DOI: 10.5194/hess-18-173-2014
Scopus记录号: 2-s2.0-84892493418
论文题名: Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: A land data assimilation application over France
作者: Barbu A ; L ; , Calvet J ; -C ; , Mahfouf J ; -F ; , Lafont S
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2014
卷: 18, 期: 1 起始页码: 173
结束页码: 192
语种: 英语
Scopus关键词: Cumulative distribution function
; Integrated applications
; Land data assimilation
; Land data assimilation systems
; Land surface modeling
; Prognostic variables
; Surface soil moisture
; Terrestrial vegetation
; Carbon
; Data processing
; Drought
; Extended Kalman filters
; Meteorological instruments
; Vegetation
; Soil moisture
; algorithm
; climatology
; correlation
; data assimilation
; geophysical method
; Kalman filter
; land cover
; land management
; leaf area index
; remote sensing
; satellite imagery
; simulation
; soil moisture
; spatial resolution
; France
英文摘要: The land monitoring service of the European Copernicus programme has developed a set of satellite-based biogeophysical products, including surface soil moisture (SSM) and leaf area index (LAI). This study investigates the impact of joint assimilation of remotely sensed SSM derived from Advanced Scatterometer (ASCAT) backscatter data and the Copernicus Global Land GEOV1 satellite-based LAI product into the the vegetation growth version of the Interactions between Soil Biosphere Atmosphere (ISBA-A-gs) land surface model within the the externalised surface model (SURFEX) modelling platform of Météo-France. The ASCAT data were bias corrected with respect to the model climatology by using a seasonal-based CDF (Cumulative Distribution Function) matching technique. A multivariate multi-scale land data assimilation system (LDAS) based on the extended Kalman Filter (EKF) is used for monitoring the soil moisture, terrestrial vegetation, surface carbon and energy fluxes across the domain of France at a spatial resolution of 8 km. Each model grid box is divided into a number of land covers, each having its own set of prognostic variables. The filter algorithm is designed to provide a distinct analysis for each land cover while using one observation per grid box. The updated values are aggregated by computing a weighted average. In this study, it is demonstrated that the assimilation scheme works effectively within the ISBA-A-gs model over a four-year period (2008-2011). The EKF is able to extract useful information from the data signal at the grid scale and distribute the root-zone soil moisture and LAI increments throughout the mosaic structure of the model. The impact of the assimilation on the vegetation phenology and on the water and carbon fluxes varies from one season to another. The spring drought of 2011 is an interesting case study of the potential of the assimilation to improve drought monitoring. A comparison between simulated and in situ soil moisture gathered at the twelve SMOSMANIA (Soil Moisture Observing System-Meteorological Automatic Network Integrated Application) stations shows improved anomaly correlations for eight stations. © Author(s) 2014. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78352
Appears in Collections: 气候变化事实与影响
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作者单位: CNRM-GAME, CNRS - UMR3589, Météo France, Toulouse, France
Recommended Citation:
Barbu A,L,, Calvet J,et al. Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: A land data assimilation application over France[J]. Hydrology and Earth System Sciences,2014-01-01,18(1)