DOI: 10.5194/hess-21-5929-2017
Scopus记录号: 2-s2.0-85036461935
论文题名: SMOS brightness temperature assimilation into the Community Land Model
作者: Rains D ; , Han X ; , Lievens H ; , Montzka C ; , Verhoest N ; E ; C
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 11 起始页码: 5929
结束页码: 5951
语种: 英语
Scopus关键词: Atmospheric humidity
; Moisture
; Soil moisture
; Soils
; Temperature
; Time series
; Brightness temperatures
; Community land models
; Data assimilation systems
; Hydrological monitoring
; In-situ measurement
; Microwave emission models
; Moisture simulations
; Soil moisture and ocean salinity missions
; Luminance
; brightness temperature
; correlation
; data assimilation
; extreme event
; Kalman filter
; monitoring system
; numerical model
; radiometer
; rhizosphere
; SMOS
; soil moisture
; temperature anomaly
; time series
; Australia
英文摘要: SMOS (Soil Moisture and Ocean Salinity mission) brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM) across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF) as well as to the Community Microwave Emission Model (CMEM). Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010-2015). Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11%) for upper soil layers if the root zone is included in the updates. A reduced improvement of 5% is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7% when updating both the top layers and root zone, and by 4% when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics. © 2017 Author. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78983
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, Ghent, Belgium; Forschungszentrum Jülich GmbH, Institute of Bio- A Nd Geosciences, Jülich, Germany; Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, United States
Recommended Citation:
Rains D,, Han X,, Lievens H,et al. SMOS brightness temperature assimilation into the Community Land Model[J]. Hydrology and Earth System Sciences,2017-01-01,21(11)