Arid
DOI10.1038/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
EISSN2052-4463
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).
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[McNally, Amy]的文章
[Arsenault, Kristi]的文章
[Kumar, Sujay]的文章
百度学术
百度学术中相似的文章
[McNally, Amy]的文章
[Arsenault, Kristi]的文章
[Kumar, Sujay]的文章
必应学术
必应学术中相似的文章
[McNally, Amy]的文章
[Arsenault, Kristi]的文章
[Kumar, Sujay]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。