Related papers: Assimilating data into an {\alpha}{\omega} dynamo …
The accuracy of simulation-based forecasting in chaotic systems is heavily dependent on high-quality estimates of the system state at the time the forecast is initialized. Data assimilation methods are used to infer these initial conditions…
We address data assimilation for linear and nonlinear dynamical systems via the so-called \emph{model reference adaptive system}. Continuing our theoretical developments in \cite{Tram_Kaltenbacher_2021}, we deliver the first practical…
This study demonstrates how the incremental 4D-Var data assimilation method can be applied efficiently preconditione d in an application to an oceanographic problem. The approach consists in performing a few iterations of the reduced-order…
The strength and morphology of the Sun's magnetic field evolves significantly during the solar cycle, with the overall polarity of the Sun's magnetic field reversing during the maximum of solar activity. Long-term changes are also observed…
We report the results of a magneto-hydrodynamic (MHD) simulation of a convective dynamo in a model solar convective envelope driven by the solar radiative diffusive heat flux. The convective dynamo produces a large-scale mean magnetic field…
We discuss recent advances made in modelling the complex magnetohydrodynamics of the Sun using our anelastic spherical harmonics (ASH) code. We have conducted extensive 3--D simulations of compressible convection in rotating spherical…
Data assimilation (DA) aims to estimate the full state of a dynamical system by combining partial and noisy observations with a prior model forecast, commonly referred to as the background. In atmospheric applications, this problem is…
Aims. We aim to infer the sub-surface distribution of the Sun's non-axisymmetric azimuthal magnetic flux from observable quantities, such as the surface magnetic field and the large scale plasma flows. Methods. We have built a kinematic…
We assess the global-scale dynamo action achieved in a simulation of a sun-like star rotating at three times the solar rate. The 3-D MHD Anelastic Spherical Harmonic code, using slope-limited diffusion, is employed to capture convection and…
Observations reveal a relatively small but statistically significant North-South (NS) asymmetry in sunspot activity varying on a time scale of several solar cycles. This paper proposes a dynamo model for the phenomenon of long-term NS…
Data assimilation (DA) is widely used to combine physical knowledge and observations. It is nowadays commonly used in geosciences to perform parametric calibration. In a context of climate change, old calibrations can not necessarily be…
We quantify possible differences between turbulent dynamo action in the Sun and the dynamo action studied in idealized simulations. For this purpose we compare Fourier-space shell-to-shell energy transfer rates of three incrementally more…
We describe, test, and apply a technique to incorporate full-sun, surface flux evolution into an MHD model of the global solar corona. Requiring only maps of the evolving surface flux, our method is similar to that of Lionello et al.…
Variational data assimilation technique applied to identification of optimal approximations of derivatives near boundary is discussed in frames of one-dimensional wave equation. Simplicity of the equation and of its numerical scheme allows…
We want to study the connections between the magnetic field generated inside the Sun and the solar wind impacting Earth, especially the influence of north-south asymmetry on the magnetic and velocity fields. We study a solar-like 11-year…
We study prediction-assimilation systems, which have become routine in meteorology and oceanography and are rapidly spreading to other areas of the geosciences and of continuum physics. The long-term, nonlinear stability of such a system…
The level of solar magnetic activity, as exemplified by the number of sunspots and by energetic events in the corona, varies on a wide range of time scales. Most prominent is the 11-year solar cycle, which is significantly modulated on…
Data assimilation is an iterative approach to the problem of estimating the state of a dynamical system using both current and past observations of the system together with a model for the system's time evolution. Rather than solving the…
A two-layer spherical $\alpha^2$-dynamo model consisting of an inner electrically conducting core (magnetic diffusivity $\lambda_i$ and radius $r_i$) with $\alpha = 0$ surrounded by an electrically conducting spherical shell (magnetic…
In this study, we analyzed a continuous data assimilation scheme applied on a double-diffusive natural convection model. The algorithm is introduced with a first order backward Euler time scheme along with a finite element discretization in…