Sensitivity analysis of standardized precipitation index to climate state selection in China

被引:7
|
作者
Zuo, Dong-Dong [1 ]
Hou, Wei [2 ]
Zhang, Qiang [2 ]
Yan, Peng-Cheng [3 ]
机构
[1] Yancheng Inst Technol, Sch Math & Phys, Yancheng 224000, Peoples R China
[2] China Meteorol Adm, Natl Climate Ctr, Key Lab Climate Studies, Beijing 100081, Peoples R China
[3] China Meteorol Adm, Inst Arid Meteorol, Lanzhou 730000, Peoples R China
基金
中国国家自然科学基金;
关键词
SPI; Reference climate states; SPI error; Precipitation distribution parameters; Meteorological Administration); DROUGHT; SPI;
D O I
10.1016/j.accre.2021.11.004
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the calculation of the standardized precipitation index (SPI) index, it is necessary to select a certain period of precipitation samples as the reference climate state, and the SPI obtained by different reference climate states have different size. Therefore, the influence of different reference climate states on the accuracy of SPI calculation is worth analyzing. Based on the monthly precipitation data of 1184 stations in China from 1961 to 2010, the influence of the selection of the reference climatic state in the calculation of SPI was analyzed. Using 30 consecutive years as the duration of the reference climatic state, 1961-2010 is divided into three periods 1961-1990, 1971-2000, 1981-2010. Taking the SPI obtained from the entire period as the standard value, the spatial distribution of SPI error and the accuracy of SPI classification based on each reference period were analyzed. Then, the resampling method was used to analyze the influence of time-continuous precipitation samples on the size of SPI. The results show that the SPI error of most sites is less than 0.2, and the accuracy of SPI classification is more than 80%. Although the errors of SPI mostly come from extreme drought and extremely wet, this does not affect the accuracy of the recognition of extreme drought and extremely wet. In most regions, it is reliable to calculate SPI based on the precipitation data of continuous 30 years, but the reliability of SPI is relatively low in areas with frequent drought. The results of the resampling analysis and 30-year sliding analysis show that the distribution parameters have noticeable turning characteristics, and the precipitation distribution parameters of nearly 85% stations had noticeable turning point before 1985, which led to the precipitation data of continuous 30 years easily overestimate the dry/wet.
引用
收藏
页码:42 / 50
页数:9
相关论文
共 50 条
  • [21] Spatial and Temporal Variability Analysis in Rainfall Using Standardized Precipitation Index for the Fuhe Basin, China
    Li, Rongfang
    Cheng, Lijun
    Ding, Yongsheng
    Chen, Yunxiang
    Khorasani, K.
    INTELLIGENT COMPUTING FOR SUSTAINABLE ENERGY AND ENVIRONMENT, 2013, 355 : 451 - 459
  • [22] Spatial and temporal variability analysis in rainfall using standardized precipitation index for the Fuhe basin, China
    Li, Rongfang
    Cheng, Lijun
    Ding, Yongsheng
    Chen, Yunxiang
    Khorasani, K.
    Communications in Computer and Information Science, 2013, 355 : 451 - 459
  • [23] Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China
    Peng Yang
    Jun Xia
    Yongyong Zhang
    Jian Han
    Xia Wu
    Theoretical and Applied Climatology, 2018, 134 : 901 - 912
  • [24] Monitoring and Analysis of Drought Characteristics Based on Climate Change in Burundi Using Standardized Precipitation Evapotranspiration Index
    Ndayiragije, Jean Marie
    Li, Fan
    WATER, 2022, 14 (16)
  • [25] Long-term Trend and Variability of China's Arid Climate and Drought Area based on the Standardized Precipitation Index
    Liu Yang
    Jiang Wenlai
    Xiao Bilin
    Gao Mingjie
    Lei Bo
    THIRD INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS 2014), 2014, : 555 - 559
  • [26] Standardized Precipitation Evapotranspiration Index is highly correlated with total water storage over China under future climate scenarios
    Zhang, Yajie
    Yu, Zhisheng
    Niu, Haishan
    ATMOSPHERIC ENVIRONMENT, 2018, 194 : 123 - 133
  • [27] Performance of the Standardized Precipitation Index Based on the TMPA and CMORPH Precipitation Products for Drought Monitoring in China
    Lu, Jing
    Jia, Li
    Menenti, Massimo
    Yan, Yuping
    Zheng, Chaolei
    Zhou, Jie
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (05) : 1387 - 1396
  • [28] Spatiotemporal Variation of Precipitation Regime in China from 1961 to 2014 from the Standardized Precipitation Index
    Yuan, Xuefeng
    Jian, Jinshi
    Jiang, Gang
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2016, 5 (11)
  • [29] Drought analysis using multi-scale standardized precipitation index in the Han River Basin,China
    Yueping XUShengji LINYan HUANGQinqing ZHANGQihua RANInstitute of Hydrology and Water ResourcesCivil EngineeringZhejiang UniversityHangzhou ChinaZhejiang Institute of Hydraulics and EstuaryHangzhou ChinaBureau of HydrologyChangjiang Water Resources CommissionWuhan China
    Journal of Zhejiang University-Science A(Applied Physics & Engineering), 2011, (06) : 483 - 494
  • [30] Comparative analysis of probability distributions for the Standardized Precipitation Index and drought evolution in China during 1961–2015
    Ruxin Zhao
    Huixiao Wang
    Chesheng Zhan
    Shi Hu
    Meihong Ma
    Yuxuan Dong
    Theoretical and Applied Climatology, 2020, 139 : 1363 - 1377