Modeling and forecasting the "weather of the ocean" at the mesoscale

被引:5
|
作者
Treguier, Anne Marie [1 ]
Chassignet, Eric P. [2 ,3 ]
Le Boyer, Arnaud [4 ]
Pinardi, Nadia [5 ]
机构
[1] IUEM, CNRS Ifremer IRD UBO, LOPS, CNRS, Rue Dumont dUrville, Plouzane, France
[2] Florida State Univ, COAPS, Tallahassee, FL 32306 USA
[3] Florida State Univ, Dept Earth Ocean & Atmospher Sci EOAS, Tallahassee, FL 32306 USA
[4] Univ Calif San Diego, Scripps Inst Oceanog, Marine Phys Lab, La Jolla, CA 92093 USA
[5] Univ Bologna, Dept Phys & Astron, Bologna, Italy
关键词
Numerical model; ocean forecast; ocean mesoscale turbulence; PRIMITIVE EQUATION MODEL; NORTH-ATLANTIC; GLOBAL OCEAN; BAROCLINIC INSTABILITY; SATELLITE ALTIMETRY; NUMERICAL-SIMULATION; KINETIC-ENERGY; GEOSTROPHIC TURBULENCE; EQUATORIAL ATLANTIC; GENERAL-CIRCULATION;
D O I
10.1357/002224017821836842
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
We present a historical perspective on ocean mesoscale variability and turbulence, from the physical basis and the first numerical models to recent simulations and forecasts. In the mesoscale range (typically, spatial scales of 100 km and time scales of a month), nonlinearity, and energy cascades were well understood in the 1970s, but the emergence of coherent vortices took place much later. New challenges have arisen with the exploration of the submesoscale regime, where frontal dynamics play a key role and the range of flow instabilities is wider than in the quasi-geostrophic regime. Special focus is placed on the interaction of mesoscale turbulence with the continental slopes. The contrast between the variability on the western and eastern boundaries of an ocean basin is illustrated by numerical simulations of the North Atlantic. On the eastern continental slope, direct forcing of currents by wind fluctuations is more important than it is on the western side of the basin, where forcing by intrinsic mesoscale variability is dominant. Dynamical characteristics of the ocean mesoscale such as these must be taken into account in building forecasting systems. These systems require improved numerical models to represent mesoscale variability with more fidelity. We present our view of the most pressing needs for model development as they relate to the challenges of data assimilation at the mesoscale.
引用
收藏
页码:301 / 329
页数:29
相关论文
共 50 条
  • [41] Ocean forecasting of mesoscale features can deteriorate by increasing model resolution towards the submesoscale
    Paul A. Sandery
    Pavel Sakov
    [J]. Nature Communications, 8
  • [42] MESOSCALE FORECASTING EXPERIMENTS
    HERING, WS
    BROWN, HA
    MUENCH, HS
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 1972, 53 (12) : 1180 - 1183
  • [43] REPORT ON THE SYMPOSIUM ON NOWCASTING II MESOSCALE OBSERVATIONS AND VERY-SHORT-RANGE WEATHER FORECASTING
    KLUGE, J
    [J]. ZEITSCHRIFT FUR METEOROLOGIE, 1985, 35 (05): : 297 - 299
  • [44] Ocean forecasting of mesoscale features can deteriorate by increasing model resolution towards the submesoscale
    Sandery, Paul A.
    Sakov, Pavel
    [J]. NATURE COMMUNICATIONS, 2017, 8
  • [45] Applications of simulated GOES-R observations for advanced product development for mesoscale weather forecasting
    Grasso, L
    Sengupta, M
    DeMaria, M
    [J]. WEATHER AND ENVIRONMENTAL SATELLITES, 2004, 5549 : 114 - 122
  • [46] Modeling of neural networks for weather forecasting in debre markos, Ethiopia
    Meheretie, Daniel Limenew
    Ji, Bing
    Mogadem, Mazin Mohammed
    Tamir, Tariku Sinshaw
    [J]. JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS, 2021, 44 (08) : 762 - 769
  • [47] Black-box modeling for temperature prediction in weather forecasting
    Karevan, Zahra
    Mehrkanoon, Siamak
    Suykens, Johan A. K.
    [J]. 2015 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2015,
  • [48] Weather forecasting for weather derivatives
    Campbell, SD
    Diebold, FX
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2005, 100 (469) : 6 - 16
  • [49] Modeling and Forecasting CAT and HDD Indices for Weather Derivative Pricing
    Zapranis, Achilleas
    Alexandridis, Antonis
    [J]. ENGINEERING APPLICATIONS OF NEURAL NETWORKS, PROCEEDINGS, 2009, 43 : 210 - 222
  • [50] Mesoscale Modeling of Extreme Coastal Weather against Sodar Data - a Case Study
    Barantiev, Damyan
    Kirova, Hristina
    Gueorguiev, Orlin
    Batchvarova, Ekaterina
    [J]. 10TH JUBILEE CONFERENCE OF THE BALKAN PHYSICAL UNION, 2019, 2075