Related papers: Bayesian Inference and Global Sensitivity Analysis…
Solar activity affects the whole heliosphere and near-Earth space environment. It has been reported in the literature that the mechanism responsible for the solar activity modulation behaves like a low-dimensional chaotic system. Studying…
We apply nested-sampling (NS) Bayesian analysis [AshtonEA22] to a model for the transport of MHD-scale solar wind fluctuations. The dual objectives are to obtain improved constraints on parameters present in the turbulence transport model…
Uncertainty in estimation of Drake Passage transport is analyzed in a Hessian-based uncertainty quantification (UQ) framework. The approach extends the adjoint-based ocean state estimation method to provide formal error bounds…
The lower solar atmosphere is an intrinsically multi-component and collisional environment with electron and proton collision frequencies in the range $10^{8}-10^{10}$ Hz, which may be considerably higher than the gyro-frequencies for both…
Empirical solar wind speed models play an important role in enabling space weather forecasting with low computational cost. Among these, one model called WS model is based on the asymptotic expansion factor. However, it is known that it…
Here we aim to separate the two main contributions of slow and fast solar wind that appear at 1 AU. The Bi-Gaussian function is proposed as the probability distribution function of the two main components of the solar wind. The positions of…
A model of geocoronal solar wind charge exchange (SWCX) emission was built and compared to five Suzaku detections of bright geocoronal SWCX events. An exospheric neutral hydrogen distribution model, charge exchange cross sections, solar…
The Solar and Heliospheric Observatory (SOHO) was launched in December 1995 with a suite of instruments designed to answer long-standing questions about the Sun's internal structure, its extensive outer atmosphere, and the solar wind. This…
The solar wind (SW) is an outflow of the solar coronal plasma, expanding supersonically throughout the heliosphere. SW particles interact by charge exchange with interstellar neutral atoms and on one hand, they modify the distribution of…
The solar corona and young solar wind may be characterized by critical surfaces -- the sonic, Alfv\'en, and first plasma-$\beta$ unity surfaces -- that demarcate regions where the solar wind flow undergoes certain crucial transformations.…
The long-term variations in the orbit of the Earth govern the insolation on its surface and hence its climate. The use of the astronomical signal, whose imprint has been recovered in the geological records, has revolutionized the…
Near-surface extreme winds profoundly affect human society, yet process-based understanding of their changes under climate forcings remains limited. This study systematically investigates the responses of high (HWE) and low (LWE) wind…
In recent years, probabilistic forecasts techniques were proposed in research as well as in applications to integrate volatile renewable energy resources into the electrical grid. These techniques allow decision makers to take the…
Uncertainty quantification (UQ) is crucial in machine learning, yet most (axiomatic) studies of uncertainty measures focus on classification, leaving a gap in regression settings with limited formal justification and evaluations. In this…
The growth of wind generation capacities in the past decades has shown that wind energy can contribute to the energy transition in many parts of the world. Being highly variable and complex to model, the quantification of the…
As a tool for capturing irregular temporal dependencies (rather than resorting to binning temporal observations to construct time series), Hawkes processes with exponential decay have seen widespread adoption across many application…
Neural networks (NNs) are increasingly used for data-driven subgrid-scale parameterization in weather and climate models. While NNs are powerful tools for learning complex nonlinear relationships from data, there are several challenges in…
The ability to replicate predictions by machine learning (ML) or artificial intelligence (AI) models and results in scientific workflows that incorporate such ML/AI predictions is driven by numerous factors. An uncertainty-aware metric that…
We have evolved 10,000 solar models using 21 input parameters that are randomly drawn for each model from separate probability distributions for every parameter. We use the results of these models to determine the theoretical uncertainties…
The Solar Wind Around Pluto (SWAP) instrument on NASA's New Horizon Pluto mission has collected solar wind observations en route from Earth to Pluto, and these observations continue beyond Pluto. Few missions have explored the solar wind in…