Abstract:
Using the monthly autumn precipitation data of 122 observation stations over Yunnan Province from 1961 to 2008 and the NOAA monthly mean reanalysis data, distributions of monthly precipitation and water vapor fluxes and water vapor flux divergence in autumn, as well as the effect of atmospheric circulation anomaly on precipitation are analyzed. The results show that, there exists the best coupling relationship of rainfall and water vapor flux, water vapor flux divergence in November, while in October it is the second, and in September it is the worst. There is a positive correlation between autumn precipitation distribution, and water vapor flux and the divergence of water vapor flux in Yunnan. The autumn precipitation field is consistent with the time variation trend of water vapor flow field. The changes of water vapor flux and water vapor flux divergence directly affect the change of precipitation. The autumn precipitation amount is largely influenced by the atmospheric circulation anomaly. When September precipitation in Yunnan is abnormal, the monsoon in Bay of Bengal blows strongly, the subtropical high is by east and weak, and the cold air is active. Otherwise appears the negative anomaly. When rainfall in October is abnormal, southern trough and southwest monsoon are active, strengthening Yunnan’s southerly warm and humid air flows, otherwise, precipitation is less. When in November the southern trough and the cold airs that influence Yunnan are active, more precipitation produces, otherwise, negative anomaly appears. Regarding the vapor net budget, the zonal net income in September is the largest, while zonal net income in October weakens. In November, under the control of the westerlies, the net income becomes very small. However, meridional water vapor income during September to November transfers from expenditure to inflows. Thinking from the whole layer and low level vapor net budget in positive and negative anomaly years in Yunnan, except for the November in negative anomaly years it is water vapor source, in all the other times it is moisture convergence. When calculating with ERA Interim reanalysis data and 20CR reanalysis data, the water vapor error is found small, and the vapor net budget variations in positive and negative anomaly years are consistent.