Synthesis of Ocean Observations Using Data Assimilation for Operational, Real-Time and Reanalysis Systems: A More Complete Picture of the State of the Ocean

被引：72

作者：

Moore, Andrew M. ^{[1
]}

Martini, Matthew J. ^{[2
]}

Akella, Santha ^{[3
]}

Arango, Hernan G. ^{[4
]}

Balmaseda, Magdalena ^{[5
]}

Bertino, Laurent ^{[6
]}

Ciavatta, Stefano ^{[7
]}

Cornuelle, Bruce ^{[8
]}

Cummings, Jim ^{[9
]}

Frolov, Sergey ^{[10
]}

Lermusiaux, Pierre ^{[11
]}

Oddo, Paolo ^{[12
]}

Oke, Peter R. ^{[13
]}

Storto, Andrea ^{[12
]}

Teruzzi, Anna ^{[14
]}

Vidard, Arthur ^{[15
]}

Weaver, Anthony T. ^{[16
]}

机构：

[1] Univ Calif Santa Cruz, Dept Ocean Sci, Santa Cruz, CA 95064 USA

[2] Met Off, Exeter, Devon, England

[3] NASA, Goddard Space Flight Ctr, Greenbelt, MD USA

[4] Rutgers State Univ, Dept Marine & Coastal Sci, New Brunswick, NJ USA

[5] European Ctr Medium Range Weather Forecasts, Reading, Berks, England

[6] Nansen Environm & Remote Sensing Ctr, Bergen, Norway

[7] Natl Ctr Earth Observat, Plymouth Marine Lab, Plymouth, Devon, England

[8] Univ Calif San Diego, Scripps Inst Oceanog, San Diego, CA 92103 USA

[9] NOAA, IMSG, NCEP, College Pk, MD USA

[10] Naval Res Lab, Monterey, CA USA

[11] MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA

[12] Ctr Maritime Res & Expt, La Spezia, Italy

[13] CSIRO, Hobart, Tas, Australia

[14] Ist Nazl Oceanog & Geofis Sperimentale, Trieste, Italy

[15] Univ Grenoble Alpes, Inria, Grenoble, France

[16] Ctr Europeen Rech & Format Avancee Calcul Sci, Toulouse, France

来源：

FRONTIERS IN MARINE SCIENCE | 2019年 / 6卷

关键词：

data assimilation; calculus of variations; Kalman filters; ensembles; modeling; HYBRID; SCHEME; IMPLEMENTATION; IMPACT; FILTER; ERROR; MODEL; BIAS;

D O I：

10.3389/fmars.2019.00090

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Ocean data assimilation is increasingly recognized as crucial for the accuracy of real-time ocean prediction systems and historical re-analyses. The current status of ocean data assimilation in support of the operational demands of analysis, forecasting and reanalysis is reviewed, focusing on methods currently adopted in operational and real-time prediction systems. Significant challenges associated with the most commonly employed approaches are identified and discussed. Overarching issues faced by ocean data assimilation are also addressed, and important future directions in response to scientific advances, evolving and forthcoming ocean observing systems and the needs of stakeholders and downstream applications are discussed.

引用

页数：6

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