资源环境科技发展态势分析平台

Prediction of Indian summer (June-September) rainfall on regional scales remains an open issue. The operational predictions of West Central Indian summer rainfall (WCI-R) and Peninsular Indian summer rainfall (PI-R) made by the Indian Meteorological Department (IMD) had no skills during 2004-2012. This motivates the present study aiming at better understanding the predictability sources and physical processes governing summer rainfall variability over these two regions. Analysis of 133 year data reveal that although the lower boundary forcing that associated with enhanced WCI-R and PI-R featured a similar developing La-Nina and "east high west low" sea-level pressure (SLP) dipole pattern across the Indo-Pacific, the anomalous high sea surface temperature (SST) over the northern Indian Ocean and weak low pressure over northern Asia tended to enhance PI-R but reduce WCI-R. Based on our understanding of physical linkages with the predictands, we selected four and two causative predictors for predictions of the WCI-R and PI-R, respectively. The intensified summer WCI-R is preceded by (a) Indian Ocean zonal dipole-like SST tendency (west-warming and east-cooling), (b) tropical Pacific zonal dipole SST tendency (west-warming and east-cooling), (c) central Pacific meridional dipole SST tendency (north-cooling and south-warming), and (d) decreasing SLP tendency over northern Asia in the previous season. The enhanced PI-R was lead by the central-eastern Pacific cooling and 2-m temperature cooling tendency east of Lake Balkhash in the previous seasons. These causative processes linking the predictors and WCI-R and PI-R are supported by ensemble numerical experiments using a coupled climate model. For the period of 1871-2012, the physics-based empirical (P-E) prediction models built on these predictors result in cross-validated forecast temporal correlation coefficient skills of 0.55 and 0.47 for WCI-R and PI-R, respectively. The independent forecast skill is significantly higher than the skill of operational seasonal forecast made by the IMD for the period of 2004-2012. These prediction models offer a tool for seasonal prediction and their retrospective forecast skills provide an estimation of the lower bound of the predictability for WCI-R and PI-R.