The comparative advantage of maize production in Jilin Province was analyzed based on the sow area index,unit yield index,benefit index and comprehensive comparative advantage index in this study.The results showed th...The comparative advantage of maize production in Jilin Province was analyzed based on the sow area index,unit yield index,benefit index and comprehensive comparative advantage index in this study.The results showed that compared with other provinces in China,there was obvious comparative advantage in sow area index and unit yield index of maize in Jilin,the average of which stood for the first and the fourth in China from 2002 to 2006;there was no comparative advantage of benefit index compared with the average value of the whole countries,the average of which stood for the 14th in China from 2002 to 2006;the comprehensive comparative advantage in Jilin provincial maize production showed significant comparative advantage,the average of which stood for the fourth in China from 2002 to 2006.On the basis of the above,the suggestions to develop maize production in Jilin province had been put forward.展开更多
Evaluating cloud seeding effects is one of the most critical issues in artificial precipitation enhancement experiments. However, the evaluation is not straightforward because there is natural rainfall variability, wh...Evaluating cloud seeding effects is one of the most critical issues in artificial precipitation enhancement experiments. However, the evaluation is not straightforward because there is natural rainfall variability, which subjects the atmosphere to spatiotemporal instabilities. The aim of this study is to analyze natural rainfall variability using the modern statistical simulation method, "bootstrap", to analyze its influence on the evaluation of seeding activities and to take proper measures to control the influence. The study is based on the 1997?2007 airborne seeding macro records and the daily precipitation data in Jilin Province. The influence of natural rainfall variability can be reduced through three approaches: the increase of the supposed "seeded" sample size N, the rejection of outliers, and the selection of similar control units. A larger N leads to smaller calculated precipitation variability and detectable lower limits of seeding effects. When N is near 470 and the seeding effect is between 20% and 30%, the confidence level reaches 90%. For a single seeding operation, the case deletion model that rejects strong influence points and selects similar control units is established to control the influence of natural precipitation variability, which obviously improves the evaluation of artificial precipitation enhancement. The results demonstrate that the relative seeding effect in Jilin Province is concentrated mainly in the range of 0 to 30%, with an average of 11.95%, and has no significant linear relationship with the actual precipitation amount. However, the fluctuation amplitude of the relative effect decreases as the precipitation amount rises.展开更多
基金Supported by Key Projects in the National Science & Technology Pillar Program in the Eleventh Five-year Plan Period(2007BAD98B06)Scientific Research Foundation of Jilin Agricultural University~~
文摘The comparative advantage of maize production in Jilin Province was analyzed based on the sow area index,unit yield index,benefit index and comprehensive comparative advantage index in this study.The results showed that compared with other provinces in China,there was obvious comparative advantage in sow area index and unit yield index of maize in Jilin,the average of which stood for the first and the fourth in China from 2002 to 2006;there was no comparative advantage of benefit index compared with the average value of the whole countries,the average of which stood for the 14th in China from 2002 to 2006;the comprehensive comparative advantage in Jilin provincial maize production showed significant comparative advantage,the average of which stood for the fourth in China from 2002 to 2006.On the basis of the above,the suggestions to develop maize production in Jilin province had been put forward.
基金supported by the National Meteorological Public Benefit Research Foundation(Grant No.GYHY201006031)the China Meteorological Administration Soft Science Project(Grant No.2012-053)+1 种基金the Jiangsu Province Science Department Grant(Grant No.CB10X_295Z)the Jiangsu Province Qinglan Project for Cloud Fog Precipitation and Aerosol Research Group
文摘Evaluating cloud seeding effects is one of the most critical issues in artificial precipitation enhancement experiments. However, the evaluation is not straightforward because there is natural rainfall variability, which subjects the atmosphere to spatiotemporal instabilities. The aim of this study is to analyze natural rainfall variability using the modern statistical simulation method, "bootstrap", to analyze its influence on the evaluation of seeding activities and to take proper measures to control the influence. The study is based on the 1997?2007 airborne seeding macro records and the daily precipitation data in Jilin Province. The influence of natural rainfall variability can be reduced through three approaches: the increase of the supposed "seeded" sample size N, the rejection of outliers, and the selection of similar control units. A larger N leads to smaller calculated precipitation variability and detectable lower limits of seeding effects. When N is near 470 and the seeding effect is between 20% and 30%, the confidence level reaches 90%. For a single seeding operation, the case deletion model that rejects strong influence points and selects similar control units is established to control the influence of natural precipitation variability, which obviously improves the evaluation of artificial precipitation enhancement. The results demonstrate that the relative seeding effect in Jilin Province is concentrated mainly in the range of 0 to 30%, with an average of 11.95%, and has no significant linear relationship with the actual precipitation amount. However, the fluctuation amplitude of the relative effect decreases as the precipitation amount rises.
