Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1038/sdata.2017.12 |
Data Descriptor: A land data assimilation system for sub-Saharan Africa food and water security applications | |
McNally, Amy1,2; Arsenault, Kristi2,3; Kumar, Sujay2; Shukla, Shraddhanand4,5; Peterson, Pete4,5; Wang, Shugong2,3; Funk, Chris4,5,6; Peters-Lidard, Christa D.2; Verdin, James P.6 | |
通讯作者 | McNally, Amy |
来源期刊 | SCIENTIFIC DATA
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EISSN | 2052-4463 |
出版年 | 2017 |
卷号 | 4 |
英文摘要 | Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa. |
类型 | Article ; Data Paper |
语种 | 英语 |
国家 | USA |
收录类别 | SCI-E |
WOS记录号 | WOS:000393855800002 |
WOS关键词 | SATELLITE RAINFALL PRODUCTS ; SOIL-MOISTURE ; SURFACE MODEL ; DROUGHT ; FRAMEWORK ; VALIDATION ; SIMULATION ; RUNOFF |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
来源机构 | United States Geological Survey |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/202275 |
作者单位 | 1.Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20740 USA; 2.NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA; 3.SAIC Inc, Mclean, VA 22102 USA; 4.Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA; 5.Univ Calif Santa Barbara, Climate Hazards Grp, Santa Barbara, CA 93106 USA; 6.US Geol Survey, Earth Resources Observat & Sci EROS Ctr, Sioux Falls, SD 57105 USA |
推荐引用方式 GB/T 7714 | McNally, Amy,Arsenault, Kristi,Kumar, Sujay,et al. Data Descriptor: A land data assimilation system for sub-Saharan Africa food and water security applications[J]. United States Geological Survey,2017,4. |
APA | McNally, Amy.,Arsenault, Kristi.,Kumar, Sujay.,Shukla, Shraddhanand.,Peterson, Pete.,...&Verdin, James P..(2017).Data Descriptor: A land data assimilation system for sub-Saharan Africa food and water security applications.SCIENTIFIC DATA,4. |
MLA | McNally, Amy,et al."Data Descriptor: A land data assimilation system for sub-Saharan Africa food and water security applications".SCIENTIFIC DATA 4(2017). |
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