Modifications to atmospheric physical parameterisations aimed at improving SST simulations in the ACCESS coupled model

2013 ◽  
Vol 63 (1) ◽  
pp. 233-247 ◽  
Author(s):  
Z Sun ◽  
C Franklin ◽  
X Zhou ◽  
Y Ma ◽  
P Okely ◽  
...  
Keyword(s):  
Coupled Model

Stability of the thermohaline circulation in a simple coupled model

1996 ◽  
Vol 48 (3) ◽  
pp. 465-476 ◽  
Author(s):  
Gerrit Lohmann ◽  
Rüdiger Gerdes ◽  
Deliang Chen
Keyword(s):  
Thermohaline Circulation ◽  
Coupled Model

The ACCESS coupled model: documentation of core CMIP5 simulations and initial results

2013 ◽  
Vol 63 (1) ◽  
pp. 83-99 ◽  
Author(s):  
M Dix ◽  
P Vohralik ◽  
D Bi ◽  
H Rashid ◽  
S Marsland ◽  
...  
Keyword(s):  
Coupled Model ◽  
Initial Results

Stress self-sensing in Amplified Piezoelectric Actuators through a fully-coupled model of hysteresis

2020 ◽  
Vol 579 ◽  
pp. 411894
Author(s):  
Valerio Apicella ◽  
Carmine Stefano Clemente ◽  
Daniele Davino ◽  
Damiano Leone ◽  
Ciro Visone
Keyword(s):  
Coupled Model ◽  
Piezoelectric Actuators ◽  
Fully Coupled

scholarly journals Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model

2019 ◽  
Vol 147 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
Yuchu Zhao ◽  
Zhengyu Liu ◽  
Fei Zheng ◽  
Yishuai Jin
Keyword(s):  
Data Assimilation ◽  
Parameter Optimization ◽  
Real World ◽  
Climate Models ◽  
Coupled Model ◽  
Prediction Skill ◽  
Model Parameters ◽  
Real World Data ◽  
The Real ◽  
Advection Term

Abstract We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.

scholarly journals Impact of air–sea coupling on the climate change signal over the Iberian Peninsula

2021 ◽  
Author(s):  
Alba de la Vara ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Claas Teichmann ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Mediterranean Sea ◽  
Large Scale ◽  
Regional Distribution ◽  
Coupled Model ◽  
Climate Change Signal ◽  
The North ◽  
The Mediterranean ◽  
The Impact

AbstractIn this work we use a regional atmosphere–ocean coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere–ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP climate is influenced by both the Atlantic Ocean and the Mediterranean sea. Complex interactions with the orography take place there and high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the twenty-first century (2070–2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between the coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model show that regionalization has an effect in terms of higher resolution over the land and ocean.

scholarly journals DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations

2021 ◽  
pp. 1-6
Author(s):  
Hao Luo ◽  
Qinghua Yang ◽  
Longjiang Mu ◽  
Xiangshan Tian-Kunze ◽  
Lars Nerger ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Southern Ocean ◽  
Sea Ice ◽  
Coupled Model ◽  
Sea Ice Concentration ◽  
Model Free ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
Data Assimilation System ◽  
Assimilation System

Abstract To improve Antarctic sea-ice simulations and estimations, an ensemble-based Data Assimilation System for the Southern Ocean (DASSO) was developed based on a regional sea ice–ocean coupled model, which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. To validate the performance of DASSO, experiments were conducted from 15 April to 14 October 2016. Generally, assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. Besides considering uncertainties in the operational atmospheric forcing data, a covariance inflation procedure in data assimilation further improves the simulation of Antarctic sea ice, especially SIT. The results demonstrate the effectiveness of assimilating sea-ice observations in reconstructing the state of Antarctic sea ice, but also highlight the necessity of more reasonable error estimation for the background as well as the observation.

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