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引用本文:徐用兵,雷秋良,周脚根,张亦涛,武淑霞,翟丽梅,王洪媛,李影,刘宏斌.1960—2015年云南省极端气候指数变化特征研究[J].中国农业资源与区划,2020,41(11):15~27
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1960—2015年云南省极端气候指数变化特征研究
徐用兵1,2雷秋良1,2※周脚根3张亦涛4武淑霞1,2翟丽梅1,2王洪媛1,2李影1刘宏斌1,2
1.中国农业科学院农业资源与农业区划研究所,北京100081;2.农业农村部面源污染控制重点实验室,北京100081; 3.淮阴师范学院城市与环境学院,江苏淮安223399; 4.中国科学院地理科学与资源研究所,北京100101
摘要:
[目的]基于1960—2015年的云南省31个气象站点逐日平均气温、最高气温、最低气温和降水量等数据,研究极端气候指数的时空变化,为降低云南省自然灾害对农业生产的影响,以及制定应对气候风险的策略提供依据。[方法]采用国际气候诊断与指数小组(ETCDD-MI)定义的极端气候指标,运用线性趋势法和克里金插值法等对其进行分析。[结果]7个气温指数中,夏季日数、冷昼日数和寒潮持续指数呈下降趋势,霜冻日数、月极端最高气温、月极端最低气温和暖夜日数呈上升的趋势。空间变异分析显示夏季日数、月极端最高气温和月极端最低气温由南向北递减,暖夜日数、冷昼日数和寒潮持续指数表现为东高西低。7个极端气温指数的变化趋势中,霜冻日数和冷昼日数的变化趋势与海拔高度呈显著的负相关关系,月极端最高气温的趋势与海拔高度呈极显著的正相关关系。6个降水指数中,日最大降水量、连续干旱日数和极强降水量呈上升的趋势,大雨日数、连续湿日数和年总降水量呈下降的趋势。日最大降水量和大雨日数由南向北递减,连续湿日数和年总降水量由西南向东北递减,连续干旱日数高值中心主要位于云南的中部和东部,极强降水量主要集中在德宏州和保山市。云南省的极端强降水由西南向东北递减。6个极端降水指数的变化趋势与海拔的相关性均未达到显著水平。[结论]这些极端气候变化特征表明云南省有变干和变暖的趋势,农业生产应采取适应性对策。
关键词:  极端气温极端降水变化趋势空间变异海拔
DOI:
分类号:S166
基金项目:国家自然科学基金项目“高原农业洱海流域农田氮素径流损失模拟研究”(31572208);公益性行业(农业)科研专项“典型流域主要农业源污染物入湖负荷及防控技术研究与示范”(201303089);国家重点研发计划项目“北方水稻化肥农药减施技术集成研究与示范”(2018YFD0200200)
STUDY ON THE CHANGE CHARACTERISTICS OF EXTREME CLIMATE INDICES FROM 1960 TO 2015 IN YUNNAN PROVINCE, CHINA
Xu Yongbing1,2, Lei Qiuliang1,2※, Zhou Jiaogen3, Zhang Yitao4, Wu Shuxia1,2, Zhai Limei1,2, Wang Hongyuan1,2, Li Ying1, Liu Hongbin1,2
1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 2. Key Laboratory of Non point Pollution Control, Ministry of Agriculture and Rural Affairs, Beijing 100081, China;3. School of Urban and Environmental Science, Huaiyin Normal University, Huai′an 223399, Jiangsu, China;4. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Abstract:
Daily data for average temperatures, maximum and minimum temperatures and precipitation, observed at 31 meteorological stations in the Yunnan province from 1960 to 2015, were used to study the changes in extreme climate index. The study employed regression analysis and Kriging methods, and adopted the indices of extreme climate defined by the CCl/CLIVAR/JCOMM expert team on climate change detection and indices. Results showed that the number of sunny days, the cold day index and the cold wave duration index all showed a downward trend from 1960 to 2015, while the number of frost days, warmest days, coldest days and warm nights all showed an upward trend. Spatial variation analysis found that the numbers of sunny days, warmest days and coldest days showed a decreasing trend from the southern to the northern areas of the province, while the warm night index, cold day index and cold wave duration index were higher in the east and lower in the north. Among the seven extreme temperature indices, the number of frost days and the cold day index were found to be significantly and negatively correlated with altitude, but the warmest day index was significantly and positively correlated with altitude. Among the six precipitation indices, the daily maximum precipitation, the number of consecutive dry days and the amount of heavy precipitation showed an upward trend, while the heavy precipitation days, the maximum consecutive wet days and the annual amount of precipitation showed a downward trend. As for spatial distribution, the daily maximum precipitation and the heavy precipitation index showed decreasing trends from the southern to the northern parts of the province, while the number of consecutive wet days and annual precipitation showed a decreasing trend from southwest to northeast. The areas with the highest values for the maximum number of continuous dry days were mainly located in the central and eastern parts of the province and strong precipitation was mainly concentrated in Dehong and Baoshan, in the western part of the province. The distribution of extremely heavy precipitation in the Yunnan province decreased from southwest to northeast. The six extreme precipitation indices showed no significant correlation with altitude. These change characteristics for the extreme climate indices from 1960 to 2015 showed that the Yunnan province tended to be warmer and dryer over time, suggesting that the agricultural production industry should consider adaptive countermeasures.
Key words:  extreme temperature  extreme precipitation  variation trend  spatial variation  elevation
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