全球地面降水月值历史数据集研制

全球降水历史数据是开展气候、水循环等研究的基础。收集整理全球12个数据源降水历史月值资料,通过站号、站名甄别不同数据源中相同台站,对344个通过相关系数、一致率、均值t检验、方差F检验的台站多源资料进行拼接,尽可能多地融合各套数据产品优势,最终形成全球降水历史月值数据集(CMA Global PrecipitationV1.0, CGP)。数据集重点解决当前国际数据产品在东亚地区站点稀少、同时应用多套数据应用门槛较高等问题。数据集收录3.1万个台站共计1.87×107组月降水记录, 4152个台站序列长度达百年。与美国大气海洋局(NOAA)的全球降水数据集(GHCN-M V2.0)对比,CGP新增1万个站点、0.5×107组有效观测记录和1030条百年序列,其中141条百年序列通过多源整合技术获取。CGP的站点和数据量优势主要体现在东亚、东欧、西伯利亚等站点稀疏地区。基于CGP分析的全球降水时空特征与国际同类产品的结果较一致。新增的数据虽然没有改变全球降水分布的总体特征,但对区域性的百年降水变化检测有一定影响。基于CGP的全球降水百年序列结果显示,20世纪前半叶全球降水量偏小,近20年是1900年以来全球降水量最大的时期,各纬度带、各个国家或地区的降水长期变化趋势呈现显著的差异。 

Development of a global historic monthly mean precipitation dataset

Global historic precipitation dataset is the base for climate and water cycle research. There have been several global historic land surface precipitation datasets developed by international data centers such as NCDC (National Climatic Data Center), ECA&D (European Climate Assessment & Dataset) project team, and Met Office etc., but so far there are no such datasets developed by any research institute in China. In addition, each dataset has its own focus of study region, and the existing global precipitation datasets only contain sparse observational stations over China, which may result in uncertainties in East Asian precipitation studies. In order to take into account comprehensive historic information, users might need to employ two or more datasets. However, the non-uniform data formats, data units, station ids and so on add extra difficulties for users to exploit these datasets. For this reason, a complete historic precipitation dataset that takes advantages of various datasets has been developed and produced in the National Meteorological Information Center (NMIC) of China. Precipitation observations from 12 sources are aggregated, and the data formats, data units, station ids are uniformed. Duplicated stations with the same identifications are identified with duplicated observations removed. Consistency test, correlation coefficient test, significance t-test at the 95% confidence level, and significance F-test at the 95% confidence level are conducted first to ensure the data reliability. Only those datasets that satisfy all the above four criteria are integrated to produce the China Meteorological Administration (CMA) Global Precipitation (CGP) historic precipitation dataset version 1.0. It contains observations at 31 thousand stations with 1.87×10⁷ data records, among which 4152 time series of precipitation are longer than 100 a. This dataset plays a critical role in climate research due to its advantages in large data volume and high station network density compared to other datasets. Using PMT (Penalized Maximal t-test) method, significant Inhomogeneity has been detected in historic precipitation datasets at 340 stations. The ratio method is then applied to effectively remove these remarkable change points. Global precipitation analysis based on CGP v1.0 shows that rainfall has been increasing during the period of 1901 to 2013 with an increasing rate 3.52±0.5 mm/(10 a), slightly higher than that in the NCDC data. Analysis also reveals distinguished long-term changing trends at different latitude zones.