DOI: 10.1016/j.jag.2015.09.012
Scopus记录号: 2-s2.0-85015844468
论文题名: Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture
作者: Martens B ; , Miralles D ; , Lievens H ; , Fernández-Prieto D ; , Verhoest N ; E ; C
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 48 起始页码: 146
结束页码: 162
语种: 英语
英文关键词: AMSR-E
; Australian hydrology
; Data assimilation
; GLEAM
; Newtonian Nudging
; SMOS
; Soil moisture
; Terrestrial evaporation
Scopus关键词: algorithm
; AMSR-E
; data assimilation
; estimation method
; evaporation
; hydrological cycle
; satellite data
; SMOS
; Australia
英文摘要: Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010–December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data assimilation on the evaporation fields is very mild, and difficult to assess due to the limited availability of eddy-covariance data. Nonetheless, our continental-scale simulations indicate that the assimilation of soil moisture can have a substantial impact on the estimated dynamics of evaporation in water-limited regimes. Progressing towards our goal of using satellite soil moisture to increase understanding of global land evaporation, future research will focus on the global application of this methodology and the consideration of multiple evaporation models. © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80088
Appears in Collections: 气候变化事实与影响
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作者单位: Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, Ghent, Belgium; Department of Earth Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085-1087, Amsterdam, Netherlands; European Space Research Institute (ESRIN), European Space Agency (ESA), Via Galileo Galilei 64, Frascati (Rome), Italy
Recommended Citation:
Martens B,, Miralles D,, Lievens H,et al. Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,48