Higher temperature sensitivity of retrogressive thaw slump activity in the Arctic compared to the Third Pole

The Science of The Total Environment, Год журнала: 2024, Номер 914, С. 170007 - 170007

Опубликована: Янв. 16, 2024

Язык: Английский

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Multi-hazard assessment of climate-related hazards for European coastal cities

Journal of Environmental Management, Год журнала: 2024, Номер 357, С. 120787 - 120787

Опубликована: Апрель 1, 2024

The assessment of risk posed by climate change in coastal cities encompasses multiple climate-related hazards. Sea-level rise, flooding and erosion are important hazards, but they not the only ones. varying availability quality data across hinders ability to conduct holistic standardized multi-hazard assessments. Indeed, there far fewer studies on hazards than single Also, comparability existing methodologies becomes challenging, making it difficult establish a cohesive understanding overall vulnerability resilience cities. use indicators allows for systematic evaluation baseline different methodology developed this work establishes framework assess wide variety diverse cities, including sea-level flooding, erosion, heavy rainfall, land droughts, extreme temperatures, heatwaves, cold spells, strong winds landslides. Indicators produced results compared mapped ten European meticulously designed be applicable geographical contexts Europe. In manner, proposed approach interventions prioritized based severity urgency specific risks faced each city.

Язык: Английский

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First Pockmark Susceptibility map of the Italian continental margins

Marine and Petroleum Geology, Год журнала: 2025, Номер unknown, С. 107337 - 107337

Опубликована: Фев. 1, 2025

Язык: Английский

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Retrogressive thaw slump susceptibility in the northern hemisphere permafrost region

Earth Surface Processes and Landforms, Год журнала: 2024, Номер 49(11), С. 3319 - 3331

Опубликована: Май 22, 2024

Abstract Mean annual temperatures in the Arctic and subarctic have increased recent decades, increasing number of permafrost hazards. Retrogressive thaw slumps (RTSs), triggered by thawing ground ice soil, become more common Arctic. Many studies report an increase RTS activity on a local or regional scale. In this study, primary goals are to: (i) examine spatial patterns occurrences across circumpolar region, (ii) assess environmental factors associated with their occurrence (iii) create first susceptibility map for Northern Hemisphere. Based our results, we predicted high continuous regions above 60th latitude, especially northern Alaska, north‐western Canada, Yamal Peninsula, eastern Russia Qinghai‐Tibetan Plateau. The model indicated that air temperature soil properties most critical RTSs Especially, climatic conditions season were highlighted. This study provided new insights into ice‐rich soils to rapid permafrost‐related hazards like impacts landscape evolution, infrastructure, hydrology carbon fluxes contribute global warming.

Язык: Английский

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A benchmark dataset and workflow for landslide susceptibility zonation

Earth-Science Reviews, Год журнала: 2024, Номер 258, С. 104927 - 104927

Опубликована: Сен. 11, 2024

Язык: Английский

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Scientometric review on multiple climate-related hazards indices

The Science of The Total Environment, Год журнала: 2024, Номер 945, С. 174004 - 174004

Опубликована: Июнь 18, 2024

As the spectre of climate change looms large, there is an increasing imperative to develop comprehensive risk assessment tools. The purpose this work evaluate evolution and current state research on multi-hazard indices associated with climate-related hazards, highlighting their crucial role in effective amidst growing challenges change. A notable gap cross-regional comparative studies persists, presenting opportunity for future enhance global understanding foster universal resilience strategies. However, a significant surge output apparent, following key milestones related action. landscape shown be highly responsive international policy developments, increasingly adopting interdisciplinary approaches that integrate physical, social, technological dimensions. Findings reveal robust emphasis geospatial analysis development various transform abstract risks into actionable data, underscoring trend towards localized, context-specific vulnerability assessments. Based dataset systematically curated under PRISMA guidelines, review explores how prevailing themes are reflected influential journals author networks, mapping out dynamic expanding academic community. Moreover, provides critical insights underlying literature by conducting thematic typology studies, focus coastal areas, inclusion scenarios, geographical coverage, types hazards. practical implications profound, providing policymakers practitioners meaningful mitigation adaptation efforts through application index-based methodologies. By charting course scholarly endeavours, article aims strengthen scientific foundations supporting resilient adaptive strategies regions worldwide facing multifaceted impacts

Язык: Английский

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ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool

Geoscientific model development, Год журнала: 2025, Номер 18(2), С. 433 - 459

Опубликована: Янв. 27, 2025

Abstract. The accurate calibration of parameters in atmospheric and Earth system models is crucial for improving their performance but remains a challenge due to inherent complexity, which reflected input–output relationships often characterised by multiple interactions between the parameters, thus hindering use simple sensitivity analysis methods. This paper introduces Machine Learning-based Automated Multi-method Parameter Sensitivity Importance Tool (ML-AMPSIT), new tool designed with aim providing flexible framework estimate importance complex numerical weather prediction models. leverages strengths regression-based probabilistic machine learning methods, including LASSO (see list abbreviations Appendix B), support vector machine, classification regression trees, random forest, extreme gradient boosting, Gaussian process regression, Bayesian ridge regression. These algorithms are used construct computationally inexpensive surrogate effectively predict impact input parameter variations on model output, thereby significantly reducing computational burden running high-fidelity analysis. Moreover, multi-method approach allows comparative results. Through detailed case study Weather Research Forecasting (WRF) coupled Noah-MP land surface model, ML-AMPSIT demonstrated efficiently effects varying values relatively small number runs simulating sea breeze circulation over an idealised flat domain. points out how can be efficient performing models, guiding user through different steps allowing simplification automatisation process.

Язык: Английский

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Functional Regression for Space‐Time Prediction of Precipitation‐Induced Shallow Landslides in South Tyrol, Italy

Journal of Geophysical Research Earth Surface, Год журнала: 2025, Номер 130(4)

Опубликована: Апрель 1, 2025

Abstract Landslides are geomorphic hazards in mountainous terrains across the globe, driven by a complex interplay of static and dynamic controls. Data‐driven approaches have been employed to assess landslide occurrence at regional scales analyzing spatial aspects time‐varying conditions separately. However, joint assessment landslides space time remains challenging. This study aims predict precipitation‐induced shallow within Italian province South Tyrol (7,400 km 2 ). We introduce functional predictor framework where precipitation is represented as continuous series, contrast conventional that treat scalar predictor. Using hourly data past occurrences from 2012 2021, we implemented generalized additive model derive statistical relationships between occurrence, various factors, preceding evaluated resulting predictions through several cross‐validation routines, yielding performance scores frequently exceeding 0.90. To demonstrate predictive capabilities, performed hindcast for storm event Passeier Valley on 4–5 August 2016, capturing observed locations illustrating evolution predicted probabilities. Compared standard early warning approaches, this eliminates need predefine fixed windows aggregation while inherently accounting lagged effects. By integrating controls, research advances prediction large areas, addressing seasonal effects underlying limitations.

Язык: Английский

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Assessing Machine Learning and Statistical Methods for Rock Glacier‐Based Permafrost Distribution in Northern Kargil Region

Permafrost and Periglacial Processes, Год журнала: 2024, Номер 35(3), С. 262 - 277

Опубликована: Июнь 18, 2024

ABSTRACT Estimating permafrost distribution in high‐mountain areas is challenging. In these situations, rock glaciers, provide valuable insights into and are often used as proxies for identifying occurrence. Integrating various climatological topographical conditioning factors with glaciers enables inferring the of environments. This study utilized three machine learning models such random forest (RF), support vector (SVM), artificial neural network (ANN), one statistical model, namely, frequency ratio (FR), to assess probability over northern Kargil region Indian Himalayas. Among 198 identified through high‐resolution images from Google Earth, 70% training dataset, rest 30% testing dataset. The considered eight factors: slope, aspect, elevation, curvature, mean annual land surface temperature (MA‐LST), normalized difference snow index (MA‐NDSI), water (MA‐NDWI), lithology mapping. Furthermore, SHapley Additive exPlanations (SHAP) test assessed variable importance model performance. results revealed that RF performs best mapping, followed by SVM, FR, ANN models. also found 11% total geographic area has a high very

Язык: Английский

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Near Pan-Svalbard permafrost cryospheric hazards inventory (SvalCryo)

Scientific Data, Год журнала: 2024, Номер 11(1)

Опубликована: Авг. 17, 2024

Cryospheric hazards - in this case, thaw slumps (TS) and thermo-erosion gullies (TEG) are phenomena typical of permafrost-dominated landscapes. Open datasets informing about their spatial, temporal size distributions the Arctic still uncommon, as opposed to systematic availability information for geomorphic processes mid- low- latitudes. To date, only most populated region Svalbard was covered with TS TEG inventories. Here, we extend respective Archipelago, totalling 8491 polygons, out which 3679 TSs 4812 TEGs. These have been manually mapped from aerial photographs throughout across 14 largest ice-free regions. The SvalCryo inventory is highly relevant environment undergoes alarming changes response global warming. idea behind two inventories support geoscientific community quest evaluate environmental climate change, by creating a baseline change monitoring, ultimately serve basis susceptibility, hazard risk assessment models.

Язык: Английский

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