DOI: 10.1175/JCLI-D-18-0104.1
Scopus记录号: 2-s2.0-85058794303
论文题名: Fidelity of the observational/reanalysis datasets and global climate models in representation of extreme precipitation in East China
作者: He S. ; Yang J. ; Bao Q. ; Wang L. ; Wang B.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2019
卷: 32, 期: 1 起始页码: 195
结束页码: 212
语种: 英语
Scopus关键词: Distribution functions
; Probability distributions
; Rain
; Rain gages
; Atmospheric model
; Chinese Academy of Sciences
; Daily precipitations
; Extreme precipitation
; Frequency distributions
; Global climate model
; Rainfall intensity
; Realistic simulation
; Climate models
; atmospheric general circulation model
; data set
; extreme event
; precipitation assessment
; precipitation intensity
; rainfall
; raingauge
; spatial distribution
; China
; Yangtze Basin
英文摘要: Realistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM)simulations.Thiswork assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean-Atmospheric Land System Model-Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations' rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days.TheTRMMobservation displays similar rainfall intensity-frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150mmday -1 , and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximumcenters, located over the lower-middle reach ofYangtze River basin and the deep SouthChina region, respectively.Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%-75% in all CMIP5models.Higher-resolution models tend to have better performance, and physical parameterizationmay be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation ofmoisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models' simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation. © 2018 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117269
Appears in Collections: 气候变化与战略
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Recommended Citation:
He S.,Yang J.,Bao Q.,et al. Fidelity of the observational/reanalysis datasets and global climate models in representation of extreme precipitation in East China[J]. Journal of Climate,2019-01-01,32(1)