We investigated the sensitivity of simulated rainfall towards different convective physics parameterizations in the WRF regional model using an MIROC5 projection dataset as the forcing. A series of 1-year period simulations under different ENSO phases for the past years were done using different cumulus physics settings at the spatial resolution of 20 km. The results were then compared with satellite and ground-based observational datasets. Preliminary results suggest that the regional model has shown to produces a more realistic detail in terms of spatial distribution with respect to the orographic influences. Different convective parameterizations also play a significant role in simulating rainfall as some options tend to produce more wet biases over another. It was also found that the results varied over different parts of the domain with different rainfall patterns, which are depending on the prominent modes of circulation affecting the area. Regional model results have a better temporal correlation in regions with “monsoonal” type rainfall pattern, primarily driven by the Asian-Australian monsoon, compared to the “equatorial” or “local” types. The results are also shown to be more realistic in illustrating the consecutive rainfall events by significantly reducing the overestimation of wet and/or dry spell that was found to be prolonged in the GCM simulated rainfall. However, as with the GCM still hardly able to represent the effect of ENSO variability on its simulated rainfall, the regional simulation result is possessing the same nature and still yet to capture inter-annual extreme events.
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