語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
到查詢結果
[ subject:"Stochastic Analysis." ]
切換:
標籤
|
MARC模式
|
ISBD
Stochastic transport in upper ocean ...
~
STUOD (Workshop) ((2021 :)
FindBook
Google Book
Amazon
博客來
Stochastic transport in upper ocean dynamics = STUOD 2021 Workshop, London, UK, September 20-23 /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Stochastic transport in upper ocean dynamics/ edited by Bertrand Chapron ... [et al.].
其他題名:
STUOD 2021 Workshop, London, UK, September 20-23 /
其他題名:
STUOD 2021
其他作者:
Chapron, Bertrand.
團體作者:
STUOD (Workshop)
出版者:
Cham :Springer International Publishing : : 2023.,
面頁冊數:
xvi, 317 p. :ill. (some col.), digital ;24 cm.
內容註:
Blow-up of strong solutions of the Thermal Quasi-Geostrophic equation (R. Mensah) -- Modeling under location uncertainty: a convergent large-scale representation of the Navier-Stokes equations -- (E. Mémin) -- A stochastic Benjamin-Bona-Mahony type equation (E. Dinvay) -- Observation-based noise calibration: an efficient dynamics for the Ensemble Kalman filter (B. Dufée) -- A two-step numerical scheme in time for surface quasi geostrophic equations under location uncertainty (C. Fiorini) -- The Dissipation Properties of Transport Noise (F. Flandoli) -- Existence and Uniqueness of Maximal Solutions to a 3D Navier-Stokes Equation with Stochastic Lie Transport (D. Goodair) -- Ponderomotive coupling of waves to sea surface currents via horizontal density gradients (R. Hu) -- Variational Stochastic Parameterisations and their Applications to Primitive Equation Models (S. Patching) -- A pathwise parameterisation for stochastic transport (O. Lang) -- Stochastic parameterization with dynamic mode decomposition (L. Li) -- Deep Learning for the Benes Filter (A. Lobbe) End-to-End Kalman Filter in a High Dimensional Linear Embedding of the Observations (S. Ouala) -- Dynamical Properties of Weather Regime Transitions (P. Platzer) -- Frequentist perspective on robust parameter estimation using the ensemble Kalman filter (S. Reich) -- Random ocean swell-rays: a stochastic framework (V. Resseguier) -- Modified (hyper-)viscosity for coarse-resolution ocean models (L. Thiry) -- Boussinesq equations under location uncertainty: theoretical description and models development (L. Li) -- Bridging Koopman Operator and time-series auto-correlation based Hilbert-Schmidt operator (Y. Zhen)
Contained By:
Springer Nature eBook
標題:
Oceanography - Congresses. -
電子資源:
https://doi.org/10.1007/978-3-031-18988-3
ISBN:
9783031189883
Stochastic transport in upper ocean dynamics = STUOD 2021 Workshop, London, UK, September 20-23 /
Stochastic transport in upper ocean dynamics
STUOD 2021 Workshop, London, UK, September 20-23 /[electronic resource] :STUOD 2021edited by Bertrand Chapron ... [et al.]. - Cham :Springer International Publishing :2023. - xvi, 317 p. :ill. (some col.), digital ;24 cm. - Mathematics of planet earth,v. 102524-4272 ;. - Mathematics of planet earth ;v. 10..
Blow-up of strong solutions of the Thermal Quasi-Geostrophic equation (R. Mensah) -- Modeling under location uncertainty: a convergent large-scale representation of the Navier-Stokes equations -- (E. Mémin) -- A stochastic Benjamin-Bona-Mahony type equation (E. Dinvay) -- Observation-based noise calibration: an efficient dynamics for the Ensemble Kalman filter (B. Dufée) -- A two-step numerical scheme in time for surface quasi geostrophic equations under location uncertainty (C. Fiorini) -- The Dissipation Properties of Transport Noise (F. Flandoli) -- Existence and Uniqueness of Maximal Solutions to a 3D Navier-Stokes Equation with Stochastic Lie Transport (D. Goodair) -- Ponderomotive coupling of waves to sea surface currents via horizontal density gradients (R. Hu) -- Variational Stochastic Parameterisations and their Applications to Primitive Equation Models (S. Patching) -- A pathwise parameterisation for stochastic transport (O. Lang) -- Stochastic parameterization with dynamic mode decomposition (L. Li) -- Deep Learning for the Benes Filter (A. Lobbe) End-to-End Kalman Filter in a High Dimensional Linear Embedding of the Observations (S. Ouala) -- Dynamical Properties of Weather Regime Transitions (P. Platzer) -- Frequentist perspective on robust parameter estimation using the ensemble Kalman filter (S. Reich) -- Random ocean swell-rays: a stochastic framework (V. Resseguier) -- Modified (hyper-)viscosity for coarse-resolution ocean models (L. Thiry) -- Boussinesq equations under location uncertainty: theoretical description and models development (L. Li) -- Bridging Koopman Operator and time-series auto-correlation based Hilbert-Schmidt operator (Y. Zhen)
Open access.
This open access proceedings volume brings selected, peer-reviewed contributions presented at the Stochastic Transport in Upper Ocean Dynamics (STUOD) 2021 Workshop, held virtually and in person at the Imperial College London, UK, September 20-23, 2021. The STUOD project is supported by an ERC Synergy Grant, and led by Imperial College London, the National Institute for Research in Computer Science and Automatic Control (INRIA) and the French Research Institute for Exploitation of the Sea (IFREMER) The project aims to deliver new capabilities for assessing variability and uncertainty in upper ocean dynamics. It will provide decision makers a means of quantifying the effects of local patterns of sea level rise, heat uptake, carbon storage and change of oxygen content and pH in the ocean. Its multimodal monitoring will enhance the scientific understanding of marine debris transport, tracking of oil spills and accumulation of plastic in the sea. All topics of these proceedings are essential to the scientific foundations of oceanography which has a vital role in climate science. Studies convened in this volume focus on a range of fundamental areas, including: Observations at a high resolution of upper ocean properties such as temperature, salinity, topography, wind, waves and velocity; Large scale numerical simulations; Data-based stochastic equations for upper ocean dynamics that quantify simulation error; Stochastic data assimilation to reduce uncertainty. These fundamental subjects in modern science and technology are urgently required in order to meet the challenges of climate change faced today by human society. This proceedings volume represents a lasting legacy of crucial scientific expertise to help meet this ongoing challenge, for the benefit of academics and professionals in pure and applied mathematics, computational science, data analysis, data assimilation and oceanography.
ISBN: 9783031189883
Standard No.: 10.1007/978-3-031-18988-3doiSubjects--Topical Terms:
555928
Oceanography
--Congresses.
LC Class. No.: GC11.2 / .S78 2021
Dewey Class. No.: 551.46
Stochastic transport in upper ocean dynamics = STUOD 2021 Workshop, London, UK, September 20-23 /
LDR
:04788nmm a2200361 a 4500
001
2315053
003
DE-He213
005
20221213140718.0
006
m d
007
cr nn 008mamaa
008
230902s2023 sz s 0 eng d
020
$a
9783031189883
$q
(electronic bk.)
020
$a
9783031189876
$q
(paper)
024
7
$a
10.1007/978-3-031-18988-3
$2
doi
035
$a
978-3-031-18988-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
GC11.2
$b
.S78 2021
072
7
$a
PBW
$2
bicssc
072
7
$a
MAT003000
$2
bisacsh
072
7
$a
PBW
$2
thema
082
0 4
$a
551.46
$2
23
090
$a
GC11.2
$b
.S934 2021
111
2
$a
STUOD (Workshop)
$d
(2021 :
$c
London, England ; Online)
$3
3627130
245
1 0
$a
Stochastic transport in upper ocean dynamics
$h
[electronic resource] :
$b
STUOD 2021 Workshop, London, UK, September 20-23 /
$c
edited by Bertrand Chapron ... [et al.].
246
3
$a
STUOD 2021
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2023.
300
$a
xvi, 317 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Mathematics of planet earth,
$x
2524-4272 ;
$v
v. 10
505
0
$a
Blow-up of strong solutions of the Thermal Quasi-Geostrophic equation (R. Mensah) -- Modeling under location uncertainty: a convergent large-scale representation of the Navier-Stokes equations -- (E. Mémin) -- A stochastic Benjamin-Bona-Mahony type equation (E. Dinvay) -- Observation-based noise calibration: an efficient dynamics for the Ensemble Kalman filter (B. Dufée) -- A two-step numerical scheme in time for surface quasi geostrophic equations under location uncertainty (C. Fiorini) -- The Dissipation Properties of Transport Noise (F. Flandoli) -- Existence and Uniqueness of Maximal Solutions to a 3D Navier-Stokes Equation with Stochastic Lie Transport (D. Goodair) -- Ponderomotive coupling of waves to sea surface currents via horizontal density gradients (R. Hu) -- Variational Stochastic Parameterisations and their Applications to Primitive Equation Models (S. Patching) -- A pathwise parameterisation for stochastic transport (O. Lang) -- Stochastic parameterization with dynamic mode decomposition (L. Li) -- Deep Learning for the Benes Filter (A. Lobbe) End-to-End Kalman Filter in a High Dimensional Linear Embedding of the Observations (S. Ouala) -- Dynamical Properties of Weather Regime Transitions (P. Platzer) -- Frequentist perspective on robust parameter estimation using the ensemble Kalman filter (S. Reich) -- Random ocean swell-rays: a stochastic framework (V. Resseguier) -- Modified (hyper-)viscosity for coarse-resolution ocean models (L. Thiry) -- Boussinesq equations under location uncertainty: theoretical description and models development (L. Li) -- Bridging Koopman Operator and time-series auto-correlation based Hilbert-Schmidt operator (Y. Zhen)
506
$a
Open access.
520
$a
This open access proceedings volume brings selected, peer-reviewed contributions presented at the Stochastic Transport in Upper Ocean Dynamics (STUOD) 2021 Workshop, held virtually and in person at the Imperial College London, UK, September 20-23, 2021. The STUOD project is supported by an ERC Synergy Grant, and led by Imperial College London, the National Institute for Research in Computer Science and Automatic Control (INRIA) and the French Research Institute for Exploitation of the Sea (IFREMER) The project aims to deliver new capabilities for assessing variability and uncertainty in upper ocean dynamics. It will provide decision makers a means of quantifying the effects of local patterns of sea level rise, heat uptake, carbon storage and change of oxygen content and pH in the ocean. Its multimodal monitoring will enhance the scientific understanding of marine debris transport, tracking of oil spills and accumulation of plastic in the sea. All topics of these proceedings are essential to the scientific foundations of oceanography which has a vital role in climate science. Studies convened in this volume focus on a range of fundamental areas, including: Observations at a high resolution of upper ocean properties such as temperature, salinity, topography, wind, waves and velocity; Large scale numerical simulations; Data-based stochastic equations for upper ocean dynamics that quantify simulation error; Stochastic data assimilation to reduce uncertainty. These fundamental subjects in modern science and technology are urgently required in order to meet the challenges of climate change faced today by human society. This proceedings volume represents a lasting legacy of crucial scientific expertise to help meet this ongoing challenge, for the benefit of academics and professionals in pure and applied mathematics, computational science, data analysis, data assimilation and oceanography.
650
0
$a
Oceanography
$x
Congresses.
$3
555928
650
1 4
$a
Mathematics of Planet Earth.
$3
3236712
650
2 4
$a
Stochastic Analysis.
$3
3599427
650
2 4
$a
Stochastic Modelling.
$3
3538808
650
2 4
$a
Differential Equations.
$3
907890
650
2 4
$a
Applied Dynamical Systems.
$3
3538870
700
1
$a
Chapron, Bertrand.
$3
3627131
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
830
0
$a
Mathematics of planet earth ;
$v
v. 10.
$3
3627132
856
4 0
$u
https://doi.org/10.1007/978-3-031-18988-3
950
$a
Mathematics and Statistics (SpringerNature-11649)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9451303
電子資源
11.線上閱覽_V
電子書
EB GC11.2 .S78 2021
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入