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Geostatistics in the Presence of Multivariate Complexities: Comparison of Multi-Gaussian Transforms
One of the most challenging aspects of multivariate geostatistics is dealing with complex relationships between variables. Geostatistical...
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A Wasserstein distance-based technique for the evaluation of GNSS error characterization
The characteristics of residual errors in GNSS positioning are crucial for fault detection and integrity monitoring. Despite the wide use of the...
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Geostatistical analysis of groundwater levels in a mining area with three active mines
Mining activities can significantly impact groundwater reservoirs in their vicinity. Different approaches have been employed, with varying success,...
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A comparison of nonlinear extensions to the ensemble Kalman filter
Ensemble Kalman filters are based on a Gaussian assumption, which can limit their performance in some non-Gaussian settings. This paper reviews two...
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Analysis of the Non-Gaussianity of the Sea Surface Temperature in the North Atlantic Based on Reanalysis Data
This paper examines the non-Gaussian properties of sea surface temperature anomalies (SSTA) variability in the North Atlantic using available for...
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Effect of Nozzle Parameters on the Cooling Conditions in the Secondary Cooling Zone of a Slab Caster
The following contribution focuses on the secondary cooling zone of a slab caster, analyzing the effects of nozzle parameters on cooling conditions....
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Reservoir porosity assessment and anomaly identification from seismic attributes using Gaussian process machine learning
Porosity, as one of the reservoir properties, is an important parameter to numerous studies, i.e., the reservoir’s oil/gas volume estimation or even...
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Conditioning geological surfaces to horizontal wells
Kriging is a standard method for conditioning surfaces to observations. Kriging works for vertical wells, but may produce surfaces that cross...
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An improved parameter filtering approach for processing GRACE gravity field models using first-order Gauss–Markov process
Removing stripe noise from the GRACE (Gravity Recovery and Climate Experiment) monthly gravity field model is crucial for accurately interpreting...
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Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation
AbstractA stochastic weather generator is proposed in the paper. The model is designed for the numerical simulation of joint time series of surface...
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gPCE Uncertainty Quantification Modeling of LiDAR for Bathymetric and Earth Science Applications
Most LiDARs, though precise, are vulnerable to position and pointing errors, and while fidelity of location/pointing solutions can be extremely high,...
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Assimilating Precipitation Features Based on the Fractions Skill Score: An Idealized Study with an Intermediate AGCM
Advanced observation techniques such as radars and satellites provide spatial patterns of precipitationPrecipitation areas on regional scales and...
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Efficient non-ergodic ground-motion prediction for large datasets
An efficient numerical method for non-ergodic ground-motion inference and prediction is proposed that alleviates the large computational and memory...
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Robust phase algorithms for estimating apparent slowness vectors of seismic waves from regional events
In this paper, we consider the problem of estimating the apparent slowness vector
p of a plane P wave caused by a regional seismic event and recorded... -
Vector Radiative Transfer in a Vertically Inhomogeneous Scattering and Emitting Atmosphere. Part I: A New Discrete Ordinate Method
The original vector discrete ordinate radiative transfer (VDISORT) model takes into account Stokes radiance vector but derives its solution assuming...
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Linear trends in temperature extremes in China, with an emphasis on non-Gaussian and serially dependent characteristics
Record-breaking hot and cold extremes have occurred in China in recent years and, therefore, it is compelling to investigate the long-term trend in...
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Hybrid soft computing models for predicting unconfined compressive strength of lime stabilized soil using strength property of virgin cohesive soil
This work introduces an optimal performance model for predicting the unconfined compressive strength (UCS) of lime-stabilized soil using the machine...
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Unbiased Proxy Calibration
The linear calibration model is a powerful statistical tool that can be utilized to predict an unknown response variable, Y , through observations of...
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Overview and introduction to development of non-ergodic earthquake ground-motion models
This paper provides an overview and introduction to the development of non-ergodic ground-motion models, GMMs. It is intended for a reader who is...
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Combination of Machine Learning and Kriging for Spatial Estimation of Geological Attributes
A growing number of studies in the spatial estimation of geological features use machine learning (ML) models, as these models promise to provide...
