Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Polly J. Smith"'
Autor:
Sanita Vetra-Carvalho, Sarah L. Dance, David C. Mason, Joanne A. Waller, Elizabeth S. Cooper, Polly J. Smith, Jemima M. Tabeart
Publikováno v:
Data in Brief, Vol 33, Iss , Pp 106338- (2020)
We present a new water level dataset extracted from images taken by four Farson Digital Ltd river cameras for a Tewkesbury, UK flood event (21st November – 5th December 2012). This data article presents the new water level data together with a desc
Externí odkaz:
https://doaj.org/article/fd454d9fa06543269ed16b1d459d0fe2
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 67, Iss 0, Pp 1-25 (2015)
Operational forecasting centres are currently developing data assimilation systems for coupled atmosphere–ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technic
Externí odkaz:
https://doaj.org/article/8e56ef4c81e645639da4ee7b6c1d3a8e
Publikováno v:
Quarterly Journal of the Royal Meteorological Society. 146:2450-2465
Strongly coupled atmosphere-ocean data assimilation offers the ability to improve information exchange across the modelled air-sea interface by enabling observations in one domain to have a direct influence on the analysis in the other. For increment
In variational data assimilation, background-error covariance structures have the ability to spread information from an observed part of the system to unobserved parts. Hence an accurate specification of these structures is crucially important for th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f655426d101b7b00a06fa2ff24651ab5
https://doi.org/10.5194/egusphere-egu21-3170
https://doi.org/10.5194/egusphere-egu21-3170
Autor:
Polly J. Smith, Elizabeth Cooper, Joanne A. Waller, Sarah L. Dance, Sanita Vetra-Carvalho, Jemima M. Tabeart, David C. Mason
Publikováno v:
Data in Brief
Data in Brief, Vol 33, Iss, Pp 106338-(2020)
Data in Brief, Vol 33, Iss, Pp 106338-(2020)
We present a new water level dataset extracted from images taken by four Farson Digital Ltd river cameras for a Tewkesbury, UK flood event (21st November – 5th December 2012). This data article presents the new water level data together with a desc
Publikováno v:
Environmental Modelling & Software. 104:199-214
Accurate inundation forecasting provides vital information about the behaviour of fluvial flood water. Using data assimilation with an Ensemble Transform Kalman Filter we combine forecasts from a numerical hydrodynamic model with synthetic observatio
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 67, Iss 0, Pp 1-25 (2015)
Tellus A; Vol 67 (2015)
Tellus A; Vol 67 (2015)
Operational forecasting centres are currently developing data assimilation systems for coupled atmosphere–ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technic
This Brief provides a quantitative and qualitative analysis of proactive strategies for management transitions in criminal justice and other public administration civic service agencies. These organizations have a unique need for managing transitions
Publikováno v:
SpringerBriefs in Criminology ISBN: 9783319278438
Command Transitions in Public Administration
Command Transitions in Public Administration
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1e460dd5db11b507b765cb578905f08
https://doi.org/10.1007/978-3-319-27844-5
https://doi.org/10.1007/978-3-319-27844-5
Publikováno v:
Command Transitions in Public Administration ISBN: 9783319278438
Effective transitions of power are essential to the smooth operation of any public administration organization, in particular a criminal justice agency. Prior research has shown generalized discussion surrounding agency succession planning. Transitio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::115d43e53e12ddc5d69d41ca6f86a23f
https://doi.org/10.1007/978-3-319-27844-5_1
https://doi.org/10.1007/978-3-319-27844-5_1