Yvonne Ruckstuhl

Yvonne Ruckstuhl
Ludwig-Maximilians-University of Munich | LMU · Department of Physics

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11
Publications
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92
Citations

Publications

Publications (11)
Article
Full-text available
Machine learning represents a potential method to cope with the gray zone problem of representing motions in dynamical systems on scales comparable to the model resolution. Here we explore the possibility of using a neural network to directly learn the error caused by unresolved scales. We use a modified shallow water model which includes highly no...
Preprint
Full-text available
Machine learning represents a potential method to cope with the gray zone problem of representing motions in dynamical systems on scales comparable to the model resolution. Here we explore the possibility of using a neural network to directly learn the error caused by unresolved scales. We use a modified shallow water model which includes highly no...
Article
Full-text available
In previous work, it was shown that the preservation of physical properties in the data assimilation framework can significantly reduce forecast errors. Proposed data assimilation methods, such as the quadratic programming ensemble (QPEns) that can impose such constraints on the calculation of the analysis, are computationally more expensive, sever...
Article
Convective scale data assimilation uses high resolution numerical weather prediction models and temporally and spatially dense observations of relevant atmospheric variables. In addition, it requires a data assimilation algorithm that is able to provide initial conditions for a state vector of large size with one third or more of its components con...
Preprint
Full-text available
In previous work, it was shown that preservation of physical properties in the data assimilation framework can significantly reduce forecasting errors. Proposed data assimilation methods, such as the quadratic programming ensemble (QPEns) that can impose such constraints on the calculation of the analysis, are computationally more expensive, severe...
Article
State of the art ensemble prediction systems usually provide ensembles with only 20-250 members for estimating the uncertainty of the forecast and its spatial and spatiotemporal covariance. Given that the degrees of freedom of atmospheric models are several magnitudes higher, the estimates are therefore substantially affected by sampling errors. Fo...
Article
Full-text available
We investigate the feasibility of addressing model error by perturbing and estimating uncertain static model parameters using the localized ensemble transform Kalman filter. In particular we use the augmented state approach, where parameters are updated by observations via their correlation with observed state variables. This online approach offers...
Preprint
Full-text available
A specialized algorithm for quadratic optimization (QO, or, formerly, QP) with disjoint linear constraints is presented. In the considered class of problems, a subset of variables are subject to linear equality constraints, while variables in a different subset are constrained to remain in a convex set. The proposed algorithm exploits the structure...
Article
Full-text available
Representation of clouds in convection permitting models is sensitive to NWP model parameters that are often very crudely known (for example roughness length). Our goal is to allow for uncertainty in these parameters and estimate them from data using the ensemble Kalman filter (EnKF) approach. However, to deal with difficulties associated with conv...
Article
Full-text available
For the numerical discretization schemes, the violation of the enstrophy conservation causes a systematic and unrealistic energy cascade towards the high wave numbers. The same also holds for the data assimilation scheme where the total energy, enstrophy and divergence could be strongly affected by the data assimilation settings. The same occurs to...
Conference Paper
Full-text available
The applications of data assimilation on convective scales require a numerical model of the atmosphere with single digit horizontal resolution in km and time evolving error covariances. Past studies have shown that ensemble Kalman filter (EnKF) algorithm can be applied to the convective scales since it is capable of handling complex and highly nonl...

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