Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Sam Hatfield"'
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 14, Iss 2, Pp n/a-n/a (2022)
Abstract Most Earth‐system simulations run on conventional central processing units in 64‐bit double precision floating‐point numbers Float64, although the need for high‐precision calculations in the presence of large uncertainties has been q
Externí odkaz:
https://doaj.org/article/30045fc5c9624844aa230109548cad1e
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 13, Iss 9, Pp n/a-n/a (2021)
Abstract We assess the ability of neural network emulators of physical parametrization schemes in numerical weather prediction models to aid in the construction of linearized models required by four‐dimensional variational (4D‐Var) data assimilat
Externí odkaz:
https://doaj.org/article/541ee394ec4045ef8f348f8ed98f6e2e
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 13, Iss 7, Pp n/a-n/a (2021)
Abstract We assess the value of machine learning as an accelerator for the parameterization schemes of operational weather forecasting systems, specifically the parameterization of nonorographic gravity wave drag. Emulators of this scheme can be trai
Externí odkaz:
https://doaj.org/article/b1af4566ff9648f8a6f5330b50b4a3aa
Autor:
Nils P. Wedi, Inna Polichtchouk, Peter Dueben, Valentine G. Anantharaj, Peter Bauer, Souhail Boussetta, Philip Browne, Willem Deconinck, Wayne Gaudin, Ioan Hadade, Sam Hatfield, Olivier Iffrig, Philippe Lopez, Pedro Maciel, Andreas Mueller, Sami Saarinen, Irina Sandu, Tiago Quintino, Frederic Vitart
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 12, Iss 11, Pp n/a-n/a (2020)
Abstract In an attempt to advance the understanding of the Earth's weather and climate by representing deep convection explicitly, we present a global, four‐month simulation (November 2018 to February 2019) with ECMWF's hydrostatic Integrated Forec
Externí odkaz:
https://doaj.org/article/f713c6fae3d14af5a5e0af351839fea7
Most Earth-system simulations run on conventional CPUs in 64-bit double precision floating-point numbers Float64, although the need for high-precision calculations in the presence of large uncertai...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69d6911b9f69cd94c26c9be5fb8b62ef
https://doi.org/10.1002/essoar.10507472.2
https://doi.org/10.1002/essoar.10507472.2
Earth-System models traditionally use double-precision, 64 bit floating-point numbers to perform arithmetic. According to orthodoxy, we must use such a relatively high level of precision in order to minimise the potential impact of rounding errors on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1779191f1a31daf02f22d663d202efb
https://doi.org/10.5194/egusphere-egu21-733
https://doi.org/10.5194/egusphere-egu21-733
Publikováno v:
Quarterly Journal of the Royal Meteorological Society
Reducing numerical precision can save computational costs which can then be reinvested for more useful purposes. This study considers the effects of reducing precision in the parametrizations of an intermediate complexity atmospheric model (SPEEDY).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c2105589bbb88c7bdffd860251fb212
https://ora.ox.ac.uk/objects/uuid:ba025581-34a2-413a-902a-5df5a512dd76
https://ora.ox.ac.uk/objects/uuid:ba025581-34a2-413a-902a-5df5a512dd76
Publikováno v:
PASC
The next generation of weather and climate models will have an unprecedented level of resolution and model complexity, and running these models efficiently will require taking advantage of future supercomputers and heterogeneous hardware. In this pap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87e4b4ace8026826a5d152cd8427e3dd
https://doi.org/10.1145/3324989.3325711
https://doi.org/10.1145/3324989.3325711
Publikováno v:
Journal of Advances in Modeling Earth Systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::ba724139168b68bc7edd56ced2d0426a
Publikováno v:
Monthly Weather Review
A new approach for improving the accuracy of data assimilation, by trading numerical precision for ensemble size, is introduced. Data assimilation is inherently uncertain because of the use of noisy observations and imperfect models. Thus, the larger
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52187ec421fc5087562bca7c24d33a99