Preprints

Filtering by Subject: Statistics and Probability

Near-term forecasts of stream temperature using process-guided deep learning and data assimilation

Jacob Aaron Zwart, Samantha Kay Oliver, William David Watkins, et al.

Published: 2021-08-13
Subjects: Computer Sciences, Hydrology, Statistics and Probability, Water Resource Management

Near-term forecasts of environmental outcomes can inform real-time decision making. Data assimilation modeling techniques can be used for forecasts to leverage real-time data streams, where the difference between model predictions and observations can be used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided deep learning and data [...]

Using sedimentological priors to improve 14C calibration of bioturbated sediment archives.

Bryan C. Lougheed

Published: 2021-06-30
Subjects: Earth Sciences, Geology, Physical Sciences and Mathematics, Probability, Statistics and Probability

Radiocarbon (14C) dating is often carried out upon multi-specimen samples sourced from bioturbated sediment archives, such as deep-sea sediment. These samples are inherently heterogeneous in age, but current 14C calibration techniques applied to such age heterogenous samples were originally developed for age homogeneous material. A lack of information about age heterogeneity leads to a systematic [...]

On the statistical learning analysis of rain gauge data over the Natuna Islands

Sandy Hardian Susanto Herho, Faiz Rohman Fajary, Dasapta Erwin Irawan

Published: 2021-06-08
Subjects: Applied Statistics, Atmospheric Sciences, Longitudinal Data Analysis and Time Series, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability

This article presents state-of-the-art statistical learning methods for analyzing rain gauge data over the Natuna Islands. By using shape preserving piecewise cubic interpolation, we managed to interpolate 671 null values from the daily precipitation data. Dominant periodicity analysis of daily precipitation signals using Lomb-Scargle Power Spectral Density shows annual, intraseasonal, and [...]

A data assimilation framework to constrain the driving processes of anthropogenically induced subsidence

Thibault Candela, Alin Chitu, Elisabeth Peters, et al.

Published: 2021-03-25
Subjects: Earth Sciences, Environmental Sciences, Oil, Gas, and Energy, Statistics and Probability

Surface movement can be induced by many human subsurface activities: natural gas production, geothermal heat extraction, ground water extraction, phreatic groundwater level lowering, storage of natural gas and CO2. In this manuscript, we focus on subsidence caused by gas production. While geological interpretations, seismic campaigns and flow modeling often provide a relatively rich pre-existing [...]

Can hydrocarbon extraction from the crust enhance or inhibit seismicity in tectonically active regions? A statistical study in Italy

Alexander Garcia, Licia Faenza, Andrea Morelli, et al.

Published: 2021-03-17
Subjects: Earth Sciences, Environmental Sciences, Statistics and Probability

A number of oil- and gas-producing leases have been operating in Italy in the last decades, many of which are located in the surroundings of tectonically active regions. Identifying human-induced seismicity in areas with high levels of natural seismicity is a difficult task for which virtually any result can be a source of controversy. We implemented a large-scale analysis aiming at tracking [...]

Seasonal Arctic sea ice forecasting with probabilistic deep learning

Tom R. Andersson, J. Scott Hosking, Maria Pérez-Ortiz, et al.

Published: 2021-02-02
Subjects: Artificial Intelligence and Robotics, Earth Sciences, Statistics and Probability

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to [...]

Classification, segmentation and correlation of zoned minerals

Tom Sheldrake, Oliver John Higgins

Published: 2021-02-01
Subjects: Earth Sciences, Environmental Sciences, Geochemistry, Geology, Numerical Analysis and Scientific Computing, Statistics and Probability, Volcanology

Minerals exhibit zoning patterns that can be related to changes in the environment in which they grew. Using statistical methods that have been designed to segment optical images, we have developed a procedure to segment zonation within minerals and correlate these zones between multiple crystals using elemental maps. This allows us to quantify the complexity and variability of chemical zoning [...]

Assessing erosion and flood risk in the coastal zone through the application of the multilevel Monte Carlo method

Mariana C A Clare, Matthew Piggott, Colin J Cotter

Published: 2021-01-07
Subjects: Applied Mathematics, Earth Sciences, Geomorphology, Hydrology, Numerical Analysis and Computation, Risk Analysis, Statistics and Probability

The risk from erosion and flooding in the coastal zone has the potential to increase in a changing climate. The development and use of coupled hydro-morphodynamic models is therefore becoming an ever higher priority. However, their use as decision support tools suffers from the high degree of uncertainty associated with them, due to incomplete knowledge as well as natural variability in the [...]

Yield estimation of the 2020 Beirut explosion using open access waveform and remote sensing data

Christoph Pilger, Patrick Hupe, Peter Gaebler, et al.

Published: 2020-12-22
Subjects: Applied Statistics, Earth Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Physics, Statistics and Probability

We report on a multi-technique analysis using publicly available data for investigating the huge, accidental explosion that struck the city of Beirut, Lebanon, on August 4, 2020. Its devastating shock wave led to thousands of injured with more than two hundred fatalities and caused immense damage to buildings and infrastructure. Our combined analysis of seismological, hydroacoustic, infrasonic [...]

A Physics-Based Decorrelation Phase CovarianceModel for Noise Reduction in UnwrappedInterferometric Phase Stacks

Yujie Zheng, Howard Zebker, Roger Michaelides

Published: 2020-10-23
Subjects: Earth Sciences, Statistics and Probability

The accuracy of geophysical parameter estimation made with Interferometric Synthetic Aperture Radar (InSAR) time-series techniques can be improved with rapidly increasing available data volumes, and with the development of noise covariance matrices applicable to joint analysis of networks of interferograms. Here we present a physics-based decorrelation phase covariance model and discuss [...]

Sedimentary structures discriminations with hyperspectral imaging on sediment cores

Kévin Jacq, Rapuc William, Benoit Alexandre, et al.

Published: 2020-07-17
Subjects: Analytical Chemistry, Chemistry, Earth Sciences, Environmental Chemistry, Environmental Monitoring, Environmental Sciences, Multivariate Analysis, Optics, Physical Sciences and Mathematics, Physics, Sedimentology, Statistical Models, Statistics and Probability

Hyperspectral imaging (HSI) is a non-destructive high-resolution sensor, which is currently under significant development to analyze geological areas with remote devices or natural samples in a laboratory. In both cases, the hyperspectral image provides several sedimentary structures that need to be separated to temporally and spatially describe the sample. Sediment sequences are composed of [...]

Climate has contrasting direct and indirect effects on armed conflicts

David Helman, Ben Zaitchik, Chris Funk

Published: 2020-07-08
Subjects: Environmental Indicators and Impact Assessment, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geography, Human Geography, International and Area Studies, Library and Information Science, Life Sciences, Nature and Society Relations, Physical and Environmental Geography, Physical Sciences and Mathematics, Remote Sensing, Social and Behavioral Sciences, Statistics and Probability

There is an active debate regarding the influence that climate has on the risk of armed conflict, which stems from challenges in assembling unbiased datasets, competing hypotheses on the mechanisms of climate influence, and the difficulty of disentangling direct and indirect climate effects. We use gridded historical non-state conflict records, satellite data, and land surface models in a [...]

GANSim: Conditional Facies Simulation Using an Improved Progressive Growing of Generative Adversarial Networks (GANs)

Suihong Song, Tapan Mukerji, Jiagen Hou

Published: 2020-07-05
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geology, Hydrology, Mathematics, Physical Sciences and Mathematics, Sedimentology, Statistical Models, Statistics and Probability

Conditional facies modeling combines geological spatial patterns with different types of observed data, to build earth models for predictions of subsurface resources. Recently, researchers have used generative adversarial networks (GANs) for conditional facies modeling, where an unconditional GAN is first trained to learn the geological patterns using the original GANs loss function, then [...]

Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe

Dominik Paprotny, Heidi Kreibich, Oswaldo Morales-Nápoles, et al.

Published: 2020-07-05
Subjects: Earth Sciences, Hydrology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability

Commercial assets comprise buildings, machinery and equipment, which are susceptible to floods. Existing damage models and exposure estimation methods for this sector have limited transferability between flood events. In this study we introduce two methodologies aiming at broader applicability: (1) disaggregation of economic statistics to obtain detailed building-level estimates of replacement [...]

Seasonal impact-based mapping of compound hazards

John Hillier, Richard Dixon

Published: 2020-06-17
Subjects: Applied Mathematics, Atmospheric Sciences, Climate, Earth Sciences, Environmental Sciences, Hydrology, Mathematics, Multivariate Analysis, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability

Impact-based, seasonal mapping of compound hazards is proposed. It is pragmatic, identifies phenomena to drive the research agenda, produces outputs relevant to stakeholders, and could be applied to many hazards globally. Illustratively, flooding and wind damage can co-occur, worsening their joint impact, yet where wet and windy seasons combine has not yet been systematically mapped. Here, [...]

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