Preprints

Filtering by Subject: Statistical Models

Wildfire Smoke Exposure Worsens Learning Outcomes

Jeff Wen, Marshall Burke

Published: 2021-12-08
Subjects: Environmental Public Health, Environmental Sciences, Environmental Studies, Statistical Models

Wildfires and associated smoke exposure have increased in frequency and severity over the past two decades, threatening to undo decades of air quality improvements. Our understanding of the impacts of these growing exposures on a range of societal outcomes remains incomplete. Building on emerging evidence that environmental exposures can negatively affect cognition, we investigate the effect of [...]

Estuarine-deltaic controls on coastal carbon burial in the western Ganges-Brahmaputra delta over the last 5,000 years

Rory Patrick Flood, Margaret Georgina Milne, Graeme T Swindles, et al.

Published: 2021-11-26
Subjects: Applied Statistics, Biogeochemistry, Earth Sciences, Environmental Sciences, Geochemistry, Geology, Geomorphology, Other Earth Sciences, Other Environmental Sciences, Other Statistics and Probability, Physical Sciences and Mathematics, Sedimentology, Statistical Methodology, Statistical Models, Statistics and Probability, Water Resource Management

The Ganges–Brahmaputra fluvial system drains the Himalayas and is one of the largest sources of terrestrial biosphere carbon to the ocean. It represents a major continental reservoir of CO2 associated with c. 1–2 billion tons of sediment transported each year. Shallow coastal environments receive substantial inputs of terrestrial carbon (900 Tg C yr−1), with allochthonous carbon capture on [...]

C3S Energy: an operational service to deliver power demand and supply for different electricity sources, time and spatial scales over Europe

Laurent Dubus, Yves-Marie Saint-Drenan, Alberto Troccoli, et al.

Published: 2021-11-17
Subjects: Applied Statistics, Climate, Earth Sciences, Environmental Sciences, Statistical Models

The EU Copernicus Climate Change Service (C3S) has produced an operational climate service, called C3S Energy, designed to enable the energy industry and policy makers to assess the impacts of climate variability and climate change on the energy sector in Europe. The C3S Energy service covers different time horizons, for the past forty years and the future. It provides time series of electricity [...]

Beyond prediction: methods for interpreting complex models of soil variation

Alexandre M.J.-C. Wadoux, Christoph Molnar

Published: 2021-10-26
Subjects: Applied Statistics, Soil Science, Statistical Models

Understanding the spatial variation of soil properties is central to many sub-disciplines of soil science. Commonly in soil mapping studies, a soil map is constructed through prediction by a statistical or non-statistical model calibrated with measured values of the soil property and environmental covariates of which maps are available. In recent years, the field has gradually shifted attention [...]

Exposures and behavioral responses to wildfire smoke

Marshall Burke, Sam Heft-Neal, Jessica Li, et al.

Published: 2021-10-11
Subjects: Environmental Monitoring, Environmental Public Health, Environmental Studies, Statistical Models

The impacts of environmental change on human outcomes often depend on local exposures and behavioral responses that are challenging to observe with traditional administrative or sensor data. We show how data from private pollution sensors, cell phones, social media posts, and internet search activity yield new insights on exposures and behavioral responses during large wildfire smoke events [...]

Predicting Fire Season Intensity in Maritime Southeast Asia with Interpretable Models

William Stewart Daniels, Dorit M Hammerling, Rebecca R Buchholz, et al.

Published: 2021-09-10
Subjects: Atmospheric Sciences, Statistical Models

There have been many extreme fire seasons in Maritime Southeast Asia (MSEA) over the last two decades, a trend which will likely continue, if not accelerate, due to climate change. Fires, in turn, are a major driver of atmospheric carbon monoxide (CO) variability, especially in the Southern Hemisphere. Previous studies have explored the relationship between climate variability and fire counts, [...]

The Rayleigh-Haring-Tayfun distribution of wave heights in deep water

Saulo Matusalem da Silva Mendes, Alberto Scotti

Published: 2021-01-17
Subjects: Engineering, Fluid Dynamics, Hydraulic Engineering, Oceanography, Statistical Models

Regarding wave statistics, nearly every known exceeding probability distribution applied to rogue waves has shown disagreement with its peers. More often than not, models and experiments have shown a fair agreement with the Rayleigh distribution whereas others show that the latter underpredicts extreme heights by almost one order of magnitude. Virtually all previous results seem to be [...]

Bias correction of global climate model using machine learning algorithms to determine meteorological variables in different tropical climates of Indonesia

Juan Nathaniel

Published: 2020-12-11
Subjects: Applied Statistics, Atmospheric Sciences, Planetary Geophysics and Seismology, Statistical Models

Accurate and localized forecasting of climate variables are important especially in the face of uncertainty imposed by climate change. However, the data used for prediction are either incomplete at the local level or inaccurate because the simulation models do not explicitly consider local contexts and extreme events. This paper, therefore, attempts to bridge this gap by applying tree-based [...]

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 [...]

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 [...]

Probabilistic soil moisture dynamics of water- and energy-limited ecosystems

Estefanía Muñoz, Andrés Ochoa, Germán Poveda, et al.

Published: 2020-05-17
Subjects: Agriculture, Agronomy and Crop Sciences Life Sciences, Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Sciences, Forest Sciences, Hydrology, Life Sciences, Physical Sciences and Mathematics, Plant Sciences, Statistical Models, Statistics and Probability

This paper presents an extension of the stochastic ecohydrological model for soil moisture dynamics at a point of Rodriguez-Iturbe et al. (1999) and Laio et al. (2001). In the original model, evapotranspiration is a function of soil moisture and vegetation parameters, so that the model is suitable for water-limited environments. Our extension introduces a dependence on maximum evapotranspiration [...]

Evaluating the INLA-SPDE approach for Bayesian modeling of earthquake damages from geolocated cluster data

Bradley Wilson

Published: 2020-01-27
Subjects: Physical Sciences and Mathematics, Statistical Models, Statistics and Probability

Modeled damage estimates are an important source of information in the hours to weeks following major earthquake disasters, but often lack sufficient spatial resolution for highlighting specific areas of need. Using damage assessment data from the 2015 Gorkha, Nepal Earthquake, this paper evaluates a Bayesian spatial model (INLA-SPDE) for interpolating geolocated damage survey data onto 1 km2 [...]

Probabilistic space- and time-interaction modeling of main-shock earthquake rupture occurrence

Luis Ceferino, Anne Kiremidjian, Gregory Deierlein

Published: 2019-04-28
Subjects: Civil and Environmental Engineering, Earth Sciences, Engineering, Geophysics and Seismology, Physical Sciences and Mathematics, Statistical Models, Statistics and Probability, Structural Engineering

This paper presents a probabilistic formulation for modeling earthquake rupture processes of mainshocks. A correlated multivariate Bernoulli distribution is used to model rupture occurrence. The model captures time interaction through the use of Brownian passage-time (BPT) distributions to assess rupture interarrival in multiple sections of the fault, and it also considers spatial interaction [...]

High-resolution prediction of organic matter concentration with hyperspectral imaging on a sediment core

Kévin Jacq, Yves Perrette, Fanget Bernard, et al.

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 [...]

A statistics-based reconstruction of high-resolution global terrestrial climate for the last 800,000 years

Mario Krapp, Robert Beyer, Stephen L. Edmundson, et al.

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 [...]

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