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基于北疆垦区新疆生产建设兵团第六师新湖农场1981-2014年数据,分析了其春、夏、秋季和棉花主要生长季(5~9月,包括2015年)及各月的平均气温、平均最高气温、最低气温的年际、年代际变化,并与棉花单产做相关性分析。结果表明,春、夏、秋季及主要生长季的气温年际变化均为变暖趋势,增温率秋季大,夏季小;34年间平均气温上升了1.2~2.7℃,平均最高气温上升了1.5~2.3℃,平均最低气温上升了2.0~2.6℃;从5~9月来看,5月平均气温、最低气温增幅大,6月最高气温增幅大;年代际的变化是平均气温和平均最高气温秋季升幅大,平均最低气温春季和秋季升幅最大;5~9月的各月分布是5、8月逐年代均为上升,但6月最高、7月最低、9月最高气温、最低气温都出现了振荡;棉花单产与气温变化趋势慢而稳定(夏季、主要生长季、7月平均气温、最高气温、8月),与上升幅度大(5月平均气温、最低气温)的温度因子关系为显著正相关;5~9月5个月的平均气温和最高气温与产量为显著正相关,其中8月与产量相关性最好。
Based on the data of Xinhu farms from the 6th division of Xinjiang Production and Construction Corps in North Xinjiang Reclamation for 1981-2014, the average temperature of spring, summer and autumn, cotton growing season (from May to September, including 2015) Average maximum temperature, minimum temperature of the interannual and interdecadal changes, and with cotton yield do correlation analysis. The results showed that the interannual variations of temperature in spring, summer, autumn and main growth seasons were all warming trend, the rate of temperature increase was big in autumn and small in summer; the average temperature increased by 1.2-2.7 ℃ in 34 years and the average maximum temperature increased by 1.5 ~ 2.3 ℃, the average minimum temperature increased by 2.0 ~ 2.6 ℃; from May to September, the average temperature in May, an increase of the minimum temperature, the maximum temperature increase in June; interdecadal changes are the average temperature and the highest average temperature fall And the average minimum temperature increased most greatly in spring and autumn. The distribution in each month from May to September was in August and August, and it increased year by year, but it was highest in June and lowest in July. The highest and lowest temperatures in September all appeared Oscillation. The trend of cotton yield and temperature changed slowly and steadily (summer, main growing season, July average temperature, maximum temperature, August), and temperature coefficient of rising (average temperature in May and lowest temperature) was significantly positive The correlation between the average temperature and the maximum temperature in May-September and the output was significant and significant. Among them, the correlation between output and August was the best.