Monsoons and Intertropical Convergence Zones (ITCZ) exhibit variability at various temporal and spatial scales. The temporal scale of variability encompasses scales from the intraseasonal through interannual to interdecadal time scales. Anthropogenic climate change can also have an impact on ITCZ and monsoons. Thus it is necessary to assess the ability of coupled ocean atmospheric models (commonly known as AOGCM) to simulate these aspects of variability of tropical climate. This has been studied with simulations from 20 AOGCMs and their AGCM from IPCCAR4 archive. In addition, we have used our own 100 year simulation with CCSM2 and also simulations with its AGCM viz. CAM2. Our analysis shows that most model have significant bias in tropical rainfall and SST. Most models underestimate SST except over a few regions such as the Eastern boundaries of Atlantic and Pacific Oceans. The AGCMs which are forced with observed SSTs have much higher annual mean rainfall as compared to AOGCMs. There is a strong correlation between error in shortwave reflectance at the top of the atmosphere and error in SST. The ability of coupled ocean-atmosphere models and their atmosphere-alone counterparts to simulate the seasonal cycle of rainfall over major monsoon regions and also over oceanic ITCZ. It is found that over the Indian monsoon region, most AGCMs overestimate the seasonal cycle while AOGCMs have a more realistic seasonal cycle. This inspite of the fact that most AOGCMs underestimate the SST over the Indian region. It is shown that this is related to errors in precipitable water-rainfall relationship in most models i.e. for a given amount of precipitable water, most models overestimate the rainfall. Thus lower SST reduces the precipitable water and hence the amount of rainfall is reduced. Therefore, the mutual cancellation of errors leads to a more realistic seasonal cycle in AOGCMs. The seasonal cycle over Africa was analysed with the help of a diagnostic model. Over Southern Africa, most models show simulate a less stable atmosphere and hence the rainfall is overestimated. A technique based on Continous Wavelet Transform in Space and Time (CWTST) has been modified to seperate northward and southward propagating modes of BSISO over the Indian and West Pacific regions. It was seen that over the Indian region, northward propagating modes were more prominent in comparison to southward modes. It was also found that the predominant spatial scale (of about 30o) did not show much interannual variability but the associated temporal scale showed significant variation. Both AOGCMs and AGCMs simulations were analysed to investigate the impact of coupling on intraseasonal activity. Most AOGCMs were able to simulate the predominant spatial scale but were unable to simulate the associated temporal scale correctly. These problems persisted with AGCMs also. It was also found that for AGCMs, there were some variations between ensemble members of the AGCMs. Comparing BSISO in increased GHG scenarios with present day simulations we found that in general, power in the spectrum increases. This could be related to higher mean precipitation that has been simulated by most AOGCMs when GHG are increased. The interannual variability in the tropics with special reference to Tropical Biennial Oscillation (TBO) and ENSO has been studied. The changes in these modes of variability due to anthropogenic climate change has also been assessed. We found that in most models over the Nino3.4 region, the mode of variation shifts from a near-four period (in pre-industrial simulations) to that of TBO mode in increased GHG (green house gas) scenario. This suggests that with increasing GHGs, ENSO quasi-periodicity might shift to about two years. It is also interesting to note that for observed rainfall, OLR and 850 hPa winds, the TBO mode has higher variance over the Eastern Indian Ocean, indicating that the TBO mode might be related to Indian Ocean Dipole Mode and EQUINOO (Equatorial Indian Ocean Oscillation).