GSTDTAP
DOI10.1007/s00382-019-05045-z
Inter-comparison of spatiotemporal features of precipitation extremes within six daily precipitation products
Chen, Shiling1,2; Liu, Bingjun2,3,4; Tan, Xuezhi2,3,4; Wu, Yi1,2
2019-11-12
发表期刊CLIMATE DYNAMICS
ISSN0930-7575
EISSN1432-0894
出版年2019
文章类型Article;Early Access
语种英语
国家Peoples R China
英文摘要

This study inter-compares the spatiotemporal features of precipitation extremes at global and regional scales within six daily precipitation datasets, i.e., gauge-based (Global Precipitation Climatology Center dataset, GPCC), satellite-retrieval (Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record, PERSIANN-CDR), three reanalysis datasets (ERA-Interim, ERAI; the National Center for Atmospheric Research Reanalysis 2, NCEP2; and the WATCH-Forcing-Data-ERA-Interim, WFDEI), and products merged from the three type datasets (the Multi-Source Weighted-Ensemble Precipitation, MSWEP). All datasets reproduce similar spatial patterns of both annual and seasonal precipitation extremes over the period from 1979 to 2017. Compared to the reference dataset gauge-based GPCC, the reanalysis WFDEI outperforms among six products with spatial correlation coefficients of 0.89 and 0.80 for the annual extreme indices (i.e., annual total amount of 95th precipitation and maximum 1-day precipitation), respectively. The satellite-based product PERSIANN-CDR performs better than reanalyses and merged datasets in capturing the temporal variability of the intensity and amount of precipitation extremes with similar changing tendencies and magnitudes of about 45 mm day(-1) and 230 mm at the global scale, respectively. The reanalyses and merged products underestimate the intensity of precipitation extremes. The selected six datasets behave differently in various regions. For the percentile-based frequency of precipitation extremes, NCEP2 performs well in regions of the Southeast Asian (SEA) and Amazon (AMZ), while WFDEI better matches GPCC over East North America (ENA) and North Australia (NAU) in both spatial patterns and temporal changes with correlation coefficients of 0.84 and 0.90, respectively. For the intensity features of annual precipitation extremes, NCEP2 performs better than other four datasets over regions of SEA, AMZ and West Africa (WAF). ERAI and WFDEI are consistent with GPCC in ENA and NAU with correlations coefficients of the intensity between ERAI (WFDEI) and GPCC are 0.82 (0.77) and 0.78 (0.64) for ENA and NAU, respectively. For the intensity of seasonal precipitation extremes, GPCC shows the highest estimates in regions of SEA, AMZ, ENA and WAF. ERAI and WFDEI perform better in reproducing the spatial patterns of seasonal precipitation extremes in all regions. NCEP2 (ERAI and WFDEI) show(s) consistent temporal variability of seasonal precipitation extremes with GPCC in regions of AMZ and WAF (ENA and NAU). Overall, there are large discrepancies in the absolute values of daily precipitation among datasets, and performances of non-gauged-based precipitation datasets in capturing the spatiotemporal variability of precipitation extremes are dependent on seasons, regions, and time periods.


英文关键词Precipitation datasets Extreme precipitation Spatiotemporal variability Global scale Regional scale
领域气候变化
收录类别SCI-E
WOS记录号WOS:000495956100003
WOS关键词GLOBAL GRIDDED PRECIPITATION ; NCEP-NCAR ; SUMMER MONSOON ; LONG-TERM ; DATA SETS ; REANALYSES ; SATELLITE ; FREQUENCY ; DATASETS ; TEMPERATURE
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/224233
专题环境与发展全球科技态势
作者单位1.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China;
2.Sun Yat Sen Univ, Ctr Water Resources & Environm, Guangzhou 510275, Guangdong, Peoples R China;
3.Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519000, Guangdong, Peoples R China;
4.Sun Yat Sen Univ, Sch Civil Engn, Guangzhou 510275, Guangdong, Peoples R China
推荐引用方式
GB/T 7714
Chen, Shiling,Liu, Bingjun,Tan, Xuezhi,et al. Inter-comparison of spatiotemporal features of precipitation extremes within six daily precipitation products[J]. CLIMATE DYNAMICS,2019.
APA Chen, Shiling,Liu, Bingjun,Tan, Xuezhi,&Wu, Yi.(2019).Inter-comparison of spatiotemporal features of precipitation extremes within six daily precipitation products.CLIMATE DYNAMICS.
MLA Chen, Shiling,et al."Inter-comparison of spatiotemporal features of precipitation extremes within six daily precipitation products".CLIMATE DYNAMICS (2019).
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