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Preprints

There are 6976 Preprints listed.

Macroscopic flow disequilibrium over aeolian dune fields

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

Published: 2020-05-08
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 [...]

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 [...]

A Reduced Order Approach for Probabilistic Inversions of 3D Magnetotelluric Data I: General Formulation

Maria Constanza Manassero, Juan Carlos Afonso, Fabio Zyserman, et al.

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

Simulation-based probabilistic inversions of 3D magnetotelluric (MT) data are arguably the best option to deal with the non-linearity and non-uniqueness of the MT problem. However, the computational cost associated with the modeling of 3D MT data has so far precluded the community from adopting and/or pursuing full probabilistic inversions of large MT datasets. In this contribution, we present a [...]

Addressing Model Data Archiving Needs for the Department of Energy’s Environmental Systems Science Community

Maegen Simmonds, William J. Riley, Shreyas Cholia, et al.

Published: 2020-05-08
Subjects: Computer Sciences, Environmental Sciences, Environmental Studies, Physical Sciences and Mathematics, Social and Behavioral Sciences

Researchers in the Department of Energy’s ESS program use a variety of models to advance robust, scale-aware predictions of terrestrial and subsurface ecosystems. ESS projects typically conduct field observations and experiments coupled with modeling exercises using a model-experimental (ModEx) approach that enables iterative co-development of experiments and models, and ensures that experimental [...]

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 [...]

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: 2020-05-08
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 [...]

Lower air pollution during COVID-19 lock-down: improving models and methods estimating ozone impacts on crops (accepted 01.07.2020)

Frank Dentener, Lisa Emberson, stefano galmarini, et al.

Published: 2020-05-07
Subjects: Agriculture, Agronomy and Crop Sciences Life Sciences, Environmental Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences

We suggest that the unprecedented and unintended decrease of emissions of air pollutants during the COVID-19 lockdown in 2020 could lead to declining seasonal ozone concentrations, and positive impacts on crop yields. An initial assessment of the potential effects of COVID-19 emission reductions was made using a set of six scenarios that variously assumed annual European and global emission [...]

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, [...]

Estimating Submicron Aerosol Mixing State at the Global Scale with Machine Learning and Earth System Modeling

Zhonghua Zheng, Jeffrey H. Curtis, Yu Yao, et al.

Published: 2020-05-07
Subjects: Atmospheric Sciences, Civil and Environmental Engineering, Computational Engineering, Computer Sciences, Earth Sciences, Engineering, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

This study integrates machine learning and particle-resolved aerosol simulations to develop emulators that predict sub-micron aerosol mixing state indices from the Earth System Model (ESM) simulations. The emulators predict aerosol mixing state using only ESM bulk aerosol species concentrations, which do not by themselves carry mixing state information. Here we used PartMC as the [...]

EC-Earth Global Climate Simulations: Ireland’s Contributions to CMIP6

Paul Nolan

Published: 2020-05-07
Subjects: Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

The global climate simulations described in this report constitute Ireland’s contribution to the Coupled Model Intercomparison Project (CMIP) (phase 6) (CMIP6) and will be included for assessment in the United Nations Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Since 1995, CMIP has co-ordinated climate model experiments involving multiple international [...]

Constraining crustal silica on ancient Earth

C. Brenhin Keller, T. Mark Harrison

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

Accurately quantifying the composition of continental crust on Hadean and Archean Earth is critical to our understanding of the physiography, tectonics, and climate of our planet at the dawn of life. One longstanding paradigm involves the growth of a relatively mafic planetary crust over the first 1-2 billion years of Earth history, implying a lack of modern plate tectonics, a paucity of [...]

Do olivine crystallization temperatures faithfully record mantle temperature variability?

Simon Matthews, Kevin Wong, Oliver Shorttle, et al.

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

Crystallization temperatures of primitive olivine crystals have been widely used as both a proxy for, or an intermediate step in calculating, mantle temperatures. The olivine-spinel aluminum-exchange thermometer has been applied to samples from mid-ocean ridges and large igneous provinces, yielding considerable variability in olivine crystallization temperatures. We supplement the existing data [...]

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: 2020-05-08
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 [...]

Projections of global delta land loss from sea-level rise in the 21st century

Jaap H. Nienhuis

Published: 2020-05-06
Subjects: Earth Sciences, Geomorphology, Hydrology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Sedimentology

River deltas will likely experience significant land loss because of relative sea-level rise (RSLR), but predictions have not been tested against observations. Here, we use global data of RSLR and river sediment supply to build a model of delta response to RSLR for 6,402 deltas, representing 86% of global delta land. We validate this model against delta land area change observations from [...]

Early earthquake detection capabilities of different types of future-generation gravity gradiometers

Tomofumi Shimoda, Kévin Juhel, Jean Paul Ampuero, et al.

Published: 2020-05-06
Subjects: Earth Sciences, Geophysics and Seismology, Physical Sciences and Mathematics

Since gravity propagates at the speed of light, gravity perturbations induced by earthquake deformation have the potential to enable faster alerts than the current earthquake early warning systems based on seismic waves. Additionally, for large earthquakes (Mw > 8), gravity signals may allow for a more reliable magnitude estimation than seismic-based methods. Prompt elastogravity signals [...]

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