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机构地区:[1]西北师范大学地理与环境科学学院,兰州730070 [2]甘肃省遥感重点实验室,兰州730000
出 处:《兰州大学学报(自然科学版)》2017年第2期213-219,共7页Journal of Lanzhou University(Natural Sciences)
基 金:甘肃省遥感重点实验室开放基金项目;国家自然科学基金项目(91025001)
摘 要:利用1961-2010年全国723个气象台站的日平均气温、月平均气温数据,分别计算≥0℃的积温,采用差值法得到积温偏差,分析了其空间分布特征及与月积温偏差的关系.结果表明,基于不同起始数据获取的年积温存在一定的不确定性和明显的时空差异,主要表现出集聚性、一致性和异质性等空间分布特征.年积温不确定性与纬经度、海拔密切相关,且纬度与海拔的影响高于经度,秦岭-淮河及横断山脉一线为年积温偏差10℃·d的分界线.月积温不确定性随月份的增大呈U型分布,11月最大、7月最小;年积温偏差贡献率范围存在明显差异,12月最大,5月最小.Using the different starting data, daily average temperature and monthly average temperature of 723 meteorological stations in China during the year 1961-2010, the annual integrated temperature (IT) above 0℃ was calculated respectively. According to the two different integrated temperatures, the integrated difference of which was obtained, and the spatial distribution of IT deviation and the rela- tionship between annual IT deviation and monthly IT deviation were analyzed. The results showed that: there was a gradient of uncertainty for IT calculated using daily and monthly temperatures, and there were significant spatial and temporal differences, mainly exhibiting clustering, consistency and heteroge- neity characteristics. The IT uncertainty was closely related to the size of the latitude, longitude and the altitude, and the higher impact of latitude and altitude than longitude. The line contained by Qinling- Huaihe and the Hengduan Mountains was the dividing line of the annual IT deviation with the value of 10 ℃. The monthly IT uncertainty was showed U-shaped distribution increasing the month from January to December, the largest uncertainty in November and the smallest uncertainty in July; there were obviously differences in the rate of contribution to annual IT, the maximum value in December and the minimum value in May.
关 键 词:积温 不确定性 时空特征 日平均气温 月平均气温
分 类 号:P423[天文地球—大气科学及气象学]
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