scholarly journals Multistatistics metric evaluation of ocean general circulation model sea surface temperature: Application to 0.08° Pacific Hybrid Coordinate Ocean Model simulations

2008 ◽  
Vol 113 (C12) ◽  
Author(s):  
A. B. Kara ◽  
E. J. Metzger ◽  
H. E. Hurlburt ◽  
A. J. Wallcraft ◽  
E. P. Chassignet
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Ocean Model ◽  
Sea Surface ◽  
Model Simulations ◽  
Hybrid Coordinate Ocean Model ◽  
Temperature Application ◽  
Ocean General Circulation

scholarly journals Retrospective Forecasts of Interannual Sea Surface Temperature Anomalies from 1982 to Present Using a Directly Coupled Atmosphere–Ocean General Circulation Model

2005 ◽  
Vol 133 (10) ◽  
pp. 2972-2995 ◽  
Author(s):  
David G. DeWitt
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation Model ◽  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Sea Surface ◽  
Initial Condition ◽  
Ocean General Circulation

Abstract A large number of ensemble hindcasts (or retrospective forecasts) of tropical Pacific sea surface temperature (SST) have been made with a coupled atmosphere–ocean general circulation model (CGCM) that does not employ flux correction in order to evaluate the potential skill of the model as a seasonal forecasting tool. Oceanic initial conditions are provided by an ocean data assimilation system. Ensembles of seven forecasts of 6-month length are made starting each month in the 1982 to 2002 period. Skill of the coupled model is evaluated from both a deterministic and a probabilistic perspective. The skill metrics are calculated using both the bulk method, which includes all initial condition months together, and as a function of initial condition month. The latter method allows a more objective evaluation of how the model has performed in the context in which forecasts are actually made and applied. The deterministic metrics used are the anomaly correlation and the root-mean-square error. The coupled model deterministic skill metrics are compared with those from persistence and damped persistence reference forecasts. Despite the fact that the coupled model has a large cold bias in the central and eastern equatorial Pacific this coupled model is shown to have forecast skill that is competitive with other state-of-the-art forecasting techniques. Potential skill from probabilistic forecasts made using the coupled model ensemble members are evaluated using the relative operating characteristics method. This analysis indicates that for most initial condition months this coupled model has more skill at forecasting cold events than warm or neutral events in the central Pacific. In common with other forecasting systems, the coupled model forecast skill is found to be lowest for forecasts passing through the Northern Hemisphere (NH) spring. Diagnostics of this so-called spring predictability barrier in the context of this coupled model indicate that two factors likely contribute to this predictability barrier. First, the coupled model shows a too-weak coupling of the surface and subsurface temperature anomalies during NH spring. Second, the coupled-model-simulated signal-to-noise ratio for SST anomalies is much lower during NH spring than at other times of the year, indicating that the model’s potential predictability is low at this time.

scholarly journals FORTE 2.0: a fast, parallel and flexible coupled climate model

2021 ◽  
Vol 14 (1) ◽  
pp. 275-293
Author(s):  
Adam T. Blaker ◽  
Manoj Joshi ◽  
Bablu Sinha ◽  
David P. Stevens ◽  
Robin S. Smith ◽  
...  
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Ocean Model ◽  
Coupled Climate Model ◽  
Layer Depth ◽  
Ocean General Circulation ◽  
Modular Ocean Model

Abstract. FORTE 2.0 is an intermediate-resolution coupled atmosphere–ocean general circulation model (AOGCM) consisting of the Intermediate General Circulation Model 4 (IGCM4), a T42 spectral atmosphere with 35σ layers, coupled to Modular Ocean Model – Array (MOMA), a 2∘ × 2∘ ocean with 15 z-layer depth levels. Sea ice is represented by a simple flux barrier. Both the atmosphere and ocean components are coded in Fortran. It is capable of producing a stable climate for long integrations without the need for flux adjustments. One flexibility afforded by the IGCM4 atmosphere is the ability to configure the atmosphere with either 35σ layers (troposphere and stratosphere) or 20σ layers (troposphere only). This enables experimental designs for exploring the roles of the troposphere and stratosphere, and the faster integration of the 20σ layer configuration enables longer duration studies on modest hardware. A description of FORTE 2.0 is given, followed by the analysis of two 2000-year control integrations, one using the 35σ configuration of IGCM4 and one using the 20σ configuration.

scholarly journals The Finite Element Sea ice-Ocean Model (FESOM): formulation of an unstructured-mesh ocean general circulation model

2013 ◽  
Vol 6 (3) ◽  
pp. 3893-3976 ◽  
Author(s):  
Q. Wang ◽  
S. Danilov ◽  
D. Sidorenko ◽  
R. Timmermann ◽  
C. Wekerle ◽  
...  
Keyword(s):  
Finite Element ◽  
Sea Ice ◽  
General Circulation Model ◽  
General Circulation ◽  
Unstructured Mesh ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Ocean Model ◽  
Climate Modelling ◽  
Ocean General Circulation

Abstract. The Finite Element Sea ice-Ocean Model (FESOM) is the first global ocean general circulation model based on unstructured-mesh methods that has been developed for the purpose of climate research. The advantage of unstructured-mesh models is their flexible multi-resolution modelling functionality. In this study, an overview of the main features of FESOM will be given; based on sensitivity experiments a number of specific parameter choices will be explained; and directions of future developments will be outlined. It is argued that FESOM is sufficiently mature to explore the benefits of multi-resolution climate modelling and that it provides an excellent platform for further developments required to advance the field of climate modelling on unstructured meshes.

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