globalchange  > 气候变化与战略
DOI: 10.5194/hess-24-919-2020
论文题名:
Rainfall Estimates on a Gridded Network (REGEN) - A global land-based gridded dataset of daily precipitation from 1950 to 2016
作者: Contractor S.; Donat M.G.; Alexander L.V.; Ziese M.; Meyer-Christoffer A.; Schneider U.; Rustemeier E.; Becker A.; Durre I.; Vose R.S.
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2020
卷: 24, 期:2
语种: 英语
Scopus关键词: Climatology ; Daily precipitations ; Environmental information ; Global historical climatology network ; Global precipitation ; Rainfall estimates ; Standard deviation ; Station network ; Uncertainty measures ; Rain ; data quality ; data set ; diurnal variation ; hydrometeorology ; kriging ; network analysis ; precipitation intensity ; time series analysis ; United States
英文摘要: We present a new global land-based daily precipitation dataset from 1950 using an interpolated network of in situ data called Rainfall Estimates on a Gridded Network - REGEN. We merged multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network - Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA, and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD). This resulted in an unprecedented station density compared to existing datasets. The station time series were qualitycontrolled using strict criteria and flagged values were removed. Remaining values were interpolated to create areaaverage estimates of daily precipitation for global land areas on a 11 latitude-longitude resolution. Besides the daily precipitation amounts, fields of standard deviation, kriging error and number of stations are also provided. We also provide a quality mask based on these uncertainty measures. For those interested in a dataset with lower station network variability we also provide a related dataset based on a network of long-term stations which interpolates stations with a record length of at least 40 years. The REGEN datasets are expected to contribute to the advancement of hydrological science and practice by facilitating studies aiming to understand changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity. Here we document the development of the dataset and guidelines for best practices for users with regards to the two datasets. © 2020 BMJ Publishing Group. All rights reserved.
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159189
Appears in Collections:气候变化与战略

Files in This Item:

There are no files associated with this item.


作者单位: Climate Change Research Centre, UNSW Sydney, Sydney, Australia; ARC Centre of Excellence for Climate System Science, Sydney, Australia; ARC Centre of Excellence for Climate Extremes, Sydney, Australia; Barcelona Supercomputing Center, Barcelona, Spain; Global Precipitation Climatology Centre, Deutscher Wetterdienst, Offenbach, Germany; National Centers for Environmental Information, National Oceanic and Atmospheric Administration, Asheville, NC, United States

Recommended Citation:
Contractor S.,Donat M.G.,Alexander L.V.,et al. Rainfall Estimates on a Gridded Network (REGEN) - A global land-based gridded dataset of daily precipitation from 1950 to 2016[J]. Hydrology and Earth System Sciences,2020-01-01,24(2)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Contractor S.]'s Articles
[Donat M.G.]'s Articles
[Alexander L.V.]'s Articles
百度学术
Similar articles in Baidu Scholar
[Contractor S.]'s Articles
[Donat M.G.]'s Articles
[Alexander L.V.]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Contractor S.]‘s Articles
[Donat M.G.]‘s Articles
[Alexander L.V.]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.