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1961-2011年中国南方地区极端降水事件变化

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基于国家气象信息中心发布的1961-2011年全国0.5°×0.5°逐日降水量数据集和气象站点日降水量实测资料,评估了该套格点降水资料在中国南方地区的可信度,并选取了世界气象组织等推荐的5个极端降水指数,利用格点资料研究了中国南方地区的极端降水事件变化.结果表明,内插到气象站点位置的格点资料和气象站点实测数据之间的偏差普遍较小,偏差在-10%~0之间的站点个数占总个数的50.64%,在绝大多数区域二者之间的相关系数均在0.80以上;各极端降水指数的多年平均值表现出明显的空间分布规律,越靠近西北方向越干旱,而越靠近东南方向越湿润;1961-2011年间,最大5日降水量(RX5day)、极端降水量(R95)、日降水量≥20mm天数(R20mm)和日降水强度(SDII)的年际倾向率分别为0.17 mm·a-1、1.14 mm·a-1、0.02 d·a-1和0.01 mm·d-1·a-1,持续降水日数(CWD)则以-0.05d·a-1的速率减少;各极端降水指数的变化趋势存在空间差异,RX5day、SDII和R95呈增加趋势的格点所占比例分别为60.85%、75.32%和75.74%;各极端降水指数与总降水量之间均存在较好的相关性,且均通过了0.01水平的置信度检验.
Changes in precipitation extremes in South China during 1961-2011
Based on the daily precipitation from a 0.5°× 0.5° gridded dataset and meteorological stations during 1961-2011 released by National Meteorological Information Center,this paper evaluates the reliability of this gridded precipitation dataset in South China.Five precipitation indices recommended by the World Meteorological Organization (WMO) were selected to investigate the changes in precipitation extremes in South China.The results indicate that the limited bias was observed between gridded data interpolated to given stations and the corresponding observed data,and that 50.64% of the stations had bias between-10% and 0.Generally,the correlation coefficients between gridded data and observed data are above 0.80 in most parts of the region.The average of precipitation indices shows a significant spatial difference with drier northwest section and wetter southeast section.The trend magnitudes of maximum 5-day precipitation (RX5day),very wet day precipitation (R95),very heavy precipitation days (R20mm) and simple daily intensity index (SDII) were 0.17 mm· a-1,1.14 mm· a-1,0.02 d· a-1 and 0.01 mm· d· a-1,respectively,while consecutive wet days (CWD) decreased by-0.05 d· a-1 during 1961-2011.There is spatial disparity in trend magnitudes of precipitation indices,and approximate 60.85%,75.32% and 75.74% of the grid boxes showed increasing trends for RX5day,SDII and R95,respectively.There were high correlations between precipitation indices and total precipitation,which was statistically significant at the 0.01 level.

precipitation extremesgridded dataSouth China

任正果、张明军、王圣杰、朱小凡、董蕾、强芳

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西北师范大学地理与环境科学学院,兰州730070

极端降水 格点数据 中国南方

科技部全球变化重大科学研究计划重大科学目标导向项目国家自然科学基金甘肃省高等学校基本科研业务费项目

2013CBA0180141161012

2014

地理学报
中国地理学会 中国科学院地理科学与资源研究所

地理学报

CSTPCDCSCDCHSSCD北大核心
影响因子:3.3
ISSN:0375-5444
年,卷(期):2014.69(5)
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