bluuebunny/crossref_metadata_2025 huggingface dataset:
Tipping the Amazon Rainforest: Regional deforestation and land-climate interactions
Authors: Hasson Shabehul , Stuch Benjamin , Kynast Ellen , Böhner Jürgen , Schaldach Rüdiger , Jungkunst Hermann
Published: February 2023

The Amazon rainforest is globally relevant and is considered a tipping element in the global climate system. Studies suggest that deforestation in the Amazon by around 30% may disturb regional convective rain patterns, which could increase drought frequencies and intensities locally and, may activate a cascade of tipping elements in the global climate system. Here, we aim to assess the relationship between deforestation and climate responses at a convection-permitting scale by employing a non-hydrostatic mesoscale Weather Research and Forecasting (WRF) model. For this, we first developed a spatially explicit deforestation model for the South-Western Amazon to see an effect of deforestation intensity ranging from 10% to 60%, and then based on 30% deforestation, we further see the role of deforestation pattern (e.g. deforestation alongside the roads, as a large single or small multiple circular plots, and their geographical positions), and shifts to anticipated land use. Then for each deforestation map, we simulate the land-atmosphere interactions and responses in the regional rainfall and temperatures by dynamically downscaling the ERA5 reanalysis using WRF for the year 2020 at 5km spatial resolution and by explicitly resolving convection. We assess non-linearity in the land-climate interaction to different combinations of deforestation quantities and deforestation patterns. Our preliminary results show a general pattern of decreasing mean and extreme rainfall with deforestation where the geographical location and the pattern of deforestation also play a role. The study will provide an insight into whether the employed quantitative methods are able, or good enough, to simulate relevant processes between the biosphere and the atmosphere that could promote assessing tipping points in the Amazon.
Assessment of the CMEMS phytoplankton functional types products for inter-mission consistency
Authors: Xi Hongyan , Bretagnon Marine , Demaria Julien , Mangin Antoine , Bracher Astrid
Published: February 2023

In the framework of Copernicus Marine Service Evolution Program, our current project GLOPHYTS aims at establishing a complete and systematic approach for a consistent long-term monitoring of surface ocean phytoplankton function types (PFTs) on global scale. The current global PFT products available on CMEMS are generated based on remote sensing reflectance from multi-sensor merged and Sentinel-3 OLCI data and OSTIA sea surface temperature product, using a set of empirical-orthogonal-function based PFT algorithms that were previously developed. These products provide global chlorophyll a data with per-pixel uncertainty for six PFTs spanning from 2002 until today. Aiming to merge these PFT data sets of different sensors into one long-term consistent satellite PFT product, as first steps we focus on the (inter-)calibration of the sensor specific PFT products using in-situ validation, cross-comparison and uncertainty estimation in different biogeochemical regions. The final continuous PFT observations will act as potentially important ocean monitoring indicators (OMI) to help sustain the ocean health by providing inter-annual variation and trend analyses of the surface phytoplankton community structure.
Microplastics are released from agricultural soils to the atmosphere by wind erosion 
Authors: Rezaei Mahrooz , Abbasi Sajjad , Pourmahmood Haniye , Oleszczuk Patryk , Turner Andrew , Ritsema Coen
Published: February 2023

Agricultural soils are a secondary source of airborne microplastics (MP) through wind-driven erosion, especially in arid and semi-arid regions. However, this transport pathway has thus far received little scientific attention. In this study, we measured microplastics in both soil and wind-eroded sediment using a portable wind tunnel in two vegetable-growing fields of Fars province, Iran that have been subject to different agricultural practices: plastic mulch (Field 1) and irrigation with wastewater (Field 2).

Microplastic concentration in soil ranged from 0.04 MP g-1 to 0.83 MP g-1 in Field 1 and from 0.20 MP g-1 to about 1.1 MP g-1 in Field 2. Fibres represented the dominant shape of MPs, but spherules, presumably from wastewater, also made a significant contribution to MPs in Field 2. Analysis of samples by Raman spectroscopy and scanning electron microscopy (SEM) revealed that polyethylene terephthalate (PET) and nylon were the most abundant polymers and that MPs exhibited varying degrees of weathering. Concentrations of MPs in this study are within the range reported previously for agricultural soils.

Results of the wind tunnel revealed threshold velocities for wind erosion of 7 and 12 m s-1 and MP erosion rates of 0.4 and 1.1 MP m-2 s-1 for Fields 1 and 2, respectively. MP concentrations in wind-eroded sediment were considerably higher than the agricultural soil samples and were significantly higher (p < 0.05) in Field 2 (mean and median of 45.26 MP g-1 and 42.89 MP g-1, respectively) than in Field 1 (mean and median of 9.08 MP g-1 and 11.35 MP g-1, respectively). This revealed enrichment of MP in wind-eroded sediment compared to the original soil. Erosion rates are significantly higher than published depositional rates of MPs and suggest that agricultural soils act as both a temporary sink and dynamic secondary source of MPs that should be considered in atmospheric transport models and risk assessments.
Influence of atmospheric forcings on water renewal in harbours.
Authors: Samper Yaiza , Liste Maria , Mestres Marc , Alsina Jose , Espino Manuel , Sánchez-Arcilla Agustin
Published: February 2023

In this paper, we use observations and numerical simulations to investigate the effect of meteorological parameters such as atmospheric pressure and wind on harbours water exchanges. Knowing these water exchanges is of vital importance to care for and improve the environmental health of the harbor water and its surrounding areas. This knowledge requires an analysis of different meteorological and hydrodynamic parameters from detailed and high definition studies. SAMOA (System of Meteorological and Oceanographic Support for Port Authorities) is a project developed by Puertos de Estado (PdE) in collaboration with several Spanish harbour authorities and Universities to provide enhanced meteorological and oceanographic information and services for harbour operations. In the framework of this project, the Maritime Engineering Laboratory (LIM/UPC) has developed a high-resolution numerical model for the forecasting ocean variables at coastal and harbour scales. The effectiveness of this model to reproduce the hydrodynamics in the ports is evaluated using meteo-oceanographic observations from different measurement campaigns during 2020 2021, and 2022 carried out in the ports. Firstly, this article analyses and validates the results of the SAMOA meteo-oceanographic prediction system in the ports of Huelva, Gijón and Cartagena (mesotidal and microtidal environments) and, secondly, based on the analysis of observations, it proposes the numerical analysis of different events with high renewal times. The data includes information on atmospheric pressure, wind, sea level and currents parameters. These variables are validated by visual matching of the time series of modelled data and observations, as well as by statistical analyses and correlations between model results and measurements. 
Diagenetic effects in Hf-Nd isotopic compositions on clay fractions: Source-to-sink analysis of signal perturbation in denudation records
Authors: Gaitan Camilo Esteban , Pucéat Emmanuelle , Pellenard Pierre , Adatte Thierry , Bayon Germain , Robin Cécile , Guillocheau François
Published: February 2023

Recent studies have coupled the Lu-Hf and Sm-Nd isotopic systems on clay fractions to assess the evolution of chemical weathering in both ancient and modern environments. Results of this proxy in the abyssal plain of the Cape Basin in Southwestern Africa show a concomitant increase of chemical weathering and physical erosion in response to a late Cretaceous tectonic uplift. In this study, we performed analyses on sediments in the continental slope of the basin that show significant differences compared to the abyssal plain: A long-steady decrease in quartz simultaneous to an increase in the calcite content during the late Cretaceous; a lower content of detrital smectite throughout the section; and the presence of mixed layer assemblages of illite – smectite (R0 or R1) and vermiculite – chlorite during the early-late Cretaceous transition, coinciding with the period of low carbonate content. First, these differences indicate a variation in the input of siliciclastic material and a change in the carbonate compensation depth. Second, clay assemblages reveal a burial diagenetic influence compared to those recorded in the abyssal domain, likely due to thicker deposition in the continental slope. These diagenetic processes indicate that there is a perturbation in the chemical weathering signal at the continental slope, therefore the disparities between the denudation record on clays in both segments cannot be attributed to an effect of signal propagation due to this post-deposition processes.
Operational machine learning for the postprocessing of surface wind forecasts
Authors: Nerini Daniele , Zanetta Francesco , Schaer Mathieu , Bhend Jonas , Spirig Christoph , Moret Lionel , Liniger Mark A.
Published: February 2023

Forecasting winds at the local scale can be challenging due to the highly variable and complex nature of wind patterns, particularly in the case of complex terrain. In such cases, the accuracy of numerical weather prediction models (NWPs) is often limited by the quality of their initial conditions and their grid resolution. This is where the use of observational data through statistical postprocessing techniques can help to improve the quality of forecasts. 

Statistical postprocessing is nowadays an established component in operational weather forecasting that is used to improve the accuracy, resolution, and calibration of NWP ensemble forecasts with historical observations. In recent years, machine learning techniques have shown great potential in the field of postprocessing, thanks to their ability to deal with increasingly large volumes of data, and the capacity to capture complex relationships between forecasts and observations that are not explicitly represented in traditional postprocessing methods. 

To capitalize on machine learning for weather applications, and for it to gain acceptance and become a reliable technology for operational use, it is also crucial to consider the technical and engineering challenges that arise when implementing machine learning in a productive environment. MLOps, or Machine Learning Operations, is a set of practices that are used to manage and streamline the deployment, monitoring, and maintenance of machine learning models in production.  

We will present our recent experience with the development and operationalization of a statistical postprocessing system based on the use of neural networks to predict the probability distribution of forecasts of surface winds. Following MLOps best practices, our framework aims to improve the reproducibility and automation of most common tasks in a machine learning-based system, such as efficient data loading and manipulation, the monitoring and visualization of prediction quality, and the automation of model training and deployment pipelines. 
Coastal Aquaculture mapping using a novel combination model of GF-3 Fully Polarimetric SAR Imagery: A case study of Yancheng coastal wetland, China
Authors: Yu Juanjuan , He Xiufeng , Motagh Mahdi , Yang Peng , Xu Jia
Published: February 2023

Coastal aquaculture has become one of the main sources of animal protein and plays an important role in food and nutrition supplies and security around the world. Accurately mapping aquaculture areas is the basis for its sustainable management and use, and provides important support to policy development and implementation at regional, national, and global levels. Considering the concentrated and densely distributed characteristics of aquacultures, it is difficult to distinguish the dikes between aquacultures and identify small-scale aquacultures using medium-and low-resolution SAR images. GaoFen-3 (GF-3) is the first launched full-polarimetric C-band SAR satellite of China at metre-level resolution. This study aims to use a novel combination model to extract coastal aquacultures in the Yancheng coastal wetland, China on the basis of GF-3 Fully Polarimetric SAR Imagery. Polarimetric decomposition algorithms were applied to extract polarimetric scattering features and feature optimization was applied based on the separability index. To separate adjacent and even adhering ponds into individual aquaculture objects, we proposed a novel model that integrated two UNet++ subnetworks with the marker-controlled watershed (MCW) segmentation strategy to obtain more refined coastal aquaculture results. The accuracy assessment results demonstrated a considerable performance, with F1 greater than 95%, IoU greater than 90%, and insF1 higher than 85%. The experimental results indicate that the proposed algorithm achieved fairly high accuracy in aquaculture extraction and can effectively improve the boundary quality of individual aquacultures.
Effects of land use change on water-related ecosystem services in the Amazon Basin
Authors: Santos Maria J. , O'Connor John C. , Nguyen Kien , Tuinenburg Obbe , Dekker Stefan C.
Published: February 2023

Land use changes can affect many dimensions of the hydrological cycle which in turn affect the provisioning of water and its related ecosystem services to society. Modification at different spatial and temporal extents due to seasonal changes in water supply and land use intensities may compound and challenge our ability to predict the cascade of processes that lead to the supply of ecosystem services, i.e., ecosystem service cascade (ecosystem property, supply and service). In the Amazon basin, land use changes may affect water supply through modification of moisture recycling periodicity, and a quantification of its effects on other water-related ecosystem services, namely crop production and biodiversity, is scarce. We investigated this process using a moisture-tracking model, to show that upstream land use changes will affect the persistence of cropland in the Amazon arch of deforestation.  We also show that biodiversity trait distributions affect the provision of water that maintains the cascades of moisture recycling, and different trait combinations enable regulation of atmospheric water regulation and land surface temperature. As trait combinations are a result of land use changes, the future of moisture recycling in the Amazon and its dependence downstream may require a better land use planning that incorporates these processes more explicitly.
Hybrid concept for a forefield reconnaissance system for melting probes capable of moving through terrestrial and extraterrestrial cryospheres
Authors: Becker Fabian , Stelzig Michael , Audehm Jan , Haberberger Niklas , Heinen Dirk , Zierke Simon , Helbing Klaus , Wiebusch Christopher , Vossiek Martin , Böck Georg
Published: February 2023

The most promising places for the development of extraterrestrial life are the ocean worlds of our Solar system such as the icy moons Europa or Enceladus and their subglacial oceans.  Space mission concepts are being developed to explore the moons’ chemical composition, investigate their habitability, and search for biosignatures.The TRIPLE Project, initiated by the German Space Agency at DLR, involves the development of technologies for rapid ice penetration and subglacial lake exploration. It consists of three components: (i) a melting probe that travels safely through the ice and carries (ii) an autonomous nano-scale underwater vehicle that explores the ocean and takes samples to be delivered to (iii) an astrobiological laboratory. The entire system will be tested in an analogue scenario in Antarctica as a demonstration for a future space mission. To ensure the success of the test, a retrievable melting probe is needed that can safely penetrate several kilometers of ice. The melting probe should also be able to detect the transition between the ice and the water body to stop at this boundary. The Forefield Reconnaissance System (FRS) for such a melting probe developed in the project TRIPLE-FRS combines radar and sonar techniques to benefit from both sensor principles inside the ice. The radar antennas as well as a piezoelectric acoustic transducer will be directly integrated into the melting head. This integration into the head should leave the melting capability of the melting probe as unaffected as possible. An in-situ permittivity sensor will also be developed to account for the propagation speed of electromagnetic waves, which is dependent on the surrounding ice structure. The goal of this system is to detect obstacles or other interference bodies to guarantee a safe transition through the ice. Damage-free melting must be secured to allow all other scientific exploration. In order to prove the functionality and performance of the system, several field tests on alpine glaciers are performed during the project. In this contribution, we describe the main ideas behind the system and show how it could serve as a baseline design for the future development of space missions to ocean worlds like Europa.
The 1804 Dalías earthquake: ranking seismic sources with the Boxer and seismic scenario methods in SE Iberia
Authors: de Pro-Díaz Yolanda , Martínez-Díaz José Jesús , Canora Catalán Carolina
Published: February 2023

SE Iberia is a tectonically active area with an important history of destructive earthquakes. Some of these earthquakes have been associated with known active faults, but the seismic source of most of them remains unclear. The majority of these earthquakes happened long before instrumental record began, so we can only study them through paleoseismology and/or historical records. In some cases, due to current soil usage, paleoseismic studies are extremely difficult to perform and researchers can only rely on historical records. Such is the case of the 1804 Dalías earthquake.In this communication our objective is double. First, we present a methodology which can be useful to constrain the seismic source of historical earthquakes for which only intensity data are available. And second, we apply this methodology to the 1804 Dalías earthquake in order to constrain its seismic source, which remains unclear up to this day. Our proposed methodology is a combination of Gasperini et al. (1999, 2010)’s and de Pro-Díaz et al. (2022)’s methods. Our methodology searches for the faults that are most plausible candidates for the earthquake rupture, then builds seismic scenarios for each candidate rupture and finally compares these scenarios with the observed intensity field in order to find the candidate with the best fit. Seismic scenarios are built using OpenQuake and ArcGIS software (although QGIS can be used as well). The candidate that generates the simulation which better resembles the observed intensity field is considered the best candidate and the one closest to the actual earthquake source.For the 1804 Dalías earthquake, we consider different ruptures along the Loma del Viento Fault (LVF) and Llano del Águila Fault (LLAF) traces as candidate ruptures, including some combined ruptures along the two faults. Our results show that there are two almost equally best candidates: a full rupture of the whole inland extension of the LVF, and a combined rupture of this fault and the LLAF.
Performing mixed-mode fracture tests to assess crack propagation in weak snowpack layers
Authors: Walet Melin , Schöttner Jakob , Adam Valentin , Schweizer Jürg , van Herwijnen Alec
Published: February 2023

Dry-snow slab avalanches release due to widespread crack propagation in a weak layer buried below cohesive slab layers. To understand the onset of crack propagation, it is essential to measure fracture properties of weak layers. As crack propagation in snow commonly occurs on inclined terrain, the interaction of different fracture modes also needs to be accounted for. Mode I denotes loading normal to the crack faces and mode II loading parallel to the crack surface but normal to the crack front. So far, experimental results on this mode interaction are lacking. Here we present results using a novel field method to derive the mixed-mode fracture toughness of weak layers, a material property describing the resistance to crack growth. Crack propagation will begin once the energy release rate exceeds the specific fracture energy, which is a measure for the fracture toughness. In order to cover the entire interaction range between mode I and mode II, we performed tilted fracture mechanical field experiments to determine fracture characteristics of different types of weak layers. Fitting the obtained results with a power law allows to represent the correlation between fracture characteristics and the full range of mode interactions. Our first results suggest a quadratic interaction and the measured specific fracture energy is larger for mode II than for mode I which both is in agreement with observed behavior in other materials. The observed fracture energies have the same order of magnitude as previous, comparable experiments. These results provide the first measurements of the mixed-mode fracture toughness of different weak layers and can be used to establish a link between snow microstructure and mechanical properties to ultimately improve avalanche forecasting. 
First evidence of polarized emissions in pulsating aurorae
Authors: Bosse Leo , Cessateur Gaël , Lamy Hervé , Lilensten Jean , Gillet Nicolas , Brogniez Colette , Pujol Olivier , Rochat Sylvain , Curaba Stéphane , Delboulbé Alain , Johnsen Magnar G.
Published: February 2023

In the last decade, several instruments have been developped to measure the auroral light polarisation. However, its study has faced the issue of anthropic light pollution and scattering in the lower atmosphere (Bosse et al., 2020). To overcome this challenge, several methods were used, and until now, the most succesfull was the use of a polarised radiative transfer model (Bosse et al., 2022) to identify the light pollution contribution. However during the past year a new look at the data revealed that pulsating aurorae are polarised, and that this polarisation carries a lot of information. The main advantage of using pulsating aurorae is that the variations in the light polarisation are very fast, of the order of a few seconds. This allows us to dismiss any potential source of polarisation that are not synched with the pulsation of the aurora.These polarisation patterns are seen in the green atomic oxygen line at 557.7 nm, the 1st N2+ negative band at 391.4 nm (purple) and 427.8 nm (blue).There are no clear explanations on the origin of this auroral polarisation, or its relation to the local state of the upper atmosphere. An hypothesis is that this polarisation can be either created directly at the radiative de-excitation or may occur when the non-polarised emission crosses the ionospheric currents.We will present how these new findings confirm the ionospheric origin of the polarisation observed from the ground, as well as some of the potentialities these observations and models offer in the frame of space weather, aerosol and light pollution study.
Spatial relationships among soil-based ecosystem services can vary at the regional and local level
Authors: Medina Roldán Eduardo , Lorenzetti Romina , Ungaro Fabrizio , Calzolari Costanza
Published: February 2023

Ecosystem services (ESs) are currently seen as a useful support tool in the context on land management and environmental policies. Thus, great efforts are in progress for exploiting their potential. One of such ESs-based tools is when two or more ESs are taken into account at the same time. Here we analysed at a regional scale, soil-based ecosystem services (SESs), and their bundles (relationships consistent in space and time among two or more ESs taken into account ), showing their usefulness for decision makers. We used SESs derived from specific-calibrated data (produced through soil digital mapping) on soil properties from the plain area of Emilia Romagna in Italy, and applied spatially-explicit tools to investigate SESs relationships (i.e., synergistic or antagonistic/trade-offs). ESs relationships in the bundles concept are usually understood as constant at a global spatial basis. For instance, a bivariate ESs relationship such as a trade-off between soil carbon and crop production are usually assumed to remain constant all over the extension of a particular area of study. However, our approach shows that, at the local level, there can be deviations from the global relationships among SESs. In such local deviations the sign of the SESs relationship can can even change (e.g., a global SESs trade-off can show local synergies). At our case such deviation from a global trade-off to local scale synergy was observed for such SESs as carbon stock (CST) and water infiltration capacity (WAR). The deviation in the CST-WAR pair relationship was likely caused by how particular soil properties determine these SESs, since the local deviations in this SESs pair were associated to pedo-units at the landscape scale with particular properties. Thus, management practices that try to maximise such SESs with a single approach at a global level (study area) are likely to succeed in some, but not all of such pedo-units. Overall, our approach highlights how SESs can be useful in guiding land management decisions, and how inherent soil properties play a role in determining the relationships among SESs.
Transfer Learning for LULC Classification on multi-modal data in the Amazon Basin
Authors: Hell Maximilian , Brandmeier Melanie , Nüchter Andreas
Published: February 2023

Mapping of Land use and land cover (LULC) changes over time requires automated processes and has been investigated using various machine learning algorithms and, more recently, deep learning models for semantic classification. New applications of these models to different satellite data and areas are regularly published. However, studies on the transfer of these models to other data and study areas are rather scarce. In a previous study [1], we used multi-modal and –temporal Sentinel data for LULC classification using traditional and novel deep learning models. The data covered parts of the Amazon basin and was comprised of a twelve-month time series of radar imagery (Sentinel-1), combined with a singular multi-spectral image (Sentinel-2). All satellite images were captured throughout the year 2018. The label map (Collection 4) of the Amazon produced by the MapBiomas project [2] was used as training and test labels. Besides state-of-the-art models, we developed five variations of a deep learning model—DeepForest—which leverages on the multi-temporal and -modal aspect of the data. The best model variation (DF1c) reached an overall accuracy of 74.4% on the test data.Currently we are investigating the transferability of these models to more recent data of the same region. The new dataset was processed in the same way as in the previous study. It comprises a Sentinel-1 time-series and a single Sentinel-2 images from 2020, with an updated version of the label map of the MapBiomas project (Collection 6). This posed some challenges, as the classification scheme changed and is not fully backwards compatible with the one used to train the DeepForest models. A test dataset was chosen in the state of Mato Grosso, as the satellite scenes cover most classes used in the classification scheme. However, this data exhibits some class imbalance, as two of the eleven classes are dominating the scene. All five DeepForest variations reached accuracies higher than 79% and thus generalize well on the major LULC classes. For comparison and to further improve our models, we currently retrain the models on the new, larger data set (114,376 training image tiles compared to 18,074). Preliminary results will be shown during the session. ReferencesCherif, E.; Hell, M.; Brandmeier, M. DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin. Remote Sensing 2022, 14, 5000, doi:10.3390/rs14195000.
MapBiomas Brasil; Available online: https://mapbiomas.org/en
Drivers of the increased impact of extreme spring frosts on European vineyards
Authors: Zappa Giuseppe , Kretschmer Marlene , Shepherd Theodore
Published: February 2023

A number of unprecedented extreme late spring frosts has recently hit Western Europe, especially France, causing severe impacts on vineyards that had already undergone bud burst. Whether climate change may have contributed to making these events more likely is poorly understood, since it depends on a subtle balance between how much the phenological cycle anticipates due to winter warming and how much cold spring nights warm. Here we shed more light on the key driving factors behind observed changes by taking a novel approach in which the different components of past warming trends, i.e. mean warming, seasonal cycle changes, diurnal temperature changes and frequency of cold snaps, are isolated and separately analysed. Bud burst date is determined using a previously tested phenological model based on growing degree days. A statistical model is introduced to modulate the different components of warming and generate thousands of sample of plausible realisations of internal climate variability. The statistical model is fit to daily mean and night minimum temperature data in 1950-2022 from the ERA5 reanalysis and EOBS. We show that in large parts of Europe even a simple seasonally and daily uniform warming leads to an increase in the risk of frosts after vineyard bud bursts. However, such simple thermodynamic effect is small compared to the observed changes in the frequency of such events. Including the effect of changes in the seasonal cycle, i.e. the winter warming amplification, and in the diurnal temperature range further increases frost risk, but it still explains only up to a third of the observed changes in the frost events. Likewise, changes in internal atmospheric variability are also insufficient to explain the observed trends. We demonstrate that only the increased frequency in an intra-seasonal  atmospheric circulation pattern causing warm winters followed by spring cold snaps, and acting on a warmed seasonal cycle, can explain the observed trends. We then analyse CMIP6 historical simulations to attribute the role of climate change versus internal climate variability. While mean warming and seasonal cycle changes are strongly influenced by climate change, the winter to spring swing in atmospheric circulation is more difficult to attribute and it may result from an extreme realisation of internal variability. We suggest that storylines can be used to illustrate plausible future risks for vineyards depending on the rate of regional warming and the type of circulation changes. 
Representation of relationship between PDO and global precipitation in CMIP6 models
Authors: Dixit Jivesh , Mehta Vikram M. , AchutaRao Krishna M.
Published: February 2023

Decadal Climate Variability (DCV) modes perturb regional climatic parameters across the globe at multi-year timescales. Precipitation is one such climatic parameter of socio-economic importance.Our study examines the ability of Coupled Model Intercomparison Project Phase 6 (CMIP6) models in representing the observed teleconnection of DCV modes; Pacific Decadal Oscillation (PDO) and Tropical Atlantic SST Gradient with the global precipitation. We chose the subset of CMIP6 models that participate in both historical and hindcast experiments.In this study we examine the relationship between the model's ability to simulate the long-term DCV pattern and its ability to simulate the teleconnection between DCV mode and global precipitation.HadGEM3-GC31-MM and MPI-ESM-1-2-HR, which simulate the observed global SST anomaly pattern in the warm phase of PDO considerably well, also simulate observed global precipitation patterns during the warm phase of PDO quite well in regions like  central India, Europe, North- and South-America, Eastern Africa, Eastern Australia etc. However, BCC-CSM2-MR and NorCPM1 fail to effectively simulate observed precipitation patterns in the warm phase of PDO in regions like, North- and South-America, Africa etc. Hence, we found that models that are able to simulate the PDO pattern of SST are also able to represent the teleconnection between PDO modes and precipitation across the globe. We also examined the regression pattern of wind circulation, and the regression pattern of converging and diverging parts of the wind with PDO index. Models that better represent the observed warm phase of PDO pattern, also well represent the observed circulation pattern in respective phases of PDO. Similar analysis is also performed for TAG.Keywords: Decadal Climate Variability (DCV), CMIP6, historical experiments, teleconnection, precipitation.
Temporal variation of Qc and its implications in medium characterization
Authors: Gupta Subhash Chandra , Sharma Mukat Lal , Jain Sanjay Kumar , Sen Arup
Published: February 2023

The heterogeneities in the medium play important role not only in earthquake genesis but also strong ground motion simulation due to its bearing on attenuation characteristics. Observational data is one of the prerequisites for such studies which are acquired through deployment of seismological networks in active seismic regions. The Himalaya is considered as one of the most seismically active region in the world. It is also source of many river valley projects, like Tehri dam and others. The Tehri dam with 260.5 meter height is highest dam in India, located in the Lesser Himalaya of the Garhwal Himalaya that lies in seismic zone IV as per the seismic zoning map of India. Besides this, a number of development activity such as road and railway infrastructures are in progress. Thus, there is need to understand the effect of physical state of media on propagation of seismic waves in the Himalayas. The medium/path characteristics of this  region has been measured by determining the seismic wave attenuation of high frequency waves of local earthquakes which is accomplished by estimating the quality factor of coda waves (Qc). In the present study, Qc, has been determined using local earthquakes recorded during last fourteen years from 2008 to 2021. The local earthquakes used in the study have been obtained through deployment of 12 to 18 stations local seismological network around Tehri dam reservoir. The results showed in the study that there is no significant change in Qc is observed in the region during this period after dam impoundment. These results found in agreement with the findings that no reservoir trigger seismicity is observed in the region associated with Tehri dam reservoir during last sixteen years.
Modelling soil water and climate dynamics to understand soil formation in Mediterranean landscapes
Authors: Román-Sánchez Andrea , Vanwalleghem Tom , Laguna Ana , Peña Adolfo , Giraldez Juan Vicente , Brocca Luca
Published: February 2023

Influence of the Mediterranean climate, relief and geology can shed light on the most important processes that affect the mechanisms and rate of bedrock weathering. Despite the effort dedicated to exploring the processes of soil formation, little is known about the quantitative aspects of these processes. This research is based on developing a spatially explicit model of soil water and climate dynamics to explain the processes in soil formation. This model includes a simple soil water balance model, climatic data, topographic variables and runs a daily time step. The model calibration is performed with satellite soil moisture data for the Mediterranean basin. The model highlights the importance of soil water flux at different topographic positions on soil formation on long-term time scales.
Using causal inference to investigate anthropogenic aerosol impacts on the diurnal temperature range
Authors: Roesch Carla , Ballinger Andrew , Runge Jakob , Hegerl Gabriele
Published: February 2023

Near surface air temperature is a primary variable to track global climate change. While mean temperature is often used to quantify global warming, the diurnal temperature range (DTR) - defined as the difference of daily minimum and maximum temperature - can provide additional information on changes to the diurnal cycle and temperature extrema, which is important for impacts of climate change. Different to increasing global mean temperature, observations have shown a decrease of global mean DTR over recent decades. This trend has been attributed to human emissions of greenhouse gases (GHG) which increase daily minimum temperature (Tmin), usually measured at night, more than daily maximum temperature (Tmax), observed during the day, by trapping outgoing longwave radiation. Aerosol radiative forcing has been associated with absorbing and scattering incoming (solar) shortwave radiation; thus, aerosols are assumed to reduce Tmax more than Tmin, decreasing the DTR. However, historical single and ALL forcing simulations from models that are part of phase 6 of the Coupled Model Intercomparison Project (CMIP6) model a decrease of the DTR for GHG and ALL forcings but show an increase in the DTR for anthropogenic aerosols due to a larger reduction of Tmin than Tmax. We investigate this discrepancy in aerosol contributions to changes in the DTR by applying causal inference methods to quantify the impact aerosols have on the DTR in Europe. To address the various effects aerosols have on the climate system, by interacting with both radiation and clouds, we include Tmin, Tmax, aerosol optical depth (AOD), cloud cover, cloud height, incoming shortwave radiation (SW) and outgoing longwave radiation using observational satellite and gridded station data for the past decade in our analysis. First results agree with the cooling effect of aerosols on Tmax by reducing SW radiation and show a positive effect of AOD on low cloud cover. They further suggest that a decrease of Tmax causes a decrease in Tmin, possibly explaining the CMIP6 model results.  
Resonant water-waves in a circular channel: forced KdV solutions
Authors: Harlander Uwe , Schön Franz-Theo , Borcia Ion D. , Richter Sebastian , Borcia Rodica , Bestehorn Michael
Published: February 2023

Tidal bores are natural phenomena observed in at least 450 river estuaries all around the world from Europe to America and Asia. Tidal bores manifest as a series of waves propagating over long distances upstream in the estuarine zone of a river. Bores can be studied experimentally using sloshing water tanks where sloshing itself is a process with many applications, not only relevant for environmental flows. In a remarkable paper, Cox and Mortell (1986) showed that for an oscillating water tank, the evolution of small-amplitude, long-wavelength, resonantly forced waves follow a forced Korteweg-de Vries (fKdV) equation. The solutions of this model agree well with experimental results by Chester and Bones (1968). At first glance this is surprising since their experimental setup is in conflict with a number of assumptions made for deriving the fKdV equation. It is hence worth to repeat the experiment by Chester and Bones but using a long narrow channel setup.We use a long circular channel and repeat the experiments by Chester and Bones. We compare the results with solutions from the fKdV equation but also with the one from a full nonlinear model solving the Navier-Stokes equations. Under resonance conditions, depending on the parameters, we find a range of nonlinear localized wave types from single and multiple solitons to undular bores. As shown by Cox and Mortell, when the fluid is considered to be inviscid a kind of Fermi-Pasta-Ulam recurrence is observed for the fKdV model. Stationarity is reached by including a weak damping to the fKdV equation. ReferencesA.A. Cox, M.P. Mortell 1986. J. Fluid Mech. 162, pp. 99-116.W. Chester and J.A. Bones 1968. Proc. Roy. Soc. A, 306, 23 (Part II).
Centrifuge model test platform for rainfall simulation triggering shallow landslides
Authors: Park Joon-Young , Cheon Enok , Lee Seung-Rae , Choo Jinhyun , Lim Hwan-hui , Nam Ye-eun
Published: February 2023

A centrifuge model test platform was designed and developed to verify the critical continuous rainfalls triggering shallow landslides in natural slopes. Based on literature reviews, in-situ dimensions of shallow landslides on natural slopes were determined to 40 m (Length) × 16 m (Width) × 2 m (Depth) on average. In consequence, considering the model mounting space of the centrifuge test facility, a gravity level was decided (N = 40g) so that the length of a model slope equals 1 m according to scaling law. The width and depth of the model slope were hence determined to 0.4 m and 0.05 m, respectively. On the other hand, a rainfall simulator comprised of a series of air-atomizing spray nozzles was designed and developed considering scaling laws of rainfall infiltration and subsurface water flows. As a simulation result in a 40g condition, rainfall dispersions reduced and its trajectory bending induced by Coriolis’ force was almost vanished. After the development of centrifuge model test platform, several 1g performance tests of the rainfall simulator were conducted to test the spatial uniformity of rainfall distributions and fit the conditions of applying water and air pressures to rainfall intensities. The study also presents preliminary test results of shallow landslides in a 1g condition conducted to find and solve errors and unexpected problems before mounting the platform to the centrifuge test facility.
Considering contact between snow-slab and base for a collapsing weak layer in closed-form models
Authors: Rosendahl Philipp , Schneider Johannes , Weißgraeber Philipp
Published: February 2023

The Weak Layer Anticrack Model (WEAC) [1] is a tool for the analysis of snow slabs and the underlying weak layer, a system prone to release dry snow slab avalanches. Based on first-order shear deformation beam theory, it provides a closed-form solution for the deformation of the snowpack and the stress and energy release rate of the weak layer. Using a mixed-mode failure criterion for the weak layer, the model can predict anticrack nucleation preceding the release of an avalanche. In the current state, it allows unbounded vertical slab deformation. To limit this deformation to the collapse height of the weak layer, contact between the snow slab and the substratum must be considered. The present work proposes an extension of the model to take this effect into account.

The propagation of a crack in the weak layer increases the deflection of the slab until it is finally in contact with the substratum. This corresponds to a change of boundary conditions and introduces a structural nonlinearity. This nonlinearity is handled by decomposing the nonlinear structural system of slab and weak layer into four linear subsystems, each of these applying to different scopes of crack lengths. For a given crack length, the subsystem to apply accordingly is evaluated by comparing the crack length at hand with the previously defined scopes. The subsystem constituted in this manner is then employed to calculate the energy release rate of a propagating anticrack and the stresses in the remaining intact weak layer.

A comparison with a finite element reference model shows good agreement with the analytical model and, thus, validates the assumptions made. Parametric investigations on propagation saw tests address the effect of slab-substratum contact on the crack propagation conditions in snowpacks or experiments such as propagation saw tests.

[1] Rosendahl, Philipp Laurens, & Weissgraeber, Philipp. (2021). Weak Layer Anticrack Nucleation Model (WEAC) (2.2.1). Zenodo. https://doi.org/10.5281/zenodo.6366666
Carbonate sediment production, redistribution and accumulation in ongoing climate warming – The case of Lakshadweep Archipelago
Authors: Menon Shradha , Khanna Pankaj
Published: February 2023

Isolated carbonate platforms in tropical regions exhibit varying geomorphic characteristics as a consequence of differences in carbonate factories, hydrodynamic and global climatic controls. The stability of islands is dependent on the interplay between local and global factors and thus, ascertaining these factors is significant. Determining the facies and their correlation with lagoon filling is significant in determining the future of the islands to sea level rise. In the Indian context, the Lakshadweep Archipelago forms the best repository to understand the variability in sediment production to local hydrodynamics and global sea level change.The Lakshadweep Archipelago is in the Arabian Sea off the western coast of the Indian Peninsula with an average elevation of 0.5m to 6m. This study investigates two islands, viz Agatti and Kavaratti and the adjacent lagoons utilizing sedimentological data; supplemented with satellite geomorphological studies. Geomorphic units have been identified by satellite and field studies. 42 samples have been collected from Agatti lagoon and 24 samples from the Kavaratti lagoon along E-W transects. The samples have been characterized texturally based on Dunham classification. Furthermore, petrographic analysis has been carried out for the soft sediments, representing different grain size classes to characterize the major sediment producers and grain types. These datasets are utilized to develop the depth and the first facies maps of these lagoons.Both, the islands are approximately 4 sq km in size and are present on the eastern part of the atoll. The lagoon is about 17 sq.km for the Agatti that is more than thrice of Kavaratti that is 5 sq km. The average depth is 2m and maximum observed depth is 4m for both the lagoons. Satellite studies indicate well developed patch reefs (Acropora and Porites) and lobate sand features. The sediments are mostly coarse to medium-grained carbonate sand. No correlation between sediment size and lagoon depths has been identified. Petrographic analyses illustrate corals and foraminifera as predominant sediment producers for the coarse-grained fraction along with algae (Halimeda) and some gastropods. Based on the annual hydrodynamic patterns it is observed that the SW monsoon plays a dominant role in sediment distribution. With significant warming, the sediment production could be lowered/reduced thereby affecting the lagoon infilling and the future of the islands. The study, thus, emphasizes the necessity of acknowledging local factors and quantifying the different carbonate factories and how they will be influenced by warming seas will be critical in determining the stability of an island.