Preprints

Filtering by Subject: Statistics and Probability

Bayesian analysis of ground motion models using chimney fragility curves: 2021, 5.9-Mw Woods Point intraplate earthquake, Victoria, Australia

James La Greca, Mark Quigley, Jaroslav Vaculik, et al.

Published: 2022-11-15
Subjects: Earth Sciences, Engineering, Physical Sciences and Mathematics, Probability, Statistics and Probability

The 22 September 2021 (AEST) Mw 5.9 Woods Point earthquake occurred in an intraplate setting (southeast Australia) approximately 130 km East Northeast of the central business district of Melbourne (pop. ∼5.15 million). A lack of seismic instrumentation and a low population density in the epicentral region resulted in a dearth of near-source instrumental and “felt” report intensity data, limiting [...]

Marine Radiocarbon Calibration in Polar Regions: A Simple Approximate Approach using Marine20

Timothy J Heaton, Martin Butzin, Edouard Bard, et al.

Published: 2022-09-22
Subjects: Earth Sciences, Environmental Sciences, Mathematics, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability

The Marine20 radiocarbon (14C) age calibration curve, and all earlier marine radiocarbon calibration curves from the IntCal group, must be used extremely cautiously for the calibration of marine 14C samples from polar regions (outside ~ 40ºS – 40ºN) during glacial periods. Calibrating polar 14C marine samples from glacial periods against any Marine calibration curve (Marine20 or any earlier [...]

Space-time landslide hazard modeling via Ensemble Neural Networks

Ashok Dahal, Hakan Tanyas, Cees J. van Westen, et al.

Published: 2022-06-02
Subjects: Applied Statistics, Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geomorphology, Physical Sciences and Mathematics, Statistics and Probability

For decades, a full numerical description of the spatio-temporal dynamics of a landslide could be achieved only via physics-based models. The part of the geomorphology community focusing on data-driven model has instead focused on predicting where landslides may occur via susceptibility models. Moreover, they have estimated when landslides may occur via models that belong to the [...]

Global dynamics of the offshore wind energy sector monitored with Sentinel-1: Turbine count, installed capacity and site specifications

Thorsten Hoeser, Claudia Kuenzer

Published: 2022-04-26
Subjects: Applied Statistics, Earth Sciences, Environmental Sciences, Natural Resource Economics, Natural Resources Management and Policy, Oil, Gas, and Energy, Other Earth Sciences, Statistics and Probability

With the promotion of renewable energy production and a planned phaseout of fossil fuels until 2040, the offshore wind energy sector has started to expand and will continue to increase its capacity in the upcoming decades. This study presents how the installed capacity can be derived from radar imagery provided by the Sentinel-1 mission for all offshore wind turbines on the entire Earth. By [...]

Multilevel multifidelity Monte Carlo methods for assessing coastal flood risk

Mariana C A Clare, Tim Leijnse, Robert McCall, et al.

Published: 2022-03-14
Subjects: Applied Mathematics, Earth Sciences, Hydrology, Risk Analysis, Statistical Methodology, Statistics and Probability

When choosing an appropriate hydrodynamic model, there is always a compromise between accuracy and computational cost, with high fidelity models being more expensive than low fidelity ones. However, when assessing uncertainty, we can use a multifidelity approach to take advantage of the accuracy of high fidelity models and the computational efficiency of low fidelity models. Here, we apply the [...]

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

Soner Uereyen, Felix Bachofer, Igor Klein, et al.

Published: 2022-03-11
Subjects: Earth Sciences, Environmental Sciences, Statistics and Probability

The Indo-Gangetic river basins feature a wide range of climatic, topographic, and land cover characteristics providing a suitable setting for the exploration of multivariate time series. Here, we collocated a comprehensive feature space for these river basins including Earth observation time series on the normalized difference vegetation index (NDVI), surface water area (SWA), and snow cover area [...]

Time-series analysis and statistical forecasting of daily rainfall in Kupang, East Nusa Tenggara, Indonesia: a pilot study

Sandy Hardian Susanto Herho, Gisma Aminurah Firdaus

Published: 2022-01-06
Subjects: Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability

This pilot study presents a novel statistical time-series approach for analyzing daily rainfall data in Kupang, East Nusa Tenggara, Indonesia. By using the piecewise cubic hermite interpolation algorithm, we succeeded in filling in the null values in the daily rainfall time series. We then analyzed the monthly average and its pattern using the continuous wavelet transform (CWT) algorithm, which [...]

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 [...]

Airborne laser scanning proxies of canopy light transmission in forests

Adam Michael Erickson, Nicholas Coops

Published: 2021-10-29
Subjects: Biodiversity, Biogeochemistry, Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences, Software Engineering, Statistics and Probability

Reliable estimates of canopy light transmission are critical to understanding the structure and function of vegetation communities but are difficult and costly to attain by traditional field inventory methods. Airborne laser scanning (ALS) data uniquely provide multi-angular vertically resolved representation of canopy geometry across large geographic areas. While previous studies have proposed [...]

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

Jacob 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 [...]

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