Preprints
Filtering by Subject: Applied Statistics
Trends of hydroclimatic intensity in Colombia
Published: 2019-05-08
Subjects: Applied Statistics, Civil and Environmental Engineering, Climate, Earth Sciences, Engineering, Environmental Engineering, Environmental Sciences, Hydrology, Life Sciences, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Risk Analysis, Statistics and Probability, Water Resource Management
Prediction of changes in precipitation in upcoming years and decades caused by global climate change associated with the greenhouse effect, deforestation and other anthropic perturbations is a practical and scientific problem of high complexity and huge consequences. To advance toward this challenge we look at the daily historical record of all available rain gauges in Colombia to estimate an [...]
Are Detected Trends in Flood Magnitude and Shifts in the Timing of Floods of A Major River Basin in India, Linked To Anthropogenic Stressors?
Published: 2019-04-10
Subjects: Applied Statistics, Civil and Environmental Engineering, Earth Sciences, Engineering, Hydraulic Engineering, Hydrology, Mathematics, Physical Sciences and Mathematics, Statistics and Probability
Analyzing of trends in flood magnitude and the timing of the dates of flood occurrences of large river basins across the globe are essential for understanding changes in water availability (high or low flows) and assessing the fidelity of global hydrological models. Our research is motivated by the recent six major consecutive floods in Mahanadi (years: 2001, 2003, 2006, 2008, 2011 and 2013) [...]
A simplified seasonal forecasting strategy, applied to wind and solar power in Europe
Published: 2019-04-01
Subjects: Applied Statistics, Earth Sciences, Environmental Sciences, Physical Sciences and Mathematics, Physics, Probability, Statistics and Probability, Sustainability
We demonstrate levels of skill for forecasts of seasonal-mean wind speed and solar irradiance in Europe, using seasonal forecast systems available from the Copernicus Climate Change Service (C3S). While skill is patchy, there is potential for the development of climate services for the energy sector. Following previous studies, we show that, where there is skill, a simple linear regression-based [...]
Deep Learning Application for 4D Pressure Saturation Inversion Compared to Bayesian Inversion on North Sea Data
Published: 2019-02-21
Subjects: Applied Statistics, Earth Sciences, Geophysics and Seismology, Physical Sciences and Mathematics, Statistics and Probability
In this work we present a deep neural network inversion on map-based 4D seismic data for pressure and saturation. We present a novel neural network architecture that trains on synthetic data and provides insights into observed field seismic. The network explicitly includes AVO gradient calculation within the network as physical knowledge to stabilize pressure and saturation changes separation. [...]
Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean
Published: 2019-01-25
Subjects: Applied Statistics, Earth Sciences, Environmental Education, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Geology, Geomorphology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Other Oceanography and Atmospheric Sciences and Meteorology, Other Statistics and Probability, Physical and Environmental Geography, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Statistics and Probability, Tectonics and Structure
The geographic focus of the current study Mariana trench, the deepest point of the Earth located in the west Pacific Ocean. Mariana trench has unique structure and features formed in the complex process of the trench development. There is a range of the environmental factors affecting trench structure and functioning: bathymetry, geography, geology and tectonics. Current research aimed to study [...]
Statistics and segmentation: Using Big Data to assess Cascades Arc compositional variability
Published: 2018-09-24
Subjects: Applied Mathematics, Applied Statistics, Earth Sciences, Geochemistry, Geology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability, Volcanology
Primitive lavas erupted in the Cascades arc of western North America demonstrate significant patterns of along-arc heterogeneity. Such compositional diversity may be the result of differences in mantle melting processes, subduction geometry, regional tectonics, or compositions of the slab, mantle or overlying lithosphere. Previous authors have partitioned the arc into four geochemically distinct [...]
Uncertainty in sea level rise projections due to the dependence between contributors
Published: 2018-03-08
Subjects: Applied Statistics, Climate, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Probability, Statistical Models, Statistics and Probability
Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion, glaciers, ice sheets...). To obtain the total sea level these contributions are added, therefore [...]
Bootstrapped high quantile estimation --- An experiment with scarce precipitation data
Published: 2018-02-25
Subjects: Applied Statistics, Physical Sciences and Mathematics, Probability, Statistics and Probability
This paper details team SUTD’s effort when participating in the “Prediction of extremal precipitation” challenge. We propose a framework that combines the generalized Pareto distribution, a bootstrap resampling scheme and inverse distance weights to capture spatial dependence. Our method reduces the quantile loss functions by 55.1% as compared to a naive benchmark, and shows improvement across [...]
Geostatistical modelling of cyclic and rhythmic facies architectures
Published: 2017-11-07
Subjects: Applied Statistics, Earth Sciences, Physical Sciences and Mathematics, Sedimentology, Statistics and Probability
A pluri-Gaussian method is developed for facies variables in three dimensions to model vertical cyclicity, related to facies ordering, and rhythmicity. Cyclicity is generally characterized by shallowing or deepening-upward sequences and rhythmicity by a low range of variability in cycle thicknesses. Both of these aspects are commonly observed in shallow-marine carbonate successions, especially [...]