scholarly journals SKRIPS v1.0: a regional coupled ocean–atmosphere modeling framework (MITgcm–WRF) using ESMF/NUOPC, description and preliminary results for the Red Sea

2019 ◽  
Vol 12 (10) ◽  
pp. 4221-4244
Author(s):  
Rui Sun ◽  
Aneesh C. Subramanian ◽  
Arthur J. Miller ◽  
Matthew R. Mazloff ◽  
Ibrahim Hoteit ◽  
...  
Keyword(s):  
Red Sea ◽  
System Modeling ◽  
Coupled Model ◽  
Ocean Model ◽  
Test Case ◽  
Modeling Framework ◽  
Model Code ◽  
Ocean Atmosphere ◽  
Atmosphere Model ◽  
Heat Events

Abstract. A new regional coupled ocean–atmosphere model is developed and its implementation is presented in this paper. The coupled model is based on two open-source community model components: the MITgcm ocean model and the Weather Research and Forecasting (WRF) atmosphere model. The coupling between these components is performed using ESMF (Earth System Modeling Framework) and implemented according to National United Operational Prediction Capability (NUOPC) protocols. The coupled model is named the Scripps–KAUST Regional Integrated Prediction System (SKRIPS). SKRIPS is demonstrated with a real-world example by simulating a 30 d period including a series of extreme heat events occurring on the eastern shore of the Red Sea region in June 2012. The results obtained by using the coupled model, along with those in forced stand-alone oceanic or atmospheric simulations, are compared with observational data and reanalysis products. We show that the coupled model is capable of performing coupled ocean–atmosphere simulations, although all configurations of coupled and uncoupled models have good skill in modeling the heat events. In addition, a scalability test is performed to investigate the parallelization of the coupled model. The results indicate that the coupled model code scales well and the ESMF/NUOPC coupler accounts for less than 5 % of the total computational resources in the Red Sea test case. The coupled model and documentation are available at https://library.ucsd.edu/dc/collection/bb1847661c (last access: 26 September 2019), and the source code is maintained at https://github.com/iurnus/scripps_kaust_model (last access: 26 September 2019).

scholarly journals A regional coupled ocean–atmosphere modeling framework (MITgcm–WRF) using ESMF/NUOPC: description and preliminary results for the Red Sea

2018 ◽  
Author(s):  
Rui Sun ◽  
Aneesh Subramanian ◽  
Art Miller ◽  
Matt Mazloff ◽  
Ibrahim Hoteit ◽  
...  
Keyword(s):  
Red Sea ◽  
System Modeling ◽  
Coupled Model ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Modeling Framework ◽  
Coupled Models ◽  
Ocean Atmosphere ◽  
Atmosphere Model ◽  
Regional Coupled Model

Abstract. A new regional coupled ocean–atmosphere model is developed to study air–sea feedbacks. The coupled model is based on two open-source community model components: (1) MITgcm ocean model; (2) Weather Research and Forecasting (WRF) atmosphere model. The coupling between these components is performed using ESMF (Earth System Modeling Framework) and implemented according to National United Operational Prediction Capability (NUOPC) consortium. The regional coupled model allows affordable simulation where oceanic mixed layer heat and momentum interact with atmospheric boundary layer dynamics at mesoscale and higher resolution. This can capture the feedbacks which are otherwise not well-resolved in coarse resolution global coupled models and are absent in regional uncoupled models. To test the regional coupled model, we focus on a series of heat wave events that occurred on the eastern shore of the Red Sea region in June 2012 using a 30-day simulation. The results obtained using the coupled model, along with those in forced uncoupled ocean or atmosphere model simulations, are compared with observational and reanalysis data. All configurations of coupled and uncoupled models have good skill in modeling variables of interest in the region. The coupled model shows improved skill in temperature and circulation evaluation metrics. In addition, a scalability test is performed to investigate the parallelization of the coupled model. The results indicate that the coupled model scales linearly for up to 128 CPUs and sublinearly for more processors. In the coupled simulation, the ESMF/NUOPC interface also scales well and accounts for less than 10 % of the total computational resources compared with uncoupled models. Hence this newly developed regional model scales efficiently for a large number of processors and can be applied for high-resolution coupled regional modeling studies.

Air–Sea Interaction in the Ligurian Sea: Assessment of a Coupled Ocean–Atmosphere Model Using In Situ Data from LASIE07

2011 ◽  
Vol 139 (6) ◽  
pp. 1785-1808 ◽  
Author(s):  
R. J. Small ◽  
T. Campbell ◽  
J. Teixeira ◽  
S. Carniel ◽  
T. A. Smith ◽  
...  
Keyword(s):  
System Modeling ◽  
Coupled Model ◽  
Ocean Model ◽  
Heat Fluxes ◽  
Naval Research ◽  
Modeling Framework ◽  
Ligurian Sea ◽  
In Situ Data ◽  
Ocean Atmosphere

Abstract In situ experimental data and numerical model results are presented for the Ligurian Sea in the northwestern Mediterranean. The Ligurian Sea Air–Sea Interaction Experiment (LASIE07) and LIGURE2007 experiments took place in June 2007. The LASIE07 and LIGURE2007 data are used to validate the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)1 developed at the Naval Research Laboratory. This system includes an atmospheric sigma coordinate, nonhydrostatic model, coupled to a hydrostatic sigma-z-level ocean model (Navy Coastal Ocean Model), using the Earth System Modeling Framework (ESMF). A month-long simulation, which includes data assimilation in the atmosphere and full coupling, is compared against an uncoupled run where analysis SST is used for computation of the bulk fluxes. This reveals that COAMPS has reasonable skill in predicting the wind stress and surface heat fluxes at LASIE07 mooring locations in shallow and deep water. At the LASIE07 coastal site (but not at the deep site) the validation shows that the coupled model has a much smaller bias in latent heat flux, because of improvements in the SST field relative to the uncoupled model. This in turn leads to large differences in upper-ocean temperature between the coupled model and an uncoupled ocean model run.

A global coupled atmosphere-ocean model

1989 ◽  
Vol 329 (1604) ◽  
pp. 263-273 ◽  
Keyword(s):  
Water Flux ◽  
Coupled Model ◽  
Ocean Model ◽  
Global Ocean ◽  
Max Planck ◽  
Weather Forecasts ◽  
Medium Range ◽  
Climate Drift ◽  
The Mean ◽  
Atmosphere Model

A low-resolution version of the European Centre for Medium Range Weather Forecasts global atmosphere model has been coupled to a global ocean model developed at the Max Planck Institut in Hamburg. The atmosphere model is driven by the sea surface temperature and the ice thickness calculated by the ocean model, which, in turn, is driven by the wind stress, the heat flux and the fresh-water flux diagnosed by the atmosphere model. Even though each model reaches stationarity when integrated on its own, the coupling of both creates problems, because the fields calculated by each model are not consistent with those the other model has to have to stay stationary, as some of the fluxes are not balanced. In the coupled experiment the combined ocean-atmosphere system drifts towards a colder state. To counteract this problem a flux correction has been applied, which balances the mean biases of each model. This method makes the climate drift of the coupled model smaller, but additional work has to be done to perfect this method.

scholarly journals Can a Regional Ocean–Atmosphere Coupled Model Improve the Simulation of the Interannual Variability of the Western North Pacific Summer Monsoon?

2013 ◽  
Vol 26 (7) ◽  
pp. 2353-2367 ◽  
Author(s):  
Liwei Zou ◽  
Tianjun Zhou
Keyword(s):  
Interannual Variability ◽  
North Pacific ◽  
Western North Pacific ◽  
Coupled Model ◽  
The Philippines ◽  
Ocean Model ◽  
Land System ◽  
Anomalous Anticyclone ◽  
Ocean Atmosphere ◽  
Sst Anomalies

Abstract A flexible regional ocean–atmosphere–land system coupled model [Flexible Regional Ocean Atmosphere Land System (FROALS)] was developed through the Ocean Atmosphere Sea Ice Soil, version 3 (OASIS3), coupler to improve the simulation of the interannual variability of the western North Pacific summer monsoon (WNPSM). The regionally coupled model consists of a regional atmospheric model, the Regional Climate Model, version 3 (RegCM3), and a global climate ocean model, the National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG)/Institute of Atmospheric Physics (IAP) Climate Ocean Model (LICOM). The impacts of local air–sea interaction on the simulation of the interannual variability of the WNPSM are investigated through regionally ocean–atmosphere coupled and uncoupled simulations, with a focus on El Niño’s decaying summer. Compared with the uncoupled simulation, the regionally coupled simulation exhibits improvements in both the climatology and the interannual variability of rainfall over the WNP. In El Niño’s decaying summer, the WNP is dominated by an anomalous anticyclone, less rainfall, and enhanced subsidence, which lead to increases in the downward shortwave radiation flux, thereby warming sea surface temperature (SST) anomalies. Thus, the ocean appears as a slave to atmospheric forcing. In the uncoupled simulation, however, the atmosphere is a slave to oceanic SST forcing, with the warm SST anomalies located east of the Philippines unrealistically producing excessive rainfall. In the regionally coupled run, the unrealistic positive rainfall anomalies and the associated atmospheric circulations east of the Philippines are significantly improved, highlighting the importance of air–sea coupling in the simulation of the interannual variability of the WNPSM. One limitation of the model is that the anomalous anticyclone over the WNP is weaker than the observations in both the regionally coupled and the uncoupled simulations. This results from the weaker simulated climatological summer rainfall intensity over the monsoon trough.

Experiences with a coupled global model

1989 ◽  
Vol 329 (1604) ◽  
pp. 275-288 ◽  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Degrees Of Freedom ◽  
Coupled Model ◽  
General Circulation Models ◽  
Ocean Model ◽  
Atmosphere Model ◽  
Component Models ◽  
Ice Model ◽  
The Tropical Pacific

General circulation models of the atmosphere have been used to investigate the climate response to factors such as the changing concentration of CO 2 . Their usefulness is restricted by the need to specify the sea surface temperature. Partial solutions to this problem exist, such as adding a model of the ocean mixed layer to the atmosphere model, but these cannot simulate the response of the ocean heat transport to changes in the atmospheric circulation. Only a coupled atmosphere—ocean-sea-ice model can represent the mechanisms that determine the climate on time scales of decades. A coupled atmosphere-ocean-sea-ice model has been developed at the Meteorological Office. This paper describes the ocean and sea-ice components of that model and some of the characteristics of the ocean model when driven by observed fluxes of heat, fresh water, and momentum during a long spin-up experiment. Aspects of a four-year integration of the coupled model are discussed. Many factors contribute to the simulation of the coupled model. Not only are the characteristics of the component models present, but the additional degrees of freedom introduced by the removal of fixed boundary conditions at the ocean surface also introduce new features into the simulation. Particular features that result from the interaction of the models used in the simulations described in this paper include a feedback between the sea-ice model and the simulations of the atmosphere model at high latitudes, and a warming of the tropical Pacific.

scholarly journals ICONGETM v1.0 – flexible NUOPC-driven two-way coupling via ESMF exchange grids between the unstructured-grid atmosphere model ICON and the structured-grid coastal ocean model GETM

2021 ◽  
Vol 14 (8) ◽  
pp. 4843-4863
Author(s):  
Tobias Peter Bauer ◽  
Peter Holtermann ◽  
Bernd Heinold ◽  
Hagen Radtke ◽  
Oswald Knoth ◽  
...  
Keyword(s):  
Data Exchange ◽  
Coastal Upwelling ◽  
Weather Prediction ◽  
Coupled Model ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Model System ◽  
Ocean Dynamics ◽  
Atmosphere Model ◽  
Coastal Ocean Model

Abstract. Two-way model coupling is important for representing the mutual interactions and feedbacks between atmosphere and ocean dynamics. This work presents the development of the two-way coupled model system ICONGETM, consisting of the atmosphere model ICON and the ocean model GETM. ICONGETM is built on the latest NUOPC coupling software with flexible data exchange and conservative interpolation via ESMF exchange grids. With ICON providing a state-of-the-art kernel for numerical weather prediction on an unstructured mesh and GETM being an established coastal ocean model, ICONGETM is especially suited for high-resolution studies. For demonstration purposes the newly developed model system has been applied to a coastal upwelling scenario in the central Baltic Sea.

scholarly journals A fully coupled Arctic sea ice-ocean-atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results

2020 ◽  
Author(s):  
Shihe Ren ◽  
Xi Liang ◽  
Qizhen Sun ◽  
Hao Yu ◽  
L. Bruno Tremblay ◽  
...  
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Model Description ◽  
Preliminary Results ◽  
Comparison Results ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Atmosphere Model

Abstract. The implementation of a new Arctic regional coupled sea ice-ocean-atmosphere model (ArcIOAM) and its preliminary results in the year of 2012 are presented in this paper. A newly developed coupler, C-Coupler2 (the Community Coupler 2), is used to couple the Arctic sea ice-oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. ArcIOAM is demonstrated with focus on seasonal simulation of the Arctic sea ice and ocean state in the year of 2012. The results obtained by ArcIOAM, along with the experiment of one-way coupling strategy, are compared with available observational data and reanalysis products. From the comparison, results obtained from two experiments both realistically capture the sea ice and oceanic variables in the Arctic region over a 1-year simulation period. The two-way coupled model has better performance in terms of sea ice extent, concentration, thickness and SST, especially in summer. This indicates that sea ice-ocean-atmosphere interaction takes a crucial role in controlling Arctic summertime sea ice distribution. The coupled model and documentation are available at  https://doi.org/10.5281/zenodo.3742692 (last access: 9 June 2020), and the source code is maintained at  https://github.com/cdmpbp123/Coupled_Atm_Ice_Oce (last access: 7 April 2020).

scholarly journals Two-Way Air–Sea Coupling: A Study of the Adriatic

2006 ◽  
Vol 134 (5) ◽  
pp. 1465-1483 ◽  
Author(s):  
Julie Pullen ◽  
James D. Doyle ◽  
Richard P. Signell
Keyword(s):  
Cold Water ◽  
Coupled Model ◽  
Ocean Model ◽  
Heat Fluxes ◽  
Strong Wind ◽  
Surface Cooling ◽  
Coupled Simulation ◽  
Wind Speeds ◽  
Atmosphere Model ◽  
The Impact

Abstract High-resolution numerical simulations of the Adriatic Sea using the Navy Coastal Ocean Model (NCOM) and Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) were conducted to examine the impact of the coupling strategy (one versus two way) on the ocean and atmosphere model skill, and to elucidate dynamical aspects of the coupled response. Simulations for 23 September–23 October 2002 utilized 2- and 4-km resolution grids for the ocean and atmosphere, respectively. During a strong wind and sea surface cooling event, cold water fringed the west and north coasts in the two-way coupled simulation (where the atmosphere interacted with SST generated by the ocean model) and attenuated by approximately 20% of the cross-basin extension of bora-driven upward heat fluxes relative to the one-way coupled simulation (where the atmosphere model was not influenced by the ocean model). An assessment of model results using remotely sensed and in situ measurements of ocean temperature along with overwater and coastal wind observations showed enhanced skill in the two-way coupled model. In particular, the two-way coupled model produced spatially complex SSTs after the cooling event that compared more favorably (using mean bias and rms error) with satellite multichannel SST (MCSST) and had a stabilizing effect on the atmosphere. As a consequence, mean mixing was suppressed by over 20% in the atmospheric boundary layer and more realistic mean 10-m wind speeds were produced during the monthlong two-way coupled simulation.

scholarly journals Nonlinear dynamics approach to the predictability of the Cane–Zebiak coupled ocean–atmosphere model

2014 ◽  
Vol 21 (1) ◽  
pp. 155-163 ◽  
Author(s):  
L. Siqueira ◽  
B. Kirtman
Keyword(s):  
Nonlinear Dynamics ◽  
Lyapunov Exponent ◽  
Finite Size ◽  
Coupled Model ◽  
Finite Amplitude ◽  
Maximum Lyapunov Exponent ◽  
Theoretical Concepts ◽  
Ocean Atmosphere ◽  
Atmosphere Model ◽  
Predictability Analysis

Abstract. The predictability of the Cane–Zebiak coupled ocean–atmosphere model is investigated using nonlinear dynamics analysis. Newer theoretical concepts are applied to the coupled model in order to help quantify maximal prediction horizons for finite amplitude perturbations on different scales. Predictability analysis based on the maximum Lyapunov exponent considers infinitesimal perturbations, which are associated with errors in the smallest fastest-evolving scales of motion. However, these errors become irrelevant for the predictability of larger scale motions. In this study we employed finite-size Lyapunov exponent analysis to assess the predictability of the Cane–Zebiak coupled ocean–atmosphere model as a function of scale. We demonstrate the existence of fast and slow timescales, as noted in earlier studies, and the expected enhanced predictability of the anomalies on large scales. The final results and conclusions clarify the applicability of these new methods to seasonal forecasting problems.

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