中国农业气象 ›› 2015, Vol. 36 ›› Issue (05): 525-535.doi: 10.3969/j.issn.1000-6362.2015.05.001

• 论文 • 上一篇    下一篇

黄河流域极端气温指数的气候演变特征分析

吴 灿,赵景波,王格慧   

  1. 1.陕西师范大学旅游与环境学院,西安 710062;2. 中国科学院地球环境研究所气溶胶化学与物理重点实验室,西安 710061
  • 收稿日期:2015-01-12 出版日期:2015-10-20 发布日期:2015-10-19
  • 作者简介:吴灿(1988-),硕士生,主要研究方向为大气污染防治。E-mail:wu_can246@163.com
  • 基金资助:
    国家自然科学重点基金项目(NSFC41230641);国家社会科学基金项目“中国丝绸之路经济带生态文明建设评价与路径研究”(14XKS019)

Characteristic Analysis of the Climatic Revolution in the Yellow River Extreme Temperature Index

WU Can, ZHAO Jing-bo, WANG Ge-hui   

  1. 1. College of Tourism and Environment, Shaanxi Normal University, Xi' an 710062,China; 2. Key Lab of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061
  • Received:2015-01-12 Online:2015-10-20 Published:2015-10-19

摘要: 利用黄河流域1963-2013年59个站点日最高和最低气温资料,结合线性拟合、M-K检验、Morlet小波分析、主成分分析及相关性分析等方法,研究了该流域极端气温的时空变化特征。结果表明:(1)整体上看,黄河流域冷日、冷夜、冰日、霜冻、冷持续日数分别以1.06、1.93、2.40、3.36、1.12d·10a-1 (P<0.001)的趋势减少,而暖日、暖夜、夏日、热夜、暖持续日数、生物生长季分别以1.56、2.22、2.66、1.56、1.48、3.47d·10a-1 (P<0.001)的趋势增加,日最低气温极小(大)值、日最高气温极小(大)值及气温日较差的变化率分别为0.25(0.4)、0.18(0.27)、-0.09℃·10a-1 (P<0.05)。(2)研究区内6个子区域的极端气温指数的变化趋势相一致,宁夏中北部、内蒙古中南部极端气温事件变化趋势最为显著。(3)夜指数(暖夜、冷夜)变化幅度大于昼指数(暖日、冷日),冷指数(极端最低、最高温度极小值)变化幅度小于暖指数(极端最低、最高温度极大值)。(4)黄河上中游比下游地区对极端气温变化更敏感。(5)WMO发布的16个指数均有3a、7a左右的短周期和26a左右的长周期,而暖(冷)持续日数、气温日较差、生物生长季还拥有一个16a左右的中长周期。(6)除日最低气温极小值、气温日较差、冷持续日数外,其余各项指数的突变年份均发生在20世纪90年代。

关键词: 突变分析, 变化周期, 影响因素, 气候变化, 黄河流域

Abstract: In this paper, the spatiotemporal variation of extreme temperature events were investigated based on the daily maximum and minimum temperature data observed by 59 meteorological stations for the period 1963-2013 in the Yellow River Basin(YRB), with the help of liner regression, Mann-Kendall test, wavelet analysis, principal component analysis and correlation analysis. The results showed that, (1)cool days, cool nights, ice days, frost days and cold speel duration days displayed significant negative trend at rates of 1.06, 1.93, 2.40, 3.36 and1.12d·10y-1, respectively(P<0.001), while warm days, warm nights, summer days, tropical nights, warm speel duration days and growing season length exhibited significant positive trend at rates of 1.56, 2.22, 2.66, 1.56, 1.48 and 3.47d·10y-1 (P<0.001), respectively. Furthermore, the trends for annual minimum value of daily minimum (maximum) temperature, annual maximum value of daily minimum (maximum) and diurnal temperature range were 0.25(0.4), 0.18(0.27) and -0.09℃·10y-1 (P<0.05), respectively. (2)The six sub-region’s extreme temperature indices remained same variation tendency, while the extreme temperature events of north-central Ningxia and south–central Inner Mongolia were more significant. (3)The change range of night indices(warm nights, cold night) were larger than those day indices (warm days, cold days), the range of variation in cold indices (annual minimum value of daily minimum/maximum) were smaller than warm indices (annual maximum value of daily minimum/maximum). (4)The upper-middle of Yellow River were more sensitive than downstream for the extreme temperatures change. (5)All of 16 indices had short cycles of 3 and 7 years, and had long cycles of 26 years, while warm/cold spell duration days, diurnal temperature range and growing season length also had another cycle of 16 years. (6)Besides, annual minimum value of daily minimum, diurnal temperature range and cold spell duration days, the time points of abrupt change for others were concentrated in 1990s.

Key words: Mann-Kendall test, Cycle variation, Influence factor, Climate change, The Yellow River Basin(YRB)