coupled global climate model
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2020 ◽  
Vol 54 (11-12) ◽  
pp. 5089-5109
Author(s):  
Anna-Lena Deppenmeier ◽  
Rein J. Haarsma ◽  
Philippe LeSager ◽  
Wilco Hazeleger

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Mansour Almazroui ◽  
Osama Tayeb ◽  
Abdulfattah S. Mashat ◽  
Ahmed Yousef ◽  
Yusuf A. Al-Turki ◽  
...  

2013 ◽  
Vol 26 (23) ◽  
pp. 9399-9407 ◽  
Author(s):  
Simon Borlace ◽  
Wenju Cai ◽  
Agus Santoso

The amplitude of the El Niño–Southern Oscillation (ENSO) can vary naturally over multidecadal time scales and can be influenced by climate change. However, determining the mechanism for this variation is difficult because of the paucity of observations over such long time scales. Using a 1000-yr integration of a coupled global climate model and a linear stability analysis, it is demonstrated that multidecadal modulation of ENSO amplitude can be driven by variations in the governing dynamics. In this model, the modulation is controlled by the underlying thermocline feedback mechanism, which in turn is governed by the response of the oceanic thermocline slope across the equatorial Pacific to changes in the overlying basinwide zonal winds. Furthermore, the episodic strengthening and weakening of this coupled interaction is shown to be linked to the slowly varying background climate. In comparison with the model statistics, the recent change of ENSO amplitude in observations appears to be still within the range of natural variability. This is despite the apparent warming trend in the mean climate. Hence, this study suggests that it may be difficult to infer a climate change signal from changes in ENSO amplitude alone, particularly given the presently limited observational data.


2013 ◽  
Vol 26 (19) ◽  
pp. 7708-7719 ◽  
Author(s):  
Marco Gaetani ◽  
Elsa Mohino

Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.


2006 ◽  
Vol 19 (22) ◽  
pp. 5934-5943 ◽  
Author(s):  
Jenny Brandefelt

Abstract The response of the atmospheric circulation to an enhanced radiative greenhouse gas forcing in a transient integration with a coupled global climate model is investigated. The spatial patterns of the leading modes of Northern Hemisphere atmospheric variability are shown to change in response to the enhanced forcing. An earlier study showed that the spatial patterns of the leading modes in the Southern Hemisphere changed in response to the enhanced forcing. These changes were associated with changes in the propagation conditions for barotropic Rossby waves. This is, however, not the case for the Northern Hemisphere, where the propagation conditions are unchanged. Other possible mechanisms for the changes in the spatial patterns of the leading modes are discussed.


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