Preprints

Filtering by Subject: Statistical Models

A Novel Definition of Climate State Using Kalman Filtering and Application to Thresholds

John Matthew Nicklas, Baylor Fox-Kemper, Charles E Lawrence

Published: 2022-10-18
Subjects: Longitudinal Data Analysis and Time Series, Non-linear Dynamics, Planetary Sciences, Statistical Models

Herein we present the Energy Balance Model – Kalman Filter (EBM-Kalman), a hybrid model of the global mean surface temperature (GMST), which combines a theoretical energy balance equation based in Earth science literature and a statistical extended Kalman Filter incorporating observed and/or climate model simulated GMST data. This synthesis is possible because climate models and historical [...]

Space-time landslide size modelling in Taiwan

Zhice Fang, Yi Wang, Cees J. van Westen, et al.

Published: 2022-10-10
Subjects: Applied Statistics, Geomorphology, Multivariate Analysis, Statistical Models

Landslide susceptibility assessment using data-driven models has predominantly focused on predicting where landslides may occur and not on how large they might be. The spatio-temporal evaluation of landslide susceptibility has only recently been addressed, as a basis for predicting where and when landslides might occur. The present study combines these new developments by proposing a data-driven [...]

Space-time landslide susceptibility modelling in Taiwan

Zhice Fang, Yi Wang, Cees J. van Westen, et al.

Published: 2022-07-27
Subjects: Applied Statistics, Geomorphology, Multivariate Analysis, Statistical Models

Portraying spatiotemporal variations in landslide susceptibility patterns is crucial for landslide prevention and management. In this study, we implement a space-time modeling approach to predict the landslide susceptibility on a yearly basis across the main island of Taiwan, from 2004 to 2018. We use a Bayesian version of a binomial generalized additive model, which assumes that landslide [...]

Hybrid machine learning for digital soil mapping across a longitudinal gradient of contrasting topography, climate and vegetation

Rodrigo Miranda, Rodolfo Nobrega, Estevão Silva, et al.

Published: 2022-07-22
Subjects: Environmental Monitoring, Soil Science, Statistical Models

Environmental models often require soil maps to represent the spatial variability of soil properties. However, mapping soils using conventional in situ survey protocols is time-consuming and costly. As an alternative, Digital Soil Mapping (DSM) offers a fast-mapping approach that has the potential to estimate soil properties and their interrelationships over large areas. In this study, we address [...]

The Lock-Down Effects of COVID-19 on the Air Pollution Indices in Iran and Its Neighbors

Mohammad Fayaz

Published: 2022-07-02
Subjects: Applied Statistics, Environmental Public Health, Environmental Sciences, Environmental Studies, Near and Middle Eastern Studies, Other Statistics and Probability, Statistical Methodology, Statistical Models

Introduction The Covid-19 restrictions have a lot of various peripheral negative and positive effects like economic shocks and decreasing air pollution, respectively. Many studies showed NO2 reduction in most parts of the world. Method Iran and its land and maritime neighbors have about 7.4% of the world population and 6.3% and 5.8% of World COVID-19 cases and deaths, respectively. The air [...]

Towards Robust River Plastic Detection: Combining Lab and Field-based Hyperspectral Imagery

Paolo Tasseron, Louise Schreyers, Joseph Peller, et al.

Published: 2022-06-29
Subjects: Earth Sciences, Environmental Monitoring, Environmental Sciences, Hydrology, Statistical Models

Plastic pollution in aquatic ecosystems has increased dramatically in the last five decades, with strong impacts on human and aquatic life. Recent studies endorse the need for innovative approaches to monitor the presence, abundance, and types of plastic in these ecosystems. One approach gaining rapid traction is the use of multi- and hyperspectral cameras. However, most experiments using this [...]

Robust Probabilities of Detection and Quantification Uncertainty for Aerial Methane Detection: Examples for Three Airborne Technologies

Bradley Mark Conrad, David R Tyner, Matthew R Johnson

Published: 2022-06-17
Subjects: Atmospheric Sciences, Climate, Environmental Monitoring, Mechanical Engineering, Oil, Gas, and Energy, Statistical Methodology, Statistical Models

Thorough characterization of probabilities of detection (POD) and quantification uncertainties is fundamentally important to understand the place of aerial measurement technologies in alternative means of emission limitation (AMEL) or alternate fugitive emissions management programs (Alt-FEMP); monitoring, reporting, and verification (MRV) efforts; and surveys designed to support [...]

Reducing the Uncertainty of Multi-Well Petrophysical Interpretation from Well Logs via Machine-Learning and Statistical Models

Wen Pan, Carlos Torres-Verdín, Ian J Duncan, et al.

Published: 2022-03-22
Subjects: Analysis, Earth Sciences, Engineering, Geophysics and Seismology, Mining Engineering, Multivariate Analysis, Statistical Methodology, Statistical Models

Well-log interpretation provides in situ estimates of formation properties such as porosity, hydrocarbon pore volume, and permeability. Reservoir models based on well-log-derived formation properties deliver reserve-volume estimates, production forecasts, and help with decision making in reservoir development. However, due to measurement errors, variability of well logs due to multiple [...]

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 have increased in frequency and severity over the past two decades, threatening to undo substantial air quality improvements. We investigate the effect of wildfire smoke exposure on learning outcomes across the US using standardized test scores from 2009-2016 for nearly 11,700 school districts and satellite-derived estimates of daily smoke exposure. Relative to a school year with no [...]

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: 2021-10-27
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: 2021-10-12
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 [...]

Interpretable Models Capture the Complex Relationship Between Climate Indices and Fire Season Intensity in Maritime Southeast Asia

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 or accelerate due to climate change. Fires, in turn, are a major driver of atmospheric carbon monoxide (CO) variability, especially in the Southern Hemisphere. Here we attempt to maximize the amount of CO variability that can be explained via [...]

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 [...]

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