Zobrazeno 1 - 10
of 159
pro vyhledávání: '"Morzfeld, Matthias"'
The ensemble Kalman filter (EnKF) is a reliable data assimilation tool for high-dimensional meteorological problems. On the other hand, the EnKF can be interpreted as a particle filter, and particle filters (PF) collapse in high-dimensional problems.
Externí odkaz:
http://hdl.handle.net/10150/623125
http://arizona.openrepository.com/arizona/handle/10150/623125
http://arizona.openrepository.com/arizona/handle/10150/623125
Low-dimensional models for Earth's magnetic dipole may be a powerful tool for studying large-scale dipole dynamics over geological time scales, where direct numerical simulation remains challenging. We investigate the utility of several low-dimension
Externí odkaz:
http://hdl.handle.net/10150/623037
http://arizona.openrepository.com/arizona/handle/10150/623037
http://arizona.openrepository.com/arizona/handle/10150/623037
Recently there has been a surge in interest in coupling ensemble-based data assimilation methods with variational methods (commonly referred to as 4DVar). Here we discuss a number of important differences between ensemble-based and variational method
Externí odkaz:
http://hdl.handle.net/10150/621807
http://arizona.openrepository.com/arizona/handle/10150/621807
http://arizona.openrepository.com/arizona/handle/10150/621807
Autor:
Webber, Robert J., Morzfeld, Matthias
A major problem in numerical weather prediction (NWP) is the estimation of high-dimensional covariance matrices from a small number of samples. Maximum likelihood estimators cannot provide reliable estimates when the overall dimension is much larger
Externí odkaz:
http://arxiv.org/abs/2301.04828
Autor:
Vishny, David1 (AUTHOR), Morzfeld, Matthias1 (AUTHOR) matti@ucsd.edu, Gwirtz, Kyle2 (AUTHOR), Bach, Eviatar3,4 (AUTHOR), Dunbar, Oliver R. A.3 (AUTHOR), Hodyss, Daniel5 (AUTHOR)
Publikováno v:
Journal of Advances in Modeling Earth Systems. Sep2024, Vol. 16 Issue 9, p1-30. 30p.
Autor:
Tong, Xin T., Morzfeld, Matthias
Ensemble Kalman inversion (EKI) is a technique for the numerical solution of inverse problems. A great advantage of the EKI's ensemble approach is that derivatives are not required in its implementation. But theoretically speaking, EKI's ensemble siz
Externí odkaz:
http://arxiv.org/abs/2201.10821
We study predictions of reversals of Earth's axial magnetic dipole field that are based solely on the dipole's intensity. The prediction strategy is, roughly, that once the dipole intensity drops below a threshold, then the field will continue to dec
Externí odkaz:
http://arxiv.org/abs/2012.12426
First-principles Markov Chain Monte Carlo sampling is used to investigate uncertainty quantification and uncertainty propagation in parameters describing hydrogen kinetics. Specifically, we sample the posterior distribution of thirty-one parameters f
Externí odkaz:
http://arxiv.org/abs/1803.03500
Autor:
Hodyss, Daniel1 (AUTHOR) daniel.hodyss@nrl.navy.mil, Morzfeld, Matthias2 (AUTHOR)
Publikováno v:
Monthly Weather Review. Sep2023, Vol. 151 Issue 9, p2413-2426. 14p. 4 Graphs.
We investigate how ideas from covariance localization in numerical weather prediction can be used in Markov chain Monte Carlo (MCMC) sampling of high-dimensional posterior distributions arising in Bayesian inverse problems. To localize an inverse pro
Externí odkaz:
http://arxiv.org/abs/1710.07747