Preprints
Filtering by Subject: Statistics and Probability
What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling
Published: 2019-04-08
Subjects: Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Life Sciences, Mathematics, Medicine and Health Sciences, Physical Sciences and Mathematics, Risk Analysis, Statistics and Probability
Computer models are essential tools in the earth system sciences. They underpin our search for understanding of earth system functioning and support decision- and policy-making across spatial and temporal scales. To understand the implications of uncertainty and environmental variability on the identification of such earth system models and their predictions, we can rely on increasingly powerful [...]
Matlab/R workflows to assess critical choices in Global Sensitivity Analysis using the SAFE toolbox
Published: 2019-04-05
Subjects: Applied Mathematics, Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Physical Sciences and Mathematics, Risk Analysis, Statistics and Probability
Global Sensitivity Analysis (GSA) is a set of statistical techniques to investigate the effects of the uncertainty in the input factors of a mathematical model on the model’s outputs. The value of GSA for the construction, evaluation, and improvement of earth system models is reviewed in a companion paper by Wagener and Pianosi [n.d.]. The present paper focuses on the implementation of GSA and [...]
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 [...]
High-resolution prediction of organic matter concentration with hyperspectral imaging on a sediment core
Published: 2019-02-21
Subjects: Analytical Chemistry, Chemistry, Earth Sciences, Environmental Chemistry, Environmental Monitoring, Environmental Sciences, Optics, Physical Sciences and Mathematics, Physics, Sedimentology, Statistical Models, Statistics and Probability
In the case of environmental samples, the use of a chemometrics-based prediction model is highly challenging because of the difficulty in experimentally creating a well-ranged reference sample set. In this study, we present a methodology using short wave infrared hyperspectral imaging to create a partial least squares regression model on a cored sediment sample. It was applied to a sediment core [...]
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 [...]
A statistics-based reconstruction of high-resolution global terrestrial climate for the last 800,000 years
Published: 2019-01-18
Subjects: Climate, Earth Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistical Models, Statistics and Probability
Curated global climate data have been generated from climate model outputs for the last 120,000 years, whereas reconstructions going back even further have been lacking due to the high computational cost of climate simulations. Here, we present a statistically-derived global terrestrial climate dataset for every 1,000 years of the last 800,000 years. It is based on a set of linear regressions [...]
A PCA-based framework for determining remotely-sensed geological surface orientations and their statistical quality
Published: 2018-11-07
Subjects: Earth Sciences, Geology, Physical Sciences and Mathematics, Planetary Geology, Planetary Sciences, Planetary Sedimentology, Statistical Methodology, Statistics and Probability, Stratigraphy, Tectonics and Structure
The orientations of planar rock layers are fundamental to our understanding of structural geology and stratigraphy. Remote-sensing platforms including satellites, unmanned aerial vehicles (UAVs), and LIDAR scanners are increasingly used to build three-dimensional models of structural features on Earth and other planets. Remotely-gathered orientation measurements are straightforward to calculate [...]
Implications of ambiguity in Antarctic ice sheet dynamics for future coastal erosion estimates: a probabilistic assessment
Published: 2018-11-02
Subjects: Earth Sciences, Engineering, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Probability, Statistical Models, Statistics and Probability
Sea-level rise (SLR) can amplify the episodic erosion from storms and drive chronic erosion on sandy shorelines, threatening many coastal communities. One of the major uncertainties in SLR projections is the potential rapid disintegration of large fractions of the Antarctic ice sheet (AIS). Quantifying this uncertainty is essential to support sound risk management of coastal areas, although it is [...]
SSPipeline: A pipeline for estimating and characterizing uncertainty in coastal storm surge levels
Published: 2018-10-22
Subjects: Computer Sciences, Engineering, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics, Statistical Models, Statistics and Probability
Effective management of coastal risks demands projections of flood hazards that account for a wide variety of potential sources of uncertainty. Two typical approaches for estimating flood hazards include (1) direct physical process-based modeling of the storms themselves and (2) statistical modeling of the distributions and relevant characteristics of extreme sea level events. Recently, flexible [...]
Learning about climate change uncertainty enables flexible water infrastructure planning
Published: 2018-09-29
Subjects: Civil and Environmental Engineering, Civil Engineering, Climate, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Hydrology, Numerical Analysis and Scientific Computing, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability, Water Resource Management
Water resources planning requires making decisions about infrastructure development under substantial uncertainty in future regional climate conditions. However, uncertainty in climate change projections will evolve over the 100-year lifetime of a dam as new climate observations become available. Flexible strategies in which infrastructure is proactively designed to be changed in the future have [...]
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 [...]
Higher potential compound flood risk in Northern Europe under anthropogenic climate change
Published: 2018-07-18
Subjects: Applied Mathematics, Atmospheric Sciences, Climate, Earth Sciences, Environmental Sciences, Hydrology, Multivariate Analysis, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Oceanography and Atmospheric Sciences and Meteorology, Other Physical Sciences and Mathematics, Physical Sciences and Mathematics, Physics, Statistics and Probability
The published version of this article is available at https://advances.sciencemag.org/content/5/9/eaaw5531. Compound flooding (CF) is an extreme event taking place in low-lying coastal areas as a result of co-occurring high sea level and large amounts of runoff, caused by precipitation. The impact from the two hazards occurring individually can be significantly lower than the result of their [...]
Preparing for the Utilization of Data Science / Data Analytics in Earth Science Research
Published: 2018-06-21
Subjects: Computational Engineering, Computer Sciences, Databases and Information Systems, Education, Engineering, Mathematics, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics, Science and Mathematics Education, Statistics and Probability
Data analytics is the process of examining large amounts of varying data types to uncover hidden patterns, unknown correlations and other useful information. The Earth Science Information Partners (ESIP) Earth Science Data Analytics (ESDA) Cluster was created to facilitate the co-analysis of Earth science data and information. In addition to pioneering the definition of ESDA, the cluster has [...]
Landscape classification with deep neural networks.
Published: 2018-06-18
Subjects: Computer and Systems Architecture, Computer Engineering, Earth Sciences, Engineering, Environmental Monitoring, Environmental Sciences, Geology, Geomorphology, Other Statistics and Probability, Physical Sciences and Mathematics, Statistics and Probability
The application of deep learning, specifically deep convolutional neural networks (DCNNs), to the classification of remotely sensed imagery of natural landscapes has the potential to greatly assist in the analysis and interpretation of geomorphic processes. However, the general usefulness of deep learning applied to conventional photographic imagery at a landscape scale is, at yet, largely [...]