Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Stefano Migliorini"'
Publikováno v:
Quarterly Journal of the Royal Meteorological Society.
Data assimilation theory relies on the assumption that the background, model, and observations are unbiased. However, this is often not the case and, if biases are left uncorrected, this can cause significant systematic errors in the analysis. When b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17400a2bae1226e360b5a010670da1d8
https://doi.org/10.5194/egusphere-egu23-7719
https://doi.org/10.5194/egusphere-egu23-7719
Autor:
Fabien Carminati, Stefano Migliorini
Publikováno v:
Advances in Atmospheric Sciences. 38:1682-1694
Microwave radiances from passive polar-orbiting radiometers have been, until recently, assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scattering are discarded. Recent sy
Autor:
Brett Candy, Stefano Migliorini
Publikováno v:
Quarterly Journal of the Royal Meteorological Society. 147:3049-3066
Autor:
Heather Lawrence, Fabien Carminati, Bruce Ingleby, Andrew Smith, Stefano Migliorini, James Hocking, William Bell, Stuart M. Newman
Publikováno v:
Atmospheric Measurement Techniques, Vol 12, Pp 83-106 (2019)
The characterisation of errors and uncertainties in numerical weather prediction (NWP) model fields is a major challenge that is addressed as part of the Horizon 2020 Gap Analysis for Integrated Atmospheric ECV CLImate Monitoring (GAIA-CLIM) project.
Autor:
Brett Candy, Stefano Migliorini
Publikováno v:
Quarterly Journal of the Royal Meteorological Society. 145:867-883
Operational data assimilation (DA) schemes rely significantly on satellite observations with much research aimed at their optimisation, leading to a great deal of progress. Here, we investigate the impact of the spatial-temporal variability of satell
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fe173954e9c939d96a92e117aca500d
https://doi.org/10.5194/egusphere-egu2020-332
https://doi.org/10.5194/egusphere-egu2020-332
Autor:
Kozo Okamoto, Min-Jeong Kim, William Bell, Emily Liu, Yanqiu Zhu, Stefano Migliorini, Alan J. Geer, Peter Weston, Christina Köpken‐Watts, Katrin Lonitz, Andrew Collard, Christoph Schraff, Philippe Chambon, Masahiro Kazumori, Nadia Fourrié
Publikováno v:
Quarterly Journal of the Royal Meteorological Society. 144:1191-1217
This article reviews developments towards assimilating cloud and precipitation-affected satellite radiances at operational forecasting centres. Satellite data assimilation is moving beyond the ‘clear-sky’ approach that discards any observations a
Publikováno v:
Quarterly Journal of the Royal Meteorological Society. 144:443-457
Autor:
Stefano Migliorini, Amos S. Lawless, F. B. Smith, Nancy Nichols, Jemima M. Tabeart, Joanne A. Waller, Sarah L. Dance
Recent developments in numerical weather prediction have led to the use of correlated observation error covariance (OEC) information in data assimilation and forecasting systems. However, diagnosed OEC matrices are often ill-conditioned and may cause
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3bb5ad7e4fee391ef721965f28e3d442
http://arxiv.org/abs/1908.04071
http://arxiv.org/abs/1908.04071