1979-2018年中国0.1°极端气候指标数据集  

A dataset of climate extreme indices at 0.1°resolution in China(1979-2018)

作　　者：陈锦河 王昆 黄铁成 黄文江 高世臣 郭培昌 邹昀轩 CHEN Jinhe;WANG Kun;HUANG Tiecheng;HUANG Wenjiang;GAO Shichen;GUO Peichang;ZOU Yunxuan(School of Science,China University of Geosciences Beijing,Beijing 100083,P.R.China;International Research Center of Big Data for Sustainable Development Goals,Beijing 100094,P.R.China;State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,P.R.China)

机构地区：[1]中国地质大学(北京)数理学院,北京100083 [2]可持续发展大数据国际研究中心,北京100094 [3]中国科学院空天信息创新研究院,遥感科学国家重点实验室,北京100094

出　　处：《中国科学数据(中英文网络版)》2025年第1期367-379,共13页China Scientific Data

基　　金：中国科学院战略性先导科技专项(A类)(XDA26010304);风云卫星应用先行计划(FY-APP)。

摘　　要：在全球气候变化背景下,极端气候事件频发,对生态环境和人类社会造成了极大的影响。特别是复合型极端气候事件的发生,如气温上升、局部干旱和高温威胁还可能导致春季霜冻的风险增加,给农业生产带来复合连锁效应。研究极端气候事件对准确、定量地预测和防范灾害性天气事件,保护生态环境和人民生命财产安全至关重要。然而,由于现有的极端气候指标数据集时空分辨率较低,限制了区域极端气候的影响和评估研究。本研究基于中国地面气象要素驱动数据集(CMFD)和中国近地表气温数据集(CDAT),利用R语言程序包climdex.pcic计算得到了中国1979-2018年0.1°极端气候指标数据集CECID(China Extreme Climate Index Dataset),数据集涵盖了27项极端气候指标。本数据集与现有的极端气候指标数据集HadEX3、CEI_0p25和CECID_0p25相比,除了与时间跨度有关的指标外,大多数指标(如霜冻日数FD、热夜日数TR、中雨日数R10mm、年降水量PRCPTOT)的相关系数在0.7以上,确保了数据的可靠性;其次,数据集的空间分辨率0.1°,明显高于其他同类中国或全球范围的数据集;再次,研究采用的公里级气温与降水数据集,相较于基于站点数据得到的极端气候数据集,在原始数据源上更为可靠;最后,相较于已发布的特定区域数据集,本研究生产的数据集以中国为研究区,可用于中国极端气候发生特征及其对生态系统的影响研究,对防灾减灾、气候变化评估等领域具有实用价值和意义。In the context of global climate change,the frequent occurrence of extreme weather events has had significant impacts on the ecological environment and human society.Particularly,the rise of compound extreme events(e.g.rising temperature,localized droughts and the heightened threat of high temperatures)may also lead to an increased risk of spring frosts,resulting in various compound and chain effects on agricultural production.The study of extreme weather events is crucial to accurately and quantitatively predict and prevent catastrophic weather events,protect the ecological environment and people’s lives and property,and reduce losses.However,due to the low spatio-temporal resolution of existing extreme climate index datasets,the study and assessment of regional climate extremes has been limited.In this study,we developed the China Extreme Climate Index Dataset(CECID),a dataset of climate extreme indices at 0.1°resolution in China from 1979 to 2018.This dataset was calculated,using the R language program package climdex.pcic,based on the China Surface Meteorological Element Driven Dataset(CMFD)and the China Near Surface Air Temperature Dataset(CDAT).It covers 27 extreme climate indices.Compared with existing extreme climate index datasets like HadEX3,CEI_0p25 and CECID_0p25,the correlation coefficients of most of the indicators(e.g.,frost days FD,tropical nights TR,moderate rain days R10mm,and annual precipitation PRCPTOT)are above 0.7 ensuring the reliability of the dataset.Moreover,its spatial resolution of 0.1°is significantly higher than that of similar datasets both in China and globally,further enhancing its usability.Additionally,the temperature and precipitation dataset used in this study,based on kilometer-scale data sources.Finally,compared with existing region-specific datasets,the dataset produced in this study covers China as a whole,making it suitable for studying the characteristics of extreme climate events in China and their impacts on ecosystems.It holds practical value and significance for

关 键 词：中国 极端气候指标 气候变化 

分 类 号：P467[天文地球—大气科学及气象学]