Laboratory Benchmarks for the Development of Numerical Ocean Models

2002 ◽  
Author(s):  
Don L. Boyer ◽  
Harindra J. Fernando ◽  
Andjelka N. Srdic ◽  
Dale B. Haidvogel
Keyword(s):  
2005 ◽  
Author(s):  
Roger M. Samelson ◽  
John S. Allen ◽  
Gary D. Egbert ◽  
John C. Kindle ◽  
Chris Snyder

2011 ◽  
Author(s):  
Shuyi S. Chen ◽  
Mark A. Donelan ◽  
Ashwanth Srinivasan ◽  
Rick Allard ◽  
Tim Campbell ◽  
...  

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Prasad G. Thoppil ◽  
Sergey Frolov ◽  
Clark D. Rowley ◽  
Carolyn A. Reynolds ◽  
Gregg A. Jacobs ◽  
...  

AbstractMesoscale eddies dominate energetics of the ocean, modify mass, heat and freshwater transport and primary production in the upper ocean. However, the forecast skill horizon for ocean mesoscales in current operational models is shorter than 10 days: eddy-resolving ocean models, with horizontal resolution finer than 10 km in mid-latitudes, represent mesoscale dynamics, but mesoscale initial conditions are hard to constrain with available observations. Here we analyze a suite of ocean model simulations at high (1/25°) and lower (1/12.5°) resolution and compare with an ensemble of lower-resolution simulations. We show that the ensemble forecast significantly extends the predictability of the ocean mesoscales to between 20 and 40 days. We find that the lack of predictive skill in data assimilative deterministic ocean models is due to high uncertainty in the initial location and forecast of mesoscale features. Ensemble simulations account for this uncertainty and filter-out unconstrained scales. We suggest that advancements in ensemble analysis and forecasting should complement the current focus on high-resolution modeling of the ocean.


2006 ◽  
Vol 23 (12) ◽  
pp. 1709-1728 ◽  
Author(s):  
David R. Jackett ◽  
Trevor J. McDougall ◽  
Rainer Feistel ◽  
Daniel G. Wright ◽  
Stephen M. Griffies

Abstract Algorithms are presented for density, potential temperature, conservative temperature, and the freezing temperature of seawater. The algorithms for potential temperature and density (in terms of potential temperature) are updates to routines recently published by McDougall et al., while the algorithms involving conservative temperature and the freezing temperatures of seawater are new. The McDougall et al. algorithms were based on the thermodynamic potential of Feistel and Hagen; the algorithms in this study are all based on the “new extended Gibbs thermodynamic potential of seawater” of Feistel. The algorithm for the computation of density in terms of salinity, pressure, and conservative temperature produces errors in density and in the corresponding thermal expansion coefficient of the same order as errors for the density equation using potential temperature, both being twice as accurate as the International Equation of State when compared with Feistel’s new equation of state. An inverse function relating potential temperature to conservative temperature is also provided. The difference between practical salinity and absolute salinity is discussed, and it is shown that the present practice of essentially ignoring the difference between these two different salinities is unlikely to cause significant errors in ocean models.


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