Preprints

Filtering by Subject: Earth Sciences

Detecting Ground Deformation in the Built Environment using Sparse Satellite InSAR data with a Convolutional Neural Network

Nantheera Anantrasirichai, Juliet Biggs, Krisztina Kelevitz, et al.

Published: 2020-05-14
Subjects: Earth Sciences, Electrical and Computer Engineering, Engineering, Other Earth Sciences, Physical Sciences and Mathematics, Signal Processing

The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of non-expert stakeholders a challenge. Here we explore the applicability of deep learning approaches by [...]

Multi-task learning based P/S wave separation and reverse time migration for VSP

Yanwen Wei, Yunyue Elita Li, Jingjing Zong, et al.

Published: 2020-05-14
Subjects: Earth Sciences, Geophysics and Seismology, Physical Sciences and Mathematics

P/S wave mode separation is an essential tool for single-mode analysis from multi-component seismic data. Wave separation methods in recorded data require expert knowledge to choose parameters in different shots of data. To make this process automatic, we propose a machine learning-based method to separate P/S waves. This method employs a multi-task neural network that extracts P- and S-potential [...]

A Near-Real-Time Approach for Monitoring Forest Disturbance Using Landsat Time Series: Stochastic Continuous Change Detection

Su Ye, John Rogan, Zhe Zhu, et al.

Published: 2020-05-13
Subjects: Earth Sciences, Engineering, Other Earth Sciences, Physical Sciences and Mathematics

Forest disturbances greatly affect the ecological functioning of natural forests. Timely information regarding extent, timing and magnitude of forest disturbance events is crucial for effective disturbance management strategies. Yet, we still lack an acute, near-real-time and high-performance remote sensing tools for monitoring abrupt and subtle forest disturbances. This study presents a new [...]

Creating Geological Field Trips with the Google Earth Creation Tools

Christie Rowe, James Kirkpatrick, Kimberly Blisniuk, et al.

Published: 2020-05-12
Subjects: Earth Sciences, Education, Instructional Media Design, Physical Sciences and Mathematics

Streetcar2Subduction (https://www.agu.org/streetcar2subduction) was launched in December 2019 as a digital update and extension of the timeless 1984 classic field trip guide “Streetcar to Subduction” by Clyde Wahrhaftig . Supported by the American Geophysical Union, we were given early access to the Google Earth Creation Tools in order to build and launch several geology and tectonics field trips [...]

COVID-19-related drop in anthropogenic aerosol emissions in China and corresponding cloud and climate effects

Axel Timmermann, Sun-Seon Lee, Jung-Eun Chu, et al.

Published: 2020-05-12
Subjects: Atmospheric Sciences, Climate, Earth Sciences, Environmental Sciences, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

The COVID-19 pandemic has led to massive disruptions of public life on a global scale. To halt the spread of the disease, China temporarily shut down parts of the manufacturing and transportation sectors. Associated anthropogenic aerosol emissions in February 2020 plunged to record lows, causing a temporary improvement of air quality with uncertain effects on cloud formation, atmospheric [...]

Three Common Statistical Missteps We Make in Reservoir Characterization

Frank Male, Jerry L. Jensen

Published: 2020-05-12
Subjects: Chemical Engineering, Earth Sciences, Engineering, Geology, Petroleum Engineering, Physical Sciences and Mathematics, Statistical Methodology, Statistics and Probability

Reservoir characterization analysis resulting from incorrect applications of statistics can be found in the literature, particularly in applications where integration of various disciplines is needed. Here, we look at three misapplications of ordinary least squares linear regression (LSLR) and show how they can lead to poor results and offer better alternatives, where available. The issues are [...]

Construction of fault geometry by finite-fault inversion of teleseismic data

Kousuke Shimizu, Yuji Yagi, Ryo Okuwaki, et al.

Published: 2020-05-09
Subjects: Earth Sciences, Geophysics and Seismology, Physical Sciences and Mathematics

Conventional seismic source inversion estimates the earthquake rupture process on an assumed fault plane that is determined a priori. It has been a difficult challenge to obtain the fault geometry together with the rupture process by seismic source inversion because of the nonlinearity of the inversion technique. In this study, we propose an inversion method to estimate the fault geometry and the [...]

Macroscopic flow disequilibrium over aeolian dune fields

Andrew Gunn, Phillip Schmutz, Matt Wanker, et al.

Published: 2020-05-09
Subjects: Atmospheric Sciences, Earth Sciences, Geomorphology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Sedimentology

Aeolian dune fields are self-organized patterns formed by wind-blown sand. Dunes are topographic roughness elements that impose drag on the atmospheric boundary layer (ABL), creating a natural coupling between form and flow. While the steady-state influence of drag on the ABL is well studied, non-equilibrium effects due to roughness transitions are less understood. Here we examine the large-scale [...]

A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling

Frederik Kratzert, Daniel Klotz, Sepp Hochreiter, et al.

Published: 2020-05-09
Subjects: Earth Sciences, Hydrology, Physical Sciences and Mathematics

A deep learning rainfall-runoff model can take multiple meteorological forcing products as inputs and learn to combine them in spatially and temporally dynamic ways. This is demonstrated using Long Short Term Memory networks (LSTMs) trained over basins in the continental US using the CAMELS data set. Using multiple precipitation products (NLDAS, Maurer, DayMet) in a single LSTM significantly [...]

On doing large-scale hydrology with Lions: Realising the value of perceptual models and knowledge accumulation

Thorsten Wagener, Tom Gleeson, Gemma Coxon, et al.

Published: 2020-05-09
Subjects: Earth Sciences, Engineering, Environmental Sciences, Hydrology, Physical Sciences and Mathematics

Moving the study domain in hydrology to larger and larger regions leaves us with significant knowledge gaps because we are unable to observe the hydrology of many parts of the world, while in-depth hydrologic studies cover only a fraction of our landscape. On medieval maps, knowledge gaps were shown as images of lions. How do we best acknowledge and reduce these gaps in hydrology, i.e. our [...]

How waves are accelerating global coastal overtopping

Rafael Almar, Harold Diaz, Erwin W. J. Bergsma, et al.

Published: 2020-05-08
Subjects: Climate, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

The world’s coastal areas are home to about 10% of the human population and support unique and dynamic ecosystems, offering € trillions worth of environmental and societal benefits. Climate change and anthropogenic pressures are however exacerbating devastating hazards such as episodic coastal flooding, the magnitudes of which remain highly uncertain to date. This study, for the first time, [...]

Geomagnetic field variability: geomagnetic dynamo and helical distributed chaos

Alexander Bershadskii

Published: 2020-05-07
Subjects: Earth Sciences, Geophysics and Seismology, Physical Sciences and Mathematics

It is shown that helicity dynamics dominates the thermal convection-driven geomagnetic field variability. The notion of the distributed chaos has been used for this purpose. The large-scale circulation in the Earths outer (metallic liquid) core is especially sensitive to the helicity dynamics and its chaotic reversals can be associated with the reversals of the mean helicity sign (the ergodic [...]

Unmixing and mapping components of Northern Ireland’s geochemical composition using FastICA and random forests

Charlie Kirkwood, Mark Cooper, Antonio Ferreira, et al.

Published: 2020-05-07
Subjects: Earth Sciences, Geology, Physical Sciences and Mathematics

There is an increasing trend for the collection of multi-sensory quantitative data to support the mapping of geology and environment. In the United Kingdom and Ireland this trend has been led by the Tellus mapping programmes; large scale multidisciplinary surveys which have collected quantitative data by a combination of geophysical survey from the air and geochemical survey on the ground. Such [...]

Benchmarking and Inter-Comparison of Sentinel-1 InSAR velocities and time series

Zahra Sadeghi, Tim J. Wright, Andy Hooper, et al.

Published: 2020-05-07
Subjects: Earth Sciences, Other Earth Sciences, Physical Sciences and Mathematics

Different InSAR algorithms and methods produce velocities and times series that are not identical, even using the same data for the same area. This inconsistency can cause confusion and be a barrier to uptake and widespread use of the data in the commercial sector. With the widespread availability of Sentinel-1 radar data and a suite of new algorithms in the commercial and academic sectors, it is [...]

The timing of magmatism and subsequent alteration of basaltic rocks cored at the base of IODP Site U1513, Naturaliste Plateau, southwestern Australia

Lloyd White, Marnie Forster, Dominique Tanner, et al.

Published: 2020-05-07
Subjects: Earth Sciences, Geology, Physical Sciences and Mathematics

An 82.2 m thick sequence of basaltic rocks was recovered from a deep-sea core on the eastern flank of the Naturaliste Plateau, offshore southwestern Australia during International Ocean Discovery Program (IODP) Expedition 369. The basaltic rocks were cored at the base of IODP Site U1513 and represent the acoustic basement of the Mentelle Basin. The recovered materials consist of subaerial to [...]

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