Ensemble simulation and forecasting of South Asian Monsoon.

This research thesis first examines the ability of Community Atmosphere Model (CAM) and Community Climate System Model (CCSM) in simulating the South Asian Monsoon (SAM) summer precipitation in a framework of ensemble. On this basis, the climatic relevant singular vectors (CSVs) perturbation theory is applied to investigate the optimal error growth of SAM seasonal forecast due to the uncertainties in the Pacific and Indian Oceans. Then, the ensemble prediction of SAM constructed by CSVs is evaluated, and further compared with one traditional ensemble method. It is found that CAM4 adequately simulated monsoon precipitation, and considerably reduced systematic errors that occurred in its predecessors, although it tends to overestimate monsoon precipitation when compared with observations. In terms of monsoon interannual variability and its teleconnection with sea surface temperature (SST), CAM4 showed modest skill. In the CCSM4 coupled simulations, several aspects of the monsoon simulation are improved, including the cross-variability of simulated precipitation and SST. A significant improvement is seen in the spatial distribution of monsoon mean climatology where a too-heavy monsoon precipitation, which occurred in CAM4, is rectified. A detailed investigation of precipitation reduction, using sensitivity experiments, showed that the large systematic cold SST errors in the northern Indian Ocean reduces monsoon precipitation and delays the monsoon onset by weakening local evaporation. The CSV analysis using CAM4 revealed that the SST uncertainties in Indian Ocean can result in much larger error growth of SAM seasonal forecast than those in the equatorial Pacific Ocean. It is seen that the CSVs error growth rate changes significantly depending on the initial states whereas the CSVs patterns are insensitive to the initial conditions. The CAM4 comparison with CCSM4 coupled model indicated that the CSVs patterns from CAM4 are similar to those from CCSM4 while the error growth rate is lower in CAM4 than in CCSM4. CAM4