bluuebunny/crossref_metadata_2025 huggingface dataset:
Northeast Greenland speleothems trap forest pollen during MIS
Authors: Donner Anika , Vessies Jet , Marquer Laurent , Spötl Christoph , Edwards R. Lawrence , Moseley Gina E.
Published: March 2024

Diminishing ice sheets, an intensification of the hydrological cycle, and shifts in vegetation composition and abundance, are some of the results of the Arctic’s amplified response to climate warming. Improved understanding of Arctic amplification can be achieved through investigation of past interglacial periods. Although an increasing number of studies exploring past interglacials in Greenland exist, northeastern Greenland remains under-investigated, despite being highly sensitive to the effects of Arctic amplification.
Here, we investigate the palaeoenvironment under warmer and wetter climate conditions by using pollen trapped in speleothems that were deposited in northeastern Greenland (80°N, 22°W) during late Marine Isotope Stage (MIS) 11. The results are placed in the context of a sensitivity study into modern pollen compositions recorded in surface samples as well as published Holocene records from eastern and northern Greenland. The deposition of speleothems in northeastern Greenland during MIS 11 and the composition of the trapped pollen assemblages provide a first-order proxy for drastically different atmospheric and oceanic boundary conditions compared to today. Modern and Holocene pollen samples are dominated by open land vegetation (shrubs and herbs), whereas the MIS 11 speleothem-trapped pollen show an abundance of conifer trees, primarily fir and pine, as well as an array of deciduous trees, shrubs, and open land vegetation. These results are in agreement with findings from other studies investigating southern Greenland during MIS 11. The speleothems and trapped pollen used in this study thus provide direct terrestrial evidence for the presence of higher vegetation in northeastern Greenland during MIS 11 and indirectly help to constrain the extent of the ice sheet at that time.
Extratropical intrusions and their role in tropical flood events: A South Pacific perspective
Authors: Pilon Romain , de Vries Andries , Domeisen Daniela
Published: March 2024

Extratropical Rossby waves are a potential source of instability for driving convective disturbances in the tropics. In the South Pacific, island nations are subject to flooding associated with such convective disturbances, yet these have not been conclusively linked to any large-scale processes. Using an object-based approach, this study specifically explores in particular how Rossby waves propagating into the tropics can contribute to the formation of extratropical-tropical cloud bands, which can cause flooding events. These cloud bands are associated with substantial precipitation events and serve as easily detectable proxies to identify when such intrusions occur. Building upon this foundation we use ERA5 reanalysis along with a detection analysis for tropical-extratropical cloud bands and potential vorticity streamers and cutoffs to establish a climatology of such intrusions and cloud bands. This allows us to demonstrate the statistical association of extratropical intrusions with intensified deep convection, in particular over the tropical central South Pacific. We find that these intrusions contribute significantly to the occurrence of floods in the Polynesian islands. In summary, this study allows us to connect the interaction between the extratropics and the tropics with flood events in the South Pacific.
Enhancing Building Height Estimation through Occlusion Reduction with Advanced Deep Learning Models
Authors: Yan Yizhen , Huang Bo , Wang Weixi , Xie Linfu , Guo Renzhong , Zhao Yunxiang
Published: March 2024

Building heights play a crucial role in various urban research fields, including 3D modeling, urban environmental analysis, sustainable development, and urban planning and management. Numerous methods have been developed to derive building heights from different data sources, including street view imagery, which offers detailed, ground-level perspectives of buildings. However, occlusions from street elements such as trees and vehicles present significant challenges, especially in densely built or complex urban areas. To address this challenge, we propose the use of advanced deep learning models for occlusion reduction, enhancing building height estimation from street view images. As trees typically cause the most occlusion, we employ an open-set detector and a large segmentation deep neural network to create tree masks in the images. Subsequently, we use a stable diffusion model for image inpainting, restoring parts of buildings occluded by trees. These inpainted images are then processed through building instance segmentation, yielding clearer building boundaries for height estimation. Moreover, we integrate a single-view metrology-based height estimation method with a building footprint auxiliary approach, leveraging their respective strengths and mitigating the impact of varying distances between street view cameras and buildings. Our methodology is validated using a dataset comprising 954 buildings and 3814 images. Experimental results demonstrate that our approach increases the percentage of height estimates within a two-meter error margin by approximately 7%, confirming its effectiveness. This work offers a cost-effective solution for large-scale building height mapping and updating, and it opens new avenues for urban research requiring accurate building height data.
Preliminary analysis of seismic attenuation and heterogeneities in Weiyuan Shale Gas Field: Coda Q and Peak delay time analysis
Authors: Abbas Aqeel , De Siena Luca , Yang Hongfeng , Gabrielli Simona , Zhu Wei-Mou
Published: March 2024

During hydraulic fracturing (HF) stimulation in unconventional reservoir development, seismic attenuation significantly affects high frequency microseismic data. Analyzing attenuation parameters, including scattering and absorption, provides valuable insights into reservoir properties and changes that result from HF injections. These attenuation parameters were mapped in 3D using the MuRAT (multi-resolution seismic attenuation tomography) software with a dataset of approximately 32,000 events over two years in the Weiyuan shale gas field (WSGF). Firstly, the coda quality factor Qc (intrinsic absorption), which quantifies coda wave energy loss, is calculated at large lapse time in three frequency bands (3, 6 and 9 Hz). Subsequently, we measure the peak delay time, the time lag between the direct S-wave onset and the highest amplitude arrival. Our preliminary results show that Qc has strong absorption at lower frequencies in specific volumes compared to higher frequencies. Meanwhile, peak delay times indicate consistently stronger scattering along the Weiyuan anticline and Molin fault structures across all frequency bands. We propose that the observed strong absorption is associated with the reservoir and injected fluid, while scattering is linked to pre-existing structural heterogeneities and unmapped faults.
A mathematical framework to quantify physical damages from concurrent and consecutive hazards
Authors: De Angeli Silvia , Borre Alessandro , Trasforini Eva , Ottonelli Daria , Boni Giorgio , Ghizzoni Tatiana
Published: March 2024

When two or more natural hazards occur in the same location simultaneously or within a short time frame, the physical integrity of assets and infrastructures can be compromised, and the resulting damage can be higher than the simple sum of the damages generated by individual hazards occurring in isolation. Current literature highlights the lack of comprehensive frameworks to quantify the damages caused by multiple hazards. Complexity in formalizing quantitative aspects and understanding feedback loops between hazard, exposure, and vulnerability emphasizes this gap. This research presents a comprehensive mathematical framework for quantitatively assessing multi-hazard physical damage on exposed assets, such as buildings or critical infrastructures, over time. The proposed framework covers both the damages generated by concurrent hazards (i.e., hazards that impact the same assets simultaneously), as well as by consecutive hazards (i.e., the second hazard impacting the asset while it is still undergoing recovery from the damages caused by the first hazard). In case of concurrent hazards, the proposed framework models the increased damage resulting from the combined impacts. In the case of consecutive events, the proposed formalization considers the effect of cumulative damages, the reduction in the exposure value, the modification of vulnerability in the time in between hazards, and the recovery dynamics. The framework is applied to a real-world case study in Puerto Rico, including the impacts from the concurrent wind and flood generated by the passage of Hurricane Maria, as well as the impacts caused by the consecutive seismic sequence of 2019-2020. The application to the Puerto Rico case study well highlights the potentialities and limitations of the proposed approach, specifically regarding data availability.By offering a generalized formalization to perform quantitative multi-hazard impact assessments across a diverse array of natural hazards and incorporating amplification phenomena and recovery dynamics, the framework provides scientists and decision-makers with a thorough and enhanced comprehension of the impacts resulting from concurrent and consecutive events. This deeper understanding serves as valuable input for conducting comprehensive multi-hazard risk assessments and implementing effective disaster risk reduction strategies.
Feasible task? The application of the Schmidt-hammer method for dating rock glaciers made of conglomerate rock
Authors: Gautsch Eva , Kellerer-Pirklbauer Andreas
Published: March 2024

The Schmidt-hammer (SH) is a well-established method in studying glacial and periglacial landforms in alpine regions. Schmidt-hammer rebound values (or R-values) allow the relative-age dating of landforms by quantifying the degree of weathering and therefore length of surface exposure. R-values are controlled by lithological variations impacting weathering rates. SH sampling in a specific study should therefore focus on one lithology. Earlier studies found out that some rock types are less suitable than others because of their specific weathering rind development over time. Some rock types are even unsuitable for the application of the SH. In the past, conglomerates for instance were rarely used for SH measurements, which may be related to problems in SH discrimination between the matrix and the clasts of conglomerates. In this study, we applied the SH method at several relict rock glacier systems and lateral moraine ridges which consist of conglomerate and sandstone material of Upper Carboniferous age. The landforms studied are in two cirques (Rosaninalm, Hinteralm; 46.9°N, 13.8°E) in the Gurktal Alps, Austria. We accomplished SH sampling at altogether 21 sites with 100 individual SH measurements per site. The 21 SH measurement sites are located along five longitudinal profiles that were placed over the different landscape forms, the longest one over a horizontal distance of 1.3 km. Measurements focussed on the matrix material of the conglomerates. Mean R-values vary between 29.6 and 39.0. Using these results and assuming a reasonable mean decrease in R-value of 1.5 per ka (based on nearby data from gneiss material), one can assume that the landforms studied were formed over a total period of approximately 6000 years. Individual landform units, in our case mostly rock glaciers, seem to have formed over periods of between 1.1 and 4.9 ka. By using these age estimates and present permafrost conditions, the onset of moraine and rock glacier formation was presumably during the Oldest Dryas and landform stabilisation occurred during the early Holocene. Several uncertainties remain, however, which will be addressed at the poster.
Variability and trends in subtropical gyres derived from 25-year satellite chlorophyll-a observations
Authors: Volta Chiara , Marullo Salvatore , Calmanti Sandro
Published: March 2024

Previous studies, based on satellite observations, suggested that global warming caused all subtropical gyres to expand over time (Polovina et al., 2008; Leonelli et al., 2022). This raised major concerns about the potential increase in ocean desertification and its impact on the Earth’s climate system. Here, the longest satellite chlorophyll-a (chl-a) concentration dataset currently available is used to analyze the evolution of the most oligotrophic areas in the five major subtropical gyres on Earth at a fine spatial-temporal resolution over 25 years (January 1998 - December 2022). These gyres include the North and South Atlantic SubTropical Gyres (NASTG and SASTG, respectively), the North and South Pacific SubTropical Gyres (NPSTG and SPSTG, respectively), and the Indian Ocean SubTropical Gyre (IOSTG). Different thresholds of chlorophyll-a concentrations are used to defined three subregions within each gyre: the oligotrophic area, whose chl-a is less than or equal to 0.1 mg m-3, and the ultra- and hyper- oligotrophic areas where chl-a does not exceed 0.07 and 0.04 mg m-3, respectively. Our results indicate that ultraoligotrophic conditions prevail in all five systems, and that oligotrophic and ultraoligotrophic zones in all gyres combined have reduced and expanded, respectively, at the same rate (0.3%/yr) since 1998, while the hyperoligotrophic area has increased globally at an annual rate of 3.4%. Results also reveal that the most affected gyres are the NASTG, the NPSTG and the IOSTG, where the hyperoligotrophic subregions have expanded at an annual rate of 17.8, 22.8 and 8.6%, respectively, and their combined area in 2022 was about 5 times larger than it was in 1998. No statistically significant (p>0.05) trends were detected in the SASTG and SPSTG, although an increasing tendency in their hyperoligotrophic subregions is observed. Altogether, the results suggest that, despite no significant variation in the overall size of subtropical gyres being observed in 25 years, their hyperoligotrophic cores are expanding and would lead to reduced productivity in these systems.
 
Polovina, J.J., Howell, E.A., and Abecassis, M. (2008). Ocean’s least productive waters are expanding. Geophysical Research Letters, 25, L03618, doi:10.1029/2007GL031745
Leonelli, F.E., Bellacicco, M., Pitarch, J., Organielli, E., Buongiorno Nardelli, B., de Toma, V., Cammarota, C., Marullo, S., and Santoleri, R. (2022). Ultra-oligotrophic Waters Expansion in the North Atlantic Subtropical Gyre Revealed by 21 Years of Satellite Observations. Geophysical Research Letters, 49, e2021GL096965, doi:10.1029/2021GL096965
Impacts of shipping emissions on air quality: emission factors and PM source apportionment in the coastal city of Toulon, France
Authors: Gunti Quentin , Chazeau Benjamin , Temime-Roussel Brice , Xueref-Remy Irène , Armengaud Alexandre , Wortham Henri , D'Anna Barbara
Published: March 2024

Maritime traffic can have a significant local impact, particularly in port areas during the docking and undocking phases. Air quality measurements conducted in certain port cities show that ship emissions are quantitatively comparable to those from road traffic and are contributing to a significant deterioration of air quality. This pollution is now recognized as a real societal problem and a proven danger for human health. Since the reduction of sulphur content in ship fuels in 2020, only few studies have been carried out to analyse in detail the contribution of shipping to urban pollution. A month-long measurement campaign was carried out from August 24 to September 21, 2021, in the port of Toulon on the French Mediterranean coast. Particle concentration, size distribution, and chemical composition as well as gas concentrations were measured using state-of-the-art instruments such as Scanning Mobility Particle Sizer (SMPS, TSI), High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS, Aerodyne), Multi-Angle Absorption Photometer (MAAP, Thermo), Gas Concentration Analyzer (G2401, Picarro), Optical Particle Counter (OPC, Grimm), Condensation Particle Counter (EnviCPC100, Palas), Aethalometer (AE33, Magee) and various gas analyzers (100E, 200E and 400E from Teledyne).In this study, the emission factors (EFs) for pollutants emitted from shipping were determined using a carbon mass balance approach. A total of 50 exhaust plumes was identified and quantified.In addition, the organic fraction of the particles measured by HR-ToF-AMS was used to populate a source apportionment model based on positive matrix factorization (PMF) method.  The source deconvolution was performed for mass spectra with mass/charge ratios (m/z) ranging from 12 to 256 with a time step of 1 minute. Besides, mass spectra derived from docked ferries were used as constraining profiles. The model has been supplemented with spectra from the literature, in particular hydrocarbon-type and cooking-type organic aerosols. These features enhanced the deconvolution process, enabling emissions associated with cooking activities, road traffic and shipping to be distinguished. Ancillary measurements such as meteorological data, particle number, black carbon, and gaseous pollutants were used to underpin the physical accuracy of each organic aerosol factor in the source apportionment model. Finally, an eight-factor solution was chosen: three organic factors were associated to shipping, a hydrocarbon-type organic aerosol (HOA) associated with traffic exhaust emissions, a cooking-type organic aerosol (COA), a less oxidized organic aerosol (LOOA), a more oxidized organic aerosol (MOOA) and a last factor of intermediate oxidation.The results of this analysis underscore the significant influence of maritime emission on urban pollution in the port area of Toulon.
Distributed and time-series estimates of basal melt from Kamb Ice Stream’s grounding zone ocean cavity
Authors: Horgan Huw , Robinson Natalie , Stevens Craig , Stewart Craig , Hulbe Christina , Lawrence Justin , Schmidt Britney , Washam Peter
Published: March 2024

Melt beneath Antarctica’s large cold-cavity ice shelves remains a major source of uncertainty in ice sheet projections. Beneath these ice shelves melt is typically greatest both at the ice shelf front and at the grounding zone where ice first goes afloat. Grounding zone melt is thought to have a significant influence on ice flow across the grounding line, but can be difficult to estimate using remote sensing methods due to flexure of the overriding ice shelf. Added complexity in the grounding zone is caused by the thin water column, abundant basal crevassing, and the possible addition of subglacial fresh water draining from beneath the ice sheets. Here we present two independent estimates of basal melt from the ocean cavity of Kamb Ice Stream’s grounding zone, Ross Ice Shelf, West Antarctica. The first method uses repeat phase-sensitive radar observations to estimate melt in profiles from approximately 5 km seaward of the grounding line to approximately 3 km upstream of the grounding line. The second method uses an approximately 10-month long time series of oceanographic observations from a site 3.5 km seaward of the grounding line. Both methods are complemented by the high resolution observations provided by the Remotely Operated Vehicle (ROV) Icefin. The spatially distributed estimates show a more than tripling of melt rate within 5 km of the grounding line. The mooring derived melt rates demonstrate a melt-rate dependence on diurnal and spring-neap tidal currents. The average mooring melt rate more closely matches the radar-based estimates when a drag coefficient previously estimated using Icefin observations is used. Lastly we demonstrate an interesting correlation between mooring derived melt rates and ice shelf surface velocities obtained from Global Navigation Satellite System (GNSS) observations.
Groundwater resource assessment in the Upper Godavari Sub Basin, India: A soft computing and CMIP6 Ensemble Approach.
Authors: Choudhary Sourav , Murlidhar Pingale Santosh , Khare Deepak
Published: March 2024

Groundwater is a critical lifeline for sustaining water resources in Upper Godavari Sub Basin, India's arid regions. However, due to impeding water requirement and demand in these regions along with anthropogenic complexities has raised serious concerns for this vital resource. Along with anthropogenic activities, Climate change also threatens this precious resource due to scarcity of surface water mostly during the summer season of the year. Hence, to comprehend this important issue, the groundwater resource assessment needs to be done for present as well as future scenarios. Therefore, the present study assesses the groundwater resource using a SWAT-MODFLOW model which is a combination of advanced hydrological model with cutting-edge numerical groundwater model. Individual surface and groundwater models are developed in SWAT and MODFLOW respectively and then are linked using the linkages files to get the more enhanced surface and groundwater interaction in the form of recharge, groundwater level and interaction of rivers with sub surface. The surface and groundwater models are calibrated and validated using the streamflow and groundwater level data. The calibrated model thus presents the current scenario of groundwater allocation which is then simulated with different bias corrected climate variables for getting the status of groundwater for future SSPs scenarios. From a range of CMIP6 climate models, the best model is selected based on the statistical index such as NSE, the correlation coefficient, R2, MAE, RMSE, MSE, and NRMSE which was NESM3 in the present case with a highest correlation and R2 with IMD precipitation and temperature dataset. The best selected climate model (NESM3) is then bias corrected using the empirical quantile method. Along with the numerical approach, to map the groundwater level data, soft computing approach using RFR and GBR is also employed to predict the groundwater level data for future scenarios. The optimization of these models was done by the Particle PSO. The study findings in Upper Godavari Sub Basin, India, revealed significant changes in groundwater levels across different seasons, with particularly significant increases observed during the dry season. The study showed that MODFLOW-GBR-PSO is more accurate in predicting groundwater level than MODFLOW-GBR, MODFLOW-RFR-PSO and MODFLOW-RFR. The result also predicted decreased rainfall for the SSP 585 scenario which in turn lead to drop in groundwater level and recharge in the distinct parts of the sub basin. Hence, from the above result a proper mitigation and framework needs to be prepared to counterfort the diminishing groundwater resource for the betterment of environment.Key words: climate change, hydrological model, SWAT, Nash-Sutcliffe efficiency (NSE), Root mean square error (RMSE), Random Forest regression (RFR) and Gradient Boosting Regression (GBR), Swarm Optimization method (PSO).
Validating monitoring methods for riverine macroplastic pollution
Authors: Vriend Paul , Drok Sylvia , Kamp Nadieh , Collas Frank , Vijver Martina , Bosker Thijs
Published: March 2024

Riverine macroplastic pollution (>0.5 cm) is omnipresent and can negatively impact ecosystems and livelihoods. Monitoring data are crucial for understanding the nature and extent of pollution as well as aiding the design of effective intervention strategies. Recent years have marked the development of methods to collect surveillance data, primarily focusing on the monitoring of floating plastics and plastics deposited on riverbanks. Today, these methods need validation. Criteria that are essential in robust monitoring are the accuracy and precision of collected data, and the minimum observable particle size. Addressing these challenges, we have conducted field experiments aimed to review the most widely employed protocols: the RIMMEL protocol for floating macroplastics and the river-OSPAR protocol for macroplastics deposited on riverbanks. We find that the recovery of larger pieces ranges between 80-90% for both methods, with the accuracy decreasing significantly when considering smaller items sizes, item colour, number of observers, and factoring in external variables such as bridge height or riverbank surface type. The precision, however, varied greatly between the different experiments. These results indicate that the limits & usage of data from different protocols are highly context dependent. It further highlights the urgent need to include these uncertainties in their communication and utilization. Our result show the urgency of standardizing the operating protocol to optimize the accuracy and precision for measuring riverine macroplastics, and of the necessity to quantify uncertainty in studies estimating plastic fluxes using the two protocols.
The GWR model-based regional downscaling of GRACE/GRACE-FO derived groundwater storage to investigate local-scale variations in the North China Plain
Authors: Ali Shoaib , Ran Jiangjun
Published: March 2024

Groundwater storage and depletion fluctuations in response to groundwater availability for irrigation require understanding on a local scale to ensure a reliable groundwater supply. However, the coarser spatial resolution and intermittent data gaps to estimate the regional groundwater storage anomalies (GWSA) prevent the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GARCE-FO) mission from being applied at the local scale. To enhance the resolution of GWSA measurements using machine learning approaches, numerous recent efforts have been made. With a focus on the development of a new algorithm, this study enhanced the GWSA resolution estimates to 0.05° by extensively investigating the continuous spatiotemporal variations of GWSA based on the regional downscaling approach using a regression algorithm known as the geographically weighted regression model (GWR). First, the modified seasonal decomposition LOESS method (STL) was used to estimate the continuous terrestrial water storage anomaly (TWSA). Secondly, to separate GWSA from TWSA, a water balance equation was used. Third, the continuous GWSA was downscaled to 0.05° based on the GWR model. Finally, spatio-temporal properties of downscaled GWSA were investigated in the North China Plain (NCP), China's fastest-urbanizing area, from 2003 to 2022. The results of the downscaled GWSA were spatially compatible with GRACE-derived GWSA. The downscaled GWSA results are validated (R = 0.83) using in-situ groundwater level data. The total loss of GWSA in cities of the NCP fluctuated between 2003 and 2022, with the largest loss seen in Handan (−">−15.21 ± 7.25 mm/yr), Xingtai (−">−14.98 ± 7.25 mm/yr), and Shijiazhuang (−">−14.58 ± 7.25 mm/yr). The irrigated winter-wheat farming strategy is linked to greater groundwater depletion in several cities of NCP (e.g., Xingtai, Handan, Anyang, Hebi, Puyang, and Xinxiang). The study's high-resolution findings can help with understanding local groundwater depletion that takes agricultural water utilization and provide quantitative data for water management.
Spontaneous tree growth and carbon dynamics during the first decade after removal of a coniferous monoculture at a humid temperate forest site
Authors: Graf Alexander , Hofer Anna , Müller Laura , Schmidt Marius , Leuchner Michael , Ketzler Gunnar , Ney Patrizia , Drüe Clemens , Pütz Thomas , Vereecken Harry
Published: March 2024

In September 2013, 8.6 hectares of a 70-year old Norway spruce (picea abies) monoculture were cleared in the newly founded national park Eifel (Germany) and left to spontaneous regrowth of the expected deciduous forest matching the site’s climate and soil conditions. The site is part of the 38.5 hectare experimental catchment “Wüstebach” (50° 30’N, 6° 19’E, 595 to 630 m a.s.l.), one of the core investigation sites of TERENO (TERrestrial ENvironmental Observatories, https://www.tereno.net). Most of the rest of the catchment is still covered by the original spruce monoculture. Its energy and matter exchange with the atmosphere, most notably of CO2, is monitored by an ICOS associated eddy-covariance station (DE-RuW) since 2010. In 2013 after the partial deforestation, a second flux station was installed near the centre of the clearcut. Due to an overpressure of game (boar and deer) in the area, 2 hectares of the central clearcut area are protected against grazing by a fence. CO2 budget and albedo results from the first four growing periods after the clearcut were presented by Ney et al. in 2019 (https://doi.org/10.1016/j.agrformet.2019.04.009). Here, we will give an update covering the first ten growing periods after deforestation (2014-2023). Most notably, regrowing vegetation on the initially almost bare clearcut turned it from a source back into a sink of atmospheric CO2 eight years after the deforestation. We will give an overview on how flux components (soil) respiration and gross primary productivity, season length and peak fluxes contributed to the difference between the spruce forest and the early and recent stages of the regrowing forest. For the last eight years, we recorded the species, height and partly the diameter of all spontaneous regrowing trees in the deforested area in a 10 m corridor both inside and outside the fence. Regrowth was strongly dominated by rowan (sorbus aucuparia, >1200 trees), a pioneer species propagated through their berries by birds that was present with at least one adult tree already before the deforestation beside further trees in distant surroundings. The next two important species were spruce and birch (betula pendula), whose seeds are propagated by wind. Rowan and birch grew in height approximately twice as fast as spruce. The presence of the protective fence affected all species, especially rowan, which grew more than twice as fast on the inside of the fence.
Will extreme precipitation events like July 2021 become more frequent in the future? Insights from Belgium using MAR 
Authors: Brajkovic Josip , Doutreloup Sébastien , Ghilain Nicolas , Archambeau Pierre , Pirotton Michel , Vandelnotte Kobe , Serras Fien , Fettweis Xavier
Published: March 2024

The July 2021 rainfall event that affected western Germany, the Netherlands and Belgium was of unprecedented intensity, reaching 170 mm of daily totals in some places. To estimate the probability of such events in the near and far future (up to 2100), the regional climate model MAR is used to run simulations at a resolution of 5 km. For this purpose, MAR is coupled with a set of 4 CMIP6 Earth System Models (ESMs) for 4 IPCC SSP scenarios over an area encompassing Belgium and Luxembourg.An extreme value analysis is applied to the output for the period 1980-2100 for different rainfall durations (1 to 5 days). Our results show that such extreme precipitation events remain extreme throughout the century, but the probability of their occurrence increases by an order of 10 or more in the most pessimistic scenario. However, our analysis suggests that methodological choices can have a major impact on the results. In particular, the Peak Over Threshold approach shows larger changes in frequency than the Annual Maxima  approach, with less uncertainty in the results due to larger sample sizes of extreme events. 
Ground Deformation Monitoring in Yan'an New District Using Time Series InSAR Method
Authors: Xiao Jinghui , Hu Xie
Published: March 2024

Urban sprawl results in an increasing area of land being transferred into impervious layers. The city of Yan'an in Shaanxi Province in China, located in the hilly gully area of the Loess Plateau, has implemented the Mountain Excavation and City Construction project, aiming to transform the loess and gully area into an urbanized environment with an area of 78.5 km2. The increased flat land will be used to accommodate 400,000 people. The Mountain Excavation and City Construction project on the Loess Plateau is by far the largest geotechnical project in the loess area in the world. It is also an engineering trail to seek the balance between urbanization and sustainable development.It is challenging to carry out such a large-scale construction in loess gullies where the hydrogeological and engineering conditions are complicated. The loess are naturally prone to deform. Our study applies time-series Interferometric Synthetic Aperture Radar (InSAR) analysis to measure the ground deformation in Yan'an New District. The reported deformation rates reach as large as 70 mm/yr, primarily in the filling areas. The main contributing factor to the deformation is sediment compaction. A stabilization of the new landform is anticipated in several years. Continuous monitoring plays an integral role in mitigating hazards in such loess environment.
Rates and Drivers of Coastal Cliff Erosion in England from 2 Decades of Lidar Observations
Authors: Coker Cristina , Javadi Akbar , Palmer Steven , van Maanen Barend
Published: March 2024

Coastal cliff erosion affects communities worldwide. In England, cliffs make up approximately 54% of the coastline, a vast proportion of which is of weak to very weak rock resistance. Being able to adequately quantify rates and styles of retreat as well as relating these to their driving forces is key to making informed decisions on future coastal management strategies.Nationwide change analysis, spanning more than 20 years in places, was carried out by comparing the earliest and most recent LiDAR Digital Elevation Models (DEMs) using raster differencing in a GIS environment. Erosion rates over the cliff face were derived by excluding any bias caused by the presence of vegetation from the change analysis. Uncertainty of erosion rates is affected predominantly by the precision of the LiDAR sensors (typically ±15cm in elevation), and was derived at each location by comparison with a network of ground control points. Limitations of a DEM differencing approach are widely discussed in the literature, particularly in areas of high relief where overhanging and undercutting features may be present. Nonetheless, this large-scale assessment provides a consistent approach to estimate erosion rates and was used as a basis for the selection of sites at which more extensive topographic analysis was carried out in 3D, overcoming some of the limitations of a raster differencing approach. Sites were selected to capture the variability in intrinsic (e.g., geology, slope, aspect) and extrinsic (e.g., waves, tides, rainfall) drivers of retreat. An open-source Python workflow was developed by integrating the M3C2 plugin for Cloud Compare to calculate distances between subsequent timesteps of point cloud data, after which the volume of meshed erosion clusters was computed. As a result, an inventory of cliff face erosion scars was compiled, with attributes relating to scar shape, area, volume and elevation relative to cliff top height. A comparison of the two approaches for calculating erosion rates highlighted the ability of the 3D workflow to capture cliff failure in greater detail and with higher accuracy, at the expense of increased computational costs. Findings also indicate spatio-temporal variations in erosion patterns which are related not only to the intrinsic nature of each site, but also to its climatology. It is expected that the broad spatial scale of this research will provide some insights into the main styles and drivers of retreat affecting specific stretches of coastline in England.
Identifying the Transitions in the Stable Socio-Environmental System Due to Extreme Events 
Authors: Jain Jagriti , Khare Deepak , Munoz-Arriola Francisco
Published: March 2024

The critical challenge in a hydrological system is to predict whether the system approaches a critical threshold. The urban centres are grappled by the extreme events especially floods with the shifts from one stable state to another in an urban socio-environmental system. Here, we identified the critical transitions of hydrological processes, including precipitation and runoff, by analyzing their shifting nature. Structural break-regression models, incorporating shifts in both mean and trend, are applied to the series.  The point of change indicates the transition within the system.  These models are then evaluated using two widely employed penalized likelihood criteria for multiple changepoints. These criteria strike a balance between the quality of model fit (measured by likelihood) and the consideration of parsimony. Two models are tested i.e., bisegmentation and penalised maximum likelihood with the white noise detection. The latter was found to be better fit to both precipitation and runoff for the three cities (Guwahati, Mumbai, and Dehradun) in India.
Using small sensors to measure the effect of mobility policies on urban air pollution
Authors: von Schneidemesser Erika , Schmitz Sean , Caseiro Alexandre , Kerschbaumer Andreas
Published: March 2024

Small sensors have the potential to provide valuable complementary measurements to established air quality monitoring stations in urban areas. The flexible deployment options of small sensors also allow for short- or longer-term deployment to e.g., accompany policy implementations. Here we present the results from a number of case studies in Berlin where we used a combination of small sensors and reference instrumentation to assess individual policy’s impacts on local air quality, a metric important to policymakers’ assessments of their success. These measurement campaigns included both the stationary and mobile deployment of small sensors, in collaboration with the city. Data generated by the small sensors were calibrated using co-locations and the open-source 7-step methodology developed in our group (Schmitz, et al. 2021, ACP). Measurements deployed alongside the implementation of several policies captured before-after measurements of nitrogen oxides (NOx) and particulate matter (PM). Data from the urban monitoring network was used to account for changes in meteorology and city-wide changes to assist in isolation of the signal from the policy implementations. Through the implementation of a new bike lane, cyclists’ exposure to NO2 was reduced by 20%; in another case, the closure of a street to vehicle traffic reduced local air pollution to the levels of the urban background. These results were subsequently accounted for by policymakers when determining the success of each measure, considering the implications for human health.
Open access Data Sets of Vertical Profiles for Turbulent Ekman Flow generated by DNS tlab code
Authors: Issa Sally , Ansorge Cedrick , Pedro Mellado Juan , Kostelecky Jonathan
Published: March 2024

In the pursuit of advancing our comprehension of the atmospheric boundary layer and the associated exchange processes near the surface, the accessibility of high-quality data assumes a pivotal role. An open-access approach is acknowledged for catalyzing collaborative efforts, empowering researchers globally to harness available information for their investigations. This has the potential to refine existing models, validate hypotheses, and instigate innovations in climate modeling and predictive simulations. Here, we introduce an open benchmark data repository, accessible through static collection of DOIs, to share the statistics of simulations for turbulent Ekman flow. This data, forming the foundation for numerous publications on Ekman flow, has been established as a suitable virtual lab environment in prior works for studying crucial aspects of the atmospheric boundary layer. We believe that the availability of this data under the FAIR paradigm has the potential to facilitate further exploitation, enhancing our understanding of process-level intricacies in the atmospheric boundary layer.The data is being generated since 2011 using the tLab tool-suite (github.com/turbulencia/tlab) for direct numerical simulation (DNS) on some of Europe’s largest supercomputers, including juqueen and juwels at Jülich Supercomputing Centre, and hawk at Höchstleistungsrechenzentrum Stuttgart. It is now accessible in the long-term data repository refubium.fu-berlin.de of Freie Universität Berlin.The inaugural contribution to this repository is a comprehensive, curated set of data exploring the influence of turbulence scale separation, specifically the Reynolds number. A series of simulations spans a range of Reynolds numbers, corresponding to a variation of approximately tenfold in the friction Reynolds number Reτ. The shared dataset encompasses various parameters, including vertical profiles of velocity, budget terms of scalar and momentum budgets, statistical moments up to the third order of velocities, scalars, and derivatives, providing a holistic view of Ekman flow dynamics across a range of Reynolds numbers. This enables the identification of inviscid scaling behavior and the development of scaling theories for the application of these simulations to real-world problems.While the dataset also captures effects of stable stratification and rough surfaces, these aspects are, beyond the scope of this abstract.Keywords— Numerical simulation, Ekman flow, Turbulence, Surface layer, Simulation Theory∗ This work is funded by the ERC Starting Grant "Turbulence-Resolving Approaches of the Intermittently Turbulent Atmos-pheric Boundary Layer [trainABL]" of the European Research Council (funding ID 851347). The data was generated under thatcomputing grants hhh07, hku24, stadit at Jülich supercomputing centre and trainABL / Bundesprojekt 44187 at Höchstleistungs-rechenzentrum Stuttgart)
Reassessing yunnanozoans from the Chengjiang fauna: Insights from ultrastructure and thermal analysis
Authors: He Kaiyue
Published: March 2024

Yunnanozoans (Yunnanozoon and Haikouella) from the early Cambrian Chengjiang fauna have been classified as stem vertebrates, cephalochordates, hemichordates, stem deuterostomes or even problematic bilaterians. The claimed ultrastructure of their branchial arches comprising cellular cartilage and fibrillin microfibers has led to speculations linking yunnanozoans to vertebrates. Raman spectrum analysis reveals that these yunnanozoans fossils experienced a maximum temperature of approximately 300°C during their geological history. Scanning electron microscopy (SEM) and transmission electron Microscopy (TEM) of branchial arches of yunnanozoans fossils, revealed that the organic matter was preserved as homogeneous membranous organic carbonaceous films, ruling out of potential preservation of cellular cartilage and fibrillin microfibers. The integrated research incorporating ultrastructure and thermal analysis have led us to removes yunnanozoans from vertebrates.
Depth dependence of mantle plume flow beneath mid-ocean ridges
Authors: Liu Sibiao , Zhang Fan , Zhao Lei , Zhang Xubo , Lin Jian
Published: March 2024

Hotspot-related anomalies observed in mid-ocean ridge systems are widely interpreted as the result of upwelling mantle plumes interacting with spreading ridges. A key indicator of this interaction is 'waist width', which measures the distance of plume flow along the ridge. Current scaling laws for waist width, premised on a gradual decrease in plume temperature along the ridge, often overlook sub-ridge longitudinal thermal variations, potentially biasing width measurements at various depths. In this study, we refined waist width measurements by tracking the material flow and its thermal diffusion from the plume source in plume-ridge interaction models. These non-Newtonian viscoplastic models integrate ridge spreading, lithospheric cooling with hydrothermal circulation, and mantle dehydration. Model results show that the hot plume initially boosts upwelling from the deep mantle to near the dehydration zone, followed by a slowdown and lateral spread across and along the ridge. In addition to strongly correlating with plume flux and spreading rate, the pattern and distance of plume flow vary with depth. At deeper depths, the plume expands radially in a pancake-like thermal pattern with shorter along-ridge distances, while shallower, it shows an axial pipe-like dispersion over longer distances, forming a concave structure. This is shaped by the cooling of the plume material during the phase of decelerated upwelling and along-ridge dispersion within the dehydration zone and cooling of the oceanic lithosphere associated with plate spreading. Estimates of plume buoyancy flux, derived from both material- and isotherm-tracking waist widths, show significant variations at different depths, suggesting that understanding depth-dependent plume dynamics beneath mid-ocean ridges is crucial for reconciling the observed discrepancies in buoyancy flux estimates.
The Effect of Natural Hazard on Residential Housing Prices: a Hedonic Difference-in-Differences Analysis of a Flooding Event in Southern Taiwan
Authors: Hsu Yaowen , Ho Shih-Ping , Tsai Christina C. W.
Published: March 2024

One of the significant factors that drives the value of a real estate property is the risk of flooding events. When the risk of flooding is perceived to be high, the market price of the property should decrease in a housing market whose participants are mainly risk-averse. In this study, we consider the case of a flooding event that ensued from a violent storm on August 23, 2018, in southern Taiwan. We estimate the effect of the flooding event on residential housing prices in Kaohsiung, the largest city in southern Taiwan.
The analysis framework we employ is the difference-in-differences (DID) approach combined with hedonic pricing. This approach represents a state-of-the-art research design that is widely used to identify the causal effect of an event, because of its compelling ability to deal with the issue of endogeneity. Houses in the region directly affected by the flooding are chosen to be the treatment group, while houses in the neighboring region that were not subject to the flooding consist of the control group.
We first test the assumption of parallel trends, which is a necessary prerequisite of the DID analysis. The test is done via three methods: visual inspection, dynamic effect test, and placebo test. The tests show that it is reasonable to assume parallel trends for the treated and control groups.
We then estimate the treatment effect of the flooding event. The regression coefficient of the interaction term, which represents the treatment effect of the event under investigation, is statistically significant and negative at the 95% level of confidence. We also find that heterogeneity in treatment effect exists – different types of housing properties are affected to different degrees, with apartments affected least. On average, housing value decreases by 8.6% after a property experiences the flooding event in the following three years. The common hedonic variables are also statistically significant with expected signs.
Our findings are informative to policymakers who aim to design better infrastructure constructions, either for enhancing the property values of the areas subject to high risks of flooding, or for taxation purposes that may provide a source of financing for infrastructure improvement.   
 
The authors gratefully acknowledge the financial support from the National Science and Technology Council of Taiwan ( Grant Number: 111-2124-M-002-006) 