DOI: 10.5194/hess-18-2657-2014
Scopus记录号: 2-s2.0-84904767657
论文题名: Global meteorological drought-Part 1: Probabilistic monitoring
作者: Dutra E ; , Wetterhall F ; , Di Giuseppe F ; , Naumann G ; , Barbosa P ; , Vogt J ; , Pozzi W ; , Pappenberger F
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2014
卷: 18, 期: 7 起始页码: 2657
结束页码: 2667
语种: 英语
Scopus关键词: Climatology
; Decision making
; Drought
; Forecasting
; Information management
; Mean square error
; Uncertainty analysis
; Water resources
; Climatological conditions
; Near-real-time monitoring
; Precipitation indices
; Precipitation products
; Probabilistic forecasts
; Root mean square errors
; Tropical rainfall measuring missions
; Water resources management
; Rain gages
英文摘要: Near-real-time drought monitoring can provide decision-makers with valuable information for use in several areas, such as water resources management, or international aid. One of the main constrains of assessing the current drought situation is associated with the lack of reliable sources of observed precipitation on a global scale available in near-real time. Furthermore, monitoring systems also need a long record of past observations to provide mean climatological conditions. To address these problems, a novel probabilistic drought monitoring methodology based on ECMWF probabilistic forecasts is presented, where probabilistic monthly means of precipitation were derived from short-range forecasts and merged with the long-term climatology of the Global Precipitation Climatology Centre (GPCC) data set. From the merged data set, the standardised precipitation index (SPI) was estimated. This methodology was compared with the GPCC first guess precipitation product as well as SPI calculations using the ECMWF ERA-Interim reanalysis and Tropical Rainfall Measuring Mission (TRMM) precipitation data sets. ECMWF probabilistic forecasts for near-real-time monitoring are similar to GPCC and TRMM in terms of correlation and root mean square errors, with the added value of including an estimate of the uncertainty given by the ensemble spread. The real-time availability of this product and its stability (i.e. that it does not directly depend on local rain gauges or single satellite products) are also beneficial in the light of an operational implementation. © 2014 Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78190
Appears in Collections: 气候变化事实与影响
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作者单位: European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom; European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy; Group on Earth Observations, Geneva, Switzerland
Recommended Citation:
Dutra E,, Wetterhall F,, Di Giuseppe F,et al. Global meteorological drought-Part 1: Probabilistic monitoring[J]. Hydrology and Earth System Sciences,2014-01-01,18(7)