bluuebunny/crossref_metadata_2025 huggingface dataset:
Microclimatic effects of idealized urban planning projects on their surrounding area
Authors: Schneider Martin , Tötzer Tanja , Bügelmayer-Blaschek Marianne
Published: March 2024

Over the past years, microclimate simulations and analyses became an important tool for the impact assessment of different planning scenarios of real estate projects on a local site. Based on the results of evaluated scenarios, the need for (additional) climate adaptation measures can be identified and improved design concepts might be realized. While this process led to several positive developments and best practice examples, the impact of a building project on the microclimate of the surrounding areas in spatial proximity to the development area is often still neglected. Especially if formerly green areas are sealed, cold-air production areas are lost, or cold-air corridors blocked. Even positively assessed microclimate studies for the local site itself, can have a negative effect on the microclimate of the surrounding area. While large urban planning projects (e.g., area size > 15 ha) in Austria require environmental impact assessments, policy makers and administrative units lack objective criteria to request spatially extended microclimate analyses for medium sized projects that not only affect the development area but also the neighbouring quarters.In the prevalent research project, “Development of a criteria catalogue for requiring extended microclimate analyses”, funded by the Climate and Energy Fund and carried out under the program "Austrian Climate Research Programme Implementation", potential microclimatic impact of urban planning projects on their surroundings during autochthonous weather conditions in summer is evaluated through sensitivity experiments with the urban climate model PALM-4U. Based on the concept of Local Climate Zones (LCZ), idealized real estate projects are set up in two locations (inner city and periphery) of the city of Linz (Austria). For each location, the following selected characteristics of static input data are varied: (1) size of building site, (2) building footprint, (3) building height, and (4) degree of soil sealing. By comparing simulation results to the reference scenario of an unsealed, green area, the potential impact in terms of intensity and spatial range is assessed.Results of the sensitivity experiments are used to compile a compact set of criteria, which allows policy makers and administrative units to request spatially extended microclimate analyses to evaluate effects of medium sized urban planning projects on the district-wide microclimate if impacts are expected.
A set of indicators to guide a WEFE transition in irrigated agriculture in the Duero Basin, Spain
Authors: Rodriguez-Sinobas Leonor , Schneider Xenia , Sanchez-Revuelta Maite , Pacetti Tommaso , Merheb Mohammad , Segovia-Cardozo Daniel A.
Published: March 2024

The Duero basin is the largest watershed in the Iberian Peninsula, with a surface of 98.073 km2 distributed in Spain and Portugal. The 80% of the surface area is in Spain (78.891 km2), where plays an important role for the country’s energy and food production. However, in the region, droughts are frequent and have increased in the last years stressing water resources and creating competition and friction among water users. Likewise, the energy demand for irrigation has also increased as along with energy and fertilizer prices. The uncertainty on future water resources is critical and it must be managed. Within this context, this paper will show the analysis of the current situation from a Water, Energy, Food and Ecosystems (WEFE) perspective and how it has developed several WEFE indicators and their inter-relations. The results may be used to analyze the effect of future scenarios, which foresee a decrease between 8 to 10% in water availability in the basin by 2039; it is also foreseen an increment in the prices of energy, fertilizers and production inputs. These indicators and their illustrations will help the stakeholders in their decision making and a WEFE-Nexus transition actions to overcome challenges in a resilient and sustainable way.The work has identified and quantified a set of 12 indicators for the present conditions at two different spatial scales: two Duero sub-basins (Cega-Eresma-Adaja, and Bajo Duero) and three irrigation districts (Río-Adaja, Villalar de los Comuneros and “El Carracillo), each one has different source of water (surface, subsurface and mix). Three indicators for water, two for energy, two for food production and five for ecosystems were proposed and quantified by using information obtained by modelling and literature review. The results were compared both at different scales and in different situations.
Stress heterogeneity and its relation to geology during the 2016-2017 central Italy earthquake sequence
Authors: Martínez-Garzón Patricia , Meier Men-Andrin , Lanza Federica , Collettini Cristiano , Dresen Georg
Published: March 2024

Quantifying the stress field variability at different wavelengths and how it evolves over time has important implications for the development of earthquake sequences. As small earthquakes occur more frequently than larger ones, their focal mechanisms are essential to create larger catalogs, that allow to statistically quantify the kinematics of earthquake sequences within a region and the preferential orientations of co-seismic strain release. Inverting earthquake focal mechanisms is widely used to infer a number of stress-related parameters characterizing a crustal volume, including the orientation of the principal stress axes, maximum horizontal stress, and the relative magnitudes of the principal (stress ratio R) and horizontal stresses (APHI). If resolution allows, these stress parameters can be employed to quantify stress variability and heterogeneity in different rock volumes. Here we studied the 2016-2017 Central Italy seismic sequence that is characterized by the occurrence of three mainshocks: the Mw 6.0 Amatrice, Mw 5.9 Visso and Mw 6.5 Norcia. These major events nucleated on normal faults with kinematics consistent with the regional stress field. Taking advantage of a high-resolution catalog generated with deep learning and containing ~56.000 focal mechanisms, we calculated the distribution of stress parameters over small crustal volumes activated during the sequence and resolved the variability of the stress field during three different time periods punctuated by the three largest events. We found a change in the local trend of SHMax with better defined orientations consistent with the regional stress field towards the SE of the Amatrice mainshock, and larger variability to the NW where also Visso and Norcia mainshocks ruptured. These changes in SHMax trend also coincide with a contrast in the APHI parameter quantifying the relative magnitude of the horizontal stresses. The area between the Amatrice, Visso and Norcia epicenters displayed the lowest APHI (i.e. representing a normal faulting stress regime where SV >> SHMAX) and the lowest relative magnitude of the S2 (SHMax in the case of normal faulting). Furthermore, an increase in the APHI parameter is observed at depths below 8 km, reaching transtensional and strike-slip stress regimes in some local volumes. The area surrounding the rupture of the Amatrice mainshock displays the largest deviations from the regional stress over the entire analysed time period, indicating a stress anomaly driven by the properties of the medium or stress heterogeneities caused by static stress transfer that are persisting over the one-year time span of the catalogue. The observed local stress deviations from the regional stress field can help illuminating dominant local loadings affecting the deformation pattern.
Nanoparticle Heteroagglomeration with Natural and Synthetic Suspended Particulate Matter
Authors: von der Kammer Frank , Walch Helene , Lehutso Raisibe Florence , Hofmann Thilo
Published: March 2024

The assessment of nanoparticle NP transformation in the aquatic environment is essential for comprehending the fate of nanoparticles and conducting accurate risk assessments. Nanoparticles encompass a variety of materials, including manufactured nanomaterials, nanoplastics, and natural colloids. Environmental transformation comprises four main routes: dissolution/leaching, abiotic transformation/degradation, biotic transformation/degradation and (hetero-)agglomeration.The kinetics of heteroagglomeration play a pivotal role in nanoparticle (NP) transport mechanisms in rivers. The parametrization of heteroagglomeration processes between NPs and suspended particulate matter (SPM) was hampered by the variability of SPM floc composition and conformation/size on spatial and temporal scales. Available analytical methods were either unsuitable or required unrealistic high NP concentrations. The SPM used in heteroagglomeration studies was either unrealistically simple (silica particles, clays) or exceptionally unique (specific natural SPM sample).After a thorough analysis of mechanisms of floc formation and the relevant building blocks of natural, riverine SPM and the successful and reproducible laboratory synthesis of model SPM flocs, we designed a method to determine the heteroagglomeration attachment efficiency αhetero  under environmentally relevant conditions. This allows well controlled laboratory experiments as well as standardization for risk assessment purposes. The heteroagglomeration attachment efficiency () constitutes the most suitable parametrization of particle-particle interactions. The presented test matrix combines synthetic model SPM flocs with the model freshwater composition suggested in OECD TG 318, both designed to represent agglomeration-relevant characteristics of natural systems. The test matrix was employed in a newly developed stirred-batch method addressing the shortcomings of existing strategies to determine αhetero. Time-resolved inductively coupled plasma mass spectrometry allowed to work at realistic concentrations of NP (5 ppb) and SPM flocs (20 and 40 ppm).The approach was evaluated by testing the heteroagglomeration of CeO2 nanoparticles in four different combinations of SPM and water chemistry.Natural flocs in natural water
Natural flocs in synthetic (TG318) water
Synthetic flocs in natural water
Synthetic flocs in synthetic water
The results show the applicability and precision of the invented test system and the synthetic SPM but also reveal some differences between results from natural and synthetic water chemistry which can be explained by the type and quality of the NOM. Calculated transport distances for 50% unassociated NPs reached up to 370 km, what is unexpectedly high.
Assessing the influence of climate on Antarctic submarine gully evolution  
Authors: Gales Jenny , McKay Robert , De Santis Laura , Rebesco Michele , Laberg Jan Sverre , Kulhanek Denise , patterson Molly , King Maxine , Kim Sookwan
Published: March 2024

Antarctica’s continental slopes hold invaluable insights for understanding past climate, ice-sheet dynamics, ocean circulation, erosional and depositional processes, and submarine geohazards over millennial timescales. We present a multidisciplinary dataset from the Ross Sea continental margin, Antarctica from the EUROFLEETS-funded ANTSSS expedition and International Ocean Discovery Program Expedition 374, including core records spanning ~3 Ma, multibeam echosounder and single-channel seismic data and legacy seismic data available through the Antarctic Seismic Data Library System. Here, gully and channel systems occur at the head of the Hillary Canyon, with palaeo-gullies evident in seismic data. New sediment core-seismic correlations show that palaeo-gullies evolved on the Ross Sea continental margin over multiple glacial cycles, filling and reforming associated with glacial advances, cold dense water cascading and other processes. We show multidisciplinary datasets that constrain the signature of down and along-slope processes and examine factors driving their timing, frequency, and impact on gully evolution. We discuss the implications of these findings in relation to Neogene and Quaternary West Antarctic Ice Sheet expansions to the shelf edge.
Connecting gas exchange, carbohydrate storage, and growth dynamics during variable drought stress and recovery in Douglas fir
Authors: Alongi Franklin , Knüver Timo , Ziegler Yanick , Ruehr Nadine
Published: March 2024

Tree mortality from increasing drought events have been reported worldwide, with the potential to threaten both forest health and services such as timber production. Tree species’ resilience to drought events is dependent on a range of inter-connected mechanisms, such as gas exchange and hydraulic regulation, which further affect processes such as non-structural carbohydrate (NSC) storage, growth, and stress signaling. The effect of drought on these numerous plant processes have been well studied, however knowledge gaps remain regarding how these processes respond in concert to different drought intensities, as well as the recovery ability following stress release. In a greenhouse setting, we investigated how variable drought intensities (control, mild, severe) affected photosynthetic assimilation (Anet), NSC storage, and growth at multiple timepoints throughout a five-week drought and five-week recovery period in two-year-old Douglas fir (Pseudotsuga menziesii). Here, we show how system-wide physiological stress tracks drought intensity, with severe drought leading to an earlier cessation of Anet, greater utilization of starch to increase soluble sugars, and reduced growth as compared to the mild and control treatments. This study offers a holistic view of plant-physiological responses to drought stress intensity, and underscores how physiological damage sustained during severe drought events can have long-lasting impacts on forest health.
A Machine Learning-based Method for Identifying Segmented Fault Surfaces Through Hypocenter Clustering
Authors: Piegari Ester , Camanni Giovanni , Mercurio Martina , Marzocchi Warner
Published: March 2024

We present a method for automatically identifying segmented fault surfaces through the clustering of earthquake hypocenters without prior information. Our approach integrates density-based clustering algorithms (DBSCAN and OPTICS) with principal component analysis (PCA). Using the spatial distribution of earthquake hypocenters, DBSCAN detects primary clusters, which represent areas with the highest density of connected seismic events. Within each primary cluster, OPTICS identifies nested higher-order clusters, providing information on their quantity and size. PCA analysis is then applied to the primary and higher-order clusters to assess eigenvalues, enabling the differentiation of seismicity associated with planar features and distributed seismicity that remains uncategorized. The identified planes are subsequently characterized in terms of their location and orientation in space, as well as their length and height. By applying PCA analysis before and after OPTICS, a planar feature derived from a primary cluster can be interpreted as a fault surface, while planes derived from high-order clusters can be interpreted as fault segments within the fault surface. The consistency between the orientation of illuminated fault surfaces and fault segments, and that of the nodal planes of earthquake focal mechanisms calculated along the same faults, supports this interpretation. We show applications of the method to earthquake hypocenter distributions from various seismically active areas (Italy, Taiwan, California) associated with faults exhibiting diverse kinematics.
Surfing the Climate Wave: Laura and Joan's Expedition in the Delta 
Authors: Boqué-Ciurana Anna , López Madrid Josep Maria , Carbonell Eloi , Aguilar Enric , Lozano Carlos
Published: March 2024

Embark on a compelling narrative that chronicles the experiences of Laura and Joan, students participating in a field trip to the Delta del Ebre, responding to a collaborative initiative spearheaded by the Center for Climate Change (C3) at the Universitat Rovira i Virgili (URV). This narrative is shaped by the surf-centric climate services thesis of Dr. Anna Boqué, emphasizing the seamless integration of academic research into pragmatic climate mitigation measures. 

 Notably, the realization of this initiative is indebted to the steadfast support of the Department of Research and Universities of the Generalitat de Catalunya. Laura and Joan, guided by insights from the URV's Climate Change Research Center, engage in data analysis and strategic formulation of climate crisis interventions, exemplifying the transformative potential of interdisciplinary collaboration. 

 This story, available in both Catalan and English, forms an integral part of a collection disseminated to educational institutions and libraries. The accompanying website offers a didactic guide and a diverse array of materials for a thorough exploration, underscoring the intersection of academic research, climate services, and community-driven initiatives. Join us in acknowledging the catalyzing impact of collaboration and recognizing the pivotal role played by the Generalitat de Catalunya in empowering students to contribute meaningfully to a resilient and sustainable future. 

We acknowledge Carlos Lozano, Montse Español, Xavier Gómez Cacho, and Jordi Sales for their contribution to this work. 

 
The potential of using a combination of in-situ, campaign and flight data to analyse Ozone across data sparse regions in Africa
Authors: Moolla Raeesa , Oluwole Adegun A. , Nyathi Clinton W. , Garland Rebecca ,   IGAC-led TOAR Africa over Ozone Working Group
Published: March 2024

Air pollution and climate change threaten Africa’s development because of their negative impacts on human health, well-being and productivity. Air pollution and climate change reduce agricultural productivity, for example, with implications for food and nutritional security. Two of the biggest issues for African countries are the lack of data on the emissions causing air pollution and climate change, and inadequate policy and implementation capacity. Countries need this data to plan policies that can reduce air pollution and deliver national development priorities and climate goals. Ozone as an anthropogenic greenhouse gas affects the climate beyond increased warming due to its impact on evaporation rates, cloud formation,precipitation levels and atmospheric circulation..  Combustion of fossil fuels is one of the principal processes that release the gaseous precursor pollutants that react to form O3, which is a major factor in Africa, as most populations on the continent are dependent on fossil and  other fuels for heating and cooking,also, emissions from vehicle exhausts and electric generators with unknown ozone concentrations (Ihedike et al, 2023)  . Furthermore, along with the presence of the precursor gases, many meteorological conditions promote the formation of O3 (Guar et al, 2014). The formation, transport, chemical destruction, deposition and atmospheric lifetime of O3 will determine its concentration in any given area.Aircrafts  and satellites provide a global-scale view on tropospheric ozone and its precursors, with different types of sensors being sensitive to different parts of the atmosphere. They help in improving forecasting of weather conditions and more recently in improving   predictions of air quality. Data from these aircraft and satellite  sensors are complementary to more detailed and more precise data sets . A wide variety of trends and variations in tropospheric ozone were reported by aircraft sensors in the Tropospheric Assessment Report (TOAR Phase I) in the 1990s (Gaudel 2018).The distribution of the tropospheric ozone over the western Pacific Ocean has also been observed during aircraft experiments, but in Africa there has been little information on these data findings and as well their potential limitations. However, this project intends to address these knowledge gaps. Data from these aircraft sensors are complementary to more detailed and more precise in-situ data that are spatially and temporally limited in which this study intends to address. Prelimanary results from the Working Group will be presented, as well as challenges and limitations of data aquisition and data represntation, in data scarce regions.
The fractions skill score for ensemble forecast verification
Authors: Wolfgruber Ludwig , Necker Tobias , Kugler Lukas , Weissmann Martin , Dorninger Manfred , Serafin Stefano
Published: March 2024

This work explores how the Fractions Skill Score (FSS), originally developed for deterministic forecasts of binary events, can be used for probabilistic forecast verification. By comparing a selection of four ensemble-based methods to compute the FSS, we highlight their distinct behaviour with ensemble size, neighbourhood size, and frequency of occurrence of the forecast event. Our study emphasizes that only a specific variant of the FSS, which we refer to as "probabilistic FSS", demonstrates reasonable behaviour with ensemble size. We reveal that the probabilistic FSS depends on ensemble size in a similar way as the Brier Skill Score, despite performing a neighbourhood-based instead of a grid-point-based forecast evaluation. We derive a formula that describes the expected behaviour of the probabilistic FSS with changes in ensemble size. Finally, utilizing a unique dataset of high-resolution 1000-member ensemble precipitation forecasts for Germany, we explore the impact of ensemble and neighbourhood size on the predictive skill by studying various subsamples of the full ensemble.
An assessment of equatorial Atlantic interannual variability in OMIP simulations
Authors: Prigent Arthur , Farneti Riccardo
Published: March 2024

The eastern equatorial Atlantic (EEA) seasonal cycle and interannual variability of the sea surface temperature strongly influence the climate of the surrounding continents. It is thus crucial that models used in both climate predictions and future climate projections are able to simulate them accurately. In that context, the EEA seasonal cycle and interannual variability are evaluated over the period 1985-2004 in models participating to the Ocean Model Intercomparison Project Phases 1 and 2 (OMIP1 and OMIP2). The main difference between OMIP1 and OMIP2 simulations is their atmospheric forcing: CORE-II and JRA55-do, respectively. Seasonal cycles of the equatorial Atlantic zonal winds, sea level anomaly and sea surface temper- ature in OMIP1 and OMIP2 are comparable to reanalysis datasets. Yet, some discrepancies exist in both OMIP ensembles: the thermocline is too diffusive and there is a lack of cooling during the development of the Atlantic cold tongue. In addition, the vertical ocean velocity in the eastern equatorial Atlantic in boreal summer is larger in OMIP1 than in OMIP2 simulations. The EEA interannual sea surface temperature variability in the OMIP1 ensemble mean is found to be 51% larger (0.62 ± 0.04 ˚C) than the OMIP2 ensemble mean (0.41 ± 0.03 ˚C). Sensitivity experiments demonstrate that the discrepancy in interannual sea surface temperature variability between OMIP1 and OMIP2 is mainly attributed to their wind forcing. While the April-May- June zonal wind variability in the western equatorial Atlantic is similar in both forcing, the zonal wind variability peaks in April for JRA55-do and in May for CORE-II. Differences in surface heat fluxes between the two atmospheric forcing datasets have no significant impacts on the simulated interannual SST variability.
Dynamic Mode Decomposition-based short-term prediction of UT1-UTC and LOD using Atmospheric Angular Momentum time series.
Authors: Michalczak Maciej , Ligas Marcin , Dobslaw Henryk , Dill Robert
Published: March 2024

We present preliminary results of ultra-short-term prediction (10-day forecast horizon) of UT1-UTC and LOD. Forecast procedure is based on Dynamic Mode Decomposition (DMD) and uses IERS EOP 14 C04 as a reference as well as Atmospheric Angular Momentum (AAM) as auxiliary data (AAM come from GFZ Potsdam and ETH Zurich).Two main prediction experiments (using different types of input data) were conducted: the ideal and the operational case. The ideal one was based on final (historical) data (both C04 and AAM); predictions performed within one year time span starting on a random MJD with 7 day step between subsequent 10 day forecasts, each yearly time span includes 51 10-day predictions. The operational case was based on operational data, covers the period of the 2nd Earth Orientation Parameters Prediction Comparison Campaign, each variant of this case includes 69 10-day predictions.Within each experiment and for each considered EOP we prepared some additional analysis. In case of LOD, we conducted predictions using 2 types of input LOD time series: directly on published IERS EOP 14 C04 time series and computed as a derivative of IERS EOP 14 C04 UT1-UTC time series. The final UT1-UTC predictions vary depending on the method of determining the constant of integration restoring the proper scale of UT1-UTC.In the ideal case the mean absolute prediction errors for UT1-UTC vary from 0.009 ms – 0.036 ms for the 1st day and 0.224 ms – 0.292 ms for the 10th day of prediction, whilst those values vary from 0.016 ms – 0.028 ms and 0.045 ms – 0.063 ms for LOD prediction. Corresponding values in the operational case are within the range of 0.058 ms – 0.065 ms and 0.438 ms – 0.463 ms for UT1-UTC, whilst for LOD these values are 0.032 ms – 0.040 ms and 0.093 ms – 0.099 ms.In operational settings of UT1-UTC prediction, we can observe that our results are slightly worse than the accuracy of IERS predictions (Bulletin A), while comparable to the accuracy of the forecast of methods from 2nd EOPPCC. The results demonstrate that the proposed techniques can efficiently forecast UT1-UTC and LOD. Nevertheless, a deeper analysis is needed on efficient incorporation of Effective Angular Momentum Functions information to improve presented prediction procedure.
Climate Change Competence Needs in the Society
Authors: Siponen Joula , Santala Marianne , Salovaara Janne , Tolppanen Sakari , Vesterinen Veli-Matti , Lavonen Jari , Lauri Katja Anniina , Riuttanen Laura
Published: March 2024

The role of geoscientists is evolving in response to the changing world and the crises we are facing. Geoscientists, whom some of us authors identify as, possess crucial insight into phenomena of existential relevance. However, we seem to lack agency to contribute to the urgently needed transformation. Inspired by the question of what society demands, especially regarding climate change expertise, we approached individuals who play important roles in mitigation and adaptation in their organisations across different sectors of Finnish society. Using qualitative methodology, including a questionnaire to fifty-eight and in-depth expert interviews with twenty-four professionals—we developed a competency framework. This framework aims to support the development of higher education and continuous learning that is based on research and scientific knowledge on climate change and addresses the needs of society.Our study revealed six categories of competencies: systemic climate change insight; visions and strategies in changing climate; compassionate climate leadership; active engagement in networks; courage and determination in climate action; and climate values and justice. These categories represent a combination of skills, knowledge, and attitudes useful for individuals aiming to drive climate change action, but also as basis for developing collective competence. For instance, a geoscientist might have strong systemic insight based on their training, but may lack compassionate leadership skills, meaning either that further education is needed or a group of differently skilled experts could fill the gaps to form a climate-competent team.Competent experts and professionals must be educated hand in hand with societal transformation. Therefore education must be transdisciplinary, involving a multitude of actors and stakeholders. To respond to the societal needs, University of Helsinki is developing new continuous education to professionals in the field and a two-year 60-credits Specialisation programme in climate expertise is planned to start in spring 2024. 
Direct image inversion of multimodal dispersion spectra and its application to deep seismic reflection data
Authors: Liu Qi , Chen Xiaofei , Guo Wenbin
Published: March 2024

Nowadays multimodal dispersion spectra can be easily obtained from surface wave data, but sometimes they are actually intractable for the traditional curve-based inversion methods due to the existences of mode-kissing phenomenon and uneven mode-energy distribution. We developed a new spectrum inversion method to circumvent these possible curve-related troubles by directly minimizing the image dissimilarity between the observed and synthetic dispersion spectra. Wherein the synthetic spectrum would be straightforwardly calculated by the Generalized Reflection and Transmission Coefficient method. The new inversion method could rapidly obtain a stable and reliable subsurface velocity structure, even without curve-extracting and mode-identifying in data processing, because it could exploit dispersion energy distribution features to constrain further the velocity structure. As an example of application, we applied this method to deep seismic reflection data in Beijing, and resolved a 2-D S-wave velocity profile above 200 m depth. The strong consistency of structural features between the inversed results of the new and traditional methods shows that the former is effective and practical for realistic data.  
Investigating the effects of Changing Land Use/Land Cover on Curve Number, Land Surface Temperature, and Vegetative Cover in the Ong Sub-Basin of the Mahanadi River, India
Authors: Prashant Prashant , Kumar Mishra Surendra , Kumar Lohani Anil
Published: March 2024

Over the past few decades, the Curve Number (SCS-CN or CN) approach has been employed to estimate direct surface runoff. In the times of urban sprawl, rapidly growing socioeconomic anthropogenic activities, and environmental changes all have a rapid growth that leads to spatial and temporal variability in the land use/land cover (LULC) complex which in a way affects the direct surface runoff, LST, and Vegetative cover. The study utilized the pixel based (PB), object directed (OD) machine learning algorithm i.e., Random Forest (RF) classifier for the LULC change study of the Google Earth Engine (GEE) platform for the verification of the SCS-CN, LST, and vegetative cover variability over 4 decades from 1980 to 2020 of the Ong River sub-basin (area = 4650 sq. km) of the Mahanadi River Basin of India. Sentinel-2 and Landsat satellite products were processed and utilized to conduct the LULC change analysis. The Kappa Coefficients of LULC maps for each decade from 1980 to 2020 equaled 0.86, 0.90, 0.891, and 0.895 with overall accuracy percentages of 97.89, 96.16, 96.79, and 96.44, respectively. The study determined the associated effects of each LULC class (i.e., built-up areas, Barren land, Water Bodies, Cropland, and Forest) on CN variability, LST, and vegetation index i.e., Normalized difference vegetation index (NDVI). The CN values varied from 64 to 78 in the 4 decades, suggesting the effects of decrease in forest cover and an increase in the built up. The LULC change analysis revealed a considerable decrease in the forest area from 1864.8 sq. km to 1098.34 sq. km and a sizeable increment in built-up area from 123.3 sq. km to 458.9 sq. km.  Furthermore, the study investigated and correlated each LULC class with the LST and NDVI. LST and NDVI for the forest and built-up areas were correlated with R2 equal to 0.91 and 0.72, respectively. Overall, the results suggest considering dominating LULC class change led to a rise in the average LST of the watershed from 28.06 °C to 28.68 °C. The increase in the average LST and increasing Curve Number value is a consequence of the scanty forest area combined with the reduction in the greenness of vegetative cover due to an increase in the built-up area indicating the alteration in the land-use patterns, land management practices, and streamflow due to anthropogenic activities. This type of study is helpful for watershed planning and management.
The February-March 2021 lava fountains events of Mt. Etna South-East crater: insights from clinopyroxenes. 
Authors: Petrone Chiara Maria , Corsaro Rosa Anna , Yannick Buret
Published: March 2024

Mt. Etna is the most active volcano in Europe with four active vents in the summit area. The South-East Crater (SEC) is the most active crater of the last 20 years and is characterised by episodic eruptions, i.e. sequences of paroxysmal lava fountains with rather variable frequency and duration from a few weeks to months. Between December 2020 and February 2022, the SEC produced over 60 paroxysmal events divided into a first phase (December 2020 – April 2021) and a second phase (May 2021 - February 2022).We investigated textural and chemical characteristics of the clinopyroxenes population to constrain frequency of magma recharge episodes and eruption triggering mechanisms of 6 paroxysms representative of the first phase, from February 16 to March 10 2021, including the February 28 paroxysm which erupted the most primitive magma.  Clinopyroxenes show frequent sector zoning superimposed on complex concentric zoning showing two main compositional domains: 1) augitic composition (Mg# 68-75) which mostly characterises rims and is less frequent in cores and mantles; 2) diopsidic composition (Mg# 74-80) mainly found in cores and less abundant in mantle and rims. Barometric estimates using the new GAIA deep learning-based thermobarometry (Chicchi et al., 2022 EPSL) indicate a shallow reservoir (0.4-1.0 ± 0.3 kbar) for the augitic domain and a deeper reservoir (1.7-2.7 ± 0.5 kbar) for the diopsidic domain. Fe-Mg diffusion timescales point to the occurrence of multiple episodes of mafic recharges starting in December 2020 and up to a few days prior eruption in agreement with monitoring data.
Accelerating raised-bog restoration in a nutrient-rich environment through moss transfer – OptiMuM – a new project to improve restoration practice in Germany
Authors: Huth Vytas , Beckert Marvin , Günther Anke , Jansen Florian , Pannek Angela , Jurasinski Gerald
Published: March 2024

Raised bogs are among the most threatened habitats in Northern Germany. Drainage-based land use has caused a shift to grassland vegetation on more than half of former raised bogs. In addition, high greenhouse gas (GHG) emissions from these areas counteract the aims of the Paris Agreement. Because all GHG emission reduction pathways require the so-called “land sink”, the pressure to restore former raised bogs under agricultural use as a nature-based climate solution is constantly increasing. However, since the mid-1980s most restoration projects have been carried out following peat extraction, whereas raised-bog restoration following intensive agricultural use is relatively new. Therefore, experience for successful restoration in a nutrient-rich environment is scarce.In German restoration practice, topsoil is removed to build cell bunds for water retention simultaneously resetting biogeochemistry (at least on some parts of the area) to more favorable conditions for raised-bog vegetation. An active water management similar to peat moss paludiculture is usually not feasible in large scale restoration, because the goal is to create a self-regulating ecosystem with minimal maintenance need after restoration. However, contrary to e.g., Canadian restoration practice, active introduction of a moss layer is currently not a standard measure, because donor material is essentially missing or strictly protected. Therefore, the return of raised bog habitats to an agricultural landscape strongly depends on nearby refuges of raised-bog species.Here, we present our new project “OptiMuM”, with which we aim to explore if, with relatively little additional effort, it is possible to speed up the restoration of raised bog habitats through varying degrees of active introduction of bog species under common German restoration practice. We selected three study sites across Northern Germany of which two are already rewetted without active introduction of bog species and one which will be rewetted within the project. On all sites we want to test the effect of active introduction for the restoration success and compare it to the development of areas within the sites without active introduction of bog species. On one site, we also want to test the additional effect of an active water management similar to peat moss paludicultures on the restoration success.Keywords: ecological restoration, peatlands, Sphagnum, C sequestration
Constraining D" seismic anisotropy with reflections and splitting
Authors: Thomas Christine , Pisconti Angelo
Published: March 2024

Detection of D" anisotropy is usually carried-out with shear wave splitting analysis. To constrain azimuthal anisotropy and infer mineralogy and deformation style, a number of crossing paths is necessary. Here we use an approach that utilises the polarity of P- and S- wave reflections from the D" discontinuity, compared with the main phases P and S, and combines these measurements with ScS splitting results. Using deformation scenarios for a number of lower(most) mantle candidate materials, we calculate the reflection coefficient for P and S-wave reflections and ScS splitting predictions. From our modelling, a clear distinction between different anisotropic media is possible by using both types of observations together. Furthermore, the approach allows to use only a single direction to distinguish between different scenarios. We apply the method to the Central/South Atlantic and South Africa, across the border of the large-low seismic velocity province (LLSVP). Shear wave splitting observations suggest that anisotropy is present in this region of the mantle, in agreement with previous studies that partially sampled this region. Modelling the observations with lattice preferred orientation and shape preferred orientation of materials expected in the D" region, we find two domains of mineralogy and deformation: sub-horizontally aligned post-perovskite outside the LLSVP, beneath the South and Central Atlantic, which is replaced by up-tilted aligned bridgmanite within the LLSVP beneath South Africa.
 Estimation of Snow Line Altitude Utilising Satellite Imagery of Alpine Glaciers
Authors: Ayub Sobia , Camporeale Carlo , Ridolfi Luca , Coppola Erika , Godio Alberto
Published: March 2024

Mountain glaciers form a critical component of the cryosphere and are sensitive to climate change. Snowline altitude (SLA) at the end of the ablation season is an indicator of climate change and a proxy forequilibrium line altitude (ELA). Here, we compute SLA by incorporating satellite imagery of 38 years(1984-2022) through mapping snow and ice over the elevation. A digital elevation model is being utilized toderive SLA over a period of time. This proxy database is quite useful in various glacier dynamics estimatedthrough numerical modelling such as mass balance reconstruction, thickness gradient, or glacier lengthestimation. The study explores various techniques to estimate the snow and glacier cover area (Otsu, k-means) apart from manual thresholding. Furthermore, the study also includes glacier surface shape changesto reduce the occurrence of misclassification. We further evaluate the performance of these techniques,however, each one has its own redundancies. In the case of Otsu image segmentation, the errors are quite eminentas the technique does not take into account the variation in glacier dimensions. The results are better interms of classification in the case of manual thresholding but the whole process is quite cumbersome. Inthe case of K-means, the clustering algorithm takes into account the glacier dynamics which improves theclassification but the technique does not work well in the case of large datasets. Furthermore, for validation,Careser glacier is being considered as it has the longest monitored observational dataset in the Italian Alps.The results are mostly in alignment with the observed dataset, particularly for years where the Sentineldataset is available. The SLA seems to depict a descending trend in the case of Careser in recent years.However, this recent behavior further needs to be evaluated. The algorithm is then further applied to theglaciers of Aosta Valley.
Improval of radiative transfer model-based LAI retrieval from Sentinel-2 data through machine learning and phenological constraints
Authors: Ledain Sélène , Stumpf Felix , Aasen Helge
Published: March 2024

In land surface monitoring, parameters such as the Leaf Area Index (LAI) have been widely studied to describe the canopy structure, foliage cover, crop yield and growth. Accurate and up to date mapping of such biophysical variables at global scale is thus essential for decision makers and agricultural management, as it can help monitor growth conditions and adapt practices. The retrieval of LAI from remotely sensed data is commonly done through the inversion of a combined leaf and canopy radiative transfer model (RTM). These models relate leaf biochemistry and canopy structure to spectral variation. However, the inversion process is computationally expensive and the ill-posed nature of the problem does not ensure a unique LAI retrieval solution. 
The aim of this research is to accelerate LAI retrieval by exploiting machine learning regression algorithms and thus allow more widespread crop monitoring from remote sensing data. We propose a more operational method for large-scale retrieval by emulating the inversion problem with a machine learning algorithm. These models effectively capture non-linearities, proving particularly pertinent in the context of land surface modeling. Our work focuses on the agricultural land in Switzerland, monitored through Sentinel-2 imagery between 2017 and 2023. We use the PROSAIL RTM to simulate the spectral response of Sentinel-2 to various combinations of biophysical and canopy variables, including LAI. A look-up table (LUT) relating leaf and canopy parameters to reflectance spectra is thus generated and used to train the machine learning algorithm. Methods among Random Forest, Neural Network and Gaussian Process Regression are tested and the best model is selected according to the root mean squared error (RMSE) on in-situ validation measurements of LAI of several fields in Switzerland.
To further improve LAI retrieval, we include phenological a priori knowledge to constrain the underdetermined problem. Specifically, we limit LAI values knowing the general relation of crop development with temperature. Accumulated Growing Degree Days (GDD) represent the cumulative temperature above the base temperature of a plant, where no growth occurs. We thus use GDDs to determine phenological macro-stages and constrain LAI values using physically sound assumptions. With the incorporation of phenological constraints, we additionally enable the customization of the model to suit specific crops or seasons, offering a simple solution to increase model performance according to stakeholder needs.
Body wave seismic attenuation tomography of the crust in the Sichuan-Yunnan Region, China
Authors: Wang Jiachen , Zhang Haijiang , Hu Jing , Liu Ying
Published: March 2024

   The Sichuan-Yunnan Region is located at the southeastern margin of the Tibetan plateau in southwest China. Determining the structure of southeaster margin of the Tibetan plateau is very important for understanding the eastward growth of the plateau. At present, most of seismic tomography studies are focused on resolving multiscale velocity anomalies of the crust and mantle. However, seismic attenuation structure of the crust and upper mantle in the Sichuan-Yunnan Region is less studied, which can be used to better understand the temperature regime and the distribution of partial melting. In this study, based on a high-resolution community velocity model of the crust and uppermost mantle in this area (Liu et al., 2021), we determined body wave attenuation structure in the Sichuan-Yunnan region using data from 350 stations and 9837 seismic events observed between 2010 and 2013 (Figure 1).  Figure 1. Distribution of seismic events (red circles) and stations (blue triangles) in the Sichuan-Yunnan region.    Q value is a reduction to a dimensionless form of the more usual measures of attenuation (Knopoff, 1964. Body wave attenuation tomography typically needs to extract a parameter called t* from the displacement or velocity spectrum in the frequency domain to calculate Q using the following equation:         Here the influence of frequency on Q was not considered. Using the measured absolute t* values, the attenuation structure was then determined with the following relationship between t* and Q:    For the Sichuan-Yunnan region, we constructed three-dimensional Qp and Qs models with a horizontal spatial grid interval of 0.4° × 0.4°. Our attenuation models exhibit a high consistency with large-scale features in previous researches. In the shallow depths (
The Role of the Stratosphere in Driving Uncertainties in the Southern Hemisphere Future Climate
Authors: Mindlin Julia , Vera Carolina S. , Shepherd Theodore G. , Osman Marisol
Published: March 2024

The strength and latitudinal position of the extratropical eddy-driven jet (EDJ) in the Southern Hemisphere (SH) winter and summer is naturally forced by the conditions of the tropical oceans and by the variability of the SH stratospheric polar vortex (SPV). Uncertainty in the responses of these remote drivers (RDs) of extratropical circulation to anthropogenic forcing leads to uncertainty in the future strength and latitude of the EDJ. In turn, these changes in tropospheric circulation can lead to changes at the regional scale. During this century, the combined effect of ozone recovery and the increase in greenhouse gases (GHGs) will influence the SPV. Therefore, understanding the ‘tug-of-war’ between these two anthropogenic forcings is crucial to understand future projections. Moreover, the influences of the stratosphere will be combined with the influences of forced changes in the tropics. This complex interplay between RDs and the magnitude of each RD’s response to anthropogenic forcings differs among Global Climate Models (GCMs), which leads to different responses of the EDJ and regional climate. In this work we analyze an ensemble of CMIP6 models to study the role of forced responses in the SPV in driving changes in climate projections, and how the influence of the stratospheric changes combines with the influence of the changes in a small set of tropical RDs. In particular, we find that a strengthening of the SPV leads to a strengthening and small poleward shift of the EDJ in winter, and that a delay in the SPV breakdown date leads to a strong poleward shift of the EDJ in summer. The evolution of the summer circulation response in CMIP6 models during the twenty-first century can be explained from the combined effect of ozone recovery and GHG increase. At the regional scale, in winter, a strengthening of the SPV leads to drying in Southeastern South America and wetting in Tierra del Fuego, in the south of South America, while in summer, a SPV breakdown delay leads to wetting in the west coast of all three large extratropical continental sectors and the coasts of Antarctica. Finally, we develop storylines of future circulation and precipitation changes in both summer and winter which help understand the relative role of the SPV among other dynamical drivers of change in the SH. 