bluuebunny/crossref_metadata_2025 huggingface dataset:
Lightning-induced electron precipitation: Statistical analysis of DEMETER satellite data and WWLLN lightning locations
Authors: Linzmayer Václav , Němec František , Santolík Ondřej , Kolmašová Ivana
Published: March 2024

We experimentally analyze the importance of lightning-generated whistlers for electron precipitation from the Van Allen radiation belts. For this purpose, we use the wave and energetic particle data measured by the low-altitude DEMETER spacecraft between 2006 and 2010, complemented by the lightning locations and times obtained by the World Wide Lightning Location Network (WWLLN). We focus on the region above the United States (L-shells between 2 and 3, geomagnetic longitudes between 300 and 360 degrees). This region exhibits a significant difference in the number of lightning between the local summer and winter, allowing us to contrast the two seasons. Additionally, it is located westward of the South Atlantic Anomaly, i.e., the drift loss cone has not yet been emptied, and there are many particles with pitch angles not too far from the bounce loss cone. We show that during the northern summer, when the number of lightning in the region increases tremendously, there is a considerable increase in both the VLF wave intensity and the precipitating energetic electron flux. We perform a correlation analysis to determine the most affected energy range. It also reveals that the effect is more pronounced during the night than during the day, in agreement with the lower wave attenuation in the ionosphere, and it is more pronounced during periods of low geomagnetic activity compared to those of high geomagnetic activity.
Atmospheric Oxidation of Imidazole by Hydroxyl Radicals: Fate of Peroxyl Radical Products
Authors: Golin Almeida Thomas , Martí Carles , Kurtén Theo , Zádor Judit , Johansen Sommer L.
Published: March 2024

In recent years, imidazole and its derivatives have received attention due to their role as components of brown carbon in atmospheric aerosol particles. These compounds absorb solar radiation in the UV-visible range, altering the aerosol optical properties, and acting as photosensitizers, prompting accelerated aerosol particle growth. Although atmospheric imidazoles are thought to be mainly produced in the particle-phase (e.g. via reaction of glyoxal with amines), these compounds were recently observed also in the gas-phase. Studies investigating the fate of imidazole in the gas-phase explored the initial steps of its oxidation by OH radical, identifying the major outcome to be the formation of an OH-addition product. However, this product is an alkyl (C-centered) radical, and its fate following reaction with O2 is still unexplored. In this work, we employed computational methods to investigate the reaction channels available to the first-generation peroxyl radicals produced from the reaction of imidazole with OH radical and O2. The unimolecular reaction pathways were explored with the automated reaction search and kinetics code KinBot. Product distributions under a range of temperatures and NOx concentrations were subsequently obtained by assembling and solving a master equation. Our findings predict that under most conditions considered, the formation of two major closed-shell products is expected: the cyclic diimine 4H-imidazole-4-ol, and the ring-opened species N,N’-diformylformamidine (FMF). The relative yields of these two products is, however, sensitive to NOx levels. While both compounds may be produced under pristine conditions (low NOx), the yield of FMF is predicted to be above 95 % under more polluted conditions (high NOx). These compounds may be further oxidized in the gas-phase, or they may partition into aerosol particles to participate in aqueous-phase reactions.
Climate change impacts on large scale avalanche risk in alpine regions
Authors: Ortner Gregor , Michel Adrien , Kropf Chahan M. , Bühler Yves , Christen Marc , Bründl Michael , Bresch David N.
Published: March 2024

Observations in various regions worldwide document a decline in mean snow depth, spatial extent, and duration of snow cover, indicating a connection to climate change, especially at low elevations. Climate scenarios project further changes, but the exact consequences on future snow cover and avalanche patterns remain unknown. Our work investigates the influence of climate change on the snow cover, specifically focusing on its impact on avalanches and the associated risk to buildings. To compare the consequences of these potential changes on snow avalanche hazard and risk with the current situation, we have developed a framework to model avalanche risk on a large scale. We applied an algorithm to generate a protection forest layer, potential release areas, and conduct snow analysis for current climatic conditions. The RAMMS::LSHIM algorithm within the RAMMS avalanche model produces avalanche hazard indication maps. They are combined with the CLIMADA risk assessment platform, incorporating exposure and vulnerability data, to create spatially explicit risk maps under different avalanche return period scenarios.To address climate change impacts, we have integrated the CH2018 climate scenario data including various model chains into avalanche hazard mapping, using the SNOWPACK snow cover model. Snow cover simulations cover the years from 1997 to 2100 and deliver three day snow accumulation data and layer temperatures for potential future avalanches. We used this data to run the RAMMS::EXTENDED avalanche model with modified snow and temperature parameters. This enabled us to create hazard indication maps considering climate change.Results indicate a potential decrease in the spatial extent of avalanches, especially at lower altitudes, due to rising snowline, particularly in model chains with reduced snowfall. However, within CH2018, other climate model chains suggest increased snow accumulation, resulting in larger avalanches and increased pressure in high-altitude areas.Applying the CLIMADA risk tool to climate change hazard analysis using an enhanced vulnerability curve and uncertainty analysis results in various risk outcomes. An average approach over all model chains suggests a decrease in risk, particularly in low-altitude side valleys. Single model chains with increased snowfall project higher risks despite a reduced affected area. The study underlines the need to incorporate climate change into practical avalanche hazard assessment and subsequently risk analysis.Overall, this research, for the first time, quantifies the impact of climate change on the potential future spatial distribution of avalanches and associated changes in potential risk. The practical applicability of climate change avalanche hazard assessment was demonstrated, offering insights for stakeholders to assess future risks and consider climate change risk appraisal options. 
Role of Earth Observation in multi-(hazard-)risk assessment and management 
Authors: Ward Philip , van Maanen Nicole , de Ruiter Marleen ,   EO4MULTIHAZARDS team
Published: March 2024

Natural hazard impacts are becoming increasingly complex, as demonstrated by real world examples of multi-hazards events. This requires major improvements of our current multi-hazard scientific modelling capabilities. High-quality earth observation (EO) data have the potential to contribute to improving our understanding of multi-hazard events and multi-risk impacts. However, to date there have been limited attempts to include EO data into the workflow of multi-hazard analysis, modelling, forecasting and added-value generation. In this contribution, we review recent developments in using EO data in multi-hazard and multi-risk assessment. We examine how EO data can support our practical understanding of multi-(hazard-)risk, and how this can be made accessible, useful and practical. We provide recommendations for improving EO information (tools, methodologies, accessibility, etc.) and an outlook on the potential evolution of using EO in disaster risk management.
Multi-method attribution of the 2023 boreal summer temperature extremes in the Mediterranean region
Authors: Fuckar Neven-Stjepan , Allen Myles , Obersteiner Michael
Published: March 2024

As global climate change accelerates a spectrum of extreme events (e.g., heatwaves, droughts, etc.) are occurring in many parts of the world at an increasing frequency and intensity threatening the socio‐economic fabric of our modern civilisation. The boreal summer (JJA) 2023 was globally the warmest, while July and August 2023 were the two warmest months on the observational record. Embedded in these global conditions were series of strong heatwaves that in the Mediterranean region often reached above 40deg.C in daily maximums of surface (2m) air temperature (SAT). We apply multi-method attribution approach to illuminate the role of climate change in setting this expectational monthly and seasonal SAT conditions in the Mediterranean.We utilise a collection of observations and reanalysis products combined with large ensembles of CMIP5 and CMIP6 historical and future simulations to analyse the role of atmospheric circulation and anthropogenic factors leading to these extreme events on monthly and seasonal timescales. We also use large ensembles of historical and counterfactual simulations of weather@home2 (climateprediction.net numerical experiments) globally distributed to and executed by volunteers on their home computers to assesses to what extent anthropogenic forcing altered the probability and magnitude of these extremes. We explore conditional perspective of the atmospheric circulation in this attribution analysis. The initial results indicate a significant role of the global climate change in modifying likelihood and intensity of these boreal SAT summer extreme events.
SWAP model potentiality in the viticultural system study and analysis.
Authors: Bonfante Antonello
Published: March 2024

The SWAP model allows studying the behavior of agricultural systems at different spatial and temporal scales, addressing climate change adaptation and mitigation issues.In recent years, it has been used in the viticultural sector to study the soil-plant-atmosphere (SPA) relationships in vineyards and to define and support the terroir concept and its resilience under climate change.This contribution presents the results relating to the ability of the model to (i) shed light on the relationships between water stress and grape quality characteristics and (ii) evaluate the impact of climate change on the responses of the vineyard system of three vine varieties cultivated in southern Italy (Aglianico, Cabernet sauvignon and Greco).In each case study, the calibrated and validated SWAP model output has been used to explore the relations between the plant water stress realized during the growing season and vine responses (physiological and productive responses). The identified relations were successively applied to evaluate the climate change (CC, RCP 4.5 and 8.5 ) adaptation of each vineyard system studied. Furthermore, in the case of the Aglianico grapevine, the evaluation of adaptation to CC was spatially extended to a region of southern Italy (Valle Telesina, BN; 20.000 ha) devoted to high-quality wine production, and the resilience of the terroir concept evaluated.Finally, the strengths and limitations of SWAP application in the viticultural context will be discussed.Keywords: grapevine, SPA system, terroir, climate change, vine water stress, grape quality.
Designing a Global Weather Station Network
Authors: Keppas Stavros , Balis Haris , Dravilas Ioannis , Pagonis John
Published: March 2024

Designing a weather station network is a demanding, multi-objective optimisation problem and usually constrained to local geographies. In this study, the authors deviate from typical approaches that focus the design of weather station networks on a small or country-wide area and present a method that is applicable on a global scale.Prior art suggests that weather networks should exhibit high density, often at 1-3km or finer resolution, especially when deployed over complex topographies and urban landscapes. High station density is usually required to support research on urban micrometeorology, agricultural applications and to capture intricate meteorological mesoscale phenomena such as convective precipitation and sea breeze. High density is also required due to the persistence of temperature inversions at near-surface layers is significantly influenced by topography, leading to prolonged periods of temperature inversion.In this novel approach, the authors suggest the design of a global weather network distributed over millions of hexagons covering the entire world. The number of weather stations per hexagon is determined by the topology (e.g. maximum elevation difference, aspects, water formations, etc.) and the land use (urban coverage, green areas, etc.) of the covered area.The method is materialized via an open-source software tool (available on GitHub) which utilizes freely available elevation data (Copernicus DEM) and land use data (OpenStreetMap) and is capable of preparing the global weather station network in reasonable computation time (~24 hours on a 16-core CPU).Finally, the authors present their findings, discuss the effect of various hexagon sizes and suggest that the design of a global weather station network is viable and computationally feasible.
The impact of model resolution on variability in a coupled land atmosphere model
Authors: Hamilton Oisín , Demaeyer Jonathan , Xavier Anupama , Vannitsem Stéphane
Published: March 2024

Reduced order quasi-geostrophic land-atmosphere coupled models display qualitatively realistic mid-latitude atmosphere behaviour, meaning that such models can produce typical atmospheric dynamical features such as atmospheric blocking. At the same time, due to a low number of degrees of freedom, they are still simple enough to allow for analysis of the system dynamics. These features mean that these models are well suited to investigating bifurcations in atmospheric dynamics, and use a dynamical systems approach to better understand the corresponding atmospheric behaviour. This project introduces a symbolic python workflow for using the flexible  land-atmosphere (qgs, 2020) spectral model with the continuation software AUTO. This work builds on the results of Xavier et al. (2023) to understand how the model variability and predictability is impacted by the model resolution. We also use bifurcation diagrams to better understand how parameters such as atmosphere-land friction impact the atmospheric blocking, and in turn the model atmosphere predictability. This is done for a range of model resolutions to investigate how the number of degrees of freedom impacts both the realism of the model, but also the structures found in the dynamics. Demaeyer, Jonathan & De Cruz, Lesley & Vannitsem, S.: qgs: A flexible Python framework of reduced-order multiscale climate models. Journal of Open Source Software. 5. 2597. 10.21105/joss.02597, 2020.  Xavier, A. K., Demaeyer, J., and Vannitsem, S.: Variability and Predictability of a reduced-order land atmosphere coupled model, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2257, 2023.
Towards the Estimation of Canadian Wetland Methane Fluxes with Airborne Lidar
Authors: Kiemle Christoph , Fruck Christian , Fix Andreas , Ehret Gerhard , Quatrevalet Mathieu , Galkowski Michal , Gerbig Christoph
Published: March 2024

Airborne and satellite based lidar remote sensing combines the advantages of high measurement accuracy, large-area coverage and low-ambient-light measurement capability. The Merlin airborne demonstrator CHARM-F is an Integrated-Path Differential-Absorption (IPDA) lidar providing vertical column concentrations of carbon dioxide and methane up to the flight altitude along the flight track. It operated onboard the German HALO (high-altitude long-range) research aircraft during the CoMet 2.0 Arctic campaign in August and September 2022 over natural and anthropogenic sources of CO2 and CH4 in Canada. Natural methane fluxes from wetlands generally produce weak atmospheric concentration enhancements of the measured atmospheric column (
Modelling greenhouse gas balances of bogs in Germany based on vegetation types and water levels
Authors: Guth Lukas , Piayda Arndt , Jurasinski Gerald , Tiemeyer Bärbel
Published: March 2024

An important share of the greenhouse gas (GHG) emissions of many European and South-East Asian countries is originating from degraded peatlands. However, only the GHG balances of a few sites can be measured directly, as these measurements are both cost- and labour-intensive. Therefore, reliable methods for upscaling peatland GHG balances to a larger scale are necessary. Ideally, such upscaling methods use readily available data and also allow for the assessment of scenarios and implemented restoration measures.In this study, we focused on unused and extensively used bogs in Germany and collected a dataset of published annual balances of carbon dioxide (CO2) and methane (CH4) from bogs within Germany and the surrounding temperate Europe. Each site was assigned to one of eight vegetation types, which are based on a clustering of the German federal biotope type classification to enable later upscaling based on this data. The relationships of the annual CO2 and CH4-balances to vegetation type, mean annual water level and temperature were then analysed with mixed effects modelling.As expected, wet extensive grassland had relatively high CO2 and low methane emissions, while semi-natural bogs showed a small CO2-uptake but higher methane emissions. Most degeneration stages showed an intermediate behaviour. Noteworthy are the comparatively low CH4 emissions of recently rewetted sites with sparse vegetation and of wet unused forested areas. Due to very little available data, the uncertainties of GHG emissions from some vegetation types are large. For very wet vegetation types such as semi-natural Sphagnum-dominated sites, water levels did not improve the GHG emission estimates compared to solely using vegetation data. For dryer sites such as wet extensive grassland, incorporating water levels significantly improved the estimation of both CO2 and CH4 fluxes.The results are broadly in line with previous findings and provide a basis for future upscaling to a German-wide estimation. In some cases, knowledge on water levels after having taking restoration measures will still improve the estimation of GHG exchange. The most severe data shortage occurred for recently rewetted sites with sparse vegetation and wet unused forested bogs as well as subalpine and alpine peatlands.
The French contribution for the NASA HelioSwarm mission
Authors: Le Contel Olivier , Lavraud Benoit , Retino Alessandro , Kretzschmar Matthieu , Génot Vincent , Alexandrova Olga , Mansour Malik , Amoros Carine , Jannet Guillaume , Baruah Rituparna , Mehrez Fatima , Camus Thierry , Alison Dominique , Grigoriev Alexander , Revillet Claire , Studniarek Marina , Mirioni Laurent , Agrapart Clémence , Sou Gérard , Geyskens Nicolas ,   HelioSwarm team
Published: March 2024

The HelioSwarm mission was selected as a MIDEX mission by NASA in February 2022 for launch in 2029 with a nominal duration of 15 months. Its main objectives are to reveal the 3D spatial structure and dynamics of turbulence in a weakly collisional plasma and to investigate the mutual impact of turbulence near boundaries (e. g., Earth’s bow shock and magnetopause) and large-scale structures evolving in the solar wind (e. g., coronal mass ejection, corotating interaction region). The HelioSwarm mission will also contribute to the space weather science and to a better understanding of the Sun-Earth relationship. It consists of a platform (Hub) and eight smaller satellites (nodes) evolving along an elliptical orbit with an apogee ~ 60 and a perigee ~15 Earth radii. These 9 satellites, three-axis stabilised, will provide 36 pair combinations and 126 tetrahedral configurations covering the scales from 50~km (subion scale) to 3000 km (MHD scale). It will be the first mission able to investigate the physical processes related to cross-scale couplings between ion and MHD scales by measuring, simultaneously at these two scales, the magnetic field, ion density and velocity variations. Thus each satellite is equipped with the same instrument suite. A fluxgate magnetometer (MAG from Imperial College, UK) and a search-coil magnetometer (SCM) provide the 3D measurements of the magnetic field fluctuations whereas a Faraday cup (FC, SAO, USA) performs the ion density and velocity measurements. In addition, the ion distribution function is measured at a single point onboard the Hub by the iESA instrument, allowing to investigate the ion heating in particular. The SCM for HelioSwarm provided by LPP and LPC2E is strongly inherited of the SCM designed for the ESA JUICE mission. It will be mounted at the tip of a 3m boom and will cover the frequency range associated with the ion and subion scales in the near-Earth environment [0.1-16Hz] with the following sensitivities [15pT/√Hz at 1 Hz and 1.5 pT/√Hz at 10 Hz]. The iESA, developped by IRAP and LAB, is inherited from the PAS instrument operating on the ESA Solar Orbiter mission. It will provide the ion distribution function at high time and angular resolutions, respectively 0.150 s and 3°. Furthermore the energy range will be ~200 eV to 20 keV with 8% energy resolution. Status of the development of SCM and iESA prototypes will be presented.
Importance of orographic gravity waves over the Tibetan Plateau on the spring rainfall in East Asia
Authors: Li Runqiu , Xu Xin , Xu Xiangde , Shepherd Theodore G , Wang Yuan
Published: March 2024

The springtime persistent rainfall (SPR) is the major rainy period before the onset of summer monsoon in East Asia, which profoundly affects the regional and even global hydrological cycle. Despite the great importance of the mechanical and thermal effects of the Tibetan Plateau (TP) large-scale orography on the formation of SPR, the impact of small-scale orography over the TP remains poorly understood. Here we show that upward-propagating orographic gravity waves (OGWs), which occur as the subtropical westerlies interact with the TP’s small-scale orography, contribute importantly to the SPR. The breaking of OGWs induces a large zonal wave drag in the middle troposphere, which drives a meridional circulation across the TP. The rising branch of the meridional circulation acts to lower the pressure and increase the meridional pressure gradient to the south of the TP by dynamically pumping the lower-tropospheric air upwards. The southwesterly monsoonal flow on the southeastern flank of the TP thus intensifies and transports more water vapor to East Asia, resulting in an enhancement of the SPR. This finding helps more completely understand the impacts of TP’s multiscale orography on the SPR and provides a new perspective on the westerly-monsoon synergy in East Asia.
Three-dimensional kinematic analysis of Northern Kapıdağ Pluton: Implications for a transtensional deformation in NW Anatolia 
Authors: Arık Tunahan , Ünal Alp , Altunkaynak Şafak
Published: March 2024

The Kapıdağ Shear Zone (KSZ) is located in the Kapıdağ Peninsula (NW Anatolia) and syn-kinematically intruded by Northern Kapıdağ Pluton (NKP) along the northern coastline of the peninsula. The NKP displays a granodioritic composition with a discernible progressive deformation from south to north. The southern part is characterized by an isotropic granodiorite with no trace of deformation. Towards the north, it gradually passes into a deformed granodiorite in which the development of ductile and brittle structures is widely observed. To comprehend the nature and origin of deformation within the KSZ, a thorough analysis of micro- and mesostructural features was undertaken, accompanied by a three-dimensional kinematic analysis of the NKP. The NKP exhibits a well-defined mylonitic foliation and stretching lineation, characterized by the shape-preferred alignment of feldspar, quartz, and biotite crystals. Various shear sense indicators, including S-C fabrics and "σ"-type rotated porphyroclasts, are extensively distributed throughout the NKP, pointing to a dextral sense of shear. Microstructures such as chessboard extinction and Grain-Boundary Migrations (GBM) in quartz, myrmekitic textures, and flame pertites in feldspar, as well as sub-grain rotations and bulging recrystallization of quartz, along with the presence of micro-faults and cracks collectively suggest continuous deformation of the NKP from temperatures starting at 600°C to those below 250°C.Three-dimensional strain analysis was conducted on the Northern Kapıdağ Pluton (NKP) using quartz crystals as shear sense indicators, and various parameters including kinematic vorticity (Wk) numbers, Flinn k values, Lode’s ratio, and octahedral shear strains were computed. The outcomes reveal a range of Flinn k values from 1.1 to 5.32. On Flinn’s diagram, the majority of samples plot above the k=1 line, indicative of a transtensional regime. Lode’s ratios exhibit a variation from -0.64 to +0.13, with the Hsu diagram showing that the majority of samples fall within the general constrictional field. To discern the strain component of the NKP, kinematic vorticity numbers (Wk) were determined, ranging from 0.73 to 0.99. This suggests a dominance of simple shear in the deformation rather than pure shear components. The U-Pb zircon and 40Ar/39Ar biotite dating results show that this deformation has developed between 48-36 Ma. In summary, both micro/mesostructural data and three-dimensional strain analyses of the NKP collectively suggest that the Kapıdağ Shear Zone (KSZ) is characterized by a dextral transtensional shear zone dominated by simple shear. We hypothesize that the KSZ was likely formed during the Eocene period as a consequence of strain localization along the break-off of the Tethyan oceanic slab.
A multi-task-oriented spatial and temporal convolutional neural network for high-resolution soil moisture estimation
Authors: Jing Yinghong , Lin Liupeng , Li Yao
Published: March 2024

Soil moisture is an essential state variable that controls the hydrological processes of infiltration, runoff, evaporation, and precipitation. It affects various studies and applications including projection of drought or waterlogging, management of water resources, estimation of agricultural production, forecasting of weather conditions, and analysis of climate change. Currently, passive microwave remote sensing is one of the most effective technologies for large-scale monitoring of soil moisture dynamics. However, due to the insufficient continuity and resolution of passive microwave soil moisture data, it is difficult to meet the requirements of regional fine-grained hydrological research. There is an urgent need for the comprehensive improvement of passive microwave soil moisture products, to enhance their capabilities for various practical applications.
Therefore, in this study, we propose a Multitask-Oriented Spatio-Temporal Convolutional Network (MOSTCN) to estimate daily soil moisture data with high accuracy, good continuity, and fine resolution. The multitask-oriented learning framework consists of gap-filling, multi-source fusion, and spatial downscaling, which can fully utilize multivariate spatio-temporal information. Firstly, the gap-filling process is employed to fill the gaps in the target dataset by considering the spatiotemporal correlation of soil moisture, which includes the partial convolution module, long short-term memory module, and cross-attention module. Subsequently, the multi-source fusion process is designed to combine the assimilated soil moisture data with the reconstructed satellite soil moisture data. The residual dense module and Laplacian attention module are introduced to extract multi-scale and multi-level features, which preliminarily enhance the spatial resolution of the soil moisture data. Lastly, the advanced residual dense convolutional module with embedded attention mechanisms is used to explore the complex nonlinear correlations between soil moisture and various ancillary factors, and then estimate the soil moisture data with high continuity and fine resolution.
The experimental results demonstrate that the MOSTCN method has a robust effect on enhancing the continuity and resolution of passive microwave soil moisture data in China. Compared with in-situ measurements, the proposed method increases the correlation coefficient from 0.57 to 0.72 and decreases the root-mean-square error by 0.015 m3/m3. Its generalization is superior to that of the two baseline methods. This provides an efficient way to generate seamless and high-resolution soil moisture products.
Potential effects of summer Cryosat-2 sea ice thickness observations on sea ice forecast
Authors: Song Ruizhe , Mu Longjiang , Chen Xianyao , Kauker Frank , Loza Svetlana , Losch Martin
Published: March 2024

Skillful Arctic sea ice forecast for the melting season remains a great challenge because there is no reliable pan-Arctic sea ice thickness (SIT) data set for the summertime. A new summer Cryosat-2 SIT observation data set based on an artificial intelligence algorithm may mitigate the situation. We assess the impact of this new data set on the initialization of both short-term and long-term sea ice forecasts in the melting seasons of 2015 and 2016 in a sea-ice couple model with data assimilation. We find that the assimilation of the new summer CryoSat-2 SIT observations can reduce the summer ice edge prediction error. Further, adding SIT observations to an established forecast system with sea ice concentration assimilation leads to a more realistic short-term summer ice edge forecast in the Arctic Pacific sector. The long-term Arctic-wide SIT prediction is also improved especially before the onset of freezing. In spite of remaining uncertainties,  summer CryoSat-2 SIT observations have the potential to enhance Arctic sea ice forecast on multiple time scales.
Interaction between Urban Heat Island and Sea-Breeze: a focus on Shanghai
Authors: Chen Hongying , Top Sara , Hamdi Rafiq , Caluwaerts Steven
Published: March 2024

In the context of ongoing global warming and the intensification of urbanization processes, urban climate research is particularly important. The urban heat island (UHI) stands out as the most typical characteristic of urban climates. Shanghai is recognized as one the largest cities in China, with over 24 million inhabitants. Located on the east coast, Shanghai’s climate is significantly affected by the UHI and sea breeze, particularly during the summer.UHI and sea breezes have been extensively explored in various coastal cities on a global scale.  This study aims to run for the first time the ALARO model over the Shanghai region and analyze interplay between sea breezes and UHI during heat waves (HW). The ALARO-SURFEX regional climate model set-up will be used for dynamical downscaling from ERA5 up to kilometric resolution. Urban effects will be taken into account by running the Town Energy Balance (TEB) module. The model runs will be evaluated based on observations in different Local Climate Zones (LCZs). The ECOCLIMAP database used to characterize the land characteristics has been updated based on detailed urban datasets of Shanghai.  Additionally, this study will explore the effects of LCZs on this interaction.
Exploring aerosol-cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean using the WRF-Chem-SBM model
Authors: Zhao Jianqi , Ma Xiaoyan , Quaas Johannes , Jia Hailing
Published: March 2024

This study employed the WRF-Chem-SBM model which couples spectral-bin cloud microphysics (SBM) and online aerosol module (MOSAIC) to investigate aerosol-cloud interactions in liquid-phase clouds over eastern China and its adjacent oceans. The results indicate that with an increase in aerosol number concentration (Na), cloud droplet number concentration (Nd) exhibits a trend of initially increasing and then decreasing, both over land and ocean. The difference lies in the stronger convective and land surface effects over land, leading to more intense activation, while over the ocean, weaker supersaturation and richer water vapor content result in weaker activation but more favorable conditions for cloud droplet growth. Cloud processes over land are more intense than over the ocean, but the cloud liquid water content (CLWC) in both regions shows a similar trend with the variation of Nd. In precipitating clouds with richer water content and stronger intracloud processes, as Nd increases, the cloud droplet effective radius decreases, and CLWC exhibits a gradual increase followed by a rapid decrease. In non-precipitating clouds with lower water content and weaker intracloud processes, the increase in Nd leads to a more gradual growth of CLWC, and the subsequent decrease in CLWC is also more subtle. Furthermore, this study discusses the impact of meteorological and aerosol conditions on aerosol activation and cloud development. Environments with a moderate Na are more conducive to aerosol activation, while in environments with low to moderate Na, CLWC exhibits faster growth. Compared to humidification, cooling has a more significant effect on aerosol activation and CLWC growth.
Analyzing Mesoscale Eddy Impact on the West Spitsbergen Current in the Fram Strait
Authors: Chien Hwa , Chen Yen-Chen , Chang Huang-Meng , Fu Ke-Hsien , Wang Bo-Shian
Published: March 2024

Accelerated melting of Arctic sea ice, a consequence of global warming, is being exacerbated by increased freshwater inputs. This has led to a significant reduction in the halocline layer within the Fram Strait, enhancing ocean stratification and creating a feedback loop that further accelerates sea ice loss. This process is critical for the formation of North Atlantic Deep Water (NADW), where the West Spitsbergen Current (WSC) plays an essential role in recirculation.Our study delves into the characteristics and influences of mesoscale eddies in the Fram Strait, particularly focusing on their impact on the WSC recirculation and NADW formation. Conducted over three years (2021-2023) during the months of minimal sea ice cover (August to October), the research involved deploying 36 specialized surface mini buoys across the strait. Analytical methods such as horizontal dispersion coefficients, finite-size Lyapunov exponents (FSLE), Lagrangian eddy identification, and sea surface temperature (SST) e-folding time were employed to assess WSC surface dynamics, eddy activities, and air-sea heat exchange.Notably, we observed WSC bifurcation and intense mesoscale seawater mixing in the southwest Yermak Plateau and east of Molloy Deep (MD), areas marked by a rise in SST e-folding scale time gradient and considerable heat loss to the atmosphere (approximately 120 W/m²). Surface water convergence and sinking were detected near the western side of Molloy Deep and the Hovgaard (HG) regions, coinciding with high vorticity zones. Analysis of the buoy trajectories identified 682 eddy samples, forming the basis for a statistical examination of their size, period, intensity, and cyclonic features. This analysis was complemented by correlating eddy trajectories with sea surface height anomaly (SSHA) data, showing notable alignment.Our results reveal a predominance of anticyclonic eddies in the Fram Strait, accounting for nearly 65% of the total eddies. Further, a consistency analysis between these eddies and wind stress curl indicated that about 66% of the anticyclonic eddies in the Molloy Deep region correlate with wind stress curl patterns, suggesting wind influence in their formation
Combining Remote Sensing and Low-Cost Sensors for LULC and Irrigation Characterization in the South of France 
Authors: Orieschnig Christina Anna , Vandôme Paul
Published: March 2024

In the face of climate change, Mediterranean regions, such as the South of France, are increasingly struggling with drought, water scarcity, and low groundwater levels. For agricultural regions relying on irrigation systems to guarantee summertime crop productivity, this is a central issue. Consequently, optimizing agricultural water uses and understanding the impact of irrigation systems on local and regional hydrological processes is indispensable. At larger scales, another challenge is to identify crop types as well as cropping and irrigation patterns for irrigation water management, reservoir operation, and real-time resource allocation. In this context, remote sensing provides a promising approach.  
This study focuses on combining land use - land cover (LULC) analyses based on Sentinel-1 and -2 data and in-situ measurements realized using innovative low-cost sensors, to characterize irrigation water use in two Southern French case study areas. The first of these, the Crau area in Provence, is specialized in using gravity irrigation to make the production of high-quality hay possible even during the arid summer months. The second area is a viticultural one, centred around the Canal de Gignac approximately 100 km further West, in which the majority of vines are sustained using drip irrigation, provided consistent water access is possible. In both cases, the study aimed first to identify irrigated plots, and then to further characterize the irrigation practices with regard to agricultural water use efficiency. 
The LULC analysis was carried out in Google Earth Engine, using a Gradient Tree Boosting (GTB) algorithm on combined Sentinel-1 and -2 imagery from which several spectral indices as well as Haralick texture features were calculated. The detection of irrigated grassland plots further relied on a temporal characterization of phenological stages. Subsequently, a comparative implementation of different irrigation monitoring approaches was carried out, using soil moisture estimates derived from Sentinel-1 and different optical spectral indices. Data from low-cost sensors and local water user associations was used for calibration and validation. 
Preliminary results indicate that combining these diverse approaches make an operational detection and monitoring of irrigation practices possible. For the detection of irrigated vineyard and grassland plots during the 2023 growing season, overall accuracies of 92% and 95% respectively were achieved. The comparison of different irrigation monitoring approaches showed that the Normalized Difference Moisture Index (NDMI, p=0.002), the Shortwave Infrared Water Stress Index (SIWSI, p=0.001) and the Specific Leaf Area Vegetation Index (SLAVI, p=0.001) showed the highest potential for accurate irrigation detection.
Projections of Elbrus glaciers, proglacial lakes and dead ice areas.
Authors: Postnikova Taisiya , Rybak Oleg , Gubanov Afanasy , Zekollari Harry , Huss Matthias
Published: March 2024

Mt Elbrus being the highest peak in Europe (5642 m a.s.l.) is an inactive volcano currently covered by nearly thirty glaciers. Glaciated area is 112.20 ± 0.58 km³ and 5.03 ± 0.85 km³ in volume as revealed by Kutuzov et al., (2019) for the year of 2017. Current and future deglaciation of the Caucasus in general and of the Elbrus glacial massif in particular can be the reason for various negative consequences for the local economy and environment. Therefore, relevant prognostic studies are of great value both for the academicians and for the policymakers.In this research, we consider probable scenarios of Elbrus glacier change in the 21st century. We mostly focus at the phenomena accompanying degradation of glaciation, such as the formation of glacial lakes and areas of “dead” ice buried under the moraine, which is relevant for predicting Glacial Lake Outburst Floods (GLOFs). Future climate projections, based on SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5 scenarios, were employed. Surface mass balance is calculated using temperature-index method (Huss and Hock, 2015). Glacier dynamics is emulated in 1-D global glacier model GloGEMflow (Zekollari et al., 2019) updated by incorporation of the module responsible for the description of debris cover evolution (Postnikova et al., 2023). Model adaptation for Elbrus involves the model transition from colluvial (e.g. slope erosion) to exarational (e.g. emergence of subglacial sediments) debris-cover sources, which aligns with the region's geological setting. These two modes of modelling the debris cover transformation in time are compared. While model validation reveals a slight underestimation of mass loss in the early 21st century, it accurately reproduces general mass loss patterns.Under the warmest climate change scenarios, almost all of the remaining ice mass in the Central Caucasus will be concentrated on Elbrus. At the same time, Elbrus glaciers are anticipated to retreat above the 4000 m elevation by 2100. In case of moderate warming the position of glacier fronts may stabilize at an altitude of 3600-3700 m. According to our estimates, glacier retreat may lead to the formation of up to 17 new proglacial lakes. Under a moderate warming scenario (SSP1-2.6), up to 8 proglacial lakes may appear. The largest of them is expected to form at the terminus of the Djikaughenkioz ice plateau dammed by debris-covered dead ice in the 2030s-2040s assuming no sufficiently effective runoff channels are established.This study was funded by the RSF grant number 23-27-00050.
Ship-based mapping of protected seafloor habitats and anthropogenic stressors in a very shallow coastal environment: Spatial data integration in a marine protected area offshore Sylt (North Sea)
Authors: Sander Lasse , Yapa Tharaka , Hoffmann Jasper , Saathoff Merten
Published: March 2024

Area-wide hydroacoustic mapping in coastal environments is a time-consuming and cumbersome task due to the limited swath width of most devices, especially in shallow waters. At the same time, these environments hold important functions for coastal ecosystems, are subject to intensive anthropogenic use, and are characterized by dynamic and complex geomorphological interactions of waves, currents, and tides. We presently investigate the seafloor geomorphology of a marine protected area in the eastern North Sea based on a combination of own archived hydroacoustic data, hydrographic single-beam survey data, and fishing vessel position data. The research area is located within 12-nautical miles from the coast, covers approx. 1,200km2, and is characterized by water depths between 12 and 18 m. The topography of the seafloor is relatively flat and dominated by mobile sands although gravel and hard substrate (boulder reef) environments commonly occur throughout the area and are protected under the EU Habitats Directive. The properties and spatial distribution of these habitats remain currently unknown, despite the fact that the area hosts intensive fisheries with bottom-contact gears and one of Europe’s largest marine sand extraction sites. Our results show that the integration of different data sources allows an effective assessment of essential habitat parameters, natural seafloor processes, and anthropogenic stressors. Against this background, a strategy to more closely survey and/or monitor specific areas can be devised in order to better protect seafloor habitats and to mitigate human impacts on coastal ecosystems.  
Recycle of quarry byproducts for producing a new Zn fertilizer
Authors: Galamini Giulio , Malferrari Daniele , Altimari Fabiana , Orlandi Silvia , Barbieri Luisa
Published: March 2024

Zinc (Zn) is a crucial micronutrient for plants, related with tolerance against diseases. When crop demand exceeds Zn availability in the soil, using Zn­-fertilizers becomes necessary (biofortication), however, even in foliar application, soluble Zn salts are mostly used, which are prone to leaching and consequently exhibit limited uptake by plants.
In response to this challenge, a novel controlled-release formulation, utilizing mine wastes as carrier, was developed, involving an energy-efficient process with ambient temperature and pressure, and a reaction time of approximately 8 hours.
Formulations were prepared by mixing a zeolite-rich (clinoptilolite) tuff with 2 quarry by-products, namely lapillus and pumice, using different dosages. We conducted studies on the kinetics of Zn adsorption and release, ultimately identifying the most effective mixture which comprised 70% zeolite-rich tuff and 30% pumice.
To assess the effectiveness, a fertilization test was performed via foliar application in Vitis vinifera, aiming to evaluate the Zn coverage, and the persistence of the product against simulated rainfall, in comparison with conventional ZnSO4 fertilizer.
The test confirmed greater Zn resistance to rain leaching, also suggesting potential for reducing treatment dosages, thereby mitigating environmental-related impacts. Moreover, the presence of 30% pumice would allow significative reuse of mining byproduct.
Project funded under the PNRR–M4C2INV1.5, NextGenerationEU-Avviso 3277/2021 -ECS_00000033-ECOSISTER-spk1
 
Predicting Coastal Flooding in the Mediterranean with Remote Sensing and Machine Learning
Authors: Re Alice , Minola Lorenzo , Pezzoli Alessandro , Camps-Valls Gustau
Published: March 2024

Due to its historically low tidal variations, the Mediterranean Sea basin has seen significant coastal urbanisation, exemplified in the densely populated Italian region Liguria. However, the region faces increased vulnerability to extreme sea level changes and coastal flooding due to potential climate change-induced storminess.Machine learning has recently received increased attention in the literature as regards the ability of data-driven approaches to solve flood-related problems, including the identification of areas potentially susceptible to inundation in support of risk preparedness and resilience in coastal cities. This work explores the application of machine learning using widely available remote sensing datasets to predict the inundation extent for a modelled 100-year return period coastal flooding event in Liguria. Numerical simulations produced by local administrations in the context of the EU Floods Directive serve as ground truth due to the absence of post-event inundation maps. Various pre-processed remote sensing datasets are employed as predictors, including land cover data, spectral indices and high-resolution DEM.The results highlight challenges in integrating diverse timescales and data types and can be used to assess the influence of predictors on coastal resilience. The study also addresses the benefits and drawbacks of different machine learning algorithms in evaluating coastal resilience within this approach.-------------------------------------------------------------------------------------------------------------------------------------ReferencesWoznicki, S. A., Baynes, J., Panlasigui, S., Mehaffey, M. and Anne Neale. “Development of a spatially complete floodplain map of the conterminous United States using random forest.” Science of the Total Environment 647 (2019): 942-953.Ireland, Gareth, Michele Volpi, and George P. Petropoulos. "Examining the capability of supervised machine learning classifiers in extracting flooded areas from Landsat TM imagery: a case study from a Mediterranean flood." Remote sensing 7.3 (2015): 3372-3399.Fogarin, S., et al. "Combining remote sensing analysis with machine learning to evaluate short-term coastal evolution trend in the shoreline of Venice." Science of The Total Environment 859 (2023): 160293.Tsiakos, Chrysovalantis-Antonios D., and Christos Chalkias. "Use of Machine Learning and Remote Sensing Techniques for Shoreline Monitoring: A Review of Recent Literature." Applied Sciences 13.5 (2023): 3268.Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., & Prabhat, F. (2019). Deep learning and process understanding for data-driven Earth system science. Nature, 566(7743), 195-204.Camps-Valls, Gustau, et al., eds. Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences. John Wiley & Sons, 2021.