资源环境科技发展态势分析平台

The complexity of the Indian summer monsoon precipitation makes it's prediction a challenging task as it is not only influenced by the large-scale flows but also by the micro-scale features. In a dynamical model, precipitation is resulted from the formation of clouds. The cloud formation and its processes occur at a micro scale. Current state-of-the-art dynamical models lack proper representation of the cloud processes, particularly at high resolutions for which the cloud processes are parameterized, thereby poorly resolving the precipitation. This study aims at examining the impact of the cloud parameters on the simulation of Indian summer monsoon precipitation in Regional Climate Model version 4 (RegCM4). The autoconversion coefficient which determines the conversion of cloud water into precipitation in the Explicit Moisture Convergence scheme is adjusted in the RegCM4. The impact of autoconversion is experimented with ten different values and it is found that it has a significant effect on the simulation of precipitation during summer monsoon season. The experiments are conducted by changing autoconversion from 1.5x10(-4) to 7.5x10(-4)/s along with the default value of 2.5x10(-4)/s. On changing the autoconversion values from 60 to 300% of the default value, the precipitation pattern improves over most parts of India. The model simulates the rainfall better when the autoconversion coefficient is changed to 7.5x10(-4)/s. With the best outcome with the adjusted autoconversion and control configuration, the model is simulated for seventeen monsoon seasons and the analyses of RegCM4 simulated vertically integrated moisture transport, convective available potential energy and atmospheric moisture budget suggest that the model efficacy is enhanced in higher autoconversion value than the control one. Statistical evaluations using bias, correlation coefficients, comprehensive rating matrices and skill score confirm the suitability of higher autoconversion rate for summer monsoon simulations. The model with adjusted autoconversion coefficient (at 7.5x10(-4)/s) has improved the representation of seasonal precipitation distribution and its year-to-year variation including other derived features. The rainfall pattern is improved over North West India and North East India especially, the monsoon core regions. The mean seasonal rainfall is in phase 94% of the time with the modeler-adjusted moisture as compared to 82% in the control in the long term simulation.