Jemima M. Tabeart
Title
Cited by
Cited by
Year
The conditioning of least‐squares problems in variational data assimilation
JM Tabeart, SL Dance, SA Haben, AS Lawless, NK Nichols, JA Waller
Numerical Linear Algebra with Applications 25 (5), e2165, 2018
162018
Improving the condition number of estimated covariance matrices
JM Tabeart, SL Dance, AS Lawless, NK Nichols, JA Waller
Tellus A: Dynamic Meteorology and Oceanography 72 (1), 1-19, 2020
72020
The impact of using reconditioned correlated observation‐error covariance matrices in the Met Office 1D‐Var system
JM Tabeart, SL Dance, AS Lawless, S Migliorini, NK Nichols, F Smith, ...
Quarterly Journal of the Royal Meteorological Society 146 (728), 1372-1390, 2020
32020
Collection and extraction of water level information from a digital river camera image dataset
S Vetra-Carvalho, SL Dance, DC Mason, JA Waller, ES Cooper, PJ Smith, ...
Data in Brief 33, 106338, 2020
22020
High temperature measurement of elastic moduli of (0001) gallium nitride
ML Hicks, J Tabeart, MJ Edwards, ED Le Boulbar, DWE Allsopp, ...
Integrated Ferroelectrics 133 (1), 17-24, 2012
22012
On the treatment of correlated observation errors in data assimilation
JM Tabeart
University of Reading, 2019
12019
The conditioning of least squares problems in preconditioned variational data assimilation
JM Tabeart, SL Dance, AS Lawless, NK Nichols, JA Waller
arXiv preprint arXiv:2010.08416, 2020
2020
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