Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017GL073904 |
Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates | |
Lievens, H.1,2; Reichle, R. H.2; Liu, Q.2,3; De Lannoy, G. J. M.4; Dunbar, R. S.5; Kim, S. B.5; Das, N. N.5; Cosh, M.6; Walker, J. P.7; Wagner, W.8 | |
2017-06-28 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS
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ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2017 |
卷号 | 44期号:12 |
文章类型 | Article |
语种 | 英语 |
国家 | Belgium; USA; Australia; Austria |
英文摘要 | SMAP (Soil Moisture Active and Passive) radiometer observations at similar to 40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9 km SMAP Level-4 Soil Moisture product. This study demonstrates that adding high-resolution radar observations from Sentinel-1 to the SMAP assimilation can increase the spatiotemporal accuracy of soil moisture estimates. Radar observations were assimilated either separately from or simultaneously with radiometer observations. Assimilation impact was assessed by comparing 3-hourly, 9 km surface and root-zone soil moisture simulations with in situ measurements from 9 km SMAP core validation sites and sparse networks, from May 2015 to December 2016. The Sentinel-1 assimilation consistently improved surface soil moisture, whereas root-zone impacts were mostly neutral. Relatively larger improvements were obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performed best, demonstrating the complementary value of radar and radiometer observations. |
英文关键词 | Sentinel-1 SMAP data assimilation soil moisture |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000405854200032 |
WOS关键词 | CLIMATE REFERENCE NETWORK ; RADIATIVE-TRANSFER MODEL ; SMOS OBSERVATIONS ; LAND ; VALIDATION ; MISSION ; SYSTEM |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/28680 |
专题 | 气候变化 |
作者单位 | 1.Univ Ghent, Lab Hydrol & Water Management, Ghent, Belgium; 2.NASA, Goddard Space Flight Ctr, Global Modeling & Assimilat Off, Greenbelt, MD 20771 USA; 3.Sci Syst & Applicat, Lanham, MD USA; 4.Katholieke Univ Leuven, Dept Earth & Environm Sci, Heverlee, Belgium; 5.CALTECH, Jet Prop Lab, Pasadena, CA USA; 6.USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD USA; 7.Monash Univ, Dept Civil Engn, Melbourne, Vic, Australia; 8.Vienna Univ Technol, Dept Geodesy & Geoinformat, Vienna, Austria |
推荐引用方式 GB/T 7714 | Lievens, H.,Reichle, R. H.,Liu, Q.,et al. Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates[J]. GEOPHYSICAL RESEARCH LETTERS,2017,44(12). |
APA | Lievens, H..,Reichle, R. H..,Liu, Q..,De Lannoy, G. J. M..,Dunbar, R. S..,...&Wagner, W..(2017).Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates.GEOPHYSICAL RESEARCH LETTERS,44(12). |
MLA | Lievens, H.,et al."Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates".GEOPHYSICAL RESEARCH LETTERS 44.12(2017). |
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