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The global land monthly precipitation data (PREC/L) are used to investigate the relation between the global land annual precipitation and ENSO during 1948–2000, and the results of composite analysis are tested with Monte Carlo simulations. Results indicate that the global land annual precipitation was significantly reduced in large scale areas in warm event years; the areas were the equatorial West Pacific, North China; equatorial Central America; North Bengal Bay and Nepal; East Australia; West India and South Pakistan; the district east of the Lena River; West Europe; and Wilkes Land of Antarctica. In contrast to this, the areas where precipitation increased in warm event years were less, and mainly in Chile and Argentina of South America; Somali, Kenya, and Tanzania of East Africa; Turkey, Iraq, and Iran of the Middle East; Libya and Nigeria of North Africa; Namibia of Southwest Africa; and Botswana and Zimbabwe of southern Africa. Statistical tests show that in warm event years, the area where the land annual precipitation was reduced was larger than the area where the annual precipitation increased, and the reduction in precipitation was more significant than the increase. The results in this paper are compared with previous studies. It is also pointed out that the interdecadal change of ENSO had no significant effect on the interdecadal variation of precipitation in the above regions. However, the warm events of El Nino affected the droughts in East Australia and North China more after the 1980s than before.

Detection efficiency mid Detection precision for 2 LLS in Guangdong province, China is analyzed comprehensively based on Ihe he close Optical-Electrical observation of Rocket-triggered lightning. The results show that the normalized space location error of ground-triggered strokes was 760 meters, 2790 meters for LLS2, lightning current amplitude are normalized to be 14% for LLS1 and 31% for LLS2.This paper also discuss the necessity of introduction of robust estimation in the lightning location computation to exclude the gross errors which may increase with the detection stations number.