Preprints
Filtering by Subject: Physical Sciences and Mathematics
A machine learning approach for ozone forecasting and its application for Kennewick, WA
Published: 2020-05-13
Subjects: Atmospheric Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
Chemical transport models (CTM) are widely used for air quality modeling, but these models miss forecasting some air pollution events, and require a lot of computational power. In Kennewick, WA, elevated O3 episodes can occur during the summer and early fall, but the CTM-based operational forecasting system (AIRPACT) struggles to capture them. This research used the 2015 – 2018 historical [...]
What is the hydrologically effective size of a catchment?
Published: 2020-05-13
Subjects: Earth Sciences, Environmental Sciences, Hydrology, Physical Sciences and Mathematics, Water Resource Management
Linking human activities and climate change with their consequences for water availability is a prerequisite for sustainable water management, which is traditionally performed at topographically delineated catchments. However, inter-catchment groundwater flow results in effective catchment sizes other than sizes suggested by topography. Here, we introduce the notion of effective catchment size [...]
Detecting Ground Deformation in the Built Environment using Sparse Satellite InSAR data with a Convolutional Neural Network
Published: 2020-05-13
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
Published: 2020-05-13
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
Published: 2020-05-12
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
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
Published: 2020-05-11
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 [...]
Danger of groundwater contamination widely underestimated because of shortcuts for aquifer recharge
Published: 2020-05-11
Subjects: Environmental Health and Protection, Environmental Sciences, Physical Sciences and Mathematics, Sustainability, Water Resource Management
Groundwater pollution threatens human and ecosystem health in many areas around the globe. Shortcuts to the groundwater through concentrated recharge are known to transmit short-lived pollutants into carbonate aquifers endangering water quality of around a quarter of the world population. However, the large-scale impact of such concentrated recharge on water quality remains poorly understood. [...]
Asian monsoon amplifies semi-direct effect of biomass burning aerosols on low cloud formation
Published: 2020-05-11
Subjects: Atmospheric Sciences, Climate, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
Low clouds play a key role in the Earth-atmosphere energy balance and influence agricultural production and solar-power generation. Smoke aloft has been found to enhance marine stratocu-mulus over the Southeast Atlantic in austral spring through aerosol-cloud interactions, but its role in regions with strong human activities and complex monsoon circulation remains unclear. Here we show that [...]
Three Common Statistical Missteps We Make in Reservoir Characterization
Published: 2020-05-11
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
Published: 2020-05-08
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 [...]
Addressing Model Data Archiving Needs for the Department of Energy’s Environmental Systems Science Community
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 [...]
Macroscopic flow disequilibrium over aeolian dune fields
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 [...]
A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling
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 [...]
On doing large-scale hydrology with Lions: Realising the value of perceptual models and knowledge accumulation
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 [...]