Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Pavel Sakov"'
Autor:
Pavel Sakov, Marc Bocquet
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 70, Iss 1, Pp 1-7 (2018)
The term ‘asynchronous data assimilation’ (ADA) refers to modifications of sequential data assimilation methods that take into consideration the observation time. In Sakov et al. [Tellus A, 62, 24–29 (2010)], a simple rule has been formulated f
Externí odkaz:
https://doaj.org/article/0f7e81e6051e4771b9ff44c1f86d5b6e
Autor:
Paul A. Sandery, Pavel Sakov
Publikováno v:
Nature Communications, Vol 8, Iss 1, Pp 1-8 (2017)
The degree to which increasing the resolution of ocean models to consider submesoscale dynamics will improve prediction of mesoscale features remains uncertain. Here, via data assimilation experiments, the authors show higher resolution models do not
Externí odkaz:
https://doaj.org/article/4f2cc084adc54af0bc8dcc9820cb9c4a
Autor:
Pavel Sakov, Paul Sandery
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 69, Iss 1 (2017)
We describe a simple adaptive quality control procedure that limits the impact of individual observations likely to be inconsistent with the state of the data assimilation system. It smoothly increases the observation error variance depending on the
Externí odkaz:
https://doaj.org/article/5cc0d3e755e14abaa0b83b8cef329cb0
Autor:
James S. Risbey, Terence J. O’Kane, Bernadette M. Sloyan, Thomas S. Moore, Paul A. Sandery, Matthew A. Chamberlain, Mark Collier, Christopher C. Chapman, Dylan Harries, Russell Fiedler, Carly R. Tozer, Pavel Sakov, Serena Schroeter, Courtney Quinn, Richard J. Matear, Amanda S. Black, Benjamin J. E. Schroeter, Doug Richardson, Vassili Kitsios, Ian Watterson, Dougal T. Squire
Publikováno v:
Journal of Climate. :1-62
The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large (96 member) ensemble retrospective analysis of the global climate system from 1960 to present with sufficiently many realizations and at spat
Publikováno v:
Monthly Weather Review. 148:2411-2431
Data assimilation (DA) experiments are performed to assess impacts of observations in climate model state estimation through the cross-domain ocean–atmosphere forecast error covariances (cross covariances). Specifically, we explore strongly and wea
Publikováno v:
SIAM/ASA Journal on Uncertainty Quantification
SIAM/ASA Journal on Uncertainty Quantification, ASA, American Statistical Association, 2020, 8 (1), pp.198-228. ⟨10.1137/19M1244147⟩
SIAM/ASA Journal on Uncertainty Quantification, ASA, American Statistical Association, 2020, 8 (1), pp.198-228. ⟨10.1137/19M1244147⟩
International audience; Ensemble variational methods are being increasingly used in the field of geophysical data assimilation. Their efficiency comes from the combined use of ensembles, which provide statistics estimates, and a variational analysis,
Autor:
Didier Monselesan, Dougal T. Squire, Mark Collier, Richard J. Matear, Pavel Sakov, Matthew A. Chamberlain, Lauren Stevens, Terence J. O’Kane, Paul A. Sandery
Publikováno v:
Journal of Climate. 32:997-1024
We develop and compare variants of coupled data assimilation (DA) systems based on ensemble optimal interpolation (EnOI) and ensemble transform Kalman filter (ETKF) methods. The assimilation system is first tested on a small paradigm model of the cou