Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Stephen G Penny"'
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 15, Iss 12, Pp n/a-n/a (2023)
Abstract The immense computational cost of traditional numerical weather and climate models has sparked the development of machine learning (ML) based emulators. Because ML methods benefit from long records of training data, it is common to use data
Externí odkaz:
https://doaj.org/article/b2fb9489890245869709bb8a9be9e472
Autor:
Tse‐Chun Chen, Stephen G. Penny, Jeffrey S. Whitaker, Sergey Frolov, Robert Pincus, Stefan Tulich
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 14, Iss 11, Pp n/a-n/a (2022)
Abstract Weather forecasts made with imperfect models contain state‐dependent errors. Data assimilation (DA) partially corrects these errors with new information from observations. As such, the corrections, or “analysis increments,” produced by
Externí odkaz:
https://doaj.org/article/6c4951f0460442fbb48290097aebc45b
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 14, Iss 5, Pp n/a-n/a (2022)
Abstract The prediction of the weather at subseasonal‐to‐seasonal (S2S) timescales is dependent on both initial and boundary conditions. An open question is how to best initialize a relatively small‐sized ensemble of numerical model integration
Externí odkaz:
https://doaj.org/article/477cfeba548d40f18fecd46d75fc6cba
Autor:
Michael Goodliff, Stephen G. Penny
Publikováno v:
Monthly Weather Review. 150:2443-2458
Four-dimensional variational (4D-Var) data assimilation (DA) is developed for a coupled atmosphere–ocean quasigeostrophic application. Complications arise in coupled data assimilation (CDA) systems due to the presence of multiple spatiotemporal sca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f5e37c1be6dfb7aa0b2145a288701e9
https://doi.org/10.1175/mwr-d-21-0240.1
https://doi.org/10.1175/mwr-d-21-0240.1
Autor:
Aneesh C. Subramanian, Magdalena A. Balmaseda, Luca Centurioni, Rajib Chattopadhyay, Bruce D. Cornuelle, Charlotte DeMott, Maria Flatau, Yosuke Fujii, Donata Giglio, Sarah T. Gille, Thomas M. Hamill, Harry Hendon, Ibrahim Hoteit, Arun Kumar, Jae-Hak Lee, Andrew J. Lucas, Amala Mahadevan, Mio Matsueda, SungHyun Nam, Shastri Paturi, Stephen G. Penny, Adam Rydbeck, Rui Sun, Yuhei Takaya, Amit Tandon, Robert E. Todd, Frederic Vitart, Dongliang Yuan, Chidong Zhang
Publikováno v:
Frontiers in Marine Science, Vol 6 (2019)
Subseasonal-to-seasonal (S2S) forecasts have the potential to provide advance information about weather and climate events. The high heat capacity of water means that the subsurface ocean stores and re-releases heat (and other properties) and is an i
Externí odkaz:
https://doaj.org/article/d0ad05b7393147e59407b91fa874ef20
Autor:
Stephen G. Penny, Santha Akella, Magdalena A. Balmaseda, Philip Browne, James A. Carton, Matthieu Chevallier, Francois Counillon, Catia Domingues, Sergey Frolov, Patrick Heimbach, Patrick Hogan, Ibrahim Hoteit, Doroteaciro Iovino, Patrick Laloyaux, Matthew J. Martin, Simona Masina, Andrew M. Moore, Patricia de Rosnay, Dinand Schepers, Bernadette M. Sloyan, Andrea Storto, Aneesh Subramanian, SungHyun Nam, Frederic Vitart, Chunxue Yang, Yosuke Fujii, Hao Zuo, Terry O’Kane, Paul Sandery, Thomas Moore, Christopher C. Chapman
Publikováno v:
Frontiers in Marine Science, Vol 6 (2019)
Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new obs
Externí odkaz:
https://doaj.org/article/cb34729933f646bdbaeb727665fc81e1
Autor:
Andrea Storto, Aida Alvera-Azcárate, Magdalena A. Balmaseda, Alexander Barth, Matthieu Chevallier, Francois Counillon, Catia M. Domingues, Marie Drevillon, Yann Drillet, Gaël Forget, Gilles Garric, Keith Haines, Fabrice Hernandez, Doroteaciro Iovino, Laura C. Jackson, Jean-Michel Lellouche, Simona Masina, Michael Mayer, Peter R. Oke, Stephen G. Penny, K. Andrew Peterson, Chunxue Yang, Hao Zuo
Publikováno v:
Frontiers in Marine Science, Vol 6 (2019)
Ocean reanalyses combine ocean models, atmospheric forcing fluxes, and observations using data assimilation to give a four-dimensional description of the ocean. Metrics assessing their reliability have improved over time, allowing reanalyses to becom
Externí odkaz:
https://doaj.org/article/7ba72897fffa4ceb8f2bd96fb434ddcd
Autor:
Baylor Fox-Kemper, Alistair Adcroft, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Gokhan Danabasoglu, Carsten Eden, Matthew H. England, Rüdiger Gerdes, Richard J. Greatbatch, Stephen M. Griffies, Robert W. Hallberg, Emmanuel Hanert, Patrick Heimbach, Helene T. Hewitt, Christopher N. Hill, Yoshiki Komuro, Sonya Legg, Julien Le Sommer, Simona Masina, Simon J. Marsland, Stephen G. Penny, Fangli Qiao, Todd D. Ringler, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Stephen G. Yeager
Publikováno v:
Frontiers in Marine Science, Vol 6 (2019)
We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, param
Externí odkaz:
https://doaj.org/article/d911a83bd727495e9eacb3d3b6f71fce
Publikováno v:
Monthly Weather Review.
This study extends initial work by Sun and Penny et al. (2019, 2022) to explore the inclusion of path information from surface drifters using an augmented-state Lagrangian Data Assimilation based on the Local Ensemble Transform Kalman Filter (LETKF-L
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fbba84d9a45d43737737d0f1b74df25
https://doi.org/10.1175/mwr-d-22-0202.1
https://doi.org/10.1175/mwr-d-22-0202.1
Publikováno v:
Monthly Weather Review. 150:949-965
Satellite-tracked in situ surface drifters, providing measurements of near-surface ocean quantities, have become increasingly prevalent in the global ocean observation system. However, the position data from these instruments are typically not levera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a4ba523035b3d1c0ee8c50f605c4e5d
https://doi.org/10.1175/mwr-d-21-0123.1
https://doi.org/10.1175/mwr-d-21-0123.1