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Multi-level emulation of tsunami simulations over Cilacap, South Java, Indonesia
Carrying out a Probabilistic Tsunami Hazard Assessment (PTHA) requires a large number of simulations done at a high resolution. Statistical emulation...
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A simple hybrid statistical–dynamical downscaling method for emulating regional climate models over Western Europe. Evaluation, application, and role of added value?
A hybrid statistical dynamical downscaling method intended to emulate regional climate models is described and applied to Western Europe. The method...
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Probabilistic Landslide-Generated Tsunamis in the Indus Canyon, NW Indian Ocean, Using Statistical Emulation
The Indus Canyon in the northwestern Indian Ocean has been reported to be the site of numerous submarine mass failures in the past. This study is the...
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Bayesian active learning for parameter calibration of landslide run-out models
Landslide run-out modeling is a powerful model-based decision support tool for landslide hazard assessment and mitigation. Most landslide run-out...
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Emulation of CPU-demanding reactive transport models: a comparison of Gaussian processes, polynomial chaos expansion, and deep neural networks
This paper presents a detailed comparison between 3 methods for emulating CPU-intensive reactive transport models (RTMs): Gaussian processes (GPs),...
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Emulator-based global sensitivity analysis for flow-like landslide run-out models
Landslide run-out modeling involves various uncertainties originating from model input data. It is therefore desirable to assess the model’s...
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Artificial Intelligence and Its Application in Numerical Weather Prediction
AbstractArtificial intelligence is one of the most popular, frequently discussed, and, meanwhile, ambiguous and controversial metaphorical concepts,...
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Regional climate model emulator based on deep learning: concept and first evaluation of a novel hybrid downscaling approach
Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we...
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Multi-level emulation of complex climate model responses to boundary forcing data
Climate model components involve both high-dimensional input and output fields. It is desirable to efficiently generate spatio-temporal outputs of...
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A dual model for emulation of thermosteric and dynamic sea-level change
Future thermosteric and dynamic sea-level changes are often projected by process-based climate models. Emulation of such computationally expensive...
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Volcanic effects on climate: recent advances and future avenues
Volcanic eruptions have long been studied for their wide range of climatic effects. Although global-scale climatic impacts following the formation of...
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Cluster Analysis of Moment Tensor Solutions and its Application to Rockburst Risk Assessment in Underground Coal Mines
High-magnitude events (HMEs) are commonly observed in underground mines, and they can lead to violent rock failures, such as rockbursts. While moment...
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Speeding Up Reactive Transport Simulations in Cement Systems by Surrogate Geochemical Modeling: Deep Neural Networks and k-Nearest Neighbors
We accelerate reactive transport (RT) simulation by replacing the geochemical solver in the RT code by a surrogate model or emulator, considering...
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Response of stratospheric water vapour to warming constrained by satellite observations
Future increases in stratospheric water vapour risk amplifying climate change and slowing down the recovery of the ozone layer. However,...
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Filling the matrix: an ANOVA-based method to emulate regional climate model simulations for equally-weighted properties of ensembles of opportunity
Collections of large ensembles of regional climate model (RCM) downscaled climate data for particular regions and scenarios can be organized in a...
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Developments in Quantitative Assessment and Modeling of Mineral Resource Potential: An Overview
The special issue entitled “Developments in Quantitative Assessment and Modeling of Mineral Resource Potential” is composed of 17 papers that cover a...
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Prediction of the mean fragment size in mine blasting operations by deep learning and grey wolf optimization algorithm
Mean fragment size is an important index in mine blasting since it significantly influences downstream work efficiency. Therefore, it is necessary to...
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Regional storm surge hazard quantification using Gaussian process metamodeling techniques
The recent, very active hurricane seasons, as well as emerging concerns related to the future effects of sea-level rise, hurricane intensification,...
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Advances in Atmospheric Radiation: Theories, Models, and Their Applications. Part I: Atmospheric Gas Absorption and Particle Scattering
Atmospheric radiation is a major branch of atmospheric physics that encompasses the fundamental theories of atmospheric absorption, particle...