditions found from the lower mantle to the surface. In this study, we first explore the impact of implementing a cut-off to limit viscosity magnitude in cold regions. Using a spherical annulus geometry, we investigate the influence of core radius, surface temperature, and convective vigour on stagnant lid formation resulting from the extreme thermally induced viscosity contrasts. We demonstrate that the cut-off viscosity must be increased with decreasing curvature factor, ƒ (=rin/rout, where rin and rout are the inner and outer radii of the annulus, respectively), in order to obtain physically valid solutions. We find that for statistically-steady systems, the mean temperature decreases with core size, and that a viscosity contrast of at least 107 is required for stagnant lid formation as ƒ decreases below 0.5. Inverting the results from over 80 calculations featuring stagnant lids (from a total of approximately 180 calculations), we apply an energy balance model for heat flow across the thermal boundary layers and find that the non-dimensionalized temperature in the Approximately Isothermal Layer (AIL) in the convecting layer under a stagnant lid is well predicted by T'AIL=½{ -(2T'out+γ) + √[γ2 + 4γ(1+T'out)] } where γ is a function of E and ƒ, and T'out is the non-dimensionalized surface temperature. Moreover, the normalized (i.e., non-dimensional) thickness of the stagnant lid, L', can be obtained from a measurement of the non-dimensional surface heat flux once T'AIL is determined. Stagnant-lid thicknesses increase from 10 to 30 percent of the shell thickness as ƒ is decreased, and thick lids can overlie vigorously convecting underlying layers in small core bodies, potentially delaying secular cooling and suggesting that small objects with small cores may have developed thick elastic outer shells early in the solar system's history while maintaining vigorously convecting interiors. However, we also find that for the small number of 3-D calculations that we examined, parametrizations based on 2-D calculations overestimate the temperature of the convecting layer and the thickness of the conductive lid when ƒ is small (less than 0.4).
Convection permitting regional climate modelling with RegCM5 over the Carpathian Region
Authors: Torma Csaba Zsolt , Giorgi Filippo
Published: March 2024

This study presents a preliminary analysis of the performance of the latest version of the RegCM regional modelling system, RegCM5, when run at a convection permitting resolution of 2 km over the Carpathian Basin. The performance of the model is evaluated by comparing various statistics of surface air temperature and precipitation against the CARPATCLIM high-resolution observational dataset and the ERA5 reanalysis, which is also utilized as the driving field for the simulations. Overall, the model performs well; however, certain biases are observed. During the warm season (JJA), a warm bias is detected over the Hungarian lowlands, while a wet (dry) bias is observed over the mountain chains (flat regions) within the basin. In addition, the model shows a significant orographic forcing effect on precipitation. An important finding is that the high-resolution of the model notably improves its ability to simulate medium to high-intensity precipitation events. This added value enhances its applicability, especially for the studies of such events. Given these promising initial results, future work will include further testing of the model with different physics configurations, longer simulations, and exploring its usability in climate change studies related to the Carpathian Basin.
Applicability of measured soil shrinkage characteristic curves to in-situ land movement monitoring data for expansive soils
Authors: Lexmond Bente , Janssen Chayenne , Erkens Gilles , Griffioen Jasper , Stouthamer Esther
Published: March 2024

Normal seasonal variations in wet and dry conditions cause vertical land movement, due to shrinkage and swelling, particularly in deposits rich in expansive clay minerals or organic matter. This land movement can be up to decimeters depending on the characteristics of the deposit, causing damage to infrastructure and buildings. Furthermore, the increase in drought duration and intensity results in a lowering of the groundwater table to unprecedented levels in shallow deltaic and coastal subsurface deposits. Exposure to resulting low water contents in the unsaturated zone induces irreversible shrinkage and densification of the soil structure, contributing to land subsidence.Understanding the relation between water content and bulk volume over time is crucial for predicting the land movement and assessing the potential for land subsidence and associated structural damage. The shrinkage behaviour is commonly characterized using soil shrinkage characteristic curves, which relate the water content to bulk volume.In this study, we characterized the soil shrinkage characteristic curves (SSCCs) of undisturbed natural samples extracted from the capillary fringe zone of shallow, marine clay-rich deposits in the Netherlands. The sample site was selected based on the presence of an extensometer, constantly monitoring the water content and thickness of the soil layer. The SSCCs were created by measuring the water content and sample volume during air drying of the samples. The sample volume was measured with optical distance sensors. The water content decreased from 0.97 to 0.08 during the experiment and the void ratio from 0.97 to 0.34.  The SSCCs of the samples show a linear relation between water content and void ratio, for a water content between 0.97 and 0.34.By applying the established linear relation to the monitored in-situ soil moisture content at the sample site, we predicted the change in thickness of the soil layer. The prediction overestimates the measured changes in land movement, indicating the importance of in-situ conditions. The measured land movement seems to be more responsive to the groundwater level than the water content. The and the coming results underscore the importance of measuring land movement in-situ.
Land-use management of invasive species could help prevent spread of mosquitoes borne diseases: Evidence from Kenya  
Authors: Osman Tasneem , Fevre Eric , Borgemeister Christian
Published: March 2024

Climate change is expected to substantially alter biodiversity, leading to alterations in phenology, genetic composition, and species distribution while also affecting species interactions and ecosystem. Invasive alien species (IAS) have threatened the integrity of ecosystems throughout the world. They affect the species diversity of native ecosystems and threaten their biological integrity. Due to increasing movement of people and goods around the world, and with new trade routes opening and enhanced transportation, the number of species being introduced into new areas is rising. IAS reduce agricultural yields, irrigated croplands, grazing areas, and water availability, and contribute to the spread of mosquito-borne diseases. Mosquitoes are widely spread Mosquitoes are widely spread and transmit malaria and several arthropod-borne viruses. A particular example of IAS is Parthenium hysterophorus (Asteraceae). It is one of the world's most serious invasive plants that is able to thrive and spread aggressively outside its original geographical areas. Native to the subtropics and tropics of North and South America, Parthenium has negative effects on human, livestock, agriculture and the environment. The aim of this study is to determine the abundance and diversity of mosquito vectors at sites with different degrees of invasive plant infestations in the Rift valley area in Kenya. Currently, the spread of invasive plant species is a major problem in Kenya, where indigenous flora is replaced. The study sites are located in Baringo county. A total of 50000 mosquitoes were captured using a combination of different trapping techniques from six sites, three of them with IAS (Parthenium) and three without. We identified 48 species. A subset of 1000 mosquitoes was analyzed for evidence of recent plant feeding using cold anthrone test. An overall low fructose positivity rate (10.9%) was found. Barcode technique was applied to identify plant food source using specific primers for a locus from the chloroplast genome, ribulose diphosphate carboxylase. The DNA from all trees or shrubs within a 100m radius from the trap was collected to build a barcode reference library. Plant DNA with 55.3% (n = 553) success rate was identified. Sequences were successfully generated from samples, indicating Parthenium plants as the predominant plant fed by mosquito vectors. This survey is an inventory of the mosquito population composition and of the abundance and richness of arboviruses. It provides an insight into how changes in community ecology interact with the main types of land-use change and influence the dynamics of relevant arboviruses in Kenya. Thus, it provides a beneficial knowledge for targeted control.KeywordsClimate change, land-use changes, agricultural expansion, infectious diseases, mosquito ecology, invasive plants, Parthenium hysterophorus
Characterization and use of commercial biochar for water purification in real case scenarios
Authors: Animali Lorenzo , Corrado Sveva , Tuccimei Paola , Bartoli Mattia , Giorcelli Mauro
Published: March 2024

Biochar has been proven to be a compelling adsorbent for contaminants  in water, however little data are available about real case histories. Moreover, such data are often related to biochar produced solely for the sake of research, this means biochar would not be readily available for actual commercial applications.  

The aim of the project is to employ commercial biochar for water purification in a real case study and test its viability as a pollutant adsorber. The chosen study area covers the surroundings of the decommissioned Malagrotta landfill in the Lazio region, Italy. The landfilling site, the largest in Europe, active from 1970 to 2013, has been the subject of numerous social and legal disputes throughout and after its operating period. 
At this stage, a chemical survey of the area’s surface water has been performed to determine its health and to evaluate remediation through biochar. Moreover, nine commercial biochar types produced in Italy and Europe have been characterized before and after experimentation to monitor structural, surface and physical-chemical properties. Post testing analyses are aimed at determining the effects of biochar’s interaction with water. Testing biochar in real case scenarios provides an assessment of its potential in an high added value application such as water purification and provides the constraints to achieve optimal performance.  

Future developments of the project build upon collected data and expertise to identify best practices for the valorisation of biochar as a contaminant adsorber. 
Decadal variability of extreme precipitation in northern of Oman
Authors: Al Zadjali Salma , Sammonds Peter , Day Simon , Phillips Ian
Published: March 2024

Climate variability and climate change are major drivers for extreme precipitation patterns on a global scale. However, under the application of weather engineering techniques such as cloud seeding, the climate variability signals must be analysed before concluding the benefits of these seeding operations in arid and semi-arid regions. The primary aim of this study is to gain insights on the drivers that contribute to extreme precipitation variability in northern Oman. In this research, the monthly high-resolution precipitation data from Climate Research Unit (CRU) Time Series (TS) version 4.05 dataset for northern Oman from 1950-2019 are analysed. The quantile perturbation method and the non-parametric Monte Carlo simulations are employed to compute high decadal and seasonal anomalies, and their statistical significance respectively. The teleconnections of Optimum Interpolation Sea Surface Temperature (OISST), Mean Sea Level Pressure (MSLP) and decadal variability patterns represented by the North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), and El Niño-Southern Oscillation (ENSO) with extreme precipitation anomalies are conducted. The severity and spatial and temporal variability of precipitation and deep convection are investigated using outgoing longwave radiation (OLR) as a proxy for extreme precipitation. These findings address the role of internal forcing on precipitation variability in the Al Hajar Mountains, an area characterised by natural convective precipitation. The extreme precipitation variability analysis is conducted to understand better whether cloud seeding operations induce the occurrence of extreme precipitation in the Al Hajar Mountains.
New Extended Mission Results from Juno’s Stellar Reference Unit 
Authors: Becker Heidi N , Florence Meghan , Brennan Martin , Lunine Jonathan , Schenk Paul , Hansen Candice , Martos Yasmina , Bolton Scott , Alexander James
Published: March 2024

Juno’s Extended Mission has expanded the scientific reach of Juno’s low-light Stellar Reference Unit (SRU) star camera to multiple new targets within the Jovian system. Close flybys of the dark sides of Ganymede and Europa (illuminated by Jupiter-shine) have yielded high-resolution SRU surface images that enabled significant improvements to the geomorphologic maps of these icy moons and revealed sites of potential present day surface activity on Europa (providing high quality baselines for Europa Clipper and JUICE). Close flybys of Jupiter’s dark side began in Spring 2023, launching the SRU’s Extended Mission study of lightning in the northern latitudes at resolutions as high as a few kilometers per pixel, and the geometry has also allowed the SRU to image Jupiter’s faint dust ring from vantage points inside the ring. The Mission’s planned flybys of Io in December 2023 and February 2024 will present additional opportunities for low-light high-resolution SRU surface imaging on the dark side of the volcanic moon. Our presentation will discuss new Extended Mission results from Juno’s SRU. 
Reconstructing total water storage changes in the Yangtze River Basin based on deep learning models
Authors: Wang Jielong , Shen Yunzhong , Awange Joseph , Yang Ling , Chen Qiujie
Published: March 2024

Understanding long-term total water storage (TWS) changes in the Yangtze River Basin (YRB) is essential for optimizing water resource management and mitigating hydrological extremes. While the Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) mission have provided valuable observations for investigating global or regional TWS changes, the approximately one-year data gap between these missions and their relatively short 20-year data record limits our ability to study the continuous and long-term variability of YRB's TWS. In this study, two deep learning models are employed to bridge the data gap and reconstruct the historical TWS changes within YRB, respectively. For the data gap filling task, a noise-augmented u-shaped network (NA-UNet) is presented to address UNet's overfitting issues associated with training on limited GRACE observations. Results show that NA-UNet can accurately bridge the data gap, exhibiting favourable and stable performance at both the basin and grid scales. Subsequently, we introduce another deep learning model named RecNet, specifically designed to reconstruct the climate-driven TWS changes in YRB from 1923 to 2022. RecNet is trained on precipitation, temperature, and GRACE observations using a weighted mean square error (WMSE) loss function. We show that RecNet can successfully reconstruct the historical TWS changes, achieving strong correlations with GRACE, water budget estimates, hydrological models, drought indices, and existing reconstruction datasets. We also observe superior performance in RecNet when trained with WMSE compared to its non-weighted counterpart. In addition, the reconstructed datasets reveal a recurring occurrence of diverse hydrological extremes over the past century within YRB, influenced by major climate patterns. Together, NA-UNet and RecNet provide valuable observations for studying long-term climate variability and projecting future hydrological extremes in YRB, which can inform effective water resource management and contribute to the development of adaptive strategies for climate change.
Thermal rheological structure analysis of crust and upper mantle in Sulawesi based on joint tomography of surface wave and gravity data
Authors: Zhang Jian , Jiang Chenghao , Hao Tianyao
Published: March 2024

Sulawesi Island is situated to the east of Kalimantan Island, composed of four branches. Throughout its tectonic evolution, influenced by both the Sulawesi Sea and the Banda Sea, Sulawesi Island involves the continental crustal fragment displacement and reorganization. Therefore, it is pivotal for studying geodynamic problems of ocean-continent coupling and subduction rollback. In this paper, combining dispersion data extracted from seismic surface wave and ambient noise with the satellite gravity anomaly data, we conducted a joint tomographic inversion to obtain a three-dimensional VS velocity model around Sulawesi. Combined with heat flow data, we derived a temperature structure and calculated the thickness and viscosity variation characteristics of the thermal rheological boundary layer at the bottom of the lithosphere by the thermal rheological method. The results suggest that: 1) The thickness of the rheological boundary layer in the southeastern part of Sulawesi Island, closer to the Banda Sea, is greater than that in the northern part, closer to the Sulawesi Sea. The different deformation rate, driven by lateral variations in rheological structure within the lithosphere, may control the continental crustal fragment displacement and reorganization in the Cenozoic, resulting in the maximum northward velocity in the eastern part of the East Branch of Sulawesi Island and the second in the western part of the North Branch of Sulawesi Island. 2) The low VS anomalous velocity zone, corresponding to the overlying crust of the subduction retreating plate of the North Sulawesi trench, likely represents a fluid-rich weak plate, leading to the extensional environment that contributes to the trench retreat. During the retreat, the area between the North Branch of Sulawesi Island and the Sulawesi subduction exhibits different rheological strengths under the influence of the surrounding tectonic stress field, resulting in the discontinuous Sulawesi subduction rollback.
Extremely high alkalinity due to dissolution of mica-group silicate in the pelagic sediments of the Ulleung Basin (East Sea): stable Si isotopes evidence and reactive transport modelling
Authors: Huang Tzu-Hao , Sun Xiaole , Kim Ji-Hoon , Mark Chris , Hong Wei-Li
Published: March 2024

Marine silicate alteration is a combined process of lithogenic silicate (LSi) dissolution (known as marine silicate weathering) and secondary clay neoformation (known as reverse weathering). Both processes have been shown to affect long-term C cycling. Yet, the net CO2 consumption and production due to marine silicate alteration have not been studied thoroughly. Factors such as silicate types and rates are crucial in determining the fate of CO2 in the marine subsurface. In this study, we aimed to constrain silicate types of marine silicate alterations and their rates by measuring Si isotopic signatures of porewater and different silicate phases (including LSi, biogenic silica (BSi) and amorphous secondary Si phase (ASSi)) and modelling downcore profiles from two drill cores retrieved from the Ulleung Basin, where up to 130 mM of alkalinity has been documented as a result of fast marine silicate weathering. A decrease in porewater dissolved Si (DSi) concentration and an increase in porewater δ30Si (δ30Sipw) value indicate the formation of ASSi in the shallow subsurface (0 to 9 meter below seafloor (mbsf)). Below the sulfate-methane transition zone (9 to 32 mbsf), an increase in DSi concentrations and a decrease in δ30Sipw values were attributed to the LSi dissolution releasing lighter Si isotopes into porewater. Such a dissolving LSi phase is likely a mica-group silicate, as suggested by the elemental content of the separated solid phase and porewater. This finding is supported by reactive transport simulation, which indicates that mica, vermiculite and albite are able to dissolve and release Mg, K and Na into porewater. Precipitation of smectite group silicates consumes Mg and K in the pore fluids at rates lower than the overall silicate dissolution rates. The dissolving mica-group silicate (and albite) neutralises CO2 produced through organic matter fermentation and increases porewater alkalinity, which is 60 times higher than the seawater value. By further conducting model sensitivity tests using various organic matter degradation rates, we found that the alkalinity concentrations contributing by dissolved Mg and K concentrations are majorly affected by changes in smectite group formation rates while mica and vermiculite dissolution rates remain constant. The decreased contribution of mica-like silicate dissolution and the increased contribution of BSi dissolution with sediment depth from 32 to 218 mbsf are indicated by increased DSi concentration, increased δ30Sipw values and rate results output by modelling.
Simulating Atmospheric CO2 Levels Using CH4 and Temperature Proxy Records by ANN-Wavelet technique
Authors: Salehnia Nasrin , Ahn Jinho
Published: March 2024

Investigating climate change through the reconstruction and modeling of atmospheric CO2 provides valuable insights for scientists aiming to unravel climate-carbon cycle feedback. The correlation between temperature and greenhouse gases, as inferred from ice core records, holds the potential to improve the accuracy of simulating CO2 variations. This study sought to investigate modeling approaches for accurately simulating atmospheric CO2 concentrations. To address data gaps in CO2, CH4 concentration, and temperature proxies (δD and δ18O) from Antarctica ice cores were incorporated. The study utilized Artificial Neural Network (ANN) and Wavelet Transform (WT) techniques to enhance precision in these simulations. Three distinct ice cores were utilized in this study, specifically the EPICA Dronning Maud Land (EDML) core for 70-115 thousand years ago (ka), the Dome Fuji (DF) core spanning 9-120 ka, and the West Antarctic Ice Sheet (WAIS) Divide core covering the period of 9~70 ka. The findings affirmed that the implementation of the WT-ANN model proved to be a successful approach for simulating CO2 concentrations throughout the study timeframe. The results highlighted the notable impact of time resolution in influencing the outcomes of the AI model. Particularly, utilizing high-resolution data from the WAIS Divide spanning 9-70 ka resulted in an impressive R2 value of up to 0.96, indicating a strong correlation between the model predictions and the ice core records using the hybrid method. Applying the WT-ANN hybrid methodology, which integrated WAIS (training periods of 9-29 and 57-70 ka) and DF data (training periods of 9-29 and 57-120 ka), a simulation of CO2 concentrations spanning 29-57 thousand years ago (MIS3) was carried out. The model demonstrated superior performance during the MIS3 test phase for the WAIS, with an R2 value of 0.85 and an RMSE of 3.62 ppm, compared to the DF core, where the R2 was 0.74 and the RMSE was 6.91 ppm. In our future initiatives, we intend to broaden our modeling efforts by integrating diverse AI techniques and employing numerous ice core samples across various time periods. Through the pursuit of this strategy, we aim to create exceptionally accurate simulations of CO2 levels. This not only advances our comprehension of historical climate dynamics but also addresses research gaps, paving the way for future investigations.
Metagenomic insights into microbial structure and metabolism in alpine permafrost on the Tibetan Plateau
Authors: Kang Luyao , Song Yutong , Mackelprang Rachel , Wu Linwei , Yang Yuanhe
Published: March 2024

Permafrost, characterized by its frozen soil, serves as a unique and ecologically significant habitat for diverse microorganisms. Understanding the intricacies of their community structure and functional attributes is crucial for predicting the response of permafrost ecosystems to climate change. However, large-scale evidence regarding microbial profiles and their differences across soil strata remains limited. Here we analyze microbial structure and metabolic potential in permafrost deposits based on 16S rRNA and metagenomic data obtained from a ∼1,000 km permafrost transect on the Tibetan Plateau. We find that microbial communities exhibit apparent discrepancy in structure among soil depth, with a decline in alpha diversity and an increase in spatial variation along soil profile. Microbial assemblages are primarily governed by dispersal limitation and drift, with dispersal limitation being more pronounced in permafrost layer. We also observe that functional genes related to reduction reactions, including nitrate reduction, denitrification, polysulfide reduction, sulfide reduction, tetrathionate reduction, Fe reduction, and methanogenesis, are enriched in the permafrost layer. Taxa involving in redox reactions are more diverse in the permafrost layer and contribute highly to community-level metabolic profiles, reflecting higher redox potential and more complicated trophic strategies for microorganisms in permafrost deposits. These findings provide new insights into the large-scale stratigraphic profiles of microbial community structure and biogeochemical processes and laying the groundwork for future endeavors that elucidate microbial responses to environmental change in permafrost regions.
Improved Diurnal Cycle in GFDL Earth System Models with Non-Equilibrium Convection
Authors: Zhang Bosong , Donner Leo , Zhao Ming , Tan Zhihong
Published: March 2024

Most global climate models with convective parameterization have trouble in simulating the observed diurnal cycle of convection. Maximum precipitation usually happens too early during local summertime, especially over land. Observational analyses indicate that deep convection over land cannot keep pace with rapid variations in convective available potential energy (CAPE), which is largely controlled by boundary layer forcing. In this study, a new convective closure in which shallow and deep convection interact strongly, out of equilibrium, is implemented in atmosphere-only and ocean-atmosphere coupled models developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The diurnal cycles of convection in both simulations are significantly improved without altering their mean states. These improvements in the diurnal cycle of these climate models are consistent with those obtained by Peter Bechtold and colleagues in the ECMWF Integrated Forecasting System. The new closure shifts maximum precipitation over land later by about three hours. Compared to satellite observations, the diurnal phase biases are reduced by half. Shallow convection to some extent equilibrates rapid changes in the boundary layer at sub-diurnal time scales. Future model improvement will focus on the remaining biases, which may be further reduced by including stochastic entrainment and cold pools.
The Role of Upper Mantle Forces in Post-subduction Tectonics: Insights from 3D Thermo-mechanical Models in the East Anatolian Plateau
Authors: Şengül Uluocak Ebru , Pysklywec Russell N. , Sembroni Andrea , Brune Sascha , Faccenna Claudio
Published: March 2024

Post-subduction tectonics can involve a wide range of spatiotemporal processes associated with regional and large-scale upper mantle forces. To better understand the interaction between these forces in collisional settings, we focus on active mantle dynamics beneath the East Anatolian Plateau, a well-documented segment of the Arabian-Eurasian continental collision zone. In detail, we use state-of-the-art instantaneous thermomechanical models by combining the advantages of 3D numerical modeling with high-resolution imaging techniques. We analyze the model’s outputs, such as 3D stress-strain and temperature variations of upper mantle convection and reconcile them with numerous geological and geophysical observations. Our results show prominent northward-directed channel flow in the mantle that cuts across the plateau and surroundings, from the Arabian foreland to the Greater Caucasus domain. This result reproduces and elucidates the proposed ~SW-NE-oriented Anatolian Background Splitting pattern and recent seismic low-ultra low-velocity anomalies. We argue that this large-scale upper mantle flow constitutes the engine for the long-wavelength dynamic topography (~400 m) in the region and promotes the relatively small-scale convection pattern by supporting intraplate rift tectonics in the extensional Van Lake zone.
Changes in coastal environments and their impact on society in northwestern Greenland
Authors: Sugiyama Shin ,   ArCS II Coastal Environments Project
Published: March 2024

Coastal environments around Greenland are rapidly changing under the influence of a warming climate. Glaciers are melting and glacial meltwater discharge is affecting ocean environments, resulting in a wide range of impacts on marine ecosystems. Steep terrains along the coast are destabilized by thawing permafrost and more frequent heavy rain events. These changes in natural environments are serious concerns of Greenlandic societies. An increasing amount of glacial melt causes flooding of streams. Settlements at the foot of steep slopes are threatened by landslide hazards. Accordingly, an increasing number of damages to buildings and infrastructures are reported. To investigate changing coastal environments and their impact on society in Greenland, we have been running a research project in Qaanaaq, a small village in northwestern Greenland, under the framework of Japanese Arctic research projects GRENE (Green Network of Excellence), ArCS (Arctic Challenge for Sustainability) and ArCS II. In this presentation, we introduce the overview of our multidisciplinary research activities performed in the Qaanaaq region since 2012.On Qaanaaq Ice Cap, annual mass balance and ice speed have been measured since 2012 to investigate glacier changes and processes driving rapid ice loss. Discharge of a glacial stream is measured to study the mechanism of foods, which frequently destroy a road connecting the village with Oaanaaq Airport. In a nearby smaller settlement Siorapaluk, a slope affected by a landslide was surveyed to study the triggering mechanism of the failure. During the late summer season, research activities were performed in the largest glacial fjord in the region, Inglefield Bredening. Using boats operated by local collaborators, seawater properties are measured, moorings are installed for year-round measurements, and habitats of fish, seabirds and marine mammals are surveyed. Biologger tagging is performed in collaboration with hunters as well as a researcher from the Greenland Institute of Natural Resources in Nuuk. Recently, a dump site in the village was surveyed by waste management engineers to investigate possible soil and water pollution. Measurements were also carried out in houses to evaluate the performance of the buildings for energy efficiency and a healthy living environment.Project activities and study results are reported to the community in a workshop organized in Qaanaaq since 2016. About 50 people attend presentations by researchers. The focus of discussion after the presentations is health and safety. Questions are raised about possible pollution around the dump site and concentrations of toxic substances in animals. The involvement of local society in scientific research is a matter of importance in the Arctic. To contribute sustainable future of Arctic societies, we continue collaboration, conversation and designing research together with the local community.
High-resolution mapping of  VOCs using the fast space-time Light Gradient Boosting Machine (LightGBM)
Authors: Lu Bingqing , Li Xiang
Published: March 2024

Volatile organic compounds (VOCs) play a crucial role in atmospheric chemistry, influencing global climate and posing potential health risks to humans. Accurate spatiotemporal estimation of VOCs is vital for establishing advanced early warning systems and controlling air pollution. However, research on high-resolution spatiotemporal prediction of VOCs concentrations using machine learning is still limited. This study conducted an extensive VOCs observational campaign in Shanghai, improving upon the LightGBM model with the integration of spatiotemporal information, satellite data, meteorological data, emission inventories, and geographical data for VOCs estimation. We achieved a high-precision distribution map of VOCs concentrations in Shanghai (1 km, 1 hour resolution), demonstrating the model’s excellent hourly VOCs estimation performance (R^2 = 0.92). Further analysis with SHapley Additive exPlanations (SHAP) regression revealed the significant contributions of each input feature to VOCs estimation. Compared to many traditional machine learning models, this approach offers lower computational demands in terms of speed and memory. Moreover, the model maintained good hourly spatiotemporal VOCs prediction performance during the COVID-19 lockdown. This research analyzed the spatiotemporal variations of VOCs concentrations in Shanghai, providing a scientific basis for future control of VOCs levels in the city and offering algorithmic support for comprehensive VOCs prediction in other regions.
Comparing Payments for Ecosystem Services in Europe and Asia: A Systematic Literature Review Approach
Authors: Jiang Tasi-jung , Chien Herlin
Published: March 2024

Payment for ecosystem services (PES) is a compensation concept used to incentivize landowners to improve land management practices in order to maintain and provide ecosystem services. Examples of such services include river basin protection, forest conservation, flood control, or carbon sequestration. Since the early 1990s, hundreds of PES schemes have been implemented worldwide, with varying degrees of success and has only become a new trend in Asia for the last decade. While analyzing PES cases can identify the factors that contribute to specific outcomes, given the high cost of implementing such schemes and the range of stakeholders involved, our study aims to compare PES cases in Europe where historically the human-nature relationship is more balanced and progressively protected with cases in Asia under rapid industrialization and urbanization. Methodologically, we employ a systematic literature review approach to include a total of 134 articles in Scopus database between 2009 and 2023 for systematic scrutiny. The study analyzes different aspects of the literature growth over the past decade, including project types, beneficiaries, who pays for activities (in USD), spatial scale and current size, and implementation barriers. Our analysis provides insights into the factors that contribute to the success of PES schemes for the goal of improving future research agenda and generating policy recommendations for Asian PES in the near future. In particular, we emphasize the importance of considering the environmental, socio-economic, political, and dynamic contexts of PES policies when designing and implementing such schemes.
Earthquake Coda Magnitude with Distributed Acoustic Sensing at Ridgecrest, California
Authors: Ye Peng , Wang Xin
Published: March 2024

Distributed Acoustic Sensing (DAS) has emerged as a transformative technology in recent years, effectively converting optical fibers into dense seismic arrays. Numerous studies have demonstrated the widespread applications of DAS in seismology, including earthquake detection and subsurface structure imaging. In terms of earthquake source studies using DAS, the conventional approach for determining earthquake magnitudes primarily relies on maximum amplitude measurements. However, this approach faces limitations, such as unknown cable couplings and instrument responses, single-component sensing, complex source radiation patterns, and uncommon amplitude saturation behaviors. To overcome these challenges, we propose a novel method that calculates earthquake magnitudes based on coda waves using DAS. Utilizing a 10 km-long DAS array deployed in Ridgecrest, California, we derive coda wave energy decay to estimate source amplitude terms. Our findings reveal a strong linear correlation between these estimates and seismic magnitudes estimated using broadband seismic network. Furthermore, our study provides insights into the attenuation structure beneath the DAS array, aligning well with shallow velocity structures. This study not only advances our understanding of seismic source characterization using DAS, but also paves the way for more accurate earthquake magnitude estimation using DAS.
Impact of stochastic modeling applied to the receiver clock parameter for Galileo-only and multi-GNSS solutions     
Authors: Mikoś Marcin , Sośnica Krzysztof , Kazmierski Kamil , Hadas Tomasz
Published: March 2024

In Precise Point Positioning (PPP), independently estimating the receiver clock parameters at each observation epoch introduces heightened noise in the estimated station coordinates and troposphere parameters due to correlations. To address this issue, stochastic modeling is applied to the receiver clock parameter, thereby enhancing the stability of PPP solutions and minimizing clock noise for precise time transfer. Importantly, the feasibility of receiver clock modeling relies on GNSS receivers being connected to exceptionally stable atomic clocks, such as hydrogen maser clocks (HM), which exhibit significantly lower noise compared to other clock types.The strategy proposed by our team involves introducing Markov stochastic process modeling for the receiver clock parameters through a random walk. We opted for this stochastic process because of its simplicity in both comprehension and implementation. We conducted tests with different levels of random walk constraints for GNSS stations equipped with various clock types, exploring both Galileo-only and multi-GNSS solutions in kinematic and static PPP modes. We compare the results against a reference solution without any additional constraints. In multi-GNSS solutions, a common clock parameter is determined alongside inter-system biases (ISBs), with the common clock parameter identified as the GPS clock.Research outcomes demonstrate that comparable results can be achieved by imposing constraints solely on the common clock parameter while treating ISBs as constant parameters. Similarly, constraints on both the common clock parameter and ISBs, with a ratio of 1:100, yield the most favorable results. However, adopting other clock-to-ISB constraint ratios, such as 1:1 and 1:10, leads to suboptimal performance. In the static PPP, the introduced clock modeling significantly enhances the precision of time transfer by effectively reducing clock noise. In the kinematic PPP, stochastic clock modeling has a marginal impact on the North and East coordinate components, whereas the Up component exhibits substantial improvement, mainly for GNSS receivers equipped with HM. An examination of Zenith Total Delay (ZTD) in both Galileo-only kinematic and static PPP modes reveals the discernible impact of clock constraints, as evidenced by observed offsets in the respective outcomes. In the case of multi-GNSS solutions, this influence is less prominent, attributed to weaker correlations between ZTD and clock parameters in multi-GNSS solutions compared to Galileo-only.
Seasonal to multiannual marine ecosystem prediction using a deep learning approach
Authors: Park Ji-sook , Park Jong-yeon , Kim Jeong-hwan , Ham Yoo-geun
Published: March 2024

Marine biogeochemistry governs the flux of climate-active gases at the ocean-atmosphere interface, influencing diverse climate feedbacks. Despite advances in Earth System Models (ESMs) for climate-ecosystem predictions, challenges persist in the initialization and validation with biogeochemical observation data. In this study, Convolutional Neural Network (CNN)-based models predict chlorophyll concentrations in a productive large coastal area. The model was trained and validated using Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble datasets and physical–biogeochemical reanalysis data from a data assimilative ESM run. Through sensitivity tests on the model structure and input data, the CNN-based model demonstrates physical interpretability consistent with previous studies. Our optimized model adeptly reproduces annual observational chlorophyll variations in coastal regions where dynamic models face challenges, demonstrating comparable prediction skill to dynamic models in seasonal prediction by capturing large-scale climate variabilities. These findings highlight the importance of combining dynamic models and deep learning approaches, offering the potential for more accurate and comprehensive predictions of marine ecosystems.
Characterisation and localisation of lightning and explosions by a flotilla of stratospheric balloons
Authors: Farges Thomas , Albert Sara , Bowman Daniel , Burgos Gael , Gainville Olaf , Sochala Pierre , Le Pichon Alexis
Published: March 2024

On 3 August 2021, Sandia launched a flotilla of four Heliotrope solar hot air balloons (Bowman et al., 2020) from Belen regional airport in New Mexico (USA) to coincide with the launch of the Boeing Starliner rocket. Three balloons were equipped with two Gem microphones (Anderson et al., 2018) spaced vertically from 30 to 100 m apart, depending on the balloon. The fourth balloon had two infraBSU microbarometers mounted in opposite polarity in order to suppress local interference. These Heliotrope balloons allow level flights between 15 and 25 km altitude for several hours from sunrise to sunset. The rocket launch was cancelled after the balloons were launched, but eight chemical explosions of between 45 and 135 kg TNT equivalent and a thunderstorm took place near the balloons in the first few hours of cruise. After characterizing the measurements of explosions on balloons and two ground seismic stations, we evaluate the performance of a Bayesian method for locating explosions, taking into account local meteorology and whether or not seismic measurements were included. Using acoustic measurements under balloon conditions alone, we highlight the importance of network geometry and propagation between the explosion and the sensors in the localization error. We then characterize the lightning that occurred in a single thunderstorm cell located between 10 and 40 km from three of the four balloons. Several lightning flashes are clearly identified (using the method proposed by Farges and Blanc (2010) for ground thunder measurements and Lamb et al. (2018) for first stratospheric balloon measurements of lightning) and located in 3D with the method validated from explosion measurements. These 3D locations are compared with the 3D thunder model defined by Lacroix et al. (2010) and with the 3D distribution of thunder sound power described by Bestard et al. (2023). Finally, as the storm lasted approximately 45 minutes, continuous thunder emissions occurred. We calculated the cross-correlation time between measurements made under one of the balloons at 30 m apart during this period. We can see a change in the relative arrival delay as the balloon moves away from the storm cell, which does not move over this period. This suggests propagation through the AtmoSOFAR channel as defined by Albert et al (2023).SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.  
Assessing rock glacier velocities on the Tibetan Plateau using satellite SAR interferometry
Authors: Sun Zhangyu , Liu Lin , Hu Yan , Fan Chengyan
Published: March 2024

The information pertaining to rock glacier kinematics plays a crucial role in addressing various scientific inquiries related to permafrost distribution, mountain hydrology, climate change, and geohazards in alpine regions. However, our understanding of rock glacier kinematics on the Tibetan Plateau remains incomplete, with limited observations only made in a few local regions. To fill in this knowledge gap, our study employed the Interferometric Synthetic Aperture Radar (InSAR) technique to comprehensively assess the moving velocities of rock glaciers across the entire Tibetan Plateau. The velocities were assessed using two different methods: the processing of single interferometric pair data and the time series analysis. By utilizing the single interferometric pair data from Sentinel-1 and incorporating time series analysis results using LiCSAR products, we derived the downslope velocities of 41,441 rock glaciers as included in the plateau-wide inventory, i.e., TPRoGI [v1.0]. Our results revealed that a significant proportion of rock glaciers exhibit downslope velocities of 3-10 cm/yr (39.5%) and 10-30 cm/yr (32.7%). Around half of the rock glaciers on the plateau fall into the transitional category (53%), active rock glaciers also occupy a substantial portion (45.6%). Both active and transitional rock glaciers exhibit widespread distribution in the northwestern and southeastern plateaus. The average downslope velocity of the rock glaciers is 15 cm/yr. Rock glaciers on the western and northern plateaus tend to move faster (mean velocity = 26 cm/yr) than those on the eastern and southern plateaus (mean velocity = 12 cm/yr). Our assessment is valuable for the future monitoring of rock glacier kinematics on the Tibetan Plateau in the context of Rock Glacier Velocity (RGV) as an associated parameter of Essential Climate Variable (ECV) Permafrost.
Assessing the climatological stability of the Congo basin rainforest
Authors: De Hertog Steven , Meunier Félicien , Verbeeck Hans
Published: March 2024

The Congo basin forests play a crucial role in the global carbon cycle, hosting a carbon sink of more than 10% of the global sink. This carbon potential also appears more stable than those of comparable other tropical forests. However, despite its importance for global climate, the Congo basin forest is receiving much less scientific attention. Yet, in recent years the body of data and knowledge is reaching a critical level which allows a study on the stability of the Congo basin forest under present and future climates. Here we applied an advanced vegetation model (ED2) over the Congo basin forests and explored their potential (in)stability under different climate forcings. The main objective was to explore the climate sensitivity of the Congo basin forests in terms of functional composition and carbon balance. This allows to asses the risk of the rain forest to shift into a savanna type vegetation. We addressed this question by integrating for the first time observational meteorological data available over the Congo basin in order to evaluate global reanalysis and climate modelling datasets. This led to unique simulations of the vegetation changes observed during past decades as well as for potential climate futures.